diff --git a/.gitignore b/.gitignore
index d32ae4e..9bf58c0 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,6 +6,9 @@ __pycache__/
 # C extensions
 *.so
 
+# Example datasetss
+notebooks/example_data/ts_spectrum_example_data/
+
 # Distribution / packaging
 .Python
 build/
diff --git a/conda/environment-ep-main.yml b/conda/environment-ep-main.yml
index ff8889a..63902aa 100644
--- a/conda/environment-ep-main.yml
+++ b/conda/environment-ep-main.yml
@@ -12,6 +12,7 @@ dependencies:
   - numba # Helps ensure a recent version is installed
   - numpy<2
   - pip
+  - pooch
   # -- holoviz --
   - jupyter_bokeh
   - datashader
diff --git a/conda/environment.yml b/conda/environment.yml
index 7d86500..6bd6644 100644
--- a/conda/environment.yml
+++ b/conda/environment.yml
@@ -10,6 +10,7 @@ dependencies:
   - cartopy
   - scipy
   - numba # Helps ensure a recent version is installed
+  - pooch
   # -- holoviz --
   - jupyter_bokeh
   - datashader
diff --git a/notebooks/_templates/gallery-cards.jinja b/notebooks/_templates/gallery-cards.jinja
index 33d8ac6..544f86f 100644
--- a/notebooks/_templates/gallery-cards.jinja
+++ b/notebooks/_templates/gallery-cards.jinja
@@ -1,7 +1,12 @@
+{% for section in data %}
+
+## {{ section["section"] }}
+
 ::::{grid} 1 2 2 3
 :gutter: 2
+:class-container: gallery-grid
 
-{% for item in data %}
+{% for item in section["items"] %}
 :::{card}
 :link: {{ item.website or item.notebook }}
 {% if item.image %}:img-top: {{ item.image }}{% endif %}
@@ -13,4 +18,6 @@
 :::
 {% endfor %}
 
-:::: 
+::::
+
+{% endfor %}
\ No newline at end of file
diff --git a/notebooks/_toc.yml b/notebooks/_toc.yml
index d5e7237..d4ce5f0 100644
--- a/notebooks/_toc.yml
+++ b/notebooks/_toc.yml
@@ -1,17 +1,28 @@
-# Table of contents
-# Learn more at https://jupyterbook.org/customize/toc.html
-
 format: jb-book
 root: index
 parts:
-  - caption: Demonstrations
-    numbered: True
+  - caption: Getting started
+    numbered: False
+    chapters:
+      - file: getting_started
+      - file: getting_started_FM_TS
+
+  - caption: Data processing
+    numbered: False
+    chapters:
+      - file: OOI_eclipse
+      - file: seafloor_detection
+      - file: transient_noise
+
+  - caption: Analysis workflows
+    numbered: False
+    chapters:
+      - file: ship_tracks
+      - file: krill_freq_diff
+      - file: hake_mask
+      - file: glider_AZFP
+
+  - caption: Community showcase
+    numbered: False
     chapters:
-    - file: getting_started
-    - file: OOI_eclipse
-    - file: ship_tracks
-    - file: krill_freq_diff
-    - file: hake_mask
-    - file: glider_AZFP
-    - file: seafloor_detection
-    - file: transient_noise
+      - file: community_showcase
\ No newline at end of file
diff --git a/notebooks/community_showcase.md b/notebooks/community_showcase.md
new file mode 100644
index 0000000..90c90f0
--- /dev/null
+++ b/notebooks/community_showcase.md
@@ -0,0 +1,6 @@
+# Community showcase
+
+Examples from the echopype community will be highlighted here.
+If you are using echopype in your own workflows, feel free to open an issue or pull request to suggest an example notebook!
+
+(Temporary file to remove)
\ No newline at end of file
diff --git a/notebooks/gallery.yml b/notebooks/gallery.yml
index 03012c9..f152871 100644
--- a/notebooks/gallery.yml
+++ b/notebooks/gallery.yml
@@ -1,55 +1,71 @@
-- name: Getting Started with Echopype
-  website: https://echopype-examples.readthedocs.io/en/latest/getting_started.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/getting_started.ipynb
-  notebook: getting_started.ipynb
-  summary: A minimum example to get started on Echopype functions.
-  image: images/gallery/01_getting_started.png
-
-- name: Watching Eclipse from a Moored Echosounder
-  website: https://echopype-examples.readthedocs.io/en/latest/OOI_eclipse.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/OOI_eclipse.ipynb
-  notebook: OOI_eclipse.ipynb
-  summary: Pairing acoustic data from an upward-looking echosounder and shortwave irradiance measured by a pyrometer on a surface mooring to observe the movement response of zooplankton to a solar eclipse. (Not binder friendly.)
-  image: images/gallery/02_OOI_eclipse.png
-
-- name: Ship Tracks Visualisation
-  website: https://echopype-examples.readthedocs.io/en/latest/ship_tracks.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/ship_tracks.ipynb
-  notebook: ship_tracks.ipynb
-  summary: Subselect sections of echo data based on ship GPS data embedded in the echosounder raw files to demonstrate the power of label-aware data processing based on standardized netCDF data model. (Not binder friendly.)
-  image: images/gallery/03_subselection.png
-
-- name: Krill Frequency Differencing
-  website: https://echopype-examples.readthedocs.io/en/latest/krill_freq_diff.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/krill_freq_diff.ipynb
-  notebook: krill_freq_diff.ipynb
-  summary: Perform frequency-differencing analysis to identify fluid-like zooplankton scatterers (likely krill) in ship echosounder data, and compute nautical acoustic scattering coefficient (NASC) based on the classification. (Not binder friendly.)
-  image: images/gallery/04_krill.png
-
-- name: Masking Echogram and Computing NASC
-  website: https://echopype-examples.readthedocs.io/en/latest/hake_mask.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/hake_mask.ipynb
-  notebook: hake_mask.ipynb
-  summary: Incorporate an externally generated mask that identify the occurrence of Pacific hake in ship echosounder data, and compute NASC based on the masked outputs.
-  image: images/gallery/05_NASC.png
-
-- name: Glider AZFP Processing
-  website: https://echopype-examples.readthedocs.io/en/latest/glider_AZFP.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/glider_AZFP.ipynb
-  notebook: glider_AZFP.ipynb
-  summary: Process acoustic data from a Slocum glider by incorporating external position, motion, and environmental data and identify zooplankton shoals.
-  image: images/gallery/06_glider.png
-
-- name: Seafloor Detection
-  website: https://echopype-examples.readthedocs.io/en/latest/seafloor_detection.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/seafloor_detection.ipynb
-  notebook: seafloor_detection.ipynb
-  summary: Seafloor detection with echopype (two algorithms) and use of echoregions; compute a bottom line and mask below-bottom data.
-  image: images/gallery/07_seafloor.png
-
-- name: Transient Noise Removal
-  website: https://echopype-examples.readthedocs.io/en/latest/transient_noise.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/transient_noise.ipynb
-  notebook: transient_noise.ipynb
-  summary: Transient noise removal with echopype (two algorithms) and exploring the effects on Sv profiles.
-  image: images/gallery/08_transient_noise.png
\ No newline at end of file
+- section: Getting started
+  items:
+    - name: Getting Started with Echopype
+      website: https://echopype-examples.readthedocs.io/en/latest/getting_started.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/getting_started.ipynb
+      notebook: getting_started.ipynb
+      summary: A minimum example to get started on Echopype functions.
+      image: images/gallery/01_getting_started.png
+      
+    - name: Getting Started with Echopype for broadband TS
+      website: https://echopype-examples.readthedocs.io/en/latest/getting_started_FM_TS.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/getting_started_FM_TS.ipynb
+      notebook: getting_started_FM_TS.ipynb
+      summary: A minimum example to get started on Echopype functions for broadband target strength (TS) estimation.
+      image: images/gallery/11_getting_started_FM_TS.png
+
+- section: Data processing
+  items:
+    - name: Watching Eclipse from a Moored Echosounder
+      website: https://echopype-examples.readthedocs.io/en/latest/OOI_eclipse.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/OOI_eclipse.ipynb
+      notebook: OOI_eclipse.ipynb
+      summary: Pairing acoustic data from an upward-looking echosounder and shortwave irradiance measured by a pyrometer on a surface mooring to observe the movement response of zooplankton to a solar eclipse. (Not binder friendly.)
+      image: images/gallery/02_OOI_eclipse.png
+
+    - name: Seafloor Detection
+      website: https://echopype-examples.readthedocs.io/en/latest/seafloor_detection.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/seafloor_detection.ipynb
+      notebook: seafloor_detection.ipynb
+      summary: Seafloor detection with echopype (two algorithms) and use of echoregions; compute a bottom line and mask below-bottom data.
+      image: images/gallery/07_seafloor.png
+
+    - name: Transient Noise Removal
+      website: https://echopype-examples.readthedocs.io/en/latest/transient_noise.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/transient_noise.ipynb
+      notebook: transient_noise.ipynb
+      summary: Transient noise removal with echopype (two algorithms) and exploring the effects on Sv profiles.
+      image: images/gallery/08_transient_noise.png
+
+- section: Analysis workflows
+  items:
+    - name: Ship Tracks Visualisation
+      website: https://echopype-examples.readthedocs.io/en/latest/ship_tracks.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/ship_tracks.ipynb
+      notebook: ship_tracks.ipynb
+      summary: Subselect sections of echo data based on ship GPS data embedded in the echosounder raw files to demonstrate the power of label-aware data processing based on standardized netCDF data model. (Not binder friendly.)
+      image: images/gallery/03_subselection.png
+
+    - name: Krill Frequency Differencing
+      website: https://echopype-examples.readthedocs.io/en/latest/krill_freq_diff.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/krill_freq_diff.ipynb
+      notebook: krill_freq_diff.ipynb
+      summary: Perform frequency-differencing analysis to identify fluid-like zooplankton scatterers (likely krill) in ship echosounder data, and compute nautical acoustic scattering coefficient (NASC) based on the classification. (Not binder friendly.)
+      image: images/gallery/04_krill.png
+
+    - name: Masking Echogram and Computing NASC
+      website: https://echopype-examples.readthedocs.io/en/latest/hake_mask.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/hake_mask.ipynb
+      notebook: hake_mask.ipynb
+      summary: Incorporate an externally generated mask that identify the occurrence of Pacific hake in ship echosounder data, and compute NASC based on the masked outputs.
+      image: images/gallery/05_NASC.png
+
+    - name: Glider AZFP Processing
+      website: https://echopype-examples.readthedocs.io/en/latest/glider_AZFP.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/glider_AZFP.ipynb
+      notebook: glider_AZFP.ipynb
+      summary: Process acoustic data from a Slocum glider by incorporating external position, motion, and environmental data and identify zooplankton shoals.
+      image: images/gallery/06_glider.png
+
+- section: Community showcase
+  items: []
\ No newline at end of file
diff --git a/notebooks/getting_started_FM_TS.ipynb b/notebooks/getting_started_FM_TS.ipynb
new file mode 100644
index 0000000..388ccfd
--- /dev/null
+++ b/notebooks/getting_started_FM_TS.ipynb
@@ -0,0 +1,11348 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "64087514",
+   "metadata": {},
+   "source": [
+    "## Broadband TS spectrum validation against CRIMAC\n",
+    "\n",
+    "This notebook demonstrates a minimal workflow for computing broadband target-strength spectra (`TS_spectrum`) with echopype from EK80 FM data.\n",
+    "\n",
+    "The results are compared against the CRIMAC reference implementation described in Andersen et al. (2024). The comparison examines intermediate processing steps as well as the final TS spectrum estimates.\n",
+    "\n",
+    "Reference implementation:\n",
+    "- Andersen, L. N. et al. (2024). *Quantitative processing of broadband data as implemented in a scientific split-beam echosounder*. Methods in Ecology and Evolution, 15(2), 317–328. https://doi.org/10.1111/2041-210X.14261\n",
+    "- CRIMAC repository: https://github.com/CRIMAC-WP4-Machine-learning/CRIMAC-Raw-To-Svf-TSf\n",
+    "\n",
+    "Reference case:\n",
+    "\n",
+    "- Raw file: `IMR-D20211215-T143432-TSf.raw`\n",
+    "- Channel: `WBT 747022-15 ES120-7CD_ES`\n",
+    "- CRIMAC ping number: 510\n",
+    "- Python ping index: 509"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "869dd6a1",
+   "metadata": {},
+   "source": [
+    "The notebook follows the processing chain step by step:\n",
+    "\n",
+    "- Open the raw EK80 file\n",
+    "- Load the exported CRIMAC reference outputs\n",
+    "- Initialise the EK80 calibration object\n",
+    "- Rebuild the transmit signal and matched filter\n",
+    "- Pulse-compress the complex samples\n",
+    "- Convert pulse-compressed signals to received power\n",
+    "- Reproduce broadband point scattering strength, `Sp`\n",
+    "- Compute split-beam angles\n",
+    "- Identify the calibration sphere target\n",
+    "- Align the matched-filter autocorrelation with the target echo\n",
+    "- Compute the target and matched-filter spectra\n",
+    "- Compute the beam-compensated gain\n",
+    "- Compute the final calibrated `TS(f)`\n",
+    "- Validate the result against the public `compute_TS_spectrum()` API"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6525b719",
+   "metadata": {},
+   "source": [
+    "We start by importing the necessary libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a253416f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "import echopype as ep\n",
+    "\n",
+    "from echopype.calibrate.calibrate_ek import CalibrateEK80\n",
+    "from echopype.calibrate.ek80_complex import (\n",
+    "    get_filter_coeff,\n",
+    "    get_transmit_signal,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2e299118",
+   "metadata": {},
+   "source": [
+    "If the example data are not already available locally, they will be downloaded from the GitHub release asset, verified with a SHA256 checksum, and extracted into the local `example_data/` folder."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c0fefef8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using local dataset: example_data\\ts_spectrum_example_data\n"
+     ]
+    }
+   ],
+   "source": [
+    "from utils.data import fetch_dataset\n",
+    "data_dir = fetch_dataset(\"ts_spectrum_example_data\")\n",
+    "\n",
+    "raw_file_TS = data_dir / \"IMR-D20211215-T143432-TSf.raw\"\n",
+    "ref_file_TS = data_dir / \"crimac_tsf_reference_outputs.npz\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "662202fc",
+   "metadata": {},
+   "source": [
+    "We convert the raw data to echodata object."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "cdedca3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "    <div class='xr-header'>\n",
+       "        <div class=\"xr-obj-type\">EchoData: standardized raw data from Internal Memory</div>\n",
+       "    </div>\n",
+       "    <ul class=\"xr-sections group-sections\">\n",
+       "        <li class=\"xr-section-list\"><input id=\"idata_30e636512bfd699b3737bb6422288382\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "            <label for=\"idata_30e636512bfd699b3737bb6422288382\" class=\"xr-section-summary\">Top-level: contains metadata about the SONAR-netCDF4 file format.</label>\n",
+       "            <div class=\"xr-section-inline-details\"></div>\n",
+       "            <div class=\"xr-section-details\">\n",
+       "                <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                    <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 0B\n",
+       "Dimensions:  ()\n",
+       "Data variables:\n",
+       "    *empty*\n",
+       "Attributes:\n",
+       "    conventions:                 CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3\n",
+       "    keywords:                    EK80\n",
+       "    sonar_convention_authority:  ICES\n",
+       "    sonar_convention_name:       SONAR-netCDF4\n",
+       "    sonar_convention_version:    1.0\n",
+       "    summary:                     \n",
+       "    title:                       \n",
+       "    date_created:                2021-12-15T14:34:32Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c5c25caa-e8a4-41be-86fb-7825e0272897' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-c5c25caa-e8a4-41be-86fb-7825e0272897' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'></div></li><li class='xr-section-item'><input id='section-6ed8e43b-ad4e-4ba3-b759-1ae2ae3b186f' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-6ed8e43b-ad4e-4ba3-b759-1ae2ae3b186f' class='xr-section-summary'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-7c609e00-3e63-4eaa-b2bc-ee9cd722e2df' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c609e00-3e63-4eaa-b2bc-ee9cd722e2df' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3</dd><dt><span>keywords :</span></dt><dd>EK80</dd><dt><span>sonar_convention_authority :</span></dt><dd>ICES</dd><dt><span>sonar_convention_name :</span></dt><dd>SONAR-netCDF4</dd><dt><span>sonar_convention_version :</span></dt><dd>1.0</dd><dt><span>summary :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd><dt><span>date_created :</span></dt><dd>2021-12-15T14:34:32Z</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                </ul>\n",
+       "            </div>\n",
+       "        </li>\n",
+       "        <ul><li class=\"xr-section-list\"><input id=\"idata_c4b3a05e308441de9a5fc7984a8a5ea7\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_c4b3a05e308441de9a5fc7984a8a5ea7\" class=\"xr-section-summary\">Environment: contains information relevant to acoustic propagation through water.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 140B\n",
+       "Dimensions:                       (time1: 1, sound_velocity_profile_depth: 2)\n",
+       "Coordinates:\n",
+       "  * time1                         (time1) datetime64[ns] 8B 2021-12-15T14:34:...\n",
+       "  * sound_velocity_profile_depth  (sound_velocity_profile_depth) float64 16B ...\n",
+       "Data variables:\n",
+       "    depth                         (time1) float64 8B 5.0\n",
+       "    acidity                       (time1) float64 8B 8.0\n",
+       "    salinity                      (time1) float64 8B 32.0\n",
+       "    temperature                   (time1) float64 8B 9.7\n",
+       "    sound_speed_indicative        (time1) float64 8B 1.485e+03\n",
+       "    sound_velocity_profile        (time1, sound_velocity_profile_depth) float64 16B ...\n",
+       "    sound_velocity_source         (time1) &lt;U6 24B &#x27;Manual&#x27;\n",
+       "    transducer_name               (time1) &lt;U7 28B &#x27;Unknown&#x27;\n",
+       "    transducer_sound_speed        (time1) float64 8B 1.5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-28eb5536-10bc-4980-90f8-4184d188b867' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-28eb5536-10bc-4980-90f8-4184d188b867' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>sound_velocity_profile_depth</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-71a05870-a553-42cd-b245-8b1aa3f3ad09' class='xr-section-summary-in' type='checkbox' checked /><label for='section-71a05870-a553-42cd-b245-8b1aa3f3ad09' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-ff39da97-dfd4-4f54-a4b9-cec6072e9069' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff39da97-dfd4-4f54-a4b9-cec6072e9069' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8495f0e6-9400-4eaf-9249-0ba6bf44f476' class='xr-var-data-in' type='checkbox'><label for='data-8495f0e6-9400-4eaf-9249-0ba6bf44f476' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA position datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to environmental variables. Note that Platform.time3 is the same as Environment.time1.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sound_velocity_profile_depth</span></div><div class='xr-var-dims'>(sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1e+03</div><input id='attrs-3c53dacc-dee2-4df1-8175-6bcfc4511bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c53dacc-dee2-4df1-8175-6bcfc4511bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb51444-8504-4048-91ca-33ba4d52f994' class='xr-var-data-in' type='checkbox'><label for='data-ecb51444-8504-4048-91ca-33ba4d52f994' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([   1., 1000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e848675-e47b-4851-ba02-bd9c877972ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-6e848675-e47b-4851-ba02-bd9c877972ac' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-013084fe-1ffe-4999-a356-8d0d0ffdcc97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-013084fe-1ffe-4999-a356-8d0d0ffdcc97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99a428ea-3629-4401-ab2b-63b36abda345' class='xr-var-data-in' type='checkbox'><label for='data-99a428ea-3629-4401-ab2b-63b36abda345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-b7244075-76f8-44bd-9201-338b4bde78cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7244075-76f8-44bd-9201-338b4bde78cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19f8335a-e760-4b87-bb47-f6741b807beb' class='xr-var-data-in' type='checkbox'><label for='data-19f8335a-e760-4b87-bb47-f6741b807beb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([8.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-5fbab09e-604a-4269-83f1-4b46233305d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5fbab09e-604a-4269-83f1-4b46233305d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a93263a4-e12b-46de-8ecd-9f93580c4065' class='xr-var-data-in' type='checkbox'><label for='data-a93263a4-e12b-46de-8ecd-9f93580c4065' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([32.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-c30f383f-f02f-40e0-8f20-94e9bd6f531e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c30f383f-f02f-40e0-8f20-94e9bd6f531e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0f49309-8d87-466c-9340-4b0494611c41' class='xr-var-data-in' type='checkbox'><label for='data-b0f49309-8d87-466c-9340-4b0494611c41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([9.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed_indicative</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-1c26e2e4-b9b1-4bd7-934d-720d520daf28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c26e2e4-b9b1-4bd7-934d-720d520daf28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dcaec79-fd23-45eb-8f40-6dfe834a8bce' class='xr-var-data-in' type='checkbox'><label for='data-7dcaec79-fd23-45eb-8f40-6dfe834a8bce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1485.4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_profile</span></div><div class='xr-var-dims'>(time1, sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03 1.485e+03</div><input id='attrs-41d3db48-95e9-40f8-a08a-5e985a5132f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41d3db48-95e9-40f8-a08a-5e985a5132f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c70f05dd-a89a-46f4-b2e3-82687fb71aaa' class='xr-var-data-in' type='checkbox'><label for='data-c70f05dd-a89a-46f4-b2e3-82687fb71aaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sound velocity profile</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>parsed from raw data files as (depth, sound_speed) value pairs</dd></dl></div><div class='xr-var-data'><pre>array([[1485.4, 1485.4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_source</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;Manual&#x27;</div><input id='attrs-dde82fed-5ff0-4c4e-969a-900e2da4e5f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dde82fed-5ff0-4c4e-969a-900e2da4e5f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac2667a-47c0-4be1-91a6-c1eb12993854' class='xr-var-data-in' type='checkbox'><label for='data-5ac2667a-47c0-4be1-91a6-c1eb12993854' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Manual&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;Unknown&#x27;</div><input id='attrs-5811d654-a60f-46c2-a651-d650e32e3558' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5811d654-a60f-46c2-a651-d650e32e3558' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b9ad8f6-4eb0-4c73-b8bc-a0faafd54946' class='xr-var-data-in' type='checkbox'><label for='data-0b9ad8f6-4eb0-4c73-b8bc-a0faafd54946' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Unknown&#x27;], dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_sound_speed</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+03</div><input id='attrs-67ac5f47-702c-48ea-aec9-98b3732cf857' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67ac5f47-702c-48ea-aec9-98b3732cf857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99b67b3-aa3a-43eb-9d11-5b32f122f6b9' class='xr-var-data-in' type='checkbox'><label for='data-b99b67b3-aa3a-43eb-9d11-5b32f122f6b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1500.])</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_ae385b7e2cc76df0a82e7acf0d2c2eb8\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_ae385b7e2cc76df0a82e7acf0d2c2eb8\" class=\"xr-section-summary\">Platform: contains information about the platform on which the sonar is installed.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 51kB\n",
+       "Dimensions:                      (time1: 1, time2: 1266, channel: 4, time3: 1)\n",
+       "Coordinates:\n",
+       "  * time1                        (time1) datetime64[ns] 8B 2021-12-15T14:34:3...\n",
+       "  * time2                        (time2) datetime64[ns] 10kB 2021-12-15T14:34...\n",
+       "  * channel                      (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7CD...\n",
+       "  * time3                        (time3) datetime64[ns] 8B 2021-12-15T14:34:3...\n",
+       "Data variables: (12/26)\n",
+       "    latitude                     (time1) float64 8B nan\n",
+       "    longitude                    (time1) float64 8B nan\n",
+       "    sentence_type                (time1) float64 8B nan\n",
+       "    pitch                        (time2) float64 10kB 0.34 0.34 ... -2.02 -2.02\n",
+       "    roll                         (time2) float64 10kB 1.73 1.73 ... -2.93 -2.93\n",
+       "    vertical_offset              (time2) float64 10kB 0.0 0.0 0.0 ... 0.0 0.0\n",
+       "    ...                           ...\n",
+       "    position_offset_y            float64 8B nan\n",
+       "    position_offset_z            float64 8B nan\n",
+       "    frequency_nominal            (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    heading                      (time2) float64 10kB 1.46 1.46 ... 0.04 0.04\n",
+       "    latitude_mru1                (time3) float64 8B nan\n",
+       "    longitude_mru1               (time3) float64 8B nan\n",
+       "Attributes:\n",
+       "    platform_name:       \n",
+       "    platform_type:       \n",
+       "    platform_code_ICES:  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-61c1c821-179c-48d8-9b66-c98242697b76' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-61c1c821-179c-48d8-9b66-c98242697b76' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-73925e75-1a24-4e6a-ad35-265f3201db03' class='xr-section-summary-in' type='checkbox' checked /><label for='section-73925e75-1a24-4e6a-ad35-265f3201db03' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-e010f183-62cd-4466-b10e-25ef5f2369fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e010f183-62cd-4466-b10e-25ef5f2369fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab95c796-b965-431b-84cc-b90afd18dfe9' class='xr-var-data-in' type='checkbox'><label for='data-ab95c796-b965-431b-84cc-b90afd18dfe9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d972a333-6b9f-4e48-b4b6-0dc4115df731' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d972a333-6b9f-4e48-b4b6-0dc4115df731' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f55aec-928e-45a5-949f-13ecff064c74' class='xr-var-data-in' type='checkbox'><label for='data-b3f55aec-928e-45a5-949f-13ecff064c74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-ac3afbc9-84c3-41bf-9f72-bacc4a565900' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac3afbc9-84c3-41bf-9f72-bacc4a565900' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c26d213-1db8-4e55-a36f-dab5efc95118' class='xr-var-data-in' type='checkbox'><label for='data-5c26d213-1db8-4e55-a36f-dab5efc95118' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-6806ea60-12a6-47bd-ba49-bc880547f5da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6806ea60-12a6-47bd-ba49-bc880547f5da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f42c48c0-9ba9-40fb-8a03-c941c8489aa2' class='xr-var-data-in' type='checkbox'><label for='data-f42c48c0-9ba9-40fb-8a03-c941c8489aa2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-109b9527-015f-4745-8845-f83e854ebac9' class='xr-section-summary-in' type='checkbox' /><label for='section-109b9527-015f-4745-8845-f83e854ebac9' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5ecbf760-e4e0-444c-9a50-2dbbf4a16f88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ecbf760-e4e0-444c-9a50-2dbbf4a16f88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7199b02-3046-4fd6-b8ad-e3ffcf411e7b' class='xr-var-data-in' type='checkbox'><label for='data-d7199b02-3046-4fd6-b8ad-e3ffcf411e7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-52f002be-3db2-403e-bd60-6d8f8ccc4e8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52f002be-3db2-403e-bd60-6d8f8ccc4e8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe4c65aa-fbdb-4a8c-a28a-5e7fa08ae61a' class='xr-var-data-in' type='checkbox'><label for='data-fe4c65aa-fbdb-4a8c-a28a-5e7fa08ae61a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sentence_type</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-21e1d573-61ac-4e53-8c2f-7d5ad4e718ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e1d573-61ac-4e53-8c2f-7d5ad4e718ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e2b282b-c5a9-4f47-99c2-912ef79355fd' class='xr-var-data-in' type='checkbox'><label for='data-7e2b282b-c5a9-4f47-99c2-912ef79355fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA sentence type</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.34 0.34 0.4 ... -2.13 -2.02 -2.02</div><input id='attrs-2a6ed2cb-fc5b-4a94-8988-3430812ebc20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a6ed2cb-fc5b-4a94-8988-3430812ebc20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e051798-2ec3-419e-ab6a-e94a8f4e5210' class='xr-var-data-in' type='checkbox'><label for='data-1e051798-2ec3-419e-ab6a-e94a8f4e5210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.34      ,  0.34      ,  0.40000001, ..., -2.13000011,\n",
+       "       -2.01999998, -2.01999998], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.73 1.73 1.28 ... -2.93 -2.93</div><input id='attrs-6a74a1ac-6c9e-4dc5-8659-bd42963eb6b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a74a1ac-6c9e-4dc5-8659-bd42963eb6b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b41395d2-c227-4a38-bc3e-059bd72e0eff' class='xr-var-data-in' type='checkbox'><label for='data-b41395d2-c227-4a38-bc3e-059bd72e0eff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 1.73000002,  1.73000002,  1.27999997, ..., -3.16000009,\n",
+       "       -2.93000007, -2.93000007], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_offset</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3634bf42-fa8d-4416-9bd0-eeae2c1080d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3634bf42-fa8d-4416-9bd0-eeae2c1080d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-709d9ff4-18f2-46eb-9891-e99e3515254a' class='xr-var-data-in' type='checkbox'><label for='data-709d9ff4-18f2-46eb-9891-e99e3515254a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform vertical offset from nominal water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-14d0cfaa-9749-4191-88ec-374084a85065' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d0cfaa-9749-4191-88ec-374084a85065' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a555a503-503d-48a8-951c-1f579f65f422' class='xr-var-data-in' type='checkbox'><label for='data-a555a503-503d-48a8-951c-1f579f65f422' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-7970ab73-5492-402d-ada1-a489c692e7c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7970ab73-5492-402d-ada1-a489c692e7c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4986adbc-c936-46ca-b9dd-3ef6771856fb' class='xr-var-data-in' type='checkbox'><label for='data-4986adbc-c936-46ca-b9dd-3ef6771856fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-74d492bb-bf4b-4369-b5ab-e5d4856cff57' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74d492bb-bf4b-4369-b5ab-e5d4856cff57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52fbb06a-63bb-4af9-9273-a0da085733b0' class='xr-var-data-in' type='checkbox'><label for='data-52fbb06a-63bb-4af9-9273-a0da085733b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level_draft_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-74be6496-44d8-40e4-b273-fe94d88c0c39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74be6496-44d8-40e4-b273-fe94d88c0c39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-645f875e-cc4c-4258-95df-c4fd81552ab3' class='xr-var-data-in' type='checkbox'><label for='data-645f875e-cc4c-4258-95df-c4fd81552ab3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-f36faab1-9608-4c12-89a0-51aafea4a570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f36faab1-9608-4c12-89a0-51aafea4a570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-329ac06e-93ef-44f5-a152-855c5435d2c2' class='xr-var-data-in' type='checkbox'><label for='data-329ac06e-93ef-44f5-a152-855c5435d2c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-9cd701e6-70ab-4a9f-85d5-6344b4619f77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cd701e6-70ab-4a9f-85d5-6344b4619f77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d2d86cd-245d-4191-b656-7129ac6d2cbc' class='xr-var-data-in' type='checkbox'><label for='data-1d2d86cd-245d-4191-b656-7129ac6d2cbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-deec74e4-29fb-42bc-ba4c-ff06c00fbb39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-deec74e4-29fb-42bc-ba4c-ff06c00fbb39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4b81604-260d-4a6d-a624-5dcf237a9900' class='xr-var-data-in' type='checkbox'><label for='data-b4b81604-260d-4a6d-a624-5dcf237a9900' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5f4904e9-68ed-486e-9567-4f3beeecc02f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f4904e9-68ed-486e-9567-4f3beeecc02f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4f5a315-63bb-4997-952e-941d5f9daf96' class='xr-var-data-in' type='checkbox'><label for='data-f4f5a315-63bb-4997-952e-941d5f9daf96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-b013f1be-9d6e-45da-b71b-5808853395d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b013f1be-9d6e-45da-b71b-5808853395d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d947a1e-70d0-4799-990e-28818e73c395' class='xr-var-data-in' type='checkbox'><label for='data-0d947a1e-70d0-4799-990e-28818e73c395' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-605efc77-57a5-419c-9eea-094559be13cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-605efc77-57a5-419c-9eea-094559be13cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8907418-c9c4-4d7c-b695-924d66a887cb' class='xr-var-data-in' type='checkbox'><label for='data-e8907418-c9c4-4d7c-b695-924d66a887cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5e5346e5-1a3a-4fa9-a57f-b87b350ea02b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e5346e5-1a3a-4fa9-a57f-b87b350ea02b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01ee79d2-a225-4654-a1a0-3a91893606e2' class='xr-var-data-in' type='checkbox'><label for='data-01ee79d2-a225-4654-a1a0-3a91893606e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the x-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-a9247696-c47b-4a5e-b96a-2c356ed58a00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9247696-c47b-4a5e-b96a-2c356ed58a00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95d6bde5-01e7-49b7-888c-b8e1f3f70113' class='xr-var-data-in' type='checkbox'><label for='data-95d6bde5-01e7-49b7-888c-b8e1f3f70113' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the y-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2338d5dc-37d0-441e-b5c7-4e5308538ae0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2338d5dc-37d0-441e-b5c7-4e5308538ae0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39cd0982-2040-45a4-8657-b5480a3e716a' class='xr-var-data-in' type='checkbox'><label for='data-39cd0982-2040-45a4-8657-b5480a3e716a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the z-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-a3ac0d0e-ad56-4b94-83b9-3401426b4d40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3ac0d0e-ad56-4b94-83b9-3401426b4d40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64f89669-1e68-4414-a9da-e3f6b49cb5e6' class='xr-var-data-in' type='checkbox'><label for='data-64f89669-1e68-4414-a9da-e3f6b49cb5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e49fc1f-279d-415d-9a59-63632374f332' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e49fc1f-279d-415d-9a59-63632374f332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d06d2472-0b2c-428d-b514-25edb42980cc' class='xr-var-data-in' type='checkbox'><label for='data-d06d2472-0b2c-428d-b514-25edb42980cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-641c7e22-810b-4bea-ae05-3e67bf1864b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-641c7e22-810b-4bea-ae05-3e67bf1864b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d8a15f3-9ea6-4e2c-882d-2f7e9dfa7c52' class='xr-var-data-in' type='checkbox'><label for='data-1d8a15f3-9ea6-4e2c-882d-2f7e9dfa7c52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-79801443-b822-4d07-9cd1-abf1342d39c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79801443-b822-4d07-9cd1-abf1342d39c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b397824-3621-4c3e-9d37-80438b40784b' class='xr-var-data-in' type='checkbox'><label for='data-7b397824-3621-4c3e-9d37-80438b40784b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46 1.46 1.46 ... 0.04 0.04 0.04</div><input id='attrs-90335375-4392-4c89-8cae-8b4abf21501b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90335375-4392-4c89-8cae-8b4abf21501b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9f636a1-d610-4a23-bf82-0f07b020f1dc' class='xr-var-data-in' type='checkbox'><label for='data-c9f636a1-d610-4a23-bf82-0f07b020f1dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform heading (true)</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>360.0</dd></dl></div><div class='xr-var-data'><pre>array([1.46000004, 1.46000004, 1.46000004, ..., 0.04      , 0.04      ,\n",
+       "       0.04      ], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e82d1e6a-f91d-464b-a437-922ebdd78eb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e82d1e6a-f91d-464b-a437-922ebdd78eb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cdbd1b1-c07a-479b-ac7e-122ba4284d2a' class='xr-var-data-in' type='checkbox'><label for='data-9cdbd1b1-c07a-479b-ac7e-122ba4284d2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e88171a2-ee65-4032-8c81-a65e31c3ec46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88171a2-ee65-4032-8c81-a65e31c3ec46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57712bcf-48f1-44cf-a77a-76a5740c054d' class='xr-var-data-in' type='checkbox'><label for='data-57712bcf-48f1-44cf-a77a-76a5740c054d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ec6422d-47b1-489d-9416-ae45d513e97a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0ec6422d-47b1-489d-9416-ae45d513e97a' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_name :</span></dt><dd></dd><dt><span>platform_type :</span></dt><dd></dd><dt><span>platform_code_ICES :</span></dt><dd></dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_1a400e45d3a521f96c766391090c4e66\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_1a400e45d3a521f96c766391090c4e66\" class=\"xr-section-summary\">NMEA: contains information specific to the NMEA protocol.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 498kB\n",
+       "Dimensions:        (nmea_time: 4351, channel: 4, time1: 1, time2: 1266, time3: 1)\n",
+       "Coordinates:\n",
+       "  * nmea_time      (nmea_time) datetime64[ns] 35kB 2021-12-15T14:34:32.661453...\n",
+       "  * channel        (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7CD_ES&#x27; ... &#x27;WBT ...\n",
+       "  * time1          (time1) datetime64[ns] 8B 2021-12-15T14:34:32.661453\n",
+       "  * time2          (time2) datetime64[ns] 10kB 2021-12-15T14:34:32.661453 ......\n",
+       "  * time3          (time3) datetime64[ns] 8B 2021-12-15T14:34:32.661453\n",
+       "Data variables:\n",
+       "    NMEA_datagram  (nmea_time) &lt;U26 453kB &#x27;$SDVLW,630.103,N,630.103,N&#x27; ... &#x27;$...\n",
+       "Attributes:\n",
+       "    description:  All NMEA sensor datagrams</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-21064d1c-c0b2-47c0-8205-0656cda6567e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-21064d1c-c0b2-47c0-8205-0656cda6567e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nmea_time</span>: 4351</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-ce6b6754-745c-4026-9b9b-169502c921ca' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ce6b6754-745c-4026-9b9b-169502c921ca' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmea_time</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-dbdeb0e9-679b-4998-8f1a-4783c7536f1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbdeb0e9-679b-4998-8f1a-4783c7536f1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0443f899-5cc1-4c17-8e07-1f6f0ebb1888' class='xr-var-data-in' type='checkbox'><label for='data-0443f899-5cc1-4c17-8e07-1f6f0ebb1888' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA sensor data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.661453000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:32.825344000&#x27;, ..., &#x27;2021-12-15T14:40:09.311146000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.381834000&#x27;, &#x27;2021-12-15T14:40:09.456507000&#x27;],\n",
+       "      shape=(4351,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-7a5b178f-5733-4b21-917e-e64454eec1bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a5b178f-5733-4b21-917e-e64454eec1bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6a7a7c7-f95d-4519-829e-f634f8ef1340' class='xr-var-data-in' type='checkbox'><label for='data-d6a7a7c7-f95d-4519-829e-f634f8ef1340' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-0694e2a3-ca9a-4949-b54e-042a9dbe4bd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0694e2a3-ca9a-4949-b54e-042a9dbe4bd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b098e67-f7cc-4575-bee6-8012f6813583' class='xr-var-data-in' type='checkbox'><label for='data-7b098e67-f7cc-4575-bee6-8012f6813583' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-6d40e0da-897e-4236-b098-9b81ad544362' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d40e0da-897e-4236-b098-9b81ad544362' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e36fa7b-34b9-4426-90a1-25f80be87da4' class='xr-var-data-in' type='checkbox'><label for='data-4e36fa7b-34b9-4426-90a1-25f80be87da4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-4eaa415c-8a1a-49e7-a20f-8fa996d9f9ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eaa415c-8a1a-49e7-a20f-8fa996d9f9ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e2fe83-d38f-4774-a6ed-b9cfcb0c5d49' class='xr-var-data-in' type='checkbox'><label for='data-d4e2fe83-d38f-4774-a6ed-b9cfcb0c5d49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95bacdf8-9390-444f-a6b1-15e87f637dd9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-95bacdf8-9390-444f-a6b1-15e87f637dd9' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NMEA_datagram</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;$SDVLW,630.103,N,630.103,N&#x27; ......</div><input id='attrs-d3a4a630-da14-40c5-b6b1-9ffb89d9ec65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3a4a630-da14-40c5-b6b1-9ffb89d9ec65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c42b128-1887-4dc4-b7e3-c8156ecb0a7b' class='xr-var-data-in' type='checkbox'><label for='data-9c42b128-1887-4dc4-b7e3-c8156ecb0a7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA datagram</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;$SDVLW,630.103,N,630.103,N&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
+       "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, ..., &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
+       "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;],\n",
+       "      shape=(4351,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c31112ec-d09d-45be-8b19-6766f9081a5b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c31112ec-d09d-45be-8b19-6766f9081a5b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>All NMEA sensor datagrams</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_956eabeb080a127ac1af6b385a14f04b\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_956eabeb080a127ac1af6b385a14f04b\" class=\"xr-section-summary\">Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
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+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
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+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 276B\n",
+       "Dimensions:           (filenames: 1)\n",
+       "Coordinates:\n",
+       "  * filenames         (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    source_filenames  (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_exampl...\n",
+       "Attributes:\n",
+       "    conversion_software_name:     echopype\n",
+       "    conversion_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    conversion_time:              2026-06-07T01:36:12+00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5ad0bb37-3d56-4aab-b871-ddede107583a' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5ad0bb37-3d56-4aab-b871-ddede107583a' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-668d1b4a-d4c3-4f9e-a0f0-ac4670851ee1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-668d1b4a-d4c3-4f9e-a0f0-ac4670851ee1' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-88036a8b-2445-4ef5-8c74-1cbda392d43a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88036a8b-2445-4ef5-8c74-1cbda392d43a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60e7ac67-f359-45ce-a620-90b9a8b2fbef' class='xr-var-data-in' type='checkbox'><label for='data-60e7ac67-f359-45ce-a620-90b9a8b2fbef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65503e90-bdd6-4eec-adc8-620911b97a54' class='xr-section-summary-in' type='checkbox' checked /><label for='section-65503e90-bdd6-4eec-adc8-620911b97a54' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-d163a7ce-e2fb-4e31-a9c4-e5129d0bb563' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d163a7ce-e2fb-4e31-a9c4-e5129d0bb563' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2f304d-8314-4223-a259-e8ea2e9a1cb3' class='xr-var-data-in' type='checkbox'><label for='data-6d2f304d-8314-4223-a259-e8ea2e9a1cb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-615a5430-4989-4d61-93f1-d61e3842fcdb' class='xr-section-summary-in' type='checkbox' checked /><label for='section-615a5430-4989-4d61-93f1-d61e3842fcdb' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conversion_software_name :</span></dt><dd>echopype</dd><dt><span>conversion_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>conversion_time :</span></dt><dd>2026-06-07T01:36:12+00:00</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_7f39d7f922d1289ec21fcfe0b1d5b653\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_7f39d7f922d1289ec21fcfe0b1d5b653\" class=\"xr-section-summary\">Sonar: contains sonar system metadata and sonar beam groups.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 1kB\n",
+       "Dimensions:                    (channel_all: 4, beam_group: 1,\n",
+       "                                beam_group_index: 1)\n",
+       "Coordinates:\n",
+       "  * channel_all                (channel_all) &lt;U26 416B &#x27;WBT 747008-15 ES333-7...\n",
+       "  * beam_group                 (beam_group) &lt;U11 44B &#x27;Beam_group1&#x27;\n",
+       "  * beam_group_index           (beam_group_index) int64 8B 1\n",
+       "Data variables:\n",
+       "    frequency_nominal          (channel_all) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    transceiver_serial_number  (channel_all) &lt;U6 96B &#x27;747008&#x27; ... &#x27;747022&#x27;\n",
+       "    transducer_name            (channel_all) &lt;U9 144B &#x27;ES333-7CD&#x27; ... &#x27;ES120-...\n",
+       "    transducer_serial_number   (channel_all) &lt;U3 48B &#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;\n",
+       "    beam_group_descr           (beam_group) &lt;U93 372B &#x27;contains FM-only or CW...\n",
+       "    waveform_encode_descr      (beam_group_index) &lt;U10 40B &#x27;complex_FM&#x27;\n",
+       "Attributes:\n",
+       "    sonar_manufacturer:      Simrad\n",
+       "    sonar_model:             EK80\n",
+       "    sonar_serial_number:     \n",
+       "    sonar_software_name:     \n",
+       "    sonar_software_version:  21.15.0.0\n",
+       "    sonar_type:              echosounder</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e0480e99-c9bf-4be0-9e1c-44a7ca9040fc' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-e0480e99-c9bf-4be0-9e1c-44a7ca9040fc' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group</span>: 1</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-494288fe-1c03-487d-afd9-50b617a83e95' class='xr-section-summary-in' type='checkbox' checked /><label for='section-494288fe-1c03-487d-afd9-50b617a83e95' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-4e6c1b00-2d5d-405c-917b-f6dea2924b73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e6c1b00-2d5d-405c-917b-f6dea2924b73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-679ceae2-b3c1-4dc3-bf93-b7f07e134b36' class='xr-var-data-in' type='checkbox'><label for='data-679ceae2-b3c1-4dc3-bf93-b7f07e134b36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-d7170963-513f-46dc-a5a2-c32a4253809a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7170963-513f-46dc-a5a2-c32a4253809a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-352c90ce-63d6-43dd-a379-4ef29c737f93' class='xr-var-data-in' type='checkbox'><label for='data-352c90ce-63d6-43dd-a379-4ef29c737f93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-58cd6f07-9fa8-4578-ad3b-040897a44a5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58cd6f07-9fa8-4578-ad3b-040897a44a5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-104fae87-c879-4dac-ad2e-76793d4133fe' class='xr-var-data-in' type='checkbox'><label for='data-104fae87-c879-4dac-ad2e-76793d4133fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93385609-52f0-4ac2-a4ce-f359b3660800' class='xr-section-summary-in' type='checkbox' checked /><label for='section-93385609-52f0-4ac2-a4ce-f359b3660800' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-bfbab478-8c30-4e67-bdb3-062a62940470' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfbab478-8c30-4e67-bdb3-062a62940470' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-021a94d2-55f0-4eb0-a99f-0a7271d6f055' class='xr-var-data-in' type='checkbox'><label for='data-021a94d2-55f0-4eb0-a99f-0a7271d6f055' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;747008&#x27; &#x27;747015&#x27; &#x27;747019&#x27; &#x27;747022&#x27;</div><input id='attrs-35a279f8-5dd0-42ed-9696-d2620aaaea89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35a279f8-5dd0-42ed-9696-d2620aaaea89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-227846be-941f-4c58-bbae-d7165c294b5e' class='xr-var-data-in' type='checkbox'><label for='data-227846be-941f-4c58-bbae-d7165c294b5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;747008&#x27;, &#x27;747015&#x27;, &#x27;747019&#x27;, &#x27;747022&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;ES333-7CD&#x27; ... &#x27;ES120-7CD&#x27;</div><input id='attrs-11b6cf28-7af9-40ec-9c01-1ab04e01b15f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b6cf28-7af9-40ec-9c01-1ab04e01b15f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4062ed2-cb5e-4ea6-bd2d-181cb561e645' class='xr-var-data-in' type='checkbox'><label for='data-b4062ed2-cb5e-4ea6-bd2d-181cb561e645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;ES333-7CD&#x27;, &#x27;ES70-7CD&#x27;, &#x27;ES200-7CD&#x27;, &#x27;ES120-7CD&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;</div><input id='attrs-2604b084-77b2-4b4c-be79-1dc555332999' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2604b084-77b2-4b4c-be79-1dc555332999' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc285f4-b477-42d1-b12e-5aed80267bcf' class='xr-var-data-in' type='checkbox'><label for='data-adc285f4-b477-42d1-b12e-5aed80267bcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;220&#x27;, &#x27;134&#x27;, &#x27;166&#x27;, &#x27;146&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_group_descr</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U93</div><div class='xr-var-preview xr-preview'>&#x27;contains FM-only or CW-only com...</div><input id='attrs-62cbbccd-7d20-4a4c-a950-6dcbbd8d3d66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62cbbccd-7d20-4a4c-a950-6dcbbd8d3d66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75b13415-223a-40d5-a0a5-67b6e55eb1a4' class='xr-var-data-in' type='checkbox'><label for='data-75b13415-223a-40d5-a0a5-67b6e55eb1a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group description</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.&#x27;],\n",
+       "      dtype=&#x27;&lt;U93&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>waveform_encode_descr</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;complex_FM&#x27;</div><input id='attrs-bcecb8bb-c4c6-419f-b176-284128395853' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bcecb8bb-c4c6-419f-b176-284128395853' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a34aafc-bbfe-4569-bb05-36e744b9a378' class='xr-var-data-in' type='checkbox'><label for='data-1a34aafc-bbfe-4569-bb05-36e744b9a378' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;complex_FM&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2871098-d7f0-4c6c-8041-c90bc429262f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-b2871098-d7f0-4c6c-8041-c90bc429262f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>sonar_manufacturer :</span></dt><dd>Simrad</dd><dt><span>sonar_model :</span></dt><dd>EK80</dd><dt><span>sonar_serial_number :</span></dt><dd></dd><dt><span>sonar_software_name :</span></dt><dd></dd><dt><span>sonar_software_version :</span></dt><dd>21.15.0.0</dd><dt><span>sonar_type :</span></dt><dd>echosounder</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_1607356be07eee7c14e2943bf9eb8628\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_1607356be07eee7c14e2943bf9eb8628\" class=\"xr-section-summary\">Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 1GB\n",
+       "Dimensions:                        (channel: 4, ping_time: 1266,\n",
+       "                                    range_sample: 3534, beam: 4,\n",
+       "                                    channel_all: 4, beam_group_index: 1,\n",
+       "                                    beam_group: 1)\n",
+       "Coordinates:\n",
+       "  * channel                        (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7...\n",
+       "  * ping_time                      (ping_time) datetime64[ns] 10kB 2021-12-15...\n",
+       "  * range_sample                   (range_sample) int64 28kB 0 1 2 ... 3532 3533\n",
+       "  * beam                           (beam) &lt;U21 336B &#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;\n",
+       "  * channel_all                    (channel_all) &lt;U26 416B &#x27;WBT 747008-15 ES3...\n",
+       "  * beam_group_index               (beam_group_index) int64 8B 1\n",
+       "  * beam_group                     (beam_group) &lt;U11 44B &#x27;Beam_group1&#x27;\n",
+       "Data variables: (12/26)\n",
+       "    frequency_nominal              (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    beam_type                      (channel) int64 32B 1 1 1 1\n",
+       "    beamwidth_twoway_alongship     (channel) float64 32B 6.73 6.96 6.79 7.26\n",
+       "    beamwidth_twoway_athwartship   (channel) float64 32B 6.77 6.87 6.85 7.28\n",
+       "    beam_direction_x               (channel) float64 32B nan nan nan nan\n",
+       "    beam_direction_y               (channel) float64 32B nan nan nan nan\n",
+       "    ...                             ...\n",
+       "    slope                          (channel, ping_time) float64 41kB 0.003488...\n",
+       "    channel_mode                   (channel, ping_time) float32 20kB 1.0 ... nan\n",
+       "    transmit_type                  (channel, ping_time) object 41kB &#x27;LFM&#x27; ......\n",
+       "    sample_time_offset             (channel, ping_time) float64 41kB 0.0 ... nan\n",
+       "    transmit_frequency_start       (channel, ping_time) float64 41kB 2.8e+05 ...\n",
+       "    transmit_frequency_stop        (channel, ping_time) float64 41kB 3.8e+05 ...\n",
+       "Attributes:\n",
+       "    beam_mode:              vertical\n",
+       "    conversion_equation_t:  type_3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5d4dd126-e08e-40e2-b782-eb08a7306160' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5d4dd126-e08e-40e2-b782-eb08a7306160' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li><li><span class='xr-has-index'>beam_group</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-4befea52-c64c-4194-bff6-c625a3a14572' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4befea52-c64c-4194-bff6-c625a3a14572' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-dce97ba4-35ed-46c3-9af4-2b7ff153908f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce97ba4-35ed-46c3-9af4-2b7ff153908f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d6e7b09-1458-40f3-a768-c4f6bbd6e33f' class='xr-var-data-in' type='checkbox'><label for='data-4d6e7b09-1458-40f3-a768-c4f6bbd6e33f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-a39b8eba-3366-4b9e-8e2f-096e770f17d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a39b8eba-3366-4b9e-8e2f-096e770f17d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e77e00ec-8265-406d-a839-6096b403b5e6' class='xr-var-data-in' type='checkbox'><label for='data-e77e00ec-8265-406d-a839-6096b403b5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-0efc1553-2bbe-4e44-938d-5a4d8dc2a6f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0efc1553-2bbe-4e44-938d-5a4d8dc2a6f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e76bbc89-37c1-4cd3-a3c5-bb0622065734' class='xr-var-data-in' type='checkbox'><label for='data-e76bbc89-37c1-4cd3-a3c5-bb0622065734' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;</div><input id='attrs-4dec811f-74a9-40f6-a725-6f6f94bb8cf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dec811f-74a9-40f6-a725-6f6f94bb8cf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d9df0e8-3f29-484e-9cc1-c47773e5f80f' class='xr-var-data-in' type='checkbox'><label for='data-1d9df0e8-3f29-484e-9cc1-c47773e5f80f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1&#x27;, &#x27;2&#x27;, &#x27;3&#x27;, &#x27;4&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-4f24ba7c-c805-441d-ba5a-2f41034c0c01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f24ba7c-c805-441d-ba5a-2f41034c0c01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b38ef3e4-0a00-453d-90e3-e8704b04f456' class='xr-var-data-in' type='checkbox'><label for='data-b38ef3e4-0a00-453d-90e3-e8704b04f456' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-2a03908d-d503-4340-b95a-d9022dfe2b46' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a03908d-d503-4340-b95a-d9022dfe2b46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f9fe727-1642-4b39-adb9-58b48a3369ff' class='xr-var-data-in' type='checkbox'><label for='data-9f9fe727-1642-4b39-adb9-58b48a3369ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-5eb8cfbe-7545-4285-944b-28adf2dcbfad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eb8cfbe-7545-4285-944b-28adf2dcbfad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f7eebb-f987-41bc-b281-9a73bb52e909' class='xr-var-data-in' type='checkbox'><label for='data-05f7eebb-f987-41bc-b281-9a73bb52e909' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd1765b9-5094-4fd2-8124-ead345df0614' class='xr-section-summary-in' type='checkbox' /><label for='section-fd1765b9-5094-4fd2-8124-ead345df0614' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-56463e2f-77a7-4513-8c33-3451a3fdc188' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56463e2f-77a7-4513-8c33-3451a3fdc188' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b1189cc-612f-48b0-b19b-9bd38a116135' class='xr-var-data-in' type='checkbox'><label for='data-2b1189cc-612f-48b0-b19b-9bd38a116135' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1</div><input id='attrs-e85df5c6-6720-42a4-b13d-41c1c722c906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e85df5c6-6720-42a4-b13d-41c1c722c906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99646d6-b0ba-4c81-97be-3ce5e0b0ec3b' class='xr-var-data-in' type='checkbox'><label for='data-b99646d6-b0ba-4c81-97be-3ce5e0b0ec3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>type of transducer (0-single, 1-split)</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.73 6.96 6.79 7.26</div><input id='attrs-7ba132a4-9ea3-4af1-9f7d-6a1a94353bdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ba132a4-9ea3-4af1-9f7d-6a1a94353bdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0c0e845-568e-4ee2-b27b-945b1ab00253' class='xr-var-data-in' type='checkbox'><label for='data-a0c0e845-568e-4ee2-b27b-945b1ab00253' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along alongship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_minor and beamwidth_transmit_minor), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.73000002, 6.96000004, 6.78999996, 7.26000023])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.77 6.87 6.85 7.28</div><input id='attrs-d0e52da8-102a-486b-a411-3bf702b0f481' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0e52da8-102a-486b-a411-3bf702b0f481' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1aa8757-0628-4dea-aebc-d5bbb7639b4b' class='xr-var-data-in' type='checkbox'><label for='data-e1aa8757-0628-4dea-aebc-d5bbb7639b4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along athwartship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_major and beamwidth_transmit_major), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.76999998, 6.86999989, 6.8499999 , 7.28000021])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-e954c18d-521b-4e32-b06c-2928190552b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e954c18d-521b-4e32-b06c-2928190552b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-918602a8-5032-4ed5-acf1-bd758f43b9a6' class='xr-var-data-in' type='checkbox'><label for='data-918602a8-5032-4ed5-acf1-bd758f43b9a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-3af45ef3-1b9a-44ad-961c-e31aef85a655' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3af45ef3-1b9a-44ad-961c-e31aef85a655' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a083cd-dd78-4efe-82aa-fb211490fc15' class='xr-var-data-in' type='checkbox'><label for='data-04a083cd-dd78-4efe-82aa-fb211490fc15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-2c77eff5-6bf4-49e8-a132-d693da421379' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c77eff5-6bf4-49e8-a132-d693da421379' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96279542-2cb0-4f72-ad52-e39977c8ec54' class='xr-var-data-in' type='checkbox'><label for='data-96279542-2cb0-4f72-ad52-e39977c8ec54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.07 -0.08 0.01 -0.07</div><input id='attrs-643dc435-159f-4d82-a26f-41ac8a88271a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-643dc435-159f-4d82-a26f-41ac8a88271a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd542c66-33c7-459d-81c7-d0408424151c' class='xr-var-data-in' type='checkbox'><label for='data-dd542c66-33c7-459d-81c7-d0408424151c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical alongship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([-0.07, -0.08,  0.01, -0.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07 -0.06 0.01 -0.01</div><input id='attrs-9582c736-a650-427b-abec-4dae0485bced' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9582c736-a650-427b-abec-4dae0485bced' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d566cb28-7a2a-4669-b722-71588c862d66' class='xr-var-data-in' type='checkbox'><label for='data-d566cb28-7a2a-4669-b722-71588c862d66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical athwartship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([ 0.07, -0.06,  0.01, -0.01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-e22748fe-a465-45ec-984b-f2405bb27a2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e22748fe-a465-45ec-984b-f2405bb27a2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3fb4ae3-f6dc-4ae8-b9b2-dac36679f99c' class='xr-var-data-in' type='checkbox'><label for='data-d3fb4ae3-f6dc-4ae8-b9b2-dac36679f99c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>alongship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-34247755-2829-4d99-a1b5-b7399d5ded46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34247755-2829-4d99-a1b5-b7399d5ded46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a349f9-5cc2-4690-a6f2-20c2a9041eec' class='xr-var-data-in' type='checkbox'><label for='data-06a349f9-5cc2-4690-a6f2-20c2a9041eec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>athwartship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.7 -20.7 -20.7 -20.7</div><input id='attrs-0a8b7b6c-c96c-487f-b4b8-7421530f83f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a8b7b6c-c96c-487f-b4b8-7421530f83f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fa8e84d-e656-4d1d-ae96-2fd767827e4d' class='xr-var-data-in' type='checkbox'><label for='data-6fa8e84d-e656-4d1d-ae96-2fd767827e4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Equivalent beam angle</dd><dt><span>units :</span></dt><dd>sr</dd><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd></dl></div><div class='xr-var-data'><pre>array([-20.7, -20.7, -20.7, -20.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_software_version</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27;</div><input id='attrs-f18f95a9-4176-42c9-9094-9902fa31030e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f18f95a9-4176-42c9-9094-9902fa31030e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1516a34f-8f8a-44b0-95f4-b7fcd1b5b47e' class='xr-var-data-in' type='checkbox'><label for='data-1516a34f-8f8a-44b0-95f4-b7fcd1b5b47e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_stabilisation</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-4781dc40-d08e-429b-8ce4-4e9e13cadd57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4781dc40-d08e-429b-8ce4-4e9e13cadd57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd4e1859-70be-4cef-a044-45355c93fda3' class='xr-var-data-in' type='checkbox'><label for='data-dd4e1859-70be-4cef-a044-45355c93fda3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam stabilisation applied (or not)</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;not stabilised&#x27;, &#x27;stabilised&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>non_quantitative_processing</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-25863a44-d6cb-4064-8030-d82e317da970' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25863a44-d6cb-4064-8030-d82e317da970' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c26680d-105a-4839-9fd9-a7d0b8f83e44' class='xr-var-data-in' type='checkbox'><label for='data-2c26680d-105a-4839-9fd9-a7d0b8f83e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Presence or not of non-quantitative processing applied to the backscattering data (sonar specific)</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;None&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_r</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.015e-06 -3.043e-06 ... nan nan</div><input id='attrs-51796ef5-1e36-48c5-9f1b-f8440c37ecd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51796ef5-1e36-48c5-9f1b-f8440c37ecd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c672a5d8-a2d4-41e9-9a5c-6cc4d09431a2' class='xr-var-data-in' type='checkbox'><label for='data-c672a5d8-a2d4-41e9-9a5c-6cc4d09431a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (real part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 2.01457806e-06, -3.04280593e-06,  9.71826069e-08,\n",
+       "          -3.96171856e-07],\n",
+       "         [-2.57343663e-06,  2.95345012e-06, -3.57061339e-07,\n",
+       "          -4.56580392e-06],\n",
+       "         [ 3.29502800e-05, -4.48711071e-05, -2.65489780e-05,\n",
+       "           3.19184528e-06],\n",
+       "         ...,\n",
+       "         [-5.15527026e-05,  3.61862447e-04,  4.46741295e-04,\n",
+       "           9.19265494e-06],\n",
+       "         [-3.07514332e-04,  4.12420253e-04,  5.00583847e-04,\n",
+       "          -1.36591814e-04],\n",
+       "         [-3.16080404e-04,  1.67110382e-04,  2.05256962e-04,\n",
+       "          -2.96069280e-04]],\n",
+       "\n",
+       "        [[ 3.04275636e-06,  1.86782506e-06, -2.01816974e-07,\n",
+       "          -2.56592944e-06],\n",
+       "         [-1.16343890e-05,  8.68735242e-07, -7.25317477e-07,\n",
+       "           1.69276484e-06],\n",
+       "         [-2.35087555e-05,  7.90977992e-06, -2.92311088e-05,\n",
+       "          -1.68325369e-05],\n",
+       "...\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]],\n",
+       "\n",
+       "        [[            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         ...,\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_i</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.127e-06 -7.477e-07 ... nan nan</div><input id='attrs-ca7523bc-709b-4542-8c02-a12c0f95a8cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca7523bc-709b-4542-8c02-a12c0f95a8cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-313715c9-8a4e-444e-b41f-fb8fca56fca7' class='xr-var-data-in' type='checkbox'><label for='data-313715c9-8a4e-444e-b41f-fb8fca56fca7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (imaginary part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[-1.12652685e-06, -7.47656998e-07,  1.54780153e-07,\n",
+       "          -3.68357291e-06],\n",
+       "         [-6.13030397e-06,  9.28021564e-06,  3.91020649e-06,\n",
+       "          -3.28862302e-06],\n",
+       "         [-2.67872038e-05, -9.96628387e-06,  8.83363555e-06,\n",
+       "          -3.67659850e-05],\n",
+       "         ...,\n",
+       "         [-2.75080121e-04,  1.48990759e-04,  1.45175451e-04,\n",
+       "          -3.60909820e-04],\n",
+       "         [-1.56141366e-04, -2.44574185e-04, -1.55665955e-04,\n",
+       "          -2.41969436e-04],\n",
+       "         [ 1.19555603e-04, -5.27278928e-04, -5.00589900e-04,\n",
+       "          -1.23716411e-04]],\n",
+       "\n",
+       "        [[-2.38715370e-06,  1.20847983e-06, -4.15739777e-07,\n",
+       "           7.34627577e-07],\n",
+       "         [ 5.83230258e-06, -1.54376824e-06,  1.94760219e-06,\n",
+       "           4.64016330e-06],\n",
+       "         [-8.37771586e-05,  2.59587637e-06, -3.51226549e-06,\n",
+       "           3.85061730e-06],\n",
+       "...\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]],\n",
+       "\n",
+       "        [[            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         ...,\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_interval</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.333e-06 5.333e-06 ... 8e-06 nan</div><input id='attrs-6d2b925a-4a26-47ac-8f4e-9d78d8093e59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d2b925a-4a26-47ac-8f4e-9d78d8093e59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34051ce8-ef3f-4c79-ae36-5bcc4c19d9be' class='xr-var-data-in' type='checkbox'><label for='data-34051ce8-ef3f-4c79-ae36-5bcc4c19d9be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Interval between recorded raw data samples</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[5.33333e-06, 5.33333e-06, 5.33333e-06, ..., 5.33333e-06,\n",
+       "        5.33333e-06, 5.33333e-06],\n",
+       "       [2.13333e-05, 2.13333e-05, 2.13333e-05, ..., 2.13333e-05,\n",
+       "        2.13333e-05, 2.13333e-05],\n",
+       "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
+       "        8.00000e-06, 8.00000e-06],\n",
+       "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
+       "        8.00000e-06,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_power</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0 40.0 40.0 ... 100.0 100.0 nan</div><input id='attrs-c5a1f9c2-f4ed-43cb-b7bc-32b110d86335' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5a1f9c2-f4ed-43cb-b7bc-32b110d86335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab004848-afa7-47ea-950d-1cb5a677ed97' class='xr-var-data-in' type='checkbox'><label for='data-ab004848-afa7-47ea-950d-1cb5a677ed97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal transmit power</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[ 40.,  40.,  40., ...,  40.,  40.,  40.],\n",
+       "       [ 75.,  75.,  75., ...,  75.,  75.,  75.],\n",
+       "       [105., 105., 105., ..., 105., 105., 105.],\n",
+       "       [100., 100., 100., ..., 100., 100.,  nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_duration_nominal</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002048 0.002048 ... 0.002048 nan</div><input id='attrs-eb16713b-6f43-41d4-bd6c-7709a104e783' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb16713b-6f43-41d4-bd6c-7709a104e783' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f5886d2-a0cc-4f01-a9c8-353814ece35c' class='xr-var-data-in' type='checkbox'><label for='data-0f5886d2-a0cc-4f01-a9c8-353814ece35c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal bandwidth of transmitted pulse</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048,      nan]],\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003488 0.003488 ... 0.01085 nan</div><input id='attrs-d0977072-a97f-45aa-a621-7c91d68348e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0977072-a97f-45aa-a621-7c91d68348e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0d4d793-85d3-405e-9e8b-f0d71c2f6ce7' class='xr-var-data-in' type='checkbox'><label for='data-f0d4d793-85d3-405e-9e8b-f0d71c2f6ce7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Hann window slope parameter for transmit signal</dd></dl></div><div class='xr-var-data'><pre>array([[0.00348772, 0.00348772, 0.00348772, ..., 0.00348772, 0.00348772,\n",
+       "        0.00348772],\n",
+       "       [0.0177557 , 0.0177557 , 0.0177557 , ..., 0.0177557 , 0.0177557 ,\n",
+       "        0.0177557 ],\n",
+       "       [0.00574449, 0.00574449, 0.00574449, ..., 0.00574449, 0.00574449,\n",
+       "        0.00574449],\n",
+       "       [0.0108507 , 0.0108507 , 0.0108507 , ..., 0.0108507 , 0.0108507 ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_mode</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-6d6359eb-49bb-4dbd-b779-071b8bc7e193' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d6359eb-49bb-4dbd-b779-071b8bc7e193' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9d1a713-b657-40cf-8fff-dd38458070b3' class='xr-var-data-in' type='checkbox'><label for='data-c9d1a713-b657-40cf-8fff-dd38458070b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver mode</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Active&#x27;, &#x27;Unknown&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0., nan]],\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_type</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;LFM&#x27; &#x27;LFM&#x27; &#x27;LFM&#x27; ... &#x27;LFM&#x27; nan</div><input id='attrs-5b1485c8-7789-4d79-b1dd-882aa280e4f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b1485c8-7789-4d79-b1dd-882aa280e4f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6221d42c-73ef-46de-990b-4eda4842b355' class='xr-var-data-in' type='checkbox'><label for='data-6221d42c-73ef-46de-990b-4eda4842b355' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Type of transmitted pulse</dd><dt><span>flag_values :</span></dt><dd>[&#x27;CW&#x27;, &#x27;LFM&#x27;, &#x27;FMD&#x27;]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Continuous Wave – a pulse nominally of one frequency&#x27;, &#x27;Linear Frequency Modulation – a pulse which varies from transmit_frequency_start to transmit_frequency_stop in a linear manner over the nominal pulse duration (transmit_duration_nominal)&#x27;, &quot;Frequency Modulated &#x27;D&#x27; - An EK80-specific FM type that is not clearly described&quot;]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, nan]],\n",
+       "      shape=(4, 1266), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_time_offset</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-9afc46c0-d2aa-4dbd-b4d7-50643b22ec57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9afc46c0-d2aa-4dbd-b4d7-50643b22ec57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9c477e6-df9e-4324-a2cb-becda37bdea5' class='xr-var-data-in' type='checkbox'><label for='data-b9c477e6-df9e-4324-a2cb-becda37bdea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time offset that is subtracted from the timestamp of each sample</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_start</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.8e+05 2.8e+05 ... 9e+04 nan</div><input id='attrs-bb246e51-cfa3-42e6-bbd8-30e7b8dd6e69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb246e51-cfa3-42e6-bbd8-30e7b8dd6e69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-870a77e3-35de-4cca-a848-920508fffb09' class='xr-var-data-in' type='checkbox'><label for='data-870a77e3-35de-4cca-a848-920508fffb09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[280000., 280000., 280000., ..., 280000., 280000., 280000.],\n",
+       "       [ 55000.,  55000.,  55000., ...,  55000.,  55000.,  55000.],\n",
+       "       [170000., 170000., 170000., ..., 170000., 170000., 170000.],\n",
+       "       [ 90000.,  90000.,  90000., ...,  90000.,  90000.,     nan]],\n",
+       "      shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_stop</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.8e+05 3.8e+05 ... 1.7e+05 nan</div><input id='attrs-687834aa-6953-4d69-b46a-20190955a6fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-687834aa-6953-4d69-b46a-20190955a6fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3520b899-5011-498a-90ec-4b0076a11867' class='xr-var-data-in' type='checkbox'><label for='data-3520b899-5011-498a-90ec-4b0076a11867' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Stop frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[380000., 380000., 380000., ..., 380000., 380000., 380000.],\n",
+       "       [ 85000.,  85000.,  85000., ...,  85000.,  85000.,  85000.],\n",
+       "       [260000., 260000., 260000., ..., 260000., 260000., 260000.],\n",
+       "       [170000., 170000., 170000., ..., 170000., 170000.,     nan]],\n",
+       "      shape=(4, 1266))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-275c3392-d5b9-4d6e-b84f-355df05d8d0b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-275c3392-d5b9-4d6e-b84f-355df05d8d0b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>beam_mode :</span></dt><dd>vertical</dd><dt><span>conversion_equation_t :</span></dt><dd>type_3</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_1ba576549b354dcfb6672af6f86f374b\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_1ba576549b354dcfb6672af6f86f374b\" class=\"xr-section-summary\">Vendor_specific: contains vendor-specific information about the sonar and the data.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 531kB\n",
+       "Dimensions:                      (channel: 4, pulse_length_bin: 5,\n",
+       "                                  cal_channel_id: 4, cal_frequency: 413,\n",
+       "                                  filter_time: 1, WBT_filter_n: 119,\n",
+       "                                  PC_filter_n: 391)\n",
+       "Coordinates:\n",
+       "  * channel                      (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7CD...\n",
+       "  * pulse_length_bin             (pulse_length_bin) int64 40B 0 1 2 3 4\n",
+       "  * cal_channel_id               (cal_channel_id) object 32B &#x27;WBT 747008-15 E...\n",
+       "  * cal_frequency                (cal_frequency) int64 3kB 55000 ... 380000\n",
+       "  * filter_time                  (filter_time) datetime64[ns] 8B 2021-12-15T1...\n",
+       "Dimensions without coordinates: WBT_filter_n, PC_filter_n\n",
+       "Data variables: (12/21)\n",
+       "    frequency_nominal            (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    sa_correction                (channel, pulse_length_bin) float64 160B 0.0...\n",
+       "    gain_correction              (channel, pulse_length_bin) float64 160B 25....\n",
+       "    pulse_length                 (channel, pulse_length_bin) float64 160B 6.4...\n",
+       "    impedance_transceiver        (channel) int64 32B 5400 5400 5400 5400\n",
+       "    receiver_sampling_frequency  (channel) float64 32B 1.5e+06 ... 1.5e+06\n",
+       "    ...                           ...\n",
+       "    WBT_coeffs_imag              (channel, filter_time, WBT_filter_n) float64 4kB ...\n",
+       "    PC_coeffs_real               (channel, filter_time, PC_filter_n) float64 13kB ...\n",
+       "    PC_coeffs_imag               (channel, filter_time, PC_filter_n) float64 13kB ...\n",
+       "    WBT_deci_fac                 (channel, filter_time) float64 32B 8.0 ... 12.0\n",
+       "    PC_deci_fac                  (channel, filter_time) float64 32B 1.0 ... 1.0\n",
+       "    config_xml                   &lt;U100225 401kB &#x27;&lt;?xml version=&quot;1.0&quot; encoding...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-970b8dc6-88b5-493b-937b-7ee2f4ea9d09' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-970b8dc6-88b5-493b-937b-7ee2f4ea9d09' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>pulse_length_bin</span>: 5</li><li><span class='xr-has-index'>cal_channel_id</span>: 4</li><li><span class='xr-has-index'>cal_frequency</span>: 413</li><li><span class='xr-has-index'>filter_time</span>: 1</li><li><span>WBT_filter_n</span>: 119</li><li><span>PC_filter_n</span>: 391</li></ul></div></li><li class='xr-section-item'><input id='section-edb1c6b2-5883-4e0e-b25c-5deb300fe4ab' class='xr-section-summary-in' type='checkbox' checked /><label for='section-edb1c6b2-5883-4e0e-b25c-5deb300fe4ab' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-c03e1641-1515-48a3-ae26-883a7df7f083' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c03e1641-1515-48a3-ae26-883a7df7f083' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b1a4533-63ec-44b6-af6f-fa688eeee0fc' class='xr-var-data-in' type='checkbox'><label for='data-5b1a4533-63ec-44b6-af6f-fa688eeee0fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pulse_length_bin</span></div><div class='xr-var-dims'>(pulse_length_bin)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-1e6697d1-d4fa-47a0-bcc0-0f7f6090adc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e6697d1-d4fa-47a0-bcc0-0f7f6090adc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fc6fb54-b709-4cd3-8a38-acbad001a55a' class='xr-var-data-in' type='checkbox'><label for='data-2fc6fb54-b709-4cd3-8a38-acbad001a55a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_channel_id</span></div><div class='xr-var-dims'>(cal_channel_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-e4ca82d4-b31f-464a-84f8-3327eeb88ab3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4ca82d4-b31f-464a-84f8-3327eeb88ab3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb072c88-15e0-48c0-8dac-0afbc5d8ed7e' class='xr-var-data-in' type='checkbox'><label for='data-bb072c88-15e0-48c0-8dac-0afbc5d8ed7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ID of channels containing broadband calibration information</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_frequency</span></div><div class='xr-var-dims'>(cal_frequency)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>55000 55480 55961 ... 379099 380000</div><input id='attrs-a3e33b5f-ec57-42a6-a039-a4f87d8c9003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3e33b5f-ec57-42a6-a039-a4f87d8c9003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7c255e2-6fd3-4211-8b11-8acd964a2768' class='xr-var-data-in' type='checkbox'><label for='data-f7c255e2-6fd3-4211-8b11-8acd964a2768' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency of calibration parameter</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 55000,  55480,  55961, ..., 378098, 379099, 380000], shape=(413,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filter_time</span></div><div class='xr-var-dims'>(filter_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-b8e4c2aa-396d-463d-9817-1c63e69d699b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8e4c2aa-396d-463d-9817-1c63e69d699b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feff9fbf-ee42-4743-9795-8bfaf2fbeedf' class='xr-var-data-in' type='checkbox'><label for='data-feff9fbf-ee42-4743-9795-8bfaf2fbeedf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3640aaf-aeb3-491f-acd8-6fcf538190f7' class='xr-section-summary-in' type='checkbox' /><label for='section-f3640aaf-aeb3-491f-acd8-6fcf538190f7' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-3bf4607e-0db3-4599-969f-e3d6db615630' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bf4607e-0db3-4599-969f-e3d6db615630' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1932405b-b524-4150-b2ae-354bba2a7f72' class='xr-var-data-in' type='checkbox'><label for='data-1932405b-b524-4150-b2ae-354bba2a7f72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... -0.4 0.0 0.0</div><input id='attrs-cd1cb706-d13e-4ebf-8804-0f775cfea268' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd1cb706-d13e-4ebf-8804-0f775cfea268' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d5be396-1656-47d2-8aa3-092776083a76' class='xr-var-data-in' type='checkbox'><label for='data-4d5be396-1656-47d2-8aa3-092776083a76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],\n",
+       "       [ 0.  ,  0.  , -0.02,  0.  ,  0.  ],\n",
+       "       [ 0.  ,  0.  , -0.26, -0.01,  0.  ],\n",
+       "       [ 0.  ,  0.  , -0.4 ,  0.  ,  0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0 25.0 25.0 ... 27.2 27.0 27.0</div><input id='attrs-bd929f78-9df3-4133-bad6-21c2224eab85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd929f78-9df3-4133-bad6-21c2224eab85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce4c0b58-57d3-445a-8e65-5015874ef421' class='xr-var-data-in' type='checkbox'><label for='data-ce4c0b58-57d3-445a-8e65-5015874ef421' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.  , 25.  , 25.  , 17.57, 25.  ],\n",
+       "       [27.  , 27.  , 27.59, 27.  , 27.  ],\n",
+       "       [26.  , 26.  , 27.48, 27.33, 26.  ],\n",
+       "       [27.  , 27.  , 27.2 , 27.  , 27.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pulse_length</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.4e-05 0.000128 ... 0.001024</div><input id='attrs-78b566e7-f6ac-47d4-bdba-073e84942e1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78b566e7-f6ac-47d4-bdba-073e84942e1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40c361ce-a7c2-4911-8749-62c7d1ccb871' class='xr-var-data-in' type='checkbox'><label for='data-40c361ce-a7c2-4911-8749-62c7d1ccb871' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
+       "       [1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03, 2.048e-03],\n",
+       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
+       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-0ca5d4f5-eab2-4fd3-a440-c34c8e917501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ca5d4f5-eab2-4fd3-a440-c34c8e917501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f88cde71-1ffe-4a13-b40b-4e3624c37ebd' class='xr-var-data-in' type='checkbox'><label for='data-f88cde71-1ffe-4a13-b40b-4e3624c37ebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-f2bb1f65-7a19-47c8-8e6e-97f045c493c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2bb1f65-7a19-47c8-8e6e-97f045c493c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4acfea4-ba18-45c2-96a1-bf09a8f855cf' class='xr-var-data-in' type='checkbox'><label for='data-a4acfea4-ba18-45c2-96a1-bf09a8f855cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27;</div><input id='attrs-42bcac06-f7ab-41ca-9660-9f567bcc7302' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42bcac06-f7ab-41ca-9660-9f567bcc7302' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66ce4645-91e7-4328-80da-b1ea318a53b2' class='xr-var-data-in' type='checkbox'><label for='data-66ce4645-91e7-4328-80da-b1ea318a53b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver type</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a73f8603-7355-442c-9bad-2387784af5ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a73f8603-7355-442c-9bad-2387784af5ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13afd17a-f26b-48b4-bf29-36c5c55d47c2' class='xr-var-data-in' type='checkbox'><label for='data-13afd17a-f26b-48b4-bf29-36c5c55d47c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., 27.85, 27.85, 27.82],\n",
+       "       [20.59, 22.95, 24.07, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cdf8b07b-cd76-4860-a2eb-9019fdb89f05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cdf8b07b-cd76-4860-a2eb-9019fdb89f05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69226643-e8d9-4acc-95b9-dc840619444b' class='xr-var-data-in' type='checkbox'><label for='data-69226643-e8d9-4acc-95b9-dc840619444b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phase</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e552e581-b4d7-490f-a383-2ab8b9c37cfc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e552e581-b4d7-490f-a383-2ab8b9c37cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1218ad84-b8df-4fda-8365-c163cb11ac9a' class='xr-var-data-in' type='checkbox'><label for='data-1218ad84-b8df-4fda-8365-c163cb11ac9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b314739a-ac75-4d88-96c9-10c63f969d61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b314739a-ac75-4d88-96c9-10c63f969d61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eccaf05-f218-4c83-a174-1470d34dde2f' class='xr-var-data-in' type='checkbox'><label for='data-6eccaf05-f218-4c83-a174-1470d34dde2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.01, 6.  , 5.97],\n",
+       "       [9.33, 8.67, 8.3 , ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6b553291-1032-4c41-9b83-daf3397a9551' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b553291-1032-4c41-9b83-daf3397a9551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c35031a7-9a53-4fc8-b420-6145194ad6f1' class='xr-var-data-in' type='checkbox'><label for='data-c35031a7-9a53-4fc8-b420-6145194ad6f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.05, 6.01, 5.99],\n",
+       "       [9.5 , 8.24, 8.38, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf46321d-9b4f-493b-b8d6-3711f0cda1e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf46321d-9b4f-493b-b8d6-3711f0cda1e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be9da896-9635-4448-ad3b-dcdcdc179102' class='xr-var-data-in' type='checkbox'><label for='data-be9da896-9635-4448-ad3b-dcdcdc179102' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.01, -0.01,  0.  ],\n",
+       "       [ 0.04, -0.18, -0.26, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-abdd0e86-9414-4748-a4a1-478248f22c6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-abdd0e86-9414-4748-a4a1-478248f22c6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cf25fbe-897f-49f9-addf-e58b98b2d915' class='xr-var-data-in' type='checkbox'><label for='data-2cf25fbe-897f-49f9-addf-e58b98b2d915' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.05, -0.05, -0.08],\n",
+       "       [ 0.35, -0.02,  0.02, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.144e-05 -0.0001601 ... 9.705e-06</div><input id='attrs-8ba515f8-123f-490f-8cf2-254391f11774' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ba515f8-123f-490f-8cf2-254391f11774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7785e6ce-31a3-4d71-b185-adefed77555e' class='xr-var-data-in' type='checkbox'><label for='data-7785e6ce-31a3-4d71-b185-adefed77555e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.14427166e-05, -1.60068841e-04, -3.74446070e-04,\n",
+       "          5.80396911e-04,  1.79292378e-03, -5.69819706e-04,\n",
+       "         -4.36119642e-03, -1.06982014e-03,  6.37054257e-03,\n",
+       "          3.98992328e-03, -5.19806752e-03, -4.50613070e-03,\n",
+       "          1.07290410e-03, -2.02566851e-03,  5.07575809e-04,\n",
+       "          1.47993285e-02,  6.74376963e-03, -2.42605228e-02,\n",
+       "         -1.99034940e-02,  1.98264010e-02,  2.28713546e-02,\n",
+       "         -4.73045558e-03,  1.66427530e-03,  1.54931960e-03,\n",
+       "         -5.10883406e-02, -3.59251946e-02,  9.50072855e-02,\n",
+       "          1.08932644e-01, -9.52564925e-02, -1.85995519e-01,\n",
+       "          4.01502699e-02,  2.19155550e-01,  4.01502699e-02,\n",
+       "         -1.85995519e-01, -9.52564925e-02,  1.08932644e-01,\n",
+       "          9.50072855e-02, -3.59251946e-02, -5.10883406e-02,\n",
+       "          1.54931960e-03,  1.66427530e-03, -4.73045558e-03,\n",
+       "          2.28713546e-02,  1.98264010e-02, -1.99034940e-02,\n",
+       "         -2.42605228e-02,  6.74376963e-03,  1.47993285e-02,\n",
+       "          5.07575809e-04, -2.02566851e-03,  1.07290410e-03,\n",
+       "         -4.50613070e-03, -5.19806752e-03,  3.98992328e-03,\n",
+       "          6.37054257e-03, -1.06982014e-03, -4.36119642e-03,\n",
+       "         -5.69819706e-04,  1.79292378e-03,  5.80396911e-04,\n",
+       "...\n",
+       "          1.28910273e-01,  6.77423924e-02, -8.72524641e-03,\n",
+       "         -7.36967400e-02, -1.07046373e-01, -1.02706917e-01,\n",
+       "         -6.94890395e-02, -2.54954696e-02,  1.07670929e-02,\n",
+       "          2.82163061e-02,  2.65309773e-02,  1.40545843e-02,\n",
+       "          2.02343985e-03, -1.57549907e-03,  4.54013515e-03,\n",
+       "          1.54866800e-02,  2.38744710e-02,  2.42441874e-02,\n",
+       "          1.58575494e-02,  2.60307826e-03, -9.54600796e-03,\n",
+       "         -1.58524998e-02, -1.50543209e-02, -9.48206428e-03,\n",
+       "         -3.28161148e-03,  5.14209241e-05, -5.86639857e-04,\n",
+       "         -3.71975894e-03, -6.53725956e-03, -6.69319043e-03,\n",
+       "         -3.60184023e-03,  1.40942517e-03,  6.01961603e-03,\n",
+       "          8.26145709e-03,  7.50966882e-03,  4.62702196e-03,\n",
+       "          1.30935630e-03, -9.04795772e-04, -1.38237234e-03,\n",
+       "         -5.43581322e-04,  5.71371173e-04,  9.88384243e-04,\n",
+       "          3.29891511e-04, -1.06842164e-03, -2.44627846e-03,\n",
+       "         -3.08986311e-03, -2.70423386e-03, -1.50845083e-03,\n",
+       "         -5.42755188e-05,  1.08743296e-03,  1.58825796e-03,\n",
+       "          1.45288126e-03,  9.33228002e-04,  3.50838847e-04,\n",
+       "         -6.20377104e-05, -2.31620375e-04, -2.17583845e-04,\n",
+       "         -1.59145377e-04,  9.70470410e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.63e-05 0.000117 ... 9.655e-06</div><input id='attrs-7e94c5d5-5a45-4d40-946f-e1db55f58448' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e94c5d5-5a45-4d40-946f-e1db55f58448' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c844e259-e4c2-42be-8d15-d40f7c48673c' class='xr-var-data-in' type='checkbox'><label for='data-c844e259-e4c2-42be-8d15-d40f7c48673c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.63023958e-05,  1.16975585e-04, -3.52505565e-04,\n",
+       "         -9.13087046e-04,  7.09498825e-04,  2.99199694e-03,\n",
+       "          9.69185190e-18, -5.61309094e-03, -2.52190628e-03,\n",
+       "          6.28564134e-03,  4.88218758e-03, -3.27457441e-03,\n",
+       "         -2.27805204e-03, -5.20343136e-04, -8.05283710e-03,\n",
+       "         -1.86947198e-03,  2.07523126e-02,  1.33378496e-02,\n",
+       "         -2.40603201e-02, -2.39648726e-02,  1.25731202e-02,\n",
+       "          1.45617211e-02,  2.10128841e-04,  2.46108808e-02,\n",
+       "          1.31174969e-02, -7.63469040e-02, -6.90261498e-02,\n",
+       "          1.02293685e-01,  1.50101691e-01, -7.36412108e-02,\n",
+       "         -2.10470200e-01,  7.60158497e-20,  2.10470200e-01,\n",
+       "          7.36412108e-02, -1.50101691e-01, -1.02293685e-01,\n",
+       "          6.90261498e-02,  7.63469040e-02, -1.31174969e-02,\n",
+       "         -2.46108808e-02, -2.10128841e-04, -1.45617211e-02,\n",
+       "         -1.25731202e-02,  2.39648726e-02,  2.40603201e-02,\n",
+       "         -1.33378496e-02, -2.07523126e-02,  1.86947198e-03,\n",
+       "          8.05283710e-03,  5.20343136e-04,  2.27805204e-03,\n",
+       "          3.27457441e-03, -4.88218758e-03, -6.28564134e-03,\n",
+       "          2.52190628e-03,  5.61309094e-03, -9.55039822e-18,\n",
+       "         -2.99199694e-03, -7.09498825e-04,  9.13087046e-04,\n",
+       "...\n",
+       "          7.80717358e-02,  1.29582077e-01,  1.38660282e-01,\n",
+       "          1.06033586e-01,  4.76594567e-02, -1.29747139e-02,\n",
+       "         -5.50751574e-02, -6.85512722e-02, -5.64508401e-02,\n",
+       "         -3.13390270e-02, -8.01062118e-03,  3.60898394e-03,\n",
+       "          2.06778105e-03, -6.71086088e-03, -1.39776571e-02,\n",
+       "         -1.33690219e-02, -4.03831480e-03,  9.59953945e-03,\n",
+       "          2.08935011e-02,  2.47807242e-02,  2.02831514e-02,\n",
+       "          1.05313919e-02,  6.30900904e-04, -5.21199452e-03,\n",
+       "         -5.68135269e-03, -2.52550538e-03,  9.22063016e-04,\n",
+       "          1.84576935e-03, -5.48824668e-04, -4.86181164e-03,\n",
+       "         -8.56491644e-03, -9.55463666e-03, -7.27825612e-03,\n",
+       "         -2.87745940e-03,  1.59654417e-03,  4.34645358e-03,\n",
+       "          4.69489116e-03,  3.23531032e-03,  1.29674340e-03,\n",
+       "          1.15227005e-04,  1.99488175e-04,  1.19654136e-03,\n",
+       "          2.24404945e-03,  2.53815181e-03,  1.77624938e-03,\n",
+       "          2.59338703e-04, -1.34165830e-03, -2.37460458e-03,\n",
+       "         -2.52039032e-03, -1.88605406e-03, -8.73966317e-04,\n",
+       "          6.09558374e-05,  6.21019106e-04,  7.48717517e-04,\n",
+       "          5.76159859e-04,  3.03197594e-04,  8.55612234e-05,\n",
+       "         -2.66669540e-05,  9.65512845e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0003825 -0.001017 ... nan nan</div><input id='attrs-4554c2c6-cf3f-4945-a25e-3eb71c0aade1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4554c2c6-cf3f-4945-a25e-3eb71c0aade1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cdbde03-aed8-4a7f-afd0-16d9487b4e40' class='xr-var-data-in' type='checkbox'><label for='data-7cdbde03-aed8-4a7f-afd0-16d9487b4e40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.82524973e-04, -1.01727119e-03,  1.55105174e-03, ...,\n",
+       "                     nan,             nan,             nan]],\n",
+       "\n",
+       "       [[-2.92797376e-05,  1.22475076e-05,  2.08751826e-05, ...,\n",
+       "                     nan,             nan,             nan]],\n",
+       "\n",
+       "       [[-4.78051297e-05,  1.28309519e-04,  1.03955274e-04, ...,\n",
+       "          1.03955274e-04,  1.28309519e-04, -4.78051297e-05]],\n",
+       "\n",
+       "       [[-3.34112738e-05, -1.13061478e-03, -2.34585186e-03, ...,\n",
+       "                     nan,             nan,             nan]]],\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0002779 0.00123 ... 0.0 0.0</div><input id='attrs-84b34193-1763-4874-9e7f-5ebe1ef1093f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84b34193-1763-4874-9e7f-5ebe1ef1093f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77de0588-a2e3-4ea8-8183-f2089e5f9c73' class='xr-var-data-in' type='checkbox'><label for='data-77de0588-a2e3-4ea8-8183-f2089e5f9c73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.77920655e-04,  1.22966967e-03,  1.45653449e-03, ...,\n",
+       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
+       "\n",
+       "       [[-5.08991980e-05,  3.11717099e-06, -1.25777024e-05, ...,\n",
+       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
+       "\n",
+       "       [[ 1.47129060e-04,  2.02183452e-04,  1.31326051e-05, ...,\n",
+       "         -1.31326051e-05, -2.02183452e-04, -1.47129060e-04]],\n",
+       "\n",
+       "       [[ 1.31017148e-18, -2.90292519e-04, -1.28964300e-03, ...,\n",
+       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]],\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0 8.0 6.0 12.0</div><input id='attrs-065376e8-2433-4523-9d8e-180c409dc855' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-065376e8-2433-4523-9d8e-180c409dc855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6952267-584f-4c92-8e74-63f9dece4db1' class='xr-var-data-in' type='checkbox'><label for='data-b6952267-584f-4c92-8e74-63f9dece4db1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[ 8.],\n",
+       "       [ 8.],\n",
+       "       [ 6.],\n",
+       "       [12.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 4.0 2.0 1.0</div><input id='attrs-3eafadcd-5552-4f6d-9f58-158761e97d15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3eafadcd-5552-4f6d-9f58-158761e97d15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98037233-e32a-468f-8b01-0897ad886f8c' class='xr-var-data-in' type='checkbox'><label for='data-98037233-e32a-468f-8b01-0897ad886f8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
+       "       [4.],\n",
+       "       [2.],\n",
+       "       [1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>config_xml</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U100225</div><div class='xr-var-preview xr-preview'>&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;u...</div><input id='attrs-f6f4376b-acb7-43da-83da-7e649ee645f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6f4376b-acb7-43da-83da-7e649ee645f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a41541d-7255-4e93-b5b6-eaf18a9c8c15' class='xr-var-data-in' type='checkbox'><label for='data-9a41541d-7255-4e93-b5b6-eaf18a9c8c15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;\\n&lt;Configuration&gt;\\n    &lt;Header Copyright=&quot;Copyright(c) Kongsberg Maritime AS, Norway&quot; ApplicationName=&quot;&quot; Version=&quot;21.15.0.0&quot; FileFormatVersion=&quot;1.27&quot; TimeBias=&quot;0&quot; /&gt;\\n    &lt;ActivePingMode Mode=&quot;Direct&quot; /&gt;\\n    &lt;Transceivers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747015&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747015&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6607&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:07&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.102&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747015&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 500W CH2: 503W CH3: 489W CH4: 500W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;1&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747015-15 ES70-7CD_ES&quot; LogicalChannelID=&quot;WBT 747015-15 ES70-7CD&quot; ChannelIdShort=&quot;ES70-7CD Serial No: 134&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;0.000128;0.000256;0.000512;0.001024;0.002048&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES70-7CD&quot; SerialNumber=&quot;134&quot; Frequency=&quot;70000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.59;27;27&quot; SaCorrection=&quot;0;0;-0.02;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0799999982118607&quot; AngleOffsetAthwartship=&quot;-0.0599999986588955&quot; BeamWidthAlongship=&quot;6.96000003814697&quot; BeamWidthAthwartship=&quot;6.86999988555908&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55000&quot; Gain=&quot;20.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;9.33&quot; BeamWidthAthwartship=&quot;9.5&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;0.35&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55480&quot; Gain=&quot;22.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.67&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55961&quot; Gain=&quot;24.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.3&quot; BeamWidthAthwartship=&quot;8.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56441&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;8.2&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56922&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.09&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57402&quot; Gain=&quot;26.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.21&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57883&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.12&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58363&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58844&quot; Gain=&quot;26.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.05&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59324&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.15&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59805&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.17&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60285&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;7.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60766&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.14&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61246&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61727&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;7.9&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62207&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.85&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62688&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.72&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63168&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.81&quot; BeamWidthAthwartship=&quot;7.81&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63649&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64129&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64610&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.73&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65090&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65571&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66051&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66532&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67012&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.29&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67492&quot; Gain=&quot;26.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.27&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67973&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68453&quot; Gain=&quot;27.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68934&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;6.9&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69414&quot; Gain=&quot;27.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69895&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70375&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.89&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70856&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.64&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71336&quot; Gain=&quot;27.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.76&quot; AngleOffsetAlongship=&quot;-0.31&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71817&quot; Gain=&quot;27.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72297&quot; Gain=&quot;27.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.71&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72778&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.75&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73258&quot; Gain=&quot;27.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73739&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74219&quot; Gain=&quot;27.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74700&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75180&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75661&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76141&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76622&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.19&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77102&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77583&quot; Gain=&quot;28.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.36&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78063&quot; Gain=&quot;28.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78544&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79024&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.28&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79505&quot; Gain=&quot;27.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79985&quot; Gain=&quot;27.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.26&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.24&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80465&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80946&quot; Gain=&quot;27.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.17&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81426&quot; Gain=&quot;27.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81907&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82387&quot; Gain=&quot;27.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82868&quot; Gain=&quot;27.41&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83348&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83829&quot; Gain=&quot;27.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.72&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84309&quot; Gain=&quot;27.33&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;5.85&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84790&quot; Gain=&quot;27.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.9&quot; BeamWidthAthwartship=&quot;5.91&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;85000&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.19&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747022&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747022&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660e&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0E&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.104&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747022&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 508W CH2: 499W CH3: 488W CH4: 501W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;2&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747022-15 ES120-7CD_ES&quot; LogicalChannelID=&quot;WBT 747022-15 ES120-7CD&quot; ChannelIdShort=&quot;ES120-7CD Serial No: 146&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES120-7CD&quot; SerialNumber=&quot;146&quot; Frequency=&quot;120000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.2;27;27&quot; SaCorrection=&quot;0;0;-0.4;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;-0.00999999977648258&quot; BeamWidthAlongship=&quot;7.26000022888184&quot; BeamWidthAthwartship=&quot;7.28000020980835&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96246&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;8.18&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96727&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.08&quot; BeamWidthAthwartship=&quot;8.11&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97207&quot; Gain=&quot;26.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.97&quot; BeamWidthAthwartship=&quot;7.74&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97688&quot; Gain=&quot;26.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.64&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98168&quot; Gain=&quot;26.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98649&quot; Gain=&quot;26.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99129&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99610&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100090&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.51&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100571&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101051&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.47&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101532&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102012&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102492&quot; Gain=&quot;26.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102973&quot; Gain=&quot;26.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103453&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103934&quot; Gain=&quot;26.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104414&quot; Gain=&quot;26.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.38&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104895&quot; Gain=&quot;26.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.41&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105375&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105856&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106336&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106817&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107297&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107778&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108258&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.23&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108739&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.27&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109219&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109700&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.21&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110180&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.25&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110661&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.28&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111141&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.11&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111622&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112102&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.05&quot; BeamWidthAthwartship=&quot;7.12&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112583&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.2&quot; BeamWidthAthwartship=&quot;7.07&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119309&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119790&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120270&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120751&quot; Gain=&quot;26.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121231&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121712&quot; Gain=&quot;26.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122192&quot; Gain=&quot;27.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122673&quot; Gain=&quot;27.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123153&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123634&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124114&quot; Gain=&quot;27.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.47&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124595&quot; Gain=&quot;27.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125075&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125556&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126036&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126517&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126997&quot; Gain=&quot;27.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.21&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127477&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127958&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128438&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128919&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129399&quot; Gain=&quot;28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129880&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.31&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130360&quot; Gain=&quot;28.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130841&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145255&quot; Gain=&quot;29.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145736&quot; Gain=&quot;29.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.52&quot; BeamWidthAthwartship=&quot;5.59&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146216&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146697&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147177&quot; Gain=&quot;29.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.49&quot; BeamWidthAthwartship=&quot;5.47&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147658&quot; Gain=&quot;29.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.4&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148138&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.18&quot; BeamWidthAthwartship=&quot;5.45&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148619&quot; Gain=&quot;29.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149099&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149580&quot; Gain=&quot;29.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150060&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.47&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150541&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151021&quot; Gain=&quot;29.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.25&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151502&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151982&quot; Gain=&quot;29.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.26&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152462&quot; Gain=&quot;29.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152943&quot; Gain=&quot;29.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.19&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153423&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153904&quot; Gain=&quot;29.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154384&quot; Gain=&quot;29.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.27&quot; BeamWidthAthwartship=&quot;5.29&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154865&quot; Gain=&quot;30.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155345&quot; Gain=&quot;30.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155826&quot; Gain=&quot;29.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.24&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156306&quot; Gain=&quot;30.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.2&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156787&quot; Gain=&quot;30.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157267&quot; Gain=&quot;30.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.15&quot; BeamWidthAthwartship=&quot;5.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157748&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.13&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158228&quot; Gain=&quot;30.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.21&quot; BeamWidthAthwartship=&quot;5.16&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158709&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.14&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159189&quot; Gain=&quot;30.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.11&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159670&quot; Gain=&quot;30.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.04&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160150&quot; Gain=&quot;30.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.12&quot; BeamWidthAthwartship=&quot;5.06&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160631&quot; Gain=&quot;30.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.06&quot; BeamWidthAthwartship=&quot;5.01&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161111&quot; Gain=&quot;30.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161592&quot; Gain=&quot;30.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90000&quot; Gain=&quot;21.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.82&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90480&quot; Gain=&quot;21.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.57&quot; BeamWidthAthwartship=&quot;8.48&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90961&quot; Gain=&quot;21.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.33&quot; BeamWidthAthwartship=&quot;8.59&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91441&quot; Gain=&quot;21.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.37&quot; BeamWidthAthwartship=&quot;8.56&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91922&quot; Gain=&quot;22.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.23&quot; BeamWidthAthwartship=&quot;8.87&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92402&quot; Gain=&quot;22.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.54&quot; BeamWidthAthwartship=&quot;8.31&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92883&quot; Gain=&quot;23.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.6&quot; BeamWidthAthwartship=&quot;8.45&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93363&quot; Gain=&quot;23.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.16&quot; BeamWidthAthwartship=&quot;8.58&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93844&quot; Gain=&quot;24.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.11&quot; BeamWidthAthwartship=&quot;8.34&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94324&quot; Gain=&quot;24.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.14&quot; BeamWidthAthwartship=&quot;8.55&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94805&quot; Gain=&quot;25.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95285&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.03&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95766&quot; Gain=&quot;25.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113063&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.92&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113544&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114024&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.91&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114505&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.87&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114985&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.78&quot; BeamWidthAthwartship=&quot;7.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115465&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115946&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.76&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116426&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.65&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116907&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117387&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.61&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117868&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118348&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118829&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131321&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131802&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132282&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.06&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132763&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.03&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133243&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133724&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134204&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;6.03&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134685&quot; Gain=&quot;28.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135165&quot; Gain=&quot;28.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135646&quot; Gain=&quot;28.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136126&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136607&quot; Gain=&quot;28.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.83&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137087&quot; Gain=&quot;29.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137568&quot; Gain=&quot;29.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.68&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138048&quot; Gain=&quot;29.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.77&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138529&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.78&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139009&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.73&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139489&quot; Gain=&quot;29.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.7&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139970&quot; Gain=&quot;29.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.71&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140450&quot; Gain=&quot;29.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.55&quot; BeamWidthAthwartship=&quot;5.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140931&quot; Gain=&quot;29.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.59&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141411&quot; Gain=&quot;29.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.61&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141892&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.42&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142372&quot; Gain=&quot;29.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.63&quot; BeamWidthAthwartship=&quot;5.69&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142853&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143333&quot; Gain=&quot;29.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143814&quot; Gain=&quot;29.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.57&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144294&quot; Gain=&quot;29.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.55&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144775&quot; Gain=&quot;29.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.69&quot; BeamWidthAthwartship=&quot;5.71&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162072&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.01&quot; BeamWidthAthwartship=&quot;5.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162553&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.97&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163033&quot; Gain=&quot;29.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.87&quot; BeamWidthAthwartship=&quot;4.89&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163514&quot; Gain=&quot;29.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.91&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163994&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164474&quot; Gain=&quot;29.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.9&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164955&quot; Gain=&quot;29.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165435&quot; Gain=&quot;28.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.84&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165916&quot; Gain=&quot;28.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.78&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166396&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.72&quot; BeamWidthAthwartship=&quot;4.76&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166877&quot; Gain=&quot;28.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.64&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167357&quot; Gain=&quot;27.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.71&quot; BeamWidthAthwartship=&quot;4.72&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167838&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.66&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168318&quot; Gain=&quot;27.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.67&quot; BeamWidthAthwartship=&quot;4.64&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168799&quot; Gain=&quot;27.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.65&quot; BeamWidthAthwartship=&quot;4.67&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169279&quot; Gain=&quot;27.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169760&quot; Gain=&quot;26.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.8&quot; BeamWidthAthwartship=&quot;4.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747019&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747019&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660b&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0B&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.101&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747019&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 511W CH2: 500W CH3: 506W CH4: 486W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;3&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747019-15 ES200-7CD_ES&quot; LogicalChannelID=&quot;WBT 747019-15 ES200-7CD&quot; ChannelIdShort=&quot;ES200-7CD Serial No: 166&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES200-7CD&quot; SerialNumber=&quot;166&quot; Frequency=&quot;200000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;26;26;27.48;27.33;26&quot; SaCorrection=&quot;0;0;-0.26;-0.01;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;0.00999999977648258&quot; AngleOffsetAthwartship=&quot;0.00999999977648258&quot; BeamWidthAlongship=&quot;6.78999996185303&quot; BeamWidthAthwartship=&quot;6.84999990463257&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;180900&quot; Gain=&quot;25.97&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;181891&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;182882&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;183873&quot; Gain=&quot;25.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.07&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;184864&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;185855&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.33&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;186846&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;187837&quot; Gain=&quot;25.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;188828&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;189819&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;190810&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;191801&quot; Gain=&quot;26.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;192792&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.06&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;193783&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;6.8&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;194774&quot; Gain=&quot;26.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;195765&quot; Gain=&quot;26.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;196756&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;197747&quot; Gain=&quot;27.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;198738&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;199729&quot; Gain=&quot;27.31&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;200720&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;201711&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;202702&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;203693&quot; Gain=&quot;27.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;204684&quot; Gain=&quot;27.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;215585&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.23&quot; BeamWidthAthwartship=&quot;6.27&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;216576&quot; Gain=&quot;28.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;217567&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;218558&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;219549&quot; Gain=&quot;28.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;220540&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.16&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;229459&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.06&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;230450&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;231441&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.96&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;232432&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;233423&quot; Gain=&quot;28.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.87&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;234414&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.87&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;235405&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;236396&quot; Gain=&quot;28.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;5.98&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;237387&quot; Gain=&quot;28.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;238378&quot; Gain=&quot;28.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;5.93&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;239369&quot; Gain=&quot;28.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;252252&quot; Gain=&quot;28.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;253243&quot; Gain=&quot;28.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.32&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;254234&quot; Gain=&quot;28.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;255225&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;256216&quot; Gain=&quot;28.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.31&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;257207&quot; Gain=&quot;28.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;258198&quot; Gain=&quot;28.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.35&quot; BeamWidthAthwartship=&quot;5.38&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;259189&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;260000&quot; Gain=&quot;28.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.41&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.9&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170990&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.92&quot; BeamWidthAthwartship=&quot;8.08&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;171981&quot; Gain=&quot;25.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.86&quot; BeamWidthAthwartship=&quot;8.01&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;172972&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.79&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;173963&quot; Gain=&quot;26.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.66&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;174954&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;175945&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.67&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;176936&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;177927&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;178918&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.57&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;179909&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.55&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;205675&quot; Gain=&quot;27.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;206666&quot; Gain=&quot;27.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;207657&quot; Gain=&quot;27.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.34&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;208648&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;209639&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.35&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;210630&quot; Gain=&quot;27.87&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;211621&quot; Gain=&quot;27.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;212612&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;213603&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;214594&quot; Gain=&quot;28.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;221531&quot; Gain=&quot;28.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.21&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;222522&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.07&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;223513&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;224504&quot; Gain=&quot;28.09&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;247297&quot; Gain=&quot;28.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;248288&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;249279&quot; Gain=&quot;28.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.51&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;250270&quot; Gain=&quot;28.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.44&quot; BeamWidthAthwartship=&quot;5.48&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;251261&quot; Gain=&quot;28.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.43&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747008&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747008&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6600&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:00&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.103&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747008&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 506W CH2: 490W CH3: 490W CH4: 498W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;4&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747008-15 ES333-7CD_ES&quot; LogicalChannelID=&quot;WBT 747008-15 ES333-7CD&quot; ChannelIdShort=&quot;ES333-7CD Serial No: 220&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES333-7CD&quot; SerialNumber=&quot;220&quot; Frequency=&quot;333000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;25;25;25;17.57;25&quot; SaCorrection=&quot;0;0;0;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;0.0700000002980232&quot; BeamWidthAlongship=&quot;6.73000001907349&quot; BeamWidthAthwartship=&quot;6.76999998092651&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;280000&quot; Gain=&quot;24.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.99&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;281001&quot; Gain=&quot;24.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;282002&quot; Gain=&quot;24.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.91&quot; BeamWidthAthwartship=&quot;7.85&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;290010&quot; Gain=&quot;25.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.67&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;291011&quot; Gain=&quot;25.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.77&quot; BeamWidthAthwartship=&quot;7.86&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;292012&quot; Gain=&quot;25.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;293013&quot; Gain=&quot;25.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;311031&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;312032&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;313033&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.34&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;314034&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;315035&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;316036&quot; Gain=&quot;25.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.36&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;317037&quot; Gain=&quot;25.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.33&quot; BeamWidthAthwartship=&quot;7.42&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;318038&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.16&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;319039&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;320040&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;321041&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;322042&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;323043&quot; Gain=&quot;25.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.04&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;324044&quot; Gain=&quot;25.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;325045&quot; Gain=&quot;25.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.26&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;326046&quot; Gain=&quot;25.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.03&quot; BeamWidthAthwartship=&quot;7.15&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;327047&quot; Gain=&quot;25.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;328048&quot; Gain=&quot;25.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;7.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;329049&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.01&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;330050&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;331051&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.93&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;332052&quot; Gain=&quot;25.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.8&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;333053&quot; Gain=&quot;25.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.87&quot; BeamWidthAthwartship=&quot;7.09&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;334054&quot; Gain=&quot;25.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.93&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;335055&quot; Gain=&quot;25.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;336056&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;337057&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;338058&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;339059&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;340060&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;341061&quot; Gain=&quot;26.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;342062&quot; Gain=&quot;26.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.47&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;343063&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;344064&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.68&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;345065&quot; Gain=&quot;26.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.55&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;346066&quot; Gain=&quot;26.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;347067&quot; Gain=&quot;26.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;348068&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;349069&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;350070&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;351071&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;352072&quot; Gain=&quot;26.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;353073&quot; Gain=&quot;26.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.73&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;354074&quot; Gain=&quot;27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;355075&quot; Gain=&quot;27.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;373093&quot; Gain=&quot;27.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;374094&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;375095&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.17&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;376096&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;377097&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;378098&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;379099&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;380000&quot; Gain=&quot;27.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.97&quot; BeamWidthAthwartship=&quot;5.99&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;283003&quot; Gain=&quot;24.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;284004&quot; Gain=&quot;25.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;285005&quot; Gain=&quot;25.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.83&quot; BeamWidthAthwartship=&quot;7.93&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;286006&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.8&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;287007&quot; Gain=&quot;25.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;288008&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;289009&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.69&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;294014&quot; Gain=&quot;25.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.6&quot; BeamWidthAthwartship=&quot;7.65&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;295015&quot; Gain=&quot;25.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.78&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;296016&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.55&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;297017&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.64&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;298018&quot; Gain=&quot;25.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;299019&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;300020&quot; Gain=&quot;25.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;301021&quot; Gain=&quot;25.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;302022&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;303023&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.49&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;304024&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.5&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;305025&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;306026&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.42&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;307027&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;308028&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;309029&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.37&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;310030&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.4&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;356076&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;357077&quot; Gain=&quot;27.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;358078&quot; Gain=&quot;27.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;359079&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;360080&quot; Gain=&quot;27.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;361081&quot; Gain=&quot;27.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.39&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;362082&quot; Gain=&quot;27.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;363083&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.33&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;364084&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;365085&quot; Gain=&quot;27.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.25&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;366086&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;367087&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;368088&quot; Gain=&quot;27.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;369089&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.15&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;370090&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.1&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;371091&quot; Gain=&quot;27.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.13&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;372092&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n    &lt;/Transceivers&gt;\\n    &lt;Transducers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transducer TransducerName=&quot;ES70-7CD&quot; TransducerSerialNumber=&quot;134&quot; TransducerCustomName=&quot;ES70-7CD Serial No: 134&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES120-7CD&quot; TransducerSerialNumber=&quot;146&quot; TransducerCustomName=&quot;ES120-7CD Serial No: 146&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES200-7CD&quot; TransducerSerialNumber=&quot;166&quot; TransducerCustomName=&quot;ES200-7CD Serial No: 166&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES333-7CD&quot; TransducerSerialNumber=&quot;220&quot; TransducerCustomName=&quot;ES333-7CD Serial No: 220&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n    &lt;/Transducers&gt;\\n    &lt;ConfiguredSensors MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Sensor Name=&quot;GPS From LAN Port 2 GPS&quot; Type=&quot;GPS&quot; Port=&quot;Lan Port 3&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;GLL from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GLL&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Geographical.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Global.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;RMC from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;RMC&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Specific.PositionSpeedCourse&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; 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Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;ZDA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;ZDA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.TimeInfo&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;TimeInfo&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;Annotation From LAN Port 3 Annotation&quot; Type=&quot;Annotation&quot; Port=&quot;Lan Port 4&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;Annotation from Annotation From LAN Port 3 Annotation&quot; SensorType=&quot;Annotation&quot; Type=&quot;Annotation&quot; SubscriptionPath=&quot;Annotation From LAN Port 3 Annotation@Annotation.Text&quot; 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+       "      dtype=&#x27;&lt;U100225&#x27;)</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
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+      "text/plain": [
+       "<EchoData: standardized raw data from Internal Memory>\n",
+       "Top-level: contains metadata about the SONAR-netCDF4 file format.\n",
+       "├── Environment: contains information relevant to acoustic propagation through water.\n",
+       "├── Platform: contains information about the platform on which the sonar is installed.\n",
+       "│   └── NMEA: contains information specific to the NMEA protocol.\n",
+       "├── Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.\n",
+       "├── Sonar: contains sonar system metadata and sonar beam groups.\n",
+       "│   └── Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.\n",
+       "└── Vendor_specific: contains vendor-specific information about the sonar and the data."
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ed_ts = ep.open_raw(raw_file_TS, sonar_model=\"EK80\")\n",
+    "ed_ts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f13c5766",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<xarray.DataArray 'channel_all' (channel_all: 4)> Size: 416B\n",
+      "array(['WBT 747008-15 ES333-7CD_ES', 'WBT 747015-15 ES70-7CD_ES',\n",
+      "       'WBT 747019-15 ES200-7CD_ES', 'WBT 747022-15 ES120-7CD_ES'],\n",
+      "      dtype='<U26')\n",
+      "Coordinates:\n",
+      "  * channel_all  (channel_all) <U26 416B 'WBT 747008-15 ES333-7CD_ES' ... 'WB...\n",
+      "Attributes:\n",
+      "    long_name:  Vendor channel ID\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ed_ts['Sonar']['channel_all'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f6e20948",
+   "metadata": {},
+   "source": [
+    "We select the same ping and frequency as those used by Andersen et al. (2024)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "e71a1ea3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tsf_channel = \"WBT 747022-15 ES120-7CD_ES\"\n",
+    "\n",
+    "# CRIMAC uses 1-based ping numbering.\n",
+    "# Python/xarray uses 0-based indexing.\n",
+    "crimac_ping_number = 510\n",
+    "tsf_ping_index = crimac_ping_number - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "22ffb426",
+   "metadata": {},
+   "source": [
+    "We initialise a `CalibrateEK80`  object to access the internal calibration data and helper functions used in the step-by-step TS spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9aaa027a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cal_obj = CalibrateEK80(\n",
+    "    ed_ts,\n",
+    "    env_params=None,\n",
+    "    cal_params=None,\n",
+    "    ecs_file=None,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "55bfebec",
+   "metadata": {},
+   "source": [
+    "We then load the reference outputs previously exported from the original CRIMAC processing chain. These results provide the benchmark against which the echopype implementation is compared."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "5cd9732a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "y_rx_nu (4, 2356) complex128\n",
+      "r_n (2356,) float64\n",
+      "f_m (1000,) float64\n",
+      "alpha_m (1000,) float64\n",
+      "lambda_m (1000,) float64\n",
+      "y_tx_n (3071,) float64\n",
+      "y_mf_n (516,) complex128\n",
+      "y_mf_auto_n (1031,) complex128\n",
+      "tau_eff () float64\n",
+      "y_pc_nu (4, 2356) complex128\n",
+      "y_pc_n (2356,) complex128\n",
+      "p_rx_e_n (2356,) float64\n",
+      "theta_n (2356,) float64\n",
+      "phi_n (2356,) float64\n",
+      "Sp_full_n (2356,) float64\n",
+      "Sp_full_r (2356,) float64\n",
+      "Sp_target_n (168,) float64\n",
+      "Sp_target_r (168,) float64\n",
+      "dum_r (168,) float64\n",
+      "dum_theta (168,) float64\n",
+      "dum_phi (168,) float64\n",
+      "r_t () float64\n",
+      "theta_t () float64\n",
+      "phi_t () float64\n",
+      "y_pc_t_n (168,) complex128\n",
+      "y_mf_auto_red_n (168,) complex128\n",
+      "Y_pc_t_m (1000,) complex128\n",
+      "Y_mf_auto_red_m (1000,) complex128\n",
+      "Y_tilde_pc_t_m (1000,) complex128\n",
+      "P_rx_e_t_m (1000,) float64\n",
+      "g_theta_phi_m (1000,) float64\n",
+      "TS_m (1000,) float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "ref_ts = np.load(ref_file_TS)\n",
+    "\n",
+    "for k in ref_ts.keys():\n",
+    "    print(k, ref_ts[k].shape, ref_ts[k].dtype)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc617532",
+   "metadata": {},
+   "source": [
+    "We define a few helper functions that will be used throughout the validation workflow."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d8840697",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def scalar_param(da, channel=None, ping_idx=None):\n",
+    "    \"\"\"Select scalar from a possibly channel/ping-dependent DataArray.\"\"\"\n",
+    "    if channel is not None and \"channel\" in da.dims:\n",
+    "        da = da.sel(channel=channel)\n",
+    "    if ping_idx is not None and \"ping_time\" in da.dims:\n",
+    "        da = da.isel(ping_time=ping_idx)\n",
+    "    return float(da)\n",
+    "\n",
+    "\n",
+    "def db20(x):\n",
+    "    return 20 * np.log10(np.abs(x))\n",
+    "\n",
+    "\n",
+    "def db10(x):\n",
+    "    return 10 * np.log10(np.abs(x))\n",
+    "\n",
+    "\n",
+    "def compare_summary(name, ref, ep):\n",
+    "    ref = np.asarray(ref)\n",
+    "    ep = np.asarray(ep)\n",
+    "\n",
+    "    n = min(ref.size, ep.size)\n",
+    "    ref = ref.reshape(-1)[:n]\n",
+    "    ep = ep.reshape(-1)[:n]\n",
+    "\n",
+    "    diff = ep - ref\n",
+    "\n",
+    "    return {\n",
+    "        \"variable\": name,\n",
+    "        \"n\": n,\n",
+    "        \"CRIMAC mean\": np.nanmean(ref),\n",
+    "        \"echopype mean\": np.nanmean(ep),\n",
+    "        \"mean diff\": np.nanmean(diff),\n",
+    "        \"median diff\": np.nanmedian(diff),\n",
+    "        \"RMSE\": np.sqrt(np.nanmean(diff**2)),\n",
+    "        \"max abs diff\": np.nanmax(np.abs(diff)),\n",
+    "    }\n",
+    "\n",
+    "\n",
+    "def compare_curve(\n",
+    "    x_ref,\n",
+    "    y_ref,\n",
+    "    x_ep,\n",
+    "    y_ep,\n",
+    "    title,\n",
+    "    xlabel,\n",
+    "    ylabel,\n",
+    "    xlim=None,\n",
+    "    ylim=None,\n",
+    "):\n",
+    "    plt.figure(figsize=(8, 3.5))\n",
+    "    plt.plot(x_ref, y_ref, label=\"CRIMAC\")\n",
+    "    plt.plot(x_ep, y_ep, \"--\", label=\"echopype\", alpha=0.85)\n",
+    "\n",
+    "    if xlim is not None:\n",
+    "        plt.xlim(*xlim)\n",
+    "    if ylim is not None:\n",
+    "        plt.ylim(*ylim)\n",
+    "\n",
+    "    plt.xlabel(xlabel)\n",
+    "    plt.ylabel(ylabel)\n",
+    "    plt.title(title)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91bcb6b2",
+   "metadata": {},
+   "source": [
+    "### Rebuild the transmit signal and matched filter\n",
+    "\n",
+    "We reconstruct the broadband transmit signal from the EK80 filter coefficients, then compute its matched-filter autocorrelation. This reproduces the signal used by CRIMAC for pulse compression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "409937dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype y_mf_n: (516,)\n",
+      "CRIMAC y_mf_n  : (516,)\n",
+      "echopype y_mf_auto_n: (1031,)\n",
+      "CRIMAC y_mf_auto_n  : (1031,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "tx_coeff = get_filter_coeff(cal_obj.vend)\n",
+    "fs = cal_obj.cal_params[\"receiver_sampling_frequency\"]\n",
+    "\n",
+    "tx, tx_time = get_transmit_signal(\n",
+    "    cal_obj.beam,\n",
+    "    tx_coeff,\n",
+    "    cal_obj.waveform_mode,\n",
+    "    fs,\n",
+    "    cal_obj.drop_last_hanning_zero,\n",
+    ")\n",
+    "\n",
+    "y_mf_n = tx[tsf_channel]\n",
+    "\n",
+    "y_mf_auto_n = np.convolve(\n",
+    "    y_mf_n,\n",
+    "    np.conj(y_mf_n[::-1]),\n",
+    "    mode=\"full\",\n",
+    ") / np.linalg.norm(y_mf_n) ** 2\n",
+    "\n",
+    "print(\"echopype y_mf_n:\", y_mf_n.shape)\n",
+    "print(\"CRIMAC y_mf_n  :\", ref_ts[\"y_mf_n\"].shape)\n",
+    "\n",
+    "print(\"echopype y_mf_auto_n:\", y_mf_auto_n.shape)\n",
+    "print(\"CRIMAC y_mf_auto_n  :\", ref_ts[\"y_mf_auto_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "966cd986",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, figsize=(11, 3))\n",
+    "\n",
+    "ax[0].plot(np.abs(ref_ts[\"y_mf_n\"]), label=\"CRIMAC\")\n",
+    "ax[0].plot(np.abs(y_mf_n), \"--\", label=\"echopype\")\n",
+    "ax[0].set_title(\"Matched filter\")\n",
+    "ax[0].set_xlabel(\"Sample\")\n",
+    "ax[0].set_ylabel(r\"$|y_{mf}(n)|$\")\n",
+    "ax[0].grid(True)\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(np.abs(ref_ts[\"y_mf_auto_n\"]), label=\"CRIMAC\")\n",
+    "ax[1].plot(np.abs(y_mf_auto_n), \"--\", label=\"echopype\")\n",
+    "ax[1].set_title(\"Matched-filter autocorrelation\")\n",
+    "ax[1].set_xlabel(\"Sample\")\n",
+    "ax[1].set_ylabel(r\"$|y_{mf,auto}(n)|$\")\n",
+    "ax[1].grid(True)\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b99f5cb",
+   "metadata": {},
+   "source": [
+    "### Apply pulse compression\n",
+    "\n",
+    "We apply pulse compression to the complex sector signals using the reconstructed matched filter. The resulting `pc` array contains the pulse-compressed signal for each transducer sector, while `pc_avg` is the sector-averaged pulse-compressed signal used for the TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "cbb9344f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype y_pc_n: (2356,)\n",
+      "CRIMAC y_pc_n  : (2356,)\n",
+      "echopype r_n   : (2356,)\n",
+      "CRIMAC r_n     : (2356,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import (\n",
+    "    _get_pulse_compressed_signal,\n",
+    "    _get_average_signal,\n",
+    ")\n",
+    "\n",
+    "pc = _get_pulse_compressed_signal(\n",
+    "    beam=cal_obj.beam,\n",
+    "    matched_filter=tx,\n",
+    ")\n",
+    "\n",
+    "pc_avg = _get_average_signal(pc)\n",
+    "\n",
+    "pc_ping = pc.sel(channel=tsf_channel).isel(ping_time=tsf_ping_index)\n",
+    "pc_avg_ping = pc_avg.sel(channel=tsf_channel).isel(ping_time=tsf_ping_index)\n",
+    "\n",
+    "r_ping = (\n",
+    "    cal_obj.range_meter\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(ping_time=tsf_ping_index)\n",
+    ")\n",
+    "\n",
+    "valid = np.isfinite(pc_avg_ping) & np.isfinite(r_ping)\n",
+    "\n",
+    "pc_ping = pc_ping.where(valid, drop=True)\n",
+    "pc_avg_ping = pc_avg_ping.where(valid, drop=True)\n",
+    "r_n = r_ping.where(valid, drop=True).values\n",
+    "\n",
+    "y_pc_n = pc_avg_ping.values\n",
+    "\n",
+    "print(\"echopype y_pc_n:\", y_pc_n.shape)\n",
+    "print(\"CRIMAC y_pc_n  :\", ref_ts[\"y_pc_n\"].shape)\n",
+    "print(\"echopype r_n   :\", r_n.shape)\n",
+    "print(\"CRIMAC r_n     :\", ref_ts[\"r_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "e8c17f15",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\lloyd\\AppData\\Local\\Temp\\ipykernel_13472\\1980613090.py:11: RuntimeWarning: divide by zero encountered in log10\n",
+      "  return 20 * np.log10(np.abs(x))\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"r_n\"],\n",
+    "    db20(ref_ts[\"y_pc_n\"]),\n",
+    "    r_n,\n",
+    "    db20(y_pc_n),\n",
+    "    title=\"Pulse-compressed averaged signal\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$|y_{pc}(n)|$ (dB)\",\n",
+    "    xlim=(3, 8),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a073555b",
+   "metadata": {},
+   "source": [
+    "check for above that we remove th surface values? (like safe_rang?) or why do we have the warning if not"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "94b88200",
+   "metadata": {},
+   "source": [
+    "### Convert pulse-compressed signals to received power\n",
+    "\n",
+    "We convert the sector-level pulse-compressed complex signals into received electrical power using the transducer and transceiver impedances. This reproduces the CRIMAC `p_rx_e_n` variable for the selected ping."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "97d6ab29",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "z_td_e: 75.0\n",
+      "z_rx_e: 5400.0\n",
+      "n_beams: 4\n",
+      "echopype p_rx_e_n: (2356,)\n",
+      "CRIMAC p_rx_e_n  : (2356,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "z_td_e = scalar_param(\n",
+    "    cal_obj.cal_params[\"impedance_transducer\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "z_rx_e = scalar_param(\n",
+    "    cal_obj.cal_params[\"impedance_transceiver\"],\n",
+    "    tsf_channel,\n",
+    "    None,\n",
+    ")\n",
+    "\n",
+    "n_beams = cal_obj.beam[\"beam\"].size\n",
+    "\n",
+    "from echopype.calibrate.ek80_complex import _compute_power_from_complex_signal\n",
+    "\n",
+    "p_rx_e_n = _compute_power_from_complex_signal(\n",
+    "    signal=pc_ping,\n",
+    "    z_et=z_td_e,\n",
+    "    z_er=z_rx_e,\n",
+    ").values\n",
+    "\n",
+    "print(\"z_td_e:\", z_td_e)\n",
+    "print(\"z_rx_e:\", z_rx_e)\n",
+    "print(\"n_beams:\", n_beams)\n",
+    "\n",
+    "print(\"echopype p_rx_e_n:\", p_rx_e_n.shape)\n",
+    "print(\"CRIMAC p_rx_e_n  :\", ref_ts[\"p_rx_e_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "53fa2d58",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"r_n\"],\n",
+    "    db10(ref_ts[\"p_rx_e_n\"]),\n",
+    "    r_n,\n",
+    "    db10(p_rx_e_n),\n",
+    "    title=\"Received electrical power\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$10\\log_{10}(p_{rx,e})$\",\n",
+    "    xlim=(3, 8),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14575fba",
+   "metadata": {},
+   "source": [
+    "### Reproduce the broadband point scattering strength (Sp)\n",
+    "\n",
+    "Using the received power, range, and calibration parameters, we reproduce the broadband point scattering strength (`Sp`) calculated by CRIMAC. This quantity is evaluated at the transducer centre frequency and is used to identify candidate single targets before computing the frequency-dependent TS spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "1b365099",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "sound_speed: 1485.4\n",
+      "absorption: 0.03770373022901242\n",
+      "transmit_power: 100.0\n",
+      "f_c: 130000.0\n",
+      "lambda_fc: 0.011426153846153846\n",
+      "gain_fc_db: 28.0375\n"
+     ]
+    }
+   ],
+   "source": [
+    "sound_speed = scalar_param(\n",
+    "    cal_obj.env_params[\"sound_speed\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "absorption = scalar_param(\n",
+    "    cal_obj.env_params[\"sound_absorption\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "transmit_power = scalar_param(\n",
+    "    cal_obj.beam[\"transmit_power\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "f_c = scalar_param(\n",
+    "    cal_obj.freq_center,\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "lambda_fc = sound_speed / f_c\n",
+    "\n",
+    "gain_fc_db = scalar_param(\n",
+    "    cal_obj.cal_params[\"gain_correction\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "g_0_fc = 10 ** (gain_fc_db / 10)\n",
+    "\n",
+    "r_n_safe = np.where(r_n > 0, r_n, 1e-20)\n",
+    "\n",
+    "Sp_n = (\n",
+    "    10 * np.log10(p_rx_e_n)\n",
+    "    + 40 * np.log10(r_n_safe)\n",
+    "    + 2 * absorption * r_n_safe\n",
+    "    - 10 * np.log10(\n",
+    "        transmit_power * lambda_fc**2 * g_0_fc**2 / (16 * np.pi**2)\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "print(\"sound_speed:\", sound_speed)\n",
+    "print(\"absorption:\", absorption)\n",
+    "print(\"transmit_power:\", transmit_power)\n",
+    "print(\"f_c:\", f_c)\n",
+    "print(\"lambda_fc:\", lambda_fc)\n",
+    "print(\"gain_fc_db:\", gain_fc_db)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e5132f50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"Sp_full_r\"],\n",
+    "    ref_ts[\"Sp_full_n\"],\n",
+    "    r_n,\n",
+    "    Sp_n,\n",
+    "    title=\"Point scattering strength Sp, full ping\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$S_p$ (dB re 1 m$^2$)\",\n",
+    "    xlim=(5.0, 6.6),\n",
+    "    ylim=(-200, 0),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "7d27cb81",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "lengths: 168 168\n",
+      "range first/last CRIMAC: 5.30584878660402 6.298095984098836\n",
+      "range first/last manual: 5.3058488 6.298096\n",
+      "Sp target RMSE: 0.3064048011908493\n",
+      "Sp target max: 1.8527138710007023\n"
+     ]
+    }
+   ],
+   "source": [
+    "i0 = int(np.argmin(np.abs(r_n - ref_ts[\"Sp_target_r\"][0])))\n",
+    "i1 = i0 + ref_ts[\"Sp_target_r\"].size\n",
+    "\n",
+    "compare_curve(\n",
+    "    ref_ts[\"Sp_target_r\"],\n",
+    "    ref_ts[\"Sp_target_n\"],\n",
+    "    r_n[i0:i1],\n",
+    "    Sp_n[i0:i1],\n",
+    "    title=\"Point scattering strength Sp, target window\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$S_p$ (dB re 1 m$^2$)\",\n",
+    ")\n",
+    "\n",
+    "diff = Sp_n[i0:i1] - ref_ts[\"Sp_target_n\"]\n",
+    "\n",
+    "print(\"lengths:\", ref_ts[\"Sp_target_n\"].size, Sp_n[i0:i1].size)\n",
+    "print(\"range first/last CRIMAC:\", ref_ts[\"Sp_target_r\"][0], ref_ts[\"Sp_target_r\"][-1])\n",
+    "print(\"range first/last manual:\", r_n[i0], r_n[i1 - 1])\n",
+    "print(\"Sp target RMSE:\", np.sqrt(np.nanmean(diff**2)))\n",
+    "print(\"Sp target max:\", np.nanmax(np.abs(diff)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "644e8175",
+   "metadata": {},
+   "source": [
+    "why do we have difference in the curves?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "d975c349",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mean: -0.03509303154669198\n",
+      "median: -0.005129335564895143\n",
+      "RMSE: 0.3064048011908493\n",
+      "max abs: 1.8527138710007023\n",
+      "95% abs: 0.7342241014215845\n",
+      "99% abs: 1.0939855293269973\n",
+      "max index: 24\n",
+      "range: 5.4484472\n",
+      "CRIMAC: -101.23159919223684\n",
+      "echopype: -103.08431306323754\n",
+      "diff: -1.8527138710007023\n"
+     ]
+    }
+   ],
+   "source": [
+    "diff = Sp_n[i0:i1] - ref_ts[\"Sp_target_n\"]\n",
+    "\n",
+    "print(\"mean:\", np.nanmean(diff))\n",
+    "print(\"median:\", np.nanmedian(diff))\n",
+    "print(\"RMSE:\", np.sqrt(np.nanmean(diff**2)))\n",
+    "print(\"max abs:\", np.nanmax(np.abs(diff)))\n",
+    "print(\"95% abs:\", np.nanpercentile(np.abs(diff), 95))\n",
+    "print(\"99% abs:\", np.nanpercentile(np.abs(diff), 99))\n",
+    "\n",
+    "imax = np.nanargmax(np.abs(diff))\n",
+    "print(\"max index:\", imax)\n",
+    "print(\"range:\", r_n[i0:i1][imax])\n",
+    "print(\"CRIMAC:\", ref_ts[\"Sp_target_n\"][imax])\n",
+    "print(\"echopype:\", Sp_n[i0:i1][imax])\n",
+    "print(\"diff:\", diff[imax])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "d6b32d7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 3))\n",
+    "plt.plot(r_n[i0:i1], diff)\n",
+    "plt.axhline(0, color=\"black\", linewidth=1)\n",
+    "plt.xlabel(\"Range (m)\")\n",
+    "plt.ylabel(\"echopype - CRIMAC (dB)\")\n",
+    "plt.title(\"Sp residual in target window\")\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c062de91",
+   "metadata": {},
+   "source": [
+    "### Get split-beam alongship and athwartship angles\n",
+    "\n",
+    "For split-beam EK80 data, the target position within the transducer beam is estimated from the phase differences between transducer sectors. Because this example uses FM complex data, the sector-level complex samples are first pulse-compressed, then combined into fore, aft, starboard, and port transducer halves.\n",
+    "\n",
+    "The alongship and athwartship angles are then computed following the CRIMAC broadband processing workflow. Phase differences between transducer halves are converted to physical angles using the calibrated angle sensitivities and the inverse-sine relationship described in Andersen et al. (2024). This approach reproduces the reference CRIMAC implementation used to generate the published broadband TS spectrum example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gamma_alongship: 24.916666666666664\n",
+      "gamma_athwartship: 24.916666666666664\n",
+      "theta shape: (2356,)\n",
+      "phi shape: (2356,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "gamma_alongship = scalar_param(\n",
+    "    cal_obj.cal_params[\"angle_sensitivity_alongship\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "gamma_athwartship = scalar_param(\n",
+    "    cal_obj.cal_params[\"angle_sensitivity_athwartship\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "from echopype.calibrate.ek80_complex import _get_splitbeam_angles\n",
+    "theta, phi = _get_splitbeam_angles(\n",
+    "    pc=pc_ping,\n",
+    "    gamma_alongship=gamma_alongship,\n",
+    "    gamma_athwartship=gamma_athwartship,\n",
+    ")\n",
+    "\n",
+    "print(\"gamma_alongship:\", gamma_alongship)\n",
+    "print(\"gamma_athwartship:\", gamma_athwartship)\n",
+    "print(\"theta shape:\", theta.shape)\n",
+    "print(\"phi shape:\", phi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "3ae46a66",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(2, 1, figsize=(8, 4), sharex=True)\n",
+    "\n",
+    "ax[0].plot(r_n, theta)\n",
+    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[0].grid(True)\n",
+    "\n",
+    "ax[1].plot(r_n, phi)\n",
+    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[1].set_xlabel(\"Range (m)\")\n",
+    "ax[1].grid(True)\n",
+    "\n",
+    "plt.xlim(3, 8)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ea9db6d",
+   "metadata": {},
+   "source": [
+    "Cmpare with Crimac"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "418f0ac8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "theta RMSE: 0.43174450157798355\n",
+      "theta max : 13.11178108969502\n",
+      "phi RMSE  : 0.9274489945255341\n",
+      "phi max   : 14.476222236380444\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare echopype CRIMAC-style angles against CRIMAC reference angles\n",
+    "\n",
+    "theta_np = np.asarray(theta)\n",
+    "phi_np = np.asarray(phi)\n",
+    "\n",
+    "n = min(theta_np.size, ref_ts[\"theta_n\"].size)\n",
+    "\n",
+    "theta_diff = theta_np[:n] - ref_ts[\"theta_n\"][:n]\n",
+    "phi_diff = phi_np[:n] - ref_ts[\"phi_n\"][:n]\n",
+    "\n",
+    "print(\"theta RMSE:\", np.sqrt(np.nanmean(theta_diff**2)))\n",
+    "print(\"theta max :\", np.nanmax(np.abs(theta_diff)))\n",
+    "print(\"phi RMSE  :\", np.sqrt(np.nanmean(phi_diff**2)))\n",
+    "print(\"phi max   :\", np.nanmax(np.abs(phi_diff)))\n",
+    "\n",
+    "fig, ax = plt.subplots(2, 1, figsize=(11, 4), sharex=True)\n",
+    "\n",
+    "ax[0].plot(r_n[:n], ref_ts[\"theta_n\"][:n], label=\"CRIMAC\")\n",
+    "ax[0].plot(r_n[:n], theta_np[:n], \"--\", label=\"echopype\")\n",
+    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(r_n[:n], ref_ts[\"phi_n\"][:n], label=\"CRIMAC\")\n",
+    "ax[1].plot(r_n[:n], phi_np[:n], \"--\", label=\"echopype\")\n",
+    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[1].set_xlabel(\"Range (m)\")\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "c095e6a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 4))\n",
+    "plt.plot(theta_np[:n] - ref_ts[\"theta_n\"][:n])\n",
+    "plt.title(\"theta difference\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(10, 4))\n",
+    "plt.plot(phi_np[:n] - ref_ts[\"phi_n\"][:n])\n",
+    "plt.title(\"phi difference\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ad45e65",
+   "metadata": {},
+   "source": [
+    "### Compare with echopype split-beam angle helper\n",
+    "\n",
+    "The CRIMAC workflow computes physical angles from pulse-compressed transducer halves using an inverse-sine relationship. Echopype also provides a generic split-beam angle helper through the consolidation module. In this section we compare the two implementations to assess whether they produce equivalent alongship and athwartship angle estimates for broadband EK80 data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "be119344",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "target_peak_idx: 975\n",
+      "range: 5.79306 5.7930599853739295\n",
+      "CRIMAC theta_t : 0.19805856629305635\n",
+      "echopype theta : 0.2555534398211754\n",
+      "theta diff     : 0.05749487352811905\n",
+      "CRIMAC phi_t   : 2.127909429160737\n",
+      "echopype phi   : 2.1099409547175005\n",
+      "phi diff       : -0.01796847444323646\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.consolidate.split_beam_angle import get_angle_complex_samples\n",
+    "from echopype.calibrate.ek80_complex import get_filter_coeff\n",
+    "\n",
+    "filter_coeff = get_filter_coeff(cal_obj.vend)\n",
+    "\n",
+    "pc_params = {\n",
+    "    **filter_coeff,\n",
+    "    \"receiver_sampling_frequency\": cal_obj.cal_params[\"receiver_sampling_frequency\"],\n",
+    "    \"drop_last_hanning_zero\": cal_obj.drop_last_hanning_zero,\n",
+    "}\n",
+    "\n",
+    "theta_ep, phi_ep = get_angle_complex_samples(\n",
+    "    ds_beam=cal_obj.beam.sel(channel=[tsf_channel]),\n",
+    "    angle_params=cal_obj.cal_params,\n",
+    "    pc_params=pc_params,\n",
+    ")\n",
+    "\n",
+    "theta_ep = (\n",
+    "    theta_ep\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(ping_time=tsf_ping_index)\n",
+    "    .dropna(\"range_sample\")\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "phi_ep = (\n",
+    "    phi_ep\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(ping_time=tsf_ping_index)\n",
+    "    .dropna(\"range_sample\")\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
+    "\n",
+    "print(\"target_peak_idx:\", target_peak_idx)\n",
+    "print(\"range:\", r_n[target_peak_idx], ref_ts[\"r_t\"])\n",
+    "\n",
+    "print(\"CRIMAC theta_t :\", ref_ts[\"theta_t\"])\n",
+    "print(\"echopype theta :\", theta_ep[target_peak_idx])\n",
+    "print(\"theta diff     :\", theta_ep[target_peak_idx] - ref_ts[\"theta_t\"])\n",
+    "\n",
+    "print(\"CRIMAC phi_t   :\", ref_ts[\"phi_t\"])\n",
+    "print(\"echopype phi   :\", phi_ep[target_peak_idx])\n",
+    "print(\"phi diff       :\", phi_ep[target_peak_idx] - ref_ts[\"phi_t\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "298f0ce9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Xxx9//KEy1NkhGThwoNkx/uzZs2r+fteuXRnu87PPPlPqBv4Nhuz633//VX8Db6Nz5844eDCjiyqz3Hv16qX+1tq1a+Ohhx5CTExMls/P/v370bdvX/V38++nn4DxOHJ63NawlJdzf8OGDar7zcfOjX+rLTALNz9/548//qhUH/y7qlWrpkYwaEZoYDyfK1asQNu2bdXt9OvXT11n2bJlyoiQz8e4ceMQGxtr02Nevny5ihTic8bXyfDhwzO8jvi38z5///139ZzztcK/cetWk2uuiW+++Ub9Tbx89OjRKomAt5kd8+bNU4+ZzxcX4L788kubHrMgCLb7rfB9xo37Qgnh0i4gNQlIjMb5GBeERiXAzdkJrWqlLyBX8HJDdV+tbDhUeQjQaRpQoU4RPmhBEATHRYruvJIYk/VGR1Cbr5sp2iyr6+WSF154QR0kffXVV6q45nz8XXfdpYpBcunSJVW8sVhZu3Ytdu/erWbhk5OTzbexbt06VTzx9LvvvlPFqKXagMUlC9W//vpLFVAskhnbZlmYs3B788031e+zoIyMjMTYsWPVZXXq1MGAAQPU47SEP/O2LeNpOKvPBYCdO3fCz88PI0aMMN8PC9PBgwdjzJgxOHDgABYuXKjy2x944IEsn5/x48crsz3eHv/2Z555Bq6urjY97pxgsd21a1dMmzZNjURwYzFpC/n9OxMTE/H666+rRQUuGpw5c0Y9l9bmoz///HNVxHMxgWMZlML/9NNPaoGD6hEuftgCi376MfAxr1mzRi2ksGhmpJ8lzz//PJ544gns27dPLWawsDdeb3yO6d3w8MMPq8u5yMHnPztYpPM2eT16QLz11lt48cUX1f9MEAT7wM9FfoZws/yMFByc89ss8rl1l7tlLV94uDpnuJohMQ+8HFn4j1EQBKEkkVbKiYiI4CCuOs1MXFxcWmBgoDq9gZd9st5+vDXjdd+olvV1vx2a8brv1rV+vVwQHR2d5uHhkbZly5YM50+ZMiVt3Lhxav/ZZ59Nq1u3blpiYqLV25g4cWJaQEBAWnJysvm82267Le2OO+5Q+8ePH1fP2+bNm82XX716Na1s2bJpixYtUj/PmzdPXWfbtm3m6xw5ckSdt337dvXzwoUL0ypUqJAWHx+vft63b19amTJl0s6cOaN+Xrdunbr+L7/8Yr6Na9euqfvh75IJEyak3XvvvRke/8aNG9OcnJys/+/S0tK8vb3T5s+fb/UyWx73yy+/nNa6desMz9fIkSPNP/fu3Tvt4YcfTrOVgvo7d+zYoW43Kioqw/2sXr3afJ23335bnXfq1CnzedOnT08bPHhwWl4ICQlRt3fw4EH1M/+X/HnOnDnm6xw+fFidx+eV8HU1bNiwDLczfvz4NF9fX/PPmZ/z2rVrp/30008Zfuf1119P69q1q9XHle37WRAEoTTx3Qh9bLHjm7Snf92fFvD0P2lvLQ284WrvLz+qLuN10i7tTUvb/X1aWmxYkTxkQRAER6slLZFOdwmETu40v2G3kGZzxvb999+bZb/sJlJOnl3nonnz5io73YAyc0OqzM6ii4uLkkAbUFrcuHFjdZkBr0O5swElwJQMG9ehJJvXWbJkifqZzvWUILMLbgk7xwYVK1bMcD/sVLMDb/m3siPMTis7vdZgZ3bq1Kmq0/7OO+/cIKvP6XEXFPn9O/fu3YuRI0cqeT4l5jR0I5YGhKRVq1bm/apVqypJN0cRLM+zlKVnB587ytj5+5Sm161bN8f75GuJGPdx7NgxdOrUKcP1M/9sSWhoqOrQT5kyJcPzQRPFzP9LQRDyDue4+X3BTWa6SwgpycBF01iXf1ezc3nHgPR57sxz3YFBkcDiScBfDwBB+wr38QqCIJQAip2RmsPw3OWsLyuTUZ6FJ09mc91M6x6PZJzhzQuGrJcy4Zo1a2a4zN3dXZ3aEqmWuSCn3Nu4bUunbkt4vqUs3Pi9zBjncUZwwoQJSlJO2TTlzbY6fhu3wcc0ffp0Nd+cGX9/f6u/S3k1C0U+R5xlfvnll/HLL78oWbQtj7swsfXvpMx70KBBauNsd5UqVVThy8KcsvOs/re8/ez+1zlx8803K/k85d41atRQv8fkgZzu0/ibsnrdZPUas/w93qflwg+xXCgSBCF/cAGX/g8kOjoaXl5e8pQ6OlcOqVluuPvimmc9nAo9e4NzuUGzGrroPhYchdQWLeAUdgYIPgTU0wu6giAIgm1I0Z1X3LyK/rpZ0KxZM1Vcs+Dq3bu31euw68jZV84L52VOj/fBedzt27ejW7du6jzGvR0/flwZWxnwOpz7NrqW7Ggyi5qdYwN2nFmk0QSLj4fFd2a2bdtmLqBp4Mb7MW6jXbt2am69QYMGufobOFfMjfPunC9m4W8U3bY87uzgYkJeukL5+Ts583316lXVuTdmyDOb1Nkb/s/ZiZ81a5ZSThDOmecW/o07duzIcF52j52deC4onT59Ws3nC4JQMHAxjItpxr5Qgua5a3fC7vMRarehXzllnJaZgIqe8HRzRmxiCsJ8GqMS/tZFuyAIgpArRF5eAqGsmIZVLCZZWFNuS9nxF198YTaZovmWYQ7G4oau4z/88IMqLm2hYcOGSsZMszAWWTTuolEbCyGeb8CCnjnqLM737NmDyZMno0uXLhmkwyzSed7TTz+til9rXXhmt9Ok69ChQ8rQp3Llyma3cP4ejdzork4JJP8Wmrvxfq0RFxen/n46eZ87d06ZeNEEzHKxwJbHnR2Ux/N36dzNQtjWrnF+/k4W6yz2aYDGYpSX0VStIKFzPccKZs+ejZMnTypTPkr3cwv/BsYS0bGcfxeLeCoQsjvIp1rh7bffVsZ1XJzgogMXTngbgiDYB46e0HiTG/eFEgAzt1vfCTQZhl3ntIlaB4uoMEucnMqgSTWd5X2yjGnsi1ndgiAIQq6QoruEwmLrpZdeUkUJi0lKjP/++2/zvC0LJRZIlAuyG87ILEp1c9P1ZoHD32NEFGeRKQdm4WR5GzxIY7FIKTevw4KaMu7McDaXcmQ6qFuD3Vs6W/P+6AbOgtKIr2HXnq7sLNbYbaUUki7WxtxwZig/ZoeWcWfsdNO5m3Fnr776aq4fd1Zw0YP3Q0WAIfO2hfz8nbwfznwvXrxY3S9vi07oBQmdyvm8cN6cagUu9Lz//vu5vp3u3bvj66+/VgUz48QYQ8bbort+VlAhMWfOHPU3t2zZUr2OuW+8xgVBEAQr1OsNjP4K6DAZu4x57jo3Ssszz3XvTqilzwg9BiRnHB8ShELh6ok8JfoIQnGgDN3UUIpht9fX1xcRERHKBCrzLBsNqngQn93Bv2AdFkCPPPKIkmXnBGOfWLxlzqVmN5rGapRa55TZXBSPWyg4qKI4evQoNm7caJfbk/ezIAiCxWdiUgpavrICSSlp2PhUX9SuaF3J8OO2c3jhj0Po1bAyvg+9DYiPAGZsAqq1lKdTKDzObAS+Gw40HQHc8YM884JD1JKWSKdbKFLYaae0m5JoawZhQumBXXmOKVCmztcDRyEmTpxY1A9LEEo1XKy67bbb1MZ9wcEJPQ4EHQBSU7D/QrgquKv6uKNWhazNVQ0ztSPBUUBVU6EtEnOhsNn0kT498hcQdUWef8HhkKJbKFI4W92jRw8lDc5KWl4SmDFjRoZoK8uNlxVXKIvP6nFzs1U2bws0UmPMHaXilJp/+umnSkIuCELRQUPIX3/9VW0SGVYC2PYFMKsnsOa19HnugIrZ+mdwppsXh0YlILzjI8BdvwONhxTigxZKPakpQND+9Kfh8O+l/ikRHA+Rl4u8XCgEmEfN15o1KEXx8/Mrlv8HurjTDC47wzhmmjsCIi8XhNzDRAkaJZJ77703T2kXQjHii85A6FFg7E+YtLUK1h8Lxcs3N8Pk7tl7YfT9YD3OXI3B9/d0Qq9GVQrt4QqC2XH/28F6v814oNM0oIaOMhQER5GXO8bRsiA4OCyqi2thnR0sqHMbxSYIQsmBRTYTE4QSQOx1XXBTwVCzE3af26P2O2bhXG5Js+o+qug+EhQpRbeQTnQI+3dAuQJeiDn6rz5teRsw6kv5DwgOiRTdNlDKveYEoUQg72NBEEo1F7br08qNcDzaHVHxyfByczZHgmVH0+re+PdgEAKDIoHAP4HL+4Au9wHlHG8xWbATCdHAV92hZg8e2gu4eRXcU9vtIaByQ6BSw4K7D0EoYGSmOxsMGV1sbGxB/x8EQShgjPexyGMFwXZSU1NVTCE37gsOzPmt+tS/izkqrF1ABbg453woaDZTY9G9/h1g04fA5b0F+3iF4s3J1UBMCBB9BTi2rGDvi530dncDAV25gg5c2AmsfVPvC4KDIJ3ubGDOMmOqOI9rZDdnZzYiCELx7HCz4Ob7mO9nvq8FQbCNuLg4NGrUyJw24eVVgN0soeDnYol/V+w8km6iZgtGVvep0BiktGsO55BAIPgA0Mg0ZyuUPgzJNzn4K9Dy1sK536RY4PsR+pSvv1odCud+BSGfSNGdA9WqVVOnRuEtCIJjwoLbeD8LgmA7NIgRHJykOOCSnuFG7c7YtUwbZHasU8GmX6/m44Hynq4Ij01CiGdDVOeZwYcK8AELxZqUJOD4ivSfz/wHJMYCbtaz3vPF0ieBCnWBNuOAshW0jL3JMODgYuDAIim6BYdBiu4cYGe7evXqygSLLq6CIDgelJRLh1sQcg872+Hh4fLUOTpOLsBdv6rC+5JTdVyOOApnpzJo41/e5mMhmqltOXUNx1FHF91XpOgutcRH6ti4y3uA3k8D9fsVTMHNPO4d31CzBjQfDRhx8i1v10X3od+AwW8CzpKqIBR/pOi2ER6wy0G7IAiCIAgOB4uSen3UtmvfJXVWixo+8HSz/TCwqano3hFXA715xrVTQGJMwRpoCcUTr0rAmFl6progxy6Pc1Y8DajRDvBRSz2a+n0Bz0pA7FXg9Hqg4cCCewyCYCfESE0QBEEQBKGUsNNkotbBhqgwS9jpVr9/1QUox1GdNOBKYIE8RsFByFxw29vYzJgbp5w88yJS8zF6nxJzQXAApOgWBEEQBMEqCQkJmDRpktq4LzggdJ1f/Qpw5G81i7vrbFiu5rkzm6nRwTytWgt9pkjMSx/h54Gg/RkLbL625g4Ctn9t30iy0xusF92k1e3phTkVF4JQzJGiWxAEQRAEqyQnJ+O7775TG/cFByT0KLDpI+D36YiIT8axK1Hq7PY2OpcbNPArB1fnMirfO7jzC8BD+4B2EwvoQQvFll3fArN6Af8+nn5eZJDOgeectb04tQZISdAmalWa4FJ4HG76+D/M3XRGX16rI1ChDuDhC1w7ab/7FYQCQma6BUEQBEHI0oTwvffeM+8LDpzPXasD9lyMUg3KOpU8UcXbPVc34+bihAZ+3qrTfTCxOqpXlDSIUokh+Q7oln5e81HA8qeBS7v1rH+l+va7H3a5y5TBLzvO42hwFD5ZfRx3dfGHu4szMPFvwKcm4CRRoELxRzrdgiAIgiBYxc3NDU8++aTauC84dj73rjzOcxs0re6tTo8E6W65UMoIPQ5cPQ44uQINB6WfX85PG/WRQ7/b7/6c3YHGQ9XuqsAr6jQyPhnrjobqy8v7S8EtOAxSdAuCIAiCIJRULhhFdxfszOM8d2YztcCgCGDLZ8Ciu4EwnfktlAKO/qNP6/UGPPRrwUyLW/UpJeb2MFQbMxt46rR63Z6/Fqu63AZ/mhz4zaQkAxGZzhOEYoYU3YIgCIIgWCU1NRWXLl1SG/cFB4OFCI2vyjgjoVpb7L8Qnq9Ot1F0q043O5qBfwKX99n1IQsOUHRbMzZrOlx3pq8es5/Bnns51cleGRisfqxZXgd1rzkSgoi4JH2dMxuBD5sAi8VfQCjeSNEtCIIgCIJV4uLiUKtWLbVxX3DQLne1ljh0NQ0Jyamo6OWGepXzlq1tOJifvx6LxCrN9JniYF46iLysZ7ZRBmg8DKmpabjvx924f8Eeta8MzYy87IO/5v1+2CWPuJjhLENaPqVHXTT0K4fElFQsPxSkL6zcCIi9BlzcCVw/nff7FYQCRopuQRAEQRCyxMXFRW2CAxJ0QJ/6d0mf5w6ogDKZ85VtpIKXG6r7euib9migzww+aKcHKxRrji1Ldw33roq9F8Kw7FAw/j0YhN3n9dgCWo8FGt2k/APyDBdxPmquI8jS0hAWk2jOlh/YrCpGta2p9v/Ye1lf37tq+jx5fop9QShgpOgWBEEQBMEqXl5eSEpKUhv3BQdjwCs62qvLTIt57rxJy2/I604L0GcE20lKLBRv2t0N3P0n0Pc59ePKw7r7TP7aZyqAm94M3LkQaHxT3u/n6FJ96llJuZavPRoCNtKbVPNG7YqeGNmmhrp425lrCI6I19dtacrsPrDIPvPkglAASNEtCIIgCIJQEmFHu2JdpPr6Y/c5w7k8byZqmee6t0ZX12dEXgRi9W0LJRhnV91Rrt8XaWlpWHFYz1kTdruTUuzk+XDMFBWWybV8UHMdUVergqcyAmRt/df+S+nz5C5lgWsngCDxGBCKJ1J0C4IgCIIglGBOX41GWGwSPFyd0LyGr1063ftCUoDyAaVnrvvcViBOG9GVdk6EROPstVi4OTspj4DrMYnYfPJq+hXCzml3e7qK54bwC0DQfj033ugmxCelYMNxHQ82qFlV89VGttES8yWGxNzdG2g8JL3bLQjFECm6BUEQBEGwSkJCAu6//361cV9wILZ9DfwyHjixyiwtb1O7PNxc8nfoZ2R1M8IptWpLwNlNm2yVZDgrPO8mYE7/0tnVX/YMsPw5s1HZikO6y92jYWUMb6UVD3/tN70GUlOAb/oBK18AzmzI29y4fxegXBVVyMclpaCGrwea10iPKBvWsjpcnMrgSFAkjl8xRYm1MknMD/2mH4MgFDOk6BYEQRAEwSrJycn48ssv1cZ9wYG4uENHPIUEYpep6O4QkL95bhJQyQuebs7KCf1st7eA5y5rA62SSnIisPZ1vX/tJPDzWCCpFDn582/d8z2w7Qtzp3+lIfluVhUjWtcwz3izM82ILzQbkV4A20FaPqBZ1QzmfzT069PYT+3/sdckMa/fH+jxKDB+MVBGyhuh+CGvSkEQBEEQrOLq6oqXX35ZbdwXHIjQ4/q0ciPsstM8N3F2KoPG1XS3+1C4q571Lcns/QEIOwt4VgbcfYEL23URWlo4vR5IigF8agI12uJSeBwOXopQdgEshtv5V1D52dEJyVh3NET/Tsvb9OmRv4Ekk9lZTrCgP7tJ7zcZhpTUNKw+YhT3ep7bklFtdbH/577LOrLMxU0bB1Zvrb0MBKGYIUW3IAiCIAhWcXNzwyuvvKI27gsOAuW1NJVic9ajDs5di1V1SLuA/BfdlnPdgZcjUeK7vBve0/u9nwbGLgB6PAZ0nIZSA9USpMkwVcyuMhmoMXqucjl3ODmVwc2t0wtgRe0uukhPiAROrLTtflw8gFvmAF0fACrVx74LYbganQhvDxd0rnejQmNA06oo5+6iFgHMkWWCUIwpdkU3JWx169aFh4cH2rdvj40bN9r0e5s3b1Y5om3atCnwxygIgiAIglBsibgAJMereesd4eXUWU2q+cDHwz5dacPBnDO1WPY08HVP4MphlMjFi7bjgSpNgPYTgbo9gQEvA06mw+eSHk9FIzRjzrrJcHWywhQVNtjkJk4MifnaYyGIjE/Sz0+LMfrCQzZmZ7t6AM1HA4PfzCBh79vYD67ON5YrHq7O5sewxJCYG4Z3S2YAR0yLBYJQTChWRffChQvxyCOP4Pnnn8fevXvRs2dPDBkyBOfPn8/29yIiInD33Xejf//+hfZYBUEQBKGkw2ig8PBwtXFfcDBpeaUG2HFed6MZs2QvmloW3UEHgOAD+rSk4V4O6P8ScN8WwMU942WUTf86GTi8BCUWSuljrwEe5YGAbgiLScSOs9dvkHzTXK+BXzkkJqem53e3uFWfHl8BxOdeEWHMcw+0cC3PzOi22sV86cEgdd+Kk6uA/T8De3/M9X0KQqkpuj/88ENMmTIFU6dORdOmTfHxxx+jdu3a+Oqrr7L9venTp+POO+9E165dC+2xCoIgCEJJJzY2FhUqVFAb9wUH4aoxz90w3UStTv5N1AyaVPNWcvWQqATEVWpW8mPDaA6Wmd3zdMH9+3Tg3BaUaGk547icXbHmaIiateb/37+Sp/lqNDkzut1mF3POVldqoE3Ngg9mfz8XdmoZf8hR9ePJkGicDo2Bq3MZ9GlcJctf61q/Evy83REem2SOFkPL29OL75hr+fnrBaFkFt2JiYnYvXs3Bg0alOF8/rxlS9YfZvPmzcOpU6eUyYstMPIkMjIywyYIgiAIglBiSIgCnN2RWKEhDl+OsHun28vdBXUqean9C2719JnsdpcUGAv24y3pxl7W6HSvllynJAA/jwNCj6HEUbYC4F1dz3Mrh3I9zz3IQlpuYBTdjPm6Gp2gzcxu/wF48iRQp3v298PO9Lo3ge1fZehyd61fGd7ZjEQ4W8yT/7HPJDH3awJUawmkJgOBJViFIDgcxabovnr1KlJSUlC1akYZCX8ODtZv8sycOHECzzzzDBYsWKDmuW3h7bffhq+vr3ljJ10QBEEQhBvx9PRUi+LcuC84CH2fBZ4Pwq5ak0BjZ7pLV/cta9e7MPK6Dyb76zOCD5WcGedNHwEnVwPLn8n6b2L3e8w3QK2OQHw48OOtQJT141WHpfdTwKOBKsIrLjEF/53Q3eTBzW+UfNep7IXWtXxVJ5xyb0XVZoCbXpzJktTU9Lnxxrq4XxUYnKO03GBUGy0xXx14BVGcJyet7tCnBxbb+pcKQukpug0sc/gIZ8gyn0dYoFNS/uqrr6JRo0Y23/6zzz6rZsCN7cKFC3Z53IIgCIJQ0uD3L6PCuFn7LhaKMU7O2H4xzu5d7sxmatuiqgBlnIG460CUqdhyZCKDgB2z9X6/l7KPn3LzBMYtBCrWByLOAz/drlUGJQmaojk5q4I7PilVLeAY//vMGF3nvwwXc0uyel6C9gJRlwG3ckDdXgiNSsDeCzoPfGDTnIvuFjV9UK+Kl8qNX37ItOjR4hZ+egEXtgFh52z/WwWhuBbdSUlJqmg9duwYrl/Xxgp5pXLlynB2dr6hqx0SEnJD95tERUVh165deOCBB1SXm9trr72G/fv3q/21a9davR93d3f4+Phk2ARBEARBEEoa6fnc9pvnzmymduBKopodV+Q0u+sI/Pe+dn5n7FXDgTlf36sScNevOsc7aL92zi4JXNqt3dtNGAZpdAzPagGORTcv2nUuTEV5KS7uAr7sBiwwzVpn5uhSfdqgv3IwX3PkihIXtKrli2q+Hjk+TD6W0aZutzmyzKeGdponB6XbLTho0R0dHY1Zs2ahT58+Sp5dp04dNGvWDFWqVEFAQACmTZuGnTt35vqBMP+TEWGrVq3KcD5/7tat2w3XZ7F88OBB7Nu3z7zNmDEDjRs3VvudO3fO9WMQBEEQBCEdysqffPJJtXFfcABoSvVVD6QsfRp7z+uOYccCKLqb1dBF98nQaKRUbalNs5IT4NBcPwPs+U7v07XcVnVHxXrAnYsAn1pAtwfh8PB5+KYf8GEz5dKenJKKNUd10T3IirTcoKqPBzrX1a+1vw1DNe9qQMhh4PwWIOLijb90bGkGabkRFTbIBmm5wUhT0b3l1FWERManS8z5mvSqbPPtCEKxKbo/+ugjVWR/88036NevH37//XdV4LLTvXXrVmVmlpycjIEDB+Kmm25SM9e54bHHHsOcOXPw7bff4siRI3j00UdVXBiLaUMazmgw9cCdnNCiRYsMm5+fn8r35r6XVw4zJIIgCIIg5Kho++CDD9TGfcEBYIFz5SBiLx9BbGIKfDxc0NBPZ3Xbk2o+Hijv6apmeI90eR94cDfQbAQcmg3vagOu+v1yNv/KTK32wEN7AP8ucHiO/qtPqWBw9VAxYXQIr+jlhg4B2Y8qjGidqevsWwsIMD2Xh36/sbgPCdTjCY0GISYhGZtOXlUXDbSIJMsJOqm38y+v/AvM7umtxwEP7ALaT7L5doQCynq/vFeeWgC2uY+ZoIv4unXr0LJlS6uXd+rUCffccw++/vprzJ07Fxs2bEDDhibJkQ3ccccduHbtmpKJBwUFqeJ56dKlqoNOeF5Omd2CIAiCINgHznI/8cQT5n3BAbiqGx7nnWqp0/YBFeDkZP95fMp6m1bzwdbT1xAYFI0Wtew/N17o2eb7f9H7/V7McNHxK1G4e+4ODGlZDS8Nb5a1v4Flljel9nQ0b2nKq3bEopvu7BbS8v5N/ODinH2/bkiLanj5r0Mqw/1kSBQa+HnrGetzm7XUu/tDGaPt3H2AGm2UU/rGQzpv27+iJxpVzd1C0ai2NbHnfLgq9qf2rGc95k0ofOhM/9cDQLuJwND3gegQoHzpNLHOVdG9eLFtcxGcm545c2aeHhB/L6vfnT9/fra/+8orr6hNEARBEIT8w9Gv999/X55KR8IUXXUsubo6bVHTt8DuihJzXXRHpjtRG+Zbjkal+sCor/Rcds12GS56e+kRBEfGY97msyhf1g0PD8ihoXT1JPDtECA5DihbHmgwAA5DdChwfqvebzJMGRobUWGc586JCl5u6NWwisr0pqHaY4MaA81GAcue0rFyXBQyPAAaDQaePAXEhGaQltO1PLfGjcNaVsdrfwfi4KUIlfPdwFB3JMVpJ/rGQ6UQL2z43K97S+9HBQEftQAqNwImmxZ1ShkO+KkoCIIgCIIgWIXdQwD74v3Uqbn4KAAMMzV2NfHLeOAdf23A5YiwM9pmHDDknQxn7zp7HeuOhZrHuz9afRyLdl3IuYBvPERL1RdNBHbPB6J0QVnsOc74rjSgemvVkTx0KRKXI+Lh6eaMHg1tm48e0cbkYr7/siraldkcJfvk4K8Zr+ziBvjWVHPja4+G2BwVlplK5dzRq1EVtf+nkdnNRaAvOgEL7wLObsz1bQr5ZPss7UxPr4Mh7+qEg3ObgKADpfKpzVWnO/P8tTW4MsW56gYNGmDkyJGoWNH+5h2CIAiCIBQ8PGCmVwthMojEhjlAZylcj+FtCtPHX/WrFFzRbURHsdOd5p2MMolRwKk1QO2OcCiSE3XxZ+X1/94KrRwY27G2mmn+Yt0pPPv7Qfh5u6NPY72wcQOs0Ed+AUQHA2f+A/5+GMDDQI12uhjv/ojV+ysWHPlHnza5WZ2sNGVm925UBR6utkm2BzStCg9XJ5y9FosDFyPQunZ5oMWtwImVwKFfgT7PAIkxOsPbtJqx82yYmhuv4Oma49x4VoxsU0MV7pSYPzawEcpQcVGvrzbH4+JH3+eBDvcAznkufwRbiQsDNn2o9/s9r80Gm40EDv2mi/FRX5S65zLPne69e/eque3Zs2er2e3169crgzWet2bNGlWUs/AODAy07yMWBEEQBKFQiI2NVRJzbtwXijnXTqouZapHBZyOK6vOYoZxQcEuuqtzGUTFJyMsYEi6WRa7m47C2U3AJ62BPT/ccNHGE1ex48x1uLk44cF+DfHEoMYY07amMo+buWAPDl2KyPp2WVSP/Rno94IutsnlPcDeHwFnC38Eytm5WFIcYJb26fV6v4l2E19hkpZn51qeGS93F1V4E7OxWZOh2lF80Bv69bFkOvBZOy39ZlqRSVrer0nVHOfGs4Idcnbkz1+PVfPdit5PA37NgfhwYNmTwNc9gFPr8nT7Qi7Y9BEQHwH4NdP/d9LZFKfH2f4YbZhXmshz0c0u9oABA3D58mXs3r0be/bswaVLl5Rz+bhx49R+r169lAO5IAiCIAiCUMAkRKuZyejyjdluRc3yZeHpVnBdPRajRid9v1cPwNkNuHpMO1I7Aiz+1ryuJbCZHJbZ5X7f1OWe0CUANcqXVUqPd25phe4NKiln+EnzduLC9WwWo9zLAb2eBO5dBzx+DBjxGdDrifQospQkYP7NwLt1gZ/Gahl6ZBCKDFcvYPJSHZfm1xRnrsbg+JVouDiVQb/GuZN8GzFe/xy4rBYp4O4NjJmtO/0pCcCptcD10yrfnM/1qiPBeZaWG/C1bsydmyXmvjWB6f8Bwz4EylYEQo8AP4zS4xB01hbsT8Ql3c0m/V9On6Wv1VEvQPH/v3teqXvm81x001jl9ddfV3nZBtynkdl7770HT09PvPTSS6ogFwRBEATB8eB3eVhYmNq4LxRzAroCD+zEv21nqx/rF+A8d+a87gNX09INwzJHQxVXTqwCLmwDXDx0cWwBO7w05fJyc8bMPvUzLDR8dVd7NKnmjavRCZg4bwfCY23IsGdedbu79WbAUQAWozRc4yw1ZegfNgFm9QbWvQ2EHEWhQjl2rQ5Az8fVwoBhoNalXiX4euYuvaBXo8oqru5KZIJSC2SA3fSkWD3rW701jl2JwoXrcXB3cVK/lx/oYk7+ORCEpBSTsR/l5B2n6Fg7dlsZUUZpe3GRma9/B/imP/DjrdqEz9EJO6vc6OHfTZvlGZQpA3S5T+/vnKsXnUoReS66IyIiEBKiDQ8sCQ0NRWSkdrEsX748EhNt+CASBEEQBKHYwc4ev8u5yTy343AyNEadNijAee7Mc93KTK35GH3mYQeQmNNka+3rer/TNMBHu70TdmY/WKkN6ab0qKtMuizx8XDF/MmdUN3XA6dDYzD1u12IT0rJ/WOg4dqjh4AZm7QMvWYHpVBA0D5gwzv6eTQ/qKRC78wabuKDcyEtN3B3ccaQFtUzSsxJyBHg57HpknNV3Ov76dmwcr6VGd3rV0Llcm64HpOIjSe0K7oZz4ra0Ou+LcCAV9PPDzsH7Psp3X3fXvA9EBWs5ezbvgL+egiYOwj4X5OM9xV6FLi0Czi5CpjdBwj8Cw4NM+4f3AOMmZWu6jCgk325qtrNvJSZ2+VLXs5M7iVLluDixYtKTs79KVOmYNSoUeo6O3bsQKNGjez5eAVBEARBEARrmArdU6HRBe5cntnBXMWGNb5Jd40pG+ascnHmyJ86wsrNG+iecRTyj72XVOyUb1lXTO1Vz+qvV/P1UIW3t4cLdp0Lw6ML9yGVMurcwqKkWkvdaZ+2BnjiuDZhY0Z2U21mpji2DPigAbBkBnDkb21EZk/Obgb+fAA4vUH9GBIVjz3nw9T+wGY5R4Vl52K+9KDO31Zs/iT9Cozxspjnzo+03IDz4MNb6fv9Y69FsW+JX5MMiyxY9SLwx33A3AHAhZ15e99FXMy40LT6VeDdOsD/Gms5+/JntKHbhe264Aw/l37djlOBW+YCAd0BmhEumgCsfMGx5e9unkB5f+teByM+A+7bmu5oX0rI83LSrFmz1Lz22LFjMzibTpw4ER9+qN3qmjRpgjlz5tjv0QqCIAiCUGhQrfbWWzpn9bnnnlOGanaHB6rJ8UB8pDZyouSzQh37309JJzUF+KCROtANvU63bFfUL0ATtcxFN82rotI84N3tQS0t9a2FYguLGSM/uNsDOtLKBItDxoKR+/rUV13trGhczRuzJ3TAxG93YNmhYLzx7xG8dHOz/D22cn5A27v0Zgld4ekIvf9nvXFxg0ULDc8a3QR45U+WrVyl9/6g52/r9cbqwBD11qTzOBcY8gJl6VW83REalaC6zv1prtZ8tH78pE4PBEXEKRk/1x5oomYPKDGfv+WsKuZjEpKVsVuW8I/knPHJNTrujoV3q7HAgFcyFuYkOQG4dkrH8jFvnP4Fav8kkBQDPBqoZ8gJ/yCat5Vx0s7dVZqoOXnzqeX7o04PfUp37zWvAls+09ulPcBt8/VrwhHg88fnpeVt2WeiN7KQnJci8lx0lytXTrmVf/TRRzh9+rQyQahfv74636BNmzb2epyCIAiCIBQySUlJePVVLcN88sknbS+6GcF05C/d/WEhnRCpi+oOkwH/Lvo6x1cCf8zQ56dmmu27/Qeg2Qh7/zklG3bOYq8iLSEKR2OdC63TzRitaj4eCI6Mx7HgKHSgTLq4Q1kriyUaa3WZmeGihTvP42JYnCoWJ3bNefGna/1K+OD21njo5734dvMZ1Cjvgak9rXfH88XQ/wEtbweO/gsc/VvPgx9bqjcWdiz4jCKRhWRmWW92UOrM2yXssFu6luej++zsVAbDW1XHvM1nlcRcFd0NBwHDPwYqNVAu7qsDteFZO/8K6jm3B61r+aJuZS9lBMfIs9Fts1kA4vPU4xGg9VhgzWvAvgXAgV+0moALH32fA8qW19flOAKLYWs4uQARF9KL7nYT9QJDpYaAq42LFnS1p7s7xwz+vF8XsGl2lrwXFHzNrXgeOL8VuH4G6Pus7eaP7gX/OVUcyNfgxMaNG1XHm0X34sWLVcH9ww8/oG7duujRw7RqIwiCIAiCQ0IF28yZM837Nh98/T4VCPzzxssCuqUX3eyExF6zuLCMPnBlAc4YJym6cwcP0HkM61sXKTFOKO/pqgriwoBmaiy6KTHvUEfngxdr6vcFpq4BIi8BHumGwHGJKfh0rTayerBfA5R1sy2XekTrGgiOiMNbS4+qbjc7w4bE2W5QAcJZWW6D3wSuHDYV4P9olYNlV/bbm9QCDCrW111WbpVMp77+NxqIMcqMmeKU2tfthaj4JGw5pSOdDDfwvMLnhkU3u86xicl6ZpuLb5nmxu0hLTeg/wQzuz9efQJL9l7Ovui2NLob9aU2XFv2NHBxJ7Bjlv4cMjrRlRsD7j4qIUBvDYEqjfU+1TmWUXAVAvL+BzQfBVRtrpUNfFyOwPHluuB2KQu0n5jhopDIeHyx7iQmdA1AAz/v9IXZvx7Uixs0uMusKiiB5Lno/u233zBhwgSMHz9exYUlJCSo86OiopQUbenSpfZ8nIIgCIIgFDLu7u744osvcvdLmz7UBbeTK9DiFsDDVxc2dGmu2T79erU7ATO36YNYXuZWDjiwENj4QXpnSbCdUB1vda1sHbOJWmGZ3zWt7o21R0O0mRqJC08vBjMdgBcb6NINbul8t/WskkLXqlAWYztamUfNhmk96+FyeLySNT+2cD+qlHNH53rpsnW7oubAW+itz9MZ57u56MVYLGYkq9z2TLDz+uCu9J/pNG90uRsNAlzcse7wZSSlpKmM9/yqJdrULg//ip5q/GD1kRBVhBtExidh2+lr+e6oW2NUm5qq6N50IlT9T23uovMzasoqnSXNgpBO5watx+nud2G8r1jQW8L/Ex/PiE/152Vxgu9zzrCTLjMAn4wLTi/+eQgrDl/BkaAoLJrRNX22m+ocyvJ3fQv0ex4lnTwbqb3xxhv4+uuvlcTc1TV9Zadbt26qCBcEQRAEoZTBA/6gA3p/6PvavXboe9qZufvDukgw4IGjmm2sqYtyxhW1Gae7HpR0CrmDcmnOVjvprp6Rn10YmM3ULpuKbioVKI/d8K79HaHzQ3SIHnmwAgvArzecUvuPDGikosFyAxc4XhzeTDl9J6akYtr3u3DiShQKBcZfWTJjM3D3X8DwjwDO2FMyXqWpngPP3IH993Hg0K96n/Ph7D6bpOX57XIbz8vNrU0u5vsyGputPxaqint6D9Sz8+u1TmUvNY9ObztmhecKFtWtbgfu+EHH8BlQIVBIC1kZ4IjOP49qN3tGi5kW2IoN+3/RCz0e5YHuj2S4aPe5MFVwkx1nr+PQpQiYYXwbYdGdFI+STp6L7mPHjqFXr143nM+s7vDw8Pw+LkEQBEEQHA0ekNL4587FGSSkQuEV3UeSqhfaPHfm2DDmLTNuS+V1U8FA+fbFHSgWcM6UcU2ftgO2fH7DxXM2nkF4bJJ63kabsp7zMsP8ydi2aOdfHpHxyZg0byeuRMYX/nuwfG1lhoYO9+gZ4bELgPu3Ac8FAbfOS78uJb6Uq/s1B+r1ARoNQUJyiiqG7dl9HtFaP58bjocgIjbdvyHdtbxgJNSjTO7pf2Qq9h0OLlDeuQjwrq7N277ppzvfxYGkOGDdm3q/1xMZVEr0+3p3mc6ad3XWixVUgpjhYhCz2jkKQSO/Ek6ei+7q1avj5MkbZSubNm1CvXoFYCAhCIIgCEKhEhMTo9Rs3LifJexSGHE5POinTDU/8LYoWRRsf75M3a9d0drFur5fwTuXGwRU8kJZV2fEJ6Uq8yplHGWKgyoWxQHVFyy4w84A3lWBxkMyXHwtOgFzN55W+48PbKSK57zi4eqMORM7ol5lL1wKj8PkeTuVvLlYQDWJxQy7kvje8SMwcwtw958q5mnLqWuITkhGVR93tK5lnzEPurw3qeatutrLDweZXeLXHw2x+zy3JZyr5/9y/4Vw/bp0ZPw7A9P/A+r0BBKjgV8nA8uf1fntRcmOb/TiGovnjtMyXLTuWIjqbru7OKnFKEPtcDU6IV050Gmq3t/+VcbItRJInovu6dOn4+GHH8b27duVdOTy5ctYsGABnnjiCbPpiiAIgiAI+YDOrnQpZubx6fXA4SVaindqXaEdoDAW1IgGtQrlw79NAX69xz7ZwX8/ArwTUDyKNUeBkWv+XZBWsR42hetCqUGVwpv7ZGHDuW6y6+x1fWaLMfo08I+iXUA58x8wbygQEwJUbanndSvVz3CVr9afQkxiClrW9MVNLfLfdaWBHTO8K5dzU+Zynd5ajVu+2oIv159UDu/sABZXVpqkwCyEnfKx+JCZm02z3HQxJ5zljkpIRuVy7mhbu2A8HDjH3aOBXoR68Y9DOH8tFg4No8Mm/JEu4d72JfDdzVqxUFTQm6NWRz0SZOHSTsXLu8v0QuCk7nUwtGV1Jffn6MVP28+n/z5d3mm+FnwQOLcFJZk8G6k99dRTiIiIQN++fREfH6+k5jRcYdH9wAMP2PdRCoIgCEJJI/gQcGyZdqg1Ns+K2kHXYFYv4LqeM72BgO7AhCXK+KigKFu2LC5evGjet8rG/2nTLGc3oPtDQA3d0cgzaSlAAk2gtBu3YAOuZYE7F+L8tRhEvr9ezSPXrJDF/6uA6NfED3vOh+Pfg0EY28kfqNdXz3hGX9EH03V7otA5/Afw+zQgJREI6AGM+0kb+1nAnOjvt51T+08Mbmw38zn/Sp6q8H7294Mqh5qzrdzeW35MGbUNaFpVPWed61WEu4ttLukFDQslQ/Jtj3luS2ig9v6KY6qTTjfrdGm5n12L+8zc26seNp28qrYBH27A1J51MbNvA5TLLru7OMPu8MBXdaH7x33aEJCKhaKCaRRcyMq0kPTH3ktq3MTHwwUzezdQ503uVgePLNyHH7adw4ze9bVvAr/zOD+/5ztg5zd63KGEkq9X3Jtvvonnn38egYGBSE1NRbNmzTLkdAuCIAiCYIVzW4EfRukOpSW+tTP+XLaCLmaZJ8x9HqDQNIndu3JVC7TgJk5OTqhZM5v51mPL0+f5hv0v/wU3YfyOxYyyYDsnQ6LVKaXN+ZFI51XK+8HK46qooly7Ujl3oOlwYO+P2gCqsIvuCzuAxZO4igM0vRkYM8dqXvKna04qqXOnuhXRq6HuitqLFjV98feDPXA5PE65u685cgWbT11TOeCcbeXm5eaMXo2qqAK8bxM/1fktKvZdCFPSX28PF3Sua1/n9doVPdHWvzz2ng/H3weCsPqI/aPCrNG9QWUse7gnXv8nEBtPXMWX60/h190X8fRNTdTsfkEW/AUK31s0pvTJm/+AXeFClcViVXxSCj5cpT+/ucDh66kNt9ntfmvpEYREJWDZoSCMbGN67F1maoO/dny/llzyvczj6emJDh0yRi4IQomDMzMrX9QZjP1fvjHjUhAEwVZCjgA/36EL7tqddaeABTU3FtKWTF6mP3cyd9+UA7PFeWHngK2fA72e1BLEwsqFZheRRU3HqUC7u+1zu+aiWzrduTIzcvHAqVBddNcvRBM1S7foFjV9cOhSJJYdCsZdXQKA5mOAvQuAWJPkvDCp2QFoPVarAIZ+oHPhM3H2agwW7bqg9p+0Y5c7MzXKl1XPBzdmVW8+eU0V4GuOhqh5bz5f3Hj3lFr3b1oV/Zv6oXFV70KLfSOGy3T/Jn65dm+3tdvNovur9SdxNToRnm7O6Fbfvgsd1mhU1Rvf39NJRZa98W8gzl2LxeOL9yuFw8s3N0M7/wooClJT09QCzImQKBy/Eo3ynq64tX0tuDrb+NwzG9wgOQHY+gXQ9YHC6Xwve0YvAFPdlEk98uO2c8rPoJqPByZ1S3+Mbi5O6j3AgvzbzWfTi26/Jnor4eSqcnjsscdsvu6HH36Yl8cjCMUPSmaWPgHsng/U7Q2kJkvRXVSwc8HMzFoWWb+C4Ggww5hKvFqd9Hyem2fW183q4MlXx0KZYbeZGdf7fgK6PQR0vR9wz3/hlZiYiE8++UTt08fFzc30eOIjgV/uBBIiAf+uwOC3Yfd8WmYMcxbYSrEkZGLhXcCl3XCr8gSAuiqjuyhgt5tFNyOaVNHN78zHj2nzssKArxd+R1MBQtOwEZ/r108WhetHq48rSXXfxlXQsU7FQnmInm4uqrvLjUXXocsRqhhkEX74cqSS6HOjFLt2xbIY1KyachFvH1ABLrYWY3mAc+YrTFFhg+wsLTcY1qq66jiz4Ca9GlZRxnOFARcv+Jz3alQZ8zefxWdrTyqDtTFfbsGYtjXx1E1NUM33RiVEQRTXjJI7ERKtlClxSRn9DpbsuYTP72wLP59cPpaFE4ATK7Sh4uivCzbajPexYxaQlgo0HKRN3iyi9z5fp422Hx3Y8Ib/752d/fG56bnfcz7M+oIHj7uLIpqtOBXde/fuzfDz7t27kZKSgsaNG6ufjx8/DmdnZ7RvLwfEQgli+yxdcBuZglbkaUIhwE7J3IF6/4XQop1hEoT8wNzXe5YD3tWyL7hzQ9sJujN8eQ+w/i1g5xygzzO6+8xOeR5JSkpSHi6EJqnmovuvB7T827sGcPv39n0/lg/QknoqASIuZOzmCNYJPa48AY5HuhV6XJglw1pWxzvLjmL7metqblcVDoVVcNNB/3c6IZti61hsZ6NKOxIUaTb1enyQPo4tbChtblWrvNoeG9gIwRHxWHP0CtYcCcHmk1dx4Xoc5m46o7YKnq6qA84CvGfDKijrZt9ilcUgO8DsRvZuVAUFgZ+3h+psc76aDGpeSK8NCzg/P713fYxuVxPvLz+Gxbsv4ve9l7D8cDDu79sAU3rUzfNCABdwLobFqmI6p+LawM3ZCfWqeCl1yoZjocrte9hnm/DFne3UyIPNdLoXOLkaOPALUN4f6Pc8Cow1r+mCm5FfFgU3mbXhlDl675Z2tW5cUy3nrkz1fttzUS1+ZCi6+fg3vA+0vkPH3ZXmonvdunUZOtne3t747rvvUKGCfsLCwsIwefJk9OxZBGYZglAQnFgNrHhW7zPrssnQ9FW4K4f1PI1QOFw2LfpVrCcFt+CY8l9Kwo0ubtVm9r19zstOW6vdzde8CoSdBf59DNj2FTDo9RsikmzFxcUFEydONO+b4QLkpT3A7d/ZX87OYqlifSD0CHD1pBTdOZEYC0RoN+DN4fogvX4Rdbo5t9umdnnsuxCOpQeDMKl73fQLo0NMHgV5XwTKkvgI4Oc7gXOb9IIN3f5rtsv2V/638rj6KudCAWeviwPstI7vHKA2ytD/O34VKwOD1Tx4WGySmkXm5uHqpApvFuAsxOmWnl9WmrrcPRtUhlcBmoxRYs6im54DnGMvKrgA8P5trZUi49W/D5vVBT/vOI/nhzZVLvZZSfs5s8xRjlOhMaqgVvsh0Th9NUb5A2RXXDes6o1GfuX0adVy8K/oaVYwnA6Nxn0/7lEGZOO+2YZnhzRRiwA2jRg0HAAM/wj4+yHgv/d0Vru9Rn4sOb9dG2eWcQL6v5ThImbSc4GIPDW4cZbKjMnd66iim58Rzw1tmq4w4OLhhW1AfDjQfnKJ63bn+V31v//9DytXrjQX3IT7b7zxBgYNGoTHH3/cXo9REIqGkKM6B5GreW3v0nMyhNEMf84EAv8CJv6l5zGFgocdPFIj+wMpwQZ4pLnne+2KzegRmnOVdujbUBDFgLrtZB2ndXYzMO7ngnNn5QEKY5rYfdg9D9jwrnYAZ3Gcx6KbqSTz55uUPpYEdAMe3JPlAlhSSqqSql6JTFAHqAlJKYhPTlX7etP77P4kcD85/XzmPf9cuwsq8qBRlEU5Y3J5Ty1bCefCyqqXAQ/ui4rhraqrovufAxZF969TtJnauIX5z3DPTFQw8OOtwJWDgJu3dijPoeDeez5MGXnRQ+vRgSYPgWIGZegs/Lglp6Ri59kwVYAz0ovzsnT/5sa/gdJ4SqfpOM6Fj7ywIjC4QFzLrUnM/zkYhFY1fVHes+gVa4yx+u2+bkr18PbSo0oGft+CPehSryKeHNwEqWlpurBmxzpUd635/GeV+kalAI0MLYvrhlXLIcCiuM6KelXKYcn93ZTj/Z/7LuONf4+oGfh3b21lm9t6+4laHfTf+zp60acG0GAA7Ab/6NWv6H0eF1fJqBD5ePUJ9RnOUYjsDPJa1PRFpzoVVVef899MDdC3OV6PSoUeBU6vA+r3Q0kiz0V3ZGQkrly5gubNm2c4PyQkBFFRUfZ4bIJQdMRcA366Xc8rMpZn2EfpK27swrBrlZIA/DxORyVU1nEIQgFyeZ8+tYc7cmlGfWm+DGzWc7pqBnjIe0Dz0SVuVdmm5+LUGt0NdvEAxi7Q5/P9vf5toMdjQNny+b8PdpyPLQWcC8mVmIVw5+lA63H6b+s6M/2yg78C10/rgxm+l3IzL80uBOO8/Jqm308Ws6GPLdqPv03S3bwwp+kMPHVryTfWsQv8v7CR7F0XCIOKoyqsOdmsiioWC7vOhSnXbpqIqQ43F7BZeNuz6L52CvhhNBB+DvDyA+76FajeOsdf+2Clzg+m/LWopPi5gcVa1/qV1PbS8GY4EhRlLsCZA045Pzc+7/XZTfXzVsZ2dSp5mk69UNXHPcuOKYtIzuKzgKeBW0HCLjpNzYoTfF5o6sVC8ev1pzDrv9PYdvq6ylbPCt+yruq1Q/+E+n5eap8Kk1oVPPOVHMDFlo/vaKMKV86/M4LvaHAkZk1ojwZ+3jnfQN/ngfALWma+aKI246zeCvmGPh70Nzq/RX9f9jGpQE2w22+YEj4zpEmO3fnJ3euoovunHefxQL8G+jOLhmxtxut5cY52StGtGT16tJKSs+PdpYvu9G3btg1PPvkkxowZk/9/riAUJeyuVGupi5Dbf8h4cMmD1DHfAN8NV8Y1WHALMHUN4FXwDpylGnbryOaPtbSJM7FC7khNBf59NN2jgPFUXBWnouPgYm065GXfmJhiK8flAcm2r4Gr+uAbTi5a/kqpNFfyt38NHPodGD0rf53p9e/o/FFK8W6ZU7gZpB4+QJ+nM57H//3ZjbqbwAMcGl3V76sPbrKbnaZ895dxQGQQcOcvQN1eWV6V8kIW3C5OZVSXjp1rHlBREst9d4ufPVwyXrbuWAi+2XjG7MIt2IApWu2KW4A6LSoTNYPqvmXRsU4F1ZmlfHRqz3pagcEM3qP/6tlreygYOHLEDnfsVaBCXWDC73r8KAc4K033cFfnMnh4gGncw4FgMdOsho/aHhnQCBeux6quPQtwFjGUPHPLDN9jLL65BVT2NO/XqeyJFYd0l7tDnYo66q2UwoL3sUGNcXvH2nh72VEluacMnfPWXMxIL7LLoZKXW4E5y/N27+5aB81r+OL+BXvU/3PE55vx3q2tlFlhDr8MjPgMiLwEBB8AEu30WUpzQtX8KAMMeFV30S34YMUxNdM+oKmfTaaEA5tVRc3yZdWCD1UGt3eonT6bzqL7+Aq9qFapPlDaO91ff/01nnjiCdx1113KaEXdmIsLpkyZgvfff9+ej1EQCh/GILDYjgmxXoTQ/IgyuTn99ezkT3cAE/+2nymScKN8MMrUNYsJNW1XZaEjt9DN16O8LgBv/gRodQew8UNg4/+0nKukv34jLwM7vtHS67gwfR7lqO0m6C96Yza55W36Cz/sDDB/GNDzMb2qn1v5+c65wIZ39D4ji5qNQJHD/zm798z5ZiF95C+9kaotgRkbMygeYmJidE53UiwuPewBr8q1gSqmTrcVtp66pg5WyYvDm2GiRVyMLSSnppmKblPRwP8Tu6RC1pgWjk6jRpHOc1vCwoBFN/OYVdFdu4s23ePnONUlTYbl/04YkcSCgp3t8b/a5C1AF2nO7RLOTbMr6ehQTj65e121hccmKjnymasxOHctBmeuxapTSqYp+z0aHKW2rOCMuEC1iKcyMqNqpzAj2zLDbvc/D/XAgz/txdbT1/DAT3ux51w4nh3aJPtYMTaK7vhRHysZPiJ5/c6kgoSGhCy6R3+l1Vu1OtwwrsHIOzb4Kcm3Vb0xoWuAMl6ct/ksbmtfSz/XVI7SEf3ESmDHbGDIuygplEnjKyof8Av51KlT6oXZoEEDeHkV3RxRXmXyvr6+iIiIgI+PD4o157cBNdsX3NxhcYDz0kXpSn1hp/4wsfVDlm7BcwZo0wfOUdLFV+Jt7M+xZcDPY/XBPuWt7Ozcudj+s4GlAX7ks0NkOfN4JVBLqo0oNsbu0PSrgu6clRhYcFMeZzhkd7lPS9nYEc5MQhSw/Blg74/6Z0qxx8yxfZTkyN/Aoru1pLb300Df51Cs4Jx50D7g1Frg1Drg4g6gfn9g/KL06/x6D2I8/VFu2Kvqx+gXq8BrxoosRzyCIuIw/NNNuBaTqCJ4/nd761wfsLLr0f2dtSjnnISDvo+jDLuYT5/Lv8y/JMNRkdPr8WbkEHxzoSbeGdMSYzv5F+lDComKR5e31iA1Ddj4VF89Z7z8WWDbl0CLW4Fb59rnjs5tAaq2sP4etuIz8NSvB7Bk7yWlqtjwVB/VxSwN8G9n4X32WozKJqdLuVGYXwiLUx1KPidrHu+txwGEYgVn+v+36ji+Wn9K/UwlCRcFchUrRlNKuprbcoxNVdzub4FVrwC9Hgd6PJrlVVn/jZ29TY03MGP8g9tyHu8w4CJRl7fXqAWhX+7tgi71TE2uk2uAH8foRfHHAm16fztCLZnvwD8W2a1atULr1q0druB2KP6YCXw7WJsflST4xg46oE+jQ4EvOgF7fiiax3JsuY6k+n2aPiC1Ba4g0hiJbqnsjPEgVrA/7t5A42HanZMLT4TSfsG2OayVL+iimrAIymwyRCdty+xzzlJ90RnY8pnt74XiBh835eF8XxpwxrnhYOCOBcBDe3XRndWXOV9zI7/QC2lUB3ChYlbPjLeXrVHdD7rgbjfxhtm3YgE7F1xg7P0UcM8y4OmzwFALlRpnAg/9hrLbP8TxB7zUVnb0x1kW3AnJKZjx4x5VcDer7oM3R7fMU4eouo+HOviPTnFFShmX9LxuIWu6PwxMWIKlUXpBiNLXoobFbOe6+gCahmqK5mPSF1E54pEXuCDIMRBLQz8bDsjpBD71u12q4Oa87Tu3tCw1BTdhV7RuZS/0beynOuKvjGiO7+7phPVP9sXR12/Cuif6YMOTfaTgLqawK/z0TU3UXLe3u4tSkQz9dBO2n75m2w2c3gB801dHPebUa2UziQqvfx8HEqP0wmw2v7P+eKgquGkgl1tTwvKebhhjihVjfJgZjjtRlTXiU8C15CwC5aroPn9eR1LYyqVLl3L7eISsMIxBOB+YUIJm3a4c0geyn7bWMhLKOfmh8NeDeu6r0B7HYeC3KTxa1tLy3HSr+aU/ZraeJzMKQsG+1OmhHWkZ2yZFd+4MAb+7WRfPfE/ZAr9cKT1OjtPF+twBQPAhOBQhR4BP2+hZdc5nGwcM7uV0J7fpcNvf481GAvdt0TPMVBlVzWgeahUWm3f8AAx+Cxj2oV0N6iiPZXeAnQ+7wkUGS2UDC5kRn8GpxS1oWDcADcc8B6e2d2b566/8FYj9F8KVuRAPDPOaIczcYsN5O9KrToaZZSFrYhKSlUqgOMx0GwxvXV2d/nPANBrERR5ffyApRktH8wK9CL7qBpzbavOvXI9JxLhvtmPD8VA11zzn7g7KNEvIWJDnqmsqFAl0lv/rwR5oUs0bV6MTcOec7fjmv9Oq25xjOkdiDHBgoX4PZXWd/z4AvuquzdJcvbTJ6oQ/svwO4/fRu6Zxoknd6qgZ7dwyyTSCRGNA+hMoeH88rqYXRAlS9+Zqprtjx44YMWIEpk2bhk6drDsPsrW+aNEifPLJJ5g+fToefNDGAz0he5hXRxdaFqVbv7jRHMdRObNBn1ZpYpqZdNMfCOzoM2eTc9UFLXFlh/2nsXo2rE5PPXuZ24NkOj9nXo0vLTLzuHD93Pnq1coCx+jSstPNL5rS5ridm1ms70fpeU/PSumRdznB55Pqjb0/ACte0B3e2b21k3evJ/Rcl63zlsZ1+WX+98NAw4E3vlcKgtWvaoM4z8pA0xFACsdW8mEO5FsTmPCn7rhavs7ZEbCcl6MkncUr4f11vT/bm+WB0uWIeITFJCI8NglhsYkIj0tCeEyiyuQNN/2szjddHhGXpF72NPF5sF8D3Nk5QHUY7A5N1pjxakPO6y87zqtsW750Ph3XNs+RRQacST58ORJBrrVREdv08yxk/fnLr9Lr+nOQec0V7JDZbA+GtKiOl/48rP6XlDKzsFPKCi5u1+ud+xtkBj39Jwjf3+ia469wIWLC3O04HRqD8p6u+HZSR7TzF48AwXHh++j3md3w/JJDSrnx5tIjOHApAh/d3jrrSDKqBG/+WC++M06MJqqMF7NsPP1+r26EkQamzG/K0bPhz/2XlEeAt4cLZvbJm+FZo6re6NGgsspu/2HbOZXbXVLJVdF95MgRvPXWW7jpppvg6uqKDh06oEaNGvDw8EBYWBgCAwNx+PBhdT7N1IYMyVsuqGDtP+UG9H9RZ71u+RTocA9QrorjP1XsqBE66NLkqfeTuqj6baouunmwzzlKfmAUBCwMFo4HIs5r11NKSfO7qsYuG2c5R311g9lEiUPNyD6pjadu+aZg7oPKDpopsdjhUT3n97g4E3ddm9hVNOXACulcPwN8P1LH6NC86O4/gSq5kH3xeWax1WCgnoGmW/x/7wGBf+rV5xpt9PVir+v4KWOj06jaPwXU7KDje9TtOelce8q9+V4vyFzwsHPAcZOzPR3u82MiYwk/nyyfQ8rMaaDYZSbQ/yVlNIZvb9IHK1Rk8PrZEBWfhEnzdmL3OZOhWy6hjPuVvwMxb8tZPDm4MYa1rF4ghj80Sp09e7bav/fee9V3vyXMY2ZhRZ4Y1Bi9G+X/e8kwAjuZWh1KVyCd7qyhM/6ql1Au4DbmyhSbLrexANCtfiVsPHEV/+y/jAf7N9SmhXkh+KAesyNcQGx1e46/cvxKFO6euwPBkfGo4euB76d0si1ySRAcwGX9w9tbo51/ebz2T6BKi2CO91ujW2T9PcDvdI4N8bv8n0cBn5rpx9ZM7+DnbNmKwE3v6PdXDt8nHCn6YIVWId3Xp36+Mtcnd6+jim4u4D4yoKH6+0oiufqrKlasiA8++ABvvPEGli5dio0bN+Ls2bOIi4tD5cqVMX78eAwePBgtWrQouEdcmmk2Gqjxme48bXgXGPYBHBp2v2iCQizjZxr0B6b/pwvXy3uABbcCt82zf4eM7SJ23y5sB9x9gTsXZVsMhETGK+lj5ZziNLgSzw8vHpBPXWVThInDQdfjH8aYohzSgPO2S/1yDZ1u+VpgsTbxL91BZEHHnHQa2AkZoSkac2ujg/Vrj9KwvKpFfKprB1QW2yy+WUwbi1J8/3zSBkiIsP67LL4NWHRzNswoErIxZck3u741ddL62K/gtsbFXfp+tn2hTKzU3BlVBex28+/LZlGUByvTf9itCm7GarE4YReOBy0VeFrWDeW9XFHB9LNvWX1awXQ9Hlz9vucSPl59Qhki0dH2m1qn8cyQpirH154kJibigQe0SmLSpEkZiu5r0QmY+eNuJKakKtfj+3rbJ9rFkJfvj/PDSO5IpzvHjO5LKeWLzTy3JTe3qqGL7gNBuujO65jML3fqha16fXVcUQ7sOnsd98zficj4ZDT0K6fml8UgTChJsLie0LWOGguY8eNupTaqXbEsZvbJxuyThp7h53VkJuNup2/UGd5VGgO3zgP8u9icCvPjtvNKScL898nd8tf86NvYDwGVPNX3Gb/b7upSwkxcTeRpKYGdbWZxSx53IcPOycDX9IwmI29oAuTI+XWUB1OWTOkru5eWlK+tu1R0D2Y3nK669oZyGmYTl3EGbp+f7QE6uzljZ2+Fi5MTFk7vorITs2T4x7roZqd+wW3AlFUF29krCnbOAS7t0pFqLKgo9eMKKv9vBZXPXbGuiqXg/6Dl5KUiK8/KPIzKDRbcfs2VuRK88xkBw9Xu5qP0wphyCm6efj4/f6KCgIr1teKAP7PQN362vI2RXwJ/zgR2zAG6PqiNvOwNfSAMs8mO01Cg9Hte+wv8eT8Qcjhdkk1vh2wKbs7APb5oP7acugYvN2csnN4VLWpm83mSBTwoGd22Jr7ZeBqz/zuN/RcjMO6bbejbuAqeHtIETarZx+3V2dkZt956q3nfgDPlD/68V8nj61X2Uk7lXJS0B0ane0tExfQFHC7SlqDZPrthUgEcSaqmTpklXNxmUJ//4yCOXYnCiStRaFjVWxfRnC2lMz1VIjl9pv06SRcKzJG/9dscPztWB17B/T/tQUJyqopcmjuxQ766cIJQnOF77OXhzZTy6b3lx9RcdZaeBUaGN6P7zm5KN1gl9Dqxkcj4JHy+Vo/9MCs+rx4eBvzumNi1juraz99yFuM7+xdpVFtBUQCDYEKBwgNfSj5V3mWwYz/ZdFMknKO2JsVkR5MzJdPWpruTsrtGCas9qNZCy26ZV0ynxCy4GBarXE8ZaRCdkKxWzy+bDGusQrMmds05M8MZ0J/HFa4pXEFD19mtX+r9fi+mm/xRMVAQUNlBJXPl1qqo4BablFIw9+Xo8GB0zDe6yzvpn/wX3JZw4Sjzl/KUlcDjR4HJ/wIjP9cdXhqP8b1FQ0JLWtyiZ6wjL2q5ekFwbpMeO/CpBTS6CQVO45uAmVt1XGC5asC4XwC/ptnOcL/+b6Dq+rk6l8HXE9rnqeA28HJ3UQc8G57siwldAlTXfN2xUAz5ZCOeWLw/+8+pXCyyL168WG3cN2DWMRcOPN2ctaOuh6tdZxZ5vHUszgeJ9QYAHSZnPDgU0r8PTRndO6J1d6pBMet0+3q6omfDKhldzLlQt+JZYMvnOl0hO7Z+rhfeaeo09uccF7AX7bqA6T/uVgV3vyZ++HFKZym4hRLPpO51MbWHXujmZ/+WU1dzzvDmdzKbQ3mA5m30HaEqifna9uC2DrWUiutkSLSSmpdEpOh2RBhj8+AuoE53lAgTtZwMVdg9Mtj+NfBlF2D3/JxjDzLD69N0hnPAxu/SFTubGTPOXU6Zv0u5RNItslHVcrgSmYDJ8yhbS8r6vryrAeMXa9n6hW06eqGkwE4iOxTMOWYEjL/JzKYgJOaMkrusY9iOOtU3L3zQmMe8AEDTutIO5f4G9BGgpLww1BW56Ty6emgvCuN9XBBwnvqBXcDIzwqmk26Ncn7A2AV68YFJBtnAjvQ8UywKs0yNYiS/VPF2x+ujWmDVY70xtGU19fH26+6L6PvBery97IgyX7Mn/x4Iwqz/Tpv/DtW9tCPsmrBbkwYn7O/1jY4yK+Y5rUVCTKh676ehDLaEm+TlxWim22B4q3QXc+WyTLVM5UZ6ROjY0ux/udM0/T0zZpaONswC3u6X60+qHG5mTjMvOD8u+oLgaNCAjJ//SSlpanyJngbZHlffMgfofG+u74ejlnM2nlH7Tw1ukrV5Wy7x9nBV71tifE+WNKTodkTYvcqPE29xgbMlPR+3XTrOL2sWdnQi5iz2nw+kdz9YeFnmCVOSzKggujHOHw582g54qwbwbgAw/2YgVHcHssOQT1IW5+ftrlxP503upPZ53n2cZUzOJraHHS/GBpH9PwGRplV+RyY5URv5kR6P6MLGKLpzEeFiM5SVcmbYxQPbo/3MZzOaCPOGAW/XAkICUarhvPUnrdNl+KS4yrJYdNOwhe9j02KK3eGYSDbKlexgXAkNaeIS87CQk8Nz/vuei3jbFK3ywrCmBRJZxA7xl+PbY8nMbuhUt6Lq9s3acBq93lunOhPxdlCI8EDuyV91d2R673oY2lIXVPbGKB5PhZSgiEx7Y/oeS/bxV7nmjMPKS2RPQTOwWVXlsH8qNEY5HeuRFVNmN80Vs4OKGXq6NL0525GN1/85oqS1ZEbv+nj/1lYqCksQSguUaH94ext0CKiAqPhk1RxigWxvPl17AnFJKWjrXx6Dm9tRTQdgYrc66uNh7dEQlXhQ0ih2n0hffvkl6tatq2Rs7du3V2ZtWfH7779j4MCBqFKlCnx8fNC1a1esWLECpQYWmez40sTHEWGXmfNctpo88Z1463yg/8t6jnjfj7qY/rAZ8HoV4KzJCZ2wENv0kZ4bO7tRG0DRhIUkRAKbPsyxU/76P4FYf8yU6zmxgzJh4QENi2/OYm4+eQ3P/n4w+3xEdvFpAMYDBuP+HRk+n5GXtJS2tSmzl8YbxnNOl/ECkJajWkvsv5z+/HF+VY0kpKVkLDZLG1zI4eITn/f9P9v8aywqH124D6O+2Iytp66h0KAxGw0Ra3XSi2f2drnPA3z/8jmY/sMu9H5/nVpoG/7ZRhy6lIVBXB5YfyxEdeDItJ51MbVnwZortvWvgIX3dlGzrFTnsNPNWJn+/9uAORtPq9naHHNdTcTGxqJmzZpqC74eoToosYkp6N6gEp4c1LjA/gZz0R0arSXIdKUvCC7sAA79BofEJC0P99Ky0nqVy9ltrt6esIPVx+Rqb87sZv4uObX2xu8Njs5xhMmG1ygXvh9dtA/fbj5jXtB6ZkiTEjkPKgg54eHqjG/u7qAWYGlyNnn+TqUOtBfLDwXj5x2M6wOeucn+77O6lb2UqRr5bsvZ0l10R0VF4YknnkCTJk2UW3n9+vUxdOhQvPnmmzh6VK/g54eFCxfikUcewfPPP4+9e/eiZ8+eKnbs/PnzVq//33//qaKbTuq7d+9G3759cfPNN6vfLRWw48iO7/JnS4/EloVWz8e0QRTnQ2kGwSKQxRdziQ2qtQI6z9Aup5xxnfgP8OAe4Lkg4JlzOvYomw+L+ZvP4Lut+iDv4zvaoFUtLd0jnMH8fHw7ODuVwW97LuKTNTlkyFLqyygyRza9I3yNcSGDdHtAy4UNeS0jXJgBSVM6e0L3elKjLQ5cDM/Y6aaJlWHIV1pZ8ZxeROJzwZgPG2Am9Pg521S+Jw0COSP/2KJ9yom6UBjxuXb1r93JfrfJ6LL/NQEWTwISbVsdZ9d34c7zav6Zz8GKw1eQmgY1U8aOHBckvlh3UklV8wNfqzMX7EFyahpGtqmBZ4cUTgYpD4b6N62KZQ/3wnu3tEI1Hw91EPbGv0cw8KP/0PXttWr27899l9T4TLZZ4pcvq+3pXw+o7gMXHz8d29ZussLsHMx9z64A3qkN/D6tYMZX5g7UUZxGfKUjUaUp0GEKAr27Fct5bkuGt65hnutWCz50S6bZY2oScOSfTDGeE/TMN9Vq2RCTkIyp3+/Cn/suKz8DflcX9IKWIBR3mHIxf3JHVPJyU6N49/P7JyUbVaYNhETFK3UnXdL5ncgOd+d69k3KsIwPI4t3XVAjniWJMmm2LnczAXL0aFXQTp8+XXWXuQL+1FNPqeKbRffw4cPx1VdfqezuvNC5c2e0a9dO3YZB06ZNMWrUKLz99ts23Ubz5s1xxx134KWXcnDENBEZGQlfX19ERESobrlDwQPNT9voeU46A7cdD4dh86daBkrDJ9eyarWa8rNc//0Xd+ri26eGLv6c8l/0rTsaginf7VQH4Fwxp1TNGj9tP4/nlhw0zzUasyglFn5U8MB0x2xg9CxtGFfQUMVxYhXCa/RAmwWpap3E+MQ6dEciyv05CajaErhvE0odJ1cDP96iVR/3rk83tMsGFl13z92uikrfsq7o38QPS/ZdUs8po6ieHdIEt7WvXSy7Zdmy+ROVVawW2xg3mM2CWlBEHH7Yek7Fq9AIhpR1dcaYdjUxqVsdFQnI9/WyQ9qosmOdCkqyV7uiZ64fFgvUW7/aojK1ezSorFQyuf6csxNUN/yy87yS7W0/c/2G0Zim1X3Qq2Fl9GhYGR3rVFQdE5KSkoKDBw/i5+3n8MupMnB3c8WvM7pmWIgsCKg+4GJIv/JX8G38o4BHeeDps/YdnQg5CnzZWe93ulfPjjsgXDzhDP+jAxrh4QEFGJOXD1ggt39jlfLl+PuBHmhZyxf4731g7Rt6HIQL6SrG8yHtG8KZ02nrslys5uv5zjnbsPd8uDLz++qu9nbJiBeEkoKRusP33NiOtfH2mJa57kyzRFy86yLe+DdQxe+x2TS9Vz081L+h+TvC3qSlpamFYRqqvTS8Ge4xGcQVZ2ytJXP17b9y5Ur88ccfePbZZzF16lQ89NBDKrPz77//xpkzZ1CtWjV07NhR7eclC5Td6kGDBmU4nz9v2WLKcs6B1NRU1Y1nnnhJgh0omuFQ9pgBGiVxJpqse9Nx3F1ZLPMA+eexytiMcsfmLy/HhyuP5a6rxL+/0WCgVnstW7VDwX0kKBIP/LRHFdy3d6ilPlyy4s7O/pjZRx8QPPPbAWw6kYPbIrNmD/8Bh4Uf1pTL0zSqMApuwkWZwW9ir2t7s+SU8iNyAPXTZe02djdLDHyvG+Z8ne+zqeA+FhyFMV9uVgV3dV8PLJ7RFR/e0Qa/39dNFVzhsUl4+reDuGP21uwNWOz5OUAJKX0C8qvA2Dk33XTJykEFv8SZ28sYoR7vrsOX60+pgpsd2+eGNsG2Z/vjzdEtlSEYuwRfjm+nFtI4RrLzbJjqhnMmOxdr1KozcPe321XB3aKmj3IqL6qCm9BQanL3uvhhSmcceHkQfpjSSX2+NavuY/7soznahLk70PrVlZgwdztmbTiFo1eiEeZRA4vOuqCMkzPeGNmiwAtuUt9Pv8+3RZRXRmGIDwdi7TwKYZm4cHRp7s05iwk8OC3unW467fdvUjWjxJxz3c7ugFs5rTpgFCULbi4k3vJtlgU334dP/3ZAFdxcLPxpWhcpuAUhE21ql8dn49qBa+i/7Lygvvdyw/lrsbhr7nY89dsBVXDze+yvB7rjqZuaFFjBTbgwwAVw8t3Ws/lWmxUncnUEULVqVcTEWD+49ff3x6xZs3D//ffj4YcfzvUDuXr1qlpR531kvs/gYNuisf73v/+px3f77bdneZ2EhAS1ImG5FXc4j0ETHBr88MAoA52m63gcSqzZgbTnATG/BAsCZgMiDajcWBXLv+25pNwWP117UsVxhcfaedYzFwfJU+bvRExiCrrWq4Q3RuW8KvjEoMYY0bqGko5SenM0OIvXE2MZPu+gM33zOHtapOR0MMrLgw8BO77R8kA7c4Az3ABa1fJFa3ZIAOy6Xhbwrq5HC4L0vGyp4b8PtAu/T02g77M5Xn3Hmeu47estynm/oV85/HZfNzQyOU5z/vfvB7rj+aFNVceIRebQTzbi3eVH82YoZgt8vcwZoCWkh5fk77bY8Q8/pzuhLXSetEFCcgp+230RIz7fjFu/3qpct/kF3qVeRXx9V3v891Rf3Nurvoo1soTveypXKM1mzi8/gx9btB8P/LzXps8nXp8mNheux8G/oifmTeqkZOvFBR4w0Tn92aFNsfThntj1wgB8MraN+pspQ6cB28YTV5Xx27BPN6m5QP7LuNB4e8fahfIYq5Rzh7eHC2LT3JHsXSt94dLe89yWHiMJhbDYZC/4OXtpD9ISovTcu8VCRXEl3cXcJDFnUf3UaW04SnPF5c/oK9K3peGAbFMA/tqvJeWz7mqvigtBEKybGL4york55nHJ3os5Pk2UorPmGPTxBuVd5O7ipFRwf8zsjuY18h5xmRuoPPPxcMG5a7HKE6VUFt0spu+55x7s3591rtv48eOxdu3aPD+gzEUOP5htkUP8/PPPeOWVV9RcuJ9fustxZihTpwTA2GrXLpwDiPwQUMkLQ0wOsfyyyQDnavs9r/c3/k8Xy/ntGq15HXivHvDPIyjoqLDrMYnmhQS+sTccD8XNn2+yq4mRLbC4mPbdLlyOiFezhDwgt6UrRRnu+7e1Uk7BUaYD7eAIK26RlL1WrA8kRmu3aUeCB0cLbtXzdZleX/zfcf6d7rH4YRSw9Il087P8cuWwlrPHR5jnuVvV9EVr0wFWqZ3r5v/D8C8Y8i7gnn1c04rDwWq1mivVLCDZ4aYpoCWczZ3Wq56KnOKXNBeRvlp/CgM/2qDGLewOP9PbjNP727/KX4eRCz2k7V2Am5aAUzr98erj6P7OWjy+eD8OXopQny93dKiNpQ/1xC/3dsVNLaopqVx2+FfyVIZkTwxqpA7wWbTf9PFGbM4mQ5T3PeOH3WqWjjN139/TSUV6FWcoqaebOrv7W5/th9WP9cLLNzdTOcdlndMQfXA1Kl3aguduKjzpMr/3DTO1cE+T2ebV4/a9EyZM1O4MjP9VR1I5UiwZFT7f9EXaJ22UUzFfynUqFe+iu28TP6Ue4ZjLXn5+E6qmwi8Ai+4GUpP1wln3rBs3PEbggiDha7Sg5koFoaRwd9c6uNek2qSh55Zsvr94TDfmqy3KeJOydDagVjzSC9N71y9QD4/MeLq5YFwn/xIXH5brovuWW25RruI33XQTvv76ayXptiyKWfzSZC238HecnZ1v6GqHhITc0P3ODAvtKVOmYNGiRRgwIOvVUUJpPDX3xnbhgnbhK+7M6KVlVlzdvRiWyQW71R3akISz3XTlzg8smjZ+oDvR+3/Rudb2xjCsqdsb209ruSC7b0tmdlddIXaHbvlqi5pRKwxYMD6+eJ9yxKZU7duJHW/ofGWHu4szZk9or4r1oIh4626RfI8YM/d7f4RDQWUCu4mUAqekm1okpaRi6ne78MrfgVgeeCXdxdxeed27vgW+uxlpG97DAdMiTMta5c3S1v0Xw5HWYKA+SKMpT3GiIGWqfC2N/krPcTcZnu1V6TtgRNsNaOqHH6d0RnlPtyyvT7k1nU/5eq7h64GLYdr9dOaC3dYXk3Ixz0nH7NhEi/dF+8laWspFGsuOY24j5fjaJEYGOCNN1pzAx6tP4Gp0ourcPjm4MbY+2x/v3toKzWrkrrDigcYD/RoqdUC9yl4IjozH+Dnb8cY/gTdEcPGzhPO1m05eVaqBeZM7oo5pHMJR4Pd5Az9vJUXnDPqWp3rj2tKPsefHt1CmkA07jaL7kkvtgim6aQg5ZSXQcCAcDlPXP6qcPpim50BBSj7tAR/fgGYmifn+oIyGmTx+4eL0iM+ynNs/ezUGD5rGvzijelcXG5NPBKGUQ6fxYS2r6wzvH3ercTNL+F32wYpjuPmzTUpZSJXRO2Na4qdpnYvsO2xC1wC1mMjv00IZeSsEcr1s8dZbb2Hr1q2qS/z4448jLi4OLVq0UDFflSpVwuuvv47338+9GYmbm5sq5letWpXhfP7crZt25rQGi/xJkybhp59+wrBhw3K8H3d3dzXkbrk5AjQdYUQLpZFzN2Wamecs84BXgIDuQLNR+bsjytW9/HQkVEqC/buy7NDxwIkzW3W6Y4sprqhb/UrqYJgGK30bV1HyRh68vvDHQSURLUg+WHkMSw8Gw9W5DGZP6JCnDxgWMt9N7oTK5dzUSiHdIlmUZqD1OP13n98CXMvdbE2RQgUFaTdBZ8SbYNePHQuiFk+MvO7z2+xzv6aOeUSFlgiNSlBdSc6fNq/ho7qOLKguN7gDuHVu8Tpo5mIVlSKUgBckNdpmeXBKhdAnq08oQzAeoLLDS/UG53ptYVDzaqrrzXgrPu98fwz4cAPmbT5jdb6K98f/0e5z19XsM7vMjy3cpxbPOryxGs1fXqGMUcbN3pY+F+1VGWh1W3q3Oy/smqcXCBsMMM9/8vPipx068YKS+Y1P98X9fRugolfWiw22QIXFPw/1wPjOevV9zqYzyuHccqTkraVHzLJXGjsVxuxzQVPW3VWllHDjwnhhYjiYn0ipXjDyckv4uuSYCruuDpTRfcVNL0g0MC1QFHeGt9JGu0sPBmmFFGk2Epj0j/YLMalVMsOF7Gnf71KKnXb+5fHqyOYSCyYINkJV5v9ub22R4b0DV0wZ3jvPXsewTzfi83UnlcrtpubVsOax3hjbyb9I32O1KnhiULNqJarbnachM5qlsbtM87M9e/bg+PHjajaa3ep+/fplK+/OjsceewwTJkxAhw4dVOb27NmzVVzYjBkzzF3qS5cu4fvvvzcX3HfffTc++eQTdOnSxdwlL1u2rFoUKGlM71VfzVf8suMCHurXUBn+mGHRwS23bxA1i3sg3YjJrwnwyAFg+yxg9cu6gGg/0f5dbt5f2QrYelrP4natryVi7DDPndgRn649oaK4ftx2HocuReKru9qhum9GSaw9YCSBYS7xzhgtE88r7DTwsY+dvU1J4F768xDeGm0xF06H9fr9gZOrgH0LdEZ5cYey7dPrdBRYt4fMZ7Nw+npD+sIB54DRweh0b9N+AIx3yys01wrWzvAH09jJCVUzyEbR2Liat5LvUmLO7myx4fQGPbdPmeTa1wEXd6Dbg/a57Zhr2oCQ4yR8LWUBi2K+9hZs14Xng/0a4LGBjXL95Unjo+eHNcPotrVU8U4n1Ff/DsTvey6p2V8uuJy7FqNmri5cj1VeCDlBNQldqbs1qJxuAkflR+BfQMQlwLdmrh6jig/0rqY7ZCaWHQxWYys0i2P0iD0lcZS80XCNsmvK9I4GR2HEZ5vx1E2N1fPOQpy8d2urEmPs5OHhgX///bdI7tvodG+Or4PbqIywZ8zc9TOAZ6V0STmNCXfNBXo8Bgx4GcUeU9f/dFqNYm+iZkmvRpVVF42KkV3nwtK/cw2llBVYnD+6cB9OhESjqo+7WkCkwkwQhNxneN/y9RacDo1R45AcOfthm47H5RjUayOam8dZiwPTetVTi6/sepcE8nU0wu40i10Wvg888ADGjh2b54KbMOrr448/xmuvvYY2bdqoHG5mcAcE6Cc7KCgoQ2Y3jduSk5OVeVv16tXNW16M3ByBng0rq05fXFKK+U1ihgfUlgfVtshbaej12xRgdl/g7Ob0813LAq1oRldGd2V5cGIvjHnfur0REhmvXFf5sDvXrZRhRe6RAY2UzJtGCjzYp+SFB+v2ZNvpa+bILxYmt9gh8ovdsE/HtVWSmJ93WHGL5Nwp2feTY2SrbzSNK/D1UCH9Q4+LCiw4PFz1Rwi7fZEVmgGuXtpl+KruwuSZkMNASqIyx9oe5mOe5zYwz3Vz1psFfuhxXbQVJezCLZqgC26aBJKVL2g3Xnuw+iVg3486izoLKBGjFJwFN99Xr41sjscHNc7XajUVKHQ4f2NUC3WwzPnol/86rPwlmG3N1wELbt4FJek0KWNnnZLuz+9sq9Qr+18ehLtNX5rztlisWFdrAdTpqc3w6FycW8pWALreD9TtaT7L+Gy8s5N/gc2gMf96+SO9VORaYkqqyr6m6Rih4cyYdiU8PrCQaGAyBlsdVg1pwz8C2txpvxv/60Hg3QDg0O/65wCToi7wD8dwMTd1/Q8kVMuwQFHcYbFsdK/MLuY5wAX4VYFXlM/KrAkd4OfjUcCPUhBKcIb3JK3KDAyKNH9f8jt79aO9i1XBTbgoQLf0gmi6FQVFl1+SBTNnzsTZs2eVyzgjxHr16mW+bP78+Vi/fr35Z+6z45Z54/VKIjxwnt5bz2/N33LWurNwXBiw4nlgoam4ywoWKd/0Aw79pov1ayczXs5OGuOhKtTVzuj24qZ3gAd2Ax2nYqtpnrtpNZ+MXXsL05V/Huyp4owoJaYZ1Oz/TuUqticrTodGY/oPu9V8Cx1VmW9aUG6Rf+6zeP4aD9GFQlJswUol7ZVhe/QfvfjS49EMF83aoA397uocoObwqRLcezEaqNVBX+GcbTF/OS7O1GiLA5e1fFfluppoY8x104yHua5fdAT2/oAiZdNHei6xViedFU0zIDdvoGLWsXM2w+fT8AIY+LrVq0TEJeHuuTtUIezm7IQv7mynDFTsARfCOD+55vHemNAlQBWbjPSgkdG3kzpg9WO9ceS1m7Dl2f7KpIyz05R0U0rK/xszwY3HsvrIFdUZN9N5BuDkYpfYt8OXI7D7XJiSd9/RqWBNMtkVmDOxA94c3cK8+HRP97pmwxoh//hX9FLjDZQWh0TZMRUhJVmreNJStZkaYfwkPQboE0ATx+IMH7/pO3trhF6wru8gnW4yvLU+sOfYSk5xQMsPBamim1A5Jk7lgpA/aBA619TUCqjkiZ+mdlbf2bnxMhLyRvHJMBFsgkYILORocPTr7guYkPmgmu7S27/W3TZKueumL1qY4co+V/nppM3Z7dvmAwGmeVxLbp2nC0R7znTwtio3ULtbTx0wz3Nn9+HALtvzSw7i972X8NbSo9h/IUJ9QOQ1gicsJhFTvtulipS2/uWVYy+LCnvCAoOFxTcbz+DJxQdQ1YcdwEpabnz3n7oTSuf54szmj/Vp05szGJWx0OWCCQube3rUxfXYRJy/HoudZ66jN+e66U5PiXnHKXm/70t71ElajXY4uMXkXG5RdLeqrfcPXoxAaquWevWwqB3Mh3+s55S7Pqj/twNe1eZeFfJZ+FJq/49p0aPdRMC/8w1XocnZpHk7VNfZ290Fs+5uj271c29omRN+3h54fVSLPP0u5a+9GlXBf8dD8f3Ws0q6bl6IeuSQig+0mQs7dbxQ15lAi1vMZ3MchdCZnI+1MBZCx3cOQK+GVXAiJAp9GvmVuDnT2NhYtG6tx4+YXOLpaX3mtiBgZzOgoidOX43BmcshqBoTpiXhvvlUElw5pBc+3X3TVSlMAaA3wLF/gSN/aRVGcYURealJSHMpi31R5Rxqppt0r19ZLcRdjU5QfiDmcZNM0OyJUX2EoyIcaxEEIf9QLbjj+QFqgd7ex7+CA3W6hexR0T49dSdl9sbTKk8vAzQTMlx8Of9pmbVN5+nlzwK/TtYFN2WdMzZaL7iJZ0X7FtyZMDrdxjx3VnCOlwYQr49srszO/j0YpAyMKE3PTmbL7FLKoH/cdg7vLDuK+3/ag5FfbEafD9bjzNUYNQtM47SCcnx9dkhTDG1ZTclPaQpnNo3hPHtxL7hJn2eVIkHNzVpgxNaNaFNDRU91rFPRbMahZOgTlgDD8+mif3mfOrnm2wxhsUnq/845boOGft7KHZqy5ouepk6V6lwVsizU8v5c3ICBrwHlTLO8fO9YFtxXAvOmANj6GRB6FPCsrA0TM8HXOQ3LWHCz+7pwetcCKbjtweRu+vn4ZecF5WhuNoLMTcFNdn4DXNoFnFid7tEYn4Q/9mpVCbvxhQn9HPo1qVoiD16oLDp58qTa7KEyyi31TMVklf+eA2b1Avb/nP8bNdzyqcyx9J6goRcp7rGOXCAY9CautJyBNDipyDdH6lJxMYVmTeTvAxYu5haExyYq47TYxBS1ME9TREEQ7AePfUvid1ZxRjrdDsjtHWoruRWjtZYdCsbNrTOZKvV6Ss8MU6IbuCS9E8QDiW1f6n3Khfu+ADjb8BJITtAH/YbZWl75+xEg9pq670teTZUBE6WDtpiXsXvErn6zGr5qZpUFNwvvZ4Y0UQUZnwtGqV0Ii1Md5pykiJxnYRxOQebnKrfI29pgw7FVSpmw72I42vlXSL8CD2BjQoFyefdBKFA4wz3M5FxuEdmy7FCQ2diPdKyj/ybO3if6doabyUU6X4z8TBXRe9OaUFutRgwsjXP4umlRwxc7zl7Hzria8Hdy1a8tdoDy21nODYzoo8HZoNd18ZgVIUeAeUP0HP/Ev4Ca7Wy7ffopbHhP7w9+Uy+EWUCnbubL09SsbmUvlQnNArC4QnOxOpU8cfZaLJbsvXRj5A+fJ2JIfq0RHQocXqL3O001n71kzyXld9Goarl8GSIKNxqpbdq0ybxf2NT388LqI8AZ1IT6ZLHHWM5FU9Fdu7OSrnORloUrGt8E8LOE33ccr6GxaHGE3xndHsCWPReBrftR3+Ty7khQYr5w1wUlH6f3hKuF/wKbCQ/+vFcpqGpVKIvP72xXqBnBgiAIBYF8ijkg7PxONMnK6SB9Q/eBnTbOk5I1r2l5KmHxTXnq2J90x8yWgvvqSeCDRiovGUl5z+lVHXcW/ZTtpSSaTdFa1PSFt4drrkwV/n6whzqo5sHSC38cwtO/HVRRB3/su6zmOY2Cm53QxlW9VT4x509fGNZUuZ7++1APbHyqX4bOaUH+r2i6RJYdtMwl3Qt81g74YQyKHdl0s77ZeFrNb9O92Xj+aOBTwdNVxbwduqzztO0Sh9VxKnZd04VsSwsTNYPWJon5vqA4oFrLDLL0QuHwH/r9te0L4ETGqMMb4EIAH2NiFPDjLfqA3hYYO5Ycr1Upre644eKv159W0lsuHi2e0bVYF9zGQpQx201figyfXdu+Br7sAqyxPrNuZu/32mSvRjugZnt1Fm/HMIRhIV/SJN5FCWPCunfvrrbCjgwj9SvrTvehBD/7ZXVf2K5Pa3fEhLnb0ff99bjM+EMPX6B+P30ZZeYFwfEVWvViBwy1l6M4l1vStV4lVPJyU0qmzCap7y4/io0nrqKsyW05v3F/giAIxQEpuh0UOgHzC4mxSQyOv4EuM3XedthZYOvn+jweiI74FGiSc565GZpAuZXTBlHHl+dvhi7uur6tmu3NX7LZzXNnBWc1F0ztjAf6NlAdUHbP7urir7reNI/68/7u2PPiQBx+dTBWPNoLcyZ2VMZmU3vWU7OezWv42pxXbA+Gtkw3jTEXGeUDgIiLwJWDQJCeWSs2rHoR+GX8DQeGzGFevPui2p9uYRbFAqeDSWK+ixJzmhCtfBHY+kW+HwpntjPPc1t1MDcVX4U21837WTI93QiMHbLsYCLAuJ/14+T74PuRtqUCDHlXR7UN+/CGUQ+OSHyxXpspvTi8me7UOQC3dqgFLzdnVTAwAtGMudhZmvVzQ6WAyuZml3ua+extp6+r2+NC2+i2uYwdE4o17HST7ZGmkQl2uvMjc48MAsI5+18Gob4tsfd8OKISkvGvIXPu+bgekbGISLQbp9YCP90OzLtJKzbyczvBh3A2JMyhnMstYeea38eZXcw5IkIvFEK/FX7HC4IglASk6HZQ6PZ9R8faGZykM+BeDujzTPr8Wl4PUjjvpuLDWN38kufHq8y1SEA3pDm5YOupq+bV7rxAKdoTgxtj2cM98d09nfDGqJaY0bs+hrWqrooxrowXl25Xn8ZVVJFBCTBzihWUCTcZrvcNV+riAI34dn6rXcszudZ/t+UsEpNTlXtsZvmuITFXed101d3yqR5xyAt8PnbPR2r4JRVPRVrW1AW2Ja1NDuZHgiKRVL1t4XW6wy8AP4/THeiGg4DBb9k+hzn+V8CvGRAdDPwwShcA2f5OOS1dr5LRXZ+LN8zi5v+DUYI3typeMR/Z4ePhajZEmr/Forjm38gce6QBO76x/stc+Iu4oA0em482n03fBsKCOzfKGSFnGMu5ePFitXG/sKln6nTviiqPtDLO2o8kKjjvN0g/jaEfKDXY7uD0BJClprEZZVTIBSBnO7+O+B28/h29z0VsLm7m9XYWTQK+7o6E4OMO2+kmTDcgyw8Fq88yLrI+/Zs2WL2/r/4+FwRBKClI0e3ATOlRV822stNtdAQzQCk544WMojmvtB6rT0+uyvvq/GlT0V23t5rTuhwRr2axO5iKtZJuVtHPJDFfaikxbztenx5YlD/pvj3ZPgtIigGqtdJOviZoekXHacLFjcwLGpad7rTaJndtdrzjtPN4rtj8CfD3w7hyYhei4pPh7uKk5nQzw1k/Lq4w9u2ERyug15O6S1WQJEQBP48Foq8Afs2BW7/NfpY7M1xsYReNUXxUobDw5kJHZs5vz2iCmAmaD1F+SUOi10e2KDYLTLZyt8lQbc3REJy/ZhEf1uU+fcr4Nz7XmTGK8bYTtHqAL7PIeKw4rIuwG2bEhXzD+M7bb79dbdwvigVmypCT4IJEb//8S8y5YEOVxMBXsee87hQTdryVxLyg4GO+uBNwplS6jDaEY8JIbuFnT0IE0so4YWt4eYeLC7OEi7ccjYmMT8Yf+y7h3h92qTElji89PjA9MUMQBKEkIEW3A8P5TaPDNeu/UzdegTPb3R8CWozJlQs5Yzpun7UVv5qkxCouivOTjCFjrndu4Uy54dpcrze2mKTl7Jh6upUOL79hLbWMjhJGs8S8Xl/ApyYQH64ltUUNixzGzREWrxavGbpN88CoXmUvlUOeGZqasTjmfN6puHKmbOo0fZCZG+IjzUZJ+1LrqtPmNXysmuiw0DRk5zvDvYF+LwAN0xcK7A7/b79N06MSHN24c6HuXucW72o6Ns67hnYkZ0a1JZz3p/yUW6JFQWqCUXev/a2l/xyxqFPZ8UyUKIflWAifUmMxR1/QH6jUAEiIBPZZcalmMgNjEC3i6H7ZcQHJqWlKbSFSVPvj5OSE3r17q437RYEhn77uWcd+c92A8gAhjD80Oq6KqCvA8ue0osVe8Hv0gV3AyC/TE0b+eUwbleYG09+e5OOP2FQXNVJRw9cB0jCswKYBY1AJO9xBEfGoV8ULH49tI67KgiCUOKTodnDuNTlIs4N67lpMvm+Pzt93f7sdO85cx3vLjyLFiLlqbTr4yEtcC+df2T1lvqpfc/M8d9diGmtUEPRp7KcOjigxP2CoEtghbXNn8ZGY7/pWLwBUaqizuU0kpaRi7kY9wjCtVz11oJQZdly5iGKe62ZeNzm/NXePQc23pwG+tbErVBejrUwycmsYEnM1113QcBGizTjdKRv3C1Bej3fk2Rl+8lLgrl8BD5+MM8t0+U9LVc8B3G40RvtgxTGVb8uD0+m902frHY1J3XUBRQfj9PgwJz0jT7gAlLnb32wEMPFvs0M9X5s/7Ug3UBPsT9myZbF+/Xq1cb8o57p3+Q7SsXwB3fJ2Qyxw6QlwJRAJSclmhZjx2jGSGdRCGF9/2fkL5AUmO7S6Dej/kl64o2FkUi6766HH1Em4Z13zgoSjKV0sGW5qHHABztvdRRmncQRFEAShpCFFt4PTrIY2EmNtPMdkPpJXeCB/97c7cCVSr7zTBdzsKkrncx6IBO0DrluZIc+O1CSgVkc1J5dWpoy5053XeW6HlZg38btRYm4U3TTGicg4Q12oUN6+5fP0ODkLyfTf+y+rcQAadWVnUpWe1x2WXnSfy2XRzS4vqdHGfEBszbncwCj0918I11J2OgMfLUDVAHN8HzkI1DIZt1mBBmfPLzmIAzktBFSsa5ZIKxiDte0r/R5z97U6K85Yth+36yLzjVEtMsSoORq9G1ZRMWccIfjdlK9tXuDj38+517DsP9PWHLmiPq8YAWiYMgklD2Oue3laF53MUbV53m6Ii3r/PKLSOA5dikRiSqqSrhuLV7vOhalxBXhVAur00L/DxI38oozbLChbHpi5DbjlG72fG0xKoIvOetHPEePCLGGMJhVUXDf4ZFwbhzSFEwRBsAUpuksAnLEli3ZdUIVzXoiKT8KkeTtUwVCzfFkMbq4lxJyzUvAgZOQXwP07TdLhXEA56NTVwJhvcCo0Wj1GSpHb+ufyYMPBMVzM/z1oITHnc0lZNLt33gVgGsMiloXowV91J5vz0mvfAJY9Dax8If16XEhhAcjuqoUHAB+nYdR3T486avEgK4z5/J2WnW6qHHIjn7ysjdBSq7czx48Z0WDWMOTlp0JjEHt8nXYGXmejsZmtcDSCTvMG2UjK6fDOCKIF289j/DfbcchkBJcj694GFk8CVj6vfx7wEuCdUcbP7FoW83zpjGlbE90cXCnC+LCJXXWHcf7mM+nvCZrH3b0EePSw7gwSjrUwr5yyXwuMmDCaSjryAoRgW6f7lCkiK/9RYZ2x57xeFGsXUAHVfcuinX959d4y/AHUAhth1GV+oD/Dx62A3+/NaGjK79S8cFV3uo+nVHNoEzXLz4GF07ti1aO90a/JjaNLgiAIJQUpuksAXepVROtavsqAhA7TuSU+KQX3fr9brfxz1f+HKZ0wpUc984wbLzcbqmVyUc4VFl1u5m1nV8CVRPo29lMxbxfD4syu3AoagNXtqaW1+YEHdJmlkH8/rAvR36YA/zwKrHoJ+O99LZ20dBev2gwo7w/0fCyDa+/646E4diVKua+P75y9fJcHr+xW0CjvimtNPa9M6XTmLo8Nne7LXk0Qm5ii7reuqctljUrl3JWhGglEA31mSKDVWeg8wTztn+4AvumvM+uzge+Tad/vUv9fPg+MIaJy5GSIFUOwzFAJ4mR63mt2ANqbZj4t+G7rORUR6OPhgueGNUVJ4Jb2tVDO3UUtmmSIPmS0Gl2mjdf1xg+BdW8CBxeZr8IFPEaOcdphXCeTwZZgd+Li4tCmTRu1cb8oMLqfZ65GIzX4MHD4j9zLsjPlcxsmavwuyhjtaFIiqRGbMnrhMDefYZn57z09MuPibt1bhWkIjGjk35SLTveeWK2cKgmdYZqpOfrigSAIQk5I0V0C4DyX0e3+fuu59PlIG+DM9iO/7MPW09dUgTN/cifUq1IOHQIqqI53dEIy1hwJufEXbY0gi7mqZaIm8pPP7egwG9yQmLPbbVc4C/zv48DXPTPmfldpqucGqTZgRBmlu53uBXo+AfR4LONtjPwcaD85w1lfr9cGfXd29odv2ezn7DiH16Sank/edS4cuG8L8MQJoHJD2/4GysPp6E2Do0Rd4Dev6Wt1htxaXveO6x5AuWpAWgoQrGNn8gVdxblgQVMvKhKymeFOTU3DY4v2Kfl3eU9X/HV/D9WFvx6TiLvm7FBeCdlCA7ixPwHNRgFjZt+wABMUEYcPV+oO1zNDmjpMJndOeFvGh222smDIme7d87V5nYsH0Mbk+A9gwTZdCPE9VavCjbPvgn1ITU3F/v371cb9ooD/XzdnJyQkpyFt/nBg8cTcm6nxO4vxmdyt1UlJyS2LbmM8gX4mVKygnB8Q0F3/7pG/8/bAL+4GTq4GGHWW+fPWYN8CHdG4/Bnrjv2ZGfoB0vq/gv/CtdJFilVBEATHQIruEsKg5tXUfCSdjek0bQuUc77wxyEsPxysDmhoYNLSJNel5GtEmxoZJeYk+CCw6G7g74dse2DMa363DrD+XVWYsLgnXUth0Z25m2KW0xJ2qCn5pmNuXuaxeRC6a67OsLUsusfMAu5dr+XrYxcAo78Ghr4P9H8R6PZAxtuhOZVFJ2bv+TBsP3NdRbvd00Ob9uREJ0uJOeXRuTH44WzjU2eASf9iT4h+blplM89tQJUHOXAxUndICbtT+YVy5vBz+nm540fdqcqC91cew9KDweq5mnVXe/U++m5yJzT0K4fgyHjcNXc7Qjgrmh2NBgG3f5cuqbaAbuUxiSlKAju2Yz4M3Iohd5sk5muPheDsVQszSErJP2+vZ3BJy1t15BrXQxKTsXi3/pwTA7WCxcPDAytXrlQb94sCLrzx+41EedfL0PG1GXarGbfl5IJLnk1UYc33q+EZwcKenyX0R1kZmFlinse57g3vpqvE6OFgDc6oM0IwKsi20ZgmQ3Gl1X0ITnBTz0tAJcee6RYEQSgtSNFdQuCX77Se+mCETtN09c2JD1cdx887zmsDk7Ft0K1BxhnRUW20adb6YyEIj01ML/A448YZ4YRo2/K56cRcsS6OBkchPDZJuXhn50hdkunbpAo8XJ1w4XqckvObiQ7Rku/d82zrdlh2h38cozsxzH+9bR7Q7m67PNbZ/+lZ7pFtaqqZR1sw53Wfs8ie5uKCrcoIFlV1emC/YaJmKqizI4ODec129im6w87pRQwy/ONs5y8X7jyPr0yKgHdvaYXOJoNA5gv/OLUz/Ct64ty1WFV4h8WY3ke5YO3RK1h2KFi9x98c3bLERelQWdOnsREfpme0Few0JloU4R2nZTD3owEbn9teDasU8iMuXTg7O2PgwIFq435Rz3Vfca2dt6Lb1OVG9dbYfVkvgDWr4ZthzGmIaVF02cHgdIk5vTaqt7rRSd+WUZkTK4AyTjqCMSvopTHsA73P7wDLRdMsOGmabQ+o6KmSIwRBEITij3xalyDGtKupZKd0muZBaXbM23wGn63VM6pvjmppPtiwpHE1b5V7m5SSli6HrtUBqFgfSIrVkric5LnGAUSdnthy6qrZ5drVSu5yaYC55FYl5rU76aguPq90sbaFyMvAvKHAuc2Auw9w129A89F2eZynQ6OVAoLc28t24zzDTC3wcqQaTcCSGcAHjYDQozbfBheMAoMiMxTU2dGipq+a62XGa1iFlvYpute/A6QkAvX6APX7Znm1zSev4vklh9T+Q/0bYkw7LZU2qOrjgQVTO6OqjzuOX4lWZoXqebGRuMQUvPTnYbU/pUfdEptDPambjgBbbBkfxtXA/i/r/dpdlKM9oULEKM7v6uJf4hYhBOsYs8un0kzfVbmVlxvz3LU6mfO52/vrzyuDISaJORVZHA2BT3XgsSNaHZRbz40N7+vTlrdZVa9koMEAoPkYvUBN7w2OC1nj7CbVdQ+6cMq8YCUIgiA4BqWz8imhcMV+sin7lo7TGeTLFvyx9xJe/TtQ7T8xqJGa182KUSaJ+Z97L6cfCNua2c0DBBrIVG6sDl62nS6989w5Ssz5vLa9y/bMbprvzB0EhBwGylXVmc+c27YT32ykmzTQv4kfGlXN2q07M+yI09iMEk3K0xF5CYgJsS2vm+7dq17GqXPnkZicCm8PFwRUynlW18vdBQ399GPcl2KScHI2PMYUd5dbrgSmv7aZp5sFJ65EYcaPu5GcmoaRbWrg0QHWZ9drV/TEj1M6o4Knq+rgT5m/M92cMAc+XXtCGbPV8PXAw/1tnI13QNitZmwQzed+33MxY6TeuIXA7d+bz+LcPA3l2OG7rX3JktoXR5KTk/Hvv/+qjftFBXPpycH4qnnrdDMlYvxvQLsJN5ioGVCq3byGj/I6WWVIzPOSgc0F5wvbtBEb/TMyJYUkJFt5/zMi0M1bLxjSx8Aa7IQvmgDPUzoWUea5BUEQHAcpuksYnG+kIRodp9cfC73h8nXHQvDE4v3m7tL9fU2Oz1nAuW4ec+w4ex0Xw0xmUEakFKXj2WVLn9mgT+v1VnFH209fL9Xz3AbsdFNiTpdvFg9mOPdHwx12ZEJz6OJ4VwMqNwIqNQCmrAKqmTq8diAkKh6/mQqfGX1y6NDYmtd9ngeg2RAVrDv8Wz7FoWAt/aQRGU0CbcGIFdt9JQ247Tvg/h1A2YwH1DbDRYwuM4GWt6fPiGeCsXeT5+9UEueOdSooWXl2j7VhVW98f09neLu7qDn5mQv2qIWF7Dh+JQrfmCT+r45soRYXSioqPszU7Z6/5azyf1DwOW18U4b4NCMm7OZWNZSEXyhYEhISMHz4cLVxv6g73duiTN8f107mTvJNz4iGAxBTvjGOBOkRnnYB5bNZFDUV3YSdZy4i27qQxzGZhw9oc0SLxA96FnR7ey3umLXtxhEwdtXptUFYdFv720zfC/vjDOdymecWBEFwFKToLmHQYdroXH+1QUvQDCipu8+iM/fS8GY5FjXsXHauq4uovwzJeoUAIKCH7mJbRPjcwJn/9Gnd3qq4ZBeL3cvmNXKe0y3pEnPGh90gMWch3XBguqNtdjDWi92/e1bo/4cdYewcC0KadtHFPrcYEvNdKq+7iz4zp063KSqMqojdwUlqt2VN2+f+W1nOdTcfBVRpnPcINs5v3/SWdhHPIRqMnfhZEzrYFH/H+fS5kzqqBZe1R0OU2zk7atZg0clMbr5XBzarqraSTpbxYRZQ8vvPAf2emWAyYBMKFicnJ3To0EFt3C8qDCn1gWhfpNG/IjkOiLRQRdgIPyP4vmM6hzWvCkNiztGRiFj9WYSfxwLzhwGBNo7+GHnzTYZmOOvzdSfV9yDVGhzxuoGOU4Gb3tGf65mf65Qk4Lr+Tt8SqRcepNMtCILgOEjRXQKh0zRdWRl9Ysjo2DW7R8laU9G7URW8f2trm2chDUM1s8Tc6MqS/b9YN8nivDFn7mgiU6e7OZ+7c91KOUZAlWoXcyMSifLmlExSTsrOlz2T/nzzoM4ro/ldfuG88Q+mednpvevb3Gm21uneez4cSdXb69cAnYOzU0UYRXeNtjh4KTyDK7kttDHFhu2/EJ7lWEWOZP49K387i+HHF+1XfxsXuOZN6oiKuei2dqpbEV/f1V69P1k8srC29nh/3X1RKQWY6/7KiOYoDbDgvq2DKT5si5X4MNPMNxeE6Didm9eHkHfKli2LnTt3qo37Rfn6qObjgRQ440Lnl4Dbf7BdzXJgkRpdwaU92GOa527rXz7L4r5JNW+14LXqyBV9Zh0uMtOs4s+c74ufZVbe0+evxWLJ3vTPwI9WncCl8ExZ407OQJf7ADcrYzUcmUlNRpqrFw5H6w53fcm2FgRBcBik6C6BcPWejtNk1oZTShZ+99wdKk6MBxpf3dUuV46nNFljpBgl60dMBlcqSqVmB6DtBOumL66ewPCPgG4PqQMjIyqstM9zW0rM3V2clKt1Bol5o5sAv2Zawk9TNcIDuI3/A/68H9j+FXBsWYE9rl92nEdkfLKanxzYNG/d1QZVyqmCNC4pBYHX0tKl79l1uy/tUSdJ1drgWHCUzc7llqZ/fE3zsZ8LCgW2fQX89ZDtrunk5BrguxHZmrB9sPKYUieoaLAJ7fNkZNSnsR8+GdtWmb8x3u/Nf49kKLzZzX1r2RG1/+jAhqojV1qY2LWOWuugEuCMZXyYacHjx+16QWhCl4A8LQgJjo3hYL6j0mig2QjA3Ua/CaZtbP5Yje6YTdSyUfEMaWG4mJuUSE1H6FMlMbeuwjDLv2f3BWb1AhJNn98mvlx/UnXYezasjE51KqrPx1f+0iaJVuH36r6fgGSTpD/0mDqJ86mLNDjBz9sdPh6utv39giAIQpEjRXcJZbrJcXpl4BWM+2abygpmZjA7c5Q35wYWUIy6ypDZ7eEDTFujs56dXazPz3W4Bxj4qupM7Twj89yWcD7XkJiz223GxQ24bwsw6A39HHOuj/nda17Tl3d/BGg8BAUB/09zN50xv37y6grN3zNk6SqvO6e5bhacpk73WbdGyi2f3ePcFJt0w6cBEjkYFA2sfBHY853usNsCn+c1r2gfgkO/W73Kop0X8KUpGuydMa3QxRQNllelwzu3tFL7czadwadrdJIAeXvpERWtx27b5O625aOXFOpU9jK/L77fmrHbveFEqIra8/Fwwc2ttcGjUEodzENtiKu0/Hy5qOPCUmt2wp7z4TkW3UNbaon5xhNXERmfpDO2q7fW7uJH/836vjYy+isNKO+foVvNhW+qV8gjAxrijdEt4OJUBqsCr2ClKSXiBhZOAP64D9j8SQa39lAPPVYh0nJBEATHQoruEgqNmwY09VPHGzxQZQHz/ZROKO+ZN+MhQ2L+177L6SZHNnLgYrha1Wch1TgXTtglnaGtspCYGx08djh+uwfYMUv/zFm/ga/mzU3XBjizz9itKt7uGNVW/7/zSkeTD4AquinNrNUx69iciAtA7FXAyQU74nQxRflwbjuZRrzYnstxQLUWuYsOO/w7EHxQR69ZydTlfOdzSw6q/Yf6NVDzx/nl9g61la8C+Wj1cXy76Qy2n76GxaaDc2Zyl8ZovfT4sIsZ4tUWmAzUbm1fG2Xdii4vurQRFxeH7t27q437RQkd7snloGBd/B5YnPMv0XAtLgxwKYvTLvWU4ou+CtnF7/H7k0VtYkoq1h4JSVd3ZScxv3YKOGh6PL2ezHDRV+tPKbl69waV0D6gokqEmGZaGGe32xyTZ0mLMfr0vw/0bZuK7nNlamVYgBAEQRAcg9J3RFeKuK9PA1WfsdhlwW3NNMZW+jbxUyZoLMrovmwmIUpL4M6bMlCNOKsd3wBXdffOmOfuUq+iZOpa0N8kMT97LdbspptBWji7j3b0dnIFbpmrZ/1sgIsiuZ1r5u/M/k93ce/pXhfuLvkraujoTXadDUNak+HA1NVZP/6Ii4BHeSWr3xekncvzMq9rOJgfuBiR7jpuS9FNg6K1b+h9jkPQediCkyHp0WAjWtfAowPT3Yjt4b/w6AB9e6/9E4j7f9Iy+3Gd/LPtxJVkejSorMYbWHD/ZlqAuHA9FmuO6uJnfJesIw4F+5OamootW7aojftFiTHDnMzvll/uBFY+b3s+d4222HMx2rxAl9OC1lCToZpZidTUVHRTDcNIsMxwBIidcI4ImTLlyeXwOCzadUHtP9QvPfaP+4xXvBwRj0/XWIk/a3ELUK8PkJIALH1SF/K3fYdVaZ3UxdLpFgRBcCxKbgaNoA7al8zsjqo+7vkquAndmenqumjXRfy571J67NeG91TMk+oC+HfW551YASx9AqjTE5j0D7aaiu6u9e1r+lUSJOZ9GlfBisNX1IFdM5M82mykFhIIuHgAdy7UB1828Pf+y8roKzk1VRXO7q5OqrDnPrs76jz+bLnv4oSE5FQcvxKtzIrsUdS0qOmrZqyvxSSq2dxsZ58DugFPn1XdqIOzD6mzWpq61nnpdB+6FIHkzm31h5tpVjxb9nwPhJ0BvKrcsDBgGQ1Gyfx7t2YfDZYXHurfQGX3UmZ+NToRlbzc8PRNjVFa4XgCu90v/XlYOelzfvvnHeeVaocFuXT4Chd3d3csWbLEvF+UGP/7LeHlAY4zR18B4sL1OFNORXftTuZ57nY2LGjRy+TTtSex/nioWgAqV7kBULUFcOUQcHJ1enQmuX5Gm4qSXk9luB36qnBkhikgnS1GUqjWeG1kc9wzf5d6749uVxNNqll8B/BzZtiHwJddgVNrgOADQPPR2LxsPYAYeR8IgiA4GNLpLuHQ1Tm/BbeBITlmgZiQbDJPa3WHPqW5FyV8GaLCeql4pd0mB/Wu+ZiBLXUu5q3GAsP+B0z/z+aC+8SVKDz16wElieQEACX9nA2+EpmgMsFZVB+8FIFd58Kw+eQ1ZVa17FAw/th3WZ2S8Z397WLOw4K+jakIZrdbkRCtD06tUaYM4lx8lcu++vPz0OmuU8lLqTG4gHDGzVS0Bu270QXeEpodbXg3/WCZjvAm+Nq99/tdajyD0WCz77YtGiy3sIh/flhTTOwaAE83Z7w5ukWex0BKCmPa1VKZ5qevxqgO98KdulN4VxeJCStsXFxcMGrUKLVxvyiheznfI2EpZZHsVS1dPp4dF3bq09qdzd9F7f1zLrrpqVC3spfyulhnUlkor42pa4GWt2W88qYPgbQUoMEAoJZJZQMgJDIeP5teuw/3T+9yG/RrUhU3Na+mDNaeX3LoxtEtjuT0eFTvL3sGiTHhOHddG7RJp1sQBMGxkE63YDNd6lZSBz00ZVt3NBQ3UX7H2dmqLYErB7UUut0k4MxG/Qt1e6vIMh600Gm1fhU9jyek079pVdURZnFxNDgqfc6Q5nTMbLWR2MRkzFywRxXanBv86PY2qvjk4ghj4ox9dZpknFqcl5yqHLntWdQwr3vH2etqrvt2r73A4kk6t3vyUqvXP3w5Qi0W8LVS1ccjTx1SdruZ8bwrujIaunkDiVHA1WNA1SxitxjDxm4ZjY/aT8pwEU3laLpEI8FvcxkNlpfC+9WRLfDC8Galco7benxYbXy7+Qye/HW/WjziZw99KoTSC9/jHD04dCkSEV51UCkmWM861+pg/ReS4oCYULUbUbkNTobstbnTzfck1V00T1x2KEib99Xve+MVuagXfMh6l/u/0+r7jyoZszosEy+PaIaNJ0JVF54y9LGdMimNWHTToC06GFFrP0RKamf1/qCCTRAEQXAcpOgWcnXAM6JNDcz+77SSmKui28jsXnlQy+s4Sxt3HXArB9Rsh61rTqur8IBDIn5uhAdPfRpVUS7z7HZnZ+6THS/+cRgnQqKVCdrHd7RVp0WNzus+pTrr6NtUd4I4Y02DOBfT46NB0PejgICuOOD3rDqrVR6k5ZZz3Sy6912MwjjOVZ7bDFw9kXXR3WEy4OwKeFbSzvEmwmMT8fUGPeP+yohmhSbllII7nbu7BmDeljOq4CZ3dvaHiyxIFDopKSnYuFEvpPbs2RPOzkVrYsf3IovuINfaqIRtZoMxq7iWBZ48qcZH9oS6mM3YbF1AoxKJRTcXmbmwaTX5gwuk09bqSERjxIou41EJWGCKuHuof8Msv/+oRKNPxBv/HsHby45iYLOqqFTO4vPb1QOYsARYcDsiI7TzOhew5ftUEATBsZCWipArRrbR7tKUfKooFUKpXRknPTu3a54+L6C7KmaMeW7J586aYSYXc+Y/59YAjbA78tueiyr3+bNxxaPgJu38K6ixRM50h7rV1oVtcjwQtD/9Spy5jjgPXD+tpO95lZYbGAX7/ovhwKgvgWcvAs1HZf0LLLhZeDPz14KvN5xWc9yUmI5snT8ndyHv8WH9TPFhjFca27G2PJVFQHx8PPr27as27hc19SrrBbCTKfpzUy2qZYdyE62HPbmY5zZgDGHtimWVgmjDsdD0+/vzAeCP+zPeB70pLJiz8bRSGXHEi9nc2UEPAy640ln9raVHb7xC3V7A02fwT/UH1Y/iayAIguB4SNEt5Ipm1X1U3jclc8sPmvJFvasC9fvp/d2morteb9UZ2HdBr8x3rScmalnRr4mflpiHxuCYaabZVo4FR+GlP7W08bGBjfKVHW1vfD1dzRFxapbSnNe9Nf1Kpnxu1GinouVIy3wU3TzAJZwNj/WsAbhlMdIQHwEkJ1q96EpkPOZv0bPnTw5uLI77RcjMvvXV2MPtHWvDLw8jB0L+YUe1WbNmaisO3dX6fvo9vT/Oz7ai24TZRM2GeW4D/r1DW5h8N0y+F0hJBPb+oOPBjvyjvSoycS06Ad9vPWee5c7peaOC463RLVTtzgVUY7E6A65lzfnkhou7IAiC4DhI0S3kCh48GIZqf+y7lH5B63EZr1i3F3aeDVMxS8wIZ7dAsI63hyt6Nayi9pceMMXT2ACzXWcu2K26Kb0aVcHMPg2K3VOsJebM62bR3UWfeX5b+hUua3fxuCqt1Fy7kdGdVzgLztlfzoZTgpolq14GPu8AnFxzw0WM7+FzSvd/LogIRQczjfe8OBCvjzTlrguFjqenJw4fPqw27hc1Rpd3dUQNpN3yLXCbaaE3M4xd/LwTsGgikqOvmxeAcxvFRxdzsvbIFWWuyGhDVGqgo7wWjgc+bglEXLrBD4LdcX6WMaHCFtr6V8CdpnnuF/44mG5WasFJo+iWjG5BEASHQ4puIdcwq5hsPX0NwREmuWGTYcAjh7Sc987FgF9zi6gwmefOiWGtquVKYs7rPL/kIE6Fxqgi86PbWxfLjizN1AjN1NI73dsY/qsNiExS82PODVUkFBdoKlvOM+YBQ56uOufr3wHmDEh3MDbmyBkTFn4OcM1YRJy7FmN2yn5qcONi0dkr7XBRyrkYvraFooGO4nxbXoj3wPW6w7P2a2DkIk0UT63F0TCaTaYoR3wqtXJD61q+qOHrgZjEFPx3PFRLyRmRaVClMeCjvxMNPwhG3eU0y22Np25qgsrl3NTn+jf/aT8UAzqbnwrRC5PiXC4IguB4SNEt5JraFT2VGyuLpL/2X0o3rClfG3D3BhoNousatp66qi6SeW4bXcydndTBFqO9cuKXnRdU1BeLkc/ubJvReKcYdroPX45ETMVmgEtZbbR37YQ2QEqKVaZ7O6Mq5Hue26C1SWKuOlss6i/u1JvB2je0qVvDwcrAzZIPVx1X6ozejapkyNQVBKF4wNi+WhW0coqflznmc9dsjz0XteqlbUCFXC9OKhdzU7fbiFbMUHT3fkoX4ia+3XRGFeic0c6t2z6TEl4c3kztf7b2pFoENAiKjFfdc/obMMJQEARBcCyk6BbyxEhDYr73stXLabJmGGNlFZUipMNs7F6NKpu73dnBaK2X/zqs9p8Y1Nhc2BZHapQvq7rXzKHddzkW6PkYMPQDbapmkpajemvsvxSd73luA8aGkQMXI5SDvoKu6eTyPuDw7zyUBvq/lOH3jgRF4q/9l82z3IIgAHFxcRg4cKDauF8cMOTV10/uBLZ8DpxcfeOVLuzQp7U7m03UbMnntsbQllqJtDrwipZ9V2sFdH8Y6P4IUC89RoxGaPOMLne/BnlSylBJxthHxji+9Odhs/LpVIj+jGTBLSkHgiAIjocU3UKeGN6yulpxDwyKxAkr5l87Tl9Xc7WUAjISRbAtnoYwOiwrouKTcP+CPcrIrm/jKpjeq16xf2ozSMzZFeo0DfCqDLh4KAM1znqrApmd7pp5jwszMAr389djEVmpdcaie+3rpivdpjPmLfhgxTGl3qCbfIt8zJULQkkiNTUVq1evVhv3i1PRXfbMSmDl88DhJdkU3Z20kaNyLs/b50vb2hVULnZUQjI2n7yqO9sDXwMGvpqhy01ZOVMPGlUth8HNTZGauYSFOj0MqHzacDwUS02GpSdNRbdIywVBEBwTKbqFPFHBy81sEJPBUM0E571JcXLTLu4MaKYl5jy4ovt2ZtjxeOb3gzh7LVbNGH54e5tiOcedmQ6mTvwumqlZ0vJW4N51CO/6jCqQ1Vl2KHYp0axXxeRwnFpXnxl2Bgj8U3fEnFyAvjoT3GDX2esqBo9y/ccHNsr3YxCEkoK7uzt+/PFHtXG/OGC8vwMTq1p3MI8O0e95lEGob0tcuB6namMj3SC38HN2iOFibqR2WFkQpYEaebBfw3x9NterUg739amv9l/9+7C6bbNzuZioCYIgOCTFruj+8ssvUbduXXh4eKB9+/bYuHFjttffsGGDuh6vX69ePXz99deF9lhLOyPbaIn5n/su32D+tUXyufMkMTfyXP+14mL+47Zz6nwqDD4f304tfDgCHU2d7j3nw5CckgqEHgd2zweide6tMYZQp5KnihmzB4bEfM8VaKdhsv5dfdp+ksrtNeBr970Vx9T+be1rqQNeQRA0Li4uGD9+vNq4XxwwCs+d0aYoSvpDWOty+zXF7ivaBZzxhTTlyytDWujO9crDwUpplBlGhFFeXr+Kl1m1lB9YdPMzMSQqAf9beVw63YIgCA5OsSq6Fy5ciEceeQTPP/889u7di549e2LIkCE4f/681eufOXMGQ4cOVdfj9Z977jk89NBD+O233wr9sZdGBjStCi83Z1wMizNnoJKwmEQ1H0uk020fifnBixF4/Z8jav+ZIU1ylTVb1DTy48Gui3IPPhIUBfw2Bfj7YeDkKnW5IS1vaSqU7QEdh8l+OpjXbJ9ufjTxH6DXUxmuSwnnjjPXVVb6wwMa2u0xCIJQsEX3tgjTZ0ZcGBBjkW1dxkmPrgR0N3835TYqzJpih8kKkfHJZiWXZXzjnI2nzV1ue7jt0zDu9VF6BOb7rWfNn5PS6RYEQXBMilXR/eGHH2LKlCmYOnUqmjZtio8//hi1a9fGV199ZfX67Gr7+/ur6/H6/L177rkHH3zwQaE/9tJIWTdnDDat/ltKzLeZDkg411bFu3jIER1JYu7qXAYnQqLNs/I0pbv/pz1ITEnFwGZVMaWHSTLtIFBmSbf7G6LD/rgP+OdRHe2l5rntN0fdyiQj5W2n1WgL+NQEnJyBuj0B76oZYnjeN3W57+4SIP4DgpCJlJQU7Ny5U23cLw4wVsuHC3lp7kgqV+vGbneToWp0BUPfx57zecvnzgwL6cHN9WfHskyLolQhhcUmKQ+T4a3y3+U26NmwijJWoz8KnctJ/VxGngmCIAjFg2JTdCcmJmL37t0YNGhQhvP585YtW6z+ztatW2+4/uDBg7Fr1y4kJSVZ/Z2EhARERkZm2IS8M8okMafs2ZDcGV2ArjLPnad5ZB5oWWZ2P7X4gJp5ZkzOB7e2dsjs6I51TXPd51h0d0m/oGwF1cW3l3O5QbPqPkqGfzU6EZca3gU8Fgj0euKG6y09FKTizMq5u2BmX5MMXRAEM/Hx8ejUqZPauF8c4GegUXyGe9WxLjHn931KqvnzxR7qIEOJtOJwsB6VYZM9MQWzTZna9/dtABdn+x5WvTC8qVIKkWo+HuqzShAEQXA8ik3RffXqVbWKXrVqeheK8OfgYOvGJTzf2vWTk5PV7Vnj7bffhq+vr3ljJ13IO8zgpuSOq/z/HQ/NMM/dtb5p3k7Is8R8/pazWH44WHW/v7iznd1mngsbI9Zs59kwpFkU3ZHl6uFyRLwyObKnYzilmczJJUYcWWZ40PzhSn2gPq1nPVR0kBl5QSjsAjcgIEBtxWnBz5BZX3KunbHoTogCErUx46FLkUohVMnLzS7Z1p3rVkQFT1f1fbf9zHV13oLt53AtJhH+FT0xsk0N2Bs/bw88fVOTfLmvC4IgCEVPsSm6DTJ/qbPTl90XvbXrWzvf4Nlnn0VERIR5u3Dhgl0ed2mFq/o3t65ulpiHRMUrwxc+/V3qFd/86OIMJeQsso9ficYb/+o57ueGNkXrPDrvFgfoSk5n9tCoBJxL9AUCeqis7gMeHcwH0Pbu4LQydc4N+Xpmft19EaevxqgD8ik9HUuyLwiFhaenJ86ePas27hcXDAfzfzyGAdPWAX2e0Rfs+R54pzaw/DlzPne7gAp2WTDg950RBcZF0fikFMwyd7nrF1h+9l1dAvDrjK54c1TLArl9QRAEoRQV3ZUrV4azs/MNXe2QkJAbutkG1apVs3p9OqxWqmQ9qoqRJz4+Phk2wT4S89VHrmB1YIhZ3lveUzqHeZWY92igVQIpqWnKNXdSN5OE0kFh59kogtVc94TfgUcOYleok93nuQ2MRYp9F24sunmw/MkaHTNEWblINgXBsTA63TsiKwA12wHu3unO5anJgFdlu5moWTLEQmL+0/bzaiGxZvmyGN3WNFteQNDIzVESKwRBEIRiXHS7ubmp6K9Vq7SjsQF/7tatm9Xf6dq16w3XX7lyJTp06ABXV8eU4ToiLKZoIBOflIoPV2mJn8xz2yeOjZLFd29tVaxknXbJ63ZxB9y8CmSeO3Ns2KFLEWrxIrPxUVBEvMo7H9/Z3+73LQhC4RTdp0Ki0yMreXphu96t1RG7z9u/6OZIFRdG6Rfx7vKj6ryZfeur9ANBEARByIpi9S3x2GOPYc6cOfj2229x5MgRPProoyoubMaMGWZp+N13322+Ps8/d+6c+j1en783d+5cPPHEjYZJQsHBgtDodl+NTlCn3RpYVxoItsHZwM/vbIvFM7qq/O6SgJHXvZNmaqZRkAOmjG6jC25PGviVg6ebM2ISU3AqNH2uOyo+CV+sO6n2HxnQSHXhBUGwDs3TRo0apbbiYqRGOKNNs0S+vyO3fAv8+zhwbjMQFQSUccYlz6aqC83rcLzFXlBCzhEgkpCciuq+Hri1fcF2uQVBEATHp1jZYN5xxx24du0aXnvtNQQFBaFFixZYunSpMnAhPM8ys7tu3brqchbnX3zxBWrUqIFPP/0Ut9xySxH+FaW3SPxo9XFztIphnCXkfSFjeCv7m/IUJUa36XRoDK5FJyApJU0dFPP10qy6/YtuZ9PBNg2PKDFvVFXLT7/ZeEYZIdWv4oUx7fRikSAI1qHB6Z9//mneLy6w+PWv5Kk+T5z2fAdc2w/EmAxUq7fC7iC9ANy8pq/dF9aGtqymPCHIfX3qw91FFu4EQRAEByq6ycyZM9Vmjfnz599wXu/evbFnz55CeGRCdtSp7IU2tcur4oaFjncJ6c4K9oMz/sxup0HcLtOsJWnoV05lvhcEnOtm0U0ztds71FbF/tyN2vjo8UGN7R7vIwglDY5+zZ4927xf3CTmLLpD3P3hjf1A4B/6glqd0ue57RAVlpnuDSorJY1zmTLqc0UQBEEQHK7oFhyXe3rUxUM/78XottI9FKxDBYQqus9eN3eHCkJannmue/8FLWP/Yt0pJUflwhAN6gRByB76o0ybNq1YPk2Gg/mZtOqob3lB7U7Yvc7+89wG/Oxa9Wgv0CqCihpBEARByAkpugW7MaJ1DfRuVAU+HvKyErIuuhdsP6/yun3KajVES1NhXBAYBf3R4EicuRqjDNTIk4MblwhzOkEozRhmaocSq2GAcWbz0Yit1hFHgg4VaLY1Pz+c5SNEEARBsBGpjgS7QldXQciKDiYzNTqK0+SMtC7ATnetCmVVDve1mEQ8+PMeJKakqvz4ng11JJvwf/buAjqK6/sD+HdmNRt3F+IQ3N2hFNpC3V2oUKMu/yr1X92FKm2RFmgLtJTiEDRCPMTdXdf/Z94kaBKyyW70fs7ZMy/JZnfZDbtz37vvXkI6ZjAYWKFSwdChQ8HzfB9sG9ZSuFNuC1z1HWIzK9gqtNDKy9PeqncfJCGEENLXqpcTQgY28SRYCZ3BiNpmHWQSDmEeLf11LbQa1dqvO6Gglh2fXBROq9yEdFJTUxMraipchHFfIhRDFByvc4CRkwCaOqCuGNEt+7nH+Fkui4YQQggxBQXdhJAeIwTBrf26BeEedhav/HvmnnGh1c9YCxRWImQgc3FxYZe+WJzRxUYODWTQKx0BlTNQX3K6iJoF9nMTQgghXUFBNyGkV/p1C0ZYMLW8VetKt7CF+/GFYRa/P0IGEmtra5SVlbGLMO5rAltSzFMDbwVULjCoXBGdW82+R0E3IYSQvoKCbkJIjxrvf3ql25L7uVtNC3LBstFeeG7xUIumshNCem9f93b7a4EVR5GpsUNNkxZKGY+hnnb0khBCCOkTqJAaIaRHCYGvk7UclQ0ajOmBVG+5lMcH142x+P0QQnpvX3dGWQM7tqaWC+0CZRJaVyCEENI3UNBNCOlRQl/bb24dj5KaZoS608ozIX1Zc3Mz7rzzTjZevXo1lEol+uJKd0ZZPTtG54ip5WNpPzchhJA+hIJuQkiPo2JmhPQPer0ev/zyCxt/9dVX6Gtag+6s8gboDUZE5bYUUaOCiYQQQvoQCroJIYQQ0ia5XI7333//1Liv8Xa0YltI1DoDkgprkV4qrnjTSjchhJC+hIJuQgghhLRJJpPhkUce6dPbVQJdrJFSXIffovLY94SvhboRhBBCSF9BVUYIIYQQ0m+1pphvji1kR1rlJoQQ0tfQSjchhBBC2mQwGJCbm8vGfn5+4Pm+N1cf2FLBXGgVJqCaEYQQQvoaCroJIYQQ0qampiYMGTKEjevr62FtLQa4fXGlu9U4qlxOCCGkj6GgmxBCCCHtUqlUffrZOTPotlVIEeJ2dhBOCCGE9DYKugkhhBDSJmFlu6GhoU8/O63p5YIx/o7gea5XHw8hhBByrr63OYsQQgghpJOsFVJ42ivZmPpzE0II6Yso6CaEEEJIvzYjxAVSnsO8oW69/VAIIYSQ83BGo9GIQay2thb29vaoqamBnZ1dbz8cQgghpM9Qq9VYsWIFG3/yySdQKBToi9Q6Pate7mYrrngTQgghfSmWpKCbgm5CCCGkTcJ+bhsbmz5dvZwQQgjp67EkFVIjhBBCSJtkMhlWrVp1akwIIYQQ09FKN610E0IIIYQQQgixUCxJhdQIIYQQQgghhBALofRyQgghhLRJqLVaXl7Oxi4uLuA46oFNCCGEmIqCbkIIIYS0qbGxEW5uYhsuKqRGCCGEdM2gD7pbO6YJ+fiEEEIIObt6eSvhc1Kv19PTQwghhLRojSEv1IV70AfddXV17Inw9fXt8IkihBBCBjMvL6/efgiEEEJIn40phYJq7Rn01csNBgMKCwtha2t73l41YeZCCMbz8vI6rEZH+g96TQceek0HFno9Bx56TQceek0HFno9Bx56TXuOsMItBNzCxDTPt1+jfNCvdAtPjo+PT4dPphBwU9A9sNBrOvDQazqw0Os58NBrOvDQazqw0Os58NBr2jM6WuFuRS3DCCGEEEIIIYQQC6GgmxBCCCGEEEIIsRAKujugUCjw4osvsiMZGOg1HXjoNR1Y6PUceOg1HXjoNR1Y6PUceOg17XsGfSE1QgghhBBCCCHEUmilmxBCCCGEEEIIsRAKugkhhBBCCCGEEAuhoJsQQgghhBBCCLEQCroJIYQQQgghhBALoaCbEEIIIYQQQgixEAq6CSGEEEIIIYQQC6GgmxBCCCGEEEIIsRAKugkhhBBCCCGEEAuhoJsQQgghhBBCCLEQCroJIYQQQgghhBALoaCbEEIIIYQQQgixEAq6CSGEEEIIIYQQC5FikDMYDCgsLIStrS04juvth0MIIYQQQgghpB8wGo2oq6uDl5cXeL799exBH3QLAbevr2+PvjiEEEIIIYQQQgaGvLw8+Pj4tPvzQR90CyvcrU+UnZ1dD740hBBCCCGEEEL6q9raWraA2xpTtmfQB92tKeVCwE1BNyGEEEIIIYQQU1xomzIVUiOEEEJImxobGxEREcEuwpgQQgghphv0K92EEEIIab9ATFJS0qkxIYQQQkxHQTchhBBC2qRUKrF79+5TY0IIIYSYjoJuQgghhLRJIpFg9uzZ9OwQQggh3UB7ugkhhBBCCCGEEAuhoHuA255YjOSi2t5+GIQQQvohnU6HzZs3s4swJoQQQojpKL18ADuRV43lP0XBx9EK+5+cc8FS9oQQQsiZ1Go1Lr/8cjaur6+HVEqnDYQQQoipaKV7ADuUWcGO+VVNyK2kVi+EEEJMw/M8pk6dyi7CmPS80tpmXPHZQaw/nkdPPyGE9FM0ZT2AHc+uPDU+mlUJf2frXn08hBBC+hcrKyscPHiwtx/GoPbniUJE51ZDbwSuGe/b2w+HEEJIF9C09QBlMBhxPKcKtmiEHFocOyMAJ4QQQkj/EJ1bxY4lNc09cn/1ah0OpJWz8whCCCHmQUH3AJVRVg9lYzEOKh7EV7L32Eo3IaTvEgoePv17HCrq1b39UAghfYTRaMS0jA/wtvRLDG84BH0PBMIf70zDTauP4Mt9mRa/L0IIGSwo6B6gjmVXYZnkIOy4JsyWnEBNRTFK63pmlpwQYrqvth6CPPob/LA/lZ4+0mc0NTVhwoQJ7CKMSc8qqGrAjYY/cY10L76RvYOKmnqL36cuOxJT+QRsOngCWr3B4vdHCCGDAQXdA9TxnEoM5XNPfT2JT8GxLDFFjRDStwhpnHfkP4tXZD8gLP7d3n44hJxiMBhw/PhxdhHGpGelJsac9XVFyenPdUu5tOI7/CJ/HcMajuGfhGKL3x8hhAwGFHQPUMezq/CJbtmpr6fwibSvm5A+KrOsDiOQzsZO9WlQ6/S9/ZD6BCE75/qvDmNjdH5vP5RBS6FQYMuWLewijEnPqks7u4hdbanlg24HfTk7FsMJPx3MsPj9EULIYEBB9wBUUtvMWoRlwAdNl3/PvjeFT8IR2tfdLVUNGtQ0atETyqtrsOW9e3Bgzz89cn+kdyWlJLGjzsjjds3jSCiooZcEwIZjeVBl/4sfdxyl56OXCH25lyxZwi7Uo7vnWZVEnfV1c0WBRe+vUa2Fq1GsAfOkdB1eKn4ACfnVFr1PQggZDCjoHqCr3IKhnnawCpkFg0yFYqMTMoorUdNkuaCxskGD17YmIb9q4PUEb1DrcNEH+7Dk4/3Q6CyfYpm98SVcUrsO0/dca/H7Ir2v7uR+dkwwBqAZClaTgQC5qVF4WfYD/q/hdeRVDrz3FUIu9LkT2JzIxlpOxo66mkKLPmmlZaWw5sRijqP5DAzjc3Bwx2/0QhFCSDdR0D0ACe3BrpfsxF02kYBBD/7pPPyf3avQGKWIzrHcyfxHO9Pw9f4svPXPwCsEdSSrAl71iXCoTmT75S3NqXDfWSdBZGCzaVnNKrQbLdQrRlymZU+s+4NmrR4xBQ3w4coxksvE0ZOUYt4b9Ho9duzYwS7CmPScxIxshHDiynam63x25Oss+95QVZLDjrWwQfnQm9k4OOsX6qpACCHdREH3ABSVXYkHpZtwee7rQEkCIJFiYoAT+5klU8x3p4rB4f60sh5pa/LjoWxc/UUkynugxdKBk8V4UfYjtiiex6GkbIveV11DA9y0pwOMzKj/LHp/pHcJLcJCNeJq1lgXPQ4pHsSynNcGfY/cqJwqnNS5o8DoDBmnR0niHvpT7QXNzc1YuHAhuwhj0nMy05NRZHRCicwXaudh7HvyphKL3mdDWR47Vktd4Dp3BRvP4aKxbd8hi94vIYQMdBR0DzD1ah1qi9LgxVXCyEsB34ns+xOGOMEZNRYrppZV3oCCilo2rm7UWnxPqlDt+YP/0lga7qZoy+5xE+xPr4Y9xFYtjcmWDYKTj++BDSee3BqMHMpyxP2+ZOBOku02jEaiJBwuY5fCk6vEKGMyMkrrMJgdTcmGI+pwQjqKfW1dcJD1LCY9i+d5jBo1il2EMek52yvcMUX9Cf6b9jPgPQ4/6+bhgEH8/2Apmirx87RB4QbONRTFrtPAc0ZIor6BjtqHEUJIl9En6AATm1uNiXwyG3Pe4wC5NaDXYlnklYhS3ofi/EyWtmluu1NK8bHsY/wpfw6T+SS22m1JcQU1bA+5YO9Jy95XUU0T0krrsbflZCe49jArVmcpf1b6Yp76HbyleBAj1N/g3dp5Frsv0vuicqvxtu46rIn4GtKhi6GDFO5cNZKS4jCYqZI3IEpxHxZwR9jXY3WxSC+1fI9icjYrKyvExsayizAmPUOYWI7OFQuYjQj2hyp0Jp7T3Yk1zVMser/xkmF4Uns3knyuYV87zX2IHS/R7cTOuEyL3jchhAxkFHQPMMJKttCTm/GfJh4lMsgU4snSeGMiYlo+yM3pQEo+ZvJxGMlnoc5ohX0nxZYjlrInpQQ8xIJmR7MqWcEZSzlwsgw+XBlynMXnc7bkBPa2pNJbwr60CmQYvRG26D408ypkVzSywJ8M3DRqwVg/R0BmhRJbMY20Ie0ABiuhS8CQ2mNshU0z/Hr2vQguB1HJ1L6IDJ42gjVNGihlPCuK6m6nZN+va9ahUWO5z7vEZhes189BQ8AC9rU8bCGqlL6w4xqRu1vshkIIIWQQBt2ff/45Ro4cCTs7O3aZMmUK/v77bwxWQpGvSZy40o2AlqBbWPUeMoMdp/JJZk8xZycA2QdZxVO1lTtSjH5Iz81DXbPlKqWfTIrFccW9eEv6FTR6PQ5nVljsvjISj+GA4mE8pP4GOl7B0n/TEyzTwii7vIG1e5NJOCwY5o7h3vbs+4fSLTuJQXqH0I/bWBANGzRifEvdBYPPZHa0LT02aF+Ww+klLGNGYD3hRlSoglgAXp20s7cfGiE9IjM+ElGKe/GVzdeQSXjYKKRwk6sRxBWgpMpyW09as7g8WoJ88Dy4WU/gHd21+Kw0AslF4jYyQgghgyzo9vHxwZtvvonjx4+zy9y5c7F06VIkJoqFiQYTYb9VSW4afPkyGDkJ4Dvp9A8DZrLDFD7R7EF3ZHoFZuE4G8u1NYhR3oen+J9xONMy+8eFtHKvsr1w4uox0yoD10t2YX9yocVS/BS5YgEnznkIGjzF1D6rnN0WKRaXcfA3fCL7CMvdkmGtkOIWhxPYJH8BDofeMPt9kd6XkFeOnySv4ITyHgRwxex7zhGz2HGYNnHQZjjkxB+AHdeERokd4DkKhoCZKDPaobC0tEeKNJLTmpqaMHv2bHYRxqRnNGZEwpmrg49cbJXHcRx28iuwU/EEagpOWux+Q6r3YxofDy+r06vpDlNuRfawe1EFO/wQadlCooQQMlD1+6D70ksvxeLFixEaGsour732GmxsbHD48GEMNslFdQjUtaRfeo0BFLanf+g/hQXifnwZinJOmrUgyu6UEsyTxLAxN/ZW2KEesyQnsM9CKdjCfvHZXCwbe2rz8IZsNSpS91ukyFJycS3GacV/m+2wi2Az/GI2nqyPxol886fpy9L+xiWSw5hvLb6OQ11kGMOnw7NC3NdKBpacxKNQcWq2jYBzHMK+pwqcyo5BfBHiUtMxGElz9rJjrTDJxUvgeOmrmIuv8WPzTCQWWrZIIzmbwWDA3r172UUYk55hVxbNjsYzJs9rpM7s2FCWa5H7FM4LntZ+hp/lb8DLeHaV9NumBrDjppgCVLXUUyGEEDKIgu4zCT1E165di4aGBpZm3ha1Wo3a2tqzLgOFsIL9r2ECHvT9HdzST8/+oRCAC4E4gNH6eCQWmuffLQS6uSlRrJeuXqIA5jwDvcQKHlwVClMtkx57KCkHE1v2reu9xrPj8IbDrIK62e8rJf/UfUlD5kESugCNvDVK4IC9KeadVNBo9QiuE58zh+EXsWPA2IXsGGrIQH6RuBJKBg5tViQ7ljuMZmmcjMoJCY7z8K1uEeJzB9+2AmF1P6JZDDjsIsS/f6mVLSYFurDxwXTLbSUh51MoFFi/fj27CGNieUJQG6oVt4m5DhOz1Forip9ZYdzcyqpr4cKJ5wb27v5n/Wy8vyPudo7DD/zL2LZ/8C1qEEJIdw2IoDs+Pp6tbgsnBPfeey82bdqEYcPEYkTneuONN2Bvb3/q4uvri4G0n1sQHhgAuIWf9/PWfd1TzLivW6jqPaKhpX/nkFmAlSOMAeL9hNQdQW6FmBpnznRvXfpOyDk9mmz9IZl6P/v+HD7WIlXMK5L3QslpUa9wB1zDAOcgbL3oIB7RrsDeNPMGRInx0fDiyqGBFH5j5rPvqVz9USjxgoQzIiua9rMOJMKElXOFGFxKA8R93K1y5nyKV3S3YFeBFIPN4ZRcjOXS2FgVdrpy/9QgYZXPiOg0y6zykbZJpVJcffXV7CKMieUlpSaLE9ngYRd0eqVbqJkiMNRaZjtVZbH4f0sNGSTW4qp6KyG9/U6rvZjMJ4M79g1t8yCEkMEYdIeFhbF2JkJK+X333Ydbb70VSUlt9zZ+5plnUFNTc+qSl5eHgXICL/SsFkxoKch0ntBFSPZchr/1E1nFb3O1CoszBuKQag4kI65i35OGLTxV5XufmVuHxRfUYIKmZf/40IuBoLkwgEcoX4CExHiz3pfQWs2lRKwgrR8yWzjrYOMZ4Z7sKKSXmzPNrjxOLACYrRoFXmF9+vtO4mq+NnOf2e6L9D6haN4Io5hF4Rox+6yfjQ9wZMeU4lrUWrAgYV90JLMSz+ruRJTHNYCTmHIvuIg7jKOKB3BZ3jusAB0hA1V5ivi5U6QMAhQ2p75vtBU/e6QNlsl6qmtJW6/inU993p2ptX3YEt0O7I7PsshjIISQgWpABN1yuRzBwcEYP348W8keNWoUPvzwwzavK6yGt1Y6b70MBELF6wkNe7FO/irGlP/Z9pX8JqNx0Qf4zzCOrXQLq8bdtSe1DAcMI3By+gfAqGvFbwaLq7TjuJM4mpJt9lZhcyTifm5J2EVsZb3ZQwxKbfN2m7UH+fHsKkyF2CvZLkJM9xZ42CsR7m6DABSZtR+5XYEYVGsCxEJareQhYnqhR+Vxi+xbJ70jOSWB9ePWQgq5n/g33EpoDxTiKMEkLhGxGZZJJe2LhL/vXZkN2KCfDfX8s4sHenl5w42rxmQuATEtbdZIz2zbOnjwILsIY2J5sgJxm1Gj+7izvi+192JHZdPZ+63Npbkinx3r5K5t/lwefhGqFN6w5xqRtYvahxFCyKALuts6cRP2bg8mQoA4nY/HJD4ZskoxNbMtI7ztWd/PqkYtMsrqu3WfQkuw1jT12WFnfEg7DYHabghknB581l5ozVi0LfJkAdbpZ6PMcfSpPuRWEWJxsxmIMWvrsP0nS/GB7ipEOi4FF3jGSqTBgJ80j2C34jGkxpmndVhZdR0iNOJKvff4JWf9rHVfd5ghA3nFljnZIj2v7uR+diy1DmP9uc/1i34lfpW/huIE8XqDgfCeVFqnhkLKY6y/uNrfivOdBA2ngCtXg9R4y7TsI+drbm7G9OnT2UUYE8sSPi+P1TnhiCEctmFnZ8AonX3Y0U5rmVoPuhpxgq+5JY39PLwE3KR72HBG1UakUvswQggZPEH3s88+i/379yM7O5vt7X7uueewZ88e3HjjjRh0/blbCn4hYHq715NzBlzpXoJ5fBSOdnNf98H0cszDUcx1LIe/k+qsn8mm3IMvcRVOaLwQm2eeKt9CKvfR/Ca8q7sGutv+AaRiUR8uRAxKhYJn+1KKYC770yuw3TABZbPeAM7c38bzkDqKtQDk2TvNkjFwPCEZ6UZvVHKOcAwYe9bPlC7+SJENw9+GSTiRltPt+yJ9wx9VQ/C89nZUDL+9zZ83uIxmRz6vpWbCIHA88STulGzDMu9aKGWSs38oVaDCWVz502eIbfyI5Ql7eYVMMuEijIllpRTV4TvNPNzNvwL3yded9TMbn+H4WTcPv+mmmeVz51zSOvHz02AjprG3xWHKbVBzSoTzedj/3yazPwZCCBmo+n3QXVJSgptvvpnt6543bx6OHDmCf/75BwsWLMBgkpGZwVoMGcEBfm1XbmdyI/Fa+cN4XbYaR7u5KrwvqRD/k32Bb5seAorElO9W/JT7kRC2AllGT+w3U4EzYX+4kF0d7mELT/szVgbdIxA95RNMU3+EPWnmSTstr1cjqWUWf1qwWDX5TDYjxNX1Cdoo1lasu7bny7BM8yq+m7D5dBXrM2yd8D1WaB/CzkJ5t++L9L6aRi0iy62wRr8AXjNuafM6qhCxIKF3bSw0usHRqqk+6V/8n2wNHmt4v82fK1sKqwXUHEOD+nQfYWI5KpUKaWlp7CKMiWVFtRREFTI9eP7sSQ4nv6F4Xn8nVmsvQmWj+dt2bZPMxpPau1EzZHH7V7JyQHXIFWzon/4Tey8jhBAyCILu1atXs1VuIZ28tLQU//3336ALuCsbNHCvFIuL6d2Gsw/FdvlMhIGXs72kJZkJ3Urhr0ndA1uuCRqlC+Ax6rzrzAgRg1VzVfk+lpSBBfxxzA8+XViG4TiEzLoOjbwNMssbzFIx/WBaKe6XbMYVrgVwUZ1fsVcWKq6uj+dTEZnUvX3rworF/pbnaGpY29X0pwSKK+2HMitoX/cAEJ0rTg4NcbGGi03bbZhch4l7+0dx6UjIH/itw4Qewa6lYgs1nLmd4wyOEWK9iAlcMo5lmrdlHyF9QVZGMuzQgHF+Z2+vEMgkPJytxfeL4hrzp/ofbfLGev0cKAJOV0xvi9v8h5AkCcdm7RSsPz4witESQoil9fugmwgz41VsL7dAGiiujrVLpoTRZyIbBjXGIL+qawGqsAo8Tn30dEGzNlZnZ/kpcRF/DPYF+1DdzVl5ITDl07bja/l7WJ71yHk/t1XKMK5lD+jek90/Gc+IP4wnZevxRsOLgKGN4kHOQahV+bHWZdWJ/3XrvpLzSqFuqIa1XHLq33AuYdVDLuFgXZeF7KKBH4ANdLlJh3GDZCcu8mi/rgLnGo563hYqTo2chIGfYh6fX41JEOsaOI9c1PaVPEaiQWLHJvuy4wbPXvf+SMjO+CO2APWUkWCS+dnvIVZxDy7Wtv25EmirQzCXj/Jy83YGESbSi2ubTxUL7QjnNhRxF23AVsNk/Hg4m9qHEUJIJ1DQPdD2c7cUF+uIJHBmt/t170kpxTxe7DEsCW87Fc0983d8KX8fyyV/4UB69wLFhMIaTNSJq/mqoeJq17ketvobv8tfRHKC+Li6c/KhyBH3jNZ7TQGkbad0c8FiRoVv+QFWVK6r8g//jhjFcnxp9y3k0rb/Swr7W/9SvYJdiseRHf1vl++L9A12mVvZFo9rmta1fyWeR4XTGDbUZh7EQJcUdwweXBU0nBwS/7P7lp/C8ygIuhZf6C7BAcu0KibnEIqnLVmyhF1MKaT27r+peHhtLB5Ze/bWI9K+oupGDNOngOeM8A4Vazqc683GF/Gf4klw2eZtIVnbqMES/R5M4+PhbnPhfuxLR3vD3kqGvMom1jqUEEJIxyjoHgBissqQbXSHRmYH+E+98C8MEVfDJ/FJXd7XfTIxCv58KfScrN1UUISIQekEPgVHksX+n121L7kIM3mxfZckrO1VsJHqaIzj02CXt6tbfXyFCspjNNHntQo7l23Lvu6ZfCwiuzGpIMvewyq9Ozm33aalldYphB11mbTC19+rE3vXnWBj6+COJ8kkQ8Sfu1RGD/htBdq03exY4TSWZeS0x+HSVXhTdwN2ltqw4orEsoQ2Ydu2bWOXzrYME16Xnw7nIJTLw6L0l3EgRWxFRTqWknQCzlwdNJDByu/sgpqtmpRu7KirMe+sU2lpAd6Vf4Gf5G9C2c7k75ms5BLcPtoO90r+ROJ/P5r1sRBCyEBEQXc/J/Sljimox93ax1G0PAlQOV34l7zHQS9RwpWrRUmGePJvCqFwimeJuBKs9ZsOKM7ZY93KOQhNNmIKtjptd7eChuLEvbDjGtEsd2SPvy3Ww8UgeLoxGseyul5Q7VBKHturLZCFtr2qzgRMxxGXK/Gc9k7s62JKe32zFuGN4gq+80jx8bdHGSzu8fWkft39WlJ+BUYgg41dh7UzYdXCbdxSvK6/Be+or+h2i7++rEmjh1/1ETaWh4rF0trjZqtEiJsNK6pozhaBpG1yuRzfffcduwjjzvjuYBbUGg2+lb+DqyT7kLLpLbZnn3Ss5uQBdiyyHnqqO8e5dCoPduRqi8x738ViZ4xqzh6QyDr1O7dZR+Jp2VosKP8J6SXdLyhKCCEDGQXd/Vxcfg20eiNcbRXwc24n+D2XVAGDj1goxafmOKvUbWoV8WmcuPdSGXF2T+lzycLFleJRzce6HDQI+8GFFG6BIXAe6xXaFi500anWYYeSs9BVFQm72ERBrdILcAps/4oyKzTMfwO7DWOwN61rBc5OxB6DF1cBDaRwHzG3w+v6jhUzB8KNGcgsKIY51TZr8U9CEZ0Y94DshEOw4jRsvzbvGtrhdeUeQ3HC5wYkG/1xLNs8lfn7ouPZ5RjFpbGx04gLF8KcPcQas/gTOJkoTlgRy5HJZLjtttvYRRh35r2kJnI13FGF/NEr2feua16Pjfui6GW6AGWx+BxpvCa0ex3Ozosd5U0lZn0+myrEgmg1so4zrs7kMO121j5sGJ+DPTv+NOvjIYSQgYaC7n5O2JPtiipMCHA0qYeqbO4zeMz6dazVz8VxE/d1704txV3ax7E29ANg2NIOrysNFU+gZ0lOYF9q1wq/7Esrx2w+ho1VER2sBjsHocFaXFmvT97V5eI/TiVigK8LmM0qo3dkcqAz5BIe+VVNrHK6qarjt7Njns1oQN5xOx6Fsz9KJJ6QcgZkR3ft39eeZzbG49410Xh3x0mz3i45nzZLLIpW5jC6zQKE55oQIGavdLX+Qn9wIKOStfz70v9dcG10QjjXrbWf4wf5W/DI+K1HHh/pvC3/7cbL+BJ7lCsxce4VKLcfDhuuGbK9r3W7oOZAz1oLbBQnsx1Cp7d7PZmTNztaq827j1pTVcCOTQr3zv+SlSOqgpaxoW/aj2zChRBCSNso6O7nUjOzcUz5AN7KvxnQmFCJ3H8KlMEz2d6xoyakYgtVxPemlkENOfwnXQbYiPvL2hUwAzpeDh+uHOlJXVvpiElIQBifD4Pw5xrU8WqwNFxc7Q6vO4SC6ibT7yu3CiOM4oqbw4h2KiifQSWT4GavfDwpXYuDiaa3DnMsFgN8feCcTl2/3EVcAdFnmW9fd0lWAuwT10CFZqzbn4jCnHSz3TY5m5AN4VTRUoCwvWJh55jirsfVkj1wT18/YJ/OyPQKNEMBt9GLOjUR4TRc3PYxXB2DohrT/5+TzhP2ccfGxrLLhfZ0C9sE7KM+ZuMyz9ng7T3hcMV77Oulxj1Y9+cWeurbkZiZh1Be3PvuMrT9oNvGWWwraa8zbxcLrk5MV9damxB0CwVTFzzEjvNwDNsOHDPrYyKEkIGEgu5+jLXRyhNXzWRK6wuulJ5r4hDTV9DiC2pQ0aCBjUKK8QFtt7c6i1yFZi8xuJAWHDa5wJnwb/wri8Ns9btIm/7eBfesK4aKgfIcSSz2dqGiqlBl/SrNi3jP71PwwR0H+AzH4aH6D3G/9E9UJeww6b5ySqswSieubPiM7zhNv5VVaMu+7qrjZiuslf/PB6yS9mHFA9gpfQgV61eY5XZJG891VROGGsRsAvfhnZtoGSPPwzuyr3B983qUtLT0GUiE1U+hO4FgWpBLp35HFSbu+47gc3A8kSaJLEmoWD5mzBh2uVD18i17InGRQZxIdF/yHDtK/SehLOAyVpF7TNJbOFlMe3/bEpNXg2e0d2KHw9XgOpjMdnD3Z0cXYyVbHTcXWYO4ZYmzE1fSO4tzj0Cx0wSWgaU/8g37zCaEEHI+Crr7sbTS+lNBmzzoAv252zBNno6Xpd8hqHhbp1te7U0uxGb5/+F9x98g03VuZd16yWtYJv0UP2qEVHbT9qUmFtaivF6DMpkPhsy+9cK/4D8NDTJnRBtCcCTF9H3d+9PKoYcEPiNnAQrbTv2OIUgMANxL95t0EnTwZDHe0N2AfVZzofK5cEqtwGfMIqw2XIp3NZfjZEn3C2s11dcgrERcfYoKehC2aMSIhkNIPSKmvRPzis6twkXqt/CS3ctQ+LVdEPBcqsAp0IOHH1+G+OSW1oADyLGUHPwpexbv2K2Hm3Xb9RrOY+OGUqsgNqxKbLufMTEPYduSl5cXu3S0hUmYUJUc/ogFX4Uu0yD1OV192/XyN6DhFKzexpbfvh3wlfi74nCBFr/q5yFn3LMdXs/GzQ+/GubjK90lKDVjlodKLe4RlzmaFnQLHOc8yI4Xa7Zjf5K4N5wQ0jP+iC3Anyeoh2Z/QEF3PyasULf25+YD2k9Ha49LZQxule7AEv4wonOrO/U7pYm7MZrPwIzG/1ghsc7gPEciKHTEqSJsptiTKq5WTwt2abeH9VlkSmTcchz3ax/Bziw126NtSlX2uHzxeZgR0rkVN4HDSLFP+QwuFkdMqKa8K6Mea/QLED/xnU6l1ArkTj7Y4/8g9hhG41BG99MLE/75GjZoQh7niZk3Po1jzpey7xt3vAijgaoNm5sw6VQLa/AhCztsi3UWpR1KrILZsCp5Lwaa4rj/MILPxlzueKerJgu0/uJEo13RQQriLEilUqGgoIBdhHF7th2MxhK9WGvCZfE5gaO9D+qnPoXX9Lfgs/wh2EV9nc8iTEIIE3KCsf4dZ5BxCht8YbsCn+gvR3Gd+fbIf6y/Ck9o74E8qOM2hm1RRFyCCoUv9hpG4bdDyWZ7TISQjuVVNKDst8dQvOFxVNQNvEy4gYaC7n4sKSMb4VxL/2t/0z8oT/frTsbxzAsHw0KV84AKcS+xUQga2qki3paZoWIQu++kaYFiZfy/+EL2Pm62i+307wz3doSztRz1at2pE5nOiEwvYStun9p+D09559+8uIAZ0HJyeHMVSDpxtFO/I0wGHMoQA/RZoZ2vFttavE1wOLN7hbWEoNo56Sc2zg+6HhKJBCFXvYpGowLhumQc/Uf82WA+Ed6RVIJSM36QHc8R/x47tTXjDM1eYrcBqyKxrdZAYl0gvqc0+piWreMyQuyMMFoXh6wuFDEk5iO0A9Ps/wgKTodihzGQB54/Cey04DFIpj4AHaRYtTXZpAnRgS67rA4XN2/DSGkeIjwv3IXE3U6csCs203YTIUNrT1MgNuhnw9knzPQb4CVouPMAVuoewF8Zpn3uEkK67uihXbhL+jfukW5FSmoiPZV9HAXd/Zg+O5Ltk2u0CwRsTSt+wniMgkZqw/pfl6ZfuPXOvtRSzOPFIlBWEeLqbmfNVqbjK9m7WFr2ZaeDGGGvZ2DFbiySHMNYfef7ifM8h5khLhjCFSEyqfPFzbLiD2I4n415hkhA3rnUckauQrWbGBRxGZ3b133iZBaW6bdjpKoKwzztOn9fQmEtP2tM5+Phl/lLt/bPJR79D4GGbDQZ5Ri2+H72PRcvfyT63cjGbsfeRrPatHZyA8mawzm4+8fjuPvHKLOspApbOO4ufxNPSX/FBBfTqvw6hs9kx8CmhE5vBbmQkyV12G9i5om5CcUOR6jFCTXnkWIQ3VmK4Bks7T6AL8GJ+DgLPULSGX/FFaKwSYYGKOFw0TPtXm/F3GC42CiQX16DX/aJW6MIkJ5wFK/JvsWvspehkFz4tCzAWo8QLh91ZeZJ5S6tFd/nFVIe9ladzzY5k5+bAxYP92Tje1YfQFTLBCMhxHKMiX+cGhdmJNBT3cdR0N1PCRV7Q5rEQFQWJJ6Qm0wihdZHLHLmWHLhImdJCdEYwpdAz0kvWEX8XPZcIxZKorCYP4wDJzt3or//ZBnmtLQKsx5uWpD/VNVL2K14DJqkbZ3+HXn2Hnas9ZzKnhtT2AwXW5mNbDyKvMoL73UvjPmbnWR9IXuXTRKYYoSDGmvkb+BJw7c4mStWnO2KhgNfsmOi8wLYO51ebR9xzQuohi2GGPMR+btYiXiwadTosOm/fdgmfwZjCtdiTyf/ZjuSkJ6NKyQHcJ/0L7jadm5rRivHcLGAnpDZEpfekt3SDTV1jfjy8/dwy+rD+KsX94JFxycghC+AARxUobNN+2WFLf4NX4UF6rexo1BuqYc46AnF066++mp2aauQmjDx9+nuDHyovxK/Tv0byvCF7T5nQgHOtyfU4x/5U3DY+wLLniJAY/pB9jSU2I7oVAbZzVWfYIfiSXhkbTbL01dWko+rJHuxyCbdpNaj53rrqpFY7KfD78aV+GP16zhswnYrQohp8isbMK5hHxs/qrkPf9SF01PYx1HQ3Y/3hu4yjMEWxRLIhon7cLui9UR3IhIRly9WEG6L3mCEVZa4ilvvObnTRcbOah3GyVgxqJTEzqWKJ8cdY63GdJwcGGLaxIK9v7iHPKzuUKcqPudUNGCEWlzFtx9u2oqbwGqYWDV9CF+M/akXDmKUueLe3AZv0wvgyZwDUCrxEPt1x+7q8pt1ZU0tDEYOrnMfOPux2Toib/gD7GeZqXEoqxt8J8bfHczGA5pvMYzPwdPSX/Hj9iPdXu0uSRTTqEvlvoCNaVsKhEyWMpk3y2wpTD6M7jr0+/t4F+/hB9lbrEe78PffG2qSxCJoJTZDWc9fU7lOvh5pRh8cyqykqskWIrQJ++2339ilrZZh2xOLkV5aD1ulFNfMHME6OnRk9lBvBPFFWMbtwa+b/7TUw+5XbMrEzx6Dz8ROXd9gI2a2SRq6Pul6puaCOPxP9iWe0H3VrdsRJlU+HJoKf74Ur/BfYcf3r+BAmnlbmxFCREcP72MLYc2Q41/DeMTmVbNzddJ3UdDdTx3PrkSkYTiORzwHhIg9a7uCawlmhaqyxzPE6qVtic2rwjSDmIJuM6ILQb7CBg3uYo9pefbOC54gCz9XZosn5HVCkC+3NunurIaJK8+z+BPYlyK2QunI4eRsjOXE/tyKsC48n85BWDt2DaaqP8KetI6L0pXVNmN4s9iz3HWM+DhNVekqnpwZssT2PKZacyQP92kfwYOea+A//Px6ABGXPYqHHT/BKvW1eG+H2OJqsBAK6h3cux3zJGKWhZLTYmbpT6ydXHfw+eJ+7FrX01WdTXFs4vsY0/wFNlaJVbu7qqisAmOyvmbj48rJrPbBoz8fMbmdn1l6lhdHsrE+wMRV7hajfB1gLZegqlGLZDO0ovo3NhOvvv8BDqQUdPu2Bgq5XI5PPvmEXYTxua9h7PbvMZlPwm1T/GGnvHBqMu83AeWBy9h48sm3kVjQuSKeA1VNkxYhGnEvpsvQzk3CShzECuPKJtPbYrZFUyn+vTfITZwMbINs9hPQTRIncv+P/x4HfnwRu6lwHjGDpMJaLF31Cz7Z3re3piQX1eKb/Zms1oUlGRLFTJdi12kwym3YZ3lGWfe72hDLoaC7nzrW0nprQkDHfasvyH0E1FI7VBltkZ7RfnC1O7kUGQYv1EicIAkXV3VNZd2Sgj1BG3XBE+SkolpM1IlBvu2IzvWwPovvJDRLbODE1SM77sKBaWXCTsg4Paqs/ADHANPvTwhUx86EETwiMyo6LBIUG3uUFV3TQAaHMDFt2FRWLRkK3jXHTZ7ZbNLosfaYmKK8dMb4Nq/Dy5W4ZZmY0r/uWC5SBlFv3S/3ZSCy2R+vqp6Gcehl7Hs3SHbhp+2RXV7tFl4jz1pxO4gqyPROA4KQkVNRBTvE5FVB240P85jf3oI7V4VSiTuuu/f/MNsqAx9V3I3Nv4jbDXqK0PKuUGuNUqMj3Eabnl0ikEl4POQagw9ln3S6iGF7csrrYLfpJvxfzYsw/HI99iR2P41/IJDJZHjggQfYRRifaV9iHu6q+wxr5atwj4c4adkZLktfZy3EJvAn8e+GL/tl9fnEwhqzvC8mnTwJP66MbbFwCJnSqd9ROvmwo43WPDUZDDVidpZa1YXaMOfiOEgXvQbdtMfYl09L1iDm5+dYRgQhXSW8R/y14Vts0t6PwCPP9dn3DKEo4ZrVH8Ln33uwKdJykwPFNc1Iq+ZQbHSE4/ir8abtBrZtJydOzKgjfRMF3f2QUEjJqSQSE7gUjPdpv4VLp/A8Mq/fhxmaD/FvgbLdAG73yTI8p7sTOxfv7XJQKg1dwI6T+WREJndcACYyMQPjuVTx98K6cEIukaLJTwxo7fJ3djjjKPybHYvFNypdF1fcBBFedi1V07WIzmm/snhd4r/sWGA3hhVh6wrvUWJv8AhjBlJN3Ne9e/8+qBqL4ONohXlD2z/JEiZ0lozwhD+KsGv9J332Q86chCJ/Qmo5wGHyJXeAu+ZHaLwnQ8FpMb34p1MV502VWlCOEUhnY/fhXZtoCXK1gYNKhmatgfWv74r03HxMLV7Dxo1Tn4SXsz1eDMtj2zgWZryG/cc7X7Cwuw6ml2OV7mY85rsW8sAu1qUAsNi4D0slkdCd7Hq/buE94K8f38NkTlxxnMmfANbdjB1xFHi3R3g/SNv+KVy5WlTLPWE73ITJWHtvNE8SeztfXfUV/j3R+YKXfcHRrEos/eQgLvvkINJK6rp1W2XJ4mdPkSKQtQfsDFtXP3Z00leY5X25NU3daOsFsxAC7wUvQD/7OfblSsl6pK19Gn/FUgYJ6ZrdSQV4qupFtsUqXJeK/Crz9ag3px8is1HQyCGYK4Ax8lOL3c/fCUX4Un8pHnRfA/vx12KYrAjhfB6as7q//YxYDgXd/VBMbjUel67FBsUrcM/7u9u3FzokgO3FqlPrWFrMuYQ90cJJvrBVb2ZYN2bCXcNRr/RgAUxl0u4Or5qQmoZYYzCqbYIApyFdujv7keIK+VRDNNvr0h6hN3eu1hFZ8ILTyK6t4guEgmgf2q3BEcUDSGxn1U1Im3ctFYvmcMFzunxfUucAlEnFfd05MZ3f1y2coLkcehX7FQ/jNf9YSC5QxO35CRx2yJ/AnRXv4VD0wK8Q/cV/yZBo6zDGzwHzh7qxk0f5/Oeh5q1QYbTDhzs7v5p3puyEQyxNvY63g8Q1tMt/X8847MQvslXIOSEW/TNV6u+vwYFrQIEsAAFzbmffG3LVayhUhcORq4d8y/0orGrosaBbMD3EtdN96tsiCxH/H3lWHu1yBoCQCvhx6UisNl6Guoib2SrsbD4W0t9uxvbYHPQlQsX36746hFu+PWq2SvYdMRgMSEtLYxdh3OpIWjEW165nY37Goyb1WBfYzX0MdXI3NuGTs+VttkLUHxRWN+H+n6OgMxhZRtPz6w93K41Ukn+MHevdOr/txMFDDLpdUY3qhu7X3LBqEreWSe3FtHVzkcx+Evp5L7PxAu4Ynll3GBuj8816HwPVT5FZuOzN39kEz2An/P9K+Ess6lpmtMOlmtdwvIOFjd7cmvbZngzYoRHBfCGmNu5ESpFlts/8HS9mjiwa6c0WmYzeYtaiTZm4LY70TRR090MnMvIwnMvuen/ucwiB1zh/R/Aw4Fgb/br3JRdhFJeOUd52rN1Ll3Ec9CGLcMQQjuSSRlYhur03ri2FNrhK8xIabu84OO8IL/QSF6px89k4Fp/c7vX2p5XjM/1SvB28BpJw06qknytEVgZ3rhrGtLZbhyUVVGKUIYWNvcd2IW3+DJUu4r5ubfahTv9ObFwMxmujIeGMGDvjkgte3zNkNArsRrGJkpq/X+5WWnNfx6rOR3+HvYpH8XZwwukqvkNmoGp5LD7H1TiSVdmliryF+dmoMNqi1GH0BQtNdWSC5CSmSpKgzzQ9hSwmKRVzqn9nY37+C6erJEvlcLn1RzRDgUlIwM7Vz1t8L5rwd5SflQIOBkwLdunWbbmNFP+fj0cS4nJNT7dNLa7Du/+ehBpy2FzyGmyv/gSSG9ezwHsOHwvZxluxJaZvrHgLk4fCCuvhzErsO1mG+9ZEW7zfdVNTE0JDQ9lFGLeK+/sreHGVqJU6w27yrabfsFwF+cWvsqGfOg2r92eirxMmBl7/fiOa6mswwk2OVco1eLf8Xny360SXMyxerl2CGzXPQDrxrk7/nsLei7XLE7ZECZXHu8uuJU1d6SKmrZuTZMYjMCz9DBuGfYJ6oxKPbTiBtUf7xv+nvmpLXCFW/7UT3zc9hL0bPhr0xbE2H07BDU2/sOfmgPddaIDVqS2Wfck3uxJQ06RBpstsNPLWbELx+G7zdBg4U2ltM3S5h9k5+6LhHux7LuFiLBCoSWF7u0nfREF3P9SQdpCtcNZbeQMOvma5zac1HyNWcQ8qUs7f/5wbtxt/KF7AN40PCUul3bofu8vfx2PWb2CPbjiOZLY9U7k/vQxClnuImw28ne27fmc2rogPfwR3aB7Hjqz2VwNaq6tOD3HpVkAksI4Q960PrT/SZj/yfRlVmKb+CB+5vQKZl1hhvav46Q/jIvWbeL76kk4HSWW7v2DpWam2k2Dr3YkVV46D87I32XChdhf+2bkTA9UX22PwAL8RzlwdQpzOLhjl4e6Bq8eLJ6Qf7zJ9tfu7iuEYp/4CpfM+6tZjlA0RP1hdK6NNSisVrvv9zmikGn2Rq4qA58Qrzvq53D0MDXNfY+Pr6n7Ar5tP9/60hPicUmzEY4hS3o9hqu7ti+U9R6Ket4MN14zMGLF9SmcJAevnv6yHXq/F3HA3XDNefD+VBM9mgbeWkyPeMAQPrY/D5pjeTY3dGleEn796G6gvRai7DezlRkzP/hivrttj8a0f9vb27NIqJrsc8yvEk2DD5BWATNml21WMvhYHpn2Pe7WP4NM9GZ3qNNFbhOf4zfV78H9Vz+JP5Qv46jJXLFPFsxNrh/0vsckbUwm/U6pRIFY6GgERkzr/ixIpfldcgXe016CkoXuTLkL2lZNBnEi0cxNX0M2NH3Mjnr1mNm6Z4s9OITZuWo8fI/v+JEtvOJJZgZXrTsAaahwyDMNtDavx17GuZVgNBMLiTO3O/8FF2Mai8of1lDuggAZFGfF9ro1v+NFnsEH+Mp6frEBl4FL2fee0DWafGD10JBIb5S/hqOoReNuIk+eOIZNZXQh/rhTJaeJWNtL3UNDdzwgrRE7lYjqawa/7q9yt3BVa2HGNsC46u1gUu798MX2Z9+reKp2A43nMENJJhQA0re1VqaOJabBDPWaHdb+SqvuSZ7DLMBbRhU1ttr4SZgTr8uIggw4zgrt/fzYtQfcEPgWHks5PSxVWp+qggv3opd1KqRUEDhvH9gHWqju3xze/rAITqraKj3Pa8k7fj03QZOS4z2er43aRb7JquwONsC/TK/FLFnA32wcBY24+7zr3zQ7CdGkShmb9yLoHmFLwREgJ5jkOI4K7N0nmPkJMpR5lTEFmaeeD1R1JJfijwA7XG1+F8tbf2vx/7DzjLhR6LWSrZ9NPPI3INv5+zSUzdi+sOTWkEgn47qa08jwq3Ca33LBpafc/b9mBt2qewiblK3hrse9ZPYqFwJtfcRT5ox5h7fMeXR+L36J6PjVWeD/+bFcq8tc/hnckn2Kd3YfYeM94/B28GfdK/8JVqY/h/W2WSym0trZGdXU1uwhjwdGt3yKQL0aDxA4OM+7p+o1zHKbNX4axfo5o1Ojx1j9iFlBf9NOBk7g09SmWyeRhr4KnbxCsr/mSneheze/Brz+vNjkTKCpXXK0b4+d4wa0+5/rbYzk+1S9DQXPXJjxalTeosVJ7H57U3gNHH8v1+RW2x7x8WQQ+DE9mhfdUfz+M1fsGbzDZlvTSOqz8cS80egP8h47FdOsCVjOhdMf7/Wb7hbn9+t8RXK//i42tF7+KicoCxCnuwqt1/8eyIvuKDX/+hSX8IYzj0zAp0Akes8TMlbmGI9h7wrwdYNRx4up5o2M4y1RjlPYokYuTZqXJYlcQ0vdQ0N3PCMHVOCSxsU1414t+ncs2fC47jtLGI7P89J7OqJwqzDCK7a0cRnW9H/iZZoW6wAF1yEg50easu2/aT4hW3ItbmsSCT93hZqtkBc4E+9sI8o+ml2Cd9EWcUN4DP5ih56lzEKoV3pBzepSeEAumtWpQ69jzKZgV2v0AXzhJmzjEmY0PdSLlOebv79m+3XKJG7wnii17Osv7itdZOuMsHMcff/6GgeabbQdwh0Ssj6AUUl4l0vOu46PJwhrpKta3e+32zq+oHs8W/u6MCPewY7UTukPuNQpNnBWbIEtL6Fy1biEL4u3tYlHCO6cHws29nWJJHAevm75EtcwNaUZvPPd7jOV6tLcEx5VCsNzNySeBKlwsLBhQe5xV5++MEznlGBP9DNs64eHmDlfX8+tVSJyH4K0rR+L6iX5QGpuRu+lFrD+SgZ4itHF7dt0RBO++D8ul4oTZkKlXwEalgtfip6GWOWAUn4kxhx/BTwd7JoAR6n4cK2hGlsEd6nH3sHaQ3SFMdLx4aQQcUQvnE18itiUQ7UuELSWyf59hJ9RqqQ2sb1kHKGzBBUxD81hx0uHe2g/w/X+mTX4Y437D09JfsMTJ9MkcD3sx2C6p7d7/UWFS8KBhBPaoLoJU5QBLEl7ry8YFCLPvuEqyD647HsTnO9vf+jWYCCnDX379GbYZH8Bt7pl47/qJsFr0EvvZ9dpN2LB38O3VFT5/Nh5ORZwxEJVOYyGLuAwOfsNZpqeQYZKQnIC+IK24FuPTPmDjqqDLwXmMgNRnLEpVwezzpehg989lW5XXqzGiRtx2aTPmyrN+Vus8Why01IkgfQ8F3f1MbEYBRnJiWhYf0LXWQ22RBYsVlYWTiqj008Fn7IkoVhBCDwn4EPHEtrtmNu1ElOJe3F77BVsBPLdV2CTdcfam6hFgnln367zL8Lh0HTJjz98Hm3ViH+y4Jhglii5XZT8Lx0E9RHyeHAv3nrUX63hSGtZJ/g8v2vyBACer7t8XgMudsvGe7DPYx3zR4fWEQMQ/81c2rhp64+n9vJ0kdQ9DcdDVbByR+B5yygdOL8gTedUYk/EFrDgNmjwmAGHt7Ot3j0CT/xz2tzk5fzViOhkc6GLW4rBiBZ5QbOz+g5VIUWwnbktoTOtcj/Yde/fg0srv4GOlwfJZF+jxrXKC4t7d+J/jC8hqkGHl+lg2EWbudMHAWvGkwGbofLPcpsuIhWzFkYcex7MuvK9bWDU6+vNLGM1nsL13bjd+1W4Wj7BC9/qyCPzp+hVWSn+D7Zbl+DnS8ul7VQ0aPPTlNtyYtBwLJVHQ83LgytXgZz8lPlaXYChu+Q1aXoE5khOQ//M4/ok3w8ThBXy6Ox3/Gcbh3bCf4bTgcbPc5ihPFXbZ/B+ek/2Cnb993qc6JQifUTt/ehPXS3ayvzH5Nd+xydVWqkUvod7aHx5cFZwPvmRSG7GAku24V7oFE3lxUswU3lZ6hHD50JRldDvoFni2BPGWxo24Cvy1P0DPSXGZ5BCG7HkQH/yT0Kde854mTMi/sfpnvKx5F/ZcI572T4VSJoF85FWotB8GW64JkgP/61Mruz3hw50nkahxx+uu/4PDXRvF9z2FDQqtxK1xFcmmbSeylC2bf8FUPhFayOB8qVg4UHisknG3sOHo8q2n/p91V+TRwxjK50IHCZzGnr14ohwyCRkGT2TUSQb1/6e+jILufqYm9QBL/6xTeACO/ua7YZdQ1Muc2axc2Zn7ulO3s0Ol6wSWvmIOKr8xLFW5rdZhx+KTMJLPYmNZV1qFtWFR4xaskP4B19yt5xUkkWWLM4a1ntNMDkTb4zJaLJA2xRiN+PzTlSuLY7djLJ+Oi6XHzbK6JxhtU40rJAcQXrWnw9TG7YdjEGjMgxZSBC68r0v35bX0JVTxTtipH4N3/hGzLQaCX7Zsx9WSvWxsteT1DrdQWC34P3a8nN+P9ds7l8psVXSMnZD72HZva0Yro5/Yy9ehTOxjf6HJFtX+N/CwdBO+9fgddsoLV5i2cvbBpzeOg1LGs+yQr3eZdzUhKjUHIzkxUHBuKYLWXZzTEPxf2F+4UvMyIrMuXC32u03bcItanIQyLnqTtbDq8PZ5HsGXPgYdJ8PFkmNw/Ps+/HjAcivLGWX1ePLjH/Fy6YMYzmdDo3CC5PatwIirzr6i7wRIr/keBvC4VrIH6RueM2nrQ2eo1Wrcdttt7JKUX4GtLYH9A3PDAJl5Jg+FFEnZxDvY8Lqab7Alum/s9xUmZz789ic8YVjNvtbPfh5c6Dl/s3IVrK/9igXkV/D7sHbN151KMy+tbcJQnbjK6x5hesu8GVW/Y4fiSUwu+Bbd0VSYhKslezBJ3oNt24ZeCsn1v0DHy7FIcgwjDq7A8xuO4/eofOxJLUVCQQ3bI2vpIoF9gfC38uIPW/Fs9UtQcWo0+c2Gcun74g95HvaXvcGGVxn/xS+d/MwZCIT3wF+PiueHzywZBl7leOpnbHJc+K9X2LlsL0uKyi7HwsLP2Lhh1G2Aw+m6CM6Tb8I6m5uxXPMofjdT1f6m2E3sWOg4gU2Sn8l99nIs0r+H9xov7rMt1QY7Crr7EWHm6pdSfyxVv4Li6WLRI7PhODR6iSfzqoLIUzP8IxrEytg2I7pXafssbsNYqxhhZbEk/ux2V41JYpBfYRcB2HajPdkZnEadbh0mtAdrJXyoD28WU+ftR5gnwBdIAmciVxGMrfrJOJByuviSTYE4K9vc0j/cHDxHiSuFw5GBxOzCdv9uvohuxCT1p9gx6iNI7Lr2vHJ2Xii58xi+MCzFloQyHDPzyX1viEwvh1X+AQjhcGPQEsBXrAjfLp9xaAwQ97dPzP0a8fk1F17VbRaDVsfwGWZ5zG4Rs1FrVKFcLWmzWN+Z/v77T8wyHmVbAwKWPtvp+whxt8UbF/vjQ9mnGLXvbhxvo6tBVxXH/ceyBcrkvuDOOEHpFo7D2NAhp17TjhxOK8b0hOeh4HQo95oL6wk3d+4uQhdCcv3PLPBeLDkKp+0PYPVe01coLyQyoxyXf3oAKxo/ZZM1asdQyO/d3e7fJhe+GMYl77LxCv53bPv+DbY31Fx0Oh1++OEHdvl72yZcx+/EonAHDPXsXE/pzrKZ8yjqFO7w5ipQuO2ddrtb9BThffPZjXG4qfoztl2oMfgSyGY91uZ1Ob/JaB53L6vXUVpZjc/3XHj1OTkpnu3XFSZCbQLEdj+mkDuIE0VWzd37vyl8Lr0j+wqXNYqdDXpM6EWQ3rgOOl6JeZIYhMa9xSqb3/bdMVz58S68+tbruPn/3sPSl1Zj2Tt/4prPD+Den6Lw/OZ4vL/jJH46lI1t8UVi14l+Svgbe33DAdyf/yT7W2h0GgarG9ec1X5PEjQbFR4z2N+gX8y7rGXdYLB54694kl+Dy0KtMDlQ3EbXyiFM/Cz1b4jv1b3uwut3YNOXiOBz0Mxbw2HhM2dfwdoZkjlPowjOWH88r9urz5UNGkRUixMvqtFnp5YLlHLpqfflmA7a5JLeQ0F3P5Jd0YiSBj2S+VD4Tr7c7LdvN1Tc1z1ME8cC0oMJGZjIi4VtrCLMGHQLKdgB4n05nJGCLRToCqwWe1jLhna9X/a5JCHzWNARwhcgJi721PcPJ2ZgVMuKmyp8gdnuT1j5iJy3Ca/rbsSudDEoE9KxR2vF+3Ybbb5/G+8UgHKpO8t+yI1tu72a0F4opbgOBpkNpl10TbfuL9zbBddOEAOlVVuSzJ563JOED0Bhr/P3+kX4IvxbqJZ0biJLtVBc7b6Mj8T6v//r8LqJ6TkI4cSJF2czBd02obNwncMveFK3HFEdtE0R+vd6x7zDxnm+SyH3GGbS/SwLU2CRNJplpBz7+UVUN2pgDopccfKp3tt822MEU4PFE7OTBWXtFvsT+lrHr3uJtRFslNjC5frPTSoOyYVeBMl1a1hq7CWSI3D/7yF8udt8gfe6Y7m4ZfVR1Dbr8YXLc2gOvwKK5f9dcOuLZMId0E57HI2cFVI0Lrj122Nsj6g5yGQyvP3223j2pVWYkPM13pCtxkt2YmEjs5JZQXHxKja8WbcR2yKj0Zu+j8zGxphC3K17EiVBV0N19Zcd/q2oFr2IyIu2YpthMj7amYakCxS3rD0pZpQVqYSMAdNTu1UuYlFGB13Hk0wXwtWJmQs6a7H1UI8KmgvpLb9DJ1HB090DM0JcMMzTDsNsGvCZ/COsU7yKP7ASmxtuxs/Fl+Hl9CtwQ/SNqN/zIf7vj0Tc/3M05vxvDyvA19laDn3JZzsScEnSSlaUsEnlBdXtm1itgHM5LX0d+RJf/KmbxCYcBrpjWeVYWPAJq2PxsuM/5/3cdZiYGRKGXCRnnZ0t2ZN2JpciolJsD6ud8hALss+1eIQHrOUS5FQ0drvneuTx4xjOZ7HzWZfx5wfdgjG+DqyVWHJWzxf9JBfWvao+pEe1riyO9LFn+33MTRk6B/H/DcfepmEIy6rEjvQGrNc8h5XhVZh6xh42c3AceTFwci2mGGLY6rNQvfVgaiFmcGIbCLuRZgzyrRxQ4TQGbpVR0Kb8C1wiVoCuStjBVizLrYbApbsVlM8xs6VQmtBXVwhWYmOOYSlXAQ1kUAWbJ/hqVe06ES5FfwHZwknc+at2v+8Xgn0jrhjrDXvVhdOLL2Tl/BBUndiKa0u2YUv0d7hsfOf+NkprmpCaFAN18nasVs9Dbo24kiXs4Z9niEQ1bFADW1TDFjVsbMPGufBEE+QQwntholj4+3/7qpHwtO9eaqtQ0Vt4faxkElx1yWLAtpMnvl6jUT9kEWyy/sGE3K+RUDAfw73b3npRkiimrRfLfOFh3b1+1KfwEowb4oqkkhwcza7ExSM827zatj9/xQ1IhAZS+F7xisl3wzkHwbj4HWDrg7hLtxZvrZmK5+6+8awK312Zqf+udgLyJTxumNC9CaBzeVpL8KdqFcL0JxGZvB9zxp4/ybBqSzKiGsZgutUxDFnyJGBreqDBhS0Cf+1P0K+7GZdIDuPnnc/gE+NbWDE3pMuPXZi8emdbAmIj/4bOEIHLRnmxv3Gl7Jx08g7I5j+P+mHXo+jXfBSUN7AVw3XLJ8O2E1sKOiKXy/HEE0/gy59/xcy0FLaX0GPuA926zXbva9TVKPjvI3jXx8Mm9Xdg9gUyTyzkUEYFVm0VU7/vvngy3GfccOFfkllh4eQxuCjdgO2JJXh8fSw2r5gOubTttQ15kVjXoNnD9FVugYO7OPnpYqxgadjt3c+FKBuL2VFi306BRUsLmA7pAwexUNOIhR7Dxe+Ve8D4xxQY6kuBxnJI1DVsYtkd1ax6fInHLOTburNsvNyCQow4+CDuirkJd11+MeaEu6E/2HA8Dw17P8Y4mVCczxZWt21q9/2I8xyJ0lv2Yvvnh8FH5+OuGYEI8zg/OB8IhMnw/Zu+wEo+G828Co4LnzzvOpydJ0qlXnDTFaIgfh/GhJqhHo+JhMUiYbInQ/sYPgxNx6Wz2u7ioJJL8VhgLgIz1iBl15WYFPhwl+9zQ7oEX6pXYWVEA+a0EeALlhl24AnFmziUIkxMbOjyfRHLoKC7HylN2o83pOshtxPaUk01/x04BWLTqK/x7cEsXJNejgMZVWgyhsN+gXlXpASS4DmsOFsQX4Tv4k5gjN9s5MbsZAVD6qVOsPEcY9b7Uw5bBByIQnDNIVagyN5KBocicaVBFyAG4ebk5WCFCDc5nMqP41BKKBqTxdnQEoex8JWrzHpf1mFzgKK/4Fsbfd7JV35lPR7IvB93yBVQDf3eLPfnquLxtvJ72KmL8Mnf76Np5IewkkvOq7osrPScyCpG48k9cCvehwna45jBl7Kfr9ZYo8AQwcbeklQskbW9Si+4Rv1/OGocemov9ZzsWNz04V149cbZmBrk0uUPzL+3bYY/J8OSadNYlXtT2Fz0PEpWJ2KnZgy27UrHFzePa/uKeUfYodZ1HMy5jjQ+wBE/Hc5BQpawpUB8Hs9UUNWIESkfQsibLwm7Cb6OXUvjVo6/GTXJ22GfuQU35r+CNftG4+ZZLSfGXUydjjGGoMllLO5vWa0wG6kcbnI1FM06lMftAM4JunellGDd8TxwnA9qbtgGZVDXT86FlG7JtT+h4fcV+EU9F4n/nkS9Wo9Fwz3gpJLDyUbOVjc6M0EhpFE/98t+XJnxHB6XJeHPYe9j2TWLTZ/c4Dg4egfjh9u9cMXnB6EuTsbL35Xi9bsv73JA1kpYNQ9J/YrlxlUGXQE3h+61vmsXx6HGdy68k+NhVd07vWaFQO6/NW9hCWTgR1+FO6eL2xY6Q3jNVi0bAXnmDiyvXIvV/36N+xafP3EgvD/6Nyaw/5/2LamyprJza1np5hqQX1UFH9e2T8IvxFojpqfLnXzQa5wCz/7aJQTcnf/g1KeKTg00VrAe9WgoxxwHX8xxDWM/yl1zP/zSj2J+cxS+WrMTm8OW45nLxp2q7t4XCa1Dn9kYDxiWYIG3BmMW3w24dVw4dqy/My4e7oG/E4rx9j8pWH2buK95oNl+IgfX1HzH/m/opjwMtDNZnR54E75KLEBtlRMu6fFHCbZHO620HvZWCsy8cgUgb39y82L7XHhKTuBAnhF1zfd3aSJUKKJ3MKMCOlEhEoYAAHSxSURBVGMg/C9qf4uil7cfbE40w68pmb3PKKTmX6AjXUdBdz9im78H10t3o1gttGjpfJ9lU0wc4siC7k0xBdDqjXCzVbB0L7NT2qPCaTRbfdal/gvjklnYWGCPHO2duGu8N2zMVGislZ2wJ/3Aa6zC5H8peRji4YIvm+cjR+aCBydfB0v4Tvsk3OSZ+CbKBsEVh9iHiDTUPBXgz+Q+Yi6wR9zXHZdVgHEhp0+I9//7O64XUtc4FayGiBU/u00qh1JIsf7rftys+x0/7boNl0yOQExuNaJzq1hVb2NhLFZwG3Atn8j27jM82Kprts1YLB8ZhifCp0LCcbAptUJxcRAk6mpI1dWQNFdBqq5iXwvjd66dA62z8Ng5WB8+Ds/oQ5ioT8HDq1cgYdHluHtGoMkByl8xWXik7l14KSqg8flZSJw37TnwGIGaOw/izw8PwJhYzCoWCy3Bzl299KoVtxRYBZl3kmyqKh/75A9DXS5HvTruvFZkO3//Grdwmay9mM+lz3f9jjgO9ld/gvoPj2NIczGidz6L+KCfMMKna0UVD6aLre26OllyIU0+04H0DFgXCBNqp1cUhIm2t38T0tpVuGPaEEwONkO9iPDFsH4iHpceKkbi3yn4e99BFO9PZxkbVUYb1EvswFk5Q2btAGcbBRyt5XC2lsOxJSgXgnNbpRQ/btuNpytfRLCkEDqJFS4f7WlSyvu5/JxVWLtEAdfNL6GmSIVX1znilRvmdDlDwWAw4Ptff8GN9cehtZXA9eKnYUnW3sORk+iGvGYzFWkzgbA/9KNvv8cqwzeQyfVQj1to8vPmqpLgNZvfYFeXjaxDLyBh1LrzMmGS8srgBTH93G1o1ya1OaUDmqCAFdSoKs7tctDtKKSnc4CNq5nqK1iCVAHYeYmXc/hd8jR0WyogT/+HFUzNTYvEi+/ehUkLr8WtUwNM7n9uacJktJAWrzMYcdkoP4y69jugk4/x8flD4JnyA+ZkROFIxmZMCup+69EzMykLqpqwbIx5s/5MISwaZG57H4u4clb3x3bWQ+1e13rGA/gm7iAcCmV402BkXSZ68n1i5/Y/oIA3HpgTfsEMQo+ZdwAnPsZUxOOvI9FYOmuSyff5b1Ix+5sJ97BFoGv7bRrdhk4DtgEhyEdCTiFGBllogpR0CQXd/URFvRrhzSdY4GJnxv7c5xof4MR6aF+NvfCTlqLJe0m30kk7wk99AE9sOox9FcMxIqsSJ+uVyJcvxEuLzLi/upXbMNTK3aBVNyE1MQYF9WOQavSDT+B4SP0tM2Os850GnMyEKnc3yow2qJHawH20kKVgXuK+bg+UaBRISkk9FXQLe9xcU4SAEigLuhx+3eyneyb5mOtQu/cD2NeeZK1MHts3FjVGayQZxTSvCA6YpxD7igrFkRr85sJ+1BJYhcxBqMIGZ4X/vsL+fnGPf1vOqtE//jIYcv6CR0UafpGtwnvbU/Fg7nK8efXoTvfAFj7Ys//5FMv4UjTKnGEd0rWVplAPeywe7smqOX+8Kx2f3jD2rJ+nl9XjsC4UUokWQ0eYN5vC1TsY4MUVqsMnMzF5xOlnVJgA+CrDHtbSGZg6YQI8bbp5YmblCOvrVsPw/aW4kt+Ll376CAGPPt2l2XrrlA2Yw8sxc4hp+8s7y0Wohp7+A4arY1iRudYMhq/X/YY/tA/hN7tluHLh5+a7Q7k17p0VBEeVDKV7DuHBBrGK7SlaQFfFo7rKBo9rl+Mvg5jBE8Fl4VLJYdQblXhL+g+c+TpoVJ6Q37we8BzZ7YcVHBKOJlsn+NXn4erUlXh/27dYueTsv8/OpHlmlDVgf3I+nrr3TjwlVBT+7GoEugTDklwmXIGILdZsfEmjBg4qOXqC8O99c91OPF7zOktlbgxdBlVwF7IxJFLYXvsV9N/Mx6WSQ3j1588QuvKps7INovIbcbn6U1wXbMSbdm1vD7kgjkO1xBlW+kLUlwn7Wk3PDqtr0sAN4rY1R4+eT9E1Cwc/SG9cC6RshXbL4/BrKMKXeANbtu/G7VH34fErZ2Okj2X7j3eWUARtzer38aQ+Hn8PeQTvXD3SpGAxyA54Qv47rAz1+OCPLzDx0efNcn72d1whote/Bl+UIMP7WwS5WWChpRN+PxiPG9Xr2SSQbMHzrD5Oe4Z52bGtYdWNWlbpXCj+2VPW7z6O9zWvoE5pA/th7WfpteKcA1HoMB5e1cfRcPRHoAtBd+Ohb/CWNBbwu7Xj+7L1QLnEHS76EhQmHsTIIMssKnWFoYcnR/oiCrr7iejMYsxsLfoVar7q1+dyMVQiWnkveLaDFijUKwDcYZn7Gn8lovY6o6SsAW/8LRZsmxrkbJl0GI5D2pINuPrXPDjlKhHWklI3PcQyK26nWoed/Akz+ROYrv4QByM88IGn2GPZrDgO22f/iee2pGNqsc2pXd3/HorCEuMx9gHmPX+Fee+Tl8B2yavAr9fiTunfuBN/Y6diLvYMfRVj/R0wxmcWjGlGcEFzYOsm9Bk10xut1xjw9+yBcdtjkJxYiydk67EvNRm3ffw43rp1PoI6mAFutfFwMm7WrBMzD+Y9y/p+dtVDs33hmPQjwpLzkVby3Vkf/Mezq/C27jrs83PCWjczZRm0snZGsdwfHpoccd/4GUH3O/+kIt/oip3hL+PKS00LtNrDBUyHesojqDv0PVLrFLjnxyhcN9EXE4c4dXpvfV5FPe5VfwcXeS0aFcJER+fTdjvLNmwW23Psx5dhR1wsFkybjK3RWViWvQoKXoslPmooO0gD7CpWXNB2CnA0HmishKGxEmiqBK9tZJXaXVCLaycFIUIZhMoGLYYVHcfNZaeLkandRkJx03qgqwHYuWzcYHX7H1B/OQ8jNVmoPPwIfnJYjZunhXTYuiixsBbHsirZqtfxnCq2B99GU4HWeNHtorard5uTtULKekYX1TSzoH+cf88E3T/sS8Wyk0/Bla9Fg+NQWF/1WZczDjifcVBPfhiqw+/jvobPsHr7HNy3ZPKpn0flCAUQOfgHi9tmuuqg0zJkFZbDX+8EsfeIacrKihHIiUUHVc69mF7eXcLrNPQSyAJnwbj7DRiPfMHqLVSXWWPppzLcMtkfj10U1qmWiZYiFHd89+tv8bruIyikOlw18mIopCZmOaicoJ/6MMvau6rme+yIuxkLR3VvsuTfhCLkbngKz0n/ZF8fSz+OILf2J8EtpbZZC80esU95lU0IHMfd1OH1ZRIeC7yaIck7jOREe4S4m38bZHtp3vLId8X2bg6hUDp3LkPEZsrtwN/HMb1uO9KKaxDiYW/SczOybCvGSNNQai92rOlIpeNIuJTvgDZXqBvR+0F3anEdPv43ASUpkVh2yVLcONWyE7d9Wb8Put944w1s3LgRKSkpsLKywtSpU/HWW28hLEzc7zNQFCfuZz20a6XOsHO24B+snSeqZR5w0ooVTR3GXGa5+xIKjoW4IrOsAS4FO3GrpBwj/TpRsKaLRkSMhJW8GOX1GlyWtQbOvD1m+psnKGmLPHgWtJDBhytHMFeAGaGju5U22pFJoULaXTo7mRP28cglPOoiV7MT/kKHcfAysXJ1Zys56wJmQ5q9B0aVK+aNGoZ5F52x39fVzIF+K4UNuMu/BAJmwrBlJWYiHuF1D+OuT17A/VcvxqLh7Qcuwup/46534czVoUYVAPsJt3XroYTJq/CK7Hs2SfXO31vxxG2nP+CO54grSOP9z+6laS51bhPgkZ8DSf5hodwT+96RjHLsTCllKZWPLwwz69+bcv6zSAm4CUd/SIU+swJVWTHYxFWi2H4khgf6sQB80hAn+Dmp2lx9SYg5hIu5WjRDAdWQ0wGIWSlsUWQTAd/6ONQm/ofSEaNR+ueLWMIXoEHmBIerPoTFhC8RL2e2BdE2s+BbCMQvdvTHxa2ViXMbgSS1+DM7byhmrGSr5mblHATFLb9D++1izMYJbPhnJf6x+wqLWgrvNah1bEuIUIwvOqsM6rwYjDQkYQJ/EkL49a/2USikPCKGhGDXG2Nh7z8KikDTV2i6ItjNhgXdmSU1GOd/uj+vpUSml8HmvycxWpKJZpk9rG9Z2+3XQzX/GdQmbYFLbRr8Dr+A+FEb2LYMYUVdmNAQdPfflux/M1bnZWG5tmup5YWNPF7QPIMIezWeEVK4+zuFLbhFr4MbdR3U/76EFOlDMMY34IdDOdgeX4DnLxuBJSM8LZa91x7hM/nlbzfixfpVrFVhU9BiqCZ17bPHZuYK1B39Gj6aUvy59UPMGf4uC0C7YndKKVLXPYsHJWLALWgqz0Fv+HJvBjY0LYSLbQMuunQ5m9i/kIe03yJYvhd/Cms2c3sm6F67fTfuMP7HJu0dhB7qnfxbshtzBZr+eZJNCK/Z/QdCrr+l0/cZGR2LRXwaDODgNuHCxTUl/hOB8h1wqjqB3pRZVo+PdiRDlfgrnpVugpe8Eut3RsMwec2gXfHu90H33r178cADD2DChAmsn+hzzz2HhQsXIikpCdbWZj6J6UWSPLFfdo3bRNhZ+APDaO8DlItBt2qo+fpXt2WBjw685G+8IPuJfV2tF5KJLXNCLqT3TQ12wd6kfDwt/YX1vTRKhArKZlpdOu8OVSh1Hg/vikOYzZ/AjNCO04K6Q1jhdbFRoK6+DrHZZazK98Lmf8QPhpn3WeZOOU5M66vJB+cUBJh5H/4FjbkRvPc46NbdgoYaHVLrnXDvmmiW7vv4QiGt+/zH89ueo7he/xd7XlTCSr2km2+BrqGoDV4Gh/RNGJvxBTLKLjm12l6VFQsr2GJcgGWCBpvQ6UD+b/Cti2WrlFKeQ8Kmt/CxLA5pEQ91uO+rSyQyjA4Lwsb7nLElrhCj43/BkuYtMDRySIn3w7EToXjHEI4c65EYEhjCgvDJgU7s+RBOcptSd7GbKXIchyEWPMHXBcwCEuJgX3IIX/2yFs8Y/2Svt+Lyj9lKUY8SWkHJ2tiL6jdJvFiazzhIr/0ehl9vwNWSffh0wzN4PuMxxOXXQFl0FFOQwNpCLufTYS1Ro7VylY6XY+Pt4zDcz01Miy77BbDkZO85lmt+xIeKzTiWeC8wUWzRZyn5VY3Y//MbeEqyFwbwUFz34wVbtHWKVAG7676B/qs5WCI5gtd+/gShjz2N0upGrFWvQJrcFyOduled3d1O/H9U3MX2cEX1RhwwjADnYrmMr17hORKKWzdCaEB3cXo5nt8Uj2drX0X+ehfce/Q+PHf5JFb7oKdSalet3Y2Vpc+yVdxG93FQXfdtp4LKNslVkAkZWn8/guvV67Ex8g5cO2NEl4q5xf78HB6VbGRf10scYKOvhrZabHHZk4QWtd/sz4IajpAt+xTSsM6VHeX9pwCVe+FYEYWeepy+Me9CxutR7jkLLoEmbE2Tq1Ax5FL4ZK6F08n10Opv6vRkSXWU+BoV2o6ETyeyoTyGTQeigFBdKsrrmuFiYqHY7sqrbGRtE4Vic8OQiS2K1ad+tki3C8cyijAppJe6JfSyfh90//PP2T38vvvuO7i5uSEqKgozZ5q5Om4vEVbnAupj2PKJtQVTy1s5Tb8D2HwMOpehkFpZdpVhHJ+OaS0Bt8DBnK3C2nCP/F98rXyLjeskjrB1t0C69xnsQmcAhw7hednPgELsmWwJQlDzhdWnGKHdhy2xH6CkvAKTuWrUSZ1hO3Kpxe5XaJMjVJrtNW7hkC7fA5+GCtx8sA7fHMjCV3vTkJObjVU3zmEFrM5M77OOfJsVdit3HAOXYZea5SE4LHoehk/+wDxJDN7f+hceve16lNU2453G/4O9ogHNSiHYNH8bG/fhc4BdwDBkISWvBCXVDVhW9yucJXWo9el8qylTjfJ1YBdYj4AhNhF8dRaGcTkYxufgVuxg+5hzk12x5MQbqIOKFQ+bEOCEm8oi2e9LgszfLeBMHmMvwY64Q9ijDcUdhW9CwhtRG3ol7Ib1Ro3b3seFXQzDkveArY9gPJJx0+FMaCHF17ItWCA5fbKqV9iD95sMzn8qpH5TMNbH9fREWkul6J7iYCWFE1cPaVWaxe/r8Q0nMFVbwc6G9PNfhizIjDVTvEZDM2UlrA79D151J/DxznSMVRZiLl8EL64aSpvufb56qYwI5fKgKK/u0p7ukpZg3cOu71b67q5pwS7452prKL4X/9YX5x3B6x/chqmX3oFrJ55VMcQifjuUimtPPgYfvhyNtgFQ3bJB/NzsBqGrRNW+j+DYkMkytxomfsO2ZXRWZHo57v7xOFZALHKqn/8KfqseiW8OZmOmcgTMX+61Yx/9Ew+1zoAJAY5YMKzzRS49RswGYt5EhC4JxdVN8HCwbPHF3/74Ew/yh9mKs/PS10z+fY/ZdyEuKxr/qSMgSSnFRREXnlyoV+sQXL5T3Oc+8opO3Y+131gckY5HZJM/RmaXYd6InimmVlzTjE93pSL2eCTi9WLavXv4ZFQqr4dTwChU73wPDtpSnNy3HpNCHsFg1O+D7nPV1NSwo5NTD69oWFBJTRPcZE2AHnAcZrkiaq24UdezNC2pj+VbUijDTr+9C6sMvIVP7oLdrAFx+ziqPafD1sKrs7aTboEx+nMYvceDN3f66Dmc7KyhqNOh6eRevFe3FEe5J/DmPD/YSntmT2SvEWb+5So8f4kYEOZtfB5XF+7AKx8+gjtuuVMMEAF8sz8TWq0bGmQqOC57y3yp1y7BqA65Ak5pv2FMxufILr8MuWlxmMnVsr7stt7d27fZHt7RH5USFzjpy5EduxcVSXswn6tDpdIPTsL+MUub/TT42U8DdcVA7mEg9xAMOYfAlcTD3kqK4T6+rJp9RYMGC06+iIl8PDtx8Bxr/mKCZ7IKnIwvPV/FxQUfsZaEDXJX2F3+LgYzyYTboZbbYXtmAK6BnGUhjK+/ESgJBPwmA35TIXENbzNbRa1WY+XKlWz83nvvQaGwfBqy0nMokA04NGRZvArx0axKHDZegyuvvR3ew80/qW017ykcl4Th5f+sIdmbgadcIlnZSGEbRGA3M23C6g7hX8VTiK8U3mNuNPn3lYWHcbUkDhEyYSJsFAYqRcBE4OZN0P75KNxrsvGh5AOs3ZKA6uG/WrRQn7CVQLvvPQzns9Ekc4Tq9k2sHke3SaSwWbIKWH8DrjFsw0974nDvRZ3bKif8vd/5w3EW5MaEr4B25j2QBU6D6nge8o2NyK83oCelFNXgssSHMVdmBc8ZH5iU+q/yGwc15GyCbndiFDymWS7FPK24FuPSP2SLX1VBl8PZw/QFG6nfBGyd+CM27s1EzbG8TgXdB6PjsQAn2dhtYicn02VK/Bb2HjZE5WNFYSPmWXZtCeX1any+Ox35RzfhYW49npcW4Anf73Hb4ukY6ydMLIqxREN+DhwSPodv7h9o1j4IpWzwtTMbUEG38AYnnBxMnz4dw4e33UtWOIEQLq1qa8W2HX1ZgJAm+n8xaK4qhNLBQqnQ5xUlMc8q4AVZna4qqvWZDIWFU+cdR10C7HuBjZ0jeqBYiIMvuEcSwEktv5JgI/TrLvgLYc0noDNeDl3QAnjM6Jk9mH3FpREuaN6fAmV5Ld7XvIovvopH8pIXMC/CG6sPZKFRfxnGXfU4Fvibd3Xe6eLnoE/biNmSE/hk62b4G8UUvQLVUMulUnMcsrwvxZbMfOyOLcRHxs0sqLW66IXup82bwtYDiFjGLixkU9fBvjoXv7pHsL2M8XlVGP7zcsh1ejQq3aDy7Hqf786aFeqKjHwv1jJNeeWnrAL7YKcYdSVeOCuuurPl0jFh29Znn4lV2d9+++0eCbqd/COAQ4CXLt+ivWbTS+thMIJVn/cSAm5LfP5I5Rg//xpcVhaDP08UwrkqlqXx6727l1ousHUVV7Ac9eXs/MfUvcqhxVtxl+xvnKgX3i8WY0ALmgvZiiMw7n8Xxn3v4Dr+P6w/cBjXLLRcRmR0bjVS6q1QIHWB48VvnN+PvBtkQxcjLeROPJQQjNyDpbh6mvqszK62CDVffvruUxi1EZgZ6oPPbhwLWUvg05rtUFLTta0KXbVt449YySdBy8kg8zaxyrxUjiKbYQioj0Vt6gHAgkH3B//E4TKjFXuczpe+3OXbuWa8L77cm4ndqaUs08T9AlkmlVEbwXNGFNiMgLew9bOTxvg5sqA7Jk+sH2EJ1Y0afLU3A6mRf+FBbi1GS8RizzqZDT6aIwNYwH2a54zbgITPMR2x+C8mGYsmWv5coK/p4U2YlrVixQrExcXh119/7bDwmr29/amLr2//6WGndPSyWCGuXnXLn0DgHCiuOKfdjiU4BwEBMwBrN6gsmXZ97sSCsLfTwlyHi5MIo7kMWKGZ9SgddIQe4st3QjP6FvZBdb9kE4Zsux73fPonGjV6jPSxx/zRFtib6hSIqtCr2XB0xmfg8o6wscbLstkihrkv4AXd7ZiqOwZbrgnltuGwGnUlepVQLMw9QhxKJayQnPLWTcDFb4uplT3wHnb3zECMvvxRaFecgCTMsnUpBjqZTIYXX3yRXYRxT3D0E0/GPLlK5BaVWux+snKyEMFlY7i7wuLFtV6+LAJh1o24UrKffe3cxf7cZ3JoafPliirUNolVyE2hUovPrcyx93oz9yiZEtzc51DsMpV9qT/+HZussJRfjuTiJ/1CfBCxAarRZn5f5jgEXf8upF4j0aDRs7aVHTmRV42t376Gj/n/YaP9+/jq+uFnrTT6SGvwuHQdrqv5Gj3lQGoxLikRWzg2jr6LtX8zldZbXFhQlQiVui3jeHYltqbU4D7dShTcdKBLj7OVUONktq8UN/HbsWu/+F7QHqHYZVyJBhkGT/DDLzfpfsb4OcAV1ZDnHYRemFk0o7pmLT747yQeeetTzDp0G1ZLXsNoPgN6iRWM0x6F9NF4IGzReb/Hu4djn/8KXK55BWsTGjAYDZig+8EHH8Sff/6J3bt3w8en/dmgZ555hqWgt17y8oT+lqRXBc4CbtkMOJm/hVCbbt4EPBJvnjSvPoRzDEADb8t6zP6uegNzg3qub2WfIrOCfNnHMFyxGhqJCpP4FGxqvgtX8vvwxEVhFju5drn4OcQoJ+Ed7TUI1yax7zmEWbauxAhve/hJKnGLZAf72u6SV3q+oN2FCI/HdwIwaTnb49oThJNJYUXBzrnz+wNJ2+RyOV566SV2EcY9gVM5oooTV0lKs+Itdj+y1C3YqngWzze8CUtztJZjvd0Hp752Cp3W7dtUOojFiISK2OWlhSb/vr1WbJ2pcu4/iw/m4DjrXnacod6HwxnlFmstJRScFFw3aUjXC6d1QKgA/fTF4Wy840gMciraDmQSCmrw++o38AInBtQho2dCqTx7/7OrlR4rpH/gWuN2NKpNn8DpSoG5qD8+QShfgEaJHewXPt2l23EeKm4JCWmKZ/ufzU2YlHnrH3FPovCZEhAkPt/d8Yp0NV6R/QBZ7A8dTvrsSS3Dr9qZuN36M3gseMik+whVVOGY8n58ideQUWi+v/HcikbM+d8efPtfDD7DG+z8Ss/LYZx0HySPxoFb8FKHBUt9LnkG8cZA7E+vQGldz2ZV9AV97OzMdMIfrLDCLbQN27VrF4YM6ThwE1Lj7OzszrqQQUYi65GV5x4nBJMOYmGYYYY0SAbiv9EE/MirIL//AOodxT3Vryt+wHRvC+4hcvSH/rq1yDW6IZgXT7bcImZaPLi8zkNMZa+2HwZ56EKL3h8hPaXCSnwvaywQJ7AsQVYhnkzrXLp/It0Z9td+Cb3MFs2+M8/aWtVlUjmqOPF2qktMa/Wk0RngYhTbGtq7W76gWF9iNWwx/vB+HIvVb+Dno5ZZeNl+6DjmGA4jwt0KY/3M8Fq3Y1qQM75yWY890oewafNv5/08uagWv37zNl4yfsm+1o5fDtmiVedlHNm0TLwI/adLyyyXXdJqS1QarmsQi+gaZzze5f8PTuEz8Jz8SVyleQkxueZPpd6VkI95+Z/CT1qFR+aHmuU2XaeLNVfmanYjKrOk3ettSxC7CF080hOccN5qAomjH2p4e9alJzdJaCtqHt8cyGRtd+2dXJEffjuM4+6A5OFYcBe/CdhcuGBsoKsNW4UXVt//jDV9orC/6/dBt9AubM2aNfjll19ga2uL4uJidmlqaurth0ZIj7Ne9h5g7wdcu6bvrXj2Bucg2Ny/B1j8Pyhu2wTOwi2jxgc44UavYjYulPlb/P4Et/uVQSqTweGaTwbm9hPS6xPb1dXV7GLJVNxzVbmOxz79CGQ1WC6l3alB3IOo8rFwpaFWHsMheSwJyts2me0ma6VixlZjuWnBY2lVFRy5eja2dxtcQbdQ8yJkycOohTW2JxajrO50nR9zEP6f6I5+iy/kH+BT5eeW3brAcRjva80y3GbmfIT4PKGSvehkSR1++OpdvGL4lG230oy5HbIlbRcR5eQq1EDMjqsuzrZ43/KS7e/BnatGjdIb1tPFzIMuUdqhKWgJymGPY9nmDbqFwDBly4e4V7oFf1i/Dg9b82T6WIUvQI3UhRWAS9q9rt2uRTUp+6CAhvWWNxnHodR+pHhbWeJ2t+4SHtOmmHw2XrVsBEKvfwvcpe8D9qZtT7kzqB5vSb+C7OB7GGz6/Vn5559/ztLEZ8+eDU9Pz1OXdeva/kMmZEATev8K+2l6qhBefyCs+E+8GxB6evaAqxfNxWHreZCG98xeYqvL/gfJU1mA97geuT8yuDQ2NsLR0ZFdhHFPqZz4BG7RPoO/mixTVbumQYNAgxhcuAaZ3m6ry5R2Zi10KBQnFOhM7K9cXSyujDdDDl5luZXYvmqYlx1bcdPqjfj9WKZZbzs6uxTzm/9lY9fJ18HSnBa/ADWnxFg+Hf9tXs2C/oyyenz15UdYZfgIEiHgHnkT5Je+1+HEbLVU7Ndeb+IEjqmSM/NwvVaceLK66CXW0767k92te6/N6c8jKbiueS0bK2avNN9ChkSKxqHXsGFA3sY20+Ij41PwA/cSopX3YYSjvmv303JOYFN+Auaw83gCthgexAvWmzEjsOvvGbNd63CtdA8WNG1FSqHlCr31Rf0+6BbeXNq63Hbbbb390Aghg5B/YDgmL7gabouf7Zk7FE6iBvlWAjLwCAWHBELwYIkV9sysdNhzjdCBh433MPRXmR6L8bb2GiRypnVkqC3NZcdKieugzZB5NLAIf8ifh/PBV9keY3OJ27keblw1aqVOsB55GSzO1gPN48XV4svKvsbPkRm44evDSGmyQxOvgmb4tazOyYWCxtYJHG2VuJppKXlNckxRf4InnD+DfFQn22B1YLKbFg9JNmJJ3nvQ6s3T8kx4z6nd8xGcuTpUW/lDNdG8MYXQs1swDSew+0jMeT8vPbqRTZbUqvzAdbH+kEu4WDciWJNslv3uVYd+gD9fisWqRPDSrmcg2Yy4BA28Dby4SkTv/QuDSb8PugkhpE8RZu1HX09tqsiAoFKpoNFo2EUY9xR/ZxWkPAepphbF1eavdFuZJZ7olsh8ur3S1puqgpbiM/0yxGpNq6iczg3BTZpnsNnjQQxWkwPsMIrPxEW63TiQLE5CmKOAWnDuBjZuHHatWEOmB9jPewwNUgcE8UVI2vYZSmrV0LqNgv7OXZBf8XmnVmk1KrFvtLHGsnttC6ubUAcVtK7DzLJ6HOAgx0rZb7iW24GUHHEfdHcdSSvG4uatbCyf/6zZ23ByzkEotB/LAuu6Iz+e9bNmrR5+xWKmhGFo1ydtHIMnwwAOvlwZkk92XN2+M33Kp9WIz4fVpDu6dVuQKVERsIQN7dJ+N3t19QEfdGu1WlYFPDU1FZWV5k3vIIQQQkjvEPajCq3ChIul22qdScZz2Kt4FHHKu1GQaf5iapqiBHastTVthbivOdVfuda0SsB5TTIcMIxApadY/XkwkofOR6XcG3ZcIzL2iEW9umtH5BFM4+LY2H32cvTotoWZT7Dhy9LvMdRFijV3TYKDT1jnK6fbitXwpQ1iXRJLBt0CL4ezK6h3Fe/oiwqJK6ScAXnx+8xym0m7foIrV8P2Xpu93VsLm8m3QWuUQF1TgvRSsb6C4HBCGiZBfH/y7M72BKUdiuVivYbSlIPdeqyHdv2JQL4YzZwV7Cd0f8uEh9CzG8Ac/SEcTjXPhNeADrrr6+vx5Zdfsr3UQr/rgIAADBs2DK6urvD398fdd9+NY8cs1zePEEIIIQMUx0EvE1PMa3ITzX7zu9QReFN7HWqCl6I/87ThEMblwr061qTfK6oRg3QP+0G8NYXnYRgnnvyPKdmIopqmbqcka459z4qWFTpPBtdTbVBbWE+9B43WvtBLFFhzuStcbU3L4KgadhOmqz/Ah/K7YUlhOb9ilXQ1RhnMN5lW6SzuXzbkHOr2bQl/B6MKxWwFzehbLJatYDf+GjzlvxYv627FhqjT++iLjm5kEwjFViHgXYO7dR+pIXfjEc392Fnn263Cdy4nf2XjiiGXAQrxfbk75AFTUCH3hjWnRtb+wVODq0tB9/vvv8+C7K+//hpz585l7bpiY2PZSvehQ4fw4osvQqfTYcGCBVi0aBHS0tLM/8gJIYQQYlFCWvkTTzzBLsK4J9XZBrGjrvSkWW9XCI7+rXTDF/rLYDt6GfozT10+tiuexlu6N6EzYT/rkNIduFqyB0NkFRjMXKbfAR2kGM1nYNeuHd26rejcKrg0ikXZ7Gf04Cp3K6kcqts2QrnkDTj7Dzf5153dfZFvdENebRcLd3VSaG0kbpLuhB/Mt6IuD5zKji5Vsd2uAbH2cCaiDcGs5ZbrLAu+jjIrXDRJrDD+e1QB248uBLjeRWJquT68+wVx7SbeiM2G6dhXyHX5edkVk4p5RrECuvscMz0fHAd1xNVsOKTgLzRYoMd6X9SlTQqRkZHYvXs3Roxou83GxIkTcccdd+CLL77A6tWrsXfvXoSE9O8ULkIIIWSwEbaP/e9//2Pjl156CXK5edrmdIpLCFCxHcoa807cC/tda5q0kPDcqYJt/ZVDS7svoeBTUXUtPJ07V1X4otrfMFx2EulqoXL7BAxa1i4o9rkIPvlboYr/EbrLLoFU0rUk0J+P5GKj9jE8FNqMlSN6qYOIa6h46QJ3e3FlvKxezQJAWRefhwtx1Im9qW3czJcJ4DliDnAYGG5IRU5ZLQLc7Lt0O0L/+p+PFaFcdxO8rnoTS2zFfe6WMjfcDS42cqgacrE/IQvCUz7FGAdwgOeU7qdxR3jZQSbhWG/t/Kom+DqZXpej7MAPUHBalFqHws1nLMzFc8ZtKIhdi8PaUBTHF+HK8V1fje8vuvQ/asOGDe0G3GdSKBS4//77cdddYpU+QgghhPQfwl7uxx9/nF2EcU9StVQVd2oS21uZS2ZONhbzhzHdsQpKWSf3u/ZRvLUT1BBfl8rizu2NFFa8nPXlbGzrOsh6dLfBfc597LhQvw974jO7XEBta5xYxGv2rLk9VkDNnFyUPJ6SrcP/pJ+jrOp0v29zamjWwsMo/u05epkv6JZ7RqCBs4YN14y0+MNdvp2/E4pQXq+Gm60CC0dYPggUJja+dvwJ+xSPIn//T/grpR6LNG9hi89j4N3Cun37wvvbUpci3CXZitQUcZ+4KbLLG/BrqT/W6udAOuU+s3Y64JyGYOO0v/Cx/gpsjDWt5WF/RdXLCSGEENImYWX7nXfeYZceXeUWFu0CxBRZP0M+apvMl9pef3IfPpN/hFd0H6Df4zhU8WJLobqyzvVXrqxrgivEoMrRg4JuWeB0xLotxaPa+7EmqqxLL8PWIwlQ6GoR7mGLMb79s++50AbqNsk/uFKyv9MTOKYqKS1i+3gFNuac8OElKLYfiXqjEkXZXd+OkrRnPabwibhhoq/FVvrP5RMsppiPKP0L2xOKkWn0gsvcB8x2+/cbfsbzsp/RlPKfyb+79lgeko3++HvIs3Ca3s2q5W1YNtaHHSMzKrpdU6E/6HYN/JUrV7b5faHKqVKpRHBwMJYuXQonJ7F5PSGEEELIhdh4hrGWN0I/7YS8HAwPNc82NWOJWMCpwb77K0l9Qb3cFWguRnNl5/orl5fmw5kzQA8ecnvLps/2CxwHp2u/wI7/7YYxrRK5FY3wc+58Gq6QOcAd/gRHFX8gwf1BcNxM9NsJHIkLrPQFqC8VsktGm/0uKouyECgUbeMc4CgzT/XyVoWz38fCtWnwr7bDLV34/cSCKlxf+TmekZegxs5bKPmGnuA67RboDr2OMXw6PNTZUNgEYkKA+WImrcc4oC4KVqUxpv2e3oDfosT3lOsnWmbV39dJhakBNrDN3YXdB61ww+K5GMi6PY0TExPD9m1/9dVXbO/2nj17WIE14Xs7d+5kQbkQeCclmb/lByGEEEIsRwgohH3dwqW7BYpMJlPikNUsrNHNQ05prdlu1rpGXAnjPYZiIGi2cmNHfSf7K9eWiquYVZyj2fsP91dCkD0zxJWNfzlq2ipvdFYp5jfvgJLTYujQC2+97PMTOMLfVCcncEzVWJrNjtUy8W/WnEaGBkMPCTLLGlBRL66mm+LIjg0I4EvQyFvDfkwPFli0cUOxu9i6b4fiSazwzWb1JszFMUwsMufflMQKtXXW3rh0PNL8GWZa52FeuPlfr1avSb7Bl/IPII/9vuc/Y/pb0C2sYs+fPx+FhYWIiopCdHQ0CgoKWOXy66+/no1nzpyJRx991DyPmBBCCCE9orGxkaWVCxdh3NP+CXsNz+vuREK9tVluT28wwkudxcYOAeZfyesNemtxtZqvE/cUX0hjuZiGXisTAywiun2UCg9Lfofn0ddNCk7idq1jPZ3rpE6w7q0CambSbOVh0gSOqTRVYjDfaOVp9tu2V8kQ6i4WRjyeXWnynvzArF/YuDbsWkBunvebzjozdXu+yryFI13Dp7FjEAqQkt35yZSCfT+yKvPvyb+waKq9++Rr2HGWejcS8kx73fqbbj+Lwj6vV199FXZ2dqe+J4yFKqdvv/02VCoVXnjhBRaQE0IIIYR0VpCrePKbUVpvlictr7QS/hCDU9cgoXJ3/1frNxdva6/Ffr5zVch1VWLRoqaWFXIimu7aiEdlv+M6wzbWJqmzwVpwrtjTuWHYdf2ygNqZDDZi0C3p5ASOqbYpl2BE8zc4OuxZi9z+Y1ZbsUu+EupoMYDurH8OHMJMiL3u3eeZbz91Z6mGXYxmlRcMnATeM8Xe8ebC2bihTOrB+scXJUZ26nfyKhowvuJPNubH327WAmrnUg1bhDqJPVy5WsTt24iBrNtBd01NDUpLS8/7fllZGWprxXQwBweHHu/vSQghhJDuESbOq6qq2EUY97QgNxuo0IymEvOs/hSkn4CEM6KWs4XEzvyrbb1BEjQbn+mXYo+6c3veDyqm4UbNM0gMMH9hpP5M6juBtUVi7ZH2fdep3/k38ghm8HFs7D77HvR3EgdhLzOgbBLbeplbYXUT6qCCk7tl9ggH2mgQyBdDWXi0079jMBhhOLaaBaWFLtPAuQSjx0mkUN6zHfxd/4FzF7s2mFOl4yh21OV17nnZt/dfRPA50EAGpyk3w6IkMlQHLWVD54xNbC/5QGWW9HKhJ/emTZuQn5/P0smF8Z133olly8Q9EUePHkVoaNf6BhJCCCGkdwhFUYWJc+EijHvaUMNJJCnvwJv1z5vlZKw+VwyQyqwCLbp605M87JTsWFrbuX2saQ0qHDSMAHzHW/iR9TMcB8Xku9lwes1fSC/puI6AsP9Ud1QMzgudp7AWSP2d0lkMhm215y+mmUNhdTM7ejmYt4haK4cwsYhdYFM8mjSd2yJwIDkXF2t2sLHznPvRaxz8AG/z9cE+k9RvIjs6Vorvfx3R6Q2wTviZjUt9LgJUli+E7TlDXN2fbTiKgwlda9s3KILuL7/8EvPmzcN1110Hf39/+Pn5sbHwvS+++IJdJzw8HN988405Hi8hhBBCBglnn3B29ObKkVvctXZOZ9qtjcC9mkeQFnwnBgp3GxnCuVyM00ahvll7weuX1IqBj6e9GKyT0+wnXo9mzgpBfBEO7tzc4VMTlV2BmerdbOwwo/+vcguswuZhuvpDXKP5P7MXtRJWlB+tfxerpKvhI6uDJbgMncGOwVwBEtPF2g0X8u/BY6gw2qFa7gHF0IsxELlNvgZXal7CHY0rUFbX8eTc/oRszNfvF39vzvIeeXxSn7EoUwawYoT5kb9ioOp20G1jY8OqlVdUVLBK5kIhNWEsVDO3thb3Yo0ePZpdCCGEENJ/CFvDhBotwqU3tolx1s6o5uzZuCQrodu3d6xchn8ME2E1fDEGCmupEf8onsYP8rdQWlp8wevPrtmMayS74SUf+H1xTaawRWXQ5WzofvKXDldLfzmWj2XqV/GX+/1Q9fMCaq3cXFyQb3RFg06CqsYLT+CYorymHku5A6w4l6uNHJbA2biiWO7HxsWJey94/bzKRvycZYX5mndQc92frN/3QGTr6odal7FQQ47YvOoOr5u7/yfYcM2oUPhBHihOYlgcx0E/4lo25ItiUdNk3r+9vsJs5eiE4HvkyJEYNWoUGxNCCCGkfxNahb388svsIox7Q4XSnx0bCrrXerRZq0d2hViBPczdFgOGTMn2qAtqSjpud9Wo1uJh4894W/Y13GUNPfQA+xePufex4zzjUew4FtduAbWtcUUogwN8ljzZ7wuotZJLeThbiwFxUY15J2XKCrPYvmkNpJDausNSal3FbRNc7uELXnfN4RwIC/rTQ9zgH9gzfbl7yxg/B3aMzatq9zrFNc1ILKpHodEJxrE39+gWHPdZd+Mum8/wrOYObIu3TCG/ARF079+/HzfddBOmTJnC9nQLfvrpJxw4cMAcN08IIYSQXiCVSnH//fezizDuDc32QeKgTOyv3VVZBUVYzm3GJco4uNtaZqWtt1RLXdixobzjoLukrAzWnJheat2yf5ecjfcaiXyHifhNPxN/RuW0+fRsjM6FWmdAuIctRvuKwcxAcb98K96VfYa6/ESz3m5tidiju0LiCvCWa0GlChFbZHnVnmAtAjuahEs/9g8U0OCWKQEY6ObZFeAV6XfwTGx/u++G43lYr5+NRz1+hMvch3r08XE2rpgwYTIbb4oWY8mBptt/9b///jsuuugiWFlZsfRytVp8M6+rq8Prr79ujsdICCGEkF6gUCjw6aefsosw7g28m7gCpartXoGd0vRoPClbh5f41eAseNLfGxrkYvsvTXXH/ZWrS8Qgsg7W4BSUldge5Z1/4QXjPfivUIaEgpqzfibsdVbsewO/yFbh0ZDSXikwaEmz9YdwpeQA1EUpZr3d5vKWvz2F2JbMUjyHz0W60Qcn9P5ILW5/7/j2o/H4zLAKR5UrMNd74FbMbjXcqgK3SHdgVM2uNicjhD33a4/lsfG1k4awDJqetnS0N1tcT87OR275wMvE6fanzqpVq1jBNGFft0x2Or1m6tSpbH83IYQQQkhX2fqILXTc1DndKu7UmC/uCa+0blk5H0C01i3purUdB92NLSvhrSvjpG0utkosGi62lPvl6NnZA9FZpVig/hdTJUmY4T2wJm8ETVZiUKyvNu9qo746nx3VKi9YksQlEC/7fYuXdLchKqeyzesI7yPVB1ZDwenQbBsAif3AaB/YEY8IcX92OLKRUXh+UcqDKXmIqN0HJyWweETvPB8e9kp87/QDjivuQ+T+fzHQdPvdIjU1FTNniiX6z2RnZ4fq6o436xNCCCGEdMQ1eCzW6WdjjW7uBSvvdkRekcyOWhexIvpAYrQVT5IlDR0XUlNXioFUg8Jye2oHihsn+WEElwnrmG9Qr9ad+n78zrVw5WpQJ3UaMAXUzqSzFoNurq7jCRxTSevEvz2jndgL3JImBIhtro5lt71/OSanHAsat7Cx9fR7MRhIHP1RzTtCxumRk3j+fvfMPWvwlfx9bLZ+A0pZ7xWUG+Ioh4LTQpG43uwV9Pt90O3p6Yn09PTzvi/s5w4MDOzuzRNCCCGklzQ0NLAsNuEijHuDwskXX9g/ih/0FyG9rL7Lt+NYn8GOSu8RGGikDmIgY9XccX9lY8tKuEZFQfeFTHKoxV+K5/E09wP+jYxi36tu1CA4bwMbNwy7bsAUUDsTZy+uRMsaS8x6uzJ1hXh0EquLW9L4AEfIoENpZnybP4/d8Su8uErUS+xhM/ZqDAochzL74WzYnHXkrB8Jk5kRxWKLPOWw3m2b5jb9Vnacrd2HmCzL9Ivvt0H38uXL8fDDD+PIkSNsX0thYSF+/vlnPP7446zwCiGEEEL6L51Oxy69KchVbEGaUdq1oLu2SYMhBnFPqVvQGAw0Ur/JeFt7LdYZ5nd8vZaVcKOdZVN8BwLOaQiKHMdDwhnRdOQ7tuq248ARTOfjYQAH99kDozf3uRSOPuxoozZvwPOgfiVGNH8DbuRVsLQxqjLEK+7EV5qnUFB19mRheb0a4Xnr2Lgh4sZe2bvca7wnsINdRexZ3965bx/G86nQg4fbzDvRm5Shc1EjdYYjV4+kfb9hIOl20P3kk09i2bJlmDNnDurr61mq+V133cWC8RUrVpjnURJCCCGkxwlFUvPz89lFGPeWUGcZwrhcVOeJKeKmysrOZCdxwkll6x7xgcRhyCh8pl+KzY0jOqzY/KPkCtyoeQa1IWIvatIx++nL2XF+09+Izi6D7vh37Osi5yksKB+IbNzElWhH/fn7frtK6Hde2aBBHVTwdLV8PQErtxAYOQnsuEakxh0962f/7tmHqXwCey9wb2kPN1i4DBUruwdrUlDXLLaAFCaTJDE/sHGR+yzA1rKF7i6Il6Au9Ao29MzeDLVOj4HCLBUgXnvtNZSXl+Po0aM4fPgwysrK8Oqrr5rjpgkhhBDSS3ieh7e3N7sI496ypGYttiuexoic77v0++UZMexYIvUGZL03eWApLjYK8BxYwF1R3/6+94QGOxw0jIC9z9AefXz9lWrUMtRLHODOVWP7hq8xX72Dfd9x5sBc5RY4uPuzo6uxCg0tgVl3Fbb0/LaWS2Cn7IHWgxIpim3FVOr6tP2nvq3TG1AU+w8bl7jPBhwsn+relzgGT2KTDcK0XGKmWNjucFoh5mt3s7HLTHGSqbd5zriNHWcYo3AgrnutIvsSs32CqlQqjB8/HhMnToSNDbWhIIQQQoh5WHmJQaJjo9jr11QHtWG4WP0GdgY/OyBfEgnPYZJ1CWbzsSgtb3uFUgg4WgvRedgNopTa7pDKUR9xPRvOrtuC17U3ItF2GlTDL8FAZeMWiAXGTzFK/TWKu1G48ExVuUn4VvY2XlCu67EWa3ofseezTYm4H1+wM6UUH9fPxeX8h3BeugqDjsIWzwZtxHT1R4gqEVeQU3f/yrKAqmVuUA5diL5A4jkcJapQyDk9iiJ/xUDRpemmlStXdvq67733XlfughBCCCG9TKPR4MMPP2RjoX6LXC7vlcfhGjAc2Av4GfLZ6pu10rQCVomlaiQb/aEKGYWB6kPD63CTl+FI/lgg0Pe8n5fV1GEFvxGlnBOcVX3j5Lo/cJ+9HIa4L1iLsKd1d+OWq58akAXUTpFIYbDzgbasASU1zQhy7f5CWmPRScyVxCLb2HPFGF2HzwKSP0GoJgE1TVrYW8nw4yFx0m7yxMlQeA28LgadETokAEhMQkxuFaoaNJDlHwYkgHr4DSy1u68wTH0Ir/0dia1FYVjcoIGTde989vR60B0TI6ZptYqKioJer0dYWBj7+uTJk5BIJBg3bpx5HiUhhBBCepxWq2W1WwRCcdTeCrptvYey4lWsuE5eHoaFdL47irBn8WRJHRuHedhioKqTucJNXYbmlrZg56osysFK2W/QQAqJ5O0ef3z9uqCay1SgLBnTnRsw2tcBA52nvRUyyhpQVNNsltvTVIq9zhtaeoD3BPvgKSyV2ocrR2RyEty8h+BkegZ4zoG1gxusWv9+Y3Kq8Ht0PlZpb8dhx0vw8dzerVp+Ls/pN+NwzBAUFtRgS1whbpkSgEEZdO/eLeb+t65k29ra4ocffoCjoyP7XlVVFW6//XbMmCE2YieEEEJI/yOVSnHrrbeeGvcauQrlEje46UtQkRMPmBB0l9U24gnN58iQeiPYaTYGqiYrd0CdBF112/2V68rEwKeSd4FHD6X4DhQet3yHjSmNWB7k1mPp0b1psWEPLpftgzzrGmCc+P+/O7hacf+wzqYHq+YrbFGoDIFvcyoqkvciNekEIhWP4IjtAvg4LsFgFeGgw4/yNxGsz8fle75g35s4dQ5g2/faCF4+xpttieEHyP+5bn+Cvvvuu/j3339PBdwCYbxq1SosXLgQjz32WHfvghBCCCG9QKFQ4Pvvu1a8zNyqVAFwqytBU6FQwXxpp38vJyMJN0h3QQMZ5AoxVX4g0lt7ANUAX9d20N1cIQY+9XLXHn5k/R9v546rJmLQiNAlY5TkAHaVixms3aVsEP8meYfztz1YUnHI9fglOgUZZW64qupbyDg9gjydMJgpbZ0xTpIOa2MjAhrjUSsbjqWj+2YLwRsn++HWqQGsZsVA0O1CarW1tSgpKTnv+6WlpairE9O5CCGEEEK6Q+sYwo58RZpJv1eddYIdi+X+fWrPorlxLb235U3nn5MJdDVi2nmzlVuPPi7S/xjtPNlR2lBkltuzVYv94RUuYmX0nuI88258rr8MccUazMUx9j33eYO8nTHPo8RGbJu4TvEqPnfbDDsTa2T0FIVUMmACbrME3ZdffjlLJf/tt99O9fIUxnfeeSeuuELss0YIIYQQ0h264EV4S3sdtugmmPR7huIkdqy3N8+qXV+lcPRmR5W67erlkjox8NH3ZIov6ZfkDi1/S82l3b4toaaCc0vPb3v3nu1tPsTFGs7Wclwv3QUpZ0CRwzjwHhEY7LSep2tuhXkP7pX/fhV0f/HFF1iyZAluuukm+Pv7s8uNN96Iiy++GJ999pl5HiUhhBBCelxDQwMcHBzYRRj3Jufh89iq1bZqf9b+qrOsa8Q+r5y7uLozUNm4+rCjo768zZ8rm8Sgm7enoJt0TOUiFhqz13Y/6K6ob4YVxIJsjl6dr8VgDsL++4u8m/GwdBP72m7W/T16/32VR/jk0+PZd/fqYxlMeHP05xaC64qKClbVPDo6GpWVlex71tbWsLR9+/bh0ksvhZeXF/vPtXnzZovfJyGEEDJY1NTUsEtv83awglLGQ6M3IL+qqVO/YzAY4aHOZGP7gIHbLkxg7zecZQK8o7kaTRqxB++ZbDTiaqPCSQzOCWmPnbsYdLsYK6E1YYKrLYU1aoxVf4W5sh8htxfT1nvS49Wvnxpbj+x8LYiBzH74IuiHzIZuykOsOj/pw0F3bq5YAfNMQoA9cuRIjBo16rxgu6Cg7fYV5iDMvAv3+cknn1jsPgghhJDByMrKirUBFS7CuDfxPIfpjjVYyB9Dbo4YSF9IXnkVAiDuS3ULGo2BzMbZGz9KLsdWw2QU1zafl+K7UrscN2iehVXIzF57jKR/cHAX914LLfpKq6q7dVuF1eIEmb2jC9tP3NMcl70Jg0QJ/SUfDuz+6qaQqyC59Q9IL3q1tx/JoNKlv/4JEybg7rvvxtGjR9u9jjAr/vXXX2P48OHYuHEjLEVIYxcqpdP+cUIIIcS8eJ5HSEgIuwjj3vas5mN8JX8fmoz9nbp+fkYS28tZx1lD6jDwV3jd7ZTsWHxOf+XaJh3StG6INAyHq0fPVpAm/Q9v5YAmKNi4svj8hTZTFFSLf4teDr0zaccFzgL/fDEk42/rlfsnpFstw5KTk/H6669j0aJFkMlkGD9+PEvvViqVrEd3UlISEhMT2fffeecdFhgTQgghhHRHo30Q0JwAY1lqp64f3eiOe5pX45ZhEjw1QHq9dmS0qgx+fCpqSjyAIOdT3y+qFVcbHVQyKGUDt4I7MROOw8Mu32B3vhEfGNwxohs35Zq+Ad/KtqJBewmAsb3zEg2C//uk7+vStLWTkxP+97//obCwEJ9//jlCQ0NRXl6OtDSxjYdQSC0qKgoHDx7scwG3Wq1mbc7OvBBCCCHkfFqtFp9++im7COPexruGsqNVbefSy1NL6tAAK9j7j8RgsLzhC3wvfweK3LMzAaoKM/Cw5Hdcq2w/Q5GQM8mcfKCF9LytCqayr0rAXEks/Fq2eRAyWHVppbuVsLItpHX3p9TuN954Ay+//HJvPwxCCCGkz9NoNFixQuxre9ttt7Hstt5k6zMMSABc1Dlsn7JQQLUjqcV17BjmYYvBQG3lDjQAhtrCs76vLUzAo7Lfka0Tep0/32uPj/Qfnqe2KnSuaGF7rBrFYFvmKBZnI2Sw6lbQ3R8988wzWLly5amvhZVuX1/a30QIIYScSyKR4Kqrrjo17m1uQ8RE1wBjIWtF5GLb/j5RtU6PR6peR7nUFkNthmMwMNp6AuWAtEFsD9ZKWyUWtG1UuPXSIyP9zThdNIbJfoU+R0gJ73rBLQdtCTuq3ALM+OgI6X8GXdCtUCjYhRBCCCEXzmjbsGFDn3maFC5DoIEUSk6L5KyTcBnZfhuwnMJiLJEcZmOjox0GA6m9Nzsqm87ur8zViSvfWmuPXnlcpP/xNRZhuOQADtcYu3wbzVo93I1lAAc4evZsj25C+preL0XaTfX19YiNjWUXQVZWFhu31daMEEIIIf2YRIpSmViFvDo3ocOrFqeL5wUVvDM4lSMGA6WzGHTbasWe3K1kLSvfnJ1Xrzwu0v8oncQsUDvt2RM4pigpK4c91yjeTksbMkIGq34fdB8/fhxjxoxhF4GQOi6MX3jhhd5+aIQQQggxsyO+d+F+zUOI0nR8Et+UF8eOFdZBg+Y1sHMT9806GSpgMJxeobRWi4GTzFEMygm5EFv3lr8lfQWrn9AVlYViwcM6WINT2tOTTgY1s6SXR0dHY//+/ZDL5Zg2bRpGjuy5KqGzZ8/u8psBIYQQQtrX2NjIenQLhA4lKpWq158uTfhSbEuKx6xqeYfXk5SnsKPWORyDhUPLaqIrqlFZ3wQXO/H1steJK9/WLlTDhnSOo7u4B9sVVaisa4SznbXJT111RQlqjSpUy90xOEoZEmLBoPuDDz5gq8sODg6QSqWsdVhERAS+//57jBs3rrs3TwghhJBeIkxqC+1BW8d9QZCrDTtmlNV3eD2nhnR2VHh3p8tw/yKzc8fH/E3IaLbD3dUNLOgW9tW6GivZvloHDypmRTpHbu8OHSSQcnqUFefD2S7M5KcuThKB29Xf4KbhblhFTzwZ5LqUXv7tt9+y1W2h5/Xrr7+ON998ExUVFSgtLUVOTg6WLl3KVqAPHDhg/kdMCCGEkB4rpBYTE8MuwrgvCHaSYQ4fg/m1m9Gk0bd5nfpmLQL02WzsFihuPxsUeAm2O16HzYbpKG4wsG+V1qqxTPMKbtU/D1uPwZNqT7qJl6CSd2LDutKcLt1EYbXYbszNyYFeDjLodWml+5133kF6ujiDbDAYcOzYMbz//vsYO3YsRo8ejVWrVsHb2xuPP/44Dh8WK4cSQgghpH8R2oQJn+t9iZMVj+/k77BxSv5KhAeev3qbkVcAT0ihBw87v8HRLqyVh50SCQW1KKlVs6+LapqQafSC3i4YnKz9FmuEnKtW5gqX5nLUV4q9tk1V2NLj28uB/u4I6dJKd3JyMurq6hAZGQmZTAae57F+/XosWbIEzs7O8Pf3Zy1GhJnxv/76i1UUJ4QQQgjpNrk1ynix33R5dtsVzJOreExUf4b7vTcAgyzQDFdUskwAbXEi+7q4tvlUME6IKdaFvINQ9Q+IVk7u0hN3Q9Fb+Fb2NkL0J+mJJ4Nel6uXC2lmEyZMYIXTRo0axVa0hUA8Li4Ob7zxBkJDQ6HVanHbbbchKCgIdnaDo0cmIYQQMlAIn+NCjRbhIoz7iiqVWDCssTC5zZ+nFNexo6/n4GuRtaDmN5YJ4Ju3hX1tzDuKhyW/Y47kRG8/NNLP2DsJ+7qlKKoRJ25MIdSAGK6Nx1xJLNxV/b5ZEiG9X0jt3XffZfu3MzMzce+997IA3M/Pj+359vLyQn5+PrskJHTcT5MQQgghfYtGo8Htt9/OxldffTXLbusLNA7BQP0x8BVpbf78ZIkYdId6DL6ayawXdxEgbyphX9sUH8ajst8R1yyk+t7b2w+P9CMe9mKWSElLtoQpquqb4Y4KNnb0HGL2x0bIoAu6hb1eUVFRLOCePHnyqeqmQiVzoeCawMfHh10IIYQQ0r/2dC9evPjUuK+QuYcB+YBtXUabP19e+ByWyzTwlL0trHdjMJG39OJWqcU2YdJ6cT+u0cazVx8X6X+C9Fl4T/YZjCVCQbVJJv1uaVEunDg9dOChcKD+8ISYpU+3kD6+Y8cOlJSUsDRzYWZcCMB9fQfXBx0hhBAykAhbybZu3Yq+xl4ojhYFeGjzoDcYIeG5Uz8rr2vCBEM8VBI1mlztMdi09uJ2aOnNbdVUyo5SCnyIiVzlGoyRHECO2sPk5666WKznVMk7w01ilnCDkH7NrP8L3N3dWbswQgghhBBLcR0i9t72QSkKy6vg6ya2NhLkpCdjHKeGGjJYuYcOuhfBwV3c7+5irGQ9um21YvCtdKaMQ2IaRw/xb0lIExfa8NkoO7+9pKlMbNlXK/eAWPaQkMGNKhsQQgghpF+R2LrjTdXjuEyzCunlYmusVlVZsexYIvcHBuEKm42rGFzbcU0o+f/27gM8imqLA/jZ9N47CaGF3hQEARXxUR6CAipNRKmKIoooKqKC4BMEC6KCIh3lgcgDUREQBJ6AgCAgHYGEEghpJCGkJ/O+c5bdl012U0g2uzv7/33fMLMzs7OzczMkZ+659yalUGBRsvZ1iDaAAqgoz1sPatw0+ZSYmFCpC1d4/ZLMczzQrAGAIegGAAAAo7KysigmJkYmXrYaGg1dqtWLjit16VyKdixgncJrJ2Se6RtD9kjj5kNZpB0e7ELsKQqidFn2u1VrCVBhzm6UptGOPpSWcKFSFy4rO5syFA8q9EGGBQCzv0fAAAAAUCHcOerZs2f1y9akfrCnzM8lZRqsd0/TjgmsCW1K9mqF79N0MqmAml3NoPs0ChWQIzl7h1r6tMAGpTsFkV9+BmUla2uuK2qxw6P0Qu4/6Is2ramV2c4OwHYg6AYAAACTHant2rVLv2xNWnhep2GOmygkLoiIWsq6oiKFwnPOEWmIfGpr19mj42GP0IZrVygh2ZdW5n5I7UIK6X0HJDdC5d10DSXKP095aZcr9b4radoMlFr+XrjsAAi6AQAAwBQeJqxTp05WeYEa0iXq5rycTmbUI6Ipsi7+ehYlFflQqIMHhTS4k+xVmK/2AclfVzIpSwmnmEDUcsPtyfcMo6IbGsq7oR1zuyJyCwop8Ya2r4UIP+t6WAdgKajpBgAAAJsTUq+5zKOVeErNzKEALzc6fS2TRuW/SY1DvWiTv/0OW1rXJZ26OByi9HxP+pMa6oNwgMo62eJVevRCP7rfrRb9s4LvSUy+TptcXqMECqIA13/gogMg6AYAAABTCgoKaN26dbLcr18/cnKynmf17iENpK2yhyaXzsb9TQHNW9DpazdkW6NwH+lszV61uPEbDXaZLctzCh6hSOUhItI+pACojODAQCqgWErIMOywsCzJV87THQ6XKIqSSeOMBz4ADA18AAAAwKjc3FwaMGCATLxsVRyd6ZpTLVlMvXhc5meuanvqbhTmTfbMLUB7Xdh4p/9Qo9xjFj0fsF2hPtqgOSG94vd/5rVYmac6YYRuAB3reWQNAAAAVsXBwYE6d+6sX7Y2GV51qVbaRcq7elJeDzw/iV5yiaO0wulE1IDslXdwbYPXrgEYtgluT4TTDfrY+XPyzs2ivIIHyMWp/P8H8lIvyvymWxguO8AtCLoBAADAKHd3d9qxY4fVXp3CgAZEaTvJOe0s5RcWUVT+eYpySKLEkECyZ/4lxuT2DDEMwgEq/LPk40n9HHfLcnxqKtUK4dECypGuHV4sz+v/GRcA9s76HlsDAAAAVIBruHYsbr+bcRR35RpFaZLkdXC9O+z6+rn4hlERj5t2i39oHYueD9gujZsfZZE2xTw14UKF3uN886r2vb7IsADQQdANAAAANsm/ZU/qmzuNhmW/SJdO/ynrUh0CSONp3zXd3N69oFgyo0cggh+4TRoNpTlq76fMJG0Ndnm8chJk7hpomHEBYM8QdAMAAIBR2dnZ1Lp1a5l42doEhkTQedfGlK540qVTB2Rdikd9S5+WVTDoux09SEMV3HDRdoiWm1J+0K0oCmUUOFGG4kHeoXVx3QFuQZtuAAAAMKqoqIiOHDmiX7Y2Go2G6od40aGLaUSJJ6QqITegsaVPyyocCuhB7VJ/pAwHX/Kx9MmATcv1CCXKJipMv1LuvhnZBTQs9xVZPtVE2wkjACDoBgAAABPc3Nxoy5Yt+mVr1NvtL3rYaTs95bBZXrvVwnjU7GCzyfTa1i7Ut3kAvWjhMgLbVuQVTpRC5HirrXZZ4tO0GTGBni7k5oK6PQAd3A0AAABglKOjI3Xr1s2qr067wkPUwkkbcB8pqkfRDdpY+pSswmPt6lNaroYeboeey6FqnPwiqShOQ0U5meXue+VW0B3h547LDlAMgm4AAACwWU4hjYjiiX4pbEOTXCfRgfp3WfqUrEKwtytNerCJpU8DVCCv5RBquC+GQt296YFy9tX8vYk2ucymiwUdiOieGjpDAOuHjtQAAADAqIKCAvrpp59k4mVr5BulHTasviaeGoV5W/p0AFQnNNBPesNPvJFDRUVKmfsqKeeoscMlCndIrbHzA7AFqOkGAAAAo3Jzc6l3796ynJmZSU5O1vdnQ0i9ljKv55BATYJdLX06AKoT4u3KI4dRfqFCKTfzJIvCFMcb8TJXvGvV4BkCWD/r++0JAAAAVsHBwYHatm2rX7ZGTr4R+uXBKZ8R0SKLng+A2jg7OtBct68ouDCBUhJiKNi7ocl93bO0na05+kfV4BkCWD8E3QAAAGCUu7s7/fHHH9Z9dbgK7pawBndY9FQA1OpuzTEKdkii/QmxRDGmg26fvASZuwfXqcGzA7B+CLorQFEUactWWFho/hIBALP0wMxpsTymLwCo0NM7iM5uI89Oz1j6TABUKd05mIJzkyg75ZLJffILiyikKIlIQ+QXXrdGzw/A2iHoLkdeXh5dvXqVsrKyaqZEAMAsPDw8KDw8nFxcXHCFAdQm4g7tBABmkeMWSpR7ggrSrpjc51rqdYrUZMiyX1g9lASAGoPuefPm0ezZsyVAbtasGc2ZM4fuvffeKh2zqKiIYmNjpZYsIiJC/lhHTRmA7WWq8MOzpKQkuZ9jYmKstm0qgLXJzs6mrl27yvLWrVsl3RwA7E+BVzhROpHDDdNBd1JiEt0oiqIgx5sU7OFfo+cHYO1UEXSvXr2axo8fL4F3p06d6Msvv6SePXvSiRMnqHbt2rd9XP5DnQPvqKgoqSUDANvEgYKzszNduHBB7ms3NzdLnxKATeDfgXv27NEvA4B9cuAOC+OJXLK0bbaNuZDnTePz3qcO9QLp32jOBWBAFdU9H330EY0cOZJGjRpFTZo0kVpuDpTnz59fLcdHrRiA7cN9DFB5rq6utG7dOpl4GQDsk2tApMy98hJN7hOfli3zCD9kxACorqaba60OHjxIr7/+usH67t2765/OAwAAQOVxB4R9+/bFpQOwc17BtalI0ZBSkG9ynyu3gu5afsgmA1Bd0J2cnCy9ioeGhhqs59cJCaVTYHJzc2XSycjQdvgAAAAAAACl+TXsRA1zl1EBOdHRnHzydnMutc/95z+goS4HKTXreSJqhMsIoLb0claygzPuPMlYp2czZswgX19f/cRp6GrGDx7GjRtH9erVk9RA/r4PPfQQbdu2TbbXqVNHrhNP3O61cePG0iEdXz+duLg42X748GGD11wDEh8fb/B53JGdbmgm3q8kzkDgjun27t1r9HwPHTpE/fv3l4cm3O62YcOGNHr0aDpz5kw1XxkAACgPP9TesWOHTBg2E8B+ebq7kfut/lCuZeQY3ScwO44aO1yiADfVhBcA1cbm74qgoCAJ4krWaicmJpaq/WaTJk2i9PR0/XTpkunxBm0dB71t2rShX3/9lWbNmkVHjx6lTZs2UZcuXWjs2LH6/aZNmybB8smTJ+mVV16hN954gxYsWFDu8blH9+XLlxusW7ZsGdWqVcvo/hcvXqTff/+dnn/+eVq0aFGp7T/++CPdfffdkonwzTffyPmsWLFCHo689dZbt3UNAADg9uXk5MjvDJ54GQDsV5iPNui+mm78/wL//Gsy9w6tU6PnBWALbD7o5mG8OLD85ZdfDNbz644dO5ban2t7fXx8DCa1eu6556TGef/+/fTYY49JrTEPpzZhwgSDmmZvb28KCwuTWm/ujK5ly5a0ZcuWco//1FNP0ZIlSwzWLV26VNYbw/v27t2bnn32Welx/ubNm/ptPA768OHD6cEHH6QNGzbIEDV169al9u3b0wcffCA90gMAQM3i3yFNmzaVCUNmAti35+nftNplGhWc/63UtozsPAqnZFkOiMAY3QCqC7oZB5ELFy6kxYsXS+3oSy+9JLWqY8aMqfbP4rTrrLwCi0zFU77Lk5qaKrXaXKPt6elZarufn5/R78YphHwNeXil8jz88MN0/fp12rVrl7zmOX8up68bOzYH3U888YSksPMDgG+//Va/ffPmzdI+/9VXXzX6WcbOFwAAzIuHyzx+/LhMGDoTwL7FFF2g9g6nSEk6W2rbtYR4ctPkUxFpyD1Q3U03AeyyIzU2cOBASklJ0adJN2/enDZu3EjR0dHV/lnZ+YXU9O3NZAknpvUgD5eKFdnZs2cl0OUAtzyvvfYavfnmm9ITfH5+vrSlfuGFF8p9HwfmHETzw4577rlH5vzaWMC+detWqc3u0aOHvOb9OMWca7fZ33//LfOKnC8AAAAA1Kx8z1CiTCK6caXUtutXY7VzjT8FOmF4QQBV1nTrUqm5DTO3B+YhxO677z6yZ7pa8YqkA06cOFE6Sdu5c6e025s8ebLR1HxjeHz0NWvWSJt6no8YMcLofhxg88MR7mSNDR48mPbt20enT582OF8AAAAAsEI+ETJzull6dKCspAsyT3cp3Z8SAKikprsmuTs7So2zpT67omJiYiTg5lTx8sZY5c7oGjRoINPatWtlzh2acbvq8nBWAddOcxDdpEkTea3r5VyHU87Xr18vtejz58/Xr+eecLl2/P3335d0c3bq1Cnq0KFDhb8nAACYT3Z2tjQlYtzfBo9yAQD2ycU/UuaeudoO04pLuZlPJ4uiKMcL7bkBVF3TXVM4kOUUb0tMlenEJiAgQFK5P//8c4MOy3TS0tKMvs/f31+GGONezCta+8y129wW3FQtN/dEHhkZSUeOHJGAXDfNmTNHejsvKCiQocQ4+Ode1o0xdb4AAGA+RUVF0jyIJ14GAPvlHqRtq+2bn1Rq238d7qKeee/TH62mW+DMAKwfgm4VmzdvntQmt2vXTmqwud0013zPnTu3zNpk7nyN0775PRXB42gnJSVJz+emUsu593SuBS8+cZDOwfRPP/0knb1xZ3i8zLUq/AceNxc4cOCAdK5mjk7xAACgbDzix9dffy0TLwOA/fK7NRRYsJJCuQWFBtuupGXLPMIP2TAAxiDoVjEecuvPP/+Udtovv/yyBLrdunWjbdu2GaR5lxQcHExDhw6lqVOnVqhmg9tpcy21rr12cdy+nmu4H3300VLbeKgyruHWjdndp08f2rNnj3TE9vjjj+vT1nk89XfffbfS3x8AAKqG/18fMmSITMb+jwcA++EbEkWFioayyZUSU9MNtl1J047djaAbwDiNYuc9WGVkZJCvr68EdiXH7M7JyaHY2FgJXrlHbwCwXbifAQAAqkBRqMusbRR7PZfWjOlAd9UJkNUFhUV0YVozylccKWjkGgqKboLLDHYjo4xYsjg8tgYAAACjuIkSZ0yxO++8kxwdK96hJwCojEZDwb6eEnQnpGtrtlni9Qyqr7lCpCEqCgiy6CkCWCsE3QAAAGAyQ4T7BWGZmZnS/wYA2K8wX23mZ/GgO/lqHPFgYrnkQq5eCLoBjEGbbgAAADCKR82Ijo6WqTIjaACAOvXM3UirXaZR+LlV+nUZCbEyT3EMltpwACgNNd0AAABglIeHh4wkAQDAIiiZWjmcop1pjfUXJDflosxvuIXhIgGYgJpuAAAAAAAol6NfpMzdcq7p1ylpl2Se58FJ5gBgDIJuAAAAAAAol3ugNuj2yUvSr3POjJe54huFKwhgAoJuAAAAMNmRWt++fWXiZQCwbz4h0TIPKEqmoiLtqMOX873pZFEUOQU3sPDZAVgvtOkGAAAAk0OGff/99/plALBvfmHaoDuY0ik5I5NC/Lzp/dxHKSOvD/3S+j5Lnx6A1ULQDQAAAEa5uLjQggUL9MsAYN+cvUOpgBzJSVNIqQmXycM9hjJyCmRbuJ+7pU8PwGohvRyMGjZsmKQTgnFTp06l1q1bV9v12rFjhwzHk5aWhktewWsOAObn7OxMo0ePlomXAcDOOThQkkMwXVUCKDU1ka5ez5LVvu7O5OWKujwAU3B3AFSDTz75hBRF27aJ3X///RIgzpkzB9cXAAAAVGNq9ArafDKJpmuiySXuT/rLdSTFOnJ77u6WPjUAq4WgG6Aa+Pr64joCgOoUFRXRyZMnZblJkybk4IAEOQB7F+rnIfOr6TlUO+8C+Wiyycch19KnBWDV8NtTpbjWddasWVSvXj1yd3enVq1a0XfffWewz/Hjx6lXr17k4+ND3t7edO+999K5c+cM9vnggw8oPDycAgMDaezYsZSfn6/fdv36dXryySfJ39+fPDw8qGfPnvT333/rty9dupT8/Pxo/fr11LBhQ3Jzc6Nu3brRpUva8Rzj4uLkD7gDBw4YfOann35K0dHR8h10adc//fSTfAc+Rvv27eno0aMG79mzZw/dd9998l2joqLohRdeoJs3b5q8PkeOHKEuXbrI9+bv36ZNG/15lHfexhRPL+flnTt3Su03nztP/F0rYvfu3VX6nl9//TW1bdtWvldYWBg9/vjjlJiYqN+uu56bN2+mO+64Q47zwAMPyD4///yz/FHN12Pw4MGUlaVNGSvPpk2b6J577pFrxj8nvXv3Nvg54u/On/mf//xHrjn/rPB3/P333w2O89VXX8l34u39+vWjjz76SI5ZliVLlsg58/Vq3LgxzZs3r0LnDAAVk52dTc2bN5eJlwEAwnzd5CIkZORQQepFWc5yD8eFASgDgu7blXfT9JSfU4l9S/wRY2q/SnrzzTclIJk/f74E1y+99BI98cQTEgyy+Ph4Cd44WPn111/p4MGDNGLECCoo0HaGwbZv3y7BE8+XLVsmwShPOhxccqC6YcMGCaA4SH7wwQcNAnMO3P71r3/J+zmgzMjIoEGDBsm2OnXqUNeuXeU8i+PXfGwO1HQmTpwoDwD++OMPCgkJoYcfflj/ORyY9ujRgx555BH666+/aPXq1bRr1y56/vnnTV6fIUOGUGRkpByPv/vrr79u0F6xrPMuDwfbHTp0kDaQV69elYmDyYqo6vfMy8uj6dOny0MFfmgQGxsr19JY++jPPvtMgnh+mDBgwABJhV+5cqU84Pjll1/k4UdFcNA/YcIEOedt27bJgxQOmrmGrLjJkyfTK6+8QocPH5aHGRzY637e+BqPGTOGXnzxRdnODzn4+peFg3Q+Ju/HNXHvvfcevfXWW1JmAFB9goKCZAIAYK2z99Fql2nU9cIc0mRclnWF3rVwcQDKoti59PR0bogr85Kys7OVEydOyLyUKT6mp68fM9z33TDT+y5+0HDf9+sa368SMjMzFTc3N2XPnj0G60eOHKkMHjxYlidNmqTUrVtXycvLM3qMp556SomOjlYKCgr06/r3768MHDhQls+cOSPXbffu3frtycnJiru7u/Ltt9/K6yVLlsg+e/fu1e9z8uRJWbdv3z55vXr1asXf31/JycmR14cPH1Y0Go0SGxsrr7dv3y77r1q1Sn+MlJQU+Rx+Lxs6dKjy9NNPG5z/b7/9pjg4OBgvO0VRvL29laVLlxrdVpHznjJlitKqVSuD69WnTx/9686dOysvvviiUlHm+p779++X4964ccPgc7Zu3arfZ8aMGbLu3Llz+nXPPPOM0qNHD+V2JCYmyvGOHj0qr7ks+fXChQv1+xw/flzW8XVl/HPVq1cvg+MMGTJE8fX11b8uec2joqKUlStXGrxn+vTpSocOHYyeV5n3MwAAAFTIqa1L5G/TI9PuVnbNeEiWj373L1w9sEvpZcSSxaGmW4VOnDhBOTk5Ulvo5eWln5YvX65P++XaRE4nL6s32mbNmpGjo6P+NaeZ61KVuWbRyclJUqB1OLW4UaNG+vZ/jPfhdGcdTgHmlGHdPpySzfusW7dOXi9evFhSkLkWvDiuOdYJCAgw+ByuqeYa+OLflWuEuaaVa3qN4ZrZUaNGSU37zJkzS6XVl3fe5lLV73no0CHq06ePpOdzijl36MYuXtSmf+m0bNlSvxwaGiop3dwUofi64mnpZeFrx2ns/H5OTa9bt265n8k/S0z3GadPn6Z27doZ7F/ydXFJSUlSQz9y5EiD6/Huu++WKksAAACoPl5BtWXuV5BC3nnXZNk9SDt+NwAYh47UbtcbV0xv0/w/UBUTz5axb4nnHuMN2/DeDl1aL6cJ16plmO7j6uoqc27LW56SATmne+uOXbyn7uJ4ffG0cN37StKt43Ffhw4dKinlnDbN6c0V7fFbdww+p2eeeUbaN5dUu7b2F4Ox9GoOFPkacVvmKVOm0KpVqyQtuiLnXZMq+j05zbt79+4ycdvu4OBgCXw5MOe0c1Nly8cvq6zL89BDD0n6PKd7R0REyPu4/Wd5n6n7TqZ+bkz9jBV/H39m8Qc/rPiDIgAAAKheAeHaipFQSiXnwnwiDZFvmPaBOwAYh6D7drl4Wn5fE5o2bSrBNQdcnTt3NroP1zpy21duL3w7Y6/yZ3B73H379lHHjh1lXUpKCp05c0Y6ttLhfbjdt67Wkms0eSxqrjnW4RpnDtK4Eyw+Hw6+S9q7d68+gOYO3PhzdMe48847pd16gwY8XEXFcbtinri9O7cv5sBfF3RX5LzLwg8TCgsLqbKq8j25zXdycrLU3OvakJfspK66cZlzTfyXX34pmROM25lXFn/H/fv3G6wr69y5Jp4fKJ0/f17a5wOAeXDWFGeUsEWLFkk/IABg39wDImXuqsmn+KIgSlc8KSa8vqVPC8CqIb1chTitmDus4mCSA2tOt+W0488//1zfyRR3vqXrHIyDG+51fMWKFRJcVkRMTIykMXNnYRxkccdd3FEbB0K8XocD+nHjxklw/ueff9Lw4cPp7rvvNkgd5iCd17322msS/BqrhZ82bZp00nXs2DHpGIw79dH1Fs7v447cuHd1Tpvn78Kdu/HnGsM98PL35568L1y4IJ14cSdgxR8WVOS8y8Lp8fxe7rmbA+GK1hpX5XtysM7BPneAxsEob+NO1cyJe67nZgULFiygs2fPSqd8nLpfWfwdNm7cKD2W8/fiIJ4zEMrKLOBshRkzZkjHdfxwgh868IMTPgYAVA9+eMgZSDzdzoNEAFAhJxdK02iHSn07fxiN9JhLjj6hlj4rAKuGoFulONh6++23JSjhYJJTjH/44Qd9e1sOlDhAyszMlNpwHjKLU3UrU+vNAQ6/j4eI4rbInA7MgVPxY3BbYQ4WOZWb9+GAmtO4S+KaFE5H5h7UjeHaW+7Zmj+PewPngJIDTF2tPffKzsEa17byUFjci7Wu3XBJnH7MNbQ83BnXdHPP3Tzc2TvvvFPp8zaFH3rw53BGgC7NuyKq8j35c7jN95o1a+Rz+VjcE7o5cU/lfF24vTlnK/CDntmzZ1f6OJ06daIvvvhCAmYeToyHIeNjlVWrxhkSCxculO/cokUL+TnmZd3POABUHf//8/HHH8uk+78IACDNKVguQqjmOkX4IQMGoDwa7k2N7BjX9vr6+lJ6erp0AlUyrY47qOI/4pFSV3kcAI0fP17SssvDwz5x8FZyXGqujeaO1TjVurwxmy1x3mA+nEVx6tQp+u2336rleLifAQAAqsexD3tTcMZRqel2a9mXPhl0By4t2KWMMmLJ4tCmGyyKa9q5TTCnRJs7FRqsG9fKc4/7np6eklrOTSG4nT8AAABYly0tPqSCnR/SbOcv6VgGV1Ig6AYoC9LLwaK4bfU999wjqcGmUsvVYMyYMQZDWxWfeJu14rR4U+fNU0XT5iuCO1LjoJtTxTnVfO7cuZJCDgCWw/1RcN8UPFW0bwoAUL9wP3eK0CSTjyabPN21I+MAgGlIL0d6OdQAHo+af9aM4VSUkJAQqywH7sWd/9guq8M4HtPcFiC9HKDyeChCfsCmy0ziTBQAgO2nEkn5pj894HiYTt71L2rS63lcFLBLGUgvB7AeHFRba2BdFg6oKzsUGwCoC3csCQBQXO2CWKrveFiWPUO043YDgGm2UUUFAAAANY5rtrm2GwCguGCf/z+MC4ioh4sDUA606a4AO+/gHUAVcB8DAABUD5+QaP2yV/D/lwFApUE3DzXVsWNHSX+r7iGldONNZ2VlVetxAaDm6e7jyoxFDwAAAEa4+RA9voboibVELujrAUD16eV5eXnUv39/6tChAy1atKhaj+3o6CiBPHeCxTiw12g01foZAGD+Gm4OuPk+5vuZ72sAqJjc3FwZZYJ99tln5OqKXooB4JaG3XEpAOyt9/KlS5fS+PHjKS2Nxwqsvh7n+PIkJCRU+rgAYF044A4LC8ODM4BKQO/lAAAApqH38jKe2vNU/EKVhWu2w8PDpefp/Pz8MvcFAOvEKeWo4Qa4vXvn3Xff1S8DAACAHaaXV9aMGTPonXfeqfT7+A92/NEOAAD2xMXFhSZPnmzp0wAAALBpVtmR2tSpU6WGuazpwIEDt3XsSZMmSSq5brp06VK1nz8AAAAAAACA1dZ0c6ctgwYNKnOfOnXq3NaxuRMYdAQDAABQPu7XJDk5WZaDgoLQJwIAAIBagm7+xc4TAAAAWA73/M99mrDMzEzy9MTQQAAAAKoIuivj4sWLlJqaKvPCwkI6fPiwrG/QoAF5eXmV+35d5+3ldagGAABgj72X6/DvSf49CwAAAGQQQ5Y3IJjNDxk2bNgwWrZsWan127dvp/vvv7/c91++fJmioqLMdHYAAAAAAACgZtxPWGRkpHqD7qoqKiqiK1eukLe3d6m2avzkggNyvojGxvAG24MyVR+UqbqgPNUHZao+KFN1QXmqD8q05nAofePGDYqIiCAHBwf1ppdXFV+csp5KMA64EXSrC8pUfVCm6oLyVB+UqfqgTNUF5ak+KNOa4evra5tDhgEAAAAAAACoAYJuAAAAAAAAADNB0F0GHs97ypQpGNdbRVCm6oMyVReUp/qgTNUHZaouKE/1QZlaH7vvSA0AAAAAAADAXFDTDQAAAAAAAGAmCLoBAAAAAAAAzARBNwAAAAAAAICZ2E3QPXXqVNJoNAZTWFhYme/Jzc2lyZMnU3R0tHRIUL9+fVq8eLHBPmvXrqWmTZvKdp6vW7fOzN8EzFmmS5cuLXVMnnJycnDhraw8hw0bZrSsmjVrZrAf7lF1lSnuUdv6P/ebb76hVq1akYeHB4WHh9Pw4cMpJSXFYB/co+oqU9yjtlemn3/+OTVp0oTc3d2pUaNGtHz58lL74D5VT3niHrUMJ7Ij/Ifb1q1b9a8dHR3L3H/AgAF07do1WrRoETVo0IASExOpoKBAv/3333+ngQMH0vTp06lfv34ScPN7du3aRe3btzfrdwHzlCnz8fGh06dPG6xzc3PDJbey8vzkk09o5syZ+tdcjvyHYP/+/fXrcI+qr0wZ7lHbKE/+Xfjkk0/Sxx9/TA899BDFx8fTmDFjaNSoUfoH1LhH1VemDPeo7ZTp/PnzadKkSfTVV1/RXXfdRfv376fRo0eTv7+/lDHDfaqu8mS4R2ueXQXdTk5O5T4d0tm0aRPt3LmTzp8/TwEBAbKuTp06BvvMmTOHunXrJj/cjOf8Hl7/73//2wzfAMxdpqwiTxHB8uXp6+srk8769evp+vXrUuuig3tUfWXKcI/aRnnu3btX/o994YUX5HXdunXpmWeeoVmzZun3wT2qvjJluEdtp0xXrFghZciVSKxevXpSzu+//74+SMN9qq7yZLhHa57dpJezv//+myIiIuSXxKBBgyT4MmXDhg3Utm1b+UVSq1YtatiwIb3yyiuUnZ2t34ef/HXv3t3gfT169KA9e/aY9XuA+cqUZWZmSvp5ZGQk9e7dmw4dOoRLboXlWRJnL3Tt2lXKTgf3qPrKlOEetY3y7NixI12+fJk2btxIiqJIltF3331HvXr10u+De1R9Zcpwj9pOmXKzu5LZfJyWzDWk+fn58hr3qbrKk+EerXl2E3Rzuje3adi8ebOkXCQkJMgvj5Jty3T4B5rTqI4dOyYpU/yUj3+xjB07Vr8PHyM0NNTgffya14Ntlmnjxo2lrQsH6JytwP9xderUSf7DA+sqz+KuXr1KP//8s6Q4Fod7VH1linvUdsqTt3H7X65xcXFxkZoaPz8/+vTTT/X74B5VX5niHrWtMuXKooULF9LBgwflQcqBAwekrxsO0JKTk2Uf3KfqKk/coxai2KnMzEwlNDRU+fDDD41u79atm+Lm5qakpaXp161du1bRaDRKVlaWvHZ2dlZWrlxp8L6vv/5acXV1NfPZg7nKtKTCwkKlVatWyrhx43DRraw8i3vvvfeUwMBAJTc312A97lH1lWlJuEettzyPHz+uhIeHK7NmzVKOHDmibNq0SWnRooUyYsQI/T64R9VXpiXhHrXuMuW/f4YPH644OTkpjo6OSkREhPLqq68qHCJcu3ZN9sF9qq7yLAn3aM2wm5rukjw9PalFixYmazC5R05OQS7evpB7AuSnRpxaxfgJb8labe6Yq2TtN9hOmZbk4OAgHVGgptv6ylOHy4+f4g4dOlRqXorDPaq+Mi0J96j1lueMGTMkU2jixInUsmVLqYGZN2+elC1nMjDco+or05Jwj1p3mXLqMZdfVlYWxcXF0cWLF6Xdvre3NwUFBck+uE/VVZ4l4R6tGXYbdHObh5MnT0ogZgz/Urly5Yq0edA5c+aM/GByW1/WoUMH+uWXXwzet2XLFkn7ANssU2N//B8+fNjkMcFy5anDneOdPXuWRo4cWWob7lH1lWlJuEettzz5jz7+/7U4Xa+7XG4M96j6yrQk3KO28f+us7Oz/C3E5blq1Srp00ZX1rhP1VWeJeEerSGKnXj55ZeVHTt2KOfPn1f27t2r9O7dW/H29lbi4uJk++uvv64MHTpUv/+NGzeUyMhI5bHHHpN0qp07dyoxMTHKqFGj9Pvs3r1bUjdmzpypnDx5UuaczsHHB9ss06lTp0q63Llz55RDhw7pU3T27duHIrWy8tR54oknlPbt2xs9Ju5RyzJHmeIetZ3yXLJkifz/OW/ePPk/ddeuXUrbtm2Vdu3a6ff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+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# ============================================================\n",
+    "# Compare CRIMAC and echopype split-beam angles near target\n",
+    "# ============================================================\n",
+    "\n",
+    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
+    "\n",
+    "i0 = max(0, target_peak_idx - 30)\n",
+    "i1 = min(len(theta_ep), target_peak_idx + 31)\n",
+    "\n",
+    "fig, ax = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n",
+    "\n",
+    "ax[0].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    ref_ts[\"theta_n\"][i0:i1],\n",
+    "    label=\"CRIMAC\",\n",
+    ")\n",
+    "ax[0].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    theta_ep[i0:i1],\n",
+    "    \"--\",\n",
+    "    label=\"echopype split_beam_angle\",\n",
+    ")\n",
+    "ax[0].axvline(ref_ts[\"r_t\"], color=\"black\", linestyle=\":\")\n",
+    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    ref_ts[\"phi_n\"][i0:i1],\n",
+    "    label=\"CRIMAC\",\n",
+    ")\n",
+    "ax[1].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    phi_ep[i0:i1],\n",
+    "    \"--\",\n",
+    "    label=\"echopype split_beam_angle\",\n",
+    ")\n",
+    "ax[1].axvline(ref_ts[\"r_t\"], color=\"black\", linestyle=\":\")\n",
+    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[1].set_xlabel(\"Range (m)\")\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97d6eace",
+   "metadata": {},
+   "source": [
+    "### Identify the target (calibration sphere) within a range gate\n",
+    "\n",
+    "Using the broadband point scattering strength (Sp), we identify the strongest target within a user-defined range gate and extract its range and angular position for subsequent TS-spectrum computation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "c337ced4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def extract_single_target(\n",
+    "    pc_avg: np.ndarray,\n",
+    "    power: np.ndarray,\n",
+    "    theta: np.ndarray,\n",
+    "    phi: np.ndarray,\n",
+    "    range_meter: np.ndarray,\n",
+    "    r0: float,\n",
+    "    r1: float,\n",
+    "    before: float,\n",
+    "    after: float,\n",
+    "):\n",
+    "    \"\"\"Extract one target echo from a range gate.\n",
+    "\n",
+    "    Equivalent to CRIMAC ``singleTarget``.\n",
+    "    \"\"\"\n",
+    "    idx = np.where((range_meter >= r0) & (range_meter <= r1))\n",
+    "\n",
+    "    range_sub = range_meter[idx]\n",
+    "    pc_sub = pc_avg[idx]\n",
+    "    power_sub = power[idx]\n",
+    "    theta_sub = theta[idx]\n",
+    "    phi_sub = phi[idx]\n",
+    "\n",
+    "    if range_sub.size == 0:\n",
+    "        raise ValueError(\"No samples found within target range gate.\")\n",
+    "\n",
+    "    if np.all(~np.isfinite(power_sub)):\n",
+    "        raise ValueError(\"No finite power samples found within target range gate.\")\n",
+    "\n",
+    "    idx_peak = np.nanargmax(power_sub)\n",
+    "\n",
+    "    target_range = range_sub[idx_peak]\n",
+    "    target_theta = theta_sub[idx_peak]\n",
+    "    target_phi = phi_sub[idx_peak]\n",
+    "\n",
+    "    idx_target = np.where(\n",
+    "        (range_sub >= target_range - before)\n",
+    "        & (range_sub <= target_range + after)\n",
+    "    )\n",
+    "\n",
+    "    return (\n",
+    "        target_range,\n",
+    "        target_theta,\n",
+    "        target_phi,\n",
+    "        pc_sub[idx_target],\n",
+    "        power_sub[idx_target],\n",
+    "        theta_sub[idx_target],\n",
+    "        phi_sub[idx_target],\n",
+    "        range_sub[idx_target],\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "118b42f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CRIMAC r_t    : 5.7930599853739295\n",
+      "echopype r_t  : 5.79306\n",
+      "CRIMAC theta_t: 0.19805856629305635\n",
+      "echopype theta: <xarray.DataArray 'angle_alongship' ()> Size: 8B\n",
+      "array(0.19805383)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975\n",
+      "CRIMAC phi_t  : 2.127909429160737\n",
+      "echopype phi  : <xarray.DataArray 'angle_athwartship' ()> Size: 8B\n",
+      "array(2.12793011)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975\n",
+      "Target samples CRIMAC : (168,)\n",
+      "Target samples echopype: (168,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "r0 = 5.3\n",
+    "r1 = 6.3\n",
+    "before = 0.5\n",
+    "after = 1.0\n",
+    "\n",
+    "(\n",
+    "    r_t,\n",
+    "    theta_t,\n",
+    "    phi_t,\n",
+    "    y_pc_t_n,\n",
+    "    p_rx_t_n,\n",
+    "    dum_theta,\n",
+    "    dum_phi,\n",
+    "    dum_r,\n",
+    ") = extract_single_target(\n",
+    "    pc_avg=y_pc_n,\n",
+    "    power=p_rx_e_n,\n",
+    "    theta=theta,\n",
+    "    phi=phi,\n",
+    "    range_meter=r_n,\n",
+    "    r0=r0,\n",
+    "    r1=r1,\n",
+    "    before=before,\n",
+    "    after=after,\n",
+    ")\n",
+    "\n",
+    "print(\"CRIMAC r_t    :\", ref_ts[\"r_t\"])\n",
+    "print(\"echopype r_t  :\", r_t)\n",
+    "\n",
+    "print(\"CRIMAC theta_t:\", ref_ts[\"theta_t\"])\n",
+    "print(\"echopype theta:\", theta_t)\n",
+    "\n",
+    "print(\"CRIMAC phi_t  :\", ref_ts[\"phi_t\"])\n",
+    "print(\"echopype phi  :\", phi_t)\n",
+    "\n",
+    "print(\"Target samples CRIMAC :\", ref_ts[\"y_pc_t_n\"].shape)\n",
+    "print(\"Target samples echopype:\", y_pc_t_n.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "3291a82c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x700 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(3, 1, figsize=(8, 7), sharex=True)\n",
+    "\n",
+    "ax[0].plot(r_n, db10(p_rx_e_n))\n",
+    "ax[0].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
+    "ax[0].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
+    "ax[0].set_ylabel(\"Power (dB)\")\n",
+    "ax[0].grid(True)\n",
+    "\n",
+    "ax[1].plot(r_n, theta)\n",
+    "ax[1].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
+    "ax[1].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
+    "ax[1].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[1].grid(True)\n",
+    "\n",
+    "ax[2].plot(r_n, phi)\n",
+    "ax[2].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
+    "ax[2].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
+    "ax[2].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[2].set_xlabel(\"Range (m)\")\n",
+    "ax[2].grid(True)\n",
+    "\n",
+    "plt.xlim(3, 8)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "730f90e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"dum_r\"],\n",
+    "    db20(ref_ts[\"y_pc_t_n\"]),\n",
+    "    dum_r,\n",
+    "    db20(y_pc_t_n),\n",
+    "    title=\"Extracted target echo\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$|y_{pc,t}(n)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fd92ece",
+   "metadata": {},
+   "source": [
+    "### Align the matched-filter autocorrelation with the extracted target echo\n",
+    "\n",
+    "The matched-filter autocorrelation is centred on the extracted target echo and reduced to the same support. This aligned autocorrelation is required for the subsequent frequency-domain TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "ecbdd657",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype y_mf_auto_red_n: (168,)\n",
+      "CRIMAC y_mf_auto_red_n  : (168,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import _align_autocorrelation\n",
+    "y_mf_auto_red_n = _align_autocorrelation(\n",
+    "    mf_auto=y_mf_auto_n,\n",
+    "    pc_target=y_pc_t_n,\n",
+    ")\n",
+    "\n",
+    "print(\"echopype y_mf_auto_red_n:\", y_mf_auto_red_n.shape)\n",
+    "print(\"CRIMAC y_mf_auto_red_n  :\", ref_ts[\"y_mf_auto_red_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "7679300e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 1, figsize=(8, 3))\n",
+    "\n",
+    "ax.plot(\n",
+    "    np.abs(ref_ts[\"y_mf_auto_red_n\"]) / np.nanmax(np.abs(ref_ts[\"y_mf_auto_red_n\"])),\n",
+    "    label=\"CRIMAC auto red\",\n",
+    ")\n",
+    "ax.plot(\n",
+    "    np.abs(y_mf_auto_red_n) / np.nanmax(np.abs(y_mf_auto_red_n)),\n",
+    "    \"--\",\n",
+    "    label=\"echopype auto red\",\n",
+    ")\n",
+    "\n",
+    "ax.plot(\n",
+    "    np.abs(y_pc_t_n) / np.nanmax(np.abs(y_pc_t_n)),\n",
+    "    \":\",\n",
+    "    label=\"echopype target echo\",\n",
+    ")\n",
+    "\n",
+    "ax.set_title(\"Reduced autocorrelation aligned with target echo\")\n",
+    "ax.set_xlabel(\"Sample\")\n",
+    "ax.grid(True)\n",
+    "ax.legend()\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdc21a45",
+   "metadata": {},
+   "source": [
+    "### Compute the target and matched-filter spectra in the frequency domain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "2aa34af3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CRIMAC y_pc_t_n size: 168\n",
+      "manual y_pc_t_n size: 168\n",
+      "RMSE abs: 1.5463490954583334e-06\n",
+      "max abs diff abs: 4.604589062179967e-06\n",
+      "first 5 CRIMAC abs: [2.31729706e-05 5.79533997e-05 6.39145546e-05 3.88268996e-05\n",
+      " 1.50424514e-05]\n",
+      "first 5 manual abs: [2.05866846e-05 5.67176606e-05 6.43208689e-05 4.10774966e-05\n",
+      " 1.35798767e-05]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"CRIMAC y_pc_t_n size:\", ref_ts[\"y_pc_t_n\"].size)\n",
+    "print(\"manual y_pc_t_n size:\", y_pc_t_n.size)\n",
+    "\n",
+    "print(\"RMSE abs:\", np.sqrt(np.nanmean((np.abs(y_pc_t_n) - np.abs(ref_ts[\"y_pc_t_n\"]))**2)))\n",
+    "print(\"max abs diff abs:\", np.nanmax(np.abs(np.abs(y_pc_t_n) - np.abs(ref_ts[\"y_pc_t_n\"]))))\n",
+    "\n",
+    "print(\"first 5 CRIMAC abs:\", np.abs(ref_ts[\"y_pc_t_n\"][:5]))\n",
+    "print(\"first 5 manual abs:\", np.abs(y_pc_t_n[:5]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "5cbb42d1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "sample_interval: 8e-06\n",
+      "fs_dec: 125000.0\n",
+      "f_start/f_stop: 90000.0 170000.0\n",
+      "f_m shape: (1000,)\n",
+      "Y_pc_t_m: (1000,)\n",
+      "Y_mf_auto_red_m: (1000,)\n",
+      "Y_tilde_pc_t_m: (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "sample_interval = scalar_param(\n",
+    "    cal_obj.beam[\"sample_interval\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "f_start = scalar_param(\n",
+    "    cal_obj.beam[\"transmit_frequency_start\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "f_stop = scalar_param(\n",
+    "    cal_obj.beam[\"transmit_frequency_stop\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "fs_dec = 1 / sample_interval\n",
+    "\n",
+    "# Use CRIMAC frequency grid exactly for manual validation.\n",
+    "f_m = ref_ts[\"f_m\"]\n",
+    "n_f_points = f_m.size\n",
+    "\n",
+    "from echopype.calibrate.ek80_complex import _compute_ts_spectrum\n",
+    "Y_pc_t_m, Y_mf_auto_red_m, Y_tilde_pc_t_m = _compute_ts_spectrum(\n",
+    "    pc_target=y_pc_t_n,\n",
+    "    mf_auto_red=y_mf_auto_red_n,\n",
+    "    NFFT=n_f_points,\n",
+    "    frequency=f_m,\n",
+    "    fs_dec=fs_dec,\n",
+    ")\n",
+    "\n",
+    "print(\"sample_interval:\", sample_interval)\n",
+    "print(\"fs_dec:\", fs_dec)\n",
+    "print(\"f_start/f_stop:\", f_start, f_stop)\n",
+    "print(\"f_m shape:\", f_m.shape)\n",
+    "print(\"Y_pc_t_m:\", Y_pc_t_m.shape)\n",
+    "print(\"Y_mf_auto_red_m:\", Y_mf_auto_red_m.shape)\n",
+    "print(\"Y_tilde_pc_t_m:\", Y_tilde_pc_t_m.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "38b09cbd",
+   "metadata": {},
+   "source": [
+    "The figure below shows the DFT of the extracted target echo. This spectrum contains both the target response and the frequency characteristics of the transmitted pulse."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "f4e0e279",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db20(ref_ts[\"Y_pc_t_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db20(Y_pc_t_m),\n",
+    "    title=\"Target DFT\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$|Y_{pc,t}(f)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7c6effbd",
+   "metadata": {},
+   "source": [
+    "The figure below shows the DFT of the aligned matched-filter autocorrelation. This spectrum represents the frequency response of the transmitted signal used for normalisation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "77ef947d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db20(ref_ts[\"Y_mf_auto_red_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db20(Y_mf_auto_red_m),\n",
+    "    title=\"Reduced autocorrelation DFT\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$|Y_{mf,auto,red}(f)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b2fe7202",
+   "metadata": {},
+   "source": [
+    "The figure below shows the normalised target spectrum obtained after dividing the target spectrum by the matched-filter spectrum. This quantity forms the basis of the broadband TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "f8caa9c9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db20(ref_ts[\"Y_tilde_pc_t_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db20(Y_tilde_pc_t_m),\n",
+    "    title=\"Normalised target spectrum\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$|\\tilde{Y}_{pc,t}(f)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6091646e",
+   "metadata": {},
+   "source": [
+    "### Convert the normalised target spectrum to received electrical power\n",
+    "\n",
+    "We convert the normalised target spectrum into a frequency-dependent received electrical power spectrum using the transducer and transceiver impedances. This reproduces the CRIMAC P_rx_e_t_m variable used in the final TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "158cf758",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype P_rx_e_t_m: (1000,)\n",
+      "CRIMAC P_rx_e_t_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import _compute_ts_spectrum_power\n",
+    "P_rx_e_t_m = _compute_ts_spectrum_power(\n",
+    "    normalized_spectrum=Y_tilde_pc_t_m,\n",
+    "    n_beams=n_beams,\n",
+    "    z_et=z_td_e,\n",
+    "    z_er=z_rx_e,\n",
+    ")\n",
+    "\n",
+    "print(\"echopype P_rx_e_t_m:\", P_rx_e_t_m.shape)\n",
+    "print(\"CRIMAC P_rx_e_t_m  :\", ref_ts[\"P_rx_e_t_m\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "540bf3ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db10(ref_ts[\"P_rx_e_t_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db10(P_rx_e_t_m),\n",
+    "    title=\"Target received power spectrum\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$10\\log_{10}(P_{rx,e,t}(f))$\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2006c97c",
+   "metadata": {},
+   "source": [
+    "### Compute the frequency-dependent beam compensation at the target location\n",
+    "\n",
+    "Using the target range angles (θ, φ), we compute the frequency-dependent beam-compensated gain. This correction accounts for the target's off-axis position within the acoustic beam and is required for the final TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "a24e5128",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype g_theta_phi_m: (1000,)\n",
+      "CRIMAC g_theta_phi_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "g_theta_phi_m = cal_obj._get_beam_compensated_gain(\n",
+    "    channel=tsf_channel,\n",
+    "    theta=float(theta_t),\n",
+    "    phi=float(phi_t),\n",
+    "    frequency=np.asarray(f_m),\n",
+    ")\n",
+    "\n",
+    "print(\"echopype g_theta_phi_m:\", g_theta_phi_m.shape)\n",
+    "print(\"CRIMAC g_theta_phi_m  :\", ref_ts[\"g_theta_phi_m\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "e0d8abd9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    10 * np.log10(ref_ts[\"g_theta_phi_m\"] ** 2),\n",
+    "    f_m / 1000,\n",
+    "    10 * np.log10(g_theta_phi_m ** 2),\n",
+    "    title=\"Beam-compensated gain\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$10\\log_{10}(g^2(\\theta,\\phi,f))$\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9129eb3a",
+   "metadata": {},
+   "source": [
+    "### Compute the calibrated TS spectrum, TS(f)\n",
+    "\n",
+    "Using the received power spectrum, target range, beam-compensated gain, and acoustic calibration parameters, we compute the final calibrated target strength spectrum TS(f), following the formulation described by Andersen et al. (2024)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "90f1d082",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "scalar absorption: 0.03770373022901242\n",
+      "CRIMAC alpha_m min/max: 0.02804324195086584 0.04521493514355129\n",
+      "echopype absorption_f min/max: 0.02804324168412123 0.04521493476510025\n",
+      "max abs alpha diff: 3.7845103439959615e-10\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.utils import uwa\n",
+    "\n",
+    "absorption_f = uwa.calc_absorption(\n",
+    "    frequency=f_m,\n",
+    "    temperature=float(scalar_param(cal_obj.env_params[\"temperature\"], tsf_channel, tsf_ping_index)),\n",
+    "    salinity=float(scalar_param(cal_obj.env_params[\"salinity\"], tsf_channel, tsf_ping_index)),\n",
+    "    pressure=float(scalar_param(cal_obj.env_params[\"pressure\"], tsf_channel, tsf_ping_index)),\n",
+    "    pH=float(scalar_param(cal_obj.env_params[\"pH\"], tsf_channel, tsf_ping_index)),\n",
+    "    sound_speed=sound_speed,\n",
+    "    formula_source=\"FG\",\n",
+    ")\n",
+    "\n",
+    "print(\"scalar absorption:\", absorption)\n",
+    "print(\"CRIMAC alpha_m min/max:\", ref_ts[\"alpha_m\"].min(), ref_ts[\"alpha_m\"].max())\n",
+    "print(\"echopype absorption_f min/max:\", absorption_f.min(), absorption_f.max())\n",
+    "print(\"max abs alpha diff:\", np.max(np.abs(absorption_f - ref_ts[\"alpha_m\"])))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "0a14d495",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype TS_m: (1000,)\n",
+      "CRIMAC TS_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import _compute_ts_spectrum_calibrated\n",
+    "TS_m = _compute_ts_spectrum_calibrated(\n",
+    "    power_spectrum=P_rx_e_t_m,\n",
+    "    target_range=r_t,\n",
+    "    frequency=f_m,\n",
+    "    sound_speed=sound_speed,\n",
+    "    absorption_f=absorption_f,\n",
+    "    transmit_power=transmit_power,\n",
+    "    gain_f=g_theta_phi_m,\n",
+    ")\n",
+    "\n",
+    "print(\"echopype TS_m:\", TS_m.shape)\n",
+    "print(\"CRIMAC TS_m  :\", ref_ts[\"TS_m\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "7ca23f61",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1000,)\n",
+      "[0.02804324 0.02806629 0.02808933 0.02811234 0.02813534 0.02815831\n",
+      " 0.02818127 0.02820421 0.02822714 0.02825004]\n",
+      "0.02804324195086584 0.04521493514355129\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ref_ts[\"alpha_m\"].shape)\n",
+    "print(ref_ts[\"alpha_m\"][:10])\n",
+    "print(ref_ts[\"alpha_m\"].min(), ref_ts[\"alpha_m\"].max())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "2903e237",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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59YJrndZQaTmup6DczBRozq9Hq6zt0MCCeJU/Tvn3g1vdDtBomMq3unI9/AMa5ByEu1bBzlZvwarWFTsTt+XYH+iQvQWnlVBMNE2Dh1bB2IZWtPAt/LNjsgLv7NMgMVcFf4MVTzfPRmbqZTS7sAihuCy32aVpC02ru6DTqGE25UJz4g+0yt4JBSoc1TZDjt4PWSYL3sq+A0arCq7IwWL9dBhglK/PgisOe/aANrI7dAZOfEm1S0ryZQSeXYIm1tPy+YOmaTinhCDKkI6PlPfhgWzEww87g8cgsm4kqgvrxb1oHbsIRmixpt4LCPfzKPR3IzvXiB0XMtAqfR16Knugh60CnAkX3Gl6Dc39NBhU14oQgxkZcUfR4vJyeFqutLjuVRrhRdODyIUWL2gXor/6SjdNu0dMTyJBVwe31clCe/fLsHrWhcaUicjjX8MtJw4HlPr41jwUz2kXoY4qodBrzynBmGJ6Allwgb9BwWPNLfCvgUMxs7Ky5Pjk1NRUeHl51bzAoqSKfUE7d+7Eli1b8PPPP2PDhg3QaDQlBhbnzp3DypUrC71eDNyeP38+xowZU6oWi/DwcCQkJFy3QCsrUly9ejUGDBjglFdzq7oMh3y2HeeSsjD9lmYY2zm8wt9LfKW2nUnC5m1bceepF64sV6lwPqg/vJr1RYuWbaH1DgPUtr7n1V1Fn4OX0nKwc+nnaHF+ATSKGEIPmFQ66BTbj8I2tz7o/8gs+LmXHIgpVisyM9Ph6uYhv//VmbN9h+Pe6wCj0Qh/L3e4T91W8oaKgsv7/8K5Ewfwb53RuKVdOLxdi///741OwTMLt+OenIXorjkCvWKEGrbuA9/q7kaTJm1x5/Ar5adYLdj63bMIj10lU0IL55Ug3G96DgEeetzcNAi93c/BLesi3I78DH9TrNzGqNLjokcLHKj3MNwDw+HnpoNf8gF4q7NRr0VneAbUgbNxtvOvKojAeM6ms9DumYObMv+GBRqcMzRGy7FvI7LOlR4QgsmYgz1//4zMjDTk6nyhdveDX0RzNIqok9/65ihn/t2HtCVPwtdypcKbq/PGth5zMLx9PfjqFSTuWoykDV/BkJuU/z3K8qoHs9oVMW2nokNUANqFe5drXpobPQd/+/j/0CFtDQ7VHYOh9794zd/do7FpSDm0EhcPbUSDrH2YlDsVyfCCClZ8rfsA9VW2vwFCrFdrmOr1R5cu3aELbixfv2P7JgSueRJa65X6n1ajglu9LvC88ytoisledyH6NG6bfwapORaM1qzDI5o/5HKDVg0FCtz0Wiy33oR30gbiHs0aWAOb4fnJk8pclo7+Dot6cEBAQKkCi2rZFWrKlCnFVvgLioqKwptvvolt27bJ1oeCOnbsiHvuuQfz5s1DSEgItm/fXmh9cnKy/JCCg4sfZCv2d/U+BfFhOvKPsqPf3xnkpifAL3k/0hGMW9rWrbTy7NUkBL2a3I7zZ1vj+IZFCD31X7gouYi8tBq4tBqx64F3reOwztoeEf5u6O+fiK7+WWjebQiC/G3NrdXRtc5B8UO842wSkrcvgi5uD/xzziHXvS6sIa3QpttguNdtgQPRSVi6Pw4Ld5xHB6sab2otuODWDD59HkOzNt2wdcknCD++AEfTXfDiu+tQP9Adz1jnwgsZtj7AFjN0lky4WNLhbs2ASrFiIl5CSHhD3NkxHLe1q96VQqf4DpuNUCy2APB87w/Q+jr/n7BOI+St23V227l+IBbc2wxxCy7CxZQjl5l0nshp+wBeH/wQVqxYcVX56dD70U8Qe/owTm1fBlNmCix+DbG0U3c0DfGEi04Em23kltZbH8LOfxbDuuNbBBmjEZW+F2/sPoWzSpZc/4hmGUZr1iNlA3DEtRHSwnqgRZsuiGzdKz9TlTj/opOy4aI2I8i36i8wVQSnOP+qyKy//8V36//FZO1luKtt50mrnN3InTcSGeO+gm/9jnKZKTsd+2c/iNDUwn37rdvVOIxAHG4yBa0790GPhgFVPmHkzuVz4LPjA/jmXbxJdImAV9f70KjbrWju6pm/XUjP8QjsPAqH5j4Oj4tbEKGKB9JtY6HeWN0L78NbHv+kBkno0qKRnLdG0ugq9Rw8fikdzyYMRR1VF/x629Drvq5NZAAQeQ8w7B5k5pjw8uE4/LbvIvSnVsqgIhXuSAm5CWFDn0ePqKK/FT169gParcbpf/ch5cAKtGzaBPouE20XAEv47OrVb4LtLzaUCWA2n+wET4xEoC4XKoMXoFIDfvUxFmp4LvgQraP/AZL+wX8/Oo5bHv+gxIss1fE7XJb3rJaBhYiKxO16PvnkExlc2F28eFGOnxCtGCL1rNCtWze89dZbiI2NRWioLT2Z6BYlAocOHTpU4v+CqqPLh9Zipm42jmibw8+9aDe4ihYR1QARUS/CZHoWh3auRcq2BQhIOwo3awb2mqJghFUO9O6buBrhmrVI2fE2dtQZiSaDHkajqIhSv4/oi755zwF8sidXVoDevaM1GgReaTKuLInJyTi1ZSm+vtwCe6NTkZhpxIe6FWiqsjW3IycGSNyO+MPfIh2uWGNpj+8tI+UqU0R3pHfsil6deub/4Pa+5wWcOz4U2/57CsgATl/OxEGNAXdoCl8csDNCh7NGb5w+lYgtpxJlBXNE355o1KR5kW3Tckw4dCEV0clZCEzag7Zd+sLPx7syi8cpWTMuw2xVYIYmv3JVkd+X0Of+wok96+Du7oEGLbvLH/Rr9e8Nrd9C3q5FrdWiy8C7oPQfhbNHd+Piv9sxRNsGJ1KAXLMV6uzWuJh8FmGmcwjNPoHQUydgPjUXO5f6Id21Dj52n4qziVkyG9YHui/g7+kK7053o3XPW+W+ybl8veEUZq8/JYPX+sHeUDefhkytL3LXzoCPJQUXFkxG9LBZiGzRFdN/WI97U0/JlrBE/45wt6TCkJsIj9xLCLdcwtzDJzDjoJusmL9+awvUr4K/y8J/d0ZjxeZYPKvVIFPrD5f+/0GHzv2hKeF81Rjc0ebhb3Bq4yLk5OQgNSkeRrOCvlluWHpehb0no+F5/i3ErMuW2RRFRTpL5QaNzoDUun3QoOdd8IxoXWifpy5nICnTKOe3CXTXysxucWk5OJOYIr93QZ4GmMxmZMefRlhoHXh6uMHH0xM6tehIrMZLvx2S+2nZvDlCg65fJyzI3UWHkR3C5S0ptRlOnBsFr4A6aB92nb/5HkGo33EgIG6lZLuIAfRpEgRA3AoTJX77hGmI/mQNjKlx6JaxGl8s+g0v3H8nnFGN/osYEVG44uXhYfvCNmjQAHXr1pWPBw4ciObNm2PcuHGYMWMGkpKSMG3aNDng2xHdmsixsi6dgrhOk+NZ8V2grhftt7tpIHDTQJjMFpxLSMdPshuUCtFJWcjacwbGkzuhN2egWcyvUL5bjE0B3RDe/xFENu9c4n7FH+W9f/8M3a6voM41YafpP/IP8ohPN+HDwX4Y2K1TiVda7LKzc3Ax+jTO714BS9oluCQdg96SAYPKgh/CXkTX1s3Rt3HhVpSYM8dwcsl0hKTuhz8s2GF8HWlwl83+SaGDEeeZAwQ0Rtb5vTDHHkbD3CPwRDa6ak/geNNgjOsahe4N/Yu9ghfZuA3++2Qz+aN0JiETltQAXMzuAa1OB61GC4ObJ9y8/eHlGwwPb1/8mmjGwu3ncXTPRgy9OBs5C7/C6taT0bz7MCREn8DlIxtxMf4ypicPlJlQhG91HyFpy3+wx78X2g+bCL8GvMhQWqmJF0UPJyTAG519Kn6sgk7vguZdB6MyqNQa2d1J3LoXWiMuRD2GSxfP49jmpVCid8Av5SD8rElQMs3Yn5xqe70KiFLFwTsjE1j7IvZv+hgZPZ7HTb0GF9tNgmqebccvQrfqBfRSt4W28QCMGP9hfnA7P8aCBse/QrglBqbfH0X/X5/HZfjiuG4SXh7aFD262jIESumXcHzbckRcDIH+hAqbTibgtU+/xjN39EKrNhUbkBeUm52Bab8dxx8HRLefdmgSFoaH7hAp90uRBl2tQYPeVxIhCH1Ei97lDCxZsxmxx+pCbzkHg8UIWMTopgxYjRnwPLYYP/17Dn+GPormoV7QJxzBTbHz4WuOhwEmpECDC4oL3OGGk3tn4RXzBEQrtuO5X/Mn7tX8LR+L4dBpUEEFRZZrnGki3PRheHl40QtFZeHn7YUurcu3j3LTucLvgZ9xYvZYeGbH4M4zr+DtF//BHY/PQJOQK61HzqBGBxalIfpeL1++HJMnT5aDvAtOkEe1i9pqRPj535Ainvg4bnCaTqtBw5Ar2WkaBnkATaeIToA4vHYRVJs/hsGYjNCELTAu2oY3w56Fb5Me8HXTQ3d+I4IvroElJx363ET4mhPgnzc4Va12x7Qu7th42RXqsxtQ76952H6gNzo99GmxV1X3nE/G+RWz0Dj2DxiUXFzdPiIGv/16LBe/HNuPQA89Hnbdgd3rzcg+tBzhSVtRN69ne5I2CI91CUfbZo3RPtIXOk3BKz23yRaUxPhYxF++hDYRkfjKq3B60uKIsRV+7n7oFCW2FUGgrQWyOO3dgfYRvjgQcg7Z6wPgbYxD/f0zkbN/JsSlBnGrCy201t4I8/NGA383WC/5Q5UTh3oJ65C6YD3O+raG0a+JHOC7X98GZ5VQWXkOdFejm3EbOvcaCq+gqg1Gq6vkhHg5YDpDIz5r56pMB4dFIHj0E/JxakoyYo/vhinLhK8C2yHS3w2Rfu5Ijm2CI3/PQ2D0n/AyxcNr7VPYvfVjmPq/iW4dO8p0u+KcP3XsAJJjTqJZlwHw8OBFrBrBYkbWH8+hl/oAYnXheOD2VoUuzAS4G9By0lzs/uFFzElqIyu/4rx4d+xdaFnnqivhnsFoPOABvCEGSidk4puFizA+4VtolnyL7acno8ttj8GadBapcSeRdno3TjS4Hzc3CypXd6mcc7sQ89MTSEi7DUALDG8diufGDJXnZHmI1u9nxgxCjqk/9pxLgjo7EUmZZhhMSciIPQXTyXX4b/pNOHk+BXvPp+Am9VncqxUtPrbiE39LvVSZCEMixJG09FPgZfCSrRmNjYlQW23biF8UEVQIgUjGbN1H+LfvV6jr6xxJc9x9g9H2sR9w+fNBSMs24i7NOkz7bD7G33EbbmkTVub5tKqrajl4u7oRg1a8vb1LNWilMogrJaJ/sciAxf6xN16GB+c/h8ALf8JoUXCky/u4ZdgIVFd7NixD/OYFaJS9Hy+b78cWa0u5/Db1Jjyu/a3QtjlqV1xqMBrtRzwGH29veVV+/YI3EH5qkRz8mq33RWqzsQhsNQANGzTG3vNJ+H5bNP7YfxH3albjfs1f8o/9RY/mMPs1hktYc7j510GCyYBNyX5YeTgOsSmZWKV/Nv+PvnDOqz0aDJ2KyKadqs2MyTmZqdi94EV4Xt4Ld1MictTuSPBtDX1UV0R0H406AXlBjaLgxN71OLryG7TI3l1oH2+bx2KN1daC0Ve9Fy9pf4BR7YrY3u+hb58BN/TD70zfYXE+PLpgJzqHGbDoidJ3FyiP6lh+iUmJOPzf6agbuzp/DoAvXR7ExcCeiE1IwefZz8qMVBlqL6S3uR9dhz8Irc4xWeGqY/lVR6sXvIv6J76Xj717TUJA/yeLLUORdezN5UdR19cVk3rVh7YUAXZ2ymVs/voJ1MvYK58bDX5wNyfDZFFwQQnEeNPz6NkoAPd0icDA5iFlDgYuH1yNxN+eh86ciRhRLR/2LUZ0blwl4zrE+X8+KUterDoVn4kwdRI6aE+jTt0oeLi6IFelR1ZiDHbs2oOON/WCf702gCHvKr1I26rWIjXhoowszp0/BUXnjuTEBPiG1UObloW7VzmD7Oh9uPjzU5iX3BI/WW6W8/jc29YXkwa2RbifW7X8DpelHuz0LRZEdmnJl+BtsVUAPOp3qtYF077XcKDnMJzY/Q86nNUgwOSNzFwzwl164iyC4enlC6+AUPiHRqJeaH200F75QyOuevQb/wrWLWuAiJ1vwtWYDNf9nwP7P8cJaPG1+Q6stNq6V5la3gVj/SFo2rEf6hczEK8fgOeGNMFPG48gemMEApREJPi2R3j/R9Gv+Y1NLFiZXNy90f2Rz2TgYMrJgNbgJru/FKFSoVH7PnJw7r7NK5B8Zh9MafHw0JjRK7QdugU2k5t5njgGS7QBeks2Itc+gT1nBqPDhA+qTSBV1UQF4vGFe2GFGj6+1TfJQFXw9/NHr0c+QUxMNC7++hxSkuLxW1oTWNIS5fqt+pboqDkFD0sqPPZ+jF1HfkP9+79FUFjpx05R1dl/Nh6+JxbLx8keDdGg96Mlbutu0OKdka3KtH9Xn0D0evIHrF80C/VOzIU+N0kmRo1T/LDVKrrpKNh4IgH7T5yDh8e3SIsagt53PAp3V5cSk2Xk5OYg5/wexG/9Ce7n/oHOquCMOhI5I2bj1vb1UFVE8BLp7y5vV1xJ1yBS4aiDmiLnTC68GnQRfYOvbJYXYHiHNpD3rcNs987MNbwtGkz7B32PxWP+3J2og8sYf+QZGI9YcaDDI2g+/IlSBavVFQMLqjXUubITFN4xj8UnDWrApHWi8tvxZjxdpDvu0FK9vM/we5DWvjM2/70EdaKXw914GVrFjF7aI/BqNRLjb4oq2nxfDINWg3t6NMWKtMnoUVOueKpU0BXIelISvVaNzr2HA+JWnJ5P4XLSBJyaP0UO+PY5+xdWv3cB7e95E/4RTeUmlxMScXLr/+Rs7h5pJ2DRukPf4V607TcKmgIBnzM4EZ8Bo8WWArZlHXbvEerUCUedqQtxLi4BTx5JRpCXC8K8XdE+YiC0sGLbH9/A99BcBOaeR/rsgdjr0RExN72BpqGe6BzlV6MrEE7VBWrpkwhCOpLVPoiYtAjQVfxkA3qdBgPGPYtj/w5F9LG9MAe3Qrc2LdDVoMXw2DQs2HIW7Q69gVDjeYQe/wr7312Ck6FDYfSuL69Ye6afxO/og6RcFWJTsvArnoEeZllxF/NFbzT0wuCHXkdIcEiFHztVvL5NgnDqrSE49vV9UMfa/q66756N7XsWI+Ku9xHe/Hq59KonBhZUa5xSwpCiWHBHv24yt3Rt4BXWCEPue060OyAzMxPpl8/jrpAI3ONy1WykVKJAPz8E/t9C/PbTV2h99EPUzz6Ey9+OwgPu05Gs8sOlpBT8V/8pgpBte4G4DLlpOrbtXYQOj/8IF7eqyQJTFeJSc/C4Zgm8VFm4v8Vrjj6caiUyJABTQopmruk1agpiOg9FzLwH4G+KQ3jGAUxadlj2JnfRqTHNYxV8PVzg6u4lr2KrjenQWI1QXHxxLGgQNibaujdeSs/B3S098dDA9lWettTZ7fj9SwQl2bpEBncfjyDvyv3ONmnaUt4KEhd53hvdBgm9P8ORjUvgf/h7BJsvI/jiPOCibZszSgh2mGyt7S7IhV5vRjI8EacJg6rN3Rg9ZJRsTaGaQ6NRo/nYd5F8dB1y/n4HWUYLQpTLSF30CLb0/Q539ql533eegVRrfG29FbEmFeZF2CZPrG3c3d3h7m7r4kNld/vdk3B+dyRO/vU5snJysT9ZXNHMgkqlxxqv29DW3wqfRl2QeHgtImOWIyTzGA7NGgb0exktO9qyxWSkpyAr5TLSEuNgtVrgWbcFwsNCa8wPR3x6Lrqpj6CeIQ1aq22uCbq+OhH1EfTcSpw8uA2nj+xG71w/HLiYgYysbPTIXA1dprjeXNSZ6GhsMo+Xj7upD6P75h+wJno4etz9nOz2Jz+T6BP462gSDqS6oHGwB5qFeqFblI/MokbXdzElGx/szMX9mjrwdDXgpr4POLTYAoJC0OuOybAOuw8nN/4M1cnVUDIuw0PJgDqkP95u3BIerjpE+bkg2O0f1PcNLr67J9Uc3nXh2/Ve5La/ExkLp0J9ei1ckYt//56LbRFR6NagZnU7ZWBBtUZK3mSaYd4V38RNtUNEh8Go03YgzsfGYX6WTs6uKrJ6+XsMu7JRj6E4sPMW6JZNkVefnv3jIsxr16M54tF0Tz9oFRPsQ3hF48ZhGJDs2RgeLYegWf/x+TnRC5KDg8VNpXJoEHIpNQutVGm27CXuRfO1U8l0egOadegtb6LjnWiFiL6UgKzdjyIp8QJM2Wmw6j1gMfjBqnMD0i4iymLEtAYN4OPhCpeNy2BIN6Le+SU4OXM10hveKgeBRmUdwhlLf/xqGSLfJwCpmOv6ITK8GsKn5yQ0bV8gBSoV8cuuC9hmbSZvax7vCWiLTo7rCGoXDzQe8CAgbnkKz/dNzsag16PR+C+wZsNazFu5DRutrbBv5b94+/ZWiE/Nkj8BNQEDC6oV0rNykSMHbqsQWgm596l2NV3XqxuGaw2NbN2pF2JCfsenK44g7owCZBixG77Q6m0TvaVo/KCoNPCzXIarkgvX9IP4fGN9HP53Mx7sUQ/dIwwwXj6FI3u3AAkn4Jp8DHURj2y1K056d4eu33MY3CJEjhEpyGi24vjBHVCSTuOcdyc0jwxFlL97udNN2jU4NR9aWKBV6wD3sk1YRYWJ4CwqNBAY/tg1i6av/UGXL7D1n/9BtelDBFouwfXYD3KxGWo09tPg8VYNcSgmFY3Pr4GbJR1uyXuB3x/BwT/ckKQLg86ixsFDH+Ix05Mwad2QY7LiPizDYO0u5Oj9YWxyC7oMe6BmjKGqIMlJifjw72Pyd+Gju9qiQRDHDZGDqVS4uXc/RDXvjJtnrUdG9CEc/eJtfGMehrph4ShwCavaYmBBtUL6iY1YpX8OB9WN4WGoCV9NqunqhEfh84cjkWm0YPOJeGzatgumrj+hcbM2UOcN2M3NTEHsmaPYsHkTlke3QO6ldDy7+AC+1H2IxqoLsA0Pv8LDmoGMxBi8+tNedK3vh7dubyVzzKdn5eDY4jfgdeZPuJqz5LY/m8djo7U1QrxcMLhlCJ4fWB8uLoWD6hyTBa/9fhjLD8SivVcqnu7hj9Zdbi75/5S8U95b9Z5AMVnEqBKpVOh2823I6j4YGxd/Cd3pVTAENkCDYf+Hu8Mb5m+WndMW+3YMQsaBZah3eQ3clSy4G0/aVloAV1M8YnNs177Vmmy4K8lwNyUDez7Env0/Ir7ZeHQdeCcMLi44m5ApJ6m8nJ4rkz5EtekFvZtzVL6tVgVrP5uEBbpYfK0Zg8EtK2dSRqIbIf6uPxd5AgNjZ8vns3Sz8fDFp3Dqciaahl2ZB6s6YmBBtUJmymUYYIWhmIniiCqL6LbkYdCiX5NA5JxS0KBJy/ygQjC4+yCqZTd5G5iag5mrjmHPuWRkpxqQqzLgkntTqP3rIbx+c7hEdEBmehJy/o2H62ENtp1OwosffonJnhvhYbwMX0ty/n5Naj3aeWVgcyoQl5aD+G2LcHLfKpjajUe74Y+KSXOxd9dmvPLnORzJFj9SCiKTNsF9+Sqs3HcrBk16r9j/j6vRlkr1cNeZ6M3TxiHcXFww6B4xv8KVORYKcnXRo1uvQUCvQTBmZ+LS+eNIiD6KE/8eRWjzbvi8YQcoWle46jVQctsjLeYEkk5uR/DxnxBgiUfAoRlIOvQh/rB0xWeW2+U+xXwcffUvIHqlFmlBnWCO6g2TwQeWtDikJMbjuCUEpz06ItDTgJ71PNGveRhUmur9t3b/6Ri0NB+BRmXFnb3bF9sFkciR7r9rFExz5iIj1wwXxYx7wk1oEFj9E69U728+UQXJTY2XKfnEpERE1VGItwtmjm4jHyuWHuJyMpoXM56iUVugV2waXvztIIbFbked7ONyuUVtQGZoFzQc/Cg8I9vJ1o6Hc81YsecMola+BVdzKlx3foKNx9bLmdvDjacxE3o8p5qI+24fjsDVXwG5QMOY/+HC+UdQN+Kqzl6mHOgtmXJciFdg3aopFCoXvas7wpu0Q0j9ljifuQJdew64qquTO1AnFOjcC7nZj+Lon1/BcPRX6HOTUV8diwBXA+oHuCNYk4q4mGCEWC/BK24rIG55RNvHWvOtWG6tI5/HbNuFIPe/ob75ZbToWjUTKN6IY7vWoBOsMHuE4pa+3R19OERFuPjVhcuYb+CZlQiz1h1hh65cPKrOGFjURpkJOHrqNAKPzMPnGX0Q1rgDWtX1RuMgD/h52AaumSxWmHOycGjLcrS8aRhc3Wt2ykxLRoLt3sXX0YdCdF3Xu9orMv8smdwdsYcVnIs+B51nIFq07gQXz8Lnt2gtubNbI0RHLsaBJTPQNH4FwtL2569P0/jg9ftGol3DOkhvPBcJH/aAVQGObfkddSOmFtqXolLhNdN4eFlTMc2/ZmUpoeszuHqg7cinAeuTuHzuCAZ6+WKkvy1YEIymAVi3bRtSD6yAd9JB+GuzkaELgMHTF33qD0Qrt/qy21TCrj1wy70M9Z9PIM74HEJ63V/9ij83A21P2bqYWOp2dfTREJUs3DaZrWIyAYdWoCZgYFHLXNz5P7ivfRn6DCNSAdyLNXj41FPoqPsKP2s7wj24AWJ92uHLvUa8rf0GXdT/4uLGV5FmCIHH0NfRqF3NzDDiknpa3qvcWSEi5xHaooe8XY9IaRs+5QMc/3cCLmz8ATpYEdS4M1q3uxluXrbvhKdPAA62eBjBh74GLuwoso+UXBX+MdtmG37Pi5nVnJZajcB6hedYsE/uNrBnd0DcriGmsx8Ozj+CRpl7kbnmfexMTEenWx+TLXDVheXcVhiMybBABbcuExx9OEROhVN+1iIXkjJw+Y/XkJBhLLTcH2nwQiYGmteje8x3GHX4cfgiDX9au+Rv45UbB/VvD+PPpT/AnDfzbo1xfjuCMo7Ih1qPGjDjNlElady0NfpNfB89J85Ek9535gcVdsFNbd9577TjSM8u/HdCTNAm+LqJNLvVp5JI1Uud0DB0mjwXuw1dZIpk/71fYMvc55CeLi5lVQ9btm+TLXNr1Z0RUa+xow+HyKkwsKgFlPRLiN6wAM8u2IB11iuTwy1yuRNxXf6DO++4C5kuwYVe873+fZlDebXbUMTqI/KX19vzLt5cskOmNawpsmIOIT3HNgGVOcTWh52Iiops0g5QqeGLdKz68Er+fEGkPeyl3o/W7jXnu0+O4e/pgpHTZuNg8K0QSb6Dzy3DyVkD8fTPu/HTjvP4a3804uMvOeTYxJwwMacOyseBUa0qLBUzEdmwK5QTi01OR8r5wziz+BWEIQFe5lvwoXUU0ro+gSf6N8aLHleyC6T6zkDitoWwXD4JXcop6Pu9hM2tb0YdHzGVE3Di2BF4/HYvjmV64Pvdifh+9yb0bRKIt4dGIdRLB7gW7tst0hMeO7wXXkn7YQpqjfbtu0Cldkwcuxg343VjADSw4OtgTjFEVBKtwQ0JAZ2wOC4QS9J7Y6jRIrMHidScfy+dh1e167FLLSZiG81CpGvSGlwx+OG38du8ALS/8CO+NQ7E8r1xWLw3Di1UZ/GJ7lMkqfTYEvkIho16AMFV1L3uckYuPs0Zisbq1vhy+Ch+ikQVjIGFk0nNMuHBz5dhatpMhKkS5Qy/TfLW9VIfQFL4ILx0a9sis/d6N+gsbzBlAxnxgG9kofWNmjSHMnkZVv9vBYLOGxCfngv9iRXI+nwRojUqaOr3gGtkB+ja3onFh9Lw8ZoTGJjzFyZqlsvX71xZF56DXkSzjvnTPVWZS2m5MEELq0qDLlHMCkV0LZ0nf4tX3loCc5YKJ+LT0bquDy6mZsNflSbXB4cyIxSVjkjhevdDz8Boegp9919E3fgMbD2diE7piUA2oFOM6H32E2yevQe3P/U5VFUw6/XJSxmIQSB0vpFwCYiq9Pcjqm0YWDiZhTvO40iiFZd0fgiDLee8sNG1L3TtxuDz7h2KBBWF6FyLBBV2Kq8w3DfuIYxTFPy+Lxr6pZ+K9PcwiqT4JzYi+8RG4O+PsNo8AUnWVliEvuikO412ylH4516A6o/J2BP7ONoPf1RO9lRVUvL6ivevo7DZm+g6VBodAsIicexkIv6NzQssUnJkYCGm4OjTrgXLkMpEDPwe1TE8/7livQlnTo9GzNLXZJayNhmbcHT1d2g+5NFKL9mTlzPkfcOgmp3pkKi6YmDhRI5cTMN7f/0LFfRIUjwBr1Ac8+2DDs0aYEK3sTLbR0UQgcmt7SKQ1OBXHDl1Fhd+fxOdLPvy13dWH0W0Rxv8+GhvhHoPQ2pyArbPfwmNk9fDe+cn2H5+N+rfPQOBflXTetDxwjyEay8iiVN6EZXKAPfT6K1dBs2R40CnJxGTkoUApEIvBm0zAQKVk+gWW79hM9R/4juc+HwU1MlnkLxlATY3vAPdGwVVavm22vUi3tVmIMGrcDplIqoYDCycRGJGLjZ+8Qhe1ZqxzGU4xj+/AAaNGg0qsWXAz8sDPdq1REqT+YhOysaaP39FnaRtuKVpPTxyc1foPdxs2/kHYuATX+LPBTPQ+PQ8BFzajM+/+Aj3P/ocIv0rfxbJBum70Uodi1VqWz5oIrq25q5J8FfvwelLtr8fSZdj0VqVAK1aC7gzsxpVEL07DGMXIO3zmxGiSsK3K1eie6NxlVe8VguC0w7AS23CHh+2WBBVBgYWTmLdwbPorT4AHcyo03NKlaaD9HHTy1uriSKLTOFMMnYajRrDJzyHtf+0ht/G17AjMxjfz1iHx/s1xNR+DaGtxOPVm9PlvUpnC3SI6Nr8I1sCewCvrLMyi06LY5/L5VqRQYeBBVWgiOAAnGp/J37ZeR4bYhR5kcw/b6LWCpcRD6vFAjM08AviWCGiysB0s87AaoX/ljdkUKHzi8DAXj1RXfXtNwSh/7cOqmDbBEyf/3Mcf00fgu0zbsPa3+ch+fLFin1DqwUu1iz5UKVnYEFUGnUatIJoqwiwJuKH3//ECXMIcqFHbN1BtnFYRBWowW0vYlPIvYhR/LH6SCWmoc24BLPVigTFG3X82WJBVBkYWDiBoxt+QXjqLvnY0GxQlQ6MvhFB3q5YNrUX3r+jNYa6HEAz1XkEpP+LiF3v4PLng3Hq+OGKezNjBqxW24R+Wj0rRESl4eLljxw329w2UXvfx/spfTHU+A6Uvi+zAKlSDG4RIoZ145Mla7Hh+OVKeY/M5DiI+V0T4YU6Pvw9IKoMDCxquKRMIzb9vVQ+1mlUCOpeif1TK5AYAH5np3B88J9nYb39a5wMGy67WWisRhz573RYzLYJ7crLmJkqZ1gVV1tddez5R1RajR/4FqLnU5g1Dt7Gi9Br1WgS4skCpEoxolUI5urexwL9O1i5ZXelvMeyLQfkfZbWF54uukp5D6LajoFFDSb6Pv+x7RD6qffK5+d7fwiVR+Vm1Khoer0Ojdr1wqBHZsLn/v/KzFXNjQdwYMVXFbL/jPQUeZ8FA1wZVxCVmjaoES56tZWPb1bvRcswL+hEvlmiShAR6InG9Wypzm8/+zoUc26Fv0fC5Rh5Xy+S81cQVRb+StQAyw7EYsPJBESfO5W/zJR0Dos++D98vfoADin1oA1tiR49b0ZN5h3ZCscbTZSPtYd+luMjyis7I1Xe56hc5dVXIiq9+iOeQ3zEUPi2vw3TR9jGRRFVlqDu98m/077WJEQf3Fzh+8/MtSIdbqgXVfxcTURUfryGWwNaJb7ZdBYjk1fDNP8DrPTvhZhcV7TK2IjOSMckbQymmqZg//iBgKbmN+22HTwef/+7GZsyWqLrptO4v1ejcu0v0acV7jC+hwgvNZ6AbawFEZVOaKN28taNBUZVQNdkAI55dkWjtG24fHgNItr1q7B955ot+CJ3ML7AYOzr1L/C9ktEhbHFogaYNqAhwgw50MKCholr0TtjBfxgS6HaXX0I/+kVAG+3mh9UCKH+fkju8w5WWjvhi43nYBEDJMohPccME7RQu7BvOBFRtRfRRd75Hl+MS0c3V+h4REGjVsHLVV9h+yWiwhhY1IBBzj0bBcLUagLMwz/BhZD+OOnVGX+hK9bVexIRE3/Cw0Ntf4idxSO9G8DLRYvL6bnYcSapXPtKzzHJew7UIyKq/hp1vUUm2xCXlE5sWlxh+025fBHBSEKwqxjKx36xRJXFabpC5ebmokuXLti/fz/27t2Ltm1tgw7tlfOrffnll3jkkUdQY6hUqN+uL5p0HiifDoLzEtlnRjUCXI4sRe4/64EG79/wvtzOr8V/tMuQaRWzbter0OMkIqKK1SCiLv7o9CqSt/+Ec2l10KOC9uu2by4W6n/FSt1wAEMraK9E5LSBxbPPPouwsDAZWBRn7ty5GDx4cP5zb2/vKjw6KqueES6IOLYRudF6HI1+Bs3CA2+oEF2S/sXN6j04qIQysCAiqgE69RqGrptdoEoAnsgyVUhXX3OmrfVbcfGtgCMkIqfuCvXnn39i1apVmDlzZonb+Pj4ICQkJP/m6srJcaqz9u27yUmMDDBiyf9uvDlcyc2wPdBzllUiopogxNsFDQLdoSjA1tMJFbJPJTtZ3qvcGFgQVaYaH1hcunQJEydOxIIFC+Dm5lbidlOmTEFAQAA6deqE2bNn58/GTNWTt7se3s1t6XPvvvwRsuLPlH0nFjMaxq+WD1UGDt4mIqopejTwRxgScHrJdKSmJJZ7f+ocW2Ch8/CrgKMjIqfsCiVSsU6YMEGOlejYsSPOnj1b7HZvvPEGbr75ZtlKsWbNGjz99NNISEjASy+9VOJ4DXGzS0tLk/cmk0neqpr9PR3x3o5Uv+fdiD22FCaLgtPb/ocmQx4r0+tVZzbAIi55AbAavGQUXdvKsKLU1nOworD8WH48/8pmRFA87tO/A5iBvX/NQ/c7Hi9XEWpyU8WuoHX3vaG/Y/wOlw/Lr2aXX1neV6WI2nk189prr2H69OnX3Gbnzp3YsmULfv75Z2zYsAEajUYGFvXq1SsyePtqs2bNwuuvv47U1NQyvf/ChQuv2SpCFS/u303on/kHzhiaILPlA2V6bXDiNgSe/U0+/jr0TdwU5hwpeYmIagPjkd/RPnszjumawtT6/hvfkWJF+/3/gdGiYEHIS2hXhy3YRGWRlZWFsWPHynqzl5dXzQssRGuCuF1LVFQUxowZgz/++KNQ1ieLxSKDjHvuuQfz5s0r9rWbN29Gjx49EBcXh+Dg4FK1WISHh8tjul6BVlakuHr1agwYMAA6Xe2qHG/bsQVhKychGwYcHLIYozqWfsbUQ8u/gNeeL/G3tT1Cbn8HuLCvVpZhRajN52BFYPmx/Hj+ld3Zo3ug/nU8clUGRDyzGQaD4caKMScV8R/1Qo7JiiO3/onBreuWeRf8DpcPy69ml5+oB4vhBKUJLKplVyhx8OJ2PZ988gnefPPN/OcXL17EoEGDZCuGSD1bEtGi4eLiIgd0F0f88SruD5j4MB1ZqXL0+ztCp47d8J/lt+KgUh9BB+Nxd7eGpX7tWa8O+NM8BpcUX/zUIgSrL9TOMqxILD+WH8+/mqumfX8btuyIw795wNWSgaMHdqLTTX1vbEcWPf7Q9EdWTiZu8vUqVxnUtDKsblh+NbP8yvKe1TKwKK2IiIhCzz08bJl/GjRogLp1bVckRIuGaJno1q2bHGOxdu1avPjii3j44Ydv/OoHVRkXgx6TnngJgz7agJgLaTBbrNBqSpdz4LI2FKusnTCyXR3oSvkaIiKqHlRqDZJ9W8M1YQv8/noU56P+QURYWNl35OKFL4zDkGYx4xZ3zrpNVJmcvrYloqwvvvhCBhatW7fGxx9/LMdXiHEWVDM0CvKAp4sWBmMyTpw9X+rXZeZa5L2rXlOJR0dERJUloM2Q/Mcnti6/oX38dSgOaTli6Dbgx8CCqFLV6BaL4sZdXD1kREyKV3BiPKp51GoVXvFahvbW1UjZPR5o8EKpXueRchTd1McQrOJAPSKimqhZr1H442IiPjmgQpOc9rAlIS+bBesOIhhJSIcbfNzYYkFUmZwqsCDnZQiIAlJEmqiDpX5Nq7il6KfdiuPZYjLEbpV6fEREVAlUKvh3GoUT+7cjK7r4TI7X0zxrJ17Xz0dKcBdo1HdU+CESUS3qCkXOwSuitbwPSNqLnJMbS/cic468U+uZIpiIqKZqUcdb3sekZCMtp+x5/NWmDHlfJziowo+NiApjYEE1QtO2PXAQDWC2Kji00TY3xfVoLFnyXmtgYEFEVFN5u+rwoPsWvKRdgHOnjpb59RpTprzXuVZ9unii2oaBBdUIIT6uMDcZIR9bkko3gFuT12LBwIKIqGYbaDiIvup9+Gv16jK9Toy71JltLRY6N1vLBxFV88BCTNwRHR2NY8eOISkpqSJ2SVREnchG8t4tO65UpaOx2iY51Lpw8DYRUU1m9o6S9yOTvsG/p8+U+nVZRgsaqGLkY4M7AwuiahtYZGRk4KuvvkKfPn3g7e0tMzI1b94cgYGBiIyMxMSJE7Fz586KPVqq1QIjbIGFhzkBiin7uttrLbYWC72re6UfGxERVZ6mPW7Pf5x4el+pX5dzdgdaqM6KMeDQM7Agqp6BxYcffigDiW+++Qb9+vXDkiVLsG/fPtlisXXrVrz66qswm81y6nGR6vXEiRMVf+RU69QNCcVL5gcwIfcZJNtihmvSK7bgw+DKMRZERDWZf4u+iPPrJB9nJV4o9esyjRYkwgtqFaAKbFKJR0hEN5xudsuWLXIG61atWhW7vnPnznjggQcwe/ZszJkzB+vXr0ejRrarzUQ3ykWvxWmP9riUlovolFz4eYo0siX7CnfCbM7AJE9mAiEiqukUrzAgCTCnXCz1ay57tcRdxpfRwEeDv4OaVerxEdENBha//PJLqbYzGAyYPHkyy5kqTKi3qwwsYlNz0Ca85O1Ss034NautfPykuwc/ASKiGk7vEybvVRmXSv2a9BwTFKihc+VYO6Jq2RUqOzsbMTG2gVAFHT58uKKOiahEnVxjMFazBsqZDdcspY/+Pp7/2MPAeSCJiGo6Vb3eeM08Hj8qA0v9mszMDOhhgqdBU6nHRkQ3EFj8+uuvaNy4MYYOHYrWrVtj+/bt+evGjRtXll0R3ZB2yjE8qFkB74ubrrnd5aQ0dFYdRR+PaPh7GFjaREQ1nG+dBthobY39Gb6lfk3U4S/wp/55DDetrNRjI6IbCCzefPNN7NmzB/v378d3330nx1EsXLgwP1c0UWXT+YTKe//Ug4DVWuJ2BmMi3tF9iw/d5vJDISJyAoEeLvI+LceMHJOlVK9RjLbJ8VQ6JvEgqgrass5XIdLJCh07dsSGDRswcuRInDx5EiqRy42okmlDmwP7AX1mLDKP/AX3lkOL3c5qss1hoWj0/EyIiJyAl4sGA7T74WlNRUJKV9QN9L/ua1SmLNu94drJPojIAS0WQUFBOHDgQP5zf39/rF69GkePHi20nKiytG7dATuU5rAqwMH9u0rczmrOm+dCa7vCRURENZtKrcbTul/wmPZ/SL1UypSzeXMeqfRM4kFU7QKLBQsWyOCiIL1ej59++kmmlCWqbGK8hGekLduTObPkWd4Vk9H2gC0WREROI1vrI+/Tk0uXGUpttrVYaAycKJWo2nWFqlu3bonrunfvXhHHQ3RdBs8Aea/KLjmwgNk2g56KLRZERE4jV+8L5MbiYmzR7JTF0eS1XmtdGFgQVYUKycOZk5Mju0LFx8fDetWA2hEjRlTEWxDl03kHyZlUUyzXyPZkzmux0LErFBGRs1BcfYF0IPXAn0i95V54u+quub3GYmux0LmwKxRRjQgs/vrrL9x3331ISEgosk4M6LZYSpe5gai0LJE9cec6V7TSeWNYCduoLLYWC7WWg7eJiJxFo0ZNkBq/Gb3UB3AxJhreDetfc/vD+jZIy4iHj1vpU9QSURVOkHe1KVOmYPTo0YiNjZWtFQVvDCqoMtjnpUjKzGuVKMa/ljr43HwrcprewQ+BiMhJBPR+BHqtreqSlXTxutvPd70PL5kfhNar8PhQIqqmgYXo/vTUU08hODi4Yo6I6Dr83W2tEAkZuSXOn3LK5I8l1l6wNryZ5UlE5CxcvHDS0AJnlRCk55iuu3mm0dZrwk1fIT2/iaiyA4tRo0Zh3bp15d0NUan5e+gxS/cFvla9jcyUoplBzBYrzCIfrfgN0mpYskRETmRR2HN40PQMovXX7gYlJlHNzbXNaeRu4G8BUVUodwj/2Wefya5QGzduRKtWraDTFR5I9cQTT5T3LYgKEVeeGqpj4aFkIT0lER6+IYXW55qtCEEiAlSpcMm5BLiHswSJiJyEr5ut1TrlGt1hpYw4zM16HOl6PTT6jVVzcES1XLkDi4ULF2LlypVwdXWVLRcFZ+AWjxlYUGXIUbvBw5KF7IzUoutMFgzV7MA9mr9hOJgF9HmOHwIRkZPwdrNdwEzJvnZXKGNOlmy9NkMDL3aFIqoZgcVLL72E119/Hc8//zzU6nL3rCIqFaPaHbAkIKe4wMJshR4miBhXzXSzREROpVP6GnTV/RfJF3oDeKPE7b5ddwSDxG8C9HBjVyiimhFYGI1G3HXXXQwqqEqZtW6ACTBmFt9iYcgLLKC5xlwXRERU43ipjfBXxSM769qzbyel2H4fchVdfvcpIqpc5W5iGD9+PH7++eeKORqiUjLrbJMdGbOKBhbGnGyM0GyBGipAy8CCiMiZ6N195L3WmHbN7RSTbT6jhnWCoFFf6aZNRNW4xULMVfH+++/LcRatW7cuMnj7gw8+KO9bEBU97/ICC3N20R8WdexeeS9bLDxDWXpERE5E72ELLJoZDwAJJ4CARsVvmBdYqHS8wERUYwKLgwcPol27dvLxoUOHCq0rOJCbqCKZDb5IgDeyzEUb3cy5WfLEludfowEseCIiZxLSRt5ZxTxG57eWHFiYbYEFdK5VeHBEtVu5A4u1a9fCkaKionDu3LlCy5577jm8++67+c/Pnz+Pxx57DP/884/MXjV27FjMnDkTej37XNZU+8PvxTdnu2OiTz30v2pdLnRIVAKQqKuPcDVzlxMRORNX3xD8bu2GEaqtoj9sidvFWz2w1docPfybV+nxEdVmTjEVpchKNXHixPznHh62bjL2rlrDhg1DYGAgNm3ahMTERDkuRMzY/OmnnzroiKm8vFxsXe7Sc8xF1iX4dcDDphfQztsHt7OoiYiciqeLFhmKC8Q8qNbcjBIHi+6xNsEf5ggsbd29io+QqPZyisDC09MTISGFJ0mzW7VqFY4cOYLo6GiEhYXJZbNmzcKECRPw1ltvwcvLq4qPlirqhwVQcPPJd4CU9wGfK5PgGS1Wea/TMP0xEZGz8TBosdnaEnGKH96JuhlXLiUWzRAouOrYck1UVZyi5vXee+/B398fbdu2lcGCSIFrt3XrVrRs2TI/qBAGDRqE3Nxc7N6920FHTOXl667HberNqJ+5F6f2rS+0zpQXWOgZWBAROR0XnQYn1fXxh/UmpHk3LXG7bJOtRdtF5xRVHaIaoca3WEydOhXt27eHr68vduzYgRdeeAFnzpzBt99+K9fHxcUhODi40GvEtmJ8hVhXHBF0iJtdWpot85DJZJK3qmZ/T0e8d3XVvb4vktSn5OPYhEREFCgb//Or8K1uPuIzOsNkai+XsQzLh+XH8nMknn8sv6u5GzQwZlmRnJGNQPeiVRnR3fkB6xIM12+F94FHYOoxieegA/E7XLPLryzvq1LEt6+aee211zB9+vRrbrNz50507NixyPLFixdj1KhRSEhIkK0YDz/8sBzcLdLhFiQCi/nz52PMmDGlfv+FCxfCzc3thv5PVPHMh35B29xd2O09CIaG/fKXG0+vR/vkFdir7wBdqztZ9ERETmbWnlz4Gy/izgYK3ALrF1lvtgJpu39EL/UBJNUdgIvBV6f5IKLSysrKkomPUlNTrzuEoNJaLMSYhldffRXfffddmV87ZcqUYiv8V2eDKk7Xrl3l/cmTJ2VgIcZebN++vdA2ycnJMvq6uiXDTrR6PPXUU4VaLMLDwzFw4ECHjMkQx7p69WoMGDCgyDwhtdk/MeuBOCDI3wfdhw7NX77jl8NAMuDm6YsBectZhuXD8mP5ORLPP5bf1dafnIvHUmfDy9IYPkOnFFmfcfE4kvYekI9bt+mAtu2v/EbwHKx6/A7X7PKz99wpjUoLLJKSkjBv3rwbCiwCAgLk7Ubs3WubHC001DYxWrdu3eS4i9jY2PxlYkC3wWBAhw4dit2HWCduVxMfpiMr9o5+/+pGpbe1HqksuYXKRaXYBuypNEXLi2VYPiw/lp8j8fxj+dmpDbYh2ypTdvG/i6nnbetFD4XgRlBV0G8nz0GWnyPpHFQPLMt73nBg8fvvv19z/enTp1HZxMDsbdu2oW/fvvD29pbdo5588kmMGDECERERchvRytC8eXOMGzcOM2bMkAHPtGnTZHpaZoSq2dT2SY9M2YVXWPL6AmoYhBEROSOtiy2wSEpOQnGXIY25tsnxLqiCUT+K6WaJqsoNBxa33XabnNn4WkM0KnvmbdGq8PPPP8vxEGKwdWRkpAwYnn322fxtNBoNli9fjsmTJ6N79+6FJsijmk2lLz6wsJrtgUWNz01ARETFqBcWBJy3tVikZObCx71wLwOz0RZYxKsDWX5EVeiGa16iW9Hnn38uA4zi7Nu3r8SuRhVFZIMSLRbXI1ovli1bVqnHQlUvzacF5loGI8i1JXoXXGG1BxZFu7MREVHN93D/Vji9TeTMtyI9M7NIYJGtdsdxJRzxmuLnuCKiynHDyZ1F0LBnz54S11+vNYOovHL9m+EHywDs17YptDwbLkiEFyw6dxYyEZETUuncoFHbekXkZmcUWX85qDsmm/4Pi11HOeDoiGqvG26xeOaZZ5CZmVni+oYNG2Lt2rU3unui63LV22ZTzTLaBmvbbQocg3knu+HxkIYYznIkInI+KhVMKj3UyEVOVkbJs27n/U4QUTUPLHr27HnN9e7u7ujdu1AHFaIK5aE2o4EqBr7Z6SLRcP5yo8XWUqbjzNtERE5rscsduJiai3uUvPF2BeSabYGFQcvAgqgqcXQr1Vj+2afxte4DpKSL+UiuzHtisljlPQMLIiLntc3jZuxLTsEtKDpxbejxH/GTbjEO5QwAcJNDjo+oNmJgQTWW3sU2hkJntWX/sOtzaR566w5DnT4RQAMHHR0REVUmt/zusOYi69S5KQhSJcNdbeSHQFSFGFhQjaV3tQcWhX84/HIvIFh1DuetRfvdEhGRc4hSxSFLdQ7mjLoA6hRap5htvwuKmvMZEVUlBhZUYxlc3SF+OvRKLiAykOXNm6K22q5eqbR6Bx8hERFVltvTfsCDukM4cdkHQOHsgDDn2u75O0BUM9LNEjmaS16LhUqxQrHPti2f2wILNX9QiIiclqJ1kfdWY+FJUgsGFirOZ0RU8wKLjRs34t5770W3bt0QExMjly1YsACbNm2qiN0TFcvFYJsQSeSAys29Ms5ClddiwcCCiMh5KVpbNihLcYGFJa+LLC8wEdWswGLx4sUYNGgQXF1dsXfvXuTm2q4SpKen4+23366IYyQqlk5vu1olGE1Xxllo8mbe1mjZt5aIyGnpbIGFco3AQqUtPCM3EVXzwOLNN9/E7Nmz8c0330Cnu1KRu+mmm645MzdReel1Oiy03Iz5loEwKldylasVW2Ch1XGMBRGRs1Lp8rpCmbKKrEvT+uOcEgyL3ssBR0ZUe5V78PaxY8fQq1evIsu9vLyQkpJS3t0TlUitVmE+hsFkUTBJdaX1Igsu0MAF6rwfHSIicj5qXd78Faa8gdoFrAqZiPlnzuFxv4ZVf2BEtVi5WyxCQ0Nx8uTJIsvF+Ir69euXd/dE16TPm13bPime8IrL8xhhfAsm/6YsPSIiJ6W2d4c1F+0KZTRbC/1GEFHVKPc3btKkSZg6dSq2b98OlUqFixcv4scff8S0adMwefLkijlKohLU1SQjShULU86VpnDRgiFw5m0iIueVHtQB31iGYY+2bYmBhUHHwIKoRnWFevbZZ5Gamoq+ffsiJydHdosyGAwysJgyZUrFHCVRCd7Gp/DRJcGa2BKoE1io9YJXqoiInFduQCssshjRTiPmsShszIU3MFyXgOSc6QAaOOT4iGqjCpkg76233sKLL76II0eOwGq1onnz5vDw8KiIXRNdk0VlO4UteTnLD19MxdTMT6DVWeFqagnAmyVIROSEXHQaqGGFYswCxEzbBVLL+hlj4a9KQqbGNnEqEVWNcrURmkwm2VJx/PhxuLm5oWPHjujcuTODCqoyVpUtE5k5L93sr7svoK36FNqpTiDAjT8oRETOyqBV43XtXHya+gRwbHmhdfnZAfVMN0tUYwILkV720KFDcmwFkSNY1LbAwmLMze9Xq4EVni5a+HjkZQwhIiKnbLEwQicnSZUtFgXY5zPS6hhYEFWlco9quu+++zBnzpyKORqiMrLaA4u8FguLxSqbxnWi+VvFQXtERM4eWFhFZGEpnHJWrZjlPeczIqphYyyMRiO+/fZbrF69WnaFcnd3L7T+gw8+KO9bEJVIuWqMhcVqkfcqqAB1hQwhIiKiatoVKhdaKIoC5P0GSFYLVIotiYdOz4lSiapSuWteoitU+/bt5WMx1qIgdpGiqmqxsOa1WCgW21UqEVdAfWU2biIicsIWCyWvK5TF1vVJsppty9hiQVTzAou1a9dWzJEQ3YCjbh2xLdUX7VzqyufWvBYLScXAgojIWbno1DBBA9FgYTHlIP8vvmJFHAJgVkwwsMWCqEqxrwjVaPu8+2HlhRZ4072hbYHVIvvcyqCCLRZERE7LoLWNsRDMptwrgYXOFY9rX0VcVg6WGZjEg6gqcXQr1Wh6rabQLKuZcMEQ47tY1nMpoLH94BARkXOOsTijhGKDtTWMPnkXl/ImSY1Ly5GP9VpWc4iqElssqEbzRDaCkAzkpsrnFpkeBNCqmQKZiMiZqdUqbFW3w3pzGwxs0A+eecu/WHsqfxt3A6s5RFWJ3ziq0fol/xcP6v9CdMw9ANrCnBdYaBhYEBHVilYL0WKdY7oyvi4jIRrf6GbBrPNAHZ9hDj0+otqGbYRUo6m0eakE8zKCuJpS8Lb2W7Q78q5jD4yIiKokMxSgIDf3ygR5alMW6qsuop1HEj8BopoWWCQmJuY/jo6OxiuvvIJnnnkGGzduLO+uia5PYwssFIvtR0VryUEX9VEEJO5m6RERObm+6j1Yo5+G4HVP5y9T8mbdVjiXEVHNCSwOHjyIqKgoBAUFoWnTpti3bx86deqEDz/8EF9//TX69u2LpUuXorKJYxDzZRS8Pf/884W2uXq9uM2ePbvSj42qgH2Adl5gkZ9ulqlmiYicnsp+cclUYII8+5wWefMcEVENCCyeffZZtGrVCuvXr0efPn0wfPhwDB06FKmpqUhOTsakSZPw7rtV0x3l9ddfR2xsbP7tpZdeKrLN3LlzC20zfvz4Kjk2qpofFXtgobLmTZDHK1VERLWmO6y91dr2mC0WRDVu8PbOnTvxzz//oHXr1mjbtq1spZg8eTLUalus8vjjj6Nr166oCp6enggJCbnmNj4+Ptfdhmruj0po5r+FWyzyzkMiInJeKo1B3sclpSHQvtBiv8DEFguiGhNYJCUl5VfUPTw84O7uDj8/v/z1vr6+SE9PR1V477338MYbbyA8PByjR4+WYzz0V822OWXKFDz00EOoV68eHnzwQTz88MP5QdDVcnNz5c0uLS1N3ptMJnmravb3dMR7V3ci64egS7+A+H+3XblSpdIUKi+WYfmw/Fh+jsTzj+VXoryLSynpmXIAt0hBa7V3jVVpK+x3k+cgy8+RTA6uB5blfcuVblaMVbjW86owdepUtG/fXgYyO3bswAsvvIAzZ87g22+/zd9GBB0333wzXF1dsWbNGjz99NNISEgotsuU8M4772D69OlFlq9atQpubo6bxXP16tUOe+/qKi7HD0vNo7HP2gC3bL6AzHRbEJianokNK1YU2Z5lWD4sP5afI/H8Y/ldrZmL7W++XmXGshV/QsyHl5iciiR4Qp1hxu5ifgd4DjoOv8M1s/yysrJKva1KURRb4v8yElf7hwwZAoPB1gz5xx9/oF+/frLlQhBX/P/66y9YLFdyS5fWa6+9VmzF/uquWB07diyyfPHixRg1apQMHPz9/Yt97axZs+S4DDEepLQtFqI1ROzTy8sLjogUxck0YMAA6HRs2r3a6K+3Y190Kj4d0wYrVq/EtPQZ8AurD48H/8cy5DlYLfA7zPLj+Vc5jPGnEPfVbUiHGyKf3QwPgxZ3f7sDu86lyN+EwS2CK+R9+B1m+TmSycH1QFEPDggIkPXm69WDb7jF4urBz/fee2+Rbe67774b2rfotjRmzJjrZoMqjn1cx8mTJ0sMLMQ2opAuXbqE4OCif3REsGQPmAoSH6YjK/aOfv/qyqDV5IXJahxTN0B/4wws6t8ZXYopK5Zh+bD8WH6OxPOP5Xc1tZc/dlqbyMAiQqWR54jZalvnoq/430yegyw/R9I5qB5Ylve84cBCZFmqLCIqErcbsXfvXnkfGhp6zW1cXFzkgG6q+boaN6OV5jTcU91hsSpQoIaWARgRkdPTeAbiResk+bd/hMUWUZittnutpuq7ZxPVduUaY+FoW7duxbZt2+ScGd7e3rJ71JNPPokRI0YgIiIiv4tWXFwcunXrJsdYrF27Fi+++KIcvF1cqwTVPO1ydiJcsx/xaZ1httg+dw2zQhER1Qp6jRrZVguMeU0VrXL24GHdn4g8fjPQ5BlHHx5RrXJDgcVTTz1V6m0/+OADVBYRGPz8889yPIYYExEZGYmJEyfKOTYKNt988cUX8pitVivq168vx1c89thjlXZcVLUUle00VqwWRJjP4SHtnwg+/C8QfmUmViIick46jQrZJsCY12LhZUlCC9VZuGbFOPrQiGodbXm6G9nt3r1bDtJu0qSJfH78+HFoNBp06NABlUlkgxItFtcyePBgeSMnltc6oVjM8FGy0Et9AO7xHItCROT0zEb8gmeh0ptgyf5bJMDPnyhVpanRnTKIaqQb+taJ7kQFWyTEBHXz5s2TKV8FMfP2/fffj549e1bckRKVQMxZYZ8cT6XYJ0bKG9BNRETOS62Fi8oIMxTk5OXaV1nz7jWF57MiospX7umJRepWMe+DPagQxOM333xTriOqdHmBBcRVqryZt1UMLIiInJ9aLRN2CGaTLU28vcVCzcCCqOYFFva0rVeLj4+vspm3qZbL6wolWyzsgQWbwImIagVL3jg7c16LhTqv5VqlZZdYohoXWNx+++2y29Ovv/6KCxcuyJt4/OCDD2LkyJEVc5REpRi8LVorFCUvsLC3YhARkVOz5gcWRnmvtrdYMLAgqnLlHtk0e/ZsTJs2TU6QJ2YGlDvVamVgMWPGjIo4RqJr2howCm9fbIe7/TtArfwOqNhiQURUW1hVGnmV1B5YGBU1smCAn9bF0YdGVOuUO7Bwc3OT6VxFEHHq1CkoioKGDRvC3d29Yo6Q6DoyDYE4peQgW+Mlcs7KZRxjQURUu1osrGZbYPGteShmW4dgW4ebHXxkRLXPDQUW58+fz5+Azk4EEq1bty52+5iYGNSpU+fGjpDoOjRq2+yqJosVKyyd8belHbb2vRmuLDkiIqd31tAImTlJ8IZOXtw0WxW5nDNvE9WQMRadOnWSE9Ht2LGjxG1SU1PxzTffoGXLlliyZEl5jpHomuplHcK9mtXwTzkAK9TIgQFqgxtLjYioFvjZ/zFMMz2CFEMdmLNS0Fp1Cg1UMdDlJfYgomreYnH06FG8/fbbcuI5MbN1x44dERYWBhcXFzmHxZEjR3D48GG5XHSRGjJkSMUfOVGeepn70EfzF06liu53N8ll2rxWDCIicm46jS2AMFkUWGMP40PdFzih1IVW84CjD42o1rmhcN7Pzw8zZ87ExYsX8eWXX6Jx48ZISEjAiRMn5Pp77rlHzsa9efNmBhVU+dS2+NhiMaOr+gie1S6C7vgfLHkiolpAr7UHFlaYzba5LCxQsSsUUU0bvC1aKERKWaaVJYfKmwxPsZhRXxWLQeqd0MY1BFrdzg+GiMjJ3Rs/Ew/rjyL68guweHnLZRZo2BWKyAHYAZFqvrw5K8QEeWrkZYXScB4LIqLawEXJhQeyYTXnwGox5wcWanaJJap56WaJHM2eWtZqscgTWiXmscjrHkVERM5NUdtm2FbMRtkl1j63BRFVPda+yGkCC8UqrlHlDdrOW0ZERE5OkzePhcUMS94keQoDCyKHYGBBNV9e64RiNYvGb1towR8VIqLa9RtgYYsFkaMxsKAa70Jgb8w46IY6hjA0wF+2hWyxICKqHexdoSxmZPs2wbeWocjQhuBORx8XUS1UIYGFyWRCXFwcsrKyEBgYKNPRElWVXNdAHFaiAMULLkoAdqpaoh5bLIiIageNXt5ZzWZkeTXAT5abEaJ1cfRREdVKN5wVKiMjA1999RX69OkDb29vREVFoXnz5jKwiIyMlDNz79y5s2KPlqgY9snwcs1W/G7thkvqICCkFcuKiKgWyHQNw1ElEulqDzmXhaDVcJJUohoTWHz44YcykPjmm2/Qr18/LFmyBPv27cOxY8ewdetWvPrqqzCbzRgwYICcnds+cR5RZfDJPodRmvVombtHDK7AQs2tQP3eLGwiolrgWOTdmGJ6AvvdukHJuIxGqgsIVqU4+rCIaqUb6gq1ZcsWrF27Fq1aFX9VuHPnznjggQcwe/ZszJkzB+vXr0ejRo3Ke6xExQrIOIZHNb/jmKkxDqvc4KNyZ0kREdUSOo3tGqnZosD77J+YrfsS28w9AYx09KER1To3FFi8/PLLaNGixXW3MxgMmDx58o28BVGp2eesqGc9j9m6D5FgDhFzsbIEiYhqAXu3J9ENSqScFWGGwgQeRDWnK1S7du2QkJAgH9evXx+JiYkVfVxEZZ7HQqNY5L0iZsgjIqJaocmFJfhZ/zp6Jy+GYjHZFnKSVKKaE1j4+PjgzJkz8vHZs2dhtdoGSxE5NLCAbcZV5cZzEhARUQ2jU3IQgFS4WDJki4XEwIKo5nSFuuOOO9C7d2+EhoZCpVKhY8eO0GiKn+n49OnT5T1GomtSa2w5zFWKAsX2iCVGRFRLqPJ+A2A1y4lSbQt5gYmoxgQWX3/9NUaOHImTJ0/iiSeekKllPT09K/7oiMrQYmELKtgVioioNgYWXbPXI8M4TD5W8ibNI6IaMkGeSCMr7N69G1OnTmVgQQ6jvqq1jF2hiIhqD4tbUP5j36S9SBcPOHibyCFuqK3w/Pnz+Y/nzp173aAiJibmRt6GqFSy/JrjWdPDmGuxBbvg4G0iolojtY5t3iJFAS77tMUPlv6Idmnq6MMiqpVuKLDo1KmT7P60Y8eOErdJTU2VE+i1bNlSTqBHVFkUVz/sVppgndX2g7JR34OFTURUS2h1ehxQ6sMCNWJ92mOuZQii3a+fEp+IqklgcfToUXh7e8vuUMHBwRg2bJgMNB5//HHce++9aN++PYKCgvD9999jxowZcnllWr58Obp06QJXV1cEBATI8R9Xt7DccsstcHd3l+vFuBCj0Vipx0RVR6u2Dda+oATKH5SNBs66TURUm34DnjRNxv3un+G8bzfbsrxJ84ioBoyx8PPzw8yZM/Hmm29ixYoV2Lhxo0w7m52dLSvu99xzDwYNGiRbKyrb4sWLZVDz9ttvo1+/flAUBQcPHsxfb7FYZOATGBiITZs2yTk3xo8fL7f79NNPK/34qPIZjEkYrt6KLBjwj7U91OwKRURUa9iCCJWceVuXfQnhqkvwUHwcfVhEtdIND94WXFxcZOvA1S0EVcVsNsuB46JV5MEHH8xf3qRJk/zHq1atwpEjRxAdHY2wsDC5bNasWZgwYQLeeusteHl5OeTYqeK4ZcfiSe2vSIYnTprqIMCebpCIiJyeLm/mbbPFijZn5uB73UZsz5oIoLujD42o1ilXYOFoe/bskQPD1Wq1nA08Li4Obdu2la0pLVrY+ldu3bpVtpzYgwpBtKbk5ubKjFZ9+/Ytsl+xTtzs0tLS5L3JZJK3qmZ/T0e8d01gycsz64t0zNW9jwtZTWAyDS20DcuwfFh+LD9H4vnH8rsmqxWjNevQxXgWdZOPIVksUmsr9DeT5yDLz5FMDq4HluV9VYroE3QDtm/fjqSkJAwZMiR/2fz58/Hqq68iMzMTt912m+xqZDAYUFkWLVqEu+++GxEREfjggw8QFRUlWyNEK8Xx48dll62HH35YdtMSywoSxyXGgIjXX+21117D9OnTiyxfuHAh3NzcKu3/QzcmKzEanc9+lv/8lKY+sttOYnESEdUCcVmA5vBPuFmzD64aBZlmFf7wuBP1mnRw9KEROYWsrCyMHTtWJma6Xk+fG26xEJXvPn365AcWYlyD6I4kuhg1a9ZMdk8SrQRiuxvZd3EV+4J27twJq9UqH7/44otyNnB7+tu6devil19+waRJtsqlmB38aiKeKm658MILL+Cpp54q1GIRHh6OgQMHOqTrlIgUV69ejQEDBkCn46Q/Vzt9ZA9w9spzvcGAvkOLtliwDHkOOgrPP5afIzn7+Xc2MRNrDv8iH+v0esBsQnBIGIZe9TtQHs5ehpWN5Vezy8/ec6c0bjiw2LdvH954441CrQciM5NIMSuIirhovbiRwGLKlCkYM2bMNbcRrRPp6XIaHDRv3rxQS0T9+vXz59oICQmRrSsFJScnyw9JZLQqjthHcS0t4sN05B8UR79/daV3cYEtxLRTl1hOLMPyYfmx/ByJ5x/Lrzguej3M9iSXeX0w1JX0e8lzkOXnSDoH1QPL8p43HFiIynnBivn69evzZ+O2z3UhBkzfCJFZStyup0OHDjIAOHbsGHr0sM1dIAIG0fUpMjJSPu/WrZscpB0bG4vQ0FC5THSLEq8TryfnmHm7YGChqJhmkIiottBp1DBDI2MKe99utZoX4Ygc4YZrYCKoOHPmjHws5oQQA6lFJd5OtCZUdlQluiU98sgjsmVEBAsiwHj00UflutGjR8t70X1JtGiMGzcOe/fuxZo1azBt2jSZopYZoZyDRn1VfMx0s0REtYZWo4JJ0cqZt5W80EKl0Tj6sIhqpRtusRCtE88//zzee+89LF26VA5q7tmzZ/76AwcOoEGDBqhsYiyHVquVgYOYR0N0x/rnn3/g6+sr12s0GjmB3uTJk9G9e3c5iZ4YgCIyR5GT8AjEy+b7cbN6L/qo98l85kREVDvo1Go567ZghhaLLTchzO1KJkgiqgGBhZgcT8xf0bt3b3h4eGDevHnQi0FTeb777jvZWlDZRKuICBKuFSiIrFHLli2r9GMhB9G5You1JRIVLyQo3nB3rY+iSYSJiMhZWyxEVyhhh3s/fJF6M15wj3D0YRHVSjccWDz33HNy1m2RmUkEFqJloCCRlUksJ6psGrWtheKYEoFjlgj0cg9koRMR1aLAYq5lML63DEIPjxAACXmzcRNRVbvhb55ooRBdj7y9vYsEFYKYQ6JgCwZRZVGbc9BfvRsD1Ltsz9kTioiolnWF0sAFRnRIXY1AJEOvMjv6sIhqpRtusbjBefWIKpzGnIUXtAvl4/3GBnC3chJDIqLaQq1WyQtKI9RbMTLjLwzVW3HI+B2ARo4+NKJa54YDC6GkCeaIqpJafaXh7Sf9mzib2gXgKAsiolqjq+Y4HlSvgFVR44wSAqNnuKMPiahWKldg0bhx4+sGF0lJSeV5C6Lr0mgKn8YKs0IREdUqkZoEOYmF6E2xztoWHTnGgqjmBRbTp0+XYyyIHEp91RgfTpBHRFSrKOJ3wCICCyBbMcgB3URUwwKLMWPGICgoqOKOhugGaIpcmeIPChFRbWJV2SbktSoKcqCHtkAXWSKqOjf8zeP4CqqOYywktlgQEdUuatt1UtFikQMddGyxIKpZgQWzQlF1oS7SFYotFkREtUpe2nuRrzIboisUWyyIHOGGv3liYjx2g6LqQK3R423zWJxQ6toWsMWCiKh2yesKdUEJxC5rE+g4oRFRzRtjQVQdaLRarLF2QIrigZ6ag/BybeboQyIiIge0WGTIafJ0bLEgchAGFlTj2S9M7VaaYLe5CUZ61XH0IRERURU66doGtya+AVNetYZZoYgcg4EF1XgikUAP9UGoYcU2a3MmFiAiqmUeH9AMsUt+xOUsM9b7jUaTYE9HHxJRrcTAgpzCq7r5UCtWPGSaBr0S5ujDISKiKtS3UQDgsRuKOzD1wRmAgdUbIkdg2gRyCvbZtr/VzUS/hIWOPhwiIqpKyWeuJAXUubLsiRyEgQU5BaXgqcxsIEREtUtG/JXHWhdHHglRrcbAgpyqxUJiulkiotrFYrzymLNuEzkMAwtyCpZCpzInyCMiqlWCmGacqDrg6CZyCopopVCuZIkiIqJaxCMIGLcUMDAbFJEjMbAgp8CuUEREtZxPuKOPgKjWY1cocgrfqe9AOtyutF4QERERUZViiwU5hY3qzkg1W9BFfRTervUcfThEREROz2KxwGQyXXc7sY1Wq0VOTo58DZVNZZefTqeDRqOpkH0xsCCnoFED/1jby9tEXwYWRERElUVRFMTFxSElJaXU24eEhCA6OprjIG9AVZSfj4+PfI/y7p+BBTmF5sopRKrScUSJhJqDt4mIiCqNPagICgqCm5vbdSujVqsVGRkZ8PDwgJrpgMusMstPBC1ZWVmIj7fNBRMaGlqu/TGwIKcwxTIfPrpEPGV6FGo0d/ThEBEROSXRFcceVPj7+5e6Ymw0GuHi4sLA4gZUdvm5utpmqxfBhfhcy9MtioEFOQUrbF+CD3Rf4swl0TTbwtGHRERE5HTsYypESwU5D7e8z1N8vuUJLJg+h5yOilmhiIiIKvm3lnNGORNVBX2eThFYLF++HF26dJFNOQEBARg5cmSRwrr6Nnv2bIcdL1U8q6pAdM3AgoiIiKjK1fjAYvHixRg3bhzuv/9+7N+/H5s3b8bYsWOLbDd37lzExsbm38aPH++Q46XKUWjuCl5FISIiohIGnj/++OOoX78+DAYDwsPDccstt2DNmjVyfVRUVP5FaHHBumnTppgxY4Yc5Gx39uxZuX7fvn2Fnmu1WsTExBR6P1HnFMvFerHd1QYOHCi7Hm3btq3Yz2vv3r2488470bhxY9ldSdxPnDgRx48fr5afb40OLMxmM6ZOnSo/8EceeUQWdpMmTTBq1KgS02jZb/aBKuQsCjThscWCiIiIriIq9h06dMA///yD999/HwcPHsRff/2Fvn374rHHHsvf7vXXX5cBwdGjRzFt2jT85z//wddff33d8gwLC8P8+fMLLZs3bx7q1KlT7Pbnz5/H1q1bMWXKFMyZM6fI+mXLlqFr167Izc2V73/48GEsWLAA3t7eePnll6vl51ujA4s9e/bIyFCMkG/Xrp1MkTVkyBBZ8FcTH5roJtWpUyfZDUqMsCfnYS1wKnOMBREREV1t8uTJsuVgx44d8iK0uCDdokULPPXUU4VaDDw9PeVFaNF68dBDD6F169ZYtWrVdQt0/PjxsodMQd9//32JvWTEtsOHD8ejjz6Kn3/+GZmZmfnrRApY0Rtn6NCh+N///oc+ffqgXr16suv/zJkz8dVXX1XLD7hGZ4U6ffq0vH/ttdfwwQcfyBNg1qxZ6N27t2wi8vPzk+vfeOMN3HzzzbKVQjR1Pf3000hISMBLL71U7H5FZChudmlpafkj5Uszw2RFs7+nI967plhlGIhxxm/lYwVKkbJiGZYPy4/l50g8/1h+jsZzsHBZiG5B4gKt/SKteJ5tKnlGaLneaIEm11Thg75ddZpS7TMpKUm2Trz55puyPnj1BWYvL69C/x/xWNyvX79etlw0bNgwf33B+4LlMHz4cHnxesOGDejRowc2bdok33fYsGGyLnp1mYnA4tNPP5UBjrgtWrRIBhPCn3/+KeuqosXE3g3LflxXH29FsP9/i8sKVZb6Z7UMLESgMH369Gtus3PnzvwCffHFF3HHHXfIx+JDqlu3Ln755RdMmjRJLisYQLRt2za/maukwOKdd94p9v1FtOrI9GqrV6922HtXd2tymiLVfBvaqE8hLcGKjBUrit2OZVg+LD+WnyPx/GP5ORrPQcjxAuJqvpiwTcytIIigodsHxY8RqGxbn+oKV/3106OKcbii4hwREZF/wbg4om75/PPPy65G4v8nKtVi/ogHHngg/3Xi/y6IFgaxzP7caDRi9OjRstuSaOUQ9+K5vZzEdvZ9rF27Vr6+W7ducpmox37zzTf59dlDhw7Je9GNKj09XT6231cGcYzZ2dkyKBJDDQoSrSc1OrAQ3ZbGjBlzzW1E64S9gJs3vzIhmhiIIwbkiH5rJRH91cSHeOnSJQQHBxdZ/8ILL8hmMTuxrRjcIwbYiAixqomTWvwxGzBgAHQ6XZW/f00w5/w2/JbZE79Ze+KZ1o0wtGe9QutZhuXD8mP5ORLPP5afo/EcvCInJwfR0dFyFmhR4Ra0xsIV0ark6eUJN/31q7P2C8Pi/lp1OdG9XrQSiO5Lly9flgGGGIMh6mB24v8uuLu7y30VfP7II4+ge/fucgyH6MIkkgrZK+piO/t7i9aJu+66K793zYQJE/DKK6/IsR1ivLCoz8r/n6envIk6r7ivrDS/4nMVLTm9evXK/1ztrhWI1YjAQoyFELfrEQNwRMEfO3ZMNjnZv/xicE5kZGSJrxMj7EWhiQHdxRH7tH+gBYlKvSMr9o5+/+osXLkIqC7hnBIMnVZTYjmxDMuH5cfycySefyw/R+M5aJt5W1RuRQXcPgu0u0GHI68PumYrQHpaugwCKnrm6NJ2hRKVdbGdqDNe7xgCAwPzuyeJ7KOiG5RoWejfv79cb3+9vQwKPm/durXMJHXPPfegWbNm8rk9e5R9W9E9SgQdos5acPoDUbZiTMZ7770nj1cQXfvFuArBXu6VQexX7L+4c7wsdc9qGViUloj6RGT46quvyhYFEUyIDFGCaHoS/vjjD5laTJwQIhITTU+i69TDDz9cbPBANdNdWQtRR3cM0833Qa3q5OjDISIiqjVEhfRarQYisDDrNXKbyqoYX49oGRg0aBA+//xzPPHEE7J1oaCUlJRiLzj7+vrK9LSiFUNcmC5NEPPAAw/IgeJffvllset//PFH2W1/6dKlhZaLccCiO/5bb70le8mIi+yi5UMEN1cr6XgdrUZnhRJEICG6TYm5LETGp3Pnzsk0YuJEsEdZX3zxhQwsRNT48ccfy/EVYpA3ORPbqfyqdj4aXPrT0QdDRERE1YyoD4pWgc6dO8vK+okTJ+TA7E8++UTWE0siUtGKlo7iKvjFmThxouxGJTJKFUeklhVZqVq2bFnoJgISETCIiZ9F4PPtt9/Kx7feeivWrVsne+Ts2rULzz77rLywXh3V+MBCBA4i7ZYYLyH6gImxCCJ1mN3gwYNlhCn6polBMiJnsZj7Qgw+IuecIE9VcE4LIiIiIkCmaxVTFYgxEyJDqKjMi7EToqWgpNYFe9cocQFbJBcqTSYmrVYrWxuKq2vu3r1bDiS3D9IuSIyhEC0V9jktRECxZcsWWdcVwYoYU3z33XcjNTVVZreqjli7JucLLDjzNhERERVDzHn22WefyVtxipsdWyg4QZ5IIFRwJu6rn19NZCS1r7/etr///nuh5x07dsSvv/4qL56LIQCO6kpWWtX76IhK7Uorhaqaf+mIiIiInBFrYOQUFFWBHNYFWi+IiIiIqGqwBkZO2BWKpzURERFRVWMNjJzCPvfuV54wsCAiIiKqchy8TU7hiFtnpFv6o6kqGgEGf0cfDhEREVGtw8CCnIJGDcy1DJGPZ/i3dvThEBEREdU67ApFTsHXkoBGqgvwRRrUTDdLREREVOUYWJBT6J+6GLN1H+JmzV4w2ywRERFR1WNgQU51Kj+q+R3Bl7c4+mCIiIiIah0GFuQcCnR/uvKIiIiIqPwmTJiA2267jUV5HQwsyDkUmseCoQURERFRVWNgQc4XWKgLzMJNRERERFWCgQU5BUV1JZhgiwUREREVqSsoCt5//33Ur18frq6uaNOmDX799df89YcPH8awYcPg5eUFT09P9OzZE6dOnSq0j5kzZyI0NBT+/v547LHHYDKZ8tclJyfjvvvug6+vL9zc3DBkyBCcOHEif/33338PHx8fLF26FI0bN4aLiwsGDBiA6Ohouf7s2bNQq9XYtWtXoff87LPP0KpVK3n869atk/Wc5cuXy+MX++jSpQsOHjxY6DVbtmxBr1695P8zPDwcTzzxBDIzMyv9pGBgQU5BVTAVFGfeJiIiqnqm7JJv5tzSb2vKKd22ZfTSSy9h7ty5+PLLL2UQ8eSTT+Lee+/F+vXrERMTIyvioqL+zz//YPfu3XjggQdgNpvzX7927VoZaIj7efPmyUBB3AqOw9i1axd+//13bN26VQYCQ4cOLRR8ZGVl4a233pKv37x5M9LS0jBmzBi5LioqCv3795fHWJB4j7Fjxxa6cPrMM8/IIGfnzp0ICgrCiBEj8t9HBBmDBg3CyJEjceDAAfz888/YtGkTpkyZgsrGCfLIKZx1b4N6+FM+ZlcoIiIiB5jdo9jFojrsGtoJGPnFlYXfDgDMJQQHdToAI7++8vz74UBOStHtHt9d6kMTV+s/+OADGTR069ZNLhMtF6LC/dVXX8lKvbe3NxYtWgSdTifXi1aFgkRLhGg90Gg0aNq0qWzdWLNmDSZOnChbJn7//XcZLNx0001y+x9//FG2FogWitGjR8tlovIv9iFaGQQRYDRr1gw7duxA586d8dBDD+GRRx6Rx2owGLB//37s27evUAAjvPrqq7K1w76PunXr4rfffsOdd96JGTNmyEDk//7v/+T6Ro0a4ZNPPkHv3r1lUCWCp8rCFgtyCue8OuJPa2ccUurBqvNw9OEQERFRNXLkyBHk5OTIyriHh0f+bf78+bIVQlTeRdcne1BRnBYtWsigwk50iYqPj5ePjx49Cq1Wmx8wCKK7VJMmTeQ6O7FNx44d85+LAEV0j7JvIzJPiW1EkCB899136Nu3LyIiIgodiz04Evz8/Aq9j2htEYFIwf+naMGwWq04c+YMKhNbLMgpqFXATPNd8vFcv+aOPhwiIqLa55FNxS5WrFZkp2egUJX9odXX2NFV2R0nLCv3oYlKtSDGJtSpU6fQOtEyYL+6fy1XBx2ia5J9v6LbU3HE8qvHfhY3FtS+TK/XY9y4cbI7lOjKtHDhQtl6URr2fYhjmjRpkhxXcbWrA5SKxsCCnIKbNR3hqkvIUFwLTmlBREREVUXnWvxyUfnWmkq3bVn2WwbNmzeXAcT58+dll6CrtW7dWnYpEl2VrtVqca39m81mbN++Pb8rVGJiIo4fPy67OtmJbcQ4DNHtSTh27BhSUlJky4Wd6A7VsmVLfPHFF/J4RIBRcJyGsG3btvwgQQwaF+9j30f79u3lGJKGDRuiqrErFDmFDol/4Hvd+7hbsxZqRhZERERUgMjyNG3aNDlgWwQQovvT3r178fnnn8vnYmCzfSC1qPiLMRMLFiyQFf/SEOMYbr31VjneQozbEGMjxMBw0ToiltuJoOXxxx+XAciePXtw//33o2vXrvmBhiACEbHsueeew9133y0zO13t9ddfl+M7Dh06JAeNBwQE5E/gJ14nBo+LrFWii5d9/Id438rGwIKcQ1662Ts0G+CZfMTRR0NERETVzBtvvIFXXnkF77zzjqy8i3EHf/zxB+rVqyfHQ4iB3RkZGbJFo0OHDvjmm2/K1Hoxd+5c+brhw4fLMRCiG9SKFSsK7UOkoRUVfzG4WmwjggYxYPxqDz74IIxGo8xMVZx3330XU6dOle8XGxsrAwfRjcre+iIyXYmAQowbadeuHV5++WU5JqSysSsUOYcCKWY1isWhh0JERETVjxiDIMYdFDf2wF4hX7lyZbHrrs7KJHz00UdFskbNnz//uschujaJ27WIYEF0h+rUqVP+OI6CevToIVsrSiJet2rVKlQ1tliQcyg4d0XBOS2IiIiIaoiMjAw5N8Wnn35aYgBUnbEGRk4h3qMZjNAiAd4wekU5+nCIiIiIykyM9RCtEaI7VkndoKozBhbkFOJ82mKE8S3cbXwJiouXow+HiIiIqBAxyFpkgLoW0eUqNzdXzpZdcM4Muz59+sixG2Lui+qIYyzIKbSp6w2rWgcvFy0aBHKCPCIiIqKqxsCCnMLNzYKx95UB0GvUcNEVjfCJiIiIqHIxsCCn4eVS9gltiIiIqOxKmmmaavfnWaPHWKxbt06mDivuJkbU24lZFm+55Ra4u7vLCUTEKHuRG5iIiIiISs8+J0NWVhaLzYlk5X2eNzLruNO0WIgp00We34LEBCB///03OnbsKJ9bLBYMGzYMgYGBciZEMb36+PHjZWQmUnkRERERUemIAcVi4HB8fHz+hG/igu61iHkYxAXdnJwcqJkSvswqs/xEfVgEFeLzFJ9rcQPGa01gIWYYDAkJyX9uMpnkzIMiVZf9JBeTgxw5cgTR0dEICwuTy2bNmiVH5r/11lvw8mIGISIiIqLSste97MFFaSqv2dnZcpbp6wUh5JjyE0FFwTp1rQwsriaCioSEBBk02G3dulXOXGgPKgQxhbtI5bV792707dvXQUdLREREVPOIym1oaCiCgoLkRd3rEdts2LABvXr1KndXm9rIVMnlJ/ZZ3pYKpwws5syZI4OG8PDw/GVxcXEIDg4uMuW6aO0Q64ojgg5xs0tLS8v/YEvzBapo9vd0xHs7C5Yhy4/nX83F7y/Lz9F4DpasNBVS0ZXHbDbLbSuqAlubWCu5/MT+xa0kZal/qpRqOKz/tddew/Tp06+5jRicbR9HIVy4cAGRkZH473//izvuuCN/+cMPP4xz585h5cqVhV4vAov58+djzJgxpX7/hQsXyr6ERERERES1QVZWFsaOHYvU1NTrDiGoloGF6M4kbtcSFRUFFxeX/OdvvPGGHIwdExNTqJnolVdewf/+9z/s378/f1lycjL8/Pzwzz//FNsVqrgWC9EKIo7JEWMyRKS4evVqDBgwgE2ILEOH4DnI8nMknn8sP0fjOcjyq83nX1pamsyqWprAolp2hRIHL26lJWKjuXPn4r777itS4N26dZODtEX2KNEf0D6g22AwoEOHDsXuT6wTt6uJfTuyb6Cj398ZsAxZfjz/ai5+f1l+jsZzkOVXG88/XRnes1oGFmUlWh7OnDmDBx98sMi6gQMHonnz5hg3bhxmzJiBpKQkTJs2DRMnTix164O9Ucc+1sIRkapohhLvz8CCZchzsObhd5jlx/OvZuN3mOVXm8+/tLz6b2k6OVXLrlBlJfp9iXEUmzdvLna9mCBv8uTJMgARqbrE9jNnziy2VaI4YvxGwQHhRERERES1SXR0NOrWrev8gUVlEyPlL168CE9PT4fkX7aP8RAfKOfdYBk6As9Blp8j8fxj+Tkaz0GWX20+/xRFQXp6upy64XoT9DlFV6jKJgrxehFaVRAnEwMLliHPwZqL32GWH8+/mo3fYZZfbT3/vL29S7Vdxc4LTkREREREtRIDCyIiIiIiKjcGFjWAGGT+6quvlnqwObEMeQ5WL/wOs/x4/tVs/A6z/Hj+lQ4HbxMRERERUbmxxYKIiIiIiMqNgQUREREREZUbAwsiIiIiIio3BhbViJh85P/+7/8QGRkpZwi/6aabsHPnzkITlLz22mtyghKxvk+fPjh8+DBqqw0bNuCWW26R5SEmLly6dGmh9aUpr9zcXDz++OMICAiAu7s7RowYIWdarw2uV35LlizBoEGDZNmI9fv27SuyD5Zf8eVnMpnw3HPPoVWrVvK8Etvcd999cqJNll/pzj/x3W3atKksP19fX/Tv3x/bt29n+ZXhO1zQpEmT5DYfffQRy7CU5TdhwgS5vOCta9euLL8ynH9Hjx6Vv6tiDgQxybAov/Pnz/M3BNcvv6vPPfttxowZ1br8GFhUIw899BBWr16NBQsW4ODBgxg4cKD8MY2JiZHr33//fXzwwQf47LPPZMAREhKCAQMGyICkNsrMzESbNm1keRSnNOUlArnffvsNixYtwqZNm5CRkYHhw4fDYrGgtpefWN+9e3e8++67Je6D5Vd8+WVlZWHPnj14+eWX5b0I0o4fPy7/6LP8Snf+NW7cWK4TfwvFdzMqKkr+Tbx8+TLPv1KWoZ2osIigTFRg+B0u/d9AYfDgwYiNjc2/rVixgt/hUpbfqVOn0KNHD3mBYN26ddi/f7/8m+ji4sLvMK5ffgXPO3H77rvvZGBxxx13VO/yU6hayMrKUjQajbJs2bJCy9u0aaO8+OKLitVqVUJCQpR33303f11OTo7i7e2tzJ49W6ntxKn822+/5T8vTXmlpKQoOp1OWbRoUf42MTExilqtVv766y+lNpdfQWfOnJHr9+7dW2g5y6905We3Y8cOud25c+dYfmU4/+xSU1Pldn///TfLrwzf4QsXLih16tRRDh06pERGRioffvghv8OlLL/x48crt956a4nnJP8GXrv87rrrLuXee+9l+VXQ30BxLvbr16/an39ssagmzGazjDALRvKC6MIjotAzZ84gLi5OXrErmFe7d+/e2LJliwOOuHorTXnt3r1bdlkpuI24oteyZUuWaSmw/MomNTVVXm3y8fFh+ZWR0WjE119/LbtTiCt8PP9Kx2q1Yty4cXjmmWfQokWLIuv5Hb4+caU9KChItqBNnDgR8fHxLL9SnnvLly+X5Sa61Ioy7NKlS6HuPjz/Su/SpUuyPB988MFqX34MLKoJ0fewW7dueOONN2Q/bBFk/PDDD7L5WjSBiUqyEBwcXOh14rl9HV1RmvIS93q9XvbfZpmWHcuv9HJycvD8889j7Nix8PLyYvmV0rJly+Dh4SEvuHz44Yeyq6joS8zzr3Tee+89aLVaPPHEE8Wu53f42oYMGYIff/wR//zzD2bNmiW71Pbr10/2a2f5XZsIwES3HNGVVnQnW7VqFW6//XaMHDkS69evZ/mV0bx582Q9UZRfdf/+ah32zlSEGFvxwAMPoE6dOtBoNGjfvr2siIg+2nbiimdBogXt6mWEcpUXy7R8WH6FiStKY8aMkVfwvvjiC5ZfGfTt21cmDUhISMA333yDO++8U15sEVc/ef5dm7ia+fHHH8vfj7L+RvA7bHPXXXfll4m4CtyxY0eZXEVcOS5YwWP5FSX+3gm33nornnzySfm4bdu28kr67NmzZe8Bll/pifEV99xzT5FeLdXx+8sWi2qkQYMGMpIXUX50dDR27NghKyX16tWTA4+Fq6NQcVXg6qvyhFKVl9hGdLFITk5mmd4Alt/1ie+vqAyLrnniaru9tYLlVzoiy0nDhg1lJpk5c+bIq+/inuV3fRs3bpR/7yIiImS5idu5c+fw9NNPy4HwLMOyCw0NlYHFiRMnWH7XIVoWxTnXvHnzQsubNWuWnxWKvyGl/y4fO3ZMJvgpqLqWHwOLavpjKv6AiZNl5cqVMuK3BxeicmInTigRiIi0tFRYacqrQ4cO0Ol0hbYR3c4OHTrEMi0Fll/pggpRCfn777/h7+/P8isncSXO3g2F59+1ibEVBw4ckC0+9pvofy3GW4jfFZZh2SUmJsqLfuL3meV3baKLTqdOnWSFuCCRHU8EZyy/0hMXU8TfO/v4Mrvq+jeQXaGqEfHHXvxwNmnSBCdPnpQ/AOLx/fffL5u1RFqxt99+G40aNZI38djNzU12l6qNRMuOKCc7cVVY/Hj6+fnJq3TXKy8xEFQMhBJX8ESlT7xu2rRpcu4Bkea3tpdfUlKSvLJkn3vB/gMhAjZxY/mVXH6iAjdq1CjZDUWMExBjpuytZ2K9+NFl+ZVcfuL7+NZbb8n0vKISJyp0ohuZyM8+evRouX1tL7/SfIevDmZFJUR8d8XvilDby/Ba5SduYi4VkdpTnINnz57Ff/7zH3klXowVEFh+1z7/RB1GdCfr1auX7Nb4119/4Y8//pAD4ll+uO73V0hLS8Mvv/wix/hcrdqefw7LR0VF/Pzzz0r9+vUVvV4vU6U+9thjMp1YwRSqr776qlxnMBiUXr16KQcPHqy1Jbl27VqZou3qm0gRWNryys7OVqZMmaL4+fkprq6uyvDhw5Xz588rtcH1ym/u3LnFrhdlasfyK7787Cl6i7uJcmf5Xfv8E+fV7bffroSFhcm/h6GhocqIESNkyt6CavP5V5rv8NWuTjdb28vwWuUnUsAPHDhQCQwMlCk9IyIi5PKry4bld+3zb86cOUrDhg0VFxcXmT5/6dKlLL8yfH+/+uor+b0sWBes7uefSvzjuLCGiIiIiIicAcdYEBERERFRuTGwICIiIiKicmNgQUREREREDCyIiIiIiMjx2GJBRERERETlxsCCiIiIiIjKjYEFERERERGVGwMLIiIiIiIqNwYWRERUaxmNRjRs2BCbN2+Wz8+ePQuVSoV9+/ZV6vsePHgQdevWRWZmZqW+DxFRVWJgQUTkJCZMmCArxVffTp486ehDq7a+/vprREZGonv37qV+TVRUFD766KMiy1977TW0bdu2VPto1aoVOnfujA8//LBMx0tEVJ0xsCAiciKDBw9GbGxsoVu9evWKvVJPwKeffoqHHnrIIUVx//3348svv4TFYuFHQUROgYEFEZETMRgMCAkJKXTTaDTo06cPpkyZgqeeegoBAQEYMGCA3P7IkSMYOnQoPDw8EBwcjHHjxiEhISF/f6Krzn333SfXh4aGYtasWXJf//d//5e/jWgVWbp0aaHj8PHxwffff5//PCYmBnfddRd8fX3h7++PW2+9VXY7Ktjactttt2HmzJnyfcQ2jz32GEwmU/42ubm5ePbZZxEeHi7/n40aNcKcOXOgKIrsziReW9ChQ4egVqtx6tSpYstqz549sjVn2LBhJZan1WrFxIkT0bhxY5w7d66Un8KVcrn6Jlo77AYNGoTExESsX7++TPslIqquGFgQEdUS8+bNg1arleMJvvrqK9ma0bt3b9l9Z9euXfjrr79w6dIl3HnnnfmveeaZZ7B27Vr89ttvWLVqFdatW4fdu3eX6X2zsrLQt29fGZxs2LABmzZtko9F60rBlhPxPiIIEPfiWEVgUjA4EQHOokWL8Mknn+Do0aOYPXu23I+osD/wwAOYO3duoff97rvv0LNnTzRo0KDY4xLHIgIGLy+vYteLYxNlIcpGHLPoMlUWBVuNRAAjgp9evXrlr9fr9WjTpg02btxYpv0SEVVbChEROYXx48crGo1GcXd3z7+NGjVKruvdu7fStm3bQtu//PLLysCBAwsti46OVsRPw7Fjx5T09HRFr9crixYtyl+fmJiouLq6KlOnTs1fJrb/7bffCu3H29tbmTt3rnw8Z84cpUmTJorVas1fn5ubK/ezcuXK/GOPjIxUzGZz/jajR49W7rrrLvlYHI94n9WrVxf7f7948aL8v2/fvl0+NxqNSmBgoPL999+XWF7i/9CvX79Cy86cOSPfZ+PGjUr//v2V7t27KykpKYW2EccpyqVgOYubTqdT2rRpU+R9xP/79ttvVzp06KBkZWUVWieWT5gwocRjJCKqSbSODmyIiKjiiJYB0W/fzt3dPf9xx44dC20rWh5E64C46n810XKQnZ0tr9p369Ytf7mfnx+aNGlSpmMS7yOu2Ht6ehZanpOTU6ibUosWLWS3LTvRJUpkTxJEliaxTrSwFEdsK7o0iVYKMSh62bJlcv+jR48u8bjE/8/FxaXYdXfffbfM2rRmzRq4ubkVWS9ackT3rYJES4poBbnaf/7zH2zduhU7d+6Eq6troXXiuWjRISJyBgwsiIiciAgkRJebktZdPX7glltuwXvvvVdsRf3EiROlek/RFcnWcHFFwbER4n06dOiAH3/8schrAwMD8x/rdLoi+xWvFa6ukBdHDMIWY0REpiXRLUqM6SguKLATY03sgcvVxLiTH374Adu2bUO/fv2Kfe3V5SyCrquJfYjjEV3IRKBytaSkpBK7ahER1TQcY0FEVEu1b98ehw8flgOKRSW54M0eoIjKvqhc2yUnJ+P48eNFggMxjsBOBCQFr8KL9xHLgoKCiryPt7d3qdOziiDjWgOdRTAgjlu02Pz5559y3MW1tGvXDv/++2+RoEh49NFH8e6772LEiBE3PLhatFKIYEeMZ+natWux24gB5uI4iIicAQMLIqJaSmRdElfMRbefHTt24PTp03KAtqiQixSooovUgw8+KLv9iC5BohIsuv+ITEsFiSv6n332mcyyJAY6P/LII4VaH+655x55hV9kghIDlc+cOSMr61OnTsWFCxdKdawi+Bk/frw8NpGBSuxDtAL897//zd9GdJUSx/fCCy/IoKVgF66Suo2JrFciuCrO448/jjfffBPDhw+Xg7fLIi4uDrfffjvGjBkjsz+J5+J2+fLl/G1EViyRLat///5l2jcRUXXFwIKIqJYKCwuTGaJEECEqvy1btpSVfdGKYA8eZsyYITMZiSv3ogLco0cP2a2pIJGCVqSAFduNHTsW06ZNK9QFSTwWYw8iIiIwcuRINGvWTAYIYoxDSRmZiiNaIkaNGoXJkyejadOmMg3s1TNXi0BIjAu5XmuFIFLaiuMprouWnUirO336dNkasmXLllIfq2gJERm2RHYr0a3MfuvUqVP+Nj/99BMGDhxY5mxTRETVlUqM4Hb0QRARUc0h5rEQKWqLm33a0USgJI5PtISIeTmuR4yxEAFTcYPLK5OYk0PMwyGCi7LM+k1EVJ2xxYKIiGo8UVEXwcHLL78s554oTVBhH7vx/vvvF5qsryqIyfZefPFFBhVE5FSYFYqIiGo8ceVfdIMSLSkLFiwo02vF2I2qJibmEzciImfCrlBERERERFRu7ApFRERERETlxsCCiIiIiIjKjYEFERERERGVGwMLIiIiIiIqNwYWRERERERUbgwsiIiIiIio3BhYEBERERFRuTGwICIiIiKicmNgQUREREREKK//B0pe8MpApa5oAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    ref_ts[\"TS_m\"],\n",
+    "    f_m / 1000,\n",
+    "    TS_m,\n",
+    "    title=\"Final TS(f)\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"TS(f) (dB re 1 m$^2$)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5edae46a",
+   "metadata": {},
+   "source": [
+    "### Reproduce the Andersen et al. (2024) Figure 7 diagnostic panel\n",
+    "\n",
+    "We reproduce a Figure 7-style diagnostic panel from Andersen et al. (2024) using the echopype implementation. The panels show the target spectrum, matched-filter autocorrelation spectrum, normalised target spectrum, beam-compensated gain, and final calibrated TS spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "70228c93",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x1000 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(5, 1, figsize=(8, 10), sharex=True)\n",
+    "\n",
+    "ax[0].plot(f_m / 1000, db20(Y_pc_t_m))\n",
+    "ax[0].set_ylabel(r\"$|Y_{pc,t}|$\")\n",
+    "\n",
+    "ax[1].plot(f_m / 1000, db20(Y_mf_auto_red_m))\n",
+    "ax[1].set_ylabel(r\"$|Y_{auto,red}|$\")\n",
+    "\n",
+    "ax[2].plot(f_m / 1000, db20(Y_tilde_pc_t_m))\n",
+    "ax[2].set_ylabel(r\"$|\\tilde{Y}_{pc,t}|$\")\n",
+    "\n",
+    "ax[3].plot(f_m / 1000, 10 * np.log10(g_theta_phi_m**2))\n",
+    "ax[3].set_ylabel(\"Gain (dB)\")\n",
+    "\n",
+    "ax[4].plot(f_m / 1000, TS_m)\n",
+    "ax[4].set_ylabel(\"TS(f)\")\n",
+    "ax[4].set_xlabel(\"Frequency (kHz)\")\n",
+    "\n",
+    "for a in ax:\n",
+    "    a.grid(True)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43d1434b",
+   "metadata": {},
+   "source": [
+    "### Summary of differences between CRIMAC and echopype processing steps\n",
+    "\n",
+    "The table below summarises the differences between corresponding variables computed by CRIMAC and echopype at each stage of the TS-spectrum workflow."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af274118",
+   "metadata": {},
+   "source": [
+    "tmp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "8abea7a8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['y_rx_nu', 'r_n', 'f_m', 'alpha_m', 'lambda_m', 'y_tx_n', 'y_mf_n', 'y_mf_auto_n', 'tau_eff', 'y_pc_nu', 'y_pc_n', 'p_rx_e_n', 'theta_n', 'phi_n', 'Sp_full_n', 'Sp_full_r', 'Sp_target_n', 'Sp_target_r', 'dum_r', 'dum_theta', 'dum_phi', 'r_t', 'theta_t', 'phi_t', 'y_pc_t_n', 'y_mf_auto_red_n', 'Y_pc_t_m', 'Y_mf_auto_red_m', 'Y_tilde_pc_t_m', 'P_rx_e_t_m', 'g_theta_phi_m', 'TS_m']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ref_ts.files)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "848ac4e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "y_pc_n abs: RMSE=0.000203375, max_abs=0.00662722\n",
+      "\n",
+      "FIRST DIFFERENCE ABOVE TOLERANCE\n",
+      "variable: y_pc_n abs\n",
+      "index: 1\n",
+      "CRIMAC: 8.244825873734117\n",
+      "echopype/manual: 8.251453096905179\n",
+      "diff: 0.006627223171062013\n"
+     ]
+    }
+   ],
+   "source": [
+    "checks = [\n",
+    "    (\"y_pc_n abs\", np.abs(ref_ts[\"y_pc_n\"]), np.abs(y_pc_n)),\n",
+    "    (\"p_rx_e_n dB\", db10(ref_ts[\"p_rx_e_n\"]), db10(p_rx_e_n)),\n",
+    "    (\"Sp_full_n dB\", ref_ts[\"Sp_full_n\"], Sp_n),\n",
+    "    (\"r_t\", np.array([ref_ts[\"r_t\"]]), np.array([r_t])),\n",
+    "    (\"theta_t\", np.array([ref_ts[\"theta_t\"]]), np.array([theta_t])),\n",
+    "    (\"phi_t\", np.array([ref_ts[\"phi_t\"]]), np.array([phi_t])),\n",
+    "    (\"y_pc_t_n abs\", np.abs(ref_ts[\"y_pc_t_n\"]), np.abs(y_pc_t_n)),\n",
+    "    (\"y_mf_auto_red_n abs\", np.abs(ref_ts[\"y_mf_auto_red_n\"]), np.abs(y_mf_auto_red_n)),\n",
+    "    (\"Y_pc_t_m dB\", db20(ref_ts[\"Y_pc_t_m\"]), db20(Y_pc_t_m)),\n",
+    "    (\"Y_mf_auto_red_m dB\", db20(ref_ts[\"Y_mf_auto_red_m\"]), db20(Y_mf_auto_red_m)),\n",
+    "    (\"Y_tilde_pc_t_m dB\", db20(ref_ts[\"Y_tilde_pc_t_m\"]), db20(Y_tilde_pc_t_m)),\n",
+    "    (\"P_rx_e_t_m dB\", db10(ref_ts[\"P_rx_e_t_m\"]), db10(P_rx_e_t_m)),\n",
+    "    (\"g_theta_phi_m dB\", db10(ref_ts[\"g_theta_phi_m\"]), db10(g_theta_phi_m)),\n",
+    "    (\"alpha_m\", ref_ts[\"alpha_m\"], absorption_f),\n",
+    "    (\"TS_m\", ref_ts[\"TS_m\"], TS_m),\n",
+    "]\n",
+    "\n",
+    "tol = 1e-6\n",
+    "\n",
+    "for name, ref, val in checks:\n",
+    "    ref = np.asarray(ref).reshape(-1)\n",
+    "    val = np.asarray(val).reshape(-1)\n",
+    "\n",
+    "    n = min(ref.size, val.size)\n",
+    "    diff = val[:n] - ref[:n]\n",
+    "\n",
+    "    max_abs = np.nanmax(np.abs(diff))\n",
+    "    rmse = np.sqrt(np.nanmean(diff**2))\n",
+    "\n",
+    "    print(f\"{name}: RMSE={rmse:.6g}, max_abs={max_abs:.6g}\")\n",
+    "\n",
+    "    if max_abs > tol:\n",
+    "        idx = int(np.nanargmax(np.abs(diff)))\n",
+    "        print(\"\\nFIRST DIFFERENCE ABOVE TOLERANCE\")\n",
+    "        print(\"variable:\", name)\n",
+    "        print(\"index:\", idx)\n",
+    "        print(\"CRIMAC:\", ref[idx])\n",
+    "        print(\"echopype/manual:\", val[idx])\n",
+    "        print(\"diff:\", diff[idx])\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f2191bfe",
+   "metadata": {},
+   "source": [
+    "end tmp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "6ff2975a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>n</th>\n",
+       "      <th>CRIMAC mean</th>\n",
+       "      <th>echopype mean</th>\n",
+       "      <th>mean diff</th>\n",
+       "      <th>median diff</th>\n",
+       "      <th>RMSE</th>\n",
+       "      <th>max abs diff</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>y_mf_n abs</td>\n",
+       "      <td>516</td>\n",
+       "      <td>0.509469</td>\n",
+       "      <td>0.509642</td>\n",
+       "      <td>1.729508e-04</td>\n",
+       "      <td>1.301043e-17</td>\n",
+       "      <td>0.001248</td>\n",
+       "      <td>0.021871</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>y_mf_auto_n abs</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>0.004699</td>\n",
+       "      <td>0.004695</td>\n",
+       "      <td>-3.954363e-06</td>\n",
+       "      <td>-6.732322e-15</td>\n",
+       "      <td>0.000098</td>\n",
+       "      <td>0.000350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>y_pc_n abs</td>\n",
+       "      <td>2356</td>\n",
+       "      <td>0.079082</td>\n",
+       "      <td>0.079071</td>\n",
+       "      <td>-1.070651e-05</td>\n",
+       "      <td>-1.008762e-08</td>\n",
+       "      <td>0.000203</td>\n",
+       "      <td>0.006627</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>p_rx_e_n dB</td>\n",
+       "      <td>2356</td>\n",
+       "      <td>-106.347106</td>\n",
+       "      <td>-106.345857</td>\n",
+       "      <td>1.248776e-03</td>\n",
+       "      <td>-2.469640e-03</td>\n",
+       "      <td>0.387861</td>\n",
+       "      <td>8.330394</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Sp_full_n dB</td>\n",
+       "      <td>2356</td>\n",
+       "      <td>-92.918309</td>\n",
+       "      <td>-92.919339</td>\n",
+       "      <td>-1.029862e-03</td>\n",
+       "      <td>-4.748281e-03</td>\n",
+       "      <td>0.387860</td>\n",
+       "      <td>8.332673</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Sp_target_n dB</td>\n",
+       "      <td>167</td>\n",
+       "      <td>-82.034552</td>\n",
+       "      <td>-82.069809</td>\n",
+       "      <td>-3.525722e-02</td>\n",
+       "      <td>-5.111712e-03</td>\n",
+       "      <td>0.307320</td>\n",
+       "      <td>1.852714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>y_pc_t_n abs</td>\n",
+       "      <td>168</td>\n",
+       "      <td>0.000436</td>\n",
+       "      <td>0.000436</td>\n",
+       "      <td>-1.777090e-07</td>\n",
+       "      <td>-7.647879e-08</td>\n",
+       "      <td>0.000002</td>\n",
+       "      <td>0.000005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>y_mf_auto_red_n abs</td>\n",
+       "      <td>168</td>\n",
+       "      <td>0.027249</td>\n",
+       "      <td>0.027238</td>\n",
+       "      <td>-1.024769e-05</td>\n",
+       "      <td>-1.586508e-05</td>\n",
+       "      <td>0.000211</td>\n",
+       "      <td>0.000350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Y_pc_t_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.450622</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>2.382618e-03</td>\n",
+       "      <td>-2.111098e-03</td>\n",
+       "      <td>0.288531</td>\n",
+       "      <td>5.399668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Y_mf_auto_red_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>3.567061</td>\n",
+       "      <td>3.570432</td>\n",
+       "      <td>3.371336e-03</td>\n",
+       "      <td>-1.389353e-03</td>\n",
+       "      <td>0.095777</td>\n",
+       "      <td>0.455695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Y_tilde_pc_t_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-39.017683</td>\n",
+       "      <td>-39.018672</td>\n",
+       "      <td>-9.887186e-04</td>\n",
+       "      <td>-3.215677e-04</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134121</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>P_rx_e_t_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-60.658788</td>\n",
+       "      <td>-60.659777</td>\n",
+       "      <td>-9.887186e-04</td>\n",
+       "      <td>-3.215677e-04</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134121</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>g_theta_phi_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>52.590609</td>\n",
+       "      <td>52.590553</td>\n",
+       "      <td>-5.644019e-05</td>\n",
+       "      <td>-5.325710e-05</td>\n",
+       "      <td>0.000060</td>\n",
+       "      <td>0.000097</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>TS_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.615550</td>\n",
+       "      <td>-41.616483</td>\n",
+       "      <td>-9.322373e-04</td>\n",
+       "      <td>-2.770378e-04</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134085</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               variable     n  CRIMAC mean  echopype mean     mean diff  \\\n",
+       "0            y_mf_n abs   516     0.509469       0.509642  1.729508e-04   \n",
+       "1       y_mf_auto_n abs  1031     0.004699       0.004695 -3.954363e-06   \n",
+       "2            y_pc_n abs  2356     0.079082       0.079071 -1.070651e-05   \n",
+       "3           p_rx_e_n dB  2356  -106.347106    -106.345857  1.248776e-03   \n",
+       "4          Sp_full_n dB  2356   -92.918309     -92.919339 -1.029862e-03   \n",
+       "5        Sp_target_n dB   167   -82.034552     -82.069809 -3.525722e-02   \n",
+       "6          y_pc_t_n abs   168     0.000436       0.000436 -1.777090e-07   \n",
+       "7   y_mf_auto_red_n abs   168     0.027249       0.027238 -1.024769e-05   \n",
+       "8           Y_pc_t_m dB  1000   -35.450622     -35.448239  2.382618e-03   \n",
+       "9    Y_mf_auto_red_m dB  1000     3.567061       3.570432  3.371336e-03   \n",
+       "10    Y_tilde_pc_t_m dB  1000   -39.017683     -39.018672 -9.887186e-04   \n",
+       "11        P_rx_e_t_m dB  1000   -60.658788     -60.659777 -9.887186e-04   \n",
+       "12     g_theta_phi_m dB  1000    52.590609      52.590553 -5.644019e-05   \n",
+       "13              TS_m dB  1000   -41.615550     -41.616483 -9.322373e-04   \n",
+       "\n",
+       "     median diff      RMSE  max abs diff  \n",
+       "0   1.301043e-17  0.001248      0.021871  \n",
+       "1  -6.732322e-15  0.000098      0.000350  \n",
+       "2  -1.008762e-08  0.000203      0.006627  \n",
+       "3  -2.469640e-03  0.387861      8.330394  \n",
+       "4  -4.748281e-03  0.387860      8.332673  \n",
+       "5  -5.111712e-03  0.307320      1.852714  \n",
+       "6  -7.647879e-08  0.000002      0.000005  \n",
+       "7  -1.586508e-05  0.000211      0.000350  \n",
+       "8  -2.111098e-03  0.288531      5.399668  \n",
+       "9  -1.389353e-03  0.095777      0.455695  \n",
+       "10 -3.215677e-04  0.267273      5.134121  \n",
+       "11 -3.215677e-04  0.267273      5.134121  \n",
+       "12 -5.325710e-05  0.000060      0.000097  \n",
+       "13 -2.770378e-04  0.267273      5.134085  "
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rows = []\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_mf_n abs\",\n",
+    "    np.abs(ref_ts[\"y_mf_n\"]),\n",
+    "    np.abs(y_mf_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_mf_auto_n abs\",\n",
+    "    np.abs(ref_ts[\"y_mf_auto_n\"]),\n",
+    "    np.abs(y_mf_auto_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_pc_n abs\",\n",
+    "    np.abs(ref_ts[\"y_pc_n\"]),\n",
+    "    np.abs(y_pc_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"p_rx_e_n dB\",\n",
+    "    db10(ref_ts[\"p_rx_e_n\"]),\n",
+    "    db10(p_rx_e_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Sp_full_n dB\",\n",
+    "    ref_ts[\"Sp_full_n\"],\n",
+    "    Sp_n,\n",
+    "))\n",
+    "\n",
+    "## target-windows\n",
+    "target_mask = (\n",
+    "    (r_n >= ref_ts[\"Sp_target_r\"].min())\n",
+    "    & (r_n <= ref_ts[\"Sp_target_r\"].max())\n",
+    ")\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Sp_target_n dB\",\n",
+    "    ref_ts[\"Sp_target_n\"],\n",
+    "    Sp_n[target_mask],\n",
+    "))\n",
+    "##\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_pc_t_n abs\",\n",
+    "    np.abs(ref_ts[\"y_pc_t_n\"]),\n",
+    "    np.abs(y_pc_t_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_mf_auto_red_n abs\",\n",
+    "    np.abs(ref_ts[\"y_mf_auto_red_n\"]),\n",
+    "    np.abs(y_mf_auto_red_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Y_pc_t_m dB\",\n",
+    "    db20(ref_ts[\"Y_pc_t_m\"]),\n",
+    "    db20(Y_pc_t_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Y_mf_auto_red_m dB\",\n",
+    "    db20(ref_ts[\"Y_mf_auto_red_m\"]),\n",
+    "    db20(Y_mf_auto_red_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Y_tilde_pc_t_m dB\",\n",
+    "    db20(ref_ts[\"Y_tilde_pc_t_m\"]),\n",
+    "    db20(Y_tilde_pc_t_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"P_rx_e_t_m dB\",\n",
+    "    db10(ref_ts[\"P_rx_e_t_m\"]),\n",
+    "    db10(P_rx_e_t_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"g_theta_phi_m dB\",\n",
+    "    10 * np.log10(ref_ts[\"g_theta_phi_m\"] ** 2),\n",
+    "    10 * np.log10(g_theta_phi_m ** 2),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"TS_m dB\",\n",
+    "    ref_ts[\"TS_m\"],\n",
+    "    TS_m,\n",
+    "))\n",
+    "\n",
+    "summary = pd.DataFrame(rows)\n",
+    "summary"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1f2a53a8",
+   "metadata": {},
+   "source": [
+    "## 18. Public API check: compute_TS_spectrum\n",
+    "\n",
+    "This validates that the public API returns the same TS spectrum product as the manual helper-chain above.\n",
+    "\n",
+    "The workflow is now:\n",
+    "\n",
+    "```text\n",
+    "compute_Sp()\n",
+    "→ simple target detection using Sp + split-beam angles\n",
+    "→ point_locations\n",
+    "→ compute_TS_spectrum(point_locations=...)\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "425572d3",
+   "metadata": {},
+   "source": [
+    "### Reproduce the TS spectrum using the public API\n",
+    "\n",
+    "The previous sections reproduced the CRIMAC processing chain step-by-step using internal helper functions. In practice, users can obtain the same TS-spectrum product directly through the public API."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44510cb1",
+   "metadata": {},
+   "source": [
+    "Before calling `compute_TS_spectrum()`, we first need to provide target locations. Here, we use the public `compute_Sp()` output to detect the strongest target within the expected calibration-sphere range gate for each ping. For each detected target, we store the ping time, channel, target range, split-beam angles, and target-window limits in a table that will be passed to `compute_TS_spectrum()`.\n",
+    "\n",
+    "**This detection step is intentionally simple and is only used here to generate `point_locations` for validating the TS-spectrum API.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "0892fb0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Available Sp channels: ['WBT 747008-15 ES333-7CD_ES' 'WBT 747015-15 ES70-7CD_ES'\n",
+      " 'WBT 747019-15 ES200-7CD_ES' 'WBT 747022-15 ES120-7CD_ES']\n",
+      "Selected channel: WBT 747022-15 ES120-7CD_ES\n",
+      "Number of detected targets: 1265\n"
+     ]
+    }
+   ],
+   "source": [
+    "target_rows = []\n",
+    "\n",
+    "ds_Sp = ep.calibrate.compute_Sp(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    ")\n",
+    "\n",
+    "print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
+    "print(\"Selected channel:\", tsf_channel)\n",
+    "\n",
+    "sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)\n",
+    "\n",
+    "tx_coeff = get_filter_coeff(cal_obj.vend)\n",
+    "fs = cal_obj.cal_params[\"receiver_sampling_frequency\"]\n",
+    "\n",
+    "matched_filter, _ = get_transmit_signal(\n",
+    "    cal_obj.beam,\n",
+    "    tx_coeff,\n",
+    "    cal_obj.waveform_mode,\n",
+    "    fs,\n",
+    "    cal_obj.drop_last_hanning_zero,\n",
+    ")\n",
+    "\n",
+    "pc = _get_pulse_compressed_signal(\n",
+    "    beam=cal_obj.beam,\n",
+    "    matched_filter=matched_filter,\n",
+    ")\n",
+    "\n",
+    "pc_ch = pc.sel(channel=tsf_channel)\n",
+    "range_ch = cal_obj.range_meter.sel(channel=tsf_channel)\n",
+    "\n",
+    "for ping_idx in range(sp_ch.sizes[\"ping_time\"]):\n",
+    "    pc_ping_i = pc_ch.isel(ping_time=ping_idx)\n",
+    "    sp_i = sp_ch.isel(ping_time=ping_idx)\n",
+    "    r_i = range_ch.isel(ping_time=ping_idx)\n",
+    "\n",
+    "    valid = np.isfinite(sp_i) & np.isfinite(r_i)\n",
+    "\n",
+    "    if not bool(valid.any()):\n",
+    "        continue\n",
+    "\n",
+    "    pc_ping_i = pc_ping_i.where(valid, drop=True)\n",
+    "    sp_i = sp_i.where(valid, drop=True).values\n",
+    "    r_i = r_i.where(valid, drop=True).values\n",
+    "\n",
+    "    gamma_theta_i = scalar_param(\n",
+    "        cal_obj.cal_params[\"angle_sensitivity_alongship\"],\n",
+    "        tsf_channel,\n",
+    "        ping_idx,\n",
+    "    )\n",
+    "\n",
+    "    gamma_phi_i = scalar_param(\n",
+    "        cal_obj.cal_params[\"angle_sensitivity_athwartship\"],\n",
+    "        tsf_channel,\n",
+    "        ping_idx,\n",
+    "    )\n",
+    "\n",
+    "    theta_i, phi_i = _get_splitbeam_angles(\n",
+    "        pc=pc_ping_i,\n",
+    "        gamma_alongship=gamma_theta_i,\n",
+    "        gamma_athwartship=gamma_phi_i,\n",
+    "    )\n",
+    "\n",
+    "    theta_i = theta_i.values\n",
+    "    phi_i = phi_i.values\n",
+    "\n",
+    "    sp_lin_i = 10 ** (sp_i / 10)\n",
+    "\n",
+    "    try:\n",
+    "        (\n",
+    "            r_t_i,\n",
+    "            theta_t_i,\n",
+    "            phi_t_i,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            dum_r_i,\n",
+    "        ) = extract_single_target(\n",
+    "            pc_avg=sp_lin_i,\n",
+    "            power=sp_lin_i,\n",
+    "            theta=theta_i,\n",
+    "            phi=phi_i,\n",
+    "            range_meter=r_i,\n",
+    "            r0=5.3,\n",
+    "            r1=6.3,\n",
+    "            before=0.5,\n",
+    "            after=1.0,\n",
+    "        )\n",
+    "    except ValueError:\n",
+    "        continue\n",
+    "\n",
+    "    target_rows.append(\n",
+    "        {\n",
+    "            \"raw_ping_index\": ping_idx,\n",
+    "            \"ping_time\": ds_Sp[\"ping_time\"].isel(ping_time=ping_idx).values,\n",
+    "            \"channel\": tsf_channel,\n",
+    "            \"target_id\": len(target_rows),\n",
+    "            \"target_range\": r_t_i,\n",
+    "            \"angle_alongship\": theta_t_i,\n",
+    "            \"angle_athwartship\": phi_t_i,\n",
+    "            \"target_range_min\": dum_r_i.min(),\n",
+    "            \"target_range_max\": dum_r_i.max(),\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "print(\"Number of detected targets:\", len(target_rows))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "dca2a887",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 287MB\n",
+       "Dimensions:                        (channel: 4, ping_time: 1266,\n",
+       "                                    range_sample: 3534, filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel                        (channel) object 32B &#x27;WBT 747008-15 ES333-...\n",
+       "  * ping_time                      (ping_time) datetime64[ns] 10kB 2021-12-15...\n",
+       "  * range_sample                   (range_sample) int64 28kB 0 1 2 ... 3532 3533\n",
+       "  * filenames                      (filenames) int64 8B 0\n",
+       "Data variables: (12/24)\n",
+       "    Sp                             (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    echo_range                     (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    frequency_nominal              (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    sound_speed                    float64 8B 1.485e+03\n",
+       "    sound_absorption               (channel, ping_time) float64 41kB 0.07527 ...\n",
+       "    temperature                    float64 8B 9.7\n",
+       "    ...                             ...\n",
+       "    beamwidth_athwartship          (channel, ping_time) float64 41kB 7.132 .....\n",
+       "    impedance_transducer           (channel, ping_time) float64 41kB 75.0 ......\n",
+       "    impedance_transceiver          (channel) int64 32B 5400 5400 5400 5400\n",
+       "    receiver_sampling_frequency    (channel) float64 32B 1.5e+06 ... 1.5e+06\n",
+       "    source_filenames               (filenames) &lt;U67 268B &#x27;example_data\\\\ts_sp...\n",
+       "    water_level                    float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:47:33+00:00\n",
+       "    processing_function:          calibrate.compute_Sp</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-257fc57a-fe69-4222-846e-91959700d3e9' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-257fc57a-fe69-4222-846e-91959700d3e9' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-c8c884f4-3d4a-4ff5-af7d-f54d6d7ba546' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c8c884f4-3d4a-4ff5-af7d-f54d6d7ba546' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-8ade1264-cebf-40a2-bf8b-46250be94e05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ade1264-cebf-40a2-bf8b-46250be94e05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3731763d-763f-461d-96c4-87adc65d0cb9' class='xr-var-data-in' type='checkbox'><label for='data-3731763d-763f-461d-96c4-87adc65d0cb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-280f09b5-483a-4d86-a233-4785c8ede359' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-280f09b5-483a-4d86-a233-4785c8ede359' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20f1ba75-9b18-4589-9ca1-c3cebf97546e' class='xr-var-data-in' type='checkbox'><label for='data-20f1ba75-9b18-4589-9ca1-c3cebf97546e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-981ab7ea-6eb3-4197-9648-983774613b29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-981ab7ea-6eb3-4197-9648-983774613b29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ca32464-12b5-4e84-b537-94d7fdb1bfa9' class='xr-var-data-in' type='checkbox'><label for='data-0ca32464-12b5-4e84-b537-94d7fdb1bfa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-e88c654e-8f04-44b9-adab-6bb31ed434f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88c654e-8f04-44b9-adab-6bb31ed434f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e7781c-0ac2-443d-8526-ad096a24013f' class='xr-var-data-in' type='checkbox'><label for='data-92e7781c-0ac2-443d-8526-ad096a24013f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4262abe7-4b9b-41e5-8cc4-7b1bb94bc1f0' class='xr-section-summary-in' type='checkbox' /><label for='section-4262abe7-4b9b-41e5-8cc4-7b1bb94bc1f0' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Sp</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-018451ee-8460-42d8-8d7c-9d497d423674' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-018451ee-8460-42d8-8d7c-9d497d423674' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a6ec994-dcbc-43cf-9c84-7412be87c0f7' class='xr-var-data-in' type='checkbox'><label for='data-1a6ec994-dcbc-43cf-9c84-7412be87c0f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Point scattering strength (Sp re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[          nan,           nan,           nan, ...,\n",
+       "         -195.57397259, -218.79009715, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -198.89271647, -222.29194801, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -203.05173598, -226.23191104, -150.30546618],\n",
+       "        ...,\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -206.32631432, -229.36708419, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -199.86920994, -223.97459584, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -201.28247937, -225.21174509, -150.30546618]],\n",
+       "\n",
+       "       [[          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "...\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan]],\n",
+       "\n",
+       "       [[          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        ...,\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan]]],\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>echo_range</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.003961 0.007922 ... nan nan</div><input id='attrs-430bf7fe-1b9e-46d2-9291-56bb61afab1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-430bf7fe-1b9e-46d2-9291-56bb61afab1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-456fdd8d-b511-4497-8303-8b75f943ef99' class='xr-var-data-in' type='checkbox'><label for='data-456fdd8d-b511-4497-8303-8b75f943ef99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Range distance</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        ...,\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01]],\n",
+       "\n",
+       "       [[0.00000000e+00, 1.58442419e-02, 3.16884838e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 1.58442419e-02, 3.16884838e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 1.58442419e-02, 3.16884838e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "...\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        ...,\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]]],\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-00bb80b6-bc78-446c-9d8b-c083f5730223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00bb80b6-bc78-446c-9d8b-c083f5730223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29855845-f9a8-42b2-88fa-ee771b7db5a0' class='xr-var-data-in' type='checkbox'><label for='data-29855845-f9a8-42b2-88fa-ee771b7db5a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-1a770251-9a45-4569-8238-961d39f876b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a770251-9a45-4569-8238-961d39f876b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4258122a-f0d4-4fae-8972-a6f2afd6a85c' class='xr-var-data-in' type='checkbox'><label for='data-4258122a-f0d4-4fae-8972-a6f2afd6a85c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1485.4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_absorption</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07527 0.07527 ... 0.0377 nan</div><input id='attrs-8767edc6-22ca-4c7f-9634-1093dcc42436' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8767edc6-22ca-4c7f-9634-1093dcc42436' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01c5e1a2-14e4-4bb3-aa49-23d86b3aba75' class='xr-var-data-in' type='checkbox'><label for='data-01c5e1a2-14e4-4bb3-aa49-23d86b3aba75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.07527219, 0.07527219, 0.07527219, ..., 0.07527219, 0.07527219,\n",
+       "        0.07527219],\n",
+       "       [0.02167407, 0.02167407, 0.02167407, ..., 0.02167407, 0.02167407,\n",
+       "        0.02167407],\n",
+       "       [0.05300738, 0.05300738, 0.05300738, ..., 0.05300738, 0.05300738,\n",
+       "        0.05300738],\n",
+       "       [0.03770373, 0.03770373, 0.03770373, ..., 0.03770373, 0.03770373,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-70a9198d-0513-4336-81e3-20bf448f2e21' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70a9198d-0513-4336-81e3-20bf448f2e21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a01fc152-7dce-4732-844a-d61d5a251940' class='xr-var-data-in' type='checkbox'><label for='data-a01fc152-7dce-4732-844a-d61d5a251940' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(9.7)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-9964122c-ecf7-47b1-9a31-172ef5bde171' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9964122c-ecf7-47b1-9a31-172ef5bde171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c05f67-fa2e-4478-a990-acebee4abc19' class='xr-var-data-in' type='checkbox'><label for='data-69c05f67-fa2e-4478-a990-acebee4abc19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-85106bbd-0567-42cc-a281-3567592c4ab1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-85106bbd-0567-42cc-a281-3567592c4ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-336fae25-4b02-450b-ba1a-b3bcd7ad48ef' class='xr-var-data-in' type='checkbox'><label for='data-336fae25-4b02-450b-ba1a-b3bcd7ad48ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-64b02427-8003-4612-8656-5ee97caf5b05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64b02427-8003-4612-8656-5ee97caf5b05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8029b272-0f32-45a2-b880-73e92bea66f1' class='xr-var-data-in' type='checkbox'><label for='data-8029b272-0f32-45a2-b880-73e92bea66f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>formula_absorption</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;FG&#x27;</div><input id='attrs-e40cdc57-2cff-4551-9a95-6d61f911d7fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e40cdc57-2cff-4551-9a95-6d61f911d7fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8de3d097-f0eb-4645-b79f-ce69c28dd1a0' class='xr-var-data-in' type='checkbox'><label for='data-8de3d097-f0eb-4645-b79f-ce69c28dd1a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;FG&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(ping_time, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-5d71772e-4e3a-44bc-8e9a-383bf6518e80' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5d71772e-4e3a-44bc-8e9a-383bf6518e80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18fc29b9-1ef4-4863-98fe-c56f2104d9d9' class='xr-var-data-in' type='checkbox'><label for='data-18fc29b9-1ef4-4863-98fe-c56f2104d9d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       ...,\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., nan]], shape=(1266, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.52 25.52 25.52 ... 28.04 nan</div><input id='attrs-0ad906ed-6359-4605-9e7f-8fff3ea04a1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ad906ed-6359-4605-9e7f-8fff3ea04a1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5bf5a8a-5f92-4e65-956b-b8cdbf17338a' class='xr-var-data-in' type='checkbox'><label for='data-d5bf5a8a-5f92-4e65-956b-b8cdbf17338a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.517003  , 25.517003  , 25.517003  , ..., 25.517003  ,\n",
+       "        25.517003  , 25.517003  ],\n",
+       "       [27.40875   , 27.40875   , 27.40875   , ..., 27.40875   ,\n",
+       "        27.40875   , 27.40875   ],\n",
+       "       [28.04229062, 28.04229062, 28.04229062, ..., 28.04229062,\n",
+       "        28.04229062, 28.04229062],\n",
+       "       [28.0375    , 28.0375    , 28.0375    , ..., 28.0375    ,\n",
+       "        28.0375    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.62 -20.62 -20.62 ... -21.4 nan</div><input id='attrs-415fc1e3-65c2-4b40-a82b-ea9f02332cfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-415fc1e3-65c2-4b40-a82b-ea9f02332cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79a95f48-ed1a-4a4c-a22e-1af52a9dc731' class='xr-var-data-in' type='checkbox'><label for='data-79a95f48-ed1a-4a4c-a22e-1af52a9dc731' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([[-20.62139413, -20.62139413, -20.62139413, ..., -20.62139413,\n",
+       "        -20.62139413, -20.62139413],\n",
+       "       [-20.7       , -20.7       , -20.7       , ..., -20.7       ,\n",
+       "        -20.7       , -20.7       ],\n",
+       "       [-21.32816929, -21.32816929, -21.32816929, ..., -21.32816929,\n",
+       "        -21.32816929, -21.32816929],\n",
+       "       [-21.39524213, -21.39524213, -21.39524213, ..., -21.39524213,\n",
+       "        -21.39524213,          nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.041 -0.041 ... -0.0575 nan</div><input id='attrs-4e30c0e7-90e3-485d-beb9-799a4d1aea6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e30c0e7-90e3-485d-beb9-799a4d1aea6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9150a043-05ca-4e7d-876d-58e42233143c' class='xr-var-data-in' type='checkbox'><label for='data-9150a043-05ca-4e7d-876d-58e42233143c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.040999  , -0.040999  , -0.040999  , ..., -0.040999  ,\n",
+       "        -0.040999  , -0.040999  ],\n",
+       "       [-0.2209375 , -0.2209375 , -0.2209375 , ..., -0.2209375 ,\n",
+       "        -0.2209375 , -0.2209375 ],\n",
+       "       [-0.00590313, -0.00590313, -0.00590313, ..., -0.00590313,\n",
+       "        -0.00590313, -0.00590313],\n",
+       "       [-0.0575    , -0.0575    , -0.0575    , ..., -0.0575    ,\n",
+       "        -0.0575    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0195 0.0195 0.0195 ... 0.0175 nan</div><input id='attrs-10d4d2e1-5a34-4a85-833f-88fff72b01da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10d4d2e1-5a34-4a85-833f-88fff72b01da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37392d71-2357-42b4-b2eb-5724357c5a9e' class='xr-var-data-in' type='checkbox'><label for='data-37392d71-2357-42b4-b2eb-5724357c5a9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0195005 ,  0.0195005 ,  0.0195005 , ...,  0.0195005 ,\n",
+       "         0.0195005 ,  0.0195005 ],\n",
+       "       [-0.124375  , -0.124375  , -0.124375  , ..., -0.124375  ,\n",
+       "        -0.124375  , -0.124375  ],\n",
+       "       [-0.08590313, -0.08590313, -0.08590313, ..., -0.08590313,\n",
+       "        -0.08590313, -0.08590313],\n",
+       "       [ 0.0175    ,  0.0175    ,  0.0175    , ...,  0.0175    ,\n",
+       "         0.0175    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-38d6697d-7772-4ee8-a0af-7bbaa895c588' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38d6697d-7772-4ee8-a0af-7bbaa895c588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d1466aa-709a-4b1d-8ac8-6b49d4ad6d0d' class='xr-var-data-in' type='checkbox'><label for='data-3d1466aa-709a-4b1d-8ac8-6b49d4ad6d0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "        22.79279279, 22.79279279],\n",
+       "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
+       "        23.        , 23.        ],\n",
+       "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
+       "        24.725     , 24.725     ],\n",
+       "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-04eade2a-a009-4a0a-9226-082cd6988f4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-04eade2a-a009-4a0a-9226-082cd6988f4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-789cb842-1dda-4082-b8c1-44bc1dcc91c6' class='xr-var-data-in' type='checkbox'><label for='data-789cb842-1dda-4082-b8c1-44bc1dcc91c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "        22.79279279, 22.79279279],\n",
+       "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
+       "        23.        , 23.        ],\n",
+       "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
+       "        24.725     , 24.725     ],\n",
+       "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.943 6.943 6.943 ... 6.17 6.17 nan</div><input id='attrs-7572befa-850c-4a01-98ff-ee37b0200703' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7572befa-850c-4a01-98ff-ee37b0200703' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39de6332-e1e6-4de3-aac4-4d44bd630972' class='xr-var-data-in' type='checkbox'><label for='data-39de6332-e1e6-4de3-aac4-4d44bd630972' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.9434965 , 6.9434965 , 6.9434965 , ..., 6.9434965 , 6.9434965 ,\n",
+       "        6.9434965 ],\n",
+       "       [6.9290625 , 6.9290625 , 6.9290625 , ..., 6.9290625 , 6.9290625 ,\n",
+       "        6.9290625 ],\n",
+       "       [6.25361251, 6.25361251, 6.25361251, ..., 6.25361251, 6.25361251,\n",
+       "        6.25361251],\n",
+       "       [6.17      , 6.17      , 6.17      , ..., 6.17      , 6.17      ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.132 7.132 7.132 ... 6.277 nan</div><input id='attrs-e822a8ac-4b22-4db7-af52-39a44eb461c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e822a8ac-4b22-4db7-af52-39a44eb461c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6beefdc-89f6-49da-bfc0-a7f39c754a2f' class='xr-var-data-in' type='checkbox'><label for='data-e6beefdc-89f6-49da-bfc0-a7f39c754a2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.131998  , 7.131998  , 7.131998  , ..., 7.131998  , 7.131998  ,\n",
+       "        7.131998  ],\n",
+       "       [6.7325    , 6.7325    , 6.7325    , ..., 6.7325    , 6.7325    ,\n",
+       "        6.7325    ],\n",
+       "       [6.24638749, 6.24638749, 6.24638749, ..., 6.24638749, 6.24638749,\n",
+       "        6.24638749],\n",
+       "       [6.2775    , 6.2775    , 6.2775    , ..., 6.2775    , 6.2775    ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>75.0 75.0 75.0 ... 75.0 75.0 nan</div><input id='attrs-e0d11157-0d1d-4f3e-9cdc-1b1c5b04a893' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0d11157-0d1d-4f3e-9cdc-1b1c5b04a893' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dd05efd-6d51-4042-a667-50e4da4f1057' class='xr-var-data-in' type='checkbox'><label for='data-6dd05efd-6d51-4042-a667-50e4da4f1057' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[75., 75., 75., ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., 75., 75., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-b571872b-73a4-44ab-944e-d241fc31c91c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b571872b-73a4-44ab-944e-d241fc31c91c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5e27f4b-82c5-44aa-a239-1479cb755b01' class='xr-var-data-in' type='checkbox'><label for='data-d5e27f4b-82c5-44aa-a239-1479cb755b01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-7d359f8a-a04f-4dc8-bf41-39718799e919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d359f8a-a04f-4dc8-bf41-39718799e919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-605050ed-2f39-4f72-90e0-bded240d8f40' class='xr-var-data-in' type='checkbox'><label for='data-605050ed-2f39-4f72-90e0-bded240d8f40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a022ed4d-4296-4b5a-81f0-4976ff8b8def' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a022ed4d-4296-4b5a-81f0-4976ff8b8def' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4663deb5-ca69-4e5d-a2df-14911cf24dd5' class='xr-var-data-in' type='checkbox'><label for='data-4663deb5-ca69-4e5d-a2df-14911cf24dd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-371ca08f-2b03-4441-a911-637e2015f167' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-371ca08f-2b03-4441-a911-637e2015f167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a6ea023-c0bd-4f52-9e92-af4917c8b7cf' class='xr-var-data-in' type='checkbox'><label for='data-6a6ea023-c0bd-4f52-9e92-af4917c8b7cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3549fb39-42d2-40a9-8f2a-14a494cf6041' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3549fb39-42d2-40a9-8f2a-14a494cf6041' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:47:33+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_Sp</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 287MB\n",
+       "Dimensions:                        (channel: 4, ping_time: 1266,\n",
+       "                                    range_sample: 3534, filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel                        (channel) object 32B 'WBT 747008-15 ES333-...\n",
+       "  * ping_time                      (ping_time) datetime64[ns] 10kB 2021-12-15...\n",
+       "  * range_sample                   (range_sample) int64 28kB 0 1 2 ... 3532 3533\n",
+       "  * filenames                      (filenames) int64 8B 0\n",
+       "Data variables: (12/24)\n",
+       "    Sp                             (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    echo_range                     (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    frequency_nominal              (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    sound_speed                    float64 8B 1.485e+03\n",
+       "    sound_absorption               (channel, ping_time) float64 41kB 0.07527 ...\n",
+       "    temperature                    float64 8B 9.7\n",
+       "    ...                             ...\n",
+       "    beamwidth_athwartship          (channel, ping_time) float64 41kB 7.132 .....\n",
+       "    impedance_transducer           (channel, ping_time) float64 41kB 75.0 ......\n",
+       "    impedance_transceiver          (channel) int64 32B 5400 5400 5400 5400\n",
+       "    receiver_sampling_frequency    (channel) float64 32B 1.5e+06 ... 1.5e+06\n",
+       "    source_filenames               (filenames) <U67 268B 'example_data\\\\ts_sp...\n",
+       "    water_level                    float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:47:33+00:00\n",
+       "    processing_function:          calibrate.compute_Sp"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_Sp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "e14b4f11",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
+    "# print(\"Selected channel:\", tsf_channel)\n",
+    "\n",
+    "# sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "052738a8",
+   "metadata": {},
+   "source": [
+    "### Create the `point_locations` dataset for `compute_TS_spectrum()`\n",
+    "\n",
+    "The public `compute_TS_spectrum()` API expects target locations as an input dataset. Here, we create this dataset for the detected calibration sphere target, including its ping time, channel, range, split-beam angles, and target-window limits."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "fbc2ca91",
+   "metadata": {},
+   "outputs": [
+    {
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+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 213kB\n",
+       "Dimensions:            (target_id: 1265)\n",
+       "Coordinates:\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "    channel            (target_id) &lt;U26 132kB &#x27;WBT 747022-15 ES120-7CD_ES&#x27; .....\n",
+       "    ping_time          (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.66...\n",
+       "Data variables:\n",
+       "    target_range       (target_id) float64 10kB 5.805 5.805 ... 5.781 5.781\n",
+       "    angle_alongship    (target_id) float64 10kB 1.852 2.139 ... -0.00917 0.153\n",
+       "    angle_athwartship  (target_id) float64 10kB 4.524 4.304 ... -0.02378 -0.1533\n",
+       "    target_range_min   (target_id) float64 10kB 5.306 5.306 ... 5.306 5.306\n",
+       "    target_range_max   (target_id) float64 10kB 6.298 6.298 ... 6.298 6.298\n",
+       "    raw_ping_index     (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ed5b5307-5159-43aa-bc50-893097e81b02' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-ed5b5307-5159-43aa-bc50-893097e81b02' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>target_id</span>: 1265</li></ul></div></li><li class='xr-section-item'><input id='section-39da32e2-fd9f-46b6-8001-0236c011f66f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-39da32e2-fd9f-46b6-8001-0236c011f66f' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-858b42ee-b3e2-4075-99ec-eb188fea688c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-858b42ee-b3e2-4075-99ec-eb188fea688c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dca6b996-4390-4001-80b4-a0aa1cbee602' class='xr-var-data-in' type='checkbox'><label for='data-dca6b996-4390-4001-80b4-a0aa1cbee602' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......</div><input id='attrs-409a4481-5143-42d2-9b0f-1c98b383c26c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-409a4481-5143-42d2-9b0f-1c98b383c26c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3461eddb-b81d-43d7-ab3b-7afb7ae00529' class='xr-var-data-in' type='checkbox'><label for='data-3461eddb-b81d-43d7-ab3b-7afb7ae00529' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, ..., &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      shape=(1265,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-2b9200e1-8afa-424e-8a20-12068f24e365' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b9200e1-8afa-424e-8a20-12068f24e365' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e50353f7-bf0b-48a5-9363-6efa241d9125' class='xr-var-data-in' type='checkbox'><label for='data-e50353f7-bf0b-48a5-9363-6efa241d9125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
+       "       &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;],\n",
+       "      shape=(1265,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ddc73db4-2a4d-4da8-9c52-4a8f891b4c65' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ddc73db4-2a4d-4da8-9c52-4a8f891b4c65' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-6bed23da-7f14-4bb7-82de-a8126fb35241' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6bed23da-7f14-4bb7-82de-a8126fb35241' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3898eabb-6795-4afa-8c90-343dde130a87' class='xr-var-data-in' type='checkbox'><label for='data-3898eabb-6795-4afa-8c90-343dde130a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "       5.7811768], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-9fc45e6b-7538-42ab-9647-b40dcc47aa39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9fc45e6b-7538-42ab-9647-b40dcc47aa39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deafdd42-2b9c-4677-99a9-aff16a78da8c' class='xr-var-data-in' type='checkbox'><label for='data-deafdd42-2b9c-4677-99a9-aff16a78da8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "       -0.00917041,  0.15295288], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-2bcca5b4-e93d-4ed9-a246-95e6135e6c8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2bcca5b4-e93d-4ed9-a246-95e6135e6c8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fbaa18d-b4eb-46e0-8a93-b4d8ae1b4740' class='xr-var-data-in' type='checkbox'><label for='data-9fbaa18d-b4eb-46e0-8a93-b4d8ae1b4740' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "       -0.02377829, -0.15330624], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_min</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.306 5.306 5.306 ... 5.306 5.306</div><input id='attrs-500c66bf-999c-43bd-bae8-15116604cea4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-500c66bf-999c-43bd-bae8-15116604cea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43f5cc1d-4a63-45d7-803e-f5441c44532b' class='xr-var-data-in' type='checkbox'><label for='data-43f5cc1d-4a63-45d7-803e-f5441c44532b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.3058488, 5.3058488, 5.3058488, ..., 5.3058488, 5.3058488,\n",
+       "       5.3058488], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_max</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.298 6.298 6.298 ... 6.298 6.298</div><input id='attrs-0eaa7df8-f1c2-4217-8f17-daf77315acc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eaa7df8-f1c2-4217-8f17-daf77315acc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b0304aa-4bf9-46ac-93c6-5c629a599678' class='xr-var-data-in' type='checkbox'><label for='data-7b0304aa-4bf9-46ac-93c6-5c629a599678' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.298096, 6.298096, 6.298096, ..., 6.298096, 6.298096, 6.298096],\n",
+       "      shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ping_index</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-6a57422a-9a20-4f4e-a603-2a0f38326f7a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a57422a-9a20-4f4e-a603-2a0f38326f7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aee484d-cc7f-4631-88a0-759ec98b1df3' class='xr-var-data-in' type='checkbox'><label for='data-9aee484d-cc7f-4631-88a0-759ec98b1df3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li></ul></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 213kB\n",
+       "Dimensions:            (target_id: 1265)\n",
+       "Coordinates:\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "    channel            (target_id) <U26 132kB 'WBT 747022-15 ES120-7CD_ES' .....\n",
+       "    ping_time          (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.66...\n",
+       "Data variables:\n",
+       "    target_range       (target_id) float64 10kB 5.805 5.805 ... 5.781 5.781\n",
+       "    angle_alongship    (target_id) float64 10kB 1.852 2.139 ... -0.00917 0.153\n",
+       "    angle_athwartship  (target_id) float64 10kB 4.524 4.304 ... -0.02378 -0.1533\n",
+       "    target_range_min   (target_id) float64 10kB 5.306 5.306 ... 5.306 5.306\n",
+       "    target_range_max   (target_id) float64 10kB 6.298 6.298 ... 6.298 6.298\n",
+       "    raw_ping_index     (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "point_locations = xr.Dataset(\n",
+    "    {\n",
+    "        \"target_range\": (\"target_id\", [row[\"target_range\"] for row in target_rows]),\n",
+    "        \"angle_alongship\": (\"target_id\", [row[\"angle_alongship\"] for row in target_rows]),\n",
+    "        \"angle_athwartship\": (\"target_id\", [row[\"angle_athwartship\"] for row in target_rows]),\n",
+    "        \"target_range_min\": (\"target_id\", [row[\"target_range_min\"] for row in target_rows]),\n",
+    "        \"target_range_max\": (\"target_id\", [row[\"target_range_max\"] for row in target_rows]),\n",
+    "        \"raw_ping_index\": (\"target_id\", [row[\"raw_ping_index\"] for row in target_rows]),\n",
+    "    },\n",
+    "    coords={\n",
+    "        \"target_id\": np.arange(len(target_rows)),\n",
+    "        \"channel\": (\"target_id\", [row[\"channel\"] for row in target_rows]),\n",
+    "        \"ping_time\": (\"target_id\", [row[\"ping_time\"] for row in target_rows]),\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "point_locations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "e0ca3c72",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "API target position: 509\n",
+      "Raw ping index: 509\n"
+     ]
+    }
+   ],
+   "source": [
+    "api_target_pos = int(\n",
+    "    np.where(point_locations[\"raw_ping_index\"].values == tsf_ping_index)[0][0]\n",
+    ")\n",
+    "\n",
+    "print(\"API target position:\", api_target_pos)\n",
+    "print(\"Raw ping index:\", point_locations[\"raw_ping_index\"].isel(target_id=api_target_pos).values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4dae12f7",
+   "metadata": {},
+   "source": [
+    "Before comparing TS spectra, we verify that the frequency grid produced by the API matches the CRIMAC reference grid."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "faf6fdb5",
+   "metadata": {},
+   "source": [
+    "#### API validation using frequency_resolution\n",
+    "\n",
+    "Here we call `compute_TS_spectrum()` using the same frequency spacing as the CRIMAC reference output. In this mode, the function infers the FFT size internally from the requested frequency resolution."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "0e515b3a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CRIMAC frequency resolution: 80.08008008007891\n"
+     ]
+    }
+   ],
+   "source": [
+    "frequency_resolution = float(np.nanmedian(np.diff(ref_ts[\"f_m\"])))\n",
+    "print(\"CRIMAC frequency resolution:\", frequency_resolution)\n",
+    "\n",
+    "frequency_expected = (\n",
+    "    ref_ts[\"f_m\"][0]\n",
+    "    + np.arange(ref_ts[\"f_m\"].size) * frequency_resolution\n",
+    ")\n",
+    "\n",
+    "assert np.allclose(frequency_expected, ref_ts[\"f_m\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30a2ffdd",
+   "metadata": {},
+   "source": [
+    "We now call the public `compute_TS_spectrum()` API using the detected `point_locations` and the same frequency resolution as the CRIMAC reference grid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "35823982",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "288c8f6e570547068b2e610390ce249e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "WBT 747022-15 ES120-7CD_ES:   0%|          | 0/1265 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       ".xr-var-item > input + label {\n",
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+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
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+       ".xr-array-wrap > input:enabled + label,\n",
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+       "\n",
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+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) &lt;U26 104B &#x27;WBT 747022-15 ES120-7CD_ES&#x27;\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:22+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a577f8c6-d6f0-40b6-a146-74ba6cf37d4c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-a577f8c6-d6f0-40b6-a146-74ba6cf37d4c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-0ba12740-d1ce-40da-997d-3da1469b3a09' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0ba12740-d1ce-40da-997d-3da1469b3a09' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-9da823e5-62fd-4a15-9328-ef90ec138ad2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9da823e5-62fd-4a15-9328-ef90ec138ad2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f03af67-de55-4761-a728-7e98edc188e0' class='xr-var-data-in' type='checkbox'><label for='data-9f03af67-de55-4761-a728-7e98edc188e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-83f25625-cd7c-49b8-9fd7-06f920564fed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83f25625-cd7c-49b8-9fd7-06f920564fed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abc85376-36c7-4428-a97e-75ea82185e8d' class='xr-var-data-in' type='checkbox'><label for='data-abc85376-36c7-4428-a97e-75ea82185e8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-9594d9f1-4214-4e78-aff4-36a68cde1690' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9594d9f1-4214-4e78-aff4-36a68cde1690' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa7cb116-0e97-4d7c-a7a3-6e6a97f9abfa' class='xr-var-data-in' type='checkbox'><label for='data-aa7cb116-0e97-4d7c-a7a3-6e6a97f9abfa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-396171c0-37ef-496b-a746-3dfed2186e7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-396171c0-37ef-496b-a746-3dfed2186e7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-777af835-7f85-4f6d-a59c-7503467effd3' class='xr-var-data-in' type='checkbox'><label for='data-777af835-7f85-4f6d-a59c-7503467effd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5577afeb-6e1d-4a3e-9722-e713d1ef83ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-5577afeb-6e1d-4a3e-9722-e713d1ef83ac' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-0b94b868-71b4-4f51-bb13-1d44430c8f71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b94b868-71b4-4f51-bb13-1d44430c8f71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da9c00ae-a9e4-45ca-b468-663e6f202cf1' class='xr-var-data-in' type='checkbox'><label for='data-da9c00ae-a9e4-45ca-b468-663e6f202cf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "         -50.89344838, -51.56443826],\n",
+       "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
+       "         -53.05996696, -53.87369709],\n",
+       "        [-44.99852747, -45.01598528, -45.15371319, ..., -49.13378461,\n",
+       "         -49.03861423, -49.611581  ],\n",
+       "        ...,\n",
+       "        [-44.48077623, -44.55109807, -44.38414421, ..., -41.62880734,\n",
+       "         -41.47933602, -41.45510495],\n",
+       "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
+       "         -41.36476302, -41.37227431],\n",
+       "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-adee60d9-a479-4c80-be26-ba9fe72cf471' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adee60d9-a479-4c80-be26-ba9fe72cf471' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3155626b-9e62-4baf-8b0b-992ddf95a4c9' class='xr-var-data-in' type='checkbox'><label for='data-3155626b-9e62-4baf-8b0b-992ddf95a4c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-3fa2d7d0-e4f6-47e8-8d74-16d2cb2e6224' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fa2d7d0-e4f6-47e8-8d74-16d2cb2e6224' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cffa51f0-84b1-439f-9c0f-c2078f8470bc' class='xr-var-data-in' type='checkbox'><label for='data-cffa51f0-84b1-439f-9c0f-c2078f8470bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-bb2b8e2a-4c31-4284-b464-c5dc1352aeca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb2b8e2a-4c31-4284-b464-c5dc1352aeca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee2142c6-eedc-42bb-9fb0-f1b30d9352c4' class='xr-var-data-in' type='checkbox'><label for='data-ee2142c6-eedc-42bb-9fb0-f1b30d9352c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-b2cd90cd-2c6d-4c4e-96ea-78623fc50042' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2cd90cd-2c6d-4c4e-96ea-78623fc50042' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-126281c8-9e4d-4ea5-b809-8ad391850196' class='xr-var-data-in' type='checkbox'><label for='data-126281c8-9e4d-4ea5-b809-8ad391850196' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
+       "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-1496af1d-a1c2-434d-a4d7-d14c2a20f758' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1496af1d-a1c2-434d-a4d7-d14c2a20f758' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6985299-43ad-498c-9d3e-1cf15f43b2bd' class='xr-var-data-in' type='checkbox'><label for='data-e6985299-43ad-498c-9d3e-1cf15f43b2bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-e2928165-5c94-4910-b17f-3b92a04a08eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2928165-5c94-4910-b17f-3b92a04a08eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11b9240d-e7f5-49fd-b322-0bade58745c1' class='xr-var-data-in' type='checkbox'><label for='data-11b9240d-e7f5-49fd-b322-0bade58745c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa7a2b1d-059f-4236-b5cf-b0acf3c7c52e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fa7a2b1d-059f-4236-b5cf-b0acf3c7c52e' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:48:22+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) <U67 268B 'example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:22+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_TS_spectrum_fr = ep.calibrate.compute_TS_spectrum(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    "    point_locations=point_locations,\n",
+    "    frequency_resolution=frequency_resolution,\n",
+    ")\n",
+    "\n",
+    "ds_TS_spectrum_fr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df591d08",
+   "metadata": {},
+   "source": [
+    "We extract the TS spectrum corresponding to the CRIMAC reference target and compare it directly with the exported CRIMAC spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "56d8ea09",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "API frequency points: 1000\n",
+      "CRIMAC frequency points: 1000\n",
+      "Frequency grids match: True\n",
+      "RMSE (dB): 0.016260102031311115\n",
+      "Max abs diff (dB): 0.07143718847996894\n"
+     ]
+    }
+   ],
+   "source": [
+    "ts_api_fr = (\n",
+    "    ds_TS_spectrum_fr[\"TS_spectrum\"]\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(target_id=api_target_pos)\n",
+    ")\n",
+    "\n",
+    "diff_fr = ts_api_fr.values - ref_ts[\"TS_m\"]\n",
+    "\n",
+    "print(\"API frequency points:\", ds_TS_spectrum_fr[\"frequency\"].size)\n",
+    "print(\"CRIMAC frequency points:\", ref_ts[\"f_m\"].size)\n",
+    "\n",
+    "print(\n",
+    "    \"Frequency grids match:\",\n",
+    "    np.allclose(ds_TS_spectrum_fr[\"frequency\"].values, ref_ts[\"f_m\"])\n",
+    ")\n",
+    "\n",
+    "print(\"RMSE (dB):\", np.sqrt(np.nanmean(diff_fr**2)))\n",
+    "print(\"Max abs diff (dB):\", np.nanmax(np.abs(diff_fr)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "c980db68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert np.allclose(\n",
+    "    ds_TS_spectrum_fr[\"frequency\"].values,\n",
+    "    ref_ts[\"f_m\"],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "83ee6444",
+   "metadata": {},
+   "source": [
+    "### Run the public API using an explicit FFT length (NFFT)\n",
+    "\n",
+    "In the previous example, the frequency grid was specified through a target frequency resolution. Alternatively, `compute_TS_spectrum()` can be called with an explicit FFT length (`NFFT`), allowing direct control over the frequency discretisation used in the TS-spectrum calculation.\n",
+    "\n",
+    "Both approaches should produce equivalent results when they generate the same frequency grid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "c96bb8ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5dec63c8df834dd788fb135d4ee90429",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "WBT 747022-15 ES120-7CD_ES:   0%|          | 0/1265 [00:00<?, ?it/s]"
+      ]
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+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) &lt;U26 104B &#x27;WBT 747022-15 ES120-7CD_ES&#x27;\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:48+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4145e14c-9b49-4081-b726-de55f7550c22' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4145e14c-9b49-4081-b726-de55f7550c22' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-df60d1b1-c4b3-4445-b71e-c6e1fc3a2a5e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-df60d1b1-c4b3-4445-b71e-c6e1fc3a2a5e' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-8dd22c23-9327-472f-b36b-fa312e2fbd0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8dd22c23-9327-472f-b36b-fa312e2fbd0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e438593c-62b5-4b4e-821b-bc1dfc97beea' class='xr-var-data-in' type='checkbox'><label for='data-e438593c-62b5-4b4e-821b-bc1dfc97beea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-3e8055df-c129-4ed6-979d-12ed199422b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e8055df-c129-4ed6-979d-12ed199422b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35821d9-abab-470a-bc4a-6881a65bef48' class='xr-var-data-in' type='checkbox'><label for='data-b35821d9-abab-470a-bc4a-6881a65bef48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-a2f04f2f-0b9b-46d0-a7f2-bdc0edb76d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2f04f2f-0b9b-46d0-a7f2-bdc0edb76d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eadbf93b-afaf-40b5-9c16-331c32443d75' class='xr-var-data-in' type='checkbox'><label for='data-eadbf93b-afaf-40b5-9c16-331c32443d75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a6b88e88-3663-4f6e-be49-81d5bc8ea65a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6b88e88-3663-4f6e-be49-81d5bc8ea65a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be6bfcc1-6178-4737-925c-6b08fe4ca72d' class='xr-var-data-in' type='checkbox'><label for='data-be6bfcc1-6178-4737-925c-6b08fe4ca72d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-043498cb-e5ee-4657-a5cb-a6a1c79ad995' class='xr-section-summary-in' type='checkbox' checked /><label for='section-043498cb-e5ee-4657-a5cb-a6a1c79ad995' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-a550c822-08d1-4fb7-bc7b-2532cf6279ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a550c822-08d1-4fb7-bc7b-2532cf6279ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8711bf66-67a5-4745-bb6f-867c71524ea1' class='xr-var-data-in' type='checkbox'><label for='data-8711bf66-67a5-4745-bb6f-867c71524ea1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "         -50.89344838, -51.56443826],\n",
+       "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
+       "         -53.05996696, -53.87369709],\n",
+       "        [-44.99852747, -45.01598528, -45.15371319, ..., -49.13378461,\n",
+       "         -49.03861423, -49.611581  ],\n",
+       "        ...,\n",
+       "        [-44.48077623, -44.55109807, -44.38414421, ..., -41.62880734,\n",
+       "         -41.47933602, -41.45510495],\n",
+       "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
+       "         -41.36476302, -41.37227431],\n",
+       "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-da786fe7-f92a-4ce6-8295-42f918ac04ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da786fe7-f92a-4ce6-8295-42f918ac04ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-283521b8-22a3-4b25-b915-d45c0f602f6b' class='xr-var-data-in' type='checkbox'><label for='data-283521b8-22a3-4b25-b915-d45c0f602f6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-59ab1373-b1f1-43a9-a061-daca06355610' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59ab1373-b1f1-43a9-a061-daca06355610' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a425cfce-1395-4517-90e0-8b174b77b1c5' class='xr-var-data-in' type='checkbox'><label for='data-a425cfce-1395-4517-90e0-8b174b77b1c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-46bd61c2-9143-4f8c-b8e1-737c71499d8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46bd61c2-9143-4f8c-b8e1-737c71499d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-123eed60-f204-4adf-864f-e653cbcc3112' class='xr-var-data-in' type='checkbox'><label for='data-123eed60-f204-4adf-864f-e653cbcc3112' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d6eae573-18ff-4e87-aebd-776d803e68e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6eae573-18ff-4e87-aebd-776d803e68e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f8b5f57-193a-4307-8042-b7c150f6f916' class='xr-var-data-in' type='checkbox'><label for='data-2f8b5f57-193a-4307-8042-b7c150f6f916' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
+       "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-ca8be6dd-b610-4ae9-b950-0f0c548b4285' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca8be6dd-b610-4ae9-b950-0f0c548b4285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de982c12-715b-4453-835a-32c729905ed9' class='xr-var-data-in' type='checkbox'><label for='data-de982c12-715b-4453-835a-32c729905ed9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-94862f3a-17db-4df1-9a23-fb77436b7e55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94862f3a-17db-4df1-9a23-fb77436b7e55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eb0b7c5-a01d-4ea7-bc35-4ed7adfd7657' class='xr-var-data-in' type='checkbox'><label for='data-5eb0b7c5-a01d-4ea7-bc35-4ed7adfd7657' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f064f7a9-6886-41b2-814b-cd5a5d850087' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f064f7a9-6886-41b2-814b-cd5a5d850087' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:48:48+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) <U67 268B 'example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:48+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f_crimac = ref_ts[\"f_m\"]\n",
+    "n_f_points = f_crimac.size\n",
+    "NFFT = int(2 ** np.ceil(np.log2(n_f_points)))\n",
+    "\n",
+    "ds_TS_spectrum_nfft = ep.calibrate.compute_TS_spectrum(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    "    point_locations=point_locations,\n",
+    "    NFFT=NFFT,\n",
+    "    n_f_points=n_f_points,\n",
+    "    split_front=0.25,\n",
+    "    window=None,\n",
+    ")\n",
+    "\n",
+    "ds_TS_spectrum_nfft"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "99bff1bb",
+   "metadata": {},
+   "source": [
+    "We extract the TS spectrum produced with the explicit `NFFT` setting, verify that it is defined on the same frequency grid as the CRIMAC reference, and compute the RMSE and maximum absolute difference between the two spectra."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "19c69452",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NFFT: 1024\n",
+      "API frequency points: 1000\n",
+      "CRIMAC frequency points: 1000\n",
+      "Frequency grids match: True\n",
+      "RMSE (dB): 0.016260102031311115\n",
+      "Max abs diff (dB): 0.07143718847996894\n"
+     ]
+    }
+   ],
+   "source": [
+    "ts_api_nfft = (\n",
+    "    ds_TS_spectrum_nfft[\"TS_spectrum\"]\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(target_id=api_target_pos)\n",
+    ")\n",
+    "\n",
+    "f_api_nfft = ds_TS_spectrum_nfft[\"frequency\"].values\n",
+    "f_crimac = ref_ts[\"f_m\"]\n",
+    "\n",
+    "print(\"NFFT:\", NFFT)\n",
+    "print(\"API frequency points:\", f_api_nfft.size)\n",
+    "print(\"CRIMAC frequency points:\", f_crimac.size)\n",
+    "print(\"Frequency grids match:\", np.allclose(f_api_nfft, f_crimac))\n",
+    "\n",
+    "diff_nfft = ts_api_nfft.values - ref_ts[\"TS_m\"]\n",
+    "\n",
+    "print(\"RMSE (dB):\", np.sqrt(np.nanmean(diff_nfft**2)))\n",
+    "print(\"Max abs diff (dB):\", np.nanmax(np.abs(diff_nfft)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f279a418",
+   "metadata": {},
+   "source": [
+    "The NFFT and frequency_resolution interfaces produce identical TS-spectrum results for this dataset, demonstrating that both parameterisations are equivalent when they define the same frequency grid."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1572b77b",
+   "metadata": {},
+   "source": [
+    "### Summarise CRIMAC, manual, and API differences\n",
+    "\n",
+    "We summarise pairwise differences between the CRIMAC reference output, the manual helper-chain reconstruction, and the public API output. This checks whether the public API reproduces the same final TS-spectrum product as both the CRIMAC reference and the step-by-step validation workflow."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "5016286d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>n</th>\n",
+       "      <th>CRIMAC mean</th>\n",
+       "      <th>echopype mean</th>\n",
+       "      <th>mean diff</th>\n",
+       "      <th>median diff</th>\n",
+       "      <th>RMSE</th>\n",
+       "      <th>max abs diff</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>TS_m dB: CRIMAC vs manual</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.615550</td>\n",
+       "      <td>-41.616483</td>\n",
+       "      <td>-0.000932</td>\n",
+       "      <td>-0.000277</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134085</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>TS_m dB: CRIMAC vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.615550</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>-0.002203</td>\n",
+       "      <td>-0.000048</td>\n",
+       "      <td>0.016260</td>\n",
+       "      <td>0.071437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>TS_m dB: manual vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.616483</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>-0.001271</td>\n",
+       "      <td>0.000360</td>\n",
+       "      <td>0.265814</td>\n",
+       "      <td>5.135526</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Y_pc_t_m dB: CRIMAC vs manual</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.450622</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>0.002383</td>\n",
+       "      <td>-0.002111</td>\n",
+       "      <td>0.288531</td>\n",
+       "      <td>5.399668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Y_pc_t_m dB: CRIMAC vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.450622</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>0.002383</td>\n",
+       "      <td>-0.002111</td>\n",
+       "      <td>0.288531</td>\n",
+       "      <td>5.399668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Y_pc_t_m dB: manual vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        variable     n  CRIMAC mean  echopype mean  mean diff  \\\n",
+       "0      TS_m dB: CRIMAC vs manual  1000   -41.615550     -41.616483  -0.000932   \n",
+       "1         TS_m dB: CRIMAC vs API  1000   -41.615550     -41.617754  -0.002203   \n",
+       "2         TS_m dB: manual vs API  1000   -41.616483     -41.617754  -0.001271   \n",
+       "3  Y_pc_t_m dB: CRIMAC vs manual  1000   -35.450622     -35.448239   0.002383   \n",
+       "4     Y_pc_t_m dB: CRIMAC vs API  1000   -35.450622     -35.448239   0.002383   \n",
+       "5     Y_pc_t_m dB: manual vs API  1000   -35.448239     -35.448239   0.000000   \n",
+       "\n",
+       "   median diff      RMSE  max abs diff  \n",
+       "0    -0.000277  0.267273      5.134085  \n",
+       "1    -0.000048  0.016260      0.071437  \n",
+       "2     0.000360  0.265814      5.135526  \n",
+       "3    -0.002111  0.288531      5.399668  \n",
+       "4    -0.002111  0.288531      5.399668  \n",
+       "5     0.000000  0.000000      0.000000  "
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rows_api = []\n",
+    "\n",
+    "def add_three_way(name, crimac, manual, api):\n",
+    "    rows_api.append(compare_summary(f\"{name}: CRIMAC vs manual\", crimac, manual))\n",
+    "    rows_api.append(compare_summary(f\"{name}: CRIMAC vs API\", crimac, api))\n",
+    "    rows_api.append(compare_summary(f\"{name}: manual vs API\", manual, api))\n",
+    "\n",
+    "add_three_way(\n",
+    "    \"TS_m dB\",\n",
+    "    ref_ts[\"TS_m\"],\n",
+    "    TS_m,\n",
+    "    ts_api_fr.values,\n",
+    ")\n",
+    "\n",
+    "add_three_way(\n",
+    "    \"Y_pc_t_m dB\",\n",
+    "    db20(ref_ts[\"Y_pc_t_m\"]),\n",
+    "    db20(Y_pc_t_m),\n",
+    "    db20(\n",
+    "        _compute_ts_spectrum(\n",
+    "            pc_target=y_pc_t_n,\n",
+    "            mf_auto_red=y_mf_auto_red_n,\n",
+    "            NFFT=n_f_points,\n",
+    "            frequency=f_m,\n",
+    "            fs_dec=fs_dec,\n",
+    "        )[0]\n",
+    "    ),\n",
+    ")\n",
+    "\n",
+    "summary_api = pd.DataFrame(rows_api)\n",
+    "summary_api"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5de90b9a",
+   "metadata": {},
+   "source": [
+    "** NOTE ** - ware we using als th NFFT or freq here?\n",
+    "\n",
+    "\n",
+    " ** NOTE ** to remove Llod - The API and manual workflows produce identical target spectra (Y_pc_t_m), while the final API TS spectrum agrees more closely with the CRIMAC reference. This suggests that the API implementation reproduces the calibration and correction steps more faithfully than the simplified manual reconstruction used in this notebook.\n",
+    "\n",
+    "The key observation is really:\n",
+    "\n",
+    "Y_pc_t_m: manual vs API\n",
+    "RMSE = 0\n",
+    "\n",
+    "but\n",
+    "\n",
+    "TS_m: manual vs API\n",
+    "RMSE = 0.266 dB"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "24167859",
+   "metadata": {},
+   "source": [
+    "We inspect one detected target from the public API output and compare it with the CRIMAC reference target. The diagnostic panel shows the target position in the pulse-compressed echogram, the corresponding TS spectrum, and the split-beam angle location."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "a8ee9fe9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "target_to_plot: 509\n",
+      "api target_id: 509\n",
+      "api ping index: 509\n",
+      "api target range: 5.79306\n",
+      "api theta/phi: 0.1980538342357811 2.1279301087201414\n",
+      "CRIMAC ping index: 509\n",
+      "CRIMAC range: 5.79306\n",
+      "CRIMAC theta/phi: <xarray.DataArray 'angle_alongship' ()> Size: 8B\n",
+      "array(0.19805383)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975 <xarray.DataArray 'angle_athwartship' ()> Size: 8B\n",
+      "array(2.12793011)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x800 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# --- Choose API target to inspect ---\n",
+    "target_to_plot = 509\n",
+    "\n",
+    "ch = tsf_channel\n",
+    "\n",
+    "api_color = \"black\"\n",
+    "crimac_color = \"orange\"\n",
+    "range_color = api_color\n",
+    "\n",
+    "# CRIMAC reference target\n",
+    "crimac_ping_idx = tsf_ping_index\n",
+    "crimac_range = r_t\n",
+    "crimac_theta = theta_t\n",
+    "crimac_phi = phi_t\n",
+    "\n",
+    "f_crimac = ref_ts[\"f_m\"]\n",
+    "ts_crimac = ref_ts[\"TS_m\"]\n",
+    "\n",
+    "# API target selection\n",
+    "ts_api_plot = (\n",
+    "    ds_TS_spectrum_fr[\"TS_spectrum\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "api_ping_time = (\n",
+    "    ds_TS_spectrum_fr[\"ping_time\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "f_api_plot = ds_TS_spectrum_fr[\"frequency\"].values\n",
+    "\n",
+    "target_range_plot = float(\n",
+    "    ds_TS_spectrum_fr[\"target_range\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "theta_plot = float(\n",
+    "    ds_TS_spectrum_fr[\"angle_alongship\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "phi_plot = float(\n",
+    "    ds_TS_spectrum_fr[\"angle_athwartship\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "api_ping_idx_plot = int(\n",
+    "    np.argmin(\n",
+    "        np.abs(\n",
+    "            cal_obj.beam[\"ping_time\"].values.astype(\"datetime64[ns]\")\n",
+    "            - np.datetime64(api_ping_time, \"ns\")\n",
+    "        )\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "print(\"target_to_plot:\", target_to_plot)\n",
+    "print(\"api target_id:\", ds_TS_spectrum_fr[\"target_id\"].isel(target_id=target_to_plot).values)\n",
+    "print(\"api ping index:\", api_ping_idx_plot)\n",
+    "print(\"api target range:\", target_range_plot)\n",
+    "print(\"api theta/phi:\", theta_plot, phi_plot)\n",
+    "print(\"CRIMAC ping index:\", crimac_ping_idx)\n",
+    "print(\"CRIMAC range:\", crimac_range)\n",
+    "print(\"CRIMAC theta/phi:\", crimac_theta, crimac_phi)\n",
+    "\n",
+    "# --- Echogram from public API Sp output ---\n",
+    "ping_start = 400\n",
+    "ping_end = 650\n",
+    "\n",
+    "echogram_db = (\n",
+    "    ds_Sp[\"Sp\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(ping_time=slice(ping_start, ping_end + 1))\n",
+    "    .transpose(\"range_sample\", \"ping_time\")\n",
+    ")\n",
+    "\n",
+    "r_plot = (\n",
+    "    cal_obj.range_meter\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(ping_time=ping_start)\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "ping_no = np.arange(ping_start, ping_end + 1)\n",
+    "valid_r = np.isfinite(r_plot)\n",
+    "\n",
+    "fig = plt.figure(figsize=(11, 8))\n",
+    "gs = fig.add_gridspec(\n",
+    "    2,\n",
+    "    2,\n",
+    "    width_ratios=[3, 1],\n",
+    "    height_ratios=[1.4, 1],\n",
+    ")\n",
+    "\n",
+    "ax0 = fig.add_subplot(gs[0, :])\n",
+    "ax1 = fig.add_subplot(gs[1, 0])\n",
+    "ax2 = fig.add_subplot(gs[1, 1])\n",
+    "\n",
+    "# --- Echogram ---\n",
+    "im = ax0.pcolormesh(\n",
+    "    ping_no,\n",
+    "    r_plot[valid_r],\n",
+    "    echogram_db.values[valid_r, :],\n",
+    "    shading=\"auto\",\n",
+    "    vmin=-110,\n",
+    "    vmax=-40,\n",
+    ")\n",
+    "\n",
+    "ax0.axvline(\n",
+    "    crimac_ping_idx,\n",
+    "    color=crimac_color,\n",
+    "    linewidth=2,\n",
+    "    label=f\"CRIMAC ping index: {crimac_ping_idx}\",\n",
+    ")\n",
+    "\n",
+    "ax0.axvline(\n",
+    "    api_ping_idx_plot,\n",
+    "    color=api_color,\n",
+    "    linestyle=\"--\",\n",
+    "    linewidth=2,\n",
+    "    label=f\"API target ping index: {api_ping_idx_plot}\",\n",
+    ")\n",
+    "\n",
+    "ax0.axhline(5.3, color=\"white\", linestyle=\"--\", linewidth=1)\n",
+    "ax0.axhline(6.3, color=\"white\", linestyle=\"--\", linewidth=1)\n",
+    "\n",
+    "ax0.axhline(\n",
+    "    crimac_range,\n",
+    "    color=crimac_color,\n",
+    "    linewidth=1.5,\n",
+    "    label=\"CRIMAC target range\",\n",
+    ")\n",
+    "\n",
+    "ax0.axhline(\n",
+    "    target_range_plot,\n",
+    "    color=range_color,\n",
+    "    linewidth=1.5,\n",
+    "    linestyle=\"--\",\n",
+    "    label=\"API target range\",\n",
+    ")\n",
+    "\n",
+    "ax0.set_ylim(8, 3)\n",
+    "ax0.set_xlabel(\"Ping index\")\n",
+    "ax0.set_ylabel(\"Range (m)\")\n",
+    "ax0.set_title(\"Broadband Sp echogram\")\n",
+    "ax0.legend(loc=\"upper right\")\n",
+    "\n",
+    "cbar = plt.colorbar(im, ax=ax0)\n",
+    "cbar.set_label(\"Sp (dB)\")\n",
+    "\n",
+    "# --- TS(f) ---\n",
+    "ax1.plot(\n",
+    "    f_crimac / 1000,\n",
+    "    ts_crimac,\n",
+    "    color=crimac_color,\n",
+    "    linewidth=2,\n",
+    "    label=\"CRIMAC reference\",\n",
+    ")\n",
+    "\n",
+    "ax1.plot(\n",
+    "    f_api_plot / 1000,\n",
+    "    ts_api_plot.values,\n",
+    "    color=api_color,\n",
+    "    linestyle=\"--\",\n",
+    "    linewidth=2,\n",
+    "    label=\"echopype API TS_spectrum\",\n",
+    ")\n",
+    "\n",
+    "ax1.set_xlabel(\"Frequency (kHz)\")\n",
+    "ax1.set_ylabel(\"TS(f) dB\")\n",
+    "ax1.set_title(\"TS(f)\")\n",
+    "ax1.grid(True)\n",
+    "ax1.legend()\n",
+    "\n",
+    "# --- Circular angle plot ---\n",
+    "beam_limit = 7.0\n",
+    "circle = plt.Circle((0, 0), beam_limit, fill=False, linestyle=\"--\")\n",
+    "ax2.add_patch(circle)\n",
+    "\n",
+    "ax2.axhline(0, color=\"grey\", linewidth=0.8)\n",
+    "ax2.axvline(0, color=\"grey\", linewidth=0.8)\n",
+    "\n",
+    "ax2.scatter(\n",
+    "    crimac_phi,\n",
+    "    crimac_theta,\n",
+    "    s=90,\n",
+    "    color=crimac_color,\n",
+    "    label=\"CRIMAC\",\n",
+    ")\n",
+    "\n",
+    "ax2.scatter(\n",
+    "    phi_plot,\n",
+    "    theta_plot,\n",
+    "    s=70,\n",
+    "    color=api_color,\n",
+    "    marker=\"x\",\n",
+    "    label=\"API\",\n",
+    ")\n",
+    "\n",
+    "ax2.set_xlim(-beam_limit, beam_limit)\n",
+    "ax2.set_ylim(-beam_limit, beam_limit)\n",
+    "ax2.set_aspect(\"equal\", adjustable=\"box\")\n",
+    "\n",
+    "ax2.set_xlabel(\"Athwartship angle (°)\")\n",
+    "ax2.set_ylabel(\"Alongship angle (°)\")\n",
+    "ax2.set_title(\"Target angle\")\n",
+    "\n",
+    "ax2.text(\n",
+    "    0.98,\n",
+    "    0.02,\n",
+    "    f\"API range = {target_range_plot:.2f} m\\n\"\n",
+    "    f\"API along = {theta_plot:.2f}°\\n\"\n",
+    "    f\"API athw. = {phi_plot:.2f}°\\n\"\n",
+    "    f\"CRIMAC range = {crimac_range:.2f} m\\n\"\n",
+    "    f\"CRIMAC along = {crimac_theta:.2f}°\\n\"\n",
+    "    f\"CRIMAC athw. = {crimac_phi:.2f}°\",\n",
+    "    transform=ax2.transAxes,\n",
+    "    ha=\"right\",\n",
+    "    va=\"bottom\",\n",
+    "    fontsize=8,\n",
+    ")\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a70f471",
+   "metadata": {},
+   "source": [
+    "Print of import and their version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "7d490e20",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Python: 3.12.13\n",
+      "echopype: 0.11.2.dev22+gc1a2a5660\n",
+      "numpy: 2.4.4\n",
+      "pandas: 3.0.2\n",
+      "xarray: 2026.4.0\n",
+      "matplotlib: 3.10.9\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "\n",
+    "print(\"Python:\", sys.version.split()[0])\n",
+    "print(\"echopype:\", ep.__version__)\n",
+    "print(\"numpy:\", np.__version__)\n",
+    "print(\"pandas:\", pd.__version__)\n",
+    "print(\"xarray:\", xr.__version__)\n",
+    "print(\"matplotlib:\", plt.matplotlib.__version__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5923b86e",
+   "metadata": {},
+   "source": [
+    "End of notebook."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "echopype-examples",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/images/gallery/11_getting_started_FM_TS.png b/notebooks/images/gallery/11_getting_started_FM_TS.png
new file mode 100644
index 0000000..d733bb7
Binary files /dev/null and b/notebooks/images/gallery/11_getting_started_FM_TS.png differ
diff --git a/notebooks/index.md b/notebooks/index.md
index 2610d48..eb23f4b 100644
--- a/notebooks/index.md
+++ b/notebooks/index.md
@@ -1,17 +1,15 @@
 # Echopype examples notebooks
 
-Jupyter notebooks demonstrating [Echopype](https://echopype.readthedocs.io) capabilities and usage.
+Jupyter notebooks demonstrating [Echopype](https://echopype.readthedocs.io) capabilities and usage. The notebooks in this site can be run locally with a [conda](https://docs.conda.io) environment created following the [instructions in the repository README.md](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-locally-on-your-machine).
 
-## Gallery
+If you want to try these notebooks on Binder, follow instructions [here](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-on-the-cloud-via-binder). However, due to the limited resources on Binder, the execution of some notebooks may fail as noted above.
+
+Please see the last cell in each notebook to see the version of Echopype and important dependencies the notebook was last run with.
+
+<!-- show the gallery -->
 
 ```{datatemplate:yaml} gallery.yml
 :template: gallery-cards.jinja
 ```
 
-## Running the notebooks
 
-The notebooks in this site can be run locally with a [conda](https://docs.conda.io) environment created following the [instructions in the repository README.md](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-locally-on-your-machine).
-
-If you want to try these notebooks on Binder, follow instructions [here](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-on-the-cloud-via-binder). However, due to the limited resources on Binder, the execution of some notebooks may fail as noted above.
-
-Please see the last cell in each notebook to see the version of Echopype and important dependencies the notebook was last run with.
diff --git a/notebooks/utils/data.py b/notebooks/utils/data.py
new file mode 100644
index 0000000..b89357a
--- /dev/null
+++ b/notebooks/utils/data.py
@@ -0,0 +1,62 @@
+from pathlib import Path
+import pooch
+
+EXAMPLE_DATA_DIR = Path("example_data")
+
+DATASETS = {
+    "ts_spectrum_example_data": {
+        "release": "example-data-v1",
+        "asset": "ts_spectrum_example_data.zip",
+        "sha256": "A35A1108DCFAFAE725D826FFA23EA2E111FDB420E7CE433E49E1797381BB6763",
+        "files": [
+            "IMR-D20211215-T143432-TSf.raw",
+            "crimac_tsf_reference_outputs.npz",
+        ],
+    },
+}
+
+def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
+    """Download and extract an example dataset if it is not available locally."""
+    if name not in DATASETS:
+        raise ValueError(f"Unknown dataset: {name}")
+
+    dataset = DATASETS[name]
+    dataset_dir = data_dir / name
+
+    expected_files = [dataset_dir / file for file in dataset["files"]]
+
+    if all(file.exists() for file in expected_files):
+        print(f"Using local dataset: {dataset_dir}")
+        return dataset_dir
+
+    print(f"Downloading dataset: {name}")
+
+    fetcher = pooch.create(
+        path=data_dir,
+        base_url=(
+            "https://github.com/echostack-org/echopype-examples/"
+            f"releases/download/{dataset['release']}/"
+        ),
+        registry={
+            dataset["asset"]: f"sha256:{dataset['sha256']}",
+        },
+    )
+
+    zip_path = Path(
+        fetcher.fetch(
+            dataset["asset"],
+            processor=pooch.Unzip(),
+        )
+    )
+
+    zip_path.unlink(missing_ok=True)
+
+    missing_files = [file for file in expected_files if not file.exists()]
+    if missing_files:
+        raise FileNotFoundError(
+            "Dataset download/extraction finished, but some expected files "
+            "are missing: "
+            + ", ".join(str(file) for file in missing_files)
+        )
+
+    return dataset_dir
\ No newline at end of file