diff --git a/.codecov.yml b/.codecov.yml index 5a94096..4af5eb2 100644 --- a/.codecov.yml +++ b/.codecov.yml @@ -1,14 +1,14 @@ coverage: status: - project: # more options at https://docs.codecov.com/docs/commit-status + project: # more options at https://docs.codecov.com/docs/commit-status default: target: auto # use the coverage from the base commit, fail if coverage is lower - threshold: 0% # allow the coverage to drop by + threshold: 0% # allow the coverage to drop by comment: layout: " diff, flags, files" behavior: default require_changes: false - require_base: false # [true :: must have a base report to post] - require_head: false # [true :: must have a head report to post] + require_base: false # [true :: must have a base report to post] + require_head: false # [true :: must have a head report to post] hide_project_coverage: false # [true :: only show coverage on the git diff aka patch coverage] diff --git a/.codespell/ignore_words.txt b/.codespell/ignore_words.txt index 9757d7c..04b4fcf 100644 --- a/.codespell/ignore_words.txt +++ b/.codespell/ignore_words.txt @@ -4,8 +4,5 @@ ;; abbreviation for "materials" often used in a journal title mater -;; alternative use of socioeconomic -socio-economic - ;; Frobenius norm used in np.linalg.norm fro diff --git a/.flake8 b/.flake8 index 2d2cb16..04d2d0b 100644 --- a/.flake8 +++ b/.flake8 @@ -1,3 +1,5 @@ +# As of now, flake8 does not natively support configuration via pyproject.toml +# https://github.com/microsoft/vscode-flake8/issues/135 [flake8] exclude = .git, diff --git a/.github/ISSUE_TEMPLATE/release_checklist.md b/.github/ISSUE_TEMPLATE/release_checklist.md index 0f56027..6107962 100644 --- a/.github/ISSUE_TEMPLATE/release_checklist.md +++ b/.github/ISSUE_TEMPLATE/release_checklist.md @@ -6,30 +6,41 @@ labels: "release" assignees: "" --- -### PyPI/GitHub release checklist: +### PyPI/GitHub rc-release preparation checklist: - [ ] All PRs/issues attached to the release are merged. - [ ] All the badges on the README are passing. - [ ] License information is verified as correct. If you are unsure, please comment below. - [ ] Locally rendered documentation contains all appropriate pages, including API references (check no modules are - missing), tutorials, and other human written text is up-to-date with any changes in the code. -- [ ] Installation instructions in the README, documentation and on the website (e.g., diffpy.org) are updated. + missing), tutorials, and other human-written text is up-to-date with any changes in the code. +- [ ] Installation instructions in the README, documentation, and the website are updated. - [ ] Successfully run any tutorial examples or do functional testing with the latest Python version. - [ ] Grammar and writing quality are checked (no typos). +- [ ] Install `pip install build twine`, run `python -m build` and `twine check dist/*` to ensure that the package can be built and is correctly formatted for PyPI release. -Please mention @sbillinge here when you are ready for PyPI/GitHub release. Include any additional comments necessary, such as -version information and details about the pre-release here: +Please tag the maintainer (e.g., @username) in the comment here when you are ready for the PyPI/GitHub release. Include any additional comments necessary, such as version information and details about the pre-release here: -### conda-forge release checklist: +### PyPI/GitHub full-release preparation checklist: - +- [ ] Create a new conda environment and install the rc from PyPI (`pip install ==??`) +- [ ] License information on PyPI is correct. +- [ ] Docs are deployed successfully to `https:///`. +- [ ] Successfully run all tests, tutorial examples or do functional testing. +Please let the maintainer know that all checks are done and the package is ready for full release. + +### conda-forge release preparation checklist: + + + +- [ ] Ensure that the full release has appeared on PyPI successfully. - [ ] New package dependencies listed in `conda.txt` and `test.txt` are added to `meta.yaml` in the feedstock. -- [ ] All relevant issues in the feedstock are addressed in the release PR. +- [ ] Close any open issues on the feedstock. Reach out to the maintainer if you have questions. +- [ ] Tag the maintainer for conda-forge release. ### Post-release checklist -- [ ] Run tutorial examples and conduct functional testing using the installation guide in the README. Attach screenshots/results as comments. -- [ ] Documentation (README, tutorials, API references, and websites) is deployed without broken links or missing figures. +- [ ] Run tutorial examples and conduct functional testing using the installation guide in the README. Attach screenshots/results as comments. +- [ ] Documentation (README, tutorials, API references, and websites) is deployed without broken links or missing figures. diff --git a/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md b/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md new file mode 100644 index 0000000..1099d86 --- /dev/null +++ b/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md @@ -0,0 +1,15 @@ +### What problem does this PR address? + + + +### What should the reviewer(s) do? + + + + diff --git a/.github/workflows/build-wheel-release-upload.yml b/.github/workflows/build-wheel-release-upload.yml index 8c575c5..c14c01b 100644 --- a/.github/workflows/build-wheel-release-upload.yml +++ b/.github/workflows/build-wheel-release-upload.yml @@ -4,13 +4,15 @@ on: workflow_dispatch: push: tags: - - '*' # Trigger on all tags initially, but tag and release privilege are verified in _build-wheel-release-upload.yml + - "*" # Trigger on all tags initially, but tag and release privilege are verified in _build-wheel-release-upload.yml jobs: release: - uses: Billingegroup/release-scripts/.github/workflows/_build-wheel-release-upload.yml@v0 + uses: scikit-package/release-scripts/.github/workflows/_build-wheel-release-upload.yml@v0 with: - project: diffpy.srmise + project: diffpy-srmise + c_extension: false + maintainer_GITHUB_username: sbillinge secrets: PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }} PAT_TOKEN: ${{ secrets.PAT_TOKEN }} diff --git a/.github/workflows/check-news-item.yml b/.github/workflows/check-news-item.yml index 960756f..5e4c993 100644 --- a/.github/workflows/check-news-item.yml +++ b/.github/workflows/check-news-item.yml @@ -3,10 +3,10 @@ name: Check for News on: pull_request_target: branches: - - main + - main jobs: - build: - uses: Billingegroup/release-scripts/.github/workflows/_check-news-item.yml@v0 + check-news-item: + uses: scikit-package/release-scripts/.github/workflows/_check-news-item.yml@v0 with: - project: diffpy.srmise + project: diffpy-srmise diff --git a/.github/workflows/matrix-and-codecov-on-merge-to-main.yml b/.github/workflows/matrix-and-codecov-on-merge-to-main.yml index f4ad74a..8c26791 100644 --- a/.github/workflows/matrix-and-codecov-on-merge-to-main.yml +++ b/.github/workflows/matrix-and-codecov-on-merge-to-main.yml @@ -11,10 +11,10 @@ on: workflow_dispatch: jobs: - coverage: - uses: Billingegroup/release-scripts/.github/workflows/_matrix-and-codecov-on-merge-to-main.yml@v0 + matrix-coverage: + uses: scikit-package/release-scripts/.github/workflows/_matrix-and-codecov-on-merge-to-main.yml@v0 with: - project: diffpy.srmise + project: diffpy-srmise c_extension: false headless: false secrets: diff --git a/.github/workflows/publish-docs-on-release.yml b/.github/workflows/publish-docs-on-release.yml new file mode 100644 index 0000000..1616c2f --- /dev/null +++ b/.github/workflows/publish-docs-on-release.yml @@ -0,0 +1,12 @@ +name: Deploy Documentation on Release + +on: + workflow_dispatch: + +jobs: + docs: + uses: scikit-package/release-scripts/.github/workflows/_publish-docs-on-release.yml@v0 + with: + project: diffpy-srmise + c_extension: false + headless: false diff --git a/.github/workflows/tests-on-pr.yml b/.github/workflows/tests-on-pr.yml index 201dad7..00e9c2a 100644 --- a/.github/workflows/tests-on-pr.yml +++ b/.github/workflows/tests-on-pr.yml @@ -1,17 +1,14 @@ name: Tests on PR on: - push: - branches: - - main pull_request: workflow_dispatch: jobs: - validate: - uses: Billingegroup/release-scripts/.github/workflows/_tests-on-pr.yml@v0 + tests-on-pr: + uses: scikit-package/release-scripts/.github/workflows/_tests-on-pr.yml@v0 with: - project: diffpy.srmise + project: diffpy-srmise c_extension: false headless: false secrets: diff --git a/.gitignore b/.gitignore index a25212e..099e294 100644 --- a/.gitignore +++ b/.gitignore @@ -10,6 +10,7 @@ __pycache__/ .Python env/ build/ +_build/ develop-eggs/ dist/ downloads/ @@ -90,10 +91,3 @@ target/ # Ipython Notebook .ipynb_checkpoints - -# version information -setup.cfg -/src/diffpy/*/version.cfg - -# Rever -rever/ diff --git a/.isort.cfg b/.isort.cfg index e0926f4..7ce0fb1 100644 --- a/.isort.cfg +++ b/.isort.cfg @@ -1,4 +1,5 @@ [settings] +# Keep import statement below line_length character limit line_length = 115 multi_line_output = 3 include_trailing_comma = True diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 9cf0556..0e4a84d 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,14 +1,14 @@ default_language_version: - python: python3 + python: python3 ci: - autofix_commit_msg: | - [pre-commit.ci] auto fixes from pre-commit hooks - autofix_prs: true - autoupdate_branch: 'pre-commit-autoupdate' - autoupdate_commit_msg: '[pre-commit.ci] pre-commit autoupdate' - autoupdate_schedule: monthly - skip: [no-commit-to-branch] - submodules: false + autofix_commit_msg: | + [pre-commit.ci] auto fixes from pre-commit hooks + autofix_prs: true + autoupdate_branch: "pre-commit-autoupdate" + autoupdate_commit_msg: "[pre-commit.ci] pre-commit autoupdate" + autoupdate_schedule: monthly + skip: [no-commit-to-branch] + submodules: false repos: - repo: https://github.com/pre-commit/pre-commit-hooks rev: v4.6.0 @@ -47,6 +47,20 @@ repos: - repo: https://github.com/codespell-project/codespell rev: v2.3.0 hooks: - - id: codespell - additional_dependencies: - - tomli + - id: codespell + additional_dependencies: + - tomli + # prettier - multi formatter for .json, .yml, and .md files + - repo: https://github.com/pre-commit/mirrors-prettier + rev: f12edd9c7be1c20cfa42420fd0e6df71e42b51ea # frozen: v4.0.0-alpha.8 + hooks: + - id: prettier + additional_dependencies: + - "prettier@^3.2.4" + # docformatter - PEP 257 compliant docstring formatter + - repo: https://github.com/s-weigand/docformatter + rev: 5757c5190d95e5449f102ace83df92e7d3b06c6c + hooks: + - id: docformatter + additional_dependencies: [tomli] + args: [--in-place, --config, ./pyproject.toml] diff --git a/.readthedocs.yaml b/.readthedocs.yaml new file mode 100644 index 0000000..47f7a01 --- /dev/null +++ b/.readthedocs.yaml @@ -0,0 +1,13 @@ +version: 2 + +build: + os: "ubuntu-22.04" + tools: + python: "latest" + +python: + install: + - requirements: requirements/docs.txt + +sphinx: + configuration: doc/source/conf.py diff --git a/AUTHORS.rst b/AUTHORS.rst index 7fe1918..870bde2 100644 --- a/AUTHORS.rst +++ b/AUTHORS.rst @@ -1,11 +1,10 @@ Authors ======= -Luke Granlund -Billinge Group and community contributors. +Simon Billinge, Billinge Group members Contributors ------------ For a list of contributors, visit -https://github.com/diffpy/diffpy.srmise/graphs/contributors +https://github.com/diffpy/diffpy-srmise/graphs/contributors diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 1466de7..f29d3b5 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -1,53 +1,5 @@ ============= -Release Notes +Release notes ============= .. current developments - -0.7.0 -===== - -**Added:** - -* Support for Python 3.13 - -**Removed:** - -* Support for Python 3.10 - - -0.6.1 -===== - -**Fixed:** - -* Recut to group's package standard, fix installation, add GitHub release workflow -* Update Python, matploblib API to run documentation CLI tutorials -* support setuptools-git-versioning>=2.0 -* Configure entry point in pyproject.toml to run CLI commands - - -0.6.0 -===== - -**Added:** - -* add api workflow - -**Changed:** - -* Moved diffpy.srmise from python2 to python3. -* Used dynamic api build generated by new cookiecutter. -* Changed workflow for build to satisfy new cookiecutter - -**Removed:** - -* Removed travis.yml and other useless files - -**Fixed:** - -* Recookiecuttered diffpy.srmise to new BillingeGroup standard -* Fixed numpy format boolean counting, numpy int slicing error. -* Cookiecuttered diffpy.srmise to new Billingegroup standard. -* add pip dependencies under pip.txt, conda dependencies under conda.txt -* add tutorial and extending examples to docs diff --git a/CODE_OF_CONDUCT.rst b/CODE_OF_CONDUCT.rst index ff9c356..e8199ca 100644 --- a/CODE_OF_CONDUCT.rst +++ b/CODE_OF_CONDUCT.rst @@ -8,7 +8,7 @@ Our Pledge We as members, contributors, and leaders pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender -identity and expression, level of experience, education, socio-economic status, +identity and expression, level of experience, education, socioeconomic status, nationality, personal appearance, race, caste, color, religion, or sexual identity and orientation. diff --git a/LICENSE.rst b/LICENSE.rst index 3675628..9cc6a9d 100644 --- a/LICENSE.rst +++ b/LICENSE.rst @@ -1,23 +1,8 @@ BSD 3-Clause License -Copyright 2014-2015, Board of Trustees of Michigan State University - 2016-2024, The Trustees of Columbia University in the City of New York. +Copyright (c) 2025, The Trustees of Columbia University in the City of New York. All rights reserved. -If you use this program to do productive scientific research that -leads to publication, we ask that you acknowledge use of the -program by citing the following paper in your publication: - - L. Granlund, S. J. L. Billinge and P. M. Duxbury, - `Algorithm for systematic peak extraction from atomic pair distribution functions - `__, - *Acta Crystallogr. A* **4**, 392-409 (2015). - -For more information please visit the diffpy web-page at - http://www.diffpy.org -or email Luke Granlund at luke.r.granlund@gmail.com, or Prof. Simon -Billinge at sb2896@columbia.edu. - Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: diff --git a/LICENSE_PDFgui.rst b/LICENSE_PDFgui.rst deleted file mode 100644 index 3ba9b69..0000000 --- a/LICENSE_PDFgui.rst +++ /dev/null @@ -1,51 +0,0 @@ -BSD 3-Clause License - -Copyright 2006-2007, Board of Trustees of Michigan State University - 2008-2024, The Trustees of Columbia University in the City of New York. -All rights reserved. - -SrMise incorporates source code from diffpy.pdfgui in the file -pdfdataset.py. The PDFgui license is reproduced in full below. - -This program is part of the DiffPy and DANSE open-source projects -and is available subject to the conditions and terms laid out -below. - -If you use this program to do productive scientific research that -leads to publication, we ask that you acknowledge use of the -program by citing the following paper in your publication: - - C. L. Farrow, P. Juhas, J. W. Liu, D. Bryndin, E. S. Bozin, - J. Bloch, Th. Proffen and S. J. L. Billinge, PDFfit2 and - PDFgui: computer programs for studying nanostructure in - crystals, J. Phys.: Condens. Matter 19, 335219 (2007) - -For more information please visit the diffpy web-page at - http://www.diffpy.org -or email Luke Granlund at luke.r.granlund@gmail.com, or Prof. Simon -Billinge at sb2896@columbia.edu. - -Redistribution and use in source and binary forms, with or without -modification, are permitted provided that the following conditions are met: - -1. Redistributions of source code must retain the above copyright notice, this - list of conditions and the following disclaimer. - -2. Redistributions in binary form must reproduce the above copyright notice, - this list of conditions and the following disclaimer in the documentation - and/or other materials provided with the distribution. - -3. Neither the name of the copyright holder nor the names of its contributors - may be used to endorse or promote products derived from this software - without specific prior written permission. - -THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE -DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE -FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL -DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR -SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER -CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, -OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE -OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/README.rst b/README.rst index 63d9aca..d5ef557 100644 --- a/README.rst +++ b/README.rst @@ -1,88 +1,52 @@ |Icon| |title|_ =============== -.. |title| replace:: diffpy.srmise -.. _title: https://diffpy.github.io/diffpy.srmise +.. |title| replace:: diffpy-srmise +.. _title: https://diffpy.github.io/diffpy-srmise .. |Icon| image:: https://avatars.githubusercontent.com/diffpy - :target: https://diffpy.github.io/diffpy.srmise + :target: https://diffpy.github.io/diffpy-srmise :height: 100px -|PyPi| |Forge| |PythonVersion| |PR| +|PyPI| |Forge| |PythonVersion| |PR| |CI| |Codecov| |Black| |Tracking| .. |Black| image:: https://img.shields.io/badge/code_style-black-black :target: https://github.com/psf/black -.. |CI| image:: https://github.com/diffpy/diffpy.srmise/actions/workflows/matrix-and-codecov-on-merge-to-main.yml/badge.svg - :target: https://github.com/diffpy/diffpy.srmise/actions/workflows/matrix-and-codecov-on-merge-to-main.yml +.. |CI| image:: https://github.com/diffpy/diffpy-srmise/actions/workflows/matrix-and-codecov-on-merge-to-main.yml/badge.svg + :target: https://github.com/diffpy/diffpy-srmise/actions/workflows/matrix-and-codecov-on-merge-to-main.yml -.. |Codecov| image:: https://codecov.io/gh/diffpy/diffpy.srmise/branch/main/graph/badge.svg - :target: https://codecov.io/gh/diffpy/diffpy.srmise +.. |Codecov| image:: https://codecov.io/gh/diffpy/diffpy-srmise/branch/main/graph/badge.svg + :target: https://codecov.io/gh/diffpy/diffpy-srmise -.. |Forge| image:: https://img.shields.io/conda/vn/conda-forge/diffpy.srmise - :target: https://anaconda.org/conda-forge/diffpy.srmise +.. |Forge| image:: https://img.shields.io/conda/vn/conda-forge/diffpy-srmise + :target: https://anaconda.org/conda-forge/diffpy-srmise .. |PR| image:: https://img.shields.io/badge/PR-Welcome-29ab47ff -.. |PyPi| image:: https://img.shields.io/pypi/v/diffpy.srmise - :target: https://pypi.org/project/diffpy.srmise/ +.. |PyPI| image:: https://img.shields.io/pypi/v/diffpy-srmise + :target: https://pypi.org/project/diffpy-srmise/ -.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/diffpy.srmise - :target: https://pypi.org/project/diffpy.srmise/ +.. |PythonVersion| image:: https://img.shields.io/pypi/pyversions/diffpy-srmise + :target: https://pypi.org/project/diffpy-srmise/ .. |Tracking| image:: https://img.shields.io/badge/issue_tracking-github-blue - :target: https://github.com/diffpy/diffpy.srmise/issues - -Implementation of the ParSCAPE algorithm for peak extraction from atomic pair distribution functions (PDFs) - -SrMise is an implementation of the `ParSCAPE algorithm -`_ for peak extraction from -atomic pair distribution functions (PDFs). It is designed to function even -when *a priori* knowledge of the physical sample is limited, utilizing the -Akaike Information Criterion (AIC) to estimate whether peaks are -statistically justified relative to alternate models. Three basic use cases -are anticipated for SrMise. The first is peak fitting a user-supplied -collections of peaks. The second is peak extraction from a PDF with no (or -only partial) user-supplied peaks. The third is an AIC-driven multimodeling -analysis where the output of multiple SrMise trials are ranked. - -The framework for peak extraction defines peak-like clusters within the data, -extracts a single peak within each cluster, and iteratively combines nearby -clusters while performing a recursive search on the residual to identify -occluded peaks. Eventually this results in a single global cluster -containing many peaks fit over all the data. Over- and underfitting are -discouraged by use of the AIC when adding or, during a pruning step, removing -peaks. Termination effects, which can lead to physically spurious peaks in -the PDF, are incorporated in the mathematical peak model and the pruning step -attempts to remove peaks which are fit better as termination ripples due to -another peak. - -Where possible, SrMise provides physically reasonable default values -for extraction parameters. However, the PDF baseline should be estimated by -the user before extraction, or by performing provisional peak extraction with -varying baseline parameters. The package defines a linear (crystalline) -baseline, arbitrary polynomial baseline, a spherical nanoparticle baseline, -and an arbitrary baseline interpolated from a list of user-supplied values. -In addition, PDFs with accurate experimentally-determined uncertainties are -necessary to provide the most reliable results, but historically such PDFs -are rare. In the absence of accurate uncertainties an *ad hoc* uncertainty -must be specified. - -For more information about the diffpy.srmise library, please consult our `online documentation `_. + :target: https://github.com/diffpy/diffpy-srmise/issues + +Peak extraction and peak fitting tool for atomic pair distribution functions. + +* LONGER DESCRIPTION HERE + +For more information about the diffpy-srmise library, please consult our `online documentation `_. Citation -------- -If you use this program for a scientific research that leads -to publication, we ask that you acknowledge use of the program -by citing the following paper in your publication: +If you use diffpy-srmise in a scientific publication, we would like you to cite this package as - L. Granlund, S. J. L. Billinge and P. M. Duxbury, - `Algorithm for systematic peak extraction from atomic pair distribution functions - `__, - *Acta Crystallogr. A* **4**, 392-409 (2015). + diffpy-srmise Package, https://github.com/diffpy/diffpy-srmise Installation ------------ @@ -96,25 +60,25 @@ To add "conda-forge" to the conda channels, run the following in a terminal. :: conda config --add channels conda-forge We want to install our packages in a suitable conda environment. -The following creates and activates a new environment named ``diffpy.srmise_env`` :: +The following creates and activates a new environment named ``diffpy-srmise_env`` :: - conda create -n diffpy.srmise_env diffpy.srmise - conda activate diffpy.srmise_env + conda create -n diffpy-srmise_env diffpy-srmise + conda activate diffpy-srmise_env To confirm that the installation was successful, type :: - python -c "import diffpy.srmise; print(diffpy.srmise.__version__)" + python -c "import diffpy_srmise; print(diffpy_srmise.__version__)" The output should print the latest version displayed on the badges above. If the above does not work, you can use ``pip`` to download and install the latest release from `Python Package Index `_. -To install using ``pip`` into your ``diffpy.srmise_env`` environment, type :: +To install using ``pip`` into your ``diffpy-srmise_env`` environment, type :: - pip install diffpy.srmise + pip install diffpy-srmise If you prefer to install from sources, after installing the dependencies, obtain the source archive from -`GitHub `_. Once installed, ``cd`` into your ``diffpy.srmise`` directory +`GitHub `_. Once installed, ``cd`` into your ``diffpy-srmise`` directory and run the following :: pip install . @@ -122,16 +86,14 @@ and run the following :: Getting Started --------------- -You may consult our `online documentation `_ for tutorials and API references. +You may consult our `online documentation `_ for tutorials and API references. Support and Contribute ---------------------- -`Diffpy user group `_ is the discussion forum for general questions and discussions about the use of diffpy.srmise. Please join the diffpy.srmise users community by joining the Google group. The diffpy.srmise project welcomes your expertise and enthusiasm! +If you see a bug or want to request a feature, please `report it as an issue `_ and/or `submit a fix as a PR `_. -If you see a bug or want to request a feature, please `report it as an issue `_ and/or `submit a fix as a PR `_. You can also post it to the `Diffpy user group `_. - -Feel free to fork the project and contribute. To install diffpy.srmise +Feel free to fork the project and contribute. To install diffpy-srmise in a development mode, with its sources being directly used by Python rather than copied to a package directory, use the following in the root directory :: @@ -152,9 +114,14 @@ trying to commit again. Improvements and fixes are always appreciated. -Before contributing, please read our `Code of Conduct `_. +Before contributing, please read our `Code of Conduct `_. Contact ------- -For more information on diffpy.srmise please visit the project `web-page `_ or email Prof. Simon Billinge at sb2896@columbia.edu. +For more information on diffpy-srmise please visit the project `web-page `_ or email Simon Billinge at sb2896@columbia.edu. + +Acknowledgements +---------------- + +``diffpy-srmise`` is built and maintained with `scikit-package `_. diff --git a/doc/Makefile b/doc/Makefile index 798f52b..55f1c59 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -6,7 +6,7 @@ SPHINXOPTS = SPHINXBUILD = sphinx-build PAPER = BUILDDIR = build -BASENAME = $(subst .,,$(subst $() $(),,diffpy.srmise)) +BASENAME = $(subst .,,$(subst $() $(),,diffpy-srmise)) # User-friendly check for sphinx-build ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) diff --git a/doc/examples/README.rst b/doc/examples/README.rst deleted file mode 100644 index fa2b571..0000000 --- a/doc/examples/README.rst +++ /dev/null @@ -1,873 +0,0 @@ -Purpose -======= - -This tutorial is an introduction to the SrMise library and command-line tool, -intended to expose new users and developers to the major use cases and options -anticipated for SrMise. - -Generating interest in SrMise is another goal of these examples, and we hope -you will discover exciting ways to apply its capabilities to your scientific -goals. If you think SrMise may help you do so, please feel free to contact us -through the DiffPy website. - -http://www.diffpy.org - -Overview -======== - -SrMise is an implementation of the `ParSCAPE algorithm`_, which incorporates -standard chi-square fitting within an iterative clustering framework. The -algorithm supposes that, in the absence of an atomic structure model, the model -complexity (informally, the number of extracted peaks) which can be -justifiably obtained from a PDF is primarily determined by the experimental -uncertainties. The Akaike Information Criterion (AIC), summarized in the -manual, is the information-theoretic tool used to balance model complexity -with goodness-of-fit. - -Three primary use cases are envisioned for SrMise: - -1) Peak fitting, where user-specified peaks are fit to the experimental data. -2) Peak extraction, where the number of peaks and their parameters are - estimated solely from the experimental data. -3) Multimodel selection, where multiple sets of peaks are ranked in an - AIC-driven analysis to determine the most plausible sets to guide - additional investigation. - -Productively running SrMise requires, in basic, the following elements: - -1) An experimental PDF. Note that peak extraction, though not peak fitting, - requires that all peaks of interest be positive. This rules out peak - extraction using SrMise for neutron PDFs obtained from samples containing - elements with both positive and negative scattering factors. -2) The experimental uncertainties. In principle these should be reported with - the data, but in practice experimental uncertainties are frequently not - reported, or are unreliable due to details of the data reduction process. - In these cases the user should specify an *ad hoc* value. In peak extraction - an *ad hoc* uncertainty necessarily results in *ad hoc* model complexity, or, - more precisely, a reasonable model complexity if the provided uncertainty - is presumed correct. (Even when the uncertainties are known, specifying an - *ad hoc* value can be a pragmatic tool for exploring alternate models, - especially in conjunction with multimodeling analysis.) For both peak - extraction and peak fitting the estimated uncertainties of peak parameters - (i.e. location, width, intensity) are dependent on the experimental - uncertainty. -3) The PDF baseline. For crystalline samples the baseline is linear and can - be readily estimated. For nanoparticles more effort is required as SrMise - includes explicit support for only a few basic shapes, although the user - can define a baseline using arbitrary polynomials or an interpolating - function constructed from a list of arbitrary numerical values. -4) The range over which to extract or fit peaks. By default SrMise will use - the entire PDF, but it is usually wise to restrict the range to the region - of immediate interest. - -The examples described below, though not exhaustive, go into detail about each -of these points. They also cover other parameters for which good default -values can usually be estimated directly from the data. - - -Getting Started -=============== - -The examples are contained in the *doc/examples/* directory of the SrMise -`source distribution `_, -available as both a |zip| and |tar.gz| archive. Download one of these files -(Windows users will generally favor the .zip, while Linux/Mac users the .tar.gz) -to a directory of your choosing. - -Uncompress the archive. If the downloaded file is *archivename.zip* or -*archivename.tar.gz* this will create a new directory *archivename* in its -current directory. On Windows this can be accomplished by right-clicking -and choosing "Extract all". On Linux/Mac OS X run, from the containing -directory, :: - - tar xvzf archivename.tar.gz - -From a command window change to the *doc/examples* directory of the new -folder. For example, a Windows' user who extracted *archivename.zip* in the -folder *C:\\Research* would type :: - - cd C:\Research\archivename\doc\examples - -Every example below includes a Python script that may be run from this -directory. While such scripts expose the full functionality of SrMise, for -many common tasks the command-line program ``srmise`` included with the package -is both sufficient and convenient, and the tutorial uses it to introduce many -fundamental concepts. Its options may be examined in detail by running :: - - srmise --help - -It is recommended to work through, in the order presented, at least the -command-line portion of each example. Users looking for more detail should find -the copiously commented scripts helpful. - -.. ~List of Examples~ .. - -* Peak extraction of a single peak: - extract_single_peak.py - -* Summary of SrMise parameters: - parameter_summary.py - -* Peak extraction with initial peaks: - extract_initial.py - -* Peak fitting with initial peaks: - fit_initial.py - -* Querying SrMise results: - query_results.py - -* Multimodeling with known uncertainties: - multimodel_known_dG1.py - multimodel_known_dG2.py - -* Multimodeling with unknown uncertainties: - multimodel_unknown_dG1.py - multimodel_unknown_dG2.py - - -.. ~Example 1~ .. - -Peak extraction of a single peak -================================ - -| Script: extract_single_peak.py_ -| Sample: `Ag`_ - -This introductory example shows how to extract the nearest-neighbor peak of an -X-ray PDF for crystalline (FCC) silver powder with experimentally determined -uncertainties. It demonstrates basic input/output with SrMise, how to set the -region over which to extract peaks, and how to automatically estimate a linear -baseline. - -First, plot the data without performing peak extraction. The first argument -must be either a PDF (as here) or a .srmise file (described later) saved by -SrMise. :: - - srmise data/Ag_nyquist_qmax30.gr --no-extract --plot - -This should result in an image very similar to the one below. The top shows the -experimental data in blue. The bottom shows the difference curve, which is -just the PDF itself since no baseline has been specified (it is identically 0), -and no peaks have been extracted. - -|images/extract_single_peak1.png| - -By default peak extraction is performed over the entire PDF, but often only -peaks in a particular region are of immediate interest. In this case the -nearest-neighbor peak near 2.9 Å is well separated from all other peaks, and -performing peak extraction from around 2 Å to 3.5 Å will be sufficient. To -restrict peak extraction to this interval use the ``--range`` option, which -accepts a pair of values. :: - - srmise data/Ag_nyquist_qmax30.gr --no-extract --plot --range 2 3.5 - -The PDF baseline of a crystal is linear, and a reasonable crystal baseline can -often be automatically estimated. To estimate baseline parameters -automatically, specify the type of baseline to use with the ``--baseline`` -option. Here we specify a polynomial of degree 1, which is at present the only -baseline for which SrMise provides automatic estimation. Since the results of -peak extraction are conditioned on the baseline parameters, it is a good idea to -see whether they are reasonable. :: - - srmise data/Ag_nyquist_qmax30.gr --no-extract --plot --range 2 3.5 - --baseline "Polynomial(degree=1)" - -|images/extract_single_peak2.png| - -The estimated baseline looks reasonable, so it's time to perform peak extraction. -By default ``srmise`` performs extraction when run, so simply remove the -``--no-extract`` option. :: - - srmise data/Ag_nyquist_qmax30.gr --plot --range 2 3.5 - --baseline "Polynomial(degree=1)" - -|images/extract_single_peak3.png| - -The plot shows the fit to the data and difference curve. The top inset shows -a vertical marker at the position of the extracted peak. The console output -indicates the nearest-neighbor peak is located at 2.9007 ± 0.0019 Å, with width -(as full-width at half-maximum) 0.2672 ± 0.0049 Å, and intensity 9.8439 ± -0.1866. (Results may vary slightly by platform.) Since this PDF has -reliable uncertainties, the reported parameter uncertainties are quantitatively -sound. Note also that these parameters are for a Gaussian in the radial -distribution function (RDF) corresponding to the experimental PDF, rather than -the Gaussian divided by radius which is the actual function being fit to the -PDF. - -SrMise has two basic formats for saving data. The first are .srmise files, -which record all information about the parameters and results of peak -extraction. These files may be loaded by ``srmise`` and in Python scripts. The -second are .pwa files, which are intended as a human readable summary, but do -not contain enough information to reproduce peak extraction results. These -may be saved with the ``--save filename.srmise`` and ``--savepwa filename.pwa`` -options. - -The script gives results identical to the commands above, and also saves both a -.srmise and .pwa file in the *output* directory. Verify this by running it. :: - - python extract_single_peak.py - - -.. ~Example 2~ .. - -Summary of SrMise parameters -============================ - -| Script: parameter_summary.py_ -| Sample: |TiO2|_ - -This example offers an overview of the SrMise extraction parameters, and -demonstrates their use by explicitly setting them to reasonable values in the -context of a titanium dioxide (rutile) X-ray PDF with unreliable uncertainties. - -For brevity, code snippets below simply add an entry to the dictionary ``kwds``, -which sets SrMise parameters as part of the following pattern: :: - - from diffpy.srmise import PDFPeakExtraction - - ... - - ppe = PDFPeakExtraction() # Initializes main extraction object - - kwds = {} # Dictionary for holding parameters - ... # Code populating the dictionary - ppe.setvars(**kwds) # Set parameters - -Run and plot the results of this example with :: - - python parameter_summary.py - -|images/parameter_summary1.png| - - -baseline --------- - -| The PDF baseline. Informally, a PDF is the baseline plus peaks. -| *Accepts* - Baseline with parameters, or BaselineFunction implementing - estimation. -| *Default* - None (identically 0). Users should specify one. - -The PDF baseline is a function upon which peaks are added. Crystalline -materials have a linear baseline, while the baseline of finite -nanomaterials is the shape-dependent "characteristic function", which is -the autocorrelation of the object. The physical origin of the baseline -is unmeasured scattering below some minimum value of the experimental -momentum transfer, |Qmin|. The effect of interparticle correlations is -sometimes also treated as part of the PDF baseline. While linear baselines -are readily estimated, for other materials the user will need to exercise -judgement, as the results of peak extraction are generally conditioned upon -a reasonable choice of baseline. - -Baselines may be specified by importing and instantiating the appropriate -classes, or by using a baseline loaded from an existing .srmise file. The -following ``BaselineFunction``\ s are importable from -``diffpy.srmise.baselines``. - -* Arbitrary. Any Python function which implements a simple interface. For - exploratory use only, as this baseline cannot be saved. See the - |Extending SrMise| documentation for information on creating new - baselines. -* FromSequence. Interpolated from lists of r and G(r) values. No - parameters. -* NanoSpherical. Characteristic function of sphere. Radius and scale - parameters. -* Polynomial(degree=1). Crystalline. Implements estimation. -* Polynomial(degree>1). An arbitrary polynomial. - ---------- - -Example - -The baseline G(r) = -0.65*r + 0, with the intercept fixed at 0, is visually -reasonable for the |TiO2| sample. This baseline may be utilized from the -command-line with the ``--bpoly1 -0.65 0c`` options, or in a script as -follows: :: - - from diffpy.srmise.baselines import Polynomial - - ... - - blfunc = Polynomial(degree=1) - slope = -.65 - intercept = 0. - kwds["baseline"] = blfunc.actualize([slope, intercept], free=[True, False]) - -Run the following command to view this baseline. :: - - srmise data/TiO2_fine_qmax26.gr --bpoly1 -0.65 0c --range 0 10 - --no-extract --plot - -|images/parameter_summary2.png| - -cres ----- - -| The clustering resolution, which influences sensitivity of peak finding. -| *Accepts* - Value greater than PDF sampling rate dr. -| *Default* - Nyquist rate |pi/Qmax|, or 4*dr if |Qmax| = ∞. - -The clustering resolution |d_c| determines when new clusters, and thus new -peak-like structures, are identified during the clustering phase of peak -extraction. When a point is being clustered, it is added to an existing -cluster if the distance (along the r-axis) to the nearest cluster, d, is -less than |d_c|. (See image.) Otherwise this point is the first in a new -cluster. Note that SrMise oversamples the PDF during the clustering phase, -so values less than the Nyquist rate may be specified. - -|images/parameter_summary3.png| - ---------- - -Example - -A clustering resolution of 0.05, about half the Nyquist sampling interval for -the |TiO2| PDF, is easily set from the command-line with the ``--cres 0.05`` -option, or from a script: :: - - kwds["cres"] = 0.05 - - -dg --- - -| PDF uncertainty used during peak extraction. -| *Accepts* - Scalar or list of scalars > 0. -| *Default* - Value reported by PDF, otherwise 5% max value of PDF. - -PDF reports reliable experimentally determined uncertainties, but otherwise -an *ad hoc* value must be specified for fitting. This parameter is the -primary determinant of model complexity during peak extraction, and even -when the reported values are reliable using an *ad hoc* value can be helpful -in generating other plausible models. This parameter can be set to a single -value, or a value for each point. The uncertainties of most PDFs have -very little r-dependence, so using the same value for each data point often -gives points with nearly the correct relative weight. This means the -refined value of peak parameters for a given model have very little -dependence on the absolute scale of the uncertainties. The estimated -uncertainty of peak parameters, however, depends directly on the absolute -magnitude. - ---------- - -Example - -An *ad hoc* uncertainty of 0.35 (each point has equal weight) may be set for the -|TiO2| example from the command-line with the ``--dg 0.35`` option, or in a -script with: :: - - kwds["dg"] = 0.35 - -The command-line tool also includes the ``--dg-mode`` option, which exposes -several methods for setting more complex uncertainties concisely. For details, -run :: - - srmise --help - -initial_peaks -------------- - -| Specifies peaks to include in model prior to extraction. -| *Accepts* - A ``Peaks`` instance containing any number of ``Peak`` instances. -| *Default* - Empty ``Peaks`` instance. - -Initial peaks are held fixed for the early stages of peak extraction, which -conditions any additional peaks extracted. In later stages initial peaks -have no special treatment, although they may be set as non-removable, which -prevents removal by pruning. - -In peak fitting, this parameter specifies the peaks which are to be fit. - -Two basic methods exist for setting peaks. The first is a convenience function -which takes a position and attempts to estimate peak parameters. The second -is manual specification, where the user provides initial values for all -peak parameters. - -SrMise version |release| does not support setting initial_peaks from the -command-line. - ---------- - -Example - -Five initial peaks are specified for the |TiO2| sample, using the peak function -described in the corresponding section. The first two peaks are estimated from -position, and show the quality of estimated parameters in regions with little -peak overlap. The other three peaks have manually specified parameters, -and occur in regions of somewhat greater overlap. To aid convergence, the -widths of these latter peaks have been fixed at a reasonable value for a peak -arising from a single atomic pair distance. Although initial_peaks may be set -directly, the ``estimate_peak()`` and ``addpeaks()`` methods of -PDFPeakExtraction used below are often more convenient. :: - - from diffpy.srmise.peaks import GaussianOverR - - pf = GaussianOverR(maxwidth=0.7) - - ... - - ## Initial peaks from approximate positions. - positions = [2.0, 4.5] - for p in positions: - ppe.estimate_peak(p) # adds to initial_peaks - - ## Initial peaks from explicit parameters. - pars = [[6.2, 0.25, 2.6],[6.45, 0.25, 2.7],[7.15, 0.25, 5]] - peaks = [] - for p in pars: - peaks.append(pf.actualize(p, free=[True, False, True], in_format="pwa")) - ppe.addpeaks(peaks) # adds to initial_peaks - -|images/parameter_summary4.png| - -While initial peaks are fixed during the early stages of peak extraction, in -later stages they are treated as any other peak identified by SrMise. In -particular, they may be removed by pruning. This can be prevented by setting -them as non-removable. :: - - ## Don't prune initial peaks - for ip in ppe.initial_peaks: - ip.removable = False - - -nyquist -------- - -| Whether to evaluate results on Nyquist-sampled grid with dr = |pi/Qmax| . -| *Accepts* - True or False -| *Default* - True when |Qmax|>0, otherwise False. - -When nyquist is False, the PDF's original sampling rate is used. By the -Nyquist-Shannon sampling theorem, all PDFs sampled faster than the Nyquist -rate contain all the information which the experiment can provide. Points -sampled much faster than the Nyquist rate are strongly correlated, however, -violating an assumption of chi-square fitting. Nyquist sampling offers the -best approximation to independently-distributed uncertainties possible for a -PDF without loss of information. - ---------- - -Example - -Setting the Nyquist parameter explicitly is straightforward, although the -default value (True for this |TiO2| sample) is preferred in most cases. From -the command line include the ``--nyquist`` or ``--no-nyquist`` option. To use -Nyquist sampling in scripts, set :: - - kwds["nyquist"] = True - -pf --- - -| The peak function used for extracting peaks. -| *Accepts* - An instance of any class inheriting from PeakFunction. -| *Default* - GaussianOverR(maxwidth=0.7), reasonable if r-axis in Å. - -The following peak functions are importable from ``diffpy.srmise.peaks``. - -* GaussianOverR(maxwidth). A Gaussian divided by radius r. Maxwidth gives - maximum full-width at half maximum, to reduce likelihood of unphysically - wide peaks. -* Gaussian(maxwidth). A Gaussian with a maximum width, as above. -* TerminationRipples(base_pf, qmax). Modifies another peak function, - base_pf, to include termination effects for given |Qmax|. Peak - extraction automatically applies termination ripples to peaks, but they - should be specified explicitly if using SrMise for peak fitting. - ---------- - -Example - -The default peak function is reasonable for the |TiO2| example, but can be -explicitly specified from the command-line with ``--pf "GaussianOverR(0.7)"``. -In scripts, use :: - - from diffpy.srmise.peaks import GaussianOverR - - ... - - kwds["pf"] = GaussianOverR(0.7) - - -qmax ----- - -| The experimental maximum momentum transfer |Qmax|. -| *Accepts* - Any value ≥ 0, where 0 indicates an infinite value. Also - allows "automatic", which estimates |Qmax| from the data. -| *Default* - Value reported by data. If not available, uses automatic - estimate. - -|Qmax| is responsible for the characteristic termination ripples observed -in the PDF. SrMise models termination effects by taking the Fourier -transform of a peak, zeroing all components above |Qmax|, and performing the -inverse transform back to real-space. PDFs where termination ripples were -smoothed during data reduction (e.g. using a Hann window) will be fit less -well. - ---------- - -Example - -For the |TiO2| PDF, |Qmax| = 26 |angstrom^-1|, which can be explicitly set -with :: - - kwds["qmax"] = 26.0 - -Alternately, to automatically estimate |Qmax| from the data (about 25.9 -|angstrom^-1| in this case), use :: - - kwds["qmax"] = "automatic" - -At the command-line, both the ``--qmax 26.0`` and ``--qmax automatic`` options -are valid. - - -rng ---- - -| The range over which to perform peak extraction or peak fitting. -| *Accepts* - A list [rmin, rmax], where rmin < rmax and neither fall - outside the data. May specify either as ``None`` to use default value. -| *Default* - The first and last r-values, respectively, in the PDF. - -Users are encouraged to restrict fits to the regions of immediate interest. - ---------- - -Example - -To extract peaks from the |TiO2| sample between 1.5 and 10 Å, in scripts use :: - - kwds["rng"] = [1.5, 10] - -At the command-line use ``--range 1.5 10``. - - -supersample ------------ - -| Minimum degree to oversample PDF during early stages of peak extraction. -| *Accepts* - A value ≥ 1. -| *Default* - 4.0 - -Peak extraction oversamples the PDF during the early phases to assist in -peak finding. This value specifies a multiple of the Nyquist rate, -equivalent to dividing the Nyquist sampling interval dr = |pi/Qmax| by this -value. The supersample parameter has no effect if the input PDF is already -sampled faster than this. - -Note that large degrees of supersampling, whether due to this parameter or -the input PDF, negatively impact the time required for chi-square fitting. - ---------- - -Example - -The default value is sufficient for the |TiO2| sample, but to set explicitly in -a script use :: - - kwds["supersample"] = 4.0 - -or ``--supersample 4.0`` at the command-line. - - -.. ~Example 3~ .. - -Peak fitting -============ - -| Script: fit_initial.py_ -| Sample: |C60|_ - -This example demonstrates peak fitting with a set of initial peaks on a |C60| -nanoparticle PDF with unreliable uncertainties. An interpolated baseline is -created from a list of (r, G(r)) pairs contained in a file. Note that the -command-line tool ``srmise`` does not currently support peak fitting. - -The initial peaks are specified as in the previous example, by giving an -approximate list of peak positions to an estimation routine, or manually -specifying peak parameters. Peak fitting never alters the peak function, so -termination effects are explicitly added to an existing peak function with -the following pattern. :: - - from diffpy.srmise.peaks import TerminationRipples - - ... - - # Return new peak function instance which adds termination effects to - # existing peak function instance "base_pf" with maximum momentum transfer - # "qmax". - pf = TerminationRipples(base_pf, qmax) - -The initial peaks used in this fit are shown below. The last two peaks use -manually specified parameters. Note that this PDF is unnormalized, so the -scale of the y-axis is arbitrary. - -|images/fit_initial1.png| - -By default, peak fitting occurs on a Nyquist-sampled grid when |qmax| > 0. To -fit a finely-sampled PDF without resampling set "nyquist" to False. - -Run the script to see the results of the fit. :: - - python fit_initial.py - -|images/fit_initial2.png| - - -.. ~Example 4~ .. - -Querying SrMise results -======================= - -| Script: query_results.py_ -| Sample: `Ag`_ - -In previous examples the results of peak extraction/fitting were read from the -console, but this is not always convenient. This example demonstrates the -basic methods for querying SrMise objects about their parameters and values -within scripts. - -First, visually check that the baseline obtained in the earlier silver example -(set using the ``--bsrmise filename.srmise`` option) is reasonable over a -larger range. :: - - srmise data/Ag_nyquist_qmax30.gr --no-extract --plot --range 2 10 - --bsrmise output/query_results.srmise - -|images/query_results1.png| - -Next, run :: - - python query_results.py - -to perform peak extraction, the example analysis, and obtain the two plots -below. - -|images/query_results2.png| - -|images/query_results3.png| - -Now the methods of the script are described. The way to evaluate model -uncertainties with SrMise is with a ``ModelCovariance`` instance returned after -peak extraction (or fitting). :: - - cov = ppe.extract() - -Model parameters denoted by a tuple ``(i,j)``, representing the *j*\ th -parameter of the *i*\ th peak, are passed to this object's methods. For a -Gaussian over r, the order of peak parameters in SrMise is position, width, and -area. Thus, the area of the nearest-neighbor peak is denoted by the tuple -(0,2). (Indexing is zero-based.) By convention, the last element (``i=-1``) is -the baseline. The methods of greatest interest are as follows. :: - - # Get (value, uncertainty) tuple for this parameter - cov.get((i,j)) - - # Get just the value of the parameter - cov.getvalue((i,j)) - - # Get just the uncertainty of the parameter - cov.getuncertainty((i,j)) - - # Get the covariance between two parameters - cov.getcovariance((i1,j1), (i2,j2)) - - # Get the correlation between two parameters - cov.getcorrelation((i1,j1), (i2,j2)) - -Suppose, for example, one wants to empirically estimate the number of silver -atoms contributing to each occupied coordination shell of the FCC structure, -knowing that the coordination number (i.e. nearest neighbors) of an ideal FCC -structure is exactly 12. For a monoelemental material the intensity of a peak -in a properly normalized PDF should equal the number of contributing atoms in -the corresponding shell. Thus, the intensity of the nearest neighbor peak -permits an estimate of the PDF scale factor, and using that an estimate of other -shell's occupancy. This simple procedure is implemented in the script using -model parameters and uncertainties obtained with the methods above. - -Another useful capability is calculating the value of a model, in whole or -part. Given a PDFPeakExtraction instance ``ppe`` and a numpy array ``r``, the -usual methods are :: - - # Return sum of peaks and baseline, evaluated on the current grid, or r. - ppe.extracted.value() - ppe.extracted.value(r) - - # Return residual (data - model) on the current grid. - ppe.extracted.residual() - - # Return the baseline evaluated on the current grid, or r. - ppe.extracted.valuebl() - ppe.extracted.valuebl(r) - - # The ith peak evaluated on r - ppe.extracted.model[i].value(r) - - # The baseline evaluated on r - ppe.extracted.baseline.value(r) - - -.. ~Example 5~ .. - -Multimodeling with known uncertainty -==================================== - -| Scripts: multimodel_known_dG1.py_, multimodel_known_dG2.py_ -| Sample: `Ag`_ - -.. note :: - - This example is intended for advanced users. The API for multimodel - selection is expected to change dramatically in a future version of SrMise. - At present multimodel selection in SrMise requires each point in the PDF be - assigned identical uncertainty. Using the mean uncertainty of a - Nyquist-sampled PDF is suggested. - -The Akaike information criterion (AIC) is a powerful but straightforward method -for multimodel selection, which in the context of SrMise means ranking -individual models (i.e. a set of peaks and baselines) by their "Akaike -probabilities." These are, in brief, an asymptotic estimate of the expected -(with respect to the data) and relative (with respect to the models under -consideration) likelihood that a particular model is the best model in the sense -of least Kullback-Leibler divergence. This approach has a basis in fundamental -concepts of information theory, and shares some conceptual similarities to -cross validation. Qualitatively speaking, a good model is both simple (has -few parameters) and fits the data well (has a small residual, e.g. the -chi-square error), but improving one of these often comes with a cost to the -other. The AIC manages this tradeoff between model complexity and -goodness-of-fit. - -A formal introduction to these methods is beyond the scope of this example. -Investigators are encouraged to consult Burnham and Anderson's "Model Selection -and Multimodel Inference" (New York: Springer, 2002) for a general introduction -to AIC-based multimodeling. See also the paper describing SrMise and the -`ParSCAPE algorithm`_ for details about this method as applied to peak -extraction from pair distribution functions. - -The suggested approach to multimodel selection with SrMise is generating a -population of models of varying complexity by treating the experimental -uncertainty dG of PDF G(r) as a parameter, denoted dg, across multiple SrMise -trials. These models may be very similar, and such model redundancy is reduced -by creating classes of similar models, namely those with the same number and -type of peak, and very similar peak parameters. Each class, represented by the -constituent model with least chi-square error, is considered distinct for the -purpose of the multimodel analysis. The Akaike probabilities are evaluated for -each class, and from these the investigator may identify the set of most -promising models for additional analysis. The investigator's *a priori* -knowledge of a system, such that a particular model is unphysical, can be -leveraged by excluding that model and recalculating the Akaike probabilities. - -Details of the multimodeling procedure are discussed in the comments of the -extraction and analysis scripts. Run these, noting that the extraction script -may take several minutes to complete. :: - - python multimodel_known_dG1.py - python multimodel_known_dG2.py - -.. ~Example 6~ .. - -Multimodeling with unknown uncertainty -====================================== - -| Scripts: multimodel_unknown_dG1.py_, multimodel_unknown_dG2.py_ -| Sample: |C60|_ - -.. note :: - - This example is intended for advanced users. The API for multimodel - selection is expected to change dramatically in a future version of SrMise. - At present multimodel selection in SrMise requires each point in the PDF - be assigned identical uncertainty. - -Multimodel selection with SrMise when experimental uncertainties are unknown is -challenging, and without an independent estimate of these uncertainties the -usual AIC-based multimodeling analysis of the previous example is not possible. -To be specific, the procedure in the previous example can be carried out under -the assumption that some *ad hoc* uncertainty is correct, but results are -clearly dependent upon that choice. - -The approach taken here, detailed in the paper describing the -`ParSCAPE algorithm`_, is to evaluate the Akaike probabilities over a broad -range of *ad hoc* uncertainties, typically the same range used to generate the -population of models in the first place. Then, identify the set of classes -which have greatest Akaike probability for at least one of the evaluated -uncertainties. This choice embodies ignorance of experimentally-determined -uncertainties. Unlike a standard AIC-based multimodeling analysis, these -classes have no particular information theoretic relationship with each other -since their Akaike probabilities were calculated assuming different -uncertainties. However, if the true experimental uncertainty lies within the -interval tested, this set of classes necessarily contains the one that would be -selected as best were the experimental uncertainties known. This is, -nevertheless, a significantly less powerful analysis than is possible when -the experimental uncertainties are known. - -Details of the multimodeling procedure are discussed in the comments of the -extraction and analysis scripts. Run these, noting that the extraction script -may take several minutes to complete. :: - - python multimodel_unknown_dG1.py - python multimodel_unknown_dG2.py - -.. ~PDF Info~ .. - -PDF Information -=============== - -Information on the sample, experimental methods, and data reduction procedures -for the example PDFs are summarized below. Special attention is given to why -each PDF does or does not report reliable uncertainties. - - -Ag --- - -A synchotron X-ray PDF (|Qmax| = 30 |angstrom^-1|, Nyquist sampled) with -reliable experimentally-estimated uncertainties for a crystalline powder of -face-centered cubic silver. The 2D diffraction pattern was measured -on an integrating detector. A Q-space 1D pattern with nearly uncorrelated -experimentally-estimated uncertainties was obtained using `SrXplanar`_. All -other data reduction was performed using `PDFgetX2`_. - -Reliable experimental uncertainties were preserved during error propagation to -the PDF by transforming the 1D pattern to the minimally-correlated (Nyquist) -grid without intermediate resampling. - - -|C60| ------ - -A synchotron X-ray PDF (|Qmax| = 21.3 |angstrom^-1|, finely sampled) for a -powder of buckminsterfullerene nanoparticles in a face-centered cubic -lattice, but with no fixed orientation at the lattice sites. The 2D diffraction -pattern was measured on an integrating detector. A 2\ *θ* 1D pattern without -propagated uncertainties was obtained using `FIT2D`_. All other data reduction -was performed using `PDFgetX2`_. This PDF is unnormalized, so the scale of the -y-axis is arbitrary. The nanoparticle baseline used for testing this PDF with -SrMise is a fit to the observed interparticle contribution using an empirical -model of thin spherical shells of constant density in an FCC lattice. - -This PDF has unreliable uncertainties. Since the 1D pattern reports no -uncertainty, PDFgetX2 treats the uncertainty as equal to the square-root of the -values in the 1D pattern, which is invalid for integrating detectors. Moreover, -the 1D pattern must be resampled onto a Q-space grid before the PDF can be -calculated, and this introduces correlations between points. Finally, the PDF is -itself oversampled, resulting in further correlations. - - -|TiO2| ------- - -A synchotron X-ray PDF (|Qmax| = 26 |angstrom^-1|, finely sampled) for a -crystalline powder of titanium dioxide (rutile). The 2D diffraction pattern was -measured on an integrating detector. A Q-space 1D pattern with nearly -uncorrelated experimentally-estimated uncertainties was obtained using -`SrXplanar`_. All other data reduction was performed using `PDFgetX2`_. - -Although the 1D diffraction pattern has reliable uncertainties, this PDF was -(illustratively) sampled faster than the Nyquist rate, introducing significant -correlations between nearby data points. Resampling this PDF at the Nyquist -rate cannot recover reliable uncertainties unless the full variance-covariance -matrix has been preserved and is propagated during resampling. diff --git a/doc/examples/data/Ag_nyquist_qmax30.gr b/doc/examples/data/Ag_nyquist_qmax30.gr deleted file mode 100644 index abdd2df..0000000 --- a/doc/examples/data/Ag_nyquist_qmax30.gr +++ /dev/null @@ -1,468 +0,0 @@ -History written: Wed Jul 30 00:37:52 2003 -Produced by me -####### Get_XPDF ####### - -##### General_Setting -title=RAPDF -workingdirectory=D:\LargeResearchFiles\Diffraction\mucat200307\Ag_silver\work\ -sourcedir=C:\Program Files\PDFgetX2\ -logfile=.pdfgetx2.log -quiet=0 debug=0 autosave_isa=1 savefilenamebase=Ag_1-6_srXp_qspace -iqfilesurfix=.iq sqfilesurfix=.sq fqfilesurfix=.fq grfilesurfix=.gr - -##### DataFileFormat -datatype=2 (0:SPEC, 1:CHI, 2:nxm column, 3:unknown) -num_skiplines=32 comment_id=# delimiter= -### SPEC Format scan_id=#S scan_delimiter= -columnname_id=#L columnname_delimiter= -data_id= data_delimiter= -### CHI Format -### nxm column Format -### End of file format - -##### Data&Background -samfile=Ag_1-6_srXp_qspace.chi num_sams=1 -sambkgfile=bkgd_1-14_srXp_qspace.chi num_sambkgs=1 -confile= num_cons=1 -conbkgfile= num_conbkgs=1 -det# used xcol detcol deterrcol xmin xmax add_det mul_det add_bkg mul_bkg add_con mul_con add_conbkg mul_conbkg - 0 1 0 1 2 0.700000 36.0000 0.000000 6.00000 0.000000 1.50000 0.000000 1.00000 0.000000 1.00000 - -##### Experiment_Setup -title=PDF analysis -user=me -facility=In house -temperature=300.000 containermut=0.0200000 filtermut=0.0200000 -## X-Ray radiationtype=3 - (0: Ag K_alpha, 1:Cu K_alpha, 2:Mo K_alpha, 3:Customize) -lambda=0.126514 energy=98.0010 polartype=0 polardegree=1.00000 -## MonoChromator crystaltype=0 (0:Perfect, 1:Mosaic, 2:None) -position=0 (0:Primary beam, 1:Diffracted beam) -dspacetype=0 (0:Si{111}, 1:Ge{111}, 2:Customize) dspacing=3.13200 - -##### Sample_Setup information num_atoms=1 -#L symbol valence fractions z user_f1 user_f2 user_macoef - Ag 0.00 1.000000 47 0.000000 0.000000 0.000000 -geometry=2 mut=1.1059000 numberdensity=0.0400000 -thickness=0.000000 packingFraction=0.000000 theory_mut=0.000000 - -##### GetIQ_Setup -xformat=2 -smoothcorr_isa=0 selfnormalize_isa=0 -#L par_name sample sample_bkg container container_bkg -smooth_degree 2 2 2 2 -smooth_width 6 6 6 6 -selfnormalize 0 0 0 0 -filtercorr_isa=0 samfiltercorr_isa=0 sambkgfiltercorr_isa=0 -confiltercorr_isa=0 conbkgfiltercorr_isa=0 -scatveffcorr_isa=0 samconveffcorr_isa=1 sambkgveffcorr_isa=1 -conbkgveffcorr_isa=1 -nonegative_isa=1 negativevalue=-1.00000 - -##### Calibration_Data -## Detection efficiency energy dependence detedepxaxis=0 -detedepfunctype=0 detedep_elastic=1.00000 detedep_fluores=1.80000 -detedep_quadra=0.000000 detedep_spline=0.000000 detedep_file= -## Detector transmission energy dependence dettcoefxaxis=0 -dettcoeffunctype=0 dettcoef_elastic=0.950000 dettcoef_fluores=0.600000 -dettcoef_quadra=0.000000 dettcoef_spline=0.000000 dettcoef_file= - -##### IQ_Simulation -### Elastic used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 -### Compton used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 -### Fluores used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 - -##### Correction_Setup corrmethod=0 -oblincident_isa=1 dettranscoef=0.999900 samfluore_isa=1 -samfluoretype=0 samfluorescale=1628.4198 -multiscat_isa=1 xraypolar_isa=1 samabsorp_isa=1 -highqscale_isa=1 highqratio=0.600000 scaleconst=0.028459948 -scaleconst_theory=0.028459948 -comptonscat_isa=1 rulandwin_isa=0 rulandintewidth=0.0100000 -comptonmethod=0 breitdirac_isa=1 breitdiracexponent=2 -detefficiency_isa=1 detefficiencytype=2 (0-1: linear, 2-3: quadratic) -detefficiency_a=-0.32297253 detefficiency_b=0.010064852 -lauediffuse_isa=1 -weight_isa=1 weighttype=0 (0: ^2, 1: , 2: Data Smoothed) -weightsmoothrmin=3.00000 weightsmoothwidth=100 weightsmoothcycles=600 -editsq_isa=0 editsqtype=0 add_sq=0.000000 mul_sq=1.00000 -editsqsmoothrmin=3.00000 editsqsmoothwidth=100 editsqsmoothcycles=600 -smoothdata_isa=0 smoothfunctype=0 smoothqmin=12.0000 smoothboxwidth=9 -interpolateqmin_isa=0 qmininterpolationtype=0 -dampfq_isa=0 dampfqtype=0 dampfqwidth=40.0000 - -##### SqGr_Optimization Setup -ftmethod=0 -## S(q) qmin=1.000000 qmax=30.000000 qgrid=0.000000 -## G(r) rmin=0.000000 rmax=35.000000 rgrid=0.104720 -## SqOptimization sqoptfunction=1 -optqmin=20.0000 optqmax=38.0000 optqgrid=0.000000 -optrmin=0.000000 optrmax=2.20000 optrgrid=0.0200000 -maxiter=20 relstep=0.000000 weighttype=0 weightfunc=0 -fitbkgmult_isa=1 fitsampmut_isa=0 fitpolariz_isa=0 -fitoblique_isa=1 fitfluores_isa=1 -fitrulandw_isa=0 fitenergya_isa=1 fitenergyb_isa=1 -fitsimurulandw_isa=1 fitDetEdepfluores_isa=0 fitDetEdepquadra_isa=0 -fitDetEdepspline_isa=0 fitDetTCoefElastic_isa=0 fitDetTCoefFluores_isa=0 -fitDetTcoefquadra_isa=0 fitDetTcoefspline_isa=0 - -##### Save&Plot Settings -datatype=GrData iqcorrtype=Int iqsimutype=SimuIq -sqcorrtype=Absorp sqtofqtype=FqData -gropttype=OptFq miscdatatype=AtomASF -##### start data -#F Ag_1-6_srXp_qspace.gr -#D Sat Feb 21 19:07:17 2015 -#C -#S 1 G(r) -#D -#L r(A) G(r) d_r d_Gr - 1.047198e-001 -8.482171e-001 -5.263789e-002 2.765272e-001 - 2.094395e-001 -4.389751e-001 -1.052758e-001 3.758883e-001 - 3.141593e-001 -7.245989e-002 -1.579137e-001 3.993384e-001 - 4.188790e-001 7.010412e-002 -2.105516e-001 4.062425e-001 - 5.235988e-001 2.410039e-001 -2.631895e-001 4.092704e-001 - 6.283185e-001 -1.081419e+000 -3.158273e-001 4.108721e-001 - 7.330383e-001 -7.305268e-001 -3.684652e-001 4.118211e-001 - 8.377581e-001 -7.892482e-001 -4.211031e-001 4.124392e-001 - 9.424778e-001 -4.799765e-001 -4.737410e-001 4.128434e-001 - 1.047198e+000 -5.515252e-001 -5.263789e-001 4.131494e-001 - 1.151917e+000 -5.276302e-001 -5.790168e-001 4.133937e-001 - 1.256637e+000 -4.785339e-001 -6.316547e-001 4.135703e-001 - 1.361357e+000 -7.453648e-001 -6.842926e-001 4.136500e-001 - 1.466077e+000 -8.511180e-001 -7.369305e-001 4.140212e-001 - 1.570796e+000 -8.502626e-001 -7.895684e-001 4.138731e-001 - 1.675516e+000 -8.591459e-001 -8.422062e-001 4.139608e-001 - 1.780236e+000 -9.441510e-001 -8.948441e-001 4.140158e-001 - 1.884956e+000 -9.574570e-001 -9.474820e-001 4.140681e-001 - 1.989675e+000 -9.424363e-001 -1.000120e+000 4.140688e-001 - 2.094395e+000 -1.062015e+000 -1.052758e+000 4.141887e-001 - 2.199115e+000 -9.869438e-001 -1.105396e+000 4.141705e-001 - 2.303835e+000 -1.155167e+000 -1.158034e+000 4.142069e-001 - 2.408554e+000 -9.980358e-001 -1.210671e+000 4.142000e-001 - 2.513274e+000 -1.075531e+000 -1.263309e+000 4.142505e-001 - 2.617994e+000 -6.605810e-001 -1.315947e+000 4.142869e-001 - 2.722714e+000 2.096964e+000 -1.368585e+000 4.142760e-001 - 2.827433e+000 8.654147e+000 -1.421223e+000 4.142350e-001 - 2.932153e+000 9.775080e+000 -1.473861e+000 4.143683e-001 - 3.036873e+000 3.943275e+000 -1.526499e+000 4.143157e-001 - 3.141593e+000 -2.514541e-001 -1.579137e+000 4.142939e-001 - 3.246312e+000 -1.592664e+000 -1.631775e+000 4.143335e-001 - 3.351032e+000 -1.876345e+000 -1.684412e+000 4.143717e-001 - 3.455752e+000 -2.079538e+000 -1.737050e+000 4.143361e-001 - 3.560472e+000 -2.093879e+000 -1.789688e+000 4.143605e-001 - 3.665192e+000 -2.136690e+000 -1.842326e+000 4.143777e-001 - 3.769911e+000 -1.959548e+000 -1.894964e+000 4.142160e-001 - 3.874631e+000 -1.372087e+000 -1.947602e+000 4.145213e-001 - 3.979351e+000 -3.297568e-002 -2.000240e+000 4.143604e-001 - 4.084071e+000 1.100315e+000 -2.052878e+000 4.143672e-001 - 4.188790e+000 4.695537e-001 -2.105516e+000 4.144080e-001 - 4.293510e+000 -1.151144e+000 -2.158154e+000 4.143034e-001 - 4.398230e+000 -2.153572e+000 -2.210791e+000 4.145074e-001 - 4.502950e+000 -2.411787e+000 -2.263429e+000 4.143658e-001 - 4.607669e+000 -2.412125e+000 -2.316067e+000 4.144454e-001 - 4.712389e+000 -1.884849e+000 -2.368705e+000 4.143957e-001 - 4.817109e+000 4.647600e-001 -2.421343e+000 4.144191e-001 - 4.921829e+000 5.563233e+000 -2.473981e+000 4.144200e-001 - 5.026548e+000 8.652539e+000 -2.526619e+000 4.144247e-001 - 5.131268e+000 5.240243e+000 -2.579257e+000 4.143801e-001 - 5.235988e+000 4.094542e-002 -2.631895e+000 4.144333e-001 - 5.340708e+000 -2.486274e+000 -2.684532e+000 4.144703e-001 - 5.445427e+000 -3.024232e+000 -2.737170e+000 4.144277e-001 - 5.550147e+000 -2.602965e+000 -2.789808e+000 4.143470e-001 - 5.654867e+000 -8.422798e-001 -2.842446e+000 4.144955e-001 - 5.759587e+000 1.189013e+000 -2.895084e+000 4.144083e-001 - 5.864306e+000 8.941194e-001 -2.947722e+000 4.144400e-001 - 5.969026e+000 -1.288374e+000 -3.000360e+000 4.143993e-001 - 6.073746e+000 -2.721730e+000 -3.052998e+000 4.144537e-001 - 6.178466e+000 -2.710301e+000 -3.105636e+000 4.144685e-001 - 6.283185e+000 -9.417379e-001 -3.158273e+000 4.143536e-001 - 6.387905e+000 2.425977e+000 -3.210911e+000 4.145365e-001 - 6.492625e+000 4.332789e+000 -3.263549e+000 4.144362e-001 - 6.597345e+000 2.210928e+000 -3.316187e+000 4.143902e-001 - 6.702065e+000 -1.306001e+000 -3.368825e+000 4.144907e-001 - 6.806784e+000 -3.032653e+000 -3.421463e+000 4.144324e-001 - 6.911504e+000 -2.905821e+000 -3.474101e+000 4.143906e-001 - 7.016224e+000 -1.871671e+000 -3.526739e+000 4.144803e-001 - 7.120944e+000 -1.230436e+000 -3.579377e+000 4.144227e-001 - 7.225663e+000 -1.929410e+000 -3.632014e+000 4.143587e-001 - 7.330383e+000 -2.517905e+000 -3.684652e+000 4.145090e-001 - 7.435103e+000 -9.698864e-001 -3.737290e+000 4.144201e-001 - 7.539823e+000 3.969724e+000 -3.789928e+000 4.144356e-001 - 7.644542e+000 8.885499e+000 -3.842566e+000 4.144505e-001 - 7.749262e+000 7.423599e+000 -3.895204e+000 4.144687e-001 - 7.853982e+000 1.538363e+000 -3.947842e+000 4.144690e-001 - 7.958702e+000 -2.446426e+000 -4.000480e+000 4.144434e-001 - 8.063421e+000 -3.261121e+000 -4.053118e+000 4.144111e-001 - 8.168141e+000 -2.948821e+000 -4.105755e+000 4.145219e-001 - 8.272861e+000 -2.909039e+000 -4.158393e+000 4.143796e-001 - 8.377581e+000 -3.056890e+000 -4.211031e+000 4.144955e-001 - 8.482300e+000 -1.787583e+000 -4.263669e+000 4.144445e-001 - 8.587020e+000 1.383534e+000 -4.316307e+000 4.144460e-001 - 8.691740e+000 3.941268e+000 -4.368945e+000 4.144502e-001 - 8.796460e+000 2.456759e+000 -4.421583e+000 4.143988e-001 - 8.901179e+000 -5.916247e-001 -4.474221e+000 4.145152e-001 - 9.005899e+000 -1.306963e+000 -4.526859e+000 4.144222e-001 - 9.110619e+000 1.201397e-001 -4.579496e+000 4.144654e-001 - 9.215339e+000 4.313306e-001 -4.632134e+000 4.144388e-001 - 9.320058e+000 -1.161763e+000 -4.684772e+000 4.144548e-001 - 9.424778e+000 -1.861300e+000 -4.737410e+000 4.144297e-001 - 9.529498e+000 -5.442582e-001 -4.790048e+000 4.144823e-001 - 9.634218e+000 4.506053e-001 -4.842686e+000 4.144444e-001 - 9.738937e+000 -6.691029e-001 -4.895324e+000 4.144652e-001 - 9.843657e+000 -1.738902e+000 -4.947962e+000 4.144644e-001 - 9.948377e+000 -8.162676e-001 -5.000600e+000 4.144417e-001 - 1.005310e+001 2.903759e-001 -5.053237e+000 4.144549e-001 - 1.015782e+001 1.157368e-002 -5.105875e+000 4.144527e-001 - 1.026254e+001 1.150713e+000 -5.158513e+000 4.144868e-001 - 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-##### General_Setting -title=X-ray PDF -workingdirectory=F:\2009-1\Juhas\reduced\ -sourcedir=C:\Program Files\Pdfgetx2\ -logfile=.pdfgetx2.log -quiet=0 debug=0 autosave_isa=1 savefilenamebase=C60pos01_300k_90keV_410-452sum -iqfilesurfix=.iq sqfilesurfix=.sq fqfilesurfix=.fq grfilesurfix=.gr - -##### DataFileFormat -datatype=1 (0:SPEC, 1:CHI, 2:nxm column, 3:unknown) -num_skiplines=46 comment_id=# delimiter= -### SPEC Format scan_id=#S scan_delimiter= -columnname_id=#L columnname_delimiter= -data_id= data_delimiter= -### CHI Format -### nxm column Format -### End of file format - -##### Data&Background -samfile=C60pos01_300k_90keV_410-452sum.chi num_sams=1 -sambkgfile=emptyKapton1mm_300k_90keV_483-487sum.chi num_sambkgs=1 -confile= num_cons=1 -conbkgfile= num_conbkgs=1 -det# used xcol detcol deterrcol xmin xmax add_det mul_det add_bkg mul_bkg add_con mul_con add_conbkg mul_conbkg - 0 1 0 1 3 0.782256 40.0000 0.000000 1.00000 0.000000 1.00000 0.000000 1.00000 0.000000 1.00000 - -##### Experiment_Setup -title=PDF analysis -user=me -facility=In house -temperature=300.000 containermut=0.000500000 filtermut=0.0200000 -## X-Ray radiationtype=3 - (0: Ag K_alpha, 1:Cu K_alpha, 2:Mo K_alpha, 3:Customize) -lambda=0.137020 energy=90.4868 polartype=0 polardegree=1.00000 -## MonoChromator crystaltype=0 (0:Perfect, 1:Mosaic, 2:None) -position=0 (0:Primary beam, 1:Diffracted beam) -dspacetype=0 (0:Si{111}, 1:Ge{111}, 2:Customize) dspacing=3.13200 - -##### Sample_Setup information num_atoms=1 -#L symbol valence fractions z user_f1 user_f2 user_macoef - C 0.00 1.000000 6 0.000000 0.000000 0.001000 -geometry=3 mut=0.00092986300 numberdensity=0.00600000 -thickness=1.00000 packingFraction=0.500000 theory_mut=0.000929863 - -##### GetIQ_Setup -xformat=1 -smoothcorr_isa=0 selfnormalize_isa=0 -#L par_name sample sample_bkg container container_bkg -smooth_degree 2 2 2 2 -smooth_width 6 6 6 6 -selfnormalize 0 0 0 0 -filtercorr_isa=0 samfiltercorr_isa=0 sambkgfiltercorr_isa=0 -confiltercorr_isa=0 conbkgfiltercorr_isa=0 -scatveffcorr_isa=0 samconveffcorr_isa=0 sambkgveffcorr_isa=1 -conbkgveffcorr_isa=0 -nonegative_isa=1 negativevalue=-1.00000 - -##### Calibration_Data -## Detection efficiency energy dependence detedepxaxis=0 -detedepfunctype=0 detedep_elastic=1.00000 detedep_fluores=1.80000 -detedep_quadra=0.000000 detedep_spline=0.000000 detedep_file= -## Detector transmission energy dependence dettcoefxaxis=0 -dettcoeffunctype=0 dettcoef_elastic=0.950000 dettcoef_fluores=0.600000 -dettcoef_quadra=0.000000 dettcoef_spline=0.000000 dettcoef_file= - -##### IQ_Simulation -### Elastic used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 -### Compton used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 -### Fluores used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 - -##### Correction_Setup corrmethod=0 -oblincident_isa=1 dettranscoef=0.980000 samfluore_isa=1 -samfluoretype=0 samfluorescale=9603.8072 -multiscat_isa=1 xraypolar_isa=1 samabsorp_isa=1 -highqscale_isa=0 highqratio=0.600000 scaleconst=10.000000 -scaleconst_theory=24.474931 -comptonscat_isa=1 rulandwin_isa=0 rulandintewidth=0.0100000 -comptonmethod=0 breitdirac_isa=1 breitdiracexponent=3 -detefficiency_isa=1 detefficiencytype=2 (0-1: linear, 2-3: quadratic) -detefficiency_a=-50.000000 detefficiency_b=-191.71183 -lauediffuse_isa=1 -weight_isa=1 weighttype=0 (0: ^2, 1: , 2: Data Smoothed) -weightsmoothrmin=3.00000 weightsmoothwidth=100 weightsmoothcycles=600 -editsq_isa=0 editsqtype=0 add_sq=0.000000 mul_sq=1.00000 -editsqsmoothrmin=3.00000 editsqsmoothwidth=100 editsqsmoothcycles=600 -smoothdata_isa=0 smoothfunctype=0 smoothqmin=12.0000 smoothboxwidth=9 -interpolateqmin_isa=0 qmininterpolationtype=0 -dampfq_isa=0 dampfqtype=0 dampfqwidth=23.0000 - -##### SqGr_Optimization Setup -ftmethod=0 -## S(q) qmin=0.010000 qmax=21.299999 qgrid=0.010000 -## G(r) rmin=0.010000 rmax=20.000000 rgrid=0.010000 -## SqOptimization sqoptfunction=1 -optqmin=15.0000 optqmax=22.0000 optqgrid=0.000000 -optrmin=0.000000 optrmax=2.20000 optrgrid=0.0200000 -maxiter=20 relstep=0.000000 weighttype=0 weightfunc=0 -fitbkgmult_isa=0 fitsampmut_isa=0 fitpolariz_isa=0 -fitoblique_isa=0 fitfluores_isa=1 -fitrulandw_isa=0 fitenergya_isa=1 fitenergyb_isa=1 -fitsimurulandw_isa=1 fitDetEdepfluores_isa=0 fitDetEdepquadra_isa=0 -fitDetEdepspline_isa=0 fitDetTCoefElastic_isa=0 fitDetTCoefFluores_isa=0 -fitDetTcoefquadra_isa=0 fitDetTcoefspline_isa=0 - -##### Save&Plot Settings -datatype=SqtoFq iqcorrtype=Int iqsimutype=SimuIq -sqcorrtype=Oblin sqtofqtype=FqData -gropttype=OptFq miscdatatype=AtomASF -##### start data -#F C60pos01_300k_90keV_410-452sum.gr -#D Fri Mar 20 01:26:57 2009 -#C -#S 1 G(r) -#D -#L r G(r) d_r d_Gr - 1.000000e-002 1.894260e+004 -7.539822e-004 8.536912e+000 - 2.000000e-002 3.772272e+004 -1.507964e-003 1.675464e+001 - 3.000000e-002 5.617755e+004 -2.261947e-003 2.434705e+001 - 4.000000e-002 7.414385e+004 -3.015929e-003 3.103361e+001 - 5.000000e-002 9.145791e+004 -3.769911e-003 3.657098e+001 - 6.000000e-002 1.079561e+005 -4.523893e-003 4.076327e+001 - 7.000000e-002 1.234755e+005 -5.277876e-003 4.347065e+001 - 8.000000e-002 1.378555e+005 -6.031858e-003 4.461615e+001 - 9.000000e-002 1.509396e+005 -6.785840e-003 4.419097e+001 - 1.000000e-001 1.625776e+005 -7.539822e-003 4.225878e+001 - 1.100000e-001 1.726287e+005 -8.293804e-003 3.896113e+001 - 1.200000e-001 1.809643e+005 -9.047787e-003 3.452824e+001 - 1.300000e-001 1.874722e+005 -9.801769e-003 2.930697e+001 - 1.400000e-001 1.920600e+005 -1.055575e-002 2.383587e+001 - 1.500000e-001 1.946585e+005 -1.130973e-002 1.902762e+001 - 1.600000e-001 1.952258e+005 -1.206372e-002 1.638514e+001 - 1.700000e-001 1.937504e+005 -1.281770e-002 1.723828e+001 - 1.800000e-001 1.902538e+005 -1.357168e-002 2.094617e+001 - 1.900000e-001 1.847926e+005 -1.432566e-002 2.582197e+001 - 2.000000e-001 1.774602e+005 -1.507964e-002 3.069799e+001 - 2.100000e-001 1.683863e+005 -1.583363e-002 3.493789e+001 - 2.200000e-001 1.577369e+005 -1.658761e-002 3.818417e+001 - 2.300000e-001 1.457120e+005 -1.734159e-002 4.023614e+001 - 2.400000e-001 1.325429e+005 -1.809557e-002 4.100325e+001 - 2.500000e-001 1.184878e+005 -1.884956e-002 4.048837e+001 - 2.600000e-001 1.038270e+005 -1.960354e-002 3.878377e+001 - 2.700000e-001 8.885653e+004 -2.035752e-002 3.607536e+001 - 2.800000e-001 7.388159e+004 -2.111150e-002 3.265653e+001 - 2.900000e-001 5.920896e+004 -2.186548e-002 2.895580e+001 - 3.000000e-001 4.513929e+004 -2.261947e-002 2.557279e+001 - 3.100000e-001 3.195916e+004 -2.337345e-002 2.326275e+001 - 3.200000e-001 1.993340e+004 -2.412743e-002 2.270262e+001 - 3.300000e-001 9.297645e+003 -2.488141e-002 2.402850e+001 - 3.400000e-001 2.517043e+002 -2.563540e-002 2.670812e+001 - 3.500000e-001 -7.046274e+003 -2.638938e-002 2.996591e+001 - 3.600000e-001 -1.248447e+004 -2.714336e-002 3.314959e+001 - 3.700000e-001 -1.600078e+004 -2.789734e-002 3.580905e+001 - 3.800000e-001 -1.758475e+004 -2.865132e-002 3.766190e+001 - 3.900000e-001 -1.727796e+004 -2.940531e-002 3.855493e+001 - 4.000000e-001 -1.517287e+004 -3.015929e-002 3.844112e+001 - 4.100000e-001 -1.141006e+004 -3.091327e-002 3.736925e+001 - 4.200000e-001 -6.173989e+003 -3.166725e-002 3.548194e+001 - 4.300000e-001 3.126408e+002 -3.242124e-002 3.302011e+001 - 4.400000e-001 7.795703e+003 -3.317522e-002 3.033101e+001 - 4.500000e-001 1.599747e+004 -3.392920e-002 2.786765e+001 - 4.600000e-001 2.462518e+004 -3.468318e-002 2.614265e+001 - 4.700000e-001 3.338004e+004 -3.543716e-002 2.558220e+001 - 4.800000e-001 4.196639e+004 -3.619115e-002 2.631236e+001 - 4.900000e-001 5.010074e+004 -3.694513e-002 2.807912e+001 - 5.000000e-001 5.752033e+004 -3.769911e-002 3.040568e+001 - 5.100000e-001 6.399094e+004 -3.845309e-002 3.280443e+001 - 5.200000e-001 6.931374e+004 -3.920708e-002 3.488602e+001 - 5.300000e-001 7.333084e+004 -3.996106e-002 3.638107e+001 - 5.400000e-001 7.592949e+004 -4.071504e-002 3.713103e+001 - 5.500000e-001 7.704472e+004 -4.146902e-002 3.707615e+001 - 5.600000e-001 7.666028e+004 -4.222300e-002 3.624777e+001 - 5.700000e-001 7.480809e+004 -4.297699e-002 3.476520e+001 - 5.800000e-001 7.156590e+004 -4.373097e-002 3.283546e+001 - 5.900000e-001 6.705361e+004 -4.448495e-002 3.075143e+001 - 6.000000e-001 6.142812e+004 -4.523893e-002 2.887649e+001 - 6.100000e-001 5.487708e+004 -4.599292e-002 2.759254e+001 - 6.200000e-001 4.761168e+004 -4.674690e-002 2.719280e+001 - 6.300000e-001 3.985885e+004 -4.750088e-002 2.775707e+001 - 6.400000e-001 3.185305e+004 -4.825486e-002 2.911213e+001 - 6.500000e-001 2.382798e+004 -4.900884e-002 3.092008e+001 - 6.600000e-001 1.600861e+004 -4.976283e-002 3.280949e+001 - 6.700000e-001 8.603690e+003 -5.051681e-002 3.446217e+001 - 6.800000e-001 1.798989e+003 -5.127079e-002 3.564602e+001 - 6.900000e-001 -4.248345e+003 -5.202477e-002 3.621989e+001 - 7.000000e-001 -9.414296e+003 -5.277876e-002 3.612981e+001 - 7.100000e-001 -1.361113e+004 -5.353274e-002 3.540484e+001 - 7.200000e-001 -1.678913e+004 -5.428672e-002 3.415408e+001 - 7.300000e-001 -1.893683e+004 -5.504070e-002 3.256366e+001 - 7.400000e-001 -2.007990e+004 -5.579468e-002 3.088879e+001 - 7.500000e-001 -2.027862e+004 -5.654867e-002 2.943093e+001 - 7.600000e-001 -1.962413e+004 -5.730265e-002 2.848585e+001 - 7.700000e-001 -1.823367e+004 -5.805663e-002 2.826030e+001 - 7.800000e-001 -1.624501e+004 -5.881061e-002 2.879264e+001 - 7.900000e-001 -1.381022e+004 -5.956460e-002 2.993744e+001 - 8.000000e-001 -1.108914e+004 -6.031858e-002 3.142871e+001 - 8.100000e-001 -8.242848e+003 -6.107256e-002 3.297014e+001 - 8.200000e-001 -5.427209e+003 -6.182654e-002 3.430074e+001 - 8.300000e-001 -2.786985e+003 -6.258052e-002 3.522605e+001 - 8.400000e-001 -4.505475e+002 -6.333451e-002 3.562775e+001 - 8.500000e-001 1.474503e+003 -6.408849e-002 3.546437e+001 - 8.600000e-001 2.904712e+003 -6.484247e-002 3.476932e+001 - 8.700000e-001 3.783006e+003 -6.559645e-002 3.364815e+001 - 8.800000e-001 4.079739e+003 -6.635044e-002 3.227359e+001 - 8.900000e-001 3.792539e+003 -6.710442e-002 3.087378e+001 - 9.000000e-001 2.944995e+003 -6.785840e-002 2.970558e+001 - 9.100000e-001 1.584281e+003 -6.861238e-002 2.900505e+001 - 9.200000e-001 -2.221585e+002 -6.936636e-002 2.892054e+001 - 9.300000e-001 -2.390679e+003 -7.012035e-002 2.945951e+001 - 9.400000e-001 -4.826074e+003 -7.087433e-002 3.048692e+001 - 9.500000e-001 -7.426548e+003 -7.162831e-002 3.177713e+001 - 9.600000e-001 -1.008880e+004 -7.238229e-002 3.308207e+001 - 9.700000e-001 -1.271298e+004 -7.313628e-002 3.418261e+001 - 9.800000e-001 -1.520728e+004 -7.389026e-002 3.491556e+001 - 9.900000e-001 -1.749203e+004 -7.464424e-002 3.518420e+001 - 1.000000e+000 -1.950295e+004 -7.539822e-002 3.496061e+001 - 1.010000e+000 -2.119365e+004 -7.615220e-002 3.428473e+001 - 1.020000e+000 -2.253705e+004 -7.690619e-002 3.326127e+001 - 1.030000e+000 -2.352587e+004 -7.766017e-002 3.205297e+001 - 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1.974000e+001 -4.976028e+003 -1.488361e+000 3.242698e+001 - 1.975000e+001 -4.869854e+003 -1.489115e+000 3.237962e+001 - 1.976000e+001 -4.746151e+003 -1.489869e+000 3.231788e+001 - 1.977000e+001 -4.604263e+003 -1.490623e+000 3.225276e+001 - 1.978000e+001 -4.444126e+003 -1.491377e+000 3.219591e+001 - 1.979000e+001 -4.266319e+003 -1.492131e+000 3.215754e+001 - 1.980000e+001 -4.072094e+003 -1.492885e+000 3.214456e+001 - 1.981000e+001 -3.863382e+003 -1.493639e+000 3.215930e+001 - 1.982000e+001 -3.642757e+003 -1.494393e+000 3.219906e+001 - 1.983000e+001 -3.413375e+003 -1.495147e+000 3.225662e+001 - 1.984000e+001 -3.178885e+003 -1.495901e+000 3.232162e+001 - 1.985000e+001 -2.943306e+003 -1.496655e+000 3.238241e+001 - 1.986000e+001 -2.710888e+003 -1.497409e+000 3.242820e+001 - 1.987000e+001 -2.485948e+003 -1.498163e+000 3.245088e+001 - 1.988000e+001 -2.272705e+003 -1.498917e+000 3.244648e+001 - 1.989000e+001 -2.075097e+003 -1.499671e+000 3.241579e+001 - 1.990000e+001 -1.896621e+003 -1.500425e+000 3.236427e+001 - 1.991000e+001 -1.740167e+003 -1.501179e+000 3.230107e+001 - 1.992000e+001 -1.607884e+003 -1.501933e+000 3.223747e+001 - 1.993000e+001 -1.501069e+003 -1.502687e+000 3.218487e+001 - 1.994000e+001 -1.420087e+003 -1.503441e+000 3.215273e+001 - 1.995000e+001 -1.364332e+003 -1.504195e+000 3.214685e+001 - 1.996000e+001 -1.332228e+003 -1.504949e+000 3.216827e+001 - 1.997000e+001 -1.321270e+003 -1.505703e+000 3.221309e+001 - 1.998000e+001 -1.328107e+003 -1.506456e+000 3.227321e+001 - 1.999000e+001 -1.348668e+003 -1.507210e+000 3.233782e+001 diff --git a/doc/examples/data/C60baseline.dat b/doc/examples/data/C60baseline.dat deleted file mode 100644 index f7639b6..0000000 --- a/doc/examples/data/C60baseline.dat +++ /dev/null @@ -1,107 +0,0 @@ -# Baseline estimated by subtracting interparticle contribution to PDF estimated -# from FCC lattice of hollow spherical shells with radius r1 and r2, and lattice -# parameter a. Parameters estimated by fitting PDF from 7.5 to 20 angstroms, -# with a few points near likely baseline below 7.5 angstroms to constrain in -# single-molecule region. -# C60baseline[r, r1, r2, a, scale] -# {r1 -> 3.06816, r2 -> 4.05546, a -> 14.1103, scale -> 13740.2} -0.1 -1475.0325650706627 -0.2 -2950.0651301413254 -0.30000000000000004 -4425.097695211988 -0.4 -5900.130260282651 -0.5 -7375.162825353313 -0.6 -8850.195390423974 -0.7000000000000001 -10325.227955494638 -0.8 -11800.260520565302 -0.9 -13275.293085635964 -1. -14750.325650706625 -1.1 -16225.358215777289 -1.2000000000000002 -17700.390780847953 -1.3000000000000003 -19175.423345918618 -1.4000000000000001 -20650.455910989276 -1.5000000000000002 -22125.48847605994 -1.6 -23600.521041130603 -1.7000000000000002 -25075.553606201265 -1.8000000000000003 -26550.58617127193 -1.9000000000000001 -28025.4599334596 -2. -29490.66450359999 -2.1 -30922.864389112267 -2.2 -32298.695523408274 -2.3000000000000003 -33596.02271110294 -2.4000000000000004 -34793.92402828217 -2.5000000000000004 -35872.67522277091 -2.6 -36813.734114401064 -2.7 -37599.72499527952 -2.8000000000000003 -38214.42303005611 -2.9000000000000004 -38643.36877998671 -3.0000000000000004 -38890.46318760791 -3.1 -38978.52316580303 -3.2 -38930.29758324947 -3.3000000000000003 -38767.46243474178 -3.4000000000000004 -38510.63644092366 -3.5000000000000004 -38179.39664801996 -3.6 -37792.294027568765 -3.7 -37366.86907615337 -3.8000000000000003 -36919.66741513431 -3.9000000000000004 -36465.76231472305 -4. -36011.685031151355 -4.1 -35557.60774757967 -4.2 -35103.53046400798 -4.3 -34649.45318043629 -4.3999999999999995 -34195.37589686459 -4.5 -33741.29861329292 -4.6 -33287.22132972121 -4.7 -32833.14404614952 -4.8 -32379.06676257782 -4.9 -31924.98947900614 -5. -31470.91219543446 -5.1 -31016.83491186277 -5.2 -30562.757628291063 -5.3 -30108.680344719356 -5.4 -29654.60306114771 -5.5 -29200.525777575986 -5.6 -28746.448494004322 -5.7 -28292.371210432615 -5.8 -27838.293926860926 -5.9 -27384.216643289248 -6. -26930.139359411234 -6.1 -26474.542488478357 -6.2 -26010.083575850655 -6.3 -25528.358372275903 -6.4 -25021.398910324362 -6.5 -24481.667989050857 -6.6 -23902.053658656267 -6.7 -23275.86370514998 -6.8 -22596.820135010832 -6.9 -21859.053659849822 -7. -21057.103538030915 -7.1 -20189.157506289514 -7.2 -19262.2608478449 -7.3 -18284.582204221027 -7.4 -17263.909088500266 -7.5 -16207.653400662406 -7.6 -15122.856942922259 -7.7 -14016.19693506814 -7.8 -12893.991529799485 -7.9 -11762.205328065833 -8. -10626.439769837914 -8.1 -9490.319158451903 -8.2 -8354.198547065878 -8.3 -7218.0779356797575 -8.4 -6081.957324293807 -8.5 -4945.8367129076605 -8.6 -3809.7161015215393 -8.7 -2673.5954901353934 -8.8 -1537.4748787493209 -8.9 -401.35426736339457 -9. 734.7602819151251 -9.1 1862.3074495985777 -9.2 2947.158200990089 -9.3 3960.188485831431 -9.4 4888.604831527597 -9.5 5719.720210100222 -9.6 6439.247704671418 -9.700000000000001 7031.349721945532 -9.8 7478.687204694779 -9.9 7762.46884423828 -10. 7862.653161699448 diff --git a/doc/examples/data/TiO2_fine_qmax26.gr b/doc/examples/data/TiO2_fine_qmax26.gr deleted file mode 100644 index 500fc51..0000000 --- a/doc/examples/data/TiO2_fine_qmax26.gr +++ /dev/null @@ -1,2134 +0,0 @@ -History written: Tue Apr 22 15:42:25 2008 -Produced by Luke -####### Get_XPDF ####### - -##### General_Setting -title=X-ray PDF -workingdirectory=D:\LargeResearchFiles\Diffraction\mucat200804\TiO2_rutile\work\ -sourcedir=C:\Program Files\PDFgetX2\ -logfile=.pdfgetx2.log -quiet=0 debug=0 autosave_isa=1 savefilenamebase=tio2r_300k_1-6_srXp_qspace -iqfilesurfix=.iq sqfilesurfix=.sq fqfilesurfix=.fq grfilesurfix=.gr - -##### DataFileFormat -datatype=2 (0:SPEC, 1:CHI, 2:nxm column, 3:unknown) -num_skiplines=32 comment_id=# delimiter= -### SPEC Format scan_id=#S scan_delimiter= -columnname_id=#L columnname_delimiter= -data_id= data_delimiter= -### CHI Format -### nxm column Format -### End of file format - -##### Data&Background -samfile=tio2r_300k_1-6_srXp_qspace.chi num_sams=1 -sambkgfile=kapton_bgrd_300k_2-3_srXp_qspace.chi num_sambkgs=1 -confile= num_cons=1 -conbkgfile= num_conbkgs=1 -det# used xcol detcol deterrcol xmin xmax add_det mul_det add_bkg mul_bkg add_con mul_con add_conbkg mul_conbkg - 0 1 0 1 2 0.500000 27.0000 0.000000 0.526067 0.000000 0.0776796 0.000000 1.00000 0.000000 1.00000 - -##### Experiment_Setup -title=PDF analysis -user=AM -facility=APS 6ID-D -temperature=300.000 containermut=0.000500000 filtermut=0.0200000 -## X-Ray radiationtype=3 - (0: Ag K_alpha, 1:Cu K_alpha, 2:Mo K_alpha, 3:Customize) -lambda=0.142773 energy=86.8406 polartype=2 polardegree=0.960000 -## MonoChromator crystaltype=0 (0:Perfect, 1:Mosaic, 2:None) -position=0 (0:Primary beam, 1:Diffracted beam) -dspacetype=0 (0:Si{111}, 1:Ge{111}, 2:Customize) dspacing=3.13200 - -##### Sample_Setup information num_atoms=2 -#L symbol valence fractions z user_f1 user_f2 user_macoef - O 0.00 2.000000 8 0.000000 0.000000 0.001000 - Ti 0.00 1.000000 22 0.000000 0.000000 0.001000 -geometry=2 mut=0.50000000 numberdensity=0.00600000 -thickness=2.00000 packingFraction=0.500000 theory_mut=0.00717669 - -##### GetIQ_Setup -xformat=2 -smoothcorr_isa=0 selfnormalize_isa=0 -#L par_name sample sample_bkg container container_bkg -smooth_degree 2 2 2 2 -smooth_width 6 6 6 6 -selfnormalize 0 0 0 0 -filtercorr_isa=0 samfiltercorr_isa=0 sambkgfiltercorr_isa=0 -confiltercorr_isa=0 conbkgfiltercorr_isa=0 -scatveffcorr_isa=1 samconveffcorr_isa=1 sambkgveffcorr_isa=0 -conbkgveffcorr_isa=0 -nonegative_isa=1 negativevalue=-1.00000 - -##### Calibration_Data -## Detection efficiency energy dependence detedepxaxis=0 -detedepfunctype=0 detedep_elastic=1.00000 detedep_fluores=1.80000 -detedep_quadra=0.000000 detedep_spline=0.000000 detedep_file= -## Detector transmission energy dependence dettcoefxaxis=0 -dettcoeffunctype=0 dettcoef_elastic=0.950000 dettcoef_fluores=0.600000 -dettcoef_quadra=0.000000 dettcoef_spline=0.000000 dettcoef_file= - -##### IQ_Simulation -### Elastic used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 -### Compton used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 -### Fluores used_isa=1 mymethod=1 -do_samabsorp=1 do_multscat=1 do_conabsorp=0 do_airabsorp=0 -do_polarization=1 do_oblincident=0 do_energydep=0 -do_breitdirac=0 breitdiracexpo=2.00000 -do_rulandwin=0 rulandwinwidth=0.00100000 -do_useredit=0 add_user=0.000000 mul_user=1.00000 - -##### Correction_Setup corrmethod=0 -oblincident_isa=1 dettranscoef=0.980000 samfluore_isa=1 -samfluoretype=0 samfluorescale=-86.872335 -multiscat_isa=1 xraypolar_isa=1 samabsorp_isa=1 -highqscale_isa=1 highqratio=0.600000 scaleconst=0.040910432 -scaleconst_theory=0.040910432 -comptonscat_isa=1 rulandwin_isa=0 rulandintewidth=0.0100000 -comptonmethod=0 breitdirac_isa=1 breitdiracexponent=3 -detefficiency_isa=1 detefficiencytype=2 (0-1: linear, 2-3: quadratic) -detefficiency_a=0.041826118 detefficiency_b=-0.021345674 -lauediffuse_isa=1 -weight_isa=1 weighttype=0 (0: ^2, 1: , 2: Data Smoothed) -weightsmoothrmin=3.00000 weightsmoothwidth=100 weightsmoothcycles=600 -editsq_isa=0 editsqtype=0 add_sq=0.000000 mul_sq=1.00000 -editsqsmoothrmin=3.00000 editsqsmoothwidth=100 editsqsmoothcycles=600 -smoothdata_isa=0 smoothfunctype=0 smoothqmin=12.0000 smoothboxwidth=9 -interpolateqmin_isa=0 qmininterpolationtype=0 -dampfq_isa=0 dampfqtype=0 dampfqwidth=23.0000 - -##### SqGr_Optimization Setup -ftmethod=0 -## S(q) qmin=0.010000 qmax=26.000000 qgrid=0.000000 -## G(r) rmin=0.010000 rmax=60.000000 rgrid=0.030000 -## SqOptimization sqoptfunction=1 -optqmin=15.0000 optqmax=40.0000 optqgrid=0.000000 -optrmin=0.000000 optrmax=2.20000 optrgrid=0.0200000 -maxiter=20 relstep=0.000000 weighttype=0 weightfunc=0 -fitbkgmult_isa=0 fitsampmut_isa=1 fitpolariz_isa=1 -fitoblique_isa=0 fitfluores_isa=1 -fitrulandw_isa=0 fitenergya_isa=1 fitenergyb_isa=1 -fitsimurulandw_isa=1 fitDetEdepfluores_isa=0 fitDetEdepquadra_isa=0 -fitDetEdepspline_isa=0 fitDetTCoefElastic_isa=0 fitDetTCoefFluores_isa=0 -fitDetTcoefquadra_isa=0 fitDetTcoefspline_isa=0 - -##### Save&Plot Settings -datatype=GrData iqcorrtype=BkgSub iqsimutype=SimuIq -sqcorrtype=Compton sqtofqtype=FqData -gropttype=OptFq miscdatatype=AtomASF -##### start data -#F tio2r_300k_1-6_srXp_qspace.gr -#D Tue May 19 20:13:15 2015 -#C -#S 1 G(r) -#D -#L r(A) G(r) d_r d_Gr - 3.000000e-002 -1.708577e-001 -2.261947e-003 7.534023e-001 - 6.000000e-002 -3.474954e-001 -4.523893e-003 1.146748e+000 - 9.000000e-002 -5.413945e-001 -6.785840e-003 1.013071e+000 - 1.200000e-001 -7.685137e-001 -9.047787e-003 5.227350e-001 - 1.500000e-001 -1.039247e+000 -1.130973e-002 5.732173e-001 - 1.800000e-001 -1.344566e+000 -1.357168e-002 9.907350e-001 - 2.100000e-001 -1.647653e+000 -1.583363e-002 1.029914e+000 - 2.400000e-001 -1.888955e+000 -1.809557e-002 7.239948e-001 - 2.700000e-001 -2.005841e+000 -2.035752e-002 6.167028e-001 - 3.000000e-001 -1.959464e+000 -2.261947e-002 9.039862e-001 - 3.300000e-001 -1.755943e+000 -2.488141e-002 9.938148e-001 - 3.600000e-001 -1.450196e+000 -2.714336e-002 7.931696e-001 - 3.900000e-001 -1.128481e+000 -2.940531e-002 6.718313e-001 - 4.200000e-001 -8.762168e-001 -3.166725e-002 8.662149e-001 - 4.500000e-001 -7.454579e-001 -3.392920e-002 9.627377e-001 - 4.800000e-001 -7.370581e-001 -3.619115e-002 8.208988e-001 - 5.100000e-001 -8.056276e-001 -3.845309e-002 7.088672e-001 - 5.400000e-001 -8.842022e-001 -4.071504e-002 8.482207e-001 - 5.700000e-001 -9.160064e-001 -4.297699e-002 9.402611e-001 - 6.000000e-001 -8.777372e-001 -4.523893e-002 8.341068e-001 - 6.300000e-001 -7.839101e-001 -4.750088e-002 7.336765e-001 - 6.600000e-001 -6.721391e-001 -4.976283e-002 8.386860e-001 - 6.900000e-001 -5.791279e-001 -5.202477e-002 9.239874e-001 - 7.200000e-001 -5.213257e-001 -5.428672e-002 8.412944e-001 - 7.500000e-001 -4.905457e-001 -5.654867e-002 7.511117e-001 - 7.800000e-001 -4.656166e-001 -5.881061e-002 8.331599e-001 - 8.100000e-001 -4.316671e-001 -6.107256e-002 9.118541e-001 - 8.400000e-001 -3.943252e-001 -6.333451e-002 8.456208e-001 - 8.700000e-001 -3.793887e-001 -6.559645e-002 7.639262e-001 - 9.000000e-001 -4.174743e-001 -6.785840e-002 8.296223e-001 - 9.300000e-001 -5.225853e-001 -7.012035e-002 9.023595e-001 - 9.600000e-001 -6.778871e-001 -7.238229e-002 8.482949e-001 - 9.900000e-001 -8.385310e-001 -7.464424e-002 7.737620e-001 - 1.020000e+000 -9.518212e-001 -7.690619e-002 8.274823e-001 - 1.050000e+000 -9.846965e-001 -7.916813e-002 8.950795e-001 - 1.080000e+000 -9.433511e-001 -8.143008e-002 8.502439e-001 - 1.110000e+000 -8.730983e-001 -8.369203e-002 7.813916e-001 - 1.140000e+000 -8.368661e-001 -8.595397e-002 8.256884e-001 - 1.170000e+000 -8.825558e-001 -8.821592e-002 8.889079e-001 - 1.200000e+000 -1.016319e+000 -9.047787e-002 8.516216e-001 - 1.230000e+000 -1.196561e+000 -9.273981e-002 7.877617e-001 - 1.260000e+000 -1.352975e+000 -9.500176e-002 8.245170e-001 - 1.290000e+000 -1.421583e+000 -9.726371e-002 8.837774e-001 - 1.320000e+000 -1.377766e+000 -9.952565e-002 8.525866e-001 - 1.350000e+000 -1.249717e+000 -1.017876e-001 7.930361e-001 - 1.380000e+000 -1.104671e+000 -1.040495e-001 8.236585e-001 - 1.410000e+000 -1.014635e+000 -1.063115e-001 8.793948e-001 - 1.440000e+000 -1.019431e+000 -1.085734e-001 8.532452e-001 - 1.470000e+000 -1.106649e+000 -1.108354e-001 7.974835e-001 - 1.500000e+000 -1.219299e+000 -1.130973e-001 8.230950e-001 - 1.530000e+000 -1.287087e+000 -1.153593e-001 8.757458e-001 - 1.560000e+000 -1.264239e+000 -1.176212e-001 8.538365e-001 - 1.590000e+000 -1.152745e+000 -1.198832e-001 8.013205e-001 - 1.620000e+000 -9.973736e-001 -1.221451e-001 8.226021e-001 - 1.650000e+000 -8.541028e-001 -1.244071e-001 8.724450e-001 - 1.680000e+000 -7.487277e-001 -1.266690e-001 8.541585e-001 - 1.710000e+000 -6.491619e-001 -1.289310e-001 8.045059e-001 - 1.740000e+000 -4.692724e-001 -1.311929e-001 8.220752e-001 - 1.770000e+000 -1.064108e-001 -1.334549e-001 8.694881e-001 - 1.800000e+000 5.030918e-001 -1.357168e-001 8.545867e-001 - 1.830000e+000 1.337073e+000 -1.379787e-001 8.077585e-001 - 1.860000e+000 2.273875e+000 -1.402407e-001 8.220728e-001 - 1.890000e+000 3.121940e+000 -1.425026e-001 8.669320e-001 - 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3.303000e+001 5.363762e-001 -2.490403e+000 8.400068e-001 - 3.306000e+001 5.482368e-001 -2.492665e+000 8.400739e-001 - 3.309000e+001 5.456692e-001 -2.494927e+000 8.369105e-001 - 3.312000e+001 5.248496e-001 -2.497189e+000 8.367799e-001 - 3.315000e+001 4.807229e-001 -2.499451e+000 8.399409e-001 - 3.318000e+001 4.093606e-001 -2.501713e+000 8.401349e-001 - 3.321000e+001 3.108263e-001 -2.503975e+000 8.369827e-001 - 3.324000e+001 1.909003e-001 -2.506237e+000 8.367250e-001 - 3.327000e+001 6.043397e-002 -2.508499e+000 8.398662e-001 - 3.330000e+001 -6.768802e-002 -2.510761e+000 8.401826e-001 - 3.333000e+001 -1.826551e-001 -2.513023e+000 8.370572e-001 - 3.336000e+001 -2.788625e-001 -2.515285e+000 8.366839e-001 - 3.339000e+001 -3.564033e-001 -2.517547e+000 8.397961e-001 - 3.342000e+001 -4.186158e-001 -2.519809e+000 8.402200e-001 - 3.345000e+001 -4.680185e-001 -2.522071e+000 8.371218e-001 - 3.348000e+001 -5.029779e-001 -2.524332e+000 8.366449e-001 - 3.351000e+001 -5.172043e-001 -2.526594e+000 8.397347e-001 - 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-This example shows how to extract an isolated peak from a simple crystalline -PDF with accurate experimentally-determined uncertainties using a crystalline -baseline estimated from the data. This is the simplest use case -for diffpy.srmise, and covers initializing diffpy.srmise, defining extraction -parameters, running peak extraction, and saving the results. - -This script is equivalent to running -srmise data/Ag_nyquist_qmax30.gr --range 2. 3.5 \ - --baseline "Polynomial(degree=1)" --save output/extract_single_peak.srmise \ - --pwa output/extract_single_peak.pwa --plot -at the command line. -""" - -import matplotlib.pyplot as plt - -from diffpy.srmise.applications.plot import makeplot -from diffpy.srmise.baselines.polynomial import Polynomial -from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction - - -def run(plot=True): - - # Initialize peak extraction - # Create peak extraction object - ppe = PDFPeakExtraction() - - # Load the PDF from a file - ppe.loadpdf("data/Ag_nyquist_qmax30.gr") - - # Set up extraction parameters. - # For convenience, we add all parameters to a dictionary before passing them - # to the extraction object. - # - # The "rng" (range) parameter defines the region over which peaks will be - # extracted and fit. For the well isolated nearest-neighbor silver peak, - # which occurs near 2.9 angstroms, it is sufficient to perform extraction - # between 2 and 3.5 angstroms. - # - # The "baseline" parameter lets us define the PDF baseline, which is - # linear for a crystal. If a linear baseline is specified without - # numerical parameters diffpy.srmise attempts to estimate them from the - # data, and this is usually sufficient when peaks do not overlap much. - kwds = {} - kwds["rng"] = [2.0, 3.5] - kwds["baseline"] = Polynomial(degree=1) - - # Apply peak extraction parameters. - ppe.setvars(**kwds) - - # Perform peak extraction - ppe.extract() - - # Save output - # The write() method saves a file which preserves all aspects of peak - # extraction and its results, by convention using the .srmise extension, - # and which can later be read by diffpy.srmise. - # - # The writepwa() method saves a file intended as a human-readable summary. - # In particular, it reports the position, width (as full-width at - # half-maximum), and area of extracted peaks. The reported values - # are for Gaussians in the radial distribution function (RDF) corresponding - # to this PDF. - ppe.write("output/extract_single_peak.srmise") - ppe.writepwa("output/extract_single_peak.pwa") - - # Plot results. - # Display plot of extracted peak. It is also possible to plot an existing - # .srmise file from the command line using - # srmise output/Ag_singlepeak.srmise --no-extract --plot - # For additional plotting options, run "srmiseplot --help". - if plot: - makeplot(ppe) - plt.show() - - -if __name__ == "__main__": - run() diff --git a/doc/examples/fit_initial.py b/doc/examples/fit_initial.py deleted file mode 100644 index fa9961c..0000000 --- a/doc/examples/fit_initial.py +++ /dev/null @@ -1,109 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""Example of peak fitting C60 PDF (unnormalized) with unreliable uncertainties. - -Peak fitting in SrMise means fitting a model of initial peaks, which may be -specified manually or estimated with a clustering-based convenience function, -just as with specifying initial peaks for peak extraction. Unlike peak -extraction, it does not attempt to add or remove peaks, apply termination -ripples, or otherwise do anything beyond chi-square fitting using the specified -grid.""" - -import matplotlib.pyplot as plt - -from diffpy.srmise.applications.plot import makeplot -from diffpy.srmise.baselines.fromsequence import FromSequence -from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction -from diffpy.srmise.peaks.base import Peaks -from diffpy.srmise.peaks.terminationripples import TerminationRipples - - -def run(plot=True): - - # Initialize peak extraction - ppe = PDFPeakExtraction() - ppe.loadpdf("data/C60_fine_qmax21.gr") - - # Set up interpolated baseline. - # The FromSequence baseline creates an interpolated baseline from provided - # r and G(r) values, either two lists or a file containing (r, G(r)) pairs. - # The baseline has no parameters. This particular baseline was estimated - # by fitting interparticle correlations of an FCC lattice of hollow - # spheres to the PDF. - blf = FromSequence("data/C60baseline.dat") - bl = blf.actualize([]) - - # Set up fitting parameters - # A summary of how parameters impact fitting is given below. - # "rng" - Same as peak extraction - # "baseline" - Same as peak extraction - # "qmax" and "nyquist" - If qmax > 0 and Nyquist is true, fitting is - # performed on a Nyquist-sampled grid. The data are - # never supersampled first. - # "dg" - Since the model to fit is prespecified, the uncertainty does not - # impact model complexity. Impact on refined parameter values and - # estimated uncertainties as per standard chi-square fitting. - # "pf" - The peak function used when estimating peak parameters given an - # approximate position. Unike peak extraction, peak fitting never - # alters the peak function used by initial peaks. - # "cres" - Estimation of peak parameters given an approximate position uses - # clustering for peak finding. No other effect on peak fitting. - # "supersample" - No effect. - kwds = {} - kwds["rng"] = [1.0, 7.25] - kwds["baseline"] = bl - kwds["cres"] = 0.05 - kwds["dg"] = 5000 # ad hoc, but gives each point equal weight in fit. - ppe.setvars(**kwds) - - # Set up termination ripples - # Peak fitting never changes the peak function, so termination ripples - # are not applied automatically as they are in peak extraction. - # Termination ripples require setting the underlying peak function and qmax. - # In this case they ared added to the default GaussianOverR peak function. - # TerminationRipples use the estimation methods of the base peak function. - pf = TerminationRipples(ppe.pf[0], ppe.qmax) - ppe.setvars(pf=[pf]) - - # Specify some initial peaks using approximate positions. These use the - # peak function passed to PDFPeakExtraction instance. - rough_guess = [1.4, 2.4, 2.8, 3.6, 4.1, 4.5, 4.8, 5.2, 5.4, 5.7, 6.1] - for g in rough_guess: - ppe.estimate_peak(g) - - # Specify some peaks explicitly. These may be constructed from any peak - # function, or combination of peak functions. - explicit_guess = [[6.7, 0.3, 100000], [7.0, 0.15, 50000]] - explicit_peaks = Peaks([pf.actualize(eg, in_format="pwa") for eg in explicit_guess]) - ppe.add_peaks(explicit_peaks) - - # Plot initial peaks - if plot: - makeplot(ppe) - plt.title("Initial Peaks") - - # Perform fit. - ppe.fit() - - # Save results - ppe.write("output/fit_initial.srmise") - ppe.writepwa("output/fit_initial.pwa") - - if plot: - plt.figure() - makeplot(ppe) - plt.show() - - -if __name__ == "__main__": - run() diff --git a/doc/examples/images/extract_single_peak1.png b/doc/examples/images/extract_single_peak1.png deleted file mode 100644 index a299a32..0000000 Binary files a/doc/examples/images/extract_single_peak1.png and /dev/null differ diff --git a/doc/examples/images/extract_single_peak2.png b/doc/examples/images/extract_single_peak2.png deleted file mode 100644 index dfc4c8e..0000000 Binary files a/doc/examples/images/extract_single_peak2.png and /dev/null differ diff --git a/doc/examples/images/extract_single_peak3.png b/doc/examples/images/extract_single_peak3.png deleted file mode 100644 index fe77e53..0000000 Binary files a/doc/examples/images/extract_single_peak3.png and /dev/null differ diff --git a/doc/examples/images/fit_initial1.png b/doc/examples/images/fit_initial1.png deleted file mode 100644 index f460758..0000000 Binary files a/doc/examples/images/fit_initial1.png and /dev/null differ diff --git a/doc/examples/images/fit_initial2.png b/doc/examples/images/fit_initial2.png deleted file mode 100644 index f21eca0..0000000 Binary files a/doc/examples/images/fit_initial2.png and /dev/null differ diff --git a/doc/examples/images/parameter_summary1.png b/doc/examples/images/parameter_summary1.png deleted file mode 100644 index 5b35700..0000000 Binary files a/doc/examples/images/parameter_summary1.png and /dev/null differ diff --git a/doc/examples/images/parameter_summary2.png b/doc/examples/images/parameter_summary2.png deleted file mode 100644 index 042dae0..0000000 Binary files a/doc/examples/images/parameter_summary2.png and /dev/null differ diff --git a/doc/examples/images/parameter_summary3.png b/doc/examples/images/parameter_summary3.png deleted file mode 100644 index 9de1730..0000000 Binary files a/doc/examples/images/parameter_summary3.png and /dev/null differ diff --git a/doc/examples/images/parameter_summary4.png b/doc/examples/images/parameter_summary4.png deleted file mode 100644 index 4cf1f89..0000000 Binary files a/doc/examples/images/parameter_summary4.png and /dev/null differ diff --git a/doc/examples/images/query_results1.png b/doc/examples/images/query_results1.png deleted file mode 100644 index 07a0b3b..0000000 Binary files a/doc/examples/images/query_results1.png and /dev/null differ diff --git a/doc/examples/images/query_results2.png b/doc/examples/images/query_results2.png deleted file mode 100644 index 3fce521..0000000 Binary files a/doc/examples/images/query_results2.png and /dev/null differ diff --git a/doc/examples/images/query_results3.png b/doc/examples/images/query_results3.png deleted file mode 100644 index 1ece41d..0000000 Binary files a/doc/examples/images/query_results3.png and /dev/null differ diff --git a/doc/examples/multimodel_known_dG1.py b/doc/examples/multimodel_known_dG1.py deleted file mode 100644 index f1fe508..0000000 --- a/doc/examples/multimodel_known_dG1.py +++ /dev/null @@ -1,91 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""Extract multiple models from crystalline PDF with known uncertainties for -use in later AIC-driven multimodeling analysis. - -The multimodel approach generates many models of varying complexity by assuming -a range of experimental uncertainties are physically plausible. This example -shows how to generate multiple models from a crystalline silver PDF with -experimentally determined uncertainties. The Akaike Information Criterion (AIC) -will later be used to see which models are relatively more likely to describe -the experimental data. For complex PDFs, especially, there are many sets of -peaks which are physically distinct yet appear to fit the experimental data -similarly well. Multimodeling can help determine which models are worth -investigating first. - -NOTE: The multimodeling API used here is expected to change drastically in a -future version of diffpy.srmise. - -For more information on the multimodeling approach taken here see -[1] Granlund, et al. (2015) Acta Crystallographica A, 71(4), 392-409. - doi:10.1107/S2053273315005276 -The standard reference of AIC-based multimodel selection is -[2] Burnham and Anderson. (2002). Model Selection and Multimodel Inference. - New York, NY: Springer. doi:10.1007/b97636 -""" - -import numpy as np - -import diffpy.srmise.srmiselog as sml -from diffpy.srmise.multimodelselection import MultimodelSelection -from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction - - -def run(plot=True): - - # Suppress mundane output - # When running scripts, especially involving multiple trials, it can be - # useful to suppress many of the diffpy.srmise messages. Valid levels - # include "debug", "info" (the default), "warning", "error", and - # "critical." See diffpy.srmise.srmiselog for more information. - sml.setlevel("warning") - - # Initialize peak extraction from saved trial - ppe = PDFPeakExtraction() - ppe.read("output/query_results.srmise") - ppe.clearcalc() - - # Set up extraction parameters - # All parameters loaded from .srmise file. - # Setting new values will override the previous values. - kwds = {} - kwds["rng"] = [10.9, 15] # Region of PDF with some overlap. - ppe.setvars(**kwds) - - # Create multimodel selection object. - # The MultimodelSelection class keeps track of the results of peak - # extraction as the assumed uncertainty dg is varied. - ms = MultimodelSelection() - ms.setppe(ppe) - - # Define range of dg values - # For the purpose of illustration use 15 evenly-spaced values of dg where - # 50% < dg < 120% of mean experimental dG in extraction range. - dg_mean = np.mean(ppe.dy[ppe.getrangeslice()]) - dgs = np.linspace(0.5 * dg_mean, 1.2 * dg_mean, 15) - - # Perform peak extraction for each of the assumed uncertainties. - ms.run(dgs) - - # Save results - # The file known_dG_models.dat saves the models generated above. The file - # known_dG_aics.dat saves the value of the AIC of each model when evaluated - # on a Nyquist-sampled grid using each of the dg values used to generate - # the models in the first place. - dr = np.pi / ppe.qmax - ms.save("output/known_dG_models.dat") - ms.makeaics(dgs, dr, filename="output/known_dG_aics.dat") - - -if __name__ == "__main__": - run() diff --git a/doc/examples/multimodel_known_dG2.py b/doc/examples/multimodel_known_dG2.py deleted file mode 100644 index 59add2e..0000000 --- a/doc/examples/multimodel_known_dG2.py +++ /dev/null @@ -1,189 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""AIC-driven multimodel analysis of crystalline PDF with known uncertainties. - -The multimodel approach generates many models of varying complexity by assuming -a range of experimental uncertainties are physically plausible. This example -shows how to analyze multiple models obtained (in the previous script) from a -crystalline silver PDF with experimentally determined uncertainties. This -involves calculating the Akaike probabilities, which are a measure of the -likelihood that a given model is the best model (in the sense of -Kullback-Leibler divergence) relative to all the other ones in the same -comparison. - -NOTE: The multimodeling API used here is expected to change drastically in a -future version of diffpy.srmise. - -For more information on the multimodeling approach taken here see -[1] Granlund, et al. (2015) Acta Crystallographica A, 71(4), 392-409. - doi:10.1107/S2053273315005276 -The standard reference of AIC-based multimodel selection is -[2] Burnham and Anderson. (2002). Model Selection and Multimodel Inference. - New York, NY: Springer. doi:10.1007/b97636 -""" -import matplotlib.pyplot as plt -import numpy as np - -import diffpy.srmise.srmiselog as sml -from diffpy.srmise.applications.plot import makeplot -from diffpy.srmise.multimodelselection import MultimodelSelection - -# distances from ideal Ag (refined to PDF) -dcif = np.array( - [ - 11.2394, - 11.608, - 11.9652, - 12.3121, - 12.6495, - 12.9781, - 13.2986, - 13.6116, - 13.9175, - 14.2168, - 14.51, - 14.7973, - ] -) - - -def run(plot=True): - - # Suppress mundane output - sml.setlevel("warning") - - # Create multimodeling object and load diffpy.srmise results from file. - ms = MultimodelSelection() - ms.load("output/known_dG_models.dat") - ms.loadaics("output/known_dG_aics.dat") - - # Use Nyquist sampling - # Standard AIC analysis assumes the data have independent uncertainties. - # Nyquist sampling minimizes correlations in the PDF, which is the closest - # approximation to independence possible for the PDF. - dr = np.pi / ms.ppe.qmax - (r, y, dr2, dy) = ms.ppe.resampledata(dr) - - # Classify models - # All models are placed into classes. Models in the same class - # should be essentially identical (same peak parameters, etc.) - # up to a small tolerance determined by comparing individual peaks. The - # best model in each class essentially stands in for all the other models - # in a class in the rest of the analysis. A tolerance of 0 indicates the - # models must be exactly identical. Increasing the tolerance allows - # increasingly different models to be classified as "identical." This step - # reduces a major source of model redundancy, which otherwise weakens - # AIC-based analysis. As a rule of thumb, AIC-based analysis is robust - # to redundant poor models (since they contribute very little to the Akaike - # probabilities in any case), but redundant good models can significantly - # alter how models are ranked. See Granlund (2015) for details. - tolerance = 0.2 - ms.classify(r, tolerance) - - # Summarize various facts about the analysis. - num_models = len(ms.results) - num_classes = len(ms.classes) - print("------- Multimodeling Summary --------") - print("Models: %i" % num_models) - print("Classes: %i (tol=%s)" % (num_classes, tolerance)) - print("Range of dgs: %f-%f" % (ms.dgs[0], ms.dgs[-1])) - print("Nyquist-sampled data points: %i" % len(r)) - - # Get dG usable as key in analysis. - # The Akaike probabilities were calculated for many assumed values of the - # experimental uncertainty dG, and each of these assumed dG is used as a - # key when obtaining the corresponding results. Numerical precision can - # make recalculating the exact value difficult, so the dg_key method returns - # the key closest to its argument. - dG = ms.dg_key(np.mean(ms.ppe.dy)) - - # Find "best" models. - # In short, models with greatest Akaike probability. Akaike probabilities - # can only be validly compared if they were calculated for identical data, - # namely identical PDF values *and* uncertainties, and are only reliable - # with respect to the actual experiment when using a Nyquist-sampled PDF - # with experimentally determined uncertainties. - # - # The present PDF satisfies these conditions, so the rankings below reflect - # an AIC-based estimate of which of the tested models the data best support. - print("\n--------- Model Rankings for dG = %f ---------" % dG) - print("Rank Model Class Free AIC Prob File") - for i in range(len(ms.classes)): - - # Generate information about best model in ith best class. - # The get(dG, *args, **kwds) method returns a tuple of values - # corresponding to string arguments for the best model in best class at - # given dG. When the corder keyword is given it returns the model from - # the corderth best class (where 0 is best, 1 is next best, etc.) - # "model" -> index of model - # "class" -> index of class - # "nfree" -> number of free parameters in corresponding model - # "aic" -> The AIC for this model given uncertainty dG - # "prob" -> The AIC probability given uncertainty dG - # These all have dedicated getter functions. For example, the model - # index can also be obtained using get_model(dG, corder=i) - (model, cls, nfree, aic, prob) = ms.get(dG, "model", "class", "nfree", "aic", "prob", corder=i) - - filename_base = "output/known_dG_m" + str(model) - - # print(info for this model - print( - "%4i %5i %5i %4i %10.4e %6.3f %s" % (i + 1, model, cls, nfree, aic, prob, filename_base + ".pwa") - ) - - # A message added as a comment to saved .pwa file. - msg = [ - "Multimodeling Summary", - "---------------------", - "Evaluated at dG: %s" % dG, - "Model: %i (of %i)" % (model, num_models), - "Class: %i (of %i, tol=%s)" % (cls, num_classes, tolerance), - "Akaike probability: %g" % prob, - "Rank: %i" % (i + 1), - ] - msg = "\n".join(msg) - - # Make this the active model - ms.setcurrent(model) - - # Save .pwa - ms.ppe.writepwa(filename_base + ".pwa", msg) - - # Plot this model - if plot: - plt.figure() - makeplot(ms.ppe, dcif) - plt.title("Model %i/Class %i (Rank %i, AIC prob=%f)" % (model, cls, i + 1, prob)) - # Uncomment line below to save figures. - # plt.savefig(filename_base + ".png", format="png") - - # 3D plot of Akaike probabilities - # This plot shows the Akaike probabilities of all classes as a function - # of assumed uncertainty dG. This gives a rough sense of how the models - # selected by an AIC-based analysis would vary if the experimental - # uncertainties contributing to the observed G(r) were different. The - # Akaike probabilities calculated for the actual experimental uncertainty - # are highlighted. - if plot: - plt.figure() - ms.plot3dclassprobs(probfilter=[0.0, 1.0], highlight=[dG]) - plt.tight_layout() - # Uncomment line below to save figure. - # plt.savefig("output/known_dG_probs.png", format="png", bbox_inches="tight") - - if plot: - plt.show() - - -if __name__ == "__main__": - run() diff --git a/doc/examples/multimodel_unknown_dG1.py b/doc/examples/multimodel_unknown_dG1.py deleted file mode 100644 index 4570f78..0000000 --- a/doc/examples/multimodel_unknown_dG1.py +++ /dev/null @@ -1,95 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""Extract multiple models from nanoparticle PDF with unknown uncertainties for -use in later AIC-driven multimodeling analysis. - -The multimodel approach generates many models of varying complexity by assuming -a range of experimental uncertainties are physically plausible. This example -shows how to generate multiple models from a C60 nanoparticle PDF with -unreliable uncertainties. The Akaike Information Criterion (AIC) will later be -used to see which models are relatively more likely to describe the experimental -data. For complex PDFs, especially, there are many sets of peaks which are -physically distinct yet appear to fit the experimental data similarly well. -Multimodeling can help determine which models are worth investigating first. - -NOTE: The multimodeling API used here is expected to change drastically in a -future version of diffpy.srmise. - -For more information on the multimodeling approach taken here see -[1] Granlund, et al. (2015) Acta Crystallographica A, 71(4), 392-409. - doi:10.1107/S2053273315005276 -The standard reference of AIC-based multimodel selection is -[2] Burnham and Anderson. (2002). Model Selection and Multimodel Inference. - New York, NY: Springer. doi:10.1007/b97636 -""" - -import numpy as np - -import diffpy.srmise.srmiselog as sml -from diffpy.srmise.baselines.fromsequence import FromSequence -from diffpy.srmise.multimodelselection import MultimodelSelection -from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction - - -def run(plot=True): - - # Suppress mundane output - # When running scripts, especially involving multiple trials, it can be - # useful to suppress many of the diffpy.srmise messages. Valid levels - # include "debug", "info" (the default), "warning", "error", and - # "critical." See diffpy.srmise.srmiselog for more information. - sml.setlevel("warning") - - # Initialize peak extraction - ppe = PDFPeakExtraction() - ppe.loadpdf("data/C60_fine_qmax21.gr") - - # Set up extraction parameters - # The FromSequence baseline interpolates (r, G(r)) values read from a - # specified file. It has parameters. This particular baseline was - # calculated by approximating the C60 sample as a face-centered cubic - # lattice of hollow spheres. - blfunc = FromSequence("data/C60baseline.dat") - kwds = {} - kwds["rng"] = [1.0, 7.25] - kwds["baseline"] = blfunc.actualize([]) - kwds["cres"] = 0.05 - ppe.setvars(**kwds) - - # Create multimodel selection object. - # The MultimodelSelection class keeps track of the results of peak - # extraction as the assumed uncertainty dg is varied. - ms = MultimodelSelection() - ms.setppe(ppe) - - # Define range of dg values - # For the purpose of illustration use 20 evenly-spaced values of dg where - # 1% < dg < 10% of max gr value between r=1 and 7.25. - grmax = np.max(ppe.y[ppe.getrangeslice()]) - dgs = np.linspace(0.01 * grmax, 0.10 * grmax, 20) - - # Perform peak extraction for each of the assumed uncertainties. - ms.run(dgs) - - # Save results - # The file C60_models.dat saves the models generated above. The file - # C60_aics.dat saves the value of the AIC of each model when evaluated - # on a Nyquist-sampled grid using each of the dg values used to generate - # the models in the first place. - dr = np.pi / ppe.qmax - ms.save("output/unknown_dG_models.dat") - ms.makeaics(dgs, dr, filename="output/unknown_dG_aics.dat") - - -if __name__ == "__main__": - run() diff --git a/doc/examples/multimodel_unknown_dG2.py b/doc/examples/multimodel_unknown_dG2.py deleted file mode 100644 index c4bbef4..0000000 --- a/doc/examples/multimodel_unknown_dG2.py +++ /dev/null @@ -1,212 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""AIC-driven multimodel analysis of nanoparticle PDF with unknown -uncertainties. - -The multimodel approach generates many models of varying complexity by assuming -a range of experimental uncertainties are physically plausible. This example -shows how to analyze multiple models obtained from a C60 nanoparticle PDF with -unreliable uncertainties. The Akaike Information Criterion (AIC) can be used to -see which models are relatively more likely to describe the experimental data. -For complex PDFs, especially, there are many sets of peaks which are physically -distinct yet appear to fit the experimental data similarly well. Here we -calculate the Akaike probabilities, which are a measure of the likelihood that a -given model is the best model (in the sense of Kullback-Leibler information -divergence) relative to all the other ones in the same comparison. This -analysis reflects ignorance of the experimental uncertainties by evaluating -the Akaike probabilities for a range of assumed uncertainties, returning models -which are selected as best at least once. This is a weaker analysis than -possible when the uncertainties are known. - -NOTE: The multimodeling API used here is expected to change drastically in a -future version of diffpy.srmise. - -For more information on the multimodeling approach taken here see -[1] Granlund, et al. (2015) Acta Crystallographica A, 71(4), 392-409. - doi:10.1107/S2053273315005276 -The standard reference of AIC-based multimodel selection is -[2] Burnham and Anderson. (2002). Model Selection and Multimodel Inference. - New York, NY: Springer. doi:10.1007/b97636 -""" -import matplotlib.pyplot as plt -import numpy as np - -import diffpy.srmise.srmiselog as sml -from diffpy.srmise.applications.plot import makeplot -from diffpy.srmise.multimodelselection import MultimodelSelection - -# distances from ideal (unrefined) C60 -dcif = np.array( - [ - 1.44, - 2.329968944, - 2.494153163, - 2.88, - 3.595985339, - 3.704477734, - 4.132591264, - 4.520339129, - 4.659937888, - 4.877358006, - 5.209968944, - 5.405310018, - 5.522583786, - 5.818426502, - 6.099937888, - 6.164518388, - 6.529777754, - 6.686673127, - 6.745638756, - 6.989906831, - 7.136693738, - ] -) - - -def run(plot=True): - - # Suppress mundane output - sml.setlevel("warning") - - # Create multimodeling object and load diffpy.srmise results from file. - ms = MultimodelSelection() - ms.load("output/unknown_dG_models.dat") - ms.loadaics("output/unknown_dG_aics.dat") - - # Use Nyquist sampling - # Standard AIC analysis assumes the data have independent uncertainties. - # Nyquist sampling minimizes correlations in the PDF, which is the closest - # approximation to independence possible for the PDF. - dr = np.pi / ms.ppe.qmax - (r, y, dr2, dy) = ms.ppe.resampledata(dr) - - # Classify models - # All models are placed into classes. Models in the same class - # should be essentially identical (same peak parameters, etc.) - # up to a small tolerance determined by comparing individual peaks. The - # best model in each class essentially stands in for all the other models - # in a class in the rest of the analysis. A tolerance of 0 indicates the - # models must be exactly identical. Increasing the tolerance allows - # increasingly different models to be classified as "identical." This step - # reduces a major source of model redundancy, which otherwise weakens - # AIC-based analysis. As a rule of thumb, AIC-based analysis is robust - # to redundant poor models (since they contribute very little to the Akaike - # probabilities in any case), but redundant good models can significantly - # alter how models are ranked. See Granlund (2015) for details. - tolerance = 0.2 - ms.classify(r, tolerance) - - # Summarize various facts about the analysis. - num_models = len(ms.results) - num_classes = len(ms.classes) - print("------- Multimodeling Summary --------") - print("Models: %i" % num_models) - print("Classes: %i (tol=%s)" % (num_classes, tolerance)) - print("Range of dgs: %f-%f" % (ms.dgs[0], ms.dgs[-1])) - print("Nyquist-sampled data points: %i" % len(r)) - - # Find "best" models. - # In short, models with greatest Akaike probability. Akaike probabilities - # can only be validly compared if they were calculated for identical data, - # namely identical PDF values *and* uncertainties, and are only reliable - # with respect to the actual experiment when using a Nyquist-sampled PDF - # with experimentally determined uncertainties. - # - # In the present case the PDF uncertainties are not reliable, and so the - # analysis cannot be performed by specifying the experimental uncertainty - # dG. Instead, perform a weaker analysis, calculating the Akaike - # probabilities for a range of assumed dG, and identifying classes which - # have greatest probability at least once. The classes identified in this - # way have no particular information-theoretic relationship, but if the - # actual experimental uncertainty is in the interval tested, the best - # class at the experimental uncertainty is among them. - - # Get classes which are best for one or more dG, and the specific dG in that - # interval at which they attain greatest Akaike probability. - best_classes = np.unique([ms.get_class(dG) for dG in ms.dgs]) - best_dGs = [] - for cls in best_classes: - cls_probs = [ms.get_prob(dG) if ms.get_class(dG) == cls else 0 for dG in ms.dgs] - dG = ms.dgs[np.argmax(cls_probs)] - best_dGs.append(dG) - - print("\n--------- Best models for at least one dG ---------" % dG) - print(" Best dG Model Class Free AIC Prob File") - for dG in best_dGs: - - # Generate information about best model. - # The get(dG, *args, **kwds) method returns a tuple of values - # corresponding to string arguments for the best model in best class at - # given dG. When the corder keyword is given it returns the model from - # the corderth best class (where 0 is best, 1 is next best, etc.) - # "model" -> index of model - # "class" -> index of class - # "nfree" -> number of free parameters in corresponding model - # "aic" -> The AIC for this model given uncertainty dG - # "prob" -> The AIC probability given uncertainty dG - # These all have dedicated getter functions. - (model, cls, nfree, aic, prob) = ms.get(dG, "model", "class", "nfree", "aic", "prob") - - filename_base = "output/unknown_dG_m" + str(model) - - # print(info for this model - print( - "%10.4e %5i %5i %4i %10.4e %6.3f %s" % (dG, model, cls, nfree, aic, prob, filename_base + ".pwa") - ) - - # A message added as a comment to saved .pwa file. - best_from = [dg for dg in ms.dgs if ms.get_class(dg) == cls] - msg = [ - "Multimodeling Summary", - "---------------------", - "Model: %i (of %i)" % (model, num_models), - "Class: %i (of %i, tol=%s)" % (cls, num_classes, tolerance), - "Best model from dG: %s-%s" % (best_from[0], best_from[-1]), - "Evaluated at dG: %s" % dG, - "Akaike probability: %g" % prob, - ] - msg = "\n".join(msg) - - # Make this the active model - ms.setcurrent(model) - - # Save .pwa - ms.ppe.writepwa(filename_base + ".pwa", msg) - - # Plot this model - if plot: - plt.figure() - makeplot(ms.ppe, dcif) - plt.title("Model %i/Class %i (Best dG=%f, AIC prob=%f)" % (model, cls, dG, prob)) - # Uncomment line below to save figures. - # plt.savefig(filename_base + ".png", format="png") - - # 3D plot of Akaike probabilities - # This plot shows the Akaike probabilities of all classes as a function - # of assumed uncertainty dG. This gives a rough sense of how the models - # selected by an AIC-based analysis would vary if the experimental - # uncertainties contributing to the observed G(r) were different. Models - # are highlighted at the various dG values found above. - if plot: - plt.figure() - ms.plot3dclassprobs(probfilter=[0.1, 1.0], highlight=best_dGs) - plt.tight_layout() - # Uncomment line below to save figure. - # plt.savefig("output/unknown_dG_probs.png", format="png", bbox_inches="tight") - - if plot: - plt.show() - - -if __name__ == "__main__": - run() diff --git a/doc/examples/output/extract_single_peak.pwa b/doc/examples/output/extract_single_peak.pwa deleted file mode 100644 index 9aa363b..0000000 --- a/doc/examples/output/extract_single_peak.pwa +++ /dev/null @@ -1,50 +0,0 @@ -Summary written: Wed Jul 1 09:49:43 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### User comments -# n/a -##### PDF Peak Extraction Summary -# The information below is not sufficient to replicate extraction. -## PDF metadata -filename=/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/Ag_nyquist_qmax30.gr -nyquist=True -qmax=30.0 -qmax_reportedbypdf=30.0 -qmax_fromdata=29.729728241905356 -scale=False -supersample=4.0 - -## Peak extraction metadata -Range=[2.0, 3.5] -cres=0.10472 -effective_dy=0.4137889 (mean) - -## Model Quality -# Quality reported by ModelEvaluator: 8.14250835003 -# Free parameters in extracted peaks: 3 -# Free parameters in baseline: 2 -# Length of data in final fit: 15 -ModelEvaluator=AIC - -## Baseline Functions -# Index Type -0 diffpy.srmise.baselines.polynomial - -## Baseline -# Parameters of baseline, followed by comment which -# gives the index of corresponding Baseline Function. -# a_1 a_0 --0.510709933517 0.00902995292416 # 0 - -## Peak Functions -# Index Type -0 diffpy.srmise.peaks.gaussianoverr -1 diffpy.srmise.peaks.terminationripples (base=0) - -## Extracted Peaks -# Parameters are given in the natural units of the data, -# where width is measured as full-width at half maximum. -# Each line is followed by a comment which gives the index -# of the corresponding Peak Function. -#L position fwhm area -2.90074809344 0.267213055365 9.84389058517 # 1 diff --git a/doc/examples/output/extract_single_peak.srmise b/doc/examples/output/extract_single_peak.srmise deleted file mode 100644 index 0a57729..0000000 --- a/doc/examples/output/extract_single_peak.srmise +++ /dev/null @@ -1,422 +0,0 @@ -History written: Wed Jul 1 09:49:43 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### PDF Peak Extraction -## BaselineFunctions -# BaselineFunction 0 -function='Polynomial' -module='diffpy.srmise.baselines.polynomial' -base=None -degree=1 - -## PeakFunctions -# PeakFunction 0 -function='GaussianOverR' -module='diffpy.srmise.peaks.gaussianoverr' -base=None -maxwidth=0.7 - -# PeakFunction 1 -function='TerminationRipples' -module='diffpy.srmise.peaks.terminationripples' -base=0 -supersample=5.0 -qmax=30.0 -extension=4.0 - -# BaselineObject -owner=0 -pars=[-0.60176135324525593, 0.0] -free=[True, True] -removable=False -static_owner=False - -## InitialPeaks -# SrMiseMetadata -pf=[0] -cres=0.10472 -ModelEvaluator=AIC -Range=[2.0, 3.5] -# Metadata -filename='/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/Ag_nyquist_qmax30.gr' -nyquist=True -qmax=30.0 -qmax_reportedbypdf=30.0 -qmax_fromdata=29.729728241905356 -scale=False -supersample=4.0 - -##### start data -#L x y dx dy edy -0.10472 -0.848217 0 0.276527 0.276527 -0.20944 -0.438975 0 0.375888 0.375888 -0.314159 -0.0724599 0 0.399338 0.399338 -0.418879 0.0701041 0 0.406243 0.406243 -0.523599 0.241004 0 0.40927 0.40927 -0.628319 -1.08142 0 0.410872 0.410872 -0.733038 -0.730527 0 0.411821 0.411821 -0.837758 -0.789248 0 0.412439 0.412439 -0.942478 -0.479976 0 0.412843 0.412843 -1.0472 -0.551525 0 0.413149 0.413149 -1.15192 -0.52763 0 0.413394 0.413394 -1.25664 -0.478534 0 0.41357 0.41357 -1.36136 -0.745365 0 0.41365 0.41365 -1.46608 -0.851118 0 0.414021 0.414021 -1.5708 -0.850263 0 0.413873 0.413873 -1.67552 -0.859146 0 0.413961 0.413961 -1.78024 -0.944151 0 0.414016 0.414016 -1.88496 -0.957457 0 0.414068 0.414068 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-0.217961 0 0.414468 0.414468 -32.5678 -0.359842 0 0.414469 0.414469 -32.6726 -0.400725 0 0.414469 0.414469 -32.7773 -0.388053 0 0.414472 0.414472 -32.882 -0.53186 0 0.414471 0.414471 -32.9867 -0.452224 0 0.414473 0.414473 -33.0914 -0.258411 0 0.414473 0.414473 -33.1962 -0.0783268 0 0.414472 0.414472 -33.3009 0.34702 0 0.414477 0.414477 -33.4056 0.813758 0 0.414477 0.414477 -33.5103 0.942157 0 0.414473 0.414473 -33.615 0.668602 0 0.414472 0.414472 -33.7198 0.416251 0 0.414469 0.414469 -33.8245 0.213257 0 0.414464 0.414464 -33.9292 0.128913 0 0.414463 0.414463 -34.0339 0.101085 0 0.414462 0.414462 -34.1386 0.126261 0 0.414463 0.414463 -34.2434 -0.088243 0 0.414466 0.414466 -34.3481 -0.505281 0 0.414463 0.414463 -34.4528 -0.865457 0 0.414461 0.414461 -34.5575 -0.931427 0 0.414465 0.414465 -34.6622 -0.677627 0 0.414469 0.414469 -34.767 -0.219618 0 0.414472 0.414472 -34.8717 0.262265 0 0.414475 0.414475 -34.9764 0.497295 0 0.414474 0.414474 -##### Results -extraction_type='extract' -### ModelCluster -peak_funcs=[0] -ModelEvaluator=AIC -slice=slice(None, 15, None) -# BaselineObject -owner=0 -pars=[-0.51070993351665106, 0.0090299529241620619] -free=[True, True] -removable=False -static_owner=False - -## ModelPeaks -# ModelPeak -owner=1 -pars=[2.9007480934434744, -0.78745534471557455, 9.8438905851705218] -free=[True, True, True] -removable=True -static_owner=False - -### start data -#L r y dy -2 -0.958664 0.414081 -2.10472 -1.05424 0.414187 -2.20944 -0.999558 0.414174 -2.31416 -1.15193 0.414206 -2.41888 -0.993455 0.414205 -2.5236 -1.07261 0.414254 -2.62832 -0.551527 0.414286 -2.73304 2.63601 0.414272 -2.83776 9.19232 0.414248 -2.94248 9.35892 0.414363 -3.0472 3.37487 0.414314 -3.15192 -0.484552 0.414298 -3.25664 -1.63658 0.414337 -3.36136 -1.90301 0.414368 -3.46608 -2.08411 0.414339 diff --git a/doc/examples/output/fit_initial.pwa b/doc/examples/output/fit_initial.pwa deleted file mode 100644 index 31b0b8d..0000000 --- a/doc/examples/output/fit_initial.pwa +++ /dev/null @@ -1,61 +0,0 @@ -Summary written: Wed Jul 1 09:49:48 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### User comments -# n/a -##### PDF Peak Extraction Summary -# The information below is not sufficient to replicate extraction. -## PDF metadata -filename=/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/C60_fine_qmax21.gr -nyquist=True -qmax=21.299999 -qmax_reportedbypdf=21.299999 -qmax_fromdata=20.755266780473114 -scale=False -supersample=4.0 - -## Peak extraction metadata -Range=[1.0, 7.25] -cres=0.05 -effective_dy=5000.0 (mean) - -## Model Quality -# Quality reported by ModelEvaluator: 92.6752408562 -# Free parameters in extracted peaks: 39 -# Free parameters in baseline: 0 -# Length of data in final fit: 43 -ModelEvaluator=AIC - -## Baseline Functions -# Index Type -0 diffpy.srmise.baselines.fromsequence - -## Baseline -# Parameters of baseline, followed by comment which -# gives the index of corresponding Baseline Function. -(no parameters) # 0 - -## Peak Functions -# Index Type -0 diffpy.srmise.peaks.gaussianoverr -1 diffpy.srmise.peaks.terminationripples (base=0) - -## Extracted Peaks -# Parameters are given in the natural units of the data, -# where width is measured as full-width at half maximum. -# Each line is followed by a comment which gives the index -# of the corresponding Peak Function. -#L position fwhm area -1.44052045545 0.126922793092 35515.0466525 # 1 -2.43843453254 0.191284037176 73907.954099 # 1 -2.84665187581 0.11855986532 22393.6834175 # 1 -3.61300300497 0.207753697835 74116.2415714 # 1 -4.11235449811 0.204425214722 57080.4376335 # 1 -4.54353747614 0.189099818179 77649.0745578 # 1 -4.82003327008 0.0890220621471 25334.5835294 # 1 -5.15599260556 0.214856321543 26922.3571293 # 1 -5.44889791859 0.249792684771 97884.5152113 # 1 -5.79393200168 0.217752816238 65017.8417157 # 1 -6.11557123515 0.2127375311 84602.184903 # 1 -6.65465778716 0.356092637998 139877.383295 # 1 -7.02738113149 0.203717659674 42013.8023086 # 1 diff --git a/doc/examples/output/fit_initial.srmise b/doc/examples/output/fit_initial.srmise deleted file mode 100644 index 9deeec6..0000000 --- a/doc/examples/output/fit_initial.srmise +++ /dev/null @@ -1,2291 +0,0 @@ -History written: Wed Jul 1 09:49:48 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### PDF Peak Extraction -## BaselineFunctions -# BaselineFunction 0 -function='FromSequence' -module='diffpy.srmise.baselines.fromsequence' -base=None -y=[-1475.0325650706627, -2950.0651301413254, -4425.0976952119881, -5900.1302602826509, -7375.1628253533127, -8850.1953904239745, -10325.227955494638, -11800.260520565302, -13275.293085635964, -14750.325650706625, -16225.358215777289, -17700.390780847953, -19175.423345918618, -20650.455910989276, -22125.488476059942, -23600.521041130603, -25075.553606201265, -26550.586171271931, -28025.459933459599, -29490.66450359999, -30922.864389112267, -32298.695523408274, -33596.022711102938, -34793.92402828217, -35872.675222770908, -36813.734114401064, -37599.724995279517, -38214.42303005611, -38643.368779986711, -38890.463187607907, -38978.523165803032, -38930.29758324947, -38767.462434741778, -38510.636440923663, -38179.39664801996, -37792.294027568765, -37366.869076153373, -36919.66741513431, -36465.762314723048, -36011.685031151355, -35557.60774757967, -35103.530464007978, -34649.453180436292, -34195.375896864593, -33741.298613292922, -33287.221329721207, -32833.144046149522, -32379.066762577819, -31924.989479006141, -31470.912195434459, -31016.83491186277, -30562.757628291063, -30108.680344719356, -29654.603061147711, -29200.525777575986, -28746.448494004322, -28292.371210432615, -27838.293926860926, -27384.216643289248, -26930.139359411234, -26474.542488478357, -26010.083575850655, -25528.358372275903, -25021.398910324362, -24481.667989050857, -23902.053658656267, -23275.863705149979, -22596.820135010832, -21859.053659849822, -21057.103538030915, -20189.157506289514, -19262.2608478449, -18284.582204221027, -17263.909088500266, -16207.653400662406, -15122.856942922259, -14016.196935068139, -12893.991529799485, -11762.205328065833, -10626.439769837914, -9490.3191584519027, -8354.1985470658783, -7218.0779356797575, -6081.9573242938068, -4945.8367129076605, -3809.7161015215393, -2673.5954901353934, -1537.4748787493209, -401.35426736339457, 734.76028191512512, 1862.3074495985777, 2947.158200990089, 3960.1884858314311, 4888.6048315275966, 5719.7202101002222, 6439.2477046714184, 7031.3497219455321, 7478.6872046947792, 7762.4688442382803, 7862.653161699448] -x=[0.10000000000000001, 0.20000000000000001, 0.30000000000000004, 0.40000000000000002, 0.5, 0.59999999999999998, 0.70000000000000007, 0.80000000000000004, 0.90000000000000002, 1.0, 1.1000000000000001, 1.2000000000000002, 1.3000000000000003, 1.4000000000000001, 1.5000000000000002, 1.6000000000000001, 1.7000000000000002, 1.8000000000000003, 1.9000000000000001, 2.0, 2.1000000000000001, 2.2000000000000002, 2.3000000000000003, 2.4000000000000004, 2.5000000000000004, 2.6000000000000001, 2.7000000000000002, 2.8000000000000003, 2.9000000000000004, 3.0000000000000004, 3.1000000000000001, 3.2000000000000002, 3.3000000000000003, 3.4000000000000004, 3.5000000000000004, 3.6000000000000001, 3.7000000000000002, 3.8000000000000003, 3.9000000000000004, 4.0, 4.0999999999999996, 4.2000000000000002, 4.2999999999999998, 4.3999999999999995, 4.5, 4.5999999999999996, 4.7000000000000002, 4.7999999999999998, 4.9000000000000004, 5.0, 5.0999999999999996, 5.2000000000000002, 5.2999999999999998, 5.4000000000000004, 5.5, 5.5999999999999996, 5.7000000000000002, 5.7999999999999998, 5.9000000000000004, 6.0, 6.0999999999999996, 6.2000000000000002, 6.2999999999999998, 6.4000000000000004, 6.5, 6.5999999999999996, 6.7000000000000002, 6.7999999999999998, 6.9000000000000004, 7.0, 7.0999999999999996, 7.2000000000000002, 7.2999999999999998, 7.4000000000000004, 7.5, 7.5999999999999996, 7.7000000000000002, 7.7999999999999998, 7.9000000000000004, 8.0, 8.0999999999999996, 8.1999999999999993, 8.3000000000000007, 8.4000000000000004, 8.5, 8.5999999999999996, 8.6999999999999993, 8.8000000000000007, 8.9000000000000004, 9.0, 9.0999999999999996, 9.1999999999999993, 9.3000000000000007, 9.4000000000000004, 9.5, 9.5999999999999996, 9.7000000000000011, 9.8000000000000007, 9.9000000000000004, 10.0] - -## PeakFunctions -# PeakFunction 0 -function='GaussianOverR' -module='diffpy.srmise.peaks.gaussianoverr' -base=None -maxwidth=0.7 - -# PeakFunction 1 -function='TerminationRipples' -module='diffpy.srmise.peaks.terminationripples' -base=0 -supersample=5.0 -qmax=21.299999 -extension=4.0 - -# BaselineObject -owner=0 -pars=[] -free=[] -removable=False -static_owner=False - -## InitialPeaks -# InitialPeak -owner=1 -pars=[1.4405204554516691, -1.2061427641856071, 35515.046652471457] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[2.438434532535517, -1.0172294915807534, 73907.95409899787] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[2.8466518758106782, -1.2304130209246791, 22393.68341747858] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[3.6130030049741437, -0.96813537498221969, 74116.241571422986] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[4.1123544981050593, -0.97808638680046245, 57080.437633499154] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[4.5435374761430225, -1.0237140623085594, 77649.074557792919] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[4.8200332700790085, -1.3157569286768298, 25334.583529360283] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[5.1559926055608667, -0.94684905205981251, 26922.357129268006] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[5.4488979185933921, -0.84101599745930467, 97884.515211333346] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[5.7939320016779119, -0.93814748912840829, 65017.841715670562] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[6.1155712351453602, -0.95320652534244166, 84602.184902963141] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[6.6546577871644779, -0.5034392826881412, 139877.38329477029] -free=[True, True, True] -removable=True -static_owner=False - -# InitialPeak -owner=1 -pars=[7.0273811314906363, -0.98019977520362001, 42013.802308636514] -free=[True, True, True] -removable=True -static_owner=False - -# SrMiseMetadata -pf=[1] -cres=0.05 -ModelEvaluator=AIC -Range=[1.0, 7.25] -# Metadata -filename='/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/C60_fine_qmax21.gr' -nyquist=True -qmax=21.299999 -qmax_reportedbypdf=21.299999 -qmax_fromdata=20.755266780473114 -scale=False -supersample=4.0 - -##### start data -#L x y dx dy edy -0.01 18942.6 0 8.53691 5000 -0.02 37722.7 0 16.7546 5000 -0.03 56177.6 0 24.347 5000 -0.04 74143.9 0 31.0336 5000 -0.05 91457.9 0 36.571 5000 -0.06 107956 0 40.7633 5000 -0.07 123476 0 43.4706 5000 -0.08 137856 0 44.6161 5000 -0.09 150940 0 44.191 5000 -0.1 162578 0 42.2588 5000 -0.11 172629 0 38.9611 5000 -0.12 180964 0 34.5282 5000 -0.13 187472 0 29.307 5000 -0.14 192060 0 23.8359 5000 -0.15 194658 0 19.0276 5000 -0.16 195226 0 16.3851 5000 -0.17 193750 0 17.2383 5000 -0.18 190254 0 20.9462 5000 -0.19 184793 0 25.822 5000 -0.2 177460 0 30.698 5000 -0.21 168386 0 34.9379 5000 -0.22 157737 0 38.1842 5000 -0.23 145712 0 40.2361 5000 -0.24 132543 0 41.0033 5000 -0.25 118488 0 40.4884 5000 -0.26 103827 0 38.7838 5000 -0.27 88856.5 0 36.0754 5000 -0.28 73881.6 0 32.6565 5000 -0.29 59209 0 28.9558 5000 -0.3 45139.3 0 25.5728 5000 -0.31 31959.2 0 23.2628 5000 -0.32 19933.4 0 22.7026 5000 -0.33 9297.65 0 24.0285 5000 -0.34 251.704 0 26.7081 5000 -0.35 -7046.27 0 29.9659 5000 -0.36 -12484.5 0 33.1496 5000 -0.37 -16000.8 0 35.809 5000 -0.38 -17584.8 0 37.6619 5000 -0.39 -17278 0 38.5549 5000 -0.4 -15172.9 0 38.4411 5000 -0.41 -11410.1 0 37.3693 5000 -0.42 -6173.99 0 35.4819 5000 -0.43 312.641 0 33.0201 5000 -0.44 7795.7 0 30.331 5000 -0.45 15997.5 0 27.8677 5000 -0.46 24625.2 0 26.1426 5000 -0.47 33380 0 25.5822 5000 -0.48 41966.4 0 26.3124 5000 -0.49 50100.7 0 28.0791 5000 -0.5 57520.3 0 30.4057 5000 -0.51 63990.9 0 32.8044 5000 -0.52 69313.7 0 34.886 5000 -0.53 73330.8 0 36.3811 5000 -0.54 75929.5 0 37.131 5000 -0.55 77044.7 0 37.0761 5000 -0.56 76660.3 0 36.2478 5000 -0.57 74808.1 0 34.7652 5000 -0.58 71565.9 0 32.8355 5000 -0.59 67053.6 0 30.7514 5000 -0.6 61428.1 0 28.8765 5000 -0.61 54877.1 0 27.5925 5000 -0.62 47611.7 0 27.1928 5000 -0.63 39858.8 0 27.7571 5000 -0.64 31853 0 29.1121 5000 -0.65 23828 0 30.9201 5000 -0.66 16008.6 0 32.8095 5000 -0.67 8603.69 0 34.4622 5000 -0.68 1798.99 0 35.646 5000 -0.69 -4248.35 0 36.2199 5000 -0.7 -9414.3 0 36.1298 5000 -0.71 -13611.1 0 35.4048 5000 -0.72 -16789.1 0 34.1541 5000 -0.73 -18936.8 0 32.5637 5000 -0.74 -20079.9 0 30.8888 5000 -0.75 -20278.6 0 29.4309 5000 -0.76 -19624.1 0 28.4858 5000 -0.77 -18233.7 0 28.2603 5000 -0.78 -16245 0 28.7926 5000 -0.79 -13810.2 0 29.9374 5000 -0.8 -11089.1 0 31.4287 5000 -0.81 -8242.85 0 32.9701 5000 -0.82 -5427.21 0 34.3007 5000 -0.83 -2786.99 0 35.2261 5000 -0.84 -450.548 0 35.6277 5000 -0.85 1474.5 0 35.4644 5000 -0.86 2904.71 0 34.7693 5000 -0.87 3783.01 0 33.6482 5000 -0.88 4079.74 0 32.2736 5000 -0.89 3792.54 0 30.8738 5000 -0.9 2944.99 0 29.7056 5000 -0.91 1584.28 0 29.0051 5000 -0.92 -222.159 0 28.9205 5000 -0.93 -2390.68 0 29.4595 5000 -0.94 -4826.07 0 30.4869 5000 -0.95 -7426.55 0 31.7771 5000 -0.96 -10088.8 0 33.0821 5000 -0.97 -12713 0 34.1826 5000 -0.98 -15207.3 0 34.9156 5000 -0.99 -17492 0 35.1842 5000 -1 -19503 0 34.9606 5000 -1.01 -21193.7 0 34.2847 5000 -1.02 -22537 0 33.2613 5000 -1.03 -23525.9 0 32.053 5000 -1.04 -24172 0 30.8661 5000 -1.05 -24504.7 0 29.9216 5000 -1.06 -24568.6 0 29.4096 5000 -1.07 -24419.8 0 29.435 5000 -1.08 -24122.2 0 29.9825 5000 -1.09 -23743.2 0 30.9231 5000 -1.1 -23349 0 32.0586 5000 -1.11 -23000.1 0 33.1763 5000 -1.12 -22747 0 34.0897 5000 -1.13 -22626 0 34.6619 5000 -1.14 -22656.6 0 34.8154 5000 -1.15 -22838.5 0 34.5356 5000 -1.16 -23150.5 0 33.8694 5000 -1.17 -23550 0 32.922 5000 -1.18 -23973.8 0 31.8483 5000 -1.19 -24339.8 0 30.8363 5000 -1.2 -24550.2 0 30.0775 5000 -1.21 -24495 0 29.7246 5000 -1.22 -24056.8 0 29.8486 5000 -1.23 -23116.2 0 30.4155 5000 -1.24 -21557.6 0 31.2994 5000 -1.25 -19274.7 0 32.3219 5000 -1.26 -16176.8 0 33.2965 5000 -1.27 -12193.8 0 34.0627 5000 -1.28 -7281.75 0 34.5058 5000 -1.29 -1426.42 0 34.5652 5000 -1.3 5353.3 0 34.2379 5000 -1.31 13003.6 0 33.5775 5000 -1.32 21435 0 32.6893 5000 -1.33 30523.3 0 31.7209 5000 -1.34 40111.4 0 30.8441 5000 -1.35 50013.2 0 30.225 5000 -1.36 60017.9 0 29.9866 5000 -1.37 69896.1 0 30.1742 5000 -1.38 79406.9 0 30.7413 5000 -1.39 88304.8 0 31.5659 5000 -1.4 96348 0 32.4856 5000 -1.41 103306 0 33.3355 5000 -1.42 108970 0 33.9764 5000 -1.43 113155 0 34.312 5000 -1.44 115713 0 34.2965 5000 -1.45 116534 0 33.9373 5000 -1.46 115552 0 33.2933 5000 -1.47 112750 0 32.4696 5000 -1.48 108158 0 31.6062 5000 -1.49 101857 0 30.8589 5000 -1.5 93973.5 0 30.3705 5000 -1.51 84679 0 30.2374 5000 -1.52 74183.6 0 30.4828 5000 -1.53 62730.5 0 31.0503 5000 -1.54 50588.5 0 31.8217 5000 -1.55 38044 0 32.6485 5000 -1.56 25391.8 0 33.3847 5000 -1.57 12926.4 0 33.9104 5000 -1.58 932.466 0 34.1461 5000 -1.59 -10323.7 0 34.0596 5000 -1.6 -20602.4 0 33.668 5000 -1.61 -29697.7 0 33.0355 5000 -1.62 -37443.6 0 32.2668 5000 -1.63 -43718.3 0 31.4948 5000 -1.64 -48447.8 0 30.8606 5000 -1.65 -51607 0 30.486 5000 -1.66 -53219.5 0 30.444 5000 -1.67 -53355.7 0 30.7394 5000 -1.68 -52129.5 0 31.3074 5000 -1.69 -49693 0 32.033 5000 -1.7 -46230.6 0 32.7797 5000 -1.71 -41951.5 0 33.4173 5000 -1.72 -37082.2 0 33.8426 5000 -1.73 -31857.8 0 33.9912 5000 -1.74 -26513.5 0 33.8433 5000 -1.75 -21276.4 0 33.4249 5000 -1.76 -16357.9 0 32.805 5000 -1.77 -11945.9 0 32.0878 5000 -1.78 -8199.74 0 31.3994 5000 -1.79 -5244.58 0 30.8672 5000 -1.8 -3168.44 0 30.5942 5000 -1.81 -2020.1 0 30.6332 5000 -1.82 -1808.73 0 30.9733 5000 -1.83 -2505.02 0 31.5432 5000 -1.84 -4043.73 0 32.2308 5000 -1.85 -6327.61 0 32.9098 5000 -1.86 -9232.41 0 33.464 5000 -1.87 -12612.9 0 33.8044 5000 -1.88 -16309.4 0 33.8798 5000 -1.89 -20154.9 0 33.6813 5000 -1.9 -23982.3 0 33.2426 5000 -1.91 -27631.4 0 32.6362 5000 -1.92 -30955 0 31.9652 5000 -1.93 -33825.5 0 31.3483 5000 -1.94 -36139.1 0 30.9002 5000 -1.95 -37819.9 0 30.7067 5000 -1.96 -38822.6 0 30.804 5000 -1.97 -39133.3 0 31.1691 5000 -1.98 -38769.7 0 31.7268 5000 -1.99 -37779.1 0 32.3689 5000 -2 -36236.3 0 32.979 5000 -2.01 -34239.2 0 33.4534 5000 -2.02 -31903.8 0 33.7162 5000 -2.03 -29358.9 0 33.7281 5000 -2.04 -26739.8 0 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5000 -19.53 -5911.26 0 32.225 5000 -19.54 -5856.84 0 32.2887 5000 -19.55 -5805.05 0 32.3541 5000 -19.56 -5755.67 0 32.4095 5000 -19.57 -5708.63 0 32.4451 5000 -19.58 -5663.99 0 32.4547 5000 -19.59 -5621.85 0 32.4365 5000 -19.6 -5582.34 0 32.3939 5000 -19.61 -5545.55 0 32.3343 5000 -19.62 -5511.44 0 32.2684 5000 -19.63 -5479.79 0 32.2079 5000 -19.64 -5450.16 0 32.1637 5000 -19.65 -5421.84 0 32.1438 5000 -19.66 -5393.8 0 32.1517 5000 -19.67 -5364.75 0 32.186 5000 -19.68 -5333.07 0 32.2404 5000 -19.69 -5296.92 0 32.3052 5000 -19.7 -5254.27 0 32.3687 5000 -19.71 -5202.97 0 32.4196 5000 -19.72 -5140.85 0 32.4489 5000 -19.73 -5065.84 0 32.4515 5000 -19.74 -4976.03 0 32.427 5000 -19.75 -4869.85 0 32.3796 5000 -19.76 -4746.15 0 32.3179 5000 -19.77 -4604.26 0 32.2528 5000 -19.78 -4444.13 0 32.1959 5000 -19.79 -4266.32 0 32.1575 5000 -19.8 -4072.09 0 32.1446 5000 -19.81 -3863.38 0 32.1593 5000 -19.82 -3642.76 0 32.1991 5000 -19.83 -3413.38 0 32.2566 5000 -19.84 -3178.89 0 32.3216 5000 -19.85 -2943.31 0 32.3824 5000 -19.86 -2710.89 0 32.4282 5000 -19.87 -2485.95 0 32.4509 5000 -19.88 -2272.7 0 32.4465 5000 -19.89 -2075.1 0 32.4158 5000 -19.9 -1896.62 0 32.3643 5000 -19.91 -1740.17 0 32.3011 5000 -19.92 -1607.88 0 32.2375 5000 -19.93 -1501.07 0 32.1849 5000 -19.94 -1420.09 0 32.1527 5000 -19.95 -1364.33 0 32.1469 5000 -19.96 -1332.23 0 32.1683 5000 -19.97 -1321.27 0 32.2131 5000 -19.98 -1328.11 0 32.2732 5000 -19.99 -1348.67 0 32.3378 5000 -##### Results -extraction_type='fit' -### ModelCluster -peak_funcs=[1] -ModelEvaluator=AIC -slice=slice(None, 43, None) -# BaselineObject -owner=0 -pars=[] -free=[] -removable=False -static_owner=False - -## ModelPeaks -# ModelPeak -owner=1 -pars=[1.4405204554516691, -1.2061427641856071, 35515.046652471457] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[2.438434532535517, -1.0172294915807534, 73907.95409899787] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[2.8466518758106782, -1.2304130209246791, 22393.68341747858] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[3.6130030049741437, -0.96813537498221969, 74116.241571422986] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[4.1123544981050593, -0.97808638680046245, 57080.437633499154] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[4.5435374761430225, -1.0237140623085594, 77649.074557792919] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[4.8200332700790085, -1.3157569286768298, 25334.583529360283] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[5.1559926055608667, -0.94684905205981251, 26922.357129268006] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[5.4488979185933921, -0.84101599745930467, 97884.515211333346] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[5.7939320016779119, -0.93814748912840829, 65017.841715670562] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[6.1155712351453602, -0.95320652534244166, 84602.184902963141] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[6.6546577871644779, -0.5034392826881412, 139877.38329477029] -free=[True, True, True] -removable=True -static_owner=False - -# ModelPeak -owner=1 -pars=[7.0273811314906363, -0.98019977520362001, 42013.802308636514] -free=[True, True, True] -removable=True -static_owner=False - -### start data -#L r y dy -1 -19502.9 5000 -1.14749 -22788.9 5000 -1.29499 1852.19 5000 -1.44248 116074 5000 -1.58997 -10291.9 5000 -1.73746 -27861.6 5000 -1.88496 -18215.1 5000 -2.03245 -28714 5000 -2.17994 -26150.2 5000 -2.32743 34592.3 5000 -2.47493 94708.1 5000 -2.62242 -34046.8 5000 -2.76991 -6095.59 5000 -2.9174 -9022.01 5000 -3.0649 -47692.9 5000 -3.21239 -39823.5 5000 -3.35988 -45615.1 5000 -3.50737 13411.8 5000 -3.65487 42196.6 5000 -3.80236 -28611.3 5000 -3.94985 -21093.7 5000 -4.09735 22420.5 5000 -4.24484 -12021.5 5000 -4.39233 -17934.3 5000 -4.53982 45713.7 5000 -4.68732 -9106.12 5000 -4.83481 459.793 5000 -4.9823 -30024.4 5000 -5.12979 -6029.52 5000 -5.27729 -3788.41 5000 -5.42478 38601.6 5000 -5.57227 5401.92 5000 -5.71976 12241.1 5000 -5.86726 6715.96 5000 -6.01475 11253.1 5000 -6.16224 26161.1 5000 -6.30973 -15451.2 5000 -6.45723 -45.4651 5000 -6.60472 29243.8 5000 -6.75221 20789.5 5000 -6.8997 3686.4 5000 -7.0472 6321.19 5000 -7.19469 -14234.2 5000 diff --git a/doc/examples/output/known_dG_aics.dat b/doc/examples/output/known_dG_aics.dat deleted file mode 100644 index 5ed556e..0000000 --- a/doc/examples/output/known_dG_aics.dat +++ /dev/null @@ -1,990 +0,0 @@ -(dp1 -cnumpy.core.multiarray -scalar -p2 -(cnumpy -dtype -p3 -(S'f8' -I0 -I1 -tRp4 -(I3 -S'<' -NNNI-1 -I-1 -I0 -tbS'\xd4\xe8-H\x0c\xda\xdb?' -tRp5 -(lp6 -g2 -(g4 -S'\xff\xf8 \x9f\xfc\xf0K@' -tRp7 -ag2 -(g4 -S'\x0bt\x8f\x81\x9f\x0bL@' -tRp8 -ag2 -(g4 -S'HB7\x9e*\x0cL@' -tRp9 -ag2 -(g4 -S'\t\x0c>\x9d*\x0cL@' -tRp10 -ag2 -(g4 -S'\xc0:\x82\x9c*\x0cL@' -tRp11 -ag2 -(g4 -S'\x12\x83imYmJ@' -tRp12 -ag2 -(g4 -S'\xbeQ\x8aqYmJ@' -tRp13 -ag2 -(g4 -S'\xc2\x18IpYmJ@' -tRp14 -ag2 -(g4 -S'\x1d\xec\x8bD\xd4jJ@' -tRp15 -ag2 -(g4 -S'\xdc\xcb]O(mJ@' -tRp16 -ag2 -(g4 -S'\x07\x8bi\xaa\xf9kJ@' -tRp17 -ag2 -(g4 -S'\xae\x8ai\xaa\xf9kJ@' -tRp18 -ag2 -(g4 -S'\x0be\x87\xdb\x9ftJ@' -tRp19 -ag2 -(g4 -S'\x03\x86\x1d~\xa3tJ@' -tRp20 -ag2 -(g4 -S'\x99\xd0k\xf6\xa1tJ@' -tRp21 -asg2 -(g4 -S'\xeb\x12\xa9\xe1j8\xd5?' -tRp22 -(lp23 -g2 -(g4 -S'\xf0\xcc\x1f.#\x9fL@' -tRp24 -ag2 -(g4 -S'\xe7\x1e0\xc6\x05\xcdL@' -tRp25 -ag2 -(g4 -S'/1\x8dj\xf5\xcdL@' -tRp26 -ag2 -(g4 -S'\xbc\xe2\xdfh\xf5\xcdL@' -tRp27 -ag2 -(g4 -S'4W\x9cg\xf5\xcdL@' -tRp28 -ag2 -(g4 -S'\xca\xc2z\r_.L@' -tRp29 -ag2 -(g4 -S'\xd0F\x97\x14_.L@' -tRp30 -ag2 -(g4 -S'\xa6\xebm\x12_.L@' -tRp31 -ag2 -(g4 -S'\xbd\t\x15\xaa\x07*L@' -tRp32 -ag2 -(g4 -S'.\x94\xb8p\n.L@' -tRp33 -ag2 -(g4 -S'\x80\xd0\x8f\x16\x01,L@' -tRp34 -ag2 -(g4 -S'\xe6\xcf\x8f\x16\x01,L@' -tRp35 -ag2 -(g4 -S'\x10=,a\xe7eN@' -tRp36 -ag2 -(g4 -S'\xdb\xdb@\xa4\xedeN@' -tRp37 -ag2 -(g4 -S'X\xba\x7f\x01\xebeN@' -tRp38 -asg2 -(g4 -S'1\x0bc\xa4\x19\x81\xde?' -tRp39 -(lp40 -g2 -(g4 -S'\x85\x1cr\xf4\xe5\xc8K@' -tRp41 -ag2 -(g4 -S'\xe3\xe3\xc8\x81\x1a\xdfK@' -tRp42 -ag2 -(g4 -S'\xc2\xbe7z\x8e\xdfK@' -tRp43 -ag2 -(g4 -S't\xfdgy\x8e\xdfK@' -tRp44 -ag2 -(g4 -S'\x90j\xcbx\x8e\xdfK@' -tRp45 -ag2 -(g4 -S'S/Q\xa3\xfc\x05J@' -tRp46 -ag2 -(g4 -S'\xca0\xc2\xa6\xfc\x05J@' -tRp47 -ag2 -(g4 -S'dg\xb6\xa5\xfc\x05J@' -tRp48 -ag2 -(g4 -S'\x1a\x17:\xcd\xe2\x03J@' -tRp49 -ag2 -(g4 -S'\xbb\xec\xfb\xb0\xd3\x05J@' -tRp50 -ag2 -(g4 -S'?\x1erd\xd7\x04J@' -tRp51 -ag2 -(g4 -S'\xf4\x1drd\xd7\x04J@' -tRp52 -ag2 -(g4 -S'\xe6\xd6q1K\x8cI@' -tRp53 -ag2 -(g4 -S'\xe6\x00:9N\x8cI@' -tRp54 -ag2 -(g4 -S'\xc8\xfc\xb0\xf2L\x8cI@' -tRp55 -asg2 -(g4 -S'\xa6W\x13\x9a\x85\x86\xca?' -tRp56 -(lp57 -g2 -(g4 -S'(\xf8\x13v\xc0&O@' -tRp58 -ag2 -(g4 -S'<\xd4\xeb\xbd7\x9cO@' -tRp59 -ag2 -(g4 -S'0_\xbb9\x9d\x9eO@' -tRp60 -ag2 -(g4 -S'\xecXp5\x9d\x9eO@' -tRp61 -ag2 -(g4 -S'p\x1242\x9d\x9eO@' -tRp62 -ag2 -(g4 -S'\x88,tD\x13ZQ@' -tRp63 -ag2 -(g4 -S'\x1fo\x8eM\x13ZQ@' -tRp64 -ag2 -(g4 -S'c#\xcaJ\x13ZQ@' -tRp65 -ag2 -(g4 -S'\xc9\xc4\xbe\xb0\x84TQ@' -tRp66 -ag2 -(g4 -S'&\xd2\xae\xf6\xa6YQ@' -tRp67 -ag2 -(g4 -S'2\xc3\xff\xa1\x0bWQ@' -tRp68 -ag2 -(g4 -S'n\xc2\xff\xa1\x0bWQ@' -tRp69 -ag2 -(g4 -S'\x1ew\xdc\x90\x8e\x87V@' -tRp70 -ag2 -(g4 -S'7\xe6\xcd\x94\x96\x87V@' -tRp71 -ag2 -(g4 -S'(_\x1e5\x93\x87V@' -tRp72 -asg2 -(g4 -S'`\x9c}R\xa0\xd4\xcf?' -tRp73 -(lp74 -g2 -(g4 -S'\x8e\xfaT\xa7\x05\xe2M@' -tRp75 -ag2 -(g4 -S'bS\xc7|\x983N@' -tRp76 -ag2 -(g4 -S'\xfe:\x89\x84B5N@' -tRp77 -ag2 -(g4 -S'\xdc\x04\x8e\x81B5N@' -tRp78 -ag2 -(g4 -S'\xeb\xd3N\x7fB5N@' -tRp79 -ag2 -(g4 -S'g!\x13\xdf\xe1nO@' -tRp80 -ag2 -(g4 -S'V\x9a\xb7\xeb\xe1nO@' -tRp81 -ag2 -(g4 -S'\xd1\xdb\xdf\xe7\xe1nO@' -tRp82 -ag2 -(g4 -S'\x18\x83\xec\x11*gO@' -tRp83 -ag2 -(g4 -S'R@\x0fsKnO@' -tRp84 -ag2 -(g4 -S'\xc69\xe3\x99\xacjO@' -tRp85 -ag2 -(g4 -S'\xb58\xe3\x99\xacjO@' -tRp86 -ag2 -(g4 -S"\xb9R'\xc8\x94\xdaR@" -tRp87 -ag2 -(g4 -S'45\x1dY\x9a\xdaR@' -tRp88 -ag2 -(g4 -S'j\x17U\x01\x98\xdaR@' -tRp89 -asg2 -(g4 -S'\xbc\x81\x8e3\xe4\xe4\xd3?' -tRp90 -(lp91 -g2 -(g4 -S'\x84\xfc\xcf\x89U\xd8L@' -tRp92 -ag2 -(g4 -S'T^L\x8d\x8a\x0cM@' -tRp93 -ag2 -(g4 -S'2c\x1a6\x9b\rM@' -tRp94 -ag2 -(g4 -S'\xa2\xee14\x9b\rM@' -tRp95 -ag2 -(g4 -S'N\xcf\xc12\x9b\rM@' -tRp96 -ag2 -(g4 -S'#\x0b\xd9<\xd8\xc1L@' -tRp97 -ag2 -(g4 -S'\xc6b\xf0D\xd8\xc1L@' -tRp98 -ag2 -(g4 -S' \xcazB\xd8\xc1L@' -tRp99 -ag2 -(g4 -S'\xb3 \x8d\xb9\xe7\xbcL@' -tRp100 -ag2 -(g4 -S'>\xd7\xb7\xf7w\xc1L@' -tRp101 -ag2 -(g4 -S'-X\xe3\xc8&\xbfL@' -tRp102 -ag2 -(g4 -S'~W\xe3\xc8&\xbfL@' -tRp103 -ag2 -(g4 -S'\xe3i\xe0Gb\xb1O@' -tRp104 -ag2 -(g4 -S'Nw\xd3gi\xb1O@' -tRp105 -ag2 -(g4 -S'A\xff\x1ahf\xb1O@' -tRp106 -asg2 -(g4 -S'v\xc6\xf8\xeb\xfe2\xd9?' -tRp107 -(lp108 -g2 -(g4 -S'\xf1<\xdf\x1dd&L@' -tRp109 -ag2 -(g4 -S'%\xbb\x7f\x1c\xeeFL@' -tRp110 -ag2 -(g4 -S"!\xd9'\r\x98GL@" -tRp111 -ag2 -(g4 -S'\xc4h\xf7\x0b\x98GL@' -tRp112 -ag2 -(g4 -S'X\xf8\x11\x0b\x98GL@' -tRp113 -ag2 -(g4 -S'\x06\x993b\x0b\xf7J@' -tRp114 -ag2 -(g4 -S'\xc0\x99>g\x0b\xf7J@' -tRp115 -ag2 -(g4 -S'd1\xb6e\x0b\xf7J@' -tRp116 -ag2 -(g4 -S'\xf6\x12\x97@\xf7\xf3J@' -tRp117 -ag2 -(g4 -S'.\xe5\xa9a\xcf\xf6J@' -tRp118 -ag2 -(g4 -S'2*M\xab]\xf5J@' -tRp119 -ag2 -(g4 -S'\xc4)M\xab]\xf5J@' -tRp120 -ag2 -(g4 -S'p{7. \xaaK@' -tRp121 -ag2 -(g4 -S'\xc6\xfd\x06\x9f$\xaaK@' -tRp122 -ag2 -(g4 -S'Q\xf6\x87\xc0"\xaaK@' -tRp123 -asg2 -(g4 -S'\xa5W\x13\x9a\x85\x86\xda?' -tRp124 -(lp125 -g2 -(g4 -S'\n\xfe\x84\x1d\xb0\tL@' -tRp126 -ag2 -(g4 -S"\x0f\xf5z\xef\r'L@" -tRp127 -ag2 -(g4 -S"\xcc\xd7nN\xa7'L@" -tRp128 -ag2 -(g4 -S";\x16\\M\xa7'L@" -tRp129 -ag2 -(g4 -S"\x9c\x04\x8dL\xa7'L@" -tRp130 -ag2 -(g4 -S'D\x16:\xa2\t\xadJ@' -tRp131 -ag2 -(g4 -S'\x907\xc7\xa6\t\xadJ@' -tRp132 -ag2 -(g4 -S'\xb2\x11e\xa5\t\xadJ@' -tRp133 -ag2 -(g4 -S'eb_XB\xaaJ@' -tRp134 -ag2 -(g4 -S'\x13iW{\xd3\xacJ@' -tRp135 -ag2 -(g4 -S'\x9a\xe1\xff\xd0\x85\xabJ@' -tRp136 -ag2 -(g4 -S'7\xe1\xff\xd0\x85\xabJ@' -tRp137 -ag2 -(g4 -S'\x90;nH\xc7\x03K@' -tRp138 -ag2 -(g4 -S'\x1c\xf3fJ\xcb\x03K@' -tRp139 -ag2 -(g4 -S'\x95/\x8f\x9a\xc9\x03K@' -tRp140 -asg2 -(g4 -S'\x02zH\xf6\x92-\xdd?' -tRp141 -(lp142 -g2 -(g4 -S'\x817a\xaa\x93\xdbK@' -tRp143 -ag2 -(g4 -S'pmt\xbd\xd8\xf3K@' -tRp144 -ag2 -(g4 -S'p\x0f-~W\xf4K@' -tRp145 -ag2 -(g4 -S'7\xfdI}W\xf4K@' -tRp146 -ag2 -(g4 -S'\x9d\xdb\x9e|W\xf4K@' -tRp147 -ag2 -(g4 -S'\x8b\xb9\xe1\x94%6J@' -tRp148 -ag2 -(g4 -S'f\xa4\xa4\x98%6J@' -tRp149 -ag2 -(g4 -S'<\xf5\x7f\x97%6J@' -tRp150 -ag2 -(g4 -S'O\x1af\xbd\xd93J@' -tRp151 -ag2 -(g4 -S'\xa8\x9c\xf3\xd3\xf85J@' -tRp152 -ag2 -(g4 -S'\xf3\xd5G\x12\xe54J@' -tRp153 -ag2 -(g4 -S'\xa2\xd5G\x12\xe54J@' -tRp154 -ag2 -(g4 -S'\xdc\xbc\xe6N\x8b\xf8I@' -tRp155 -ag2 -(g4 -S'\x08\xcb\xcf\x9e\x8e\xf8I@' -tRp156 -ag2 -(g4 -S'\xf6\xb2\xea9\x8d\xf8I@' -tRp157 -asg2 -(g4 -S'\x8e\xf0s\x85]\x91\xd2?' -tRp158 -(lp159 -g2 -(g4 -S'>0\nf8\x1eM@' -tRp160 -ag2 -(g4 -S'\x19\xc5\x82\xe3&ZM@' -tRp161 -ag2 -(g4 -S'#U\xfc\xe3_[M@' -tRp162 -ag2 -(g4 -S'\x15\x9b\xcb\xe1_[M@' -tRp163 -ag2 -(g4 -S'/\x04%\xe0_[M@' -tRp164 -ag2 -(g4 -S'\xe8f-6\tvM@' -tRp165 -ag2 -(g4 -S'\xec7w?\tvM@' -tRp166 -ag2 -(g4 -S'\xb4w\xa4<\tvM@' -tRp167 -ag2 -(g4 -S'@\xd3:\x9a]pM@' -tRp168 -ag2 -(g4 -S'\xaf\n\x93\xb2\x9auM@' -tRp169 -ag2 -(g4 -S'\xd0xm\xbf\xf1rM@' -tRp170 -ag2 -(g4 -S'\x07xm\xbf\xf1rM@' -tRp171 -ag2 -(g4 -S'\xacQ\xf8\xd63\xa3P@' -tRp172 -ag2 -(g4 -S'\xc36\xe1\xed7\xa3P@' -tRp173 -ag2 -(g4 -S'\xacJ956\xa3P@' -tRp174 -asg2 -(g4 -S'H5\xde=x\xdf\xd7?' -tRp175 -(lp176 -g2 -(g4 -S'x6B\x83\x02HL@' -tRp177 -ag2 -(g4 -S',\xec\xad\xc5ClL@' -tRp178 -ag2 -(g4 -S'T\xe1u\x1e\x01mL@' -tRp179 -ag2 -(g4 -S'\xd4\xac"\x1d\x01mL@' -tRp180 -ag2 -(g4 -S'\xda\x08#\x1c\x01mL@' -tRp181 -ag2 -(g4 -S'\xbcGz\xb8\xb9MK@' -tRp182 -ag2 -(g4 -S'_\xb6\x18\xbe\xb9MK@' -tRp183 -ag2 -(g4 -S'$~c\xbc\xb9MK@' -tRp184 -ag2 -(g4 -S'D:0\x96KJK@' -tRp185 -ag2 -(g4 -S'\xb2\xe3\xcd\xddvMK@' -tRp186 -ag2 -(g4 -S'\xe6\xa7\x0f\xef\xdaKK@' -tRp187 -ag2 -(g4 -S'm\xa7\x0f\xef\xdaKK@' -tRp188 -ag2 -(g4 -S'\xfae?\x07\xf6lL@' -tRp189 -ag2 -(g4 -S'\xda\x12\xe1\xf9\xfalL@' -tRp190 -ag2 -(g4 -S'&j\xbd\xe4\xf8lL@' -tRp191 -asg2 -(g4 -S'\x03zH\xf6\x92-\xcd?' -tRp192 -(lp193 -g2 -(g4 -S'\x04\xde\x84\xa9NnN@' -tRp194 -ag2 -(g4 -S'\xbf\xb5\xd1\xf5b\xcfN@' -tRp195 -ag2 -(g4 -S'\xbe=\xb4\xf8]\xd1N@' -tRp196 -ag2 -(g4 -S"\xdc\xf4'\xf5]\xd1N@" -tRp197 -ag2 -(g4 -S'rn{\xf2]\xd1N@' -tRp198 -ag2 -(g4 -S'\x15s\xc3)KlP@' -tRp199 -ag2 -(g4 -S'\xccHI1KlP@' -tRp200 -ag2 -(g4 -S'x\xea\xff.KlP@' -tRp201 -ag2 -(g4 -S'\x9e4\xccz\xb3gP@' -tRp202 -ag2 -(g4 -S'P9\xe7\xa7\xf1kP@' -tRp203 -ag2 -(g4 -S'\xe6\xab\x8f$\xcaiP@' -tRp204 -ag2 -(g4 -S'D\xab\x8f$\xcaiP@' -tRp205 -ag2 -(g4 -S'\xb8y\xcd\x9d\x16qT@' -tRp206 -ag2 -(g4 -S'\x10\x96\x9f=\x1dqT@' -tRp207 -ag2 -(g4 -S'\xebe\xd5s\x1aqT@' -tRp208 -asg2 -(g4 -S'__Y\xd7\xd6=\xd1?' -tRp209 -(lp210 -g2 -(g4 -S'\xf37h\xe3\xd8tM@' -tRp211 -ag2 -(g4 -S'\x98K\xa5\x8bZ\xbaM@' -tRp212 -ag2 -(g4 -S'\xf0\x10\xb6\x8d\xc5\xbbM@' -tRp213 -ag2 -(g4 -S'~\xc1+\x8b\xc5\xbbM@' -tRp214 -ag2 -(g4 -S'\xef\xa6A\x89\xc5\xbbM@' -tRp215 -ag2 -(g4 -S'H\n\\\x0edUN@' -tRp216 -ag2 -(g4 -S'\x95\xbe!\x19dUN@' -tRp217 -ag2 -(g4 -S'H\x86\xdb\x15dUN@' -tRp218 -ag2 -(g4 -S'Z\xb2t\x88\xd0NN@' -tRp219 -ag2 -(g4 -S'\xea\xdb\xcb\xe2\xe3TN@' -tRp220 -ag2 -(g4 -S'\x97\xbc4%\xceQN@' -tRp221 -ag2 -(g4 -S'\xae\xbb4%\xceQN@' -tRp222 -ag2 -(g4 -S'O4\x9c\x179\x9eQ@' -tRp223 -ag2 -(g4 -S'\x9d\x16\xc7\xd5=\x9eQ@' -tRp224 -ag2 -(g4 -S'A\x99\xb8\xd6;\x9eQ@' -tRp225 -asg2 -(g4 -S'`\x9c}R\xa0\xd4\xdf?' -tRp226 -(lp227 -g2 -(g4 -S'\xa3>\xd5i\x81\xb8K@' -tRp228 -ag2 -(g4 -S'\xd9\xd41\x1f\xe6\xccK@' -tRp229 -ag2 -(g4 -S'\xbfN"\xa1P\xcdK@' -tRp230 -ag2 -(g4 -S'7\x81c\xa0P\xcdK@' -tRp231 -ag2 -(g4 -S'\xfb\xb4\xd3\x9fP\xcdK@' -tRp232 -ag2 -(g4 -S'Z\xc8\xc4w\xb8\xdbI@' -tRp233 -ag2 -(g4 -S'\x96\xe6\xedz\xb8\xdbI@' -tRp234 -ag2 -(g4 -S'\xf4\xf6\xf7y\xb8\xdbI@' -tRp235 -ag2 -(g4 -S'\xc6 {\x84\xca\xd9I@' -tRp236 -ag2 -(g4 -S'\x14\xd0\xc3\xdc\x92\xdbI@' -tRp237 -ag2 -(g4 -S'r\xcex&\xab\xdaI@' -tRp238 -ag2 -(g4 -S'-\xcex&\xab\xdaI@' -tRp239 -ag2 -(g4 -S'\\\xa9\x13dJ-I@' -tRp240 -ag2 -(g4 -S'\x9a\x9a\x8e,M-I@' -tRp241 -ag2 -(g4 -S'\xb5\x8b\xaa\x00L-I@' -tRp242 -asg2 -(g4 -S'\x1a\xa4\xc3\x8f\xf1\x8b\xd6?' -tRp243 -(lp244 -g2 -(g4 -S'>j\xb5\xf3\xbboL@' -tRp245 -ag2 -(g4 -S'"\xa1I=a\x98L@' -tRp246 -ag2 -(g4 -S'\xce\x86y\x845\x99L@' -tRp247 -ag2 -(g4 -S'\xc6=\xfd\x825\x99L@' -tRp248 -ag2 -(g4 -S'\x0e\xa4\xde\x815\x99L@' -tRp249 -ag2 -(g4 -S'\xa2\xb3\xf8"&\xb4K@' -tRp250 -ag2 -(g4 -S'\xa5VE)&\xb4K@' -tRp251 -ag2 -(g4 -S"\x18+['&\xb4K@" -tRp252 -ag2 -(g4 -S'\xb5\xd1}\xa7M\xb0K@' -tRp253 -ag2 -(g4 -S'\x147\x96/\xdb\xb3K@' -tRp254 -ag2 -(g4 -S'\xd8\x0c\x82]\r\xb2K@' -tRp255 -ag2 -(g4 -S'O\x0c\x82]\r\xb2K@' -tRp256 -ag2 -(g4 -S'\xb3\x86\x05f.SM@' -tRp257 -ag2 -(g4 -S'\x82)\r\xf23SM@' -tRp258 -ag2 -(g4 -S'\x1dWX\x9c1SM@' -tRp259 -as. diff --git a/doc/examples/output/known_dG_m0.pwa b/doc/examples/output/known_dG_m0.pwa deleted file mode 100644 index d384002..0000000 --- a/doc/examples/output/known_dG_m0.pwa +++ /dev/null @@ -1,65 +0,0 @@ -Summary written: Wed Jul 1 09:54:31 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### User comments -# Multimodeling Summary -# --------------------- -# Evaluated at dG: 0.414460564103 -# Model: 0 (of 15) -# Class: 0 (of 4, tol=0.2) -# Akaike probability: 0.116014 -# Rank: 3 -##### PDF Peak Extraction Summary -# The information below is not sufficient to replicate extraction. -## PDF metadata -filename=/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/Ag_nyquist_qmax30.gr -nyquist=True -qmax=30.0 -qmax_reportedbypdf=30.0 -qmax_fromdata=29.729728241905356 -scale=False -supersample=4.0 - -## Peak extraction metadata -Range=[10.9, 15] -cres=0.10472 -effective_dy=0.207230282051 (mean) - -## Model Quality -# Quality reported by ModelEvaluator: 62.302748451 -# Free parameters in extracted peaks: 27 -# Free parameters in baseline: 2 -# Length of data in final fit: 40 -ModelEvaluator=AIC - -## Baseline Functions -# Index Type -0 diffpy.srmise.baselines.polynomial - -## Baseline -# Parameters of baseline, followed by comment which -# gives the index of corresponding Baseline Function. -# a_1 a_0 --0.510418401742 0.00840743355082 # 0 - -## Peak Functions -# Index Type -0 diffpy.srmise.peaks.gaussianoverr -1 diffpy.srmise.peaks.gaussianoverr -2 diffpy.srmise.peaks.terminationripples (base=1) - -## Extracted Peaks -# Parameters are given in the natural units of the data, -# where width is measured as full-width at half maximum. -# Each line is followed by a comment which gives the index -# of the corresponding Peak Function. -#L position fwhm area -11.2310491383 0.29009226516 19.2512559254 # 2 -11.4396028801 0.699999999983 27.0749215956 # 2 -11.9917737278 0.362929903251 35.1440957376 # 2 -12.2970626245 0.246439663133 11.2573010498 # 2 -12.6468606943 0.420659409723 59.0581484285 # 2 -13.3022057364 0.561794132185 56.019285676 # 2 -13.9271227928 0.461410605827 46.9264650576 # 2 -14.5144826305 0.383957447583 62.6172758881 # 2 -15.2120923348 0.640989083839 148.197881104 # 2 diff --git a/doc/examples/output/known_dG_m1.pwa b/doc/examples/output/known_dG_m1.pwa deleted file mode 100644 index 6c93d54..0000000 --- a/doc/examples/output/known_dG_m1.pwa +++ /dev/null @@ -1,65 +0,0 @@ -Summary written: Wed Jul 1 09:54:31 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### User comments -# Multimodeling Summary -# --------------------- -# Evaluated at dG: 0.414460564103 -# Model: 1 (of 15) -# Class: 1 (of 4, tol=0.2) -# Akaike probability: 0.103441 -# Rank: 4 -##### PDF Peak Extraction Summary -# The information below is not sufficient to replicate extraction. -## PDF metadata -filename=/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/Ag_nyquist_qmax30.gr -nyquist=True -qmax=30.0 -qmax_reportedbypdf=30.0 -qmax_fromdata=29.729728241905356 -scale=False -supersample=4.0 - -## Peak extraction metadata -Range=[10.9, 15] -cres=0.10472 -effective_dy=0.227953310256 (mean) - -## Model Quality -# Quality reported by ModelEvaluator: 61.6202075266 -# Free parameters in extracted peaks: 27 -# Free parameters in baseline: 2 -# Length of data in final fit: 40 -ModelEvaluator=AIC - -## Baseline Functions -# Index Type -0 diffpy.srmise.baselines.polynomial - -## Baseline -# Parameters of baseline, followed by comment which -# gives the index of corresponding Baseline Function. -# a_1 a_0 --0.510418401742 0.00840743355082 # 0 - -## Peak Functions -# Index Type -0 diffpy.srmise.peaks.gaussianoverr -1 diffpy.srmise.peaks.gaussianoverr -2 diffpy.srmise.peaks.terminationripples (base=1) - -## Extracted Peaks -# Parameters are given in the natural units of the data, -# where width is measured as full-width at half maximum. -# Each line is followed by a comment which gives the index -# of the corresponding Peak Function. -#L position fwhm area -11.2529285169 0.364905691879 35.069510576 # 2 -11.6049995958 0.242603175181 5.75251157226 # 2 -11.9810995228 0.395837076343 41.2543174499 # 2 -12.301949991 0.23763791237 9.95499038734 # 2 -12.6464816828 0.421778331973 59.2512366853 # 2 -13.3021821206 0.560737418698 55.9130337232 # 2 -13.9270960895 0.462233109053 47.0245789698 # 2 -14.5135618376 0.382520817816 61.9638372907 # 2 -15.2395954065 0.673266802865 163.664297749 # 2 diff --git a/doc/examples/output/known_dG_m12.pwa b/doc/examples/output/known_dG_m12.pwa deleted file mode 100644 index a64f88b..0000000 --- a/doc/examples/output/known_dG_m12.pwa +++ /dev/null @@ -1,63 +0,0 @@ -Summary written: Wed Jul 1 09:54:31 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### User comments -# Multimodeling Summary -# --------------------- -# Evaluated at dG: 0.414460564103 -# Model: 12 (of 15) -# Class: 3 (of 4, tol=0.2) -# Akaike probability: 0.322723 -# Rank: 2 -##### PDF Peak Extraction Summary -# The information below is not sufficient to replicate extraction. -## PDF metadata -filename=/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/Ag_nyquist_qmax30.gr -nyquist=True -qmax=30.0 -qmax_reportedbypdf=30.0 -qmax_fromdata=29.729728241905356 -scale=False -supersample=4.0 - -## Peak extraction metadata -Range=[10.9, 15] -cres=0.10472 -effective_dy=0.455906620513 (mean) - -## Model Quality -# Quality reported by ModelEvaluator: 51.9417513491 -# Free parameters in extracted peaks: 21 -# Free parameters in baseline: 2 -# Length of data in final fit: 40 -ModelEvaluator=AIC - -## Baseline Functions -# Index Type -0 diffpy.srmise.baselines.polynomial - -## Baseline -# Parameters of baseline, followed by comment which -# gives the index of corresponding Baseline Function. -# a_1 a_0 --0.496000505209 0.00938437875474 # 0 - -## Peak Functions -# Index Type -0 diffpy.srmise.peaks.gaussianoverr -1 diffpy.srmise.peaks.gaussianoverr -2 diffpy.srmise.peaks.terminationripples (base=1) - -## Extracted Peaks -# Parameters are given in the natural units of the data, -# where width is measured as full-width at half maximum. -# Each line is followed by a comment which gives the index -# of the corresponding Peak Function. -#L position fwhm area -11.2573520325 0.373991203999 34.6040498151 # 2 -12.0087151394 0.566599746057 54.4028330737 # 2 -12.6511637826 0.451133520536 60.4517207938 # 2 -13.3046624137 0.512055342072 49.875933375 # 2 -13.9194024649 0.476336586991 47.6570175965 # 2 -14.5143782484 0.376556097123 59.8635311432 # 2 -15.2397459182 0.673630329652 160.521742315 # 2 diff --git a/doc/examples/output/known_dG_m8.pwa b/doc/examples/output/known_dG_m8.pwa deleted file mode 100644 index 8067ee2..0000000 --- a/doc/examples/output/known_dG_m8.pwa +++ /dev/null @@ -1,64 +0,0 @@ -Summary written: Wed Jul 1 09:54:31 2015 -produced by luke -diffpy.srmise version 0.5.2 -##### User comments -# Multimodeling Summary -# --------------------- -# Evaluated at dG: 0.414460564103 -# Model: 8 (of 15) -# Class: 2 (of 4, tol=0.2) -# Akaike probability: 0.457822 -# Rank: 1 -##### PDF Peak Extraction Summary -# The information below is not sufficient to replicate extraction. -## PDF metadata -filename=/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/Ag_nyquist_qmax30.gr -nyquist=True -qmax=30.0 -qmax_reportedbypdf=30.0 -qmax_fromdata=29.729728241905356 -scale=False -supersample=4.0 - -## Peak extraction metadata -Range=[10.9, 15] -cres=0.10472 -effective_dy=0.373014507692 (mean) - -## Model Quality -# Quality reported by ModelEvaluator: 54.5804317222 -# Free parameters in extracted peaks: 24 -# Free parameters in baseline: 2 -# Length of data in final fit: 40 -ModelEvaluator=AIC - -## Baseline Functions -# Index Type -0 diffpy.srmise.baselines.polynomial - -## Baseline -# Parameters of baseline, followed by comment which -# gives the index of corresponding Baseline Function. -# a_1 a_0 --0.510418401742 0.00840743355082 # 0 - -## Peak Functions -# Index Type -0 diffpy.srmise.peaks.gaussianoverr -1 diffpy.srmise.peaks.gaussianoverr -2 diffpy.srmise.peaks.terminationripples (base=1) - -## Extracted Peaks -# Parameters are given in the natural units of the data, -# where width is measured as full-width at half maximum. -# Each line is followed by a comment which gives the index -# of the corresponding Peak Function. -#L position fwhm area -11.2506286561 0.370187490596 34.3566941925 # 2 -11.9567809353 0.178069824317 4.11976261759 # 2 -12.0484452287 0.699999913404 59.8073862592 # 2 -12.663000713 0.41644345755 53.4693315884 # 2 -13.3038885037 0.552815380886 55.2238045805 # 2 -13.9261201547 0.462771154733 47.2081766576 # 2 -14.5137553558 0.382974377398 62.1392302623 # 2 -15.2319313936 0.664623912597 159.251769113 # 2 diff --git a/doc/examples/output/known_dG_models.dat b/doc/examples/output/known_dG_models.dat deleted file mode 100644 index 5fe1270..0000000 --- a/doc/examples/output/known_dG_models.dat +++ /dev/null @@ -1,5282 +0,0 @@ -(lp1 -(lp2 -(lp3 -cnumpy.core.multiarray -scalar -p4 -(cnumpy -dtype -p5 -(S'f8' -I0 -I1 -tRp6 -(I3 -S'<' -NNNI-1 -I-1 -I0 -tbS'\xa6W\x13\x9a\x85\x86\xca?' -tRp7 -accopy_reg -_reconstructor -p8 -(cdiffpy.srmise.peaks.base -Peaks -p9 -c__builtin__ -list -p10 -(lp11 -g8 -(cdiffpy.srmise.peaks.base -Peak -p12 -c__builtin__ -object -p13 -NtRp14 -(dp15 -S'_owner' -p16 -g8 -(cdiffpy.srmise.peaks.terminationripples -TerminationRipples -p17 -g13 -NtRp18 -(dp19 -S'supersample' -p20 -F5 -sS'metadict' -p21 -(dp22 -g20 -(F5 -c__builtin__ -repr -p23 -tp24 -sS'qmax' -p25 -(F30 -g23 -tp26 -sS'extension' -p27 -(F4 -g23 -tp28 -ssg27 -F4 -sS'npars' -p29 -I3 -sg25 -F30 -sS'base' -p30 -g8 -(cdiffpy.srmise.peaks.gaussianoverr -GaussianOverR -p31 -g13 -NtRp32 -(dp33 -g21 -(dp34 -S'maxwidth' -p35 -(F0.69999999999999996 -g23 -tp36 -ssg35 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-tRp134 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp135 -(dp136 -g16 -g111 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp137 -(I1 -(I3 -tg6 -I00 -S'\x82\xacj\x9d\xb7\x9a*@\xc1-rmHc\xd2?U\x8e\xfeI\xde\xf4K@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp138 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp139 -(dp140 -g16 -g111 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp141 -(I1 -(I3 -tg6 -I00 -S'\xf7`\xb1V\xac\xda+@\xda%\rP8k\xc0\xbf\\\xa3Wg%\x83G@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp142 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp143 -(dp144 -g16 -g111 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp145 -(I1 -(I3 -tg6 -I00 -S'_\x91\xc1\x93\xf1\x06-@\xacJ\xa56\xc8\x87\xda\xbf\x1d\x145\x05_\xfbN@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp146 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp147 -(dp148 -g16 -g111 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp149 -(I1 -(I3 -tg6 -I00 -S'\x9f\x8f\xc6?\xacz.@\xdd\x06w!\xb0B\xf0?\xe9hZ\xedAud@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp150 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp151 -a(dp152 -g60 -g61 -(g62 -(I0 -tS'b' -tRp153 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp154 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp155 -aa(lp156 -g4 -(g6 -S'`\x9c}R\xa0\xd4\xcf?' -tRp157 -ag8 -(g9 -g10 -(lp158 -g8 -(g12 -g13 -NtRp159 -(dp160 -g16 -g8 -(g17 -g13 -NtRp161 -(dp162 -g20 -F5 -sg21 -(dp163 -g20 -(F5 -g23 -tp164 -sg25 -(F30 -g23 -tp165 -sg27 -(F4 -g23 -tp166 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp167 -(I1 -(I3 -tg6 -I00 -S'z\x88\xc8r\x8d\x81&@N\xfd\x96f\xa8M\xde\xbf\xfa^\xff\x91u\x8bA@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp168 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp169 -(dp170 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp171 -(I1 -(I3 -tg6 -I00 -S"\xe0\xdc\x87\xf4B5'@\xe1\xd7\xad\xec\xe1\xd7\xeb\xbf\xeb.8\x19\x90\x8a\x16@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp172 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp173 -(dp174 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp175 -(I1 -(I3 -tg6 -I00 -S"\x9e%\x97\x03\x8a\xf6'@\x1e\n\xcc\xc1!\xff\xd6\xbf$\xf8C\xd6#\xc4D@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp176 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp177 -(dp178 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp179 -(I1 -(I3 -tg6 -I00 -S'\x1e.ZRm#@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp180 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp181 -(dp182 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp183 -(I1 -(I3 -tg6 -I00 -S'\xab\xd9\x11E\xf0J)@\x95\xb1\xed\x0e3\x9c\xd1\xbf3\xf7\xb5\xf4\xfc\xacM@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp184 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp185 -(dp186 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp187 -(I1 -(I3 -tg6 -I00 -S'\xe1:\xfc}\xb4\x9a*@\xf7\xdc\x81M\x1a"\xd2?9\x96:\xda\x7f\xeaK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp188 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp189 -(dp190 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp191 -(I1 -(I3 -tg6 -I00 -S'\x88\x12\x01;\xa2\xda+@\x90\xcd5\x00\xa4(\xc0\xbf\x1a`T\\}\x8bG@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp192 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp193 -(dp194 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp195 -(I1 -(I3 -tg6 -I00 -S'y\x93\x9b\xf3\xaf\x06-@%\xea\x8f\xd4Z\xb3\xda\xbf\xa4r\xe8\xa8\xd2\xc8N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp196 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp197 -(dp198 -g16 -g161 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp199 -(I1 -(I3 -tg6 -I00 -S'\xf1\xaa"\xc9\n\x85.@\x83yVE\xf2v\xf5?\x93\xd22\xcd_\xf2e@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp200 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp201 -a(dp202 -g60 -g61 -(g62 -(I0 -tS'b' -tRp203 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp204 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp205 -aa(lp206 -g4 -(g6 -S'__Y\xd7\xd6=\xd1?' -tRp207 -ag8 -(g9 -g10 -(lp208 -g8 -(g12 -g13 -NtRp209 -(dp210 -g16 -g8 -(g17 -g13 -NtRp211 -(dp212 -g20 -F5 -sg21 -(dp213 -g20 -(F5 -g23 -tp214 -sg25 -(F30 -g23 -tp215 -sg27 -(F4 -g23 -tp216 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp217 -(I1 -(I3 -tg6 -I00 -S'm\x85\xc5r\x8d\x81&@\xf3\x8e\xc2g\xa8M\xde\xbf\x98\n|\x91u\x8bA@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp218 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp219 -(dp220 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp221 -(I1 -(I3 -tg6 -I00 -S"\xb1\x13\xe3\xf4B5'@JU\x9f\xd0\xe1\xd7\xeb\xbf!\xdd\xc1Y\x90\x8a\x16@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp222 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp223 -(dp224 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp225 -(I1 -(I3 -tg6 -I00 -S'5\xd7t\x03\x8a\xf6\'@\xfc\t:""\xff\xd6\xbf\xd8\xe7\xb7\xc0#\xc4D@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp226 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp227 -(dp228 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp229 -(I1 -(I3 -tg6 -I00 -S'8\xfc\x8f\x86\xee\x9a(@\x83\xc7\xeb\x02\xe0P\xec\xbf\xa2\x15]\x95Rm#@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp230 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp231 -(dp232 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp233 -(I1 -(I3 -tg6 -I00 -S'=\x86\x0fE\xf0J)@\xb88\xe8\x153\x9c\xd1\xbf\xa1\x93\x17\xf2\xfc\xacM@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp234 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp235 -(dp236 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp237 -(I1 -(I3 -tg6 -I00 -S'\x85\x0b\x02~\xb4\x9a*@\xdat\x04j\x1a"\xd2?\x1c\x14\xc4\xde\x7f\xeaK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp238 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp239 -(dp240 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp241 -(I1 -(I3 -tg6 -I00 -S'\x00x\x02;\xa2\xda+@n^\x11*\xa4(\xc0\xbfC\x86~W}\x8bG@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp242 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp243 -(dp244 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp245 -(I1 -(I3 -tg6 -I00 -S'\xea\xa1\xda\xf3\xaf\x06-@~3\\\xabZ\xb3\xda\xbfe\xa8P\xdb\xd2\xc8N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp246 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp247 -(dp248 -g16 -g211 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp249 -(I1 -(I3 -tg6 -I00 -S'\x7fBA\xbd\n\x85.@uj\xc6\xa8\xe8v\xf5?\\\xa6N\x0e^\xf2e@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp250 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp251 -a(dp252 -g60 -g61 -(g62 -(I0 -tS'b' -tRp253 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp254 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp255 -aa(lp256 -g4 -(g6 -S'\x8e\xf0s\x85]\x91\xd2?' -tRp257 -ag8 -(g9 -g10 -(lp258 -g8 -(g12 -g13 -NtRp259 -(dp260 -g16 -g8 -(g17 -g13 -NtRp261 -(dp262 -g20 -F5 -sg21 -(dp263 -g20 -(F5 -g23 -tp264 -sg25 -(F30 -g23 -tp265 -sg27 -(F4 -g23 -tp266 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp267 -(I1 -(I3 -tg6 -I00 -S'X?\xc3r\x8d\x81&@\x0e\n\xa5h\xa8M\xde\xbf\xe1\xe3\x18\x91u\x8bA@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp268 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp269 -(dp270 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp271 -(I1 -(I3 -tg6 -I00 -S"\x95\xcf'\xf5B5'@w\xb9x\xbb\xe1\xd7\xeb\xbf\xe7\x02g\x8a\x90\x8a\x16@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp272 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp273 -(dp274 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp275 -(I1 -(I3 -tg6 -I00 -S'\x0c\xfcZ\x03\x8a\xf6\'@\x04\x9c\xe6j"\xff\xd6\xbf/\x9dz\xb0#\xc4D@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp276 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp277 -(dp278 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp279 -(I1 -(I3 -tg6 -I00 -S'\x9d\x82V\x86\xee\x9a(@\x8c\x8b+\xf1\xdfP\xec\xbft\x8b\xfa\xc1Rm#@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp280 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp281 -(dp282 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp283 -(I1 -(I3 -tg6 -I00 -S'\xf7\xc7\rE\xf0J)@\xec\x9e,\x1b3\x9c\xd1\xbf\xd3\xab\x1d\xf0\xfc\xacM@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp284 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp285 -(dp286 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp287 -(I1 -(I3 -tg6 -I00 -S'\xb9l\x06~\xb4\x9a*@\xb9s\x80\x7f\x1a"\xd2?\xb0]/\xe2\x7f\xeaK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp288 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp289 -(dp290 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp291 -(I1 -(I3 -tg6 -I00 -S'\xa3\x85\x03;\xa2\xda+@\xc2\x19\x9bI\xa4(\xc0\xbf2\xd3\xd9S}\x8bG@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp292 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp293 -(dp294 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp295 -(I1 -(I3 -tg6 -I00 -S'C(\n\xf4\xaf\x06-@\x0f\xa6O\x8cZ\xb3\xda\xbf|\xd3M\x01\xd3\xc8N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp296 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp297 -(dp298 -g16 -g261 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp299 -(I1 -(I3 -tg6 -I00 -S'\x89(M\xb4\n\x85.@\x18\xceqj\xe1v\xf5?\xe1r\x84\xbd\\\xf2e@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp300 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp301 -a(dp302 -g60 -g61 -(g62 -(I0 -tS'b' -tRp303 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp304 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp305 -aa(lp306 -g4 -(g6 -S'\xbc\x81\x8e3\xe4\xe4\xd3?' -tRp307 -ag8 -(g9 -g10 -(lp308 -g8 -(g12 -g13 -NtRp309 -(dp310 -g16 -g8 -(g17 -g13 -NtRp311 -(dp312 -g20 -F5 -sg21 -(dp313 -g20 -(F5 -g23 -tp314 -sg25 -(F30 -g23 -tp315 -sg27 -(F4 -g23 -tp316 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp317 -(I1 -(I3 -tg6 -I00 -S'#O\x04\rT\x80&@\xcd\xae\xf1\xee:3\xdd\xbf\xad&\xc2\x91\xfb-A@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp318 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp319 -(dp320 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp321 -(I1 -(I3 -tg6 -I00 -S"\xb55\x1f\xa0\xd9\xe9'@\xa0\xb1mst\xe5\xf0\xbfQ\xc5\xa6\xa5m|\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp322 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp323 -(dp324 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp325 -(I1 -(I3 -tg6 -I00 -S'\xcf\xc2\xe1b\xd8\x18(@\x96\x97\xba\x1d>\x1d\xf9?M\xb2\x11h\xd1\xe7M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp326 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp327 -(dp328 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp329 -(I1 -(I3 -tg6 -I00 -S'\x1a\xd2 \xc7gS)@B\xf7}^M\x05\xd3\xbf\xe2\xad"\xb6J\xb6J@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp330 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp331 -(dp332 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp333 -(I1 -(I3 -tg6 -I00 -S'\x12\x9bI,\xcf\x9b*@x\x13c\xad\xf7\x82\xd0?F\x14\xc6\xbd\xaf\xaeK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp334 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp335 -(dp336 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp337 -(I1 -(I3 -tg6 -I00 -S'\x9c\xc8\x03;\xa2\xda+@r1oQ\xa4(\xc0\xbfkM\xf2R}\x8bG@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp338 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp339 -(dp340 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp341 -(I1 -(I3 -tg6 -I00 -S'\xa8\xf4\x15\xf4\xaf\x06-@\xa0}\x9a\x84Z\xb3\xda\xbf\x08\x1c\xbc\n\xd3\xc8N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp342 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp343 -(dp344 -g16 -g311 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp345 -(I1 -(I3 -tg6 -I00 -S'\x9c%\x14\xb2\n\x85.@)\x08\x1d\x9e\xdfv\xf5?[\xef\xe8i\\\xf2e@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp346 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp347 -a(dp348 -g60 -g61 -(g62 -(I0 -tS'b' -tRp349 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp350 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp351 -aa(lp352 -g4 -(g6 -S'\xeb\x12\xa9\xe1j8\xd5?' -tRp353 -ag8 -(g9 -g10 -(lp354 -g8 -(g12 -g13 -NtRp355 -(dp356 -g16 -g8 -(g17 -g13 -NtRp357 -(dp358 -g20 -F5 -sg21 -(dp359 -g20 -(F5 -g23 -tp360 -sg25 -(F30 -g23 -tp361 -sg27 -(F4 -g23 -tp362 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp363 -(I1 -(I3 -tg6 -I00 -S'T\xa1\x0c\rT\x80&@k\xdcq\xe4:3\xdd\xbf\x9aM\xf6\x93\xfb-A@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp364 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp365 -(dp366 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp367 -(I1 -(I3 -tg6 -I00 -S"\x03\xb0C\xa0\xd9\xe9'@\xb0\x87\xecYt\xe5\xf0\xbf\x91\xba\x8e\xe0m|\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp368 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp369 -(dp370 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp371 -(I1 -(I3 -tg6 -I00 -S'\xf1o\x91b\xd8\x18(@\xc3\xa5\x1d\xe1?\x1d\xf9?\x12\x1a\x15P\xd1\xe7M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp372 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp373 -(dp374 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp375 -(I1 -(I3 -tg6 -I00 -S'\xa4Z\x13\xc7gS)@\xc4\xa4\xca\x1bM\x05\xd3\xbf\xa60\xff\xcdJ\xb6J@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp376 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp377 -(dp378 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp379 -(I1 -(I3 -tg6 -I00 -S'X\xefZ,\xcf\x9b*@\xd1\xfa\xedR\xf7\x82\xd0?\x19]\x1b\xaf\xaf\xaeK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp380 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp381 -(dp382 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp383 -(I1 -(I3 -tg6 -I00 -S'\xfa\n\x01;\xa2\xda+@\x82mS\xff\xa3(\xc0\xbf\xa2\x86n\\}\x8bG@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp384 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp385 -(dp386 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp387 -(I1 -(I3 -tg6 -I00 -S'\x98>\x9a\xf3\xaf\x06-@\xdc\xaen\xd5Z\xb3\xda\xbfv\xef\xd7\xa7\xd2\xc8N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp388 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp389 -(dp390 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp391 -(I1 -(I3 -tg6 -I00 -S'w\xe5b\xc9\n\x85.@\xa2\xc2Ly\xf2v\xf5?N\xd3\xa2\xd6_\xf2e@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp392 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp393 -a(dp394 -g60 -g61 -(g62 -(I0 -tS'b' -tRp395 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp396 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp397 -aa(lp398 -g4 -(g6 -S'\x1a\xa4\xc3\x8f\xf1\x8b\xd6?' -tRp399 -ag8 -(g9 -g10 -(lp400 -g8 -(g12 -g13 -NtRp401 -(dp402 -g16 -g8 -(g17 -g13 -NtRp403 -(dp404 -g20 -F5 -sg21 -(dp405 -g20 -(F5 -g23 -tp406 -sg25 -(F30 -g23 -tp407 -sg27 -(F4 -g23 -tp408 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp409 -(I1 -(I3 -tg6 -I00 -S'\x1c\x1a\n\rT\x80&@M\xbb\xa2\xe7:3\xdd\xbfk\xe2J\x93\xfb-A@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp410 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp411 -(dp412 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp413 -(I1 -(I3 -tg6 -I00 -S"\x90\x978\xa0\xd9\xe9'@\xe4\xc6\xadat\xe5\xf0\xbf\xce\x9d\xa4\xcem|\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp414 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp415 -(dp416 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp417 -(I1 -(I3 -tg6 -I00 -S'\x11\xdc\xa9b\xd8\x18(@\x8d\xd1\xeaW?\x1d\xf9?(\x1a`W\xd1\xe7M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp418 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp419 -(dp420 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp421 -(I1 -(I3 -tg6 -I00 -S'ir\x17\xc7gS)@\xcf*\x130M\x05\xd3\xbfT\xd7\xbd\xc6J\xb6J@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp422 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp423 -(dp424 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp425 -(I1 -(I3 -tg6 -I00 -S'*\xa9U,\xcf\x9b*@\xe1/on\xf7\x82\xd0?\xb7\x03\x91\xb3\xaf\xaeK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp426 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp427 -(dp428 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp429 -(I1 -(I3 -tg6 -I00 -S'\x13\xe0\x01;\xa2\xda+@\x8b\xeaH\x18\xa4(\xc0\xbf\xbcl\x8cY}\x8bG@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp430 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp431 -(dp432 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp433 -(I1 -(I3 -tg6 -I00 -S'8\xd7\xbf\xf3\xaf\x06-@.\x92\xdd\xbcZ\xb3\xda\xbf\x13\xf2\xe5\xc5\xd2\xc8N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp434 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp435 -(dp436 -g16 -g403 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp437 -(I1 -(I3 -tg6 -I00 -S'\xdczM\xc2\n\x85.@F\xf53\xbe\xecv\xf5?%\x1f.\xcc^\xf2e@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp438 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp439 -a(dp440 -g60 -g61 -(g62 -(I0 -tS'b' -tRp441 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp442 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp443 -aa(lp444 -g4 -(g6 -S'H5\xde=x\xdf\xd7?' -tRp445 -ag8 -(g9 -g10 -(lp446 -g8 -(g12 -g13 -NtRp447 -(dp448 -g16 -g8 -(g17 -g13 -NtRp449 -(dp450 -g20 -F5 -sg21 -(dp451 -g20 -(F5 -g23 -tp452 -sg25 -(F30 -g23 -tp453 -sg27 -(F4 -g23 -tp454 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp455 -(I1 -(I3 -tg6 -I00 -S"h\x1a3fR\x80&@&\xbb~t\x894\xdd\xbf>\xab\xc1'\xa8-A@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp456 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp457 -(dp458 -g16 -g449 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp459 -(I1 -(I3 -tg6 -I00 -S"\x9e\xd4\xd40\xdf\xe9'@\xf3\xf3\xee:\xe6\xe6\xf0\xbf^R7\r\xa3z\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp460 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp461 -(dp462 -g16 -g449 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp463 -(I1 -(I3 -tg6 -I00 -S'\xf1\x0b"\xd0\xcd\x18(@\x1f\xbb\xd6/\xe8\x1d\xf9?\x0fU\xd5nX\xe7M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp464 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp465 -(dp466 -g16 -g449 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp467 -(I1 -(I3 -tg6 -I00 -S'\x90\x85W\xd4tS)@F\x8es\xa0L\xf9\xd2\xbf\xc1\x8c\xb7\x0e\x13\xbcJ@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp468 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp469 -(dp470 -g16 -g449 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp471 -(I1 -(I3 -tg6 -I00 -S'\xf6O"F\x97\x9b*@\x94TM\x8e\xbd\xfe\xcf?{\x0e\xe5\xa0\xa5\x9cK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp472 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp473 -(dp474 -g16 -g449 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp475 -(I1 -(I3 -tg6 -I00 -S'\x9eE\x9b\xef\xd4\xed?OZ\x19~\x0e\xe8c@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp484 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp485 -a(dp486 -g60 -g61 -(g62 -(I0 -tS'b' -tRp487 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp488 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp489 -aa(lp490 -g4 -(g6 -S'v\xc6\xf8\xeb\xfe2\xd9?' -tRp491 -ag8 -(g9 -g10 -(lp492 -g8 -(g12 -g13 -NtRp493 -(dp494 -g16 -g8 -(g17 -g13 -NtRp495 -(dp496 -g20 -F5 -sg21 -(dp497 -g20 -(F5 -g23 -tp498 -sg25 -(F30 -g23 -tp499 -sg27 -(F4 -g23 -tp500 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp501 -(I1 -(I3 -tg6 -I00 -S'\xc4\x90;\x00T\x80&@\xaa2;\x89\x0e3\xdd\xbfa\t\xc1 \x00.A@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp502 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp503 -(dp504 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp505 -(I1 -(I3 -tg6 -I00 -S"s\x14=\xf5\xd9\xe9'@De\x98\xac\x93\xe5\xf0\xbf\xfc\xa9\x15\xecs|\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp506 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp507 -(dp508 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp509 -(I1 -(I3 -tg6 -I00 -S'\xb2\xb2h~\xd7\x18(@\xd4&\x11\xa80\x1c\xf9?{.\xb66\xb5\xe7M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp510 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp511 -(dp512 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp513 -(I1 -(I3 -tg6 -I00 -S'\xed\tY\xd7dS)@Y\x83\x1b\x8cn\x06\xd3\xbf\x9e\xd6#\x11\xad\xb5J@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp514 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp515 -(dp516 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp517 -(I1 -(I3 -tg6 -I00 -S'\x0f\x07)\xae\xd6\x9b*@t\xdaZ\t\xc9\x94\xd0?\x1eRZzy\xb1K@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp518 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp519 -(dp520 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp521 -(I1 -(I3 -tg6 -I00 -S'\r\x13\xf9\xd9\xa8\xda+@Z\x9b\xbc \x03>\xc0\xbf$\x18\xfcB\x93\x88G@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp522 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp523 -(dp524 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp525 -(I1 -(I3 -tg6 -I00 -S'\x8c\xa2b\x8d\xbc\x06-@X\xbbSn\x80\xaa\xda\xbfZ\xa8\x1f\x10n\xd3N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp526 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp527 -(dp528 -g16 -g495 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp529 -(I1 -(I3 -tg6 -I00 -S'\x84\x04cD\xb5\x82.@\x00\xa0:LM\xe0\xf3?4\xfd\x86\\7\x9be@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp530 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp531 -a(dp532 -g60 -g61 -(g62 -(I0 -tS'b' -tRp533 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp534 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp535 -aa(lp536 -g4 -(g6 -S'\xa5W\x13\x9a\x85\x86\xda?' -tRp537 -ag8 -(g9 -g10 -(lp538 -g8 -(g12 -g13 -NtRp539 -(dp540 -g16 -g8 -(g17 -g13 -NtRp541 -(dp542 -g20 -F5 -sg21 -(dp543 -g20 -(F5 -g23 -tp544 -sg25 -(F30 -g23 -tp545 -sg27 -(F4 -g23 -tp546 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp547 -(I1 -(I3 -tg6 -I00 -S"\x03\xbb\x82\rP\x80&@C\x07\xb2 S6\xdd\xbf'\xedc//-A@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp548 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp549 -(dp550 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp551 -(I1 -(I3 -tg6 -I00 -S"\xf8Q\x1a\x88\xe9\xe9'@<~\x02\xcdK\xea\xf0\xbfDw\xca\xf9%u\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp552 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp553 -(dp554 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp555 -(I1 -(I3 -tg6 -I00 -S't\xc9\x06\x02\xbb\x18(@\xf6 \x13\x15"\x04\xf9?.\n7\xef\xb4\xe6M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp556 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp557 -(dp558 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp559 -(I1 -(I3 -tg6 -I00 -S'.\xb8[\x00gS)@\x81O\xf7Jl\xf2\xd2\xbf\xee\xee\xe4l\x8d\xbbJ@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp560 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp561 -(dp562 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp563 -(I1 -(I3 -tg6 -I00 -S'\xeb/\x9bv\xeb\x9b*@>\xd3\x11\xc2S\x81\xd0?\x14\xa7\xfa\xfa\xfc\xaeK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp564 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp565 -(dp566 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp567 -(I1 -(I3 -tg6 -I00 -S'/a\xdc\x90\x9f\xda+@\x9c\xb0\x0c\x1e\xb8_\xc0\xbf\xe6\xe3\xf0C3\x85G@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp568 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp569 -(dp570 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp571 -(I1 -(I3 -tg6 -I00 -S"6\x8fC\xff\x10\x07-@'{q\x91?w\xda\xbf>%B?Y\x0fO@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp572 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp573 -(dp574 -g16 -g541 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp575 -(I1 -(I3 -tg6 -I00 -S'\xcdW\xe9\x93\xbfv.@\xeb\x9cL\xb8\xb7\xd1\xed?\xdd\x97\x99/\r\xe9c@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp576 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp577 -a(dp578 -g60 -g61 -(g62 -(I0 -tS'b' -tRp579 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp580 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp581 -aa(lp582 -g4 -(g6 -S'\xd4\xe8-H\x0c\xda\xdb?' -tRp583 -ag8 -(g9 -g10 -(lp584 -g8 -(g12 -g13 -NtRp585 -(dp586 -g16 -g8 -(g17 -g13 -NtRp587 -(dp588 -g20 -F5 -sg21 -(dp589 -g20 -(F5 -g23 -tp590 -sg25 -(F30 -g23 -tp591 -sg27 -(F4 -g23 -tp592 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp593 -(I1 -(I3 -tg6 -I00 -S'\x01\xbb\x82\rP\x80&@<\t\xb2 S6\xdd\xbf\xbd\xecc//-A@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp594 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp595 -(dp596 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp597 -(I1 -(I3 -tg6 -I00 -S"\xf8Q\x1a\x88\xe9\xe9'@\x0c\x87\x02\xcdK\xea\xf0\xbf\xe7`\xca\xf9%u\x10@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp598 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp599 -(dp600 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp601 -(I1 -(I3 -tg6 -I00 -S's\xc9\x06\x02\xbb\x18(@w7\x13\x15"\x04\xf9?\x93\x0e7\xef\xb4\xe6M@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp602 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp603 -(dp604 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp605 -(I1 -(I3 -tg6 -I00 -S'/\xb8[\x00gS)@$W\xf7Jl\xf2\xd2\xbf\xa3\xec\xe4l\x8d\xbbJ@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp606 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp607 -(dp608 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp609 -(I1 -(I3 -tg6 -I00 -S'\xe6/\x9bv\xeb\x9b*@\x88\xdb\x11\xc2S\x81\xd0?U\xa8\xfa\xfa\xfc\xaeK@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp610 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp611 -(dp612 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp613 -(I1 -(I3 -tg6 -I00 -S'0a\xdc\x90\x9f\xda+@4\xb0\x0c\x1e\xb8_\xc0\xbf\xeb\xe3\xf0C3\x85G@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp614 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp615 -(dp616 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp617 -(I1 -(I3 -tg6 -I00 -S'7\x8fC\xff\x10\x07-@\x01{q\x91?w\xda\xbfm%B?Y\x0fO@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp618 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp619 -(dp620 -g16 -g587 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp621 -(I1 -(I3 -tg6 -I00 -S'\xc6W\xe9\x93\xbfv.@\xad\x97L\xb8\xb7\xd1\xed?\xdd\x96\x99/\r\xe9c@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp622 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp623 -a(dp624 -g60 -g61 -(g62 -(I0 -tS'b' -tRp625 -(I1 -(I2 -tg6 -I00 -S"\x89>\xd8\xf8XU\xe0\xbf\xec\x01'\xa1\xea7\x81?" -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp626 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp627 -aa(lp628 -g4 -(g6 -S'\x02zH\xf6\x92-\xdd?' -tRp629 -ag8 -(g9 -g10 -(lp630 -g8 -(g12 -g13 -NtRp631 -(dp632 -g16 -g8 -(g17 -g13 -NtRp633 -(dp634 -g20 -F5 -sg21 -(dp635 -g20 -(F5 -g23 -tp636 -sg25 -(F30 -g23 -tp637 -sg27 -(F4 -g23 -tp638 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp639 -(I1 -(I3 -tg6 -I00 -S'\xbcIF\xa5\xc3\x83&@r\xc7f\x1eRb\xdc\xbf\xa6\x8c\x1c\x81QMA@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp640 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp641 -(dp642 -g16 -g633 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp643 -(I1 -(I3 -tg6 -I00 -S'[\x11\x8dOv\x04(@\xc25I\xf5\x1e2\xd4?\xae\x9d\xbe\x08\x903K@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp644 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp645 -(dp646 -g16 -g633 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp647 -(I1 -(I3 -tg6 -I00 -S'\xcf\xd4\xdcVeM)@\xe6krZz\xc6\xc5\xbf\x970\xaa\xfc\xd19N@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp648 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp649 -(dp650 -g16 -g633 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp651 -(I1 -(I3 -tg6 -I00 -S'\xb8\xf4=\xb6\xfc\x9b*@\x99I\x90\xed\xdc\xfc\xb1?\x82|\xb7\x95\x1e\xf0H@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp652 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp653 -(dp654 -g16 -g633 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp655 -(I1 -(I3 -tg6 -I00 -S"\xa1\x98}\xeb\xbb\xd6+@|bR/\xfb\xee\xb2\xbf\xc8\x02\x11'\x19\xd4G@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp656 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp657 -(dp658 -g16 -g633 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp659 -(I1 -(I3 -tg6 -I00 -S'\xd1\x12\xf5\x95\\\x07-@d\x82\x16\\\x16\xd4\xdb\xbfh\x9bA0\x88\xeeM@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp660 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp661 -(dp662 -g16 -g633 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp663 -(I1 -(I3 -tg6 -I00 -S'\xb6C\x1c\xfa\xbfz.@\x9f\x97\xa1cHR\xf0?_\x90\xf0\x1c\xb2\x10d@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp664 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp665 -a(dp666 -g60 -g61 -(g62 -(I0 -tS'b' -tRp667 -(I1 -(I2 -tg6 -I00 -S'\xc4\x12+\xe7x\xbe\xdf\xbf3^\xc2\xfe\x1d8\x83?' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp668 -(I1 -(I2 -tg67 -I00 -S'\x01\x01' -tbsg68 -I00 -sag4 -(g6 -S'\x00\xec{\xf3\xe9\xce\xba?' -tRp669 -aa(lp670 -g4 -(g6 -S'1\x0bc\xa4\x19\x81\xde?' -tRp671 -ag8 -(g9 -g10 -(lp672 -g8 -(g12 -g13 -NtRp673 -(dp674 -g16 -g8 -(g17 -g13 -NtRp675 -(dp676 -g20 -F5 -sg21 -(dp677 -g20 -(F5 -g23 -tp678 -sg25 -(F30 -g23 -tp679 -sg27 -(F4 -g23 -tp680 -ssg27 -F4 -sg29 -I3 -sg25 -F30 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp681 -(I1 -(I3 -tg6 -I00 -S'\x96\x8ahK\xc2\x83&@F\x88O\x02\xe1[\xdc\xbf\x1bA\x1f\xbc\xe3OA@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp682 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp683 -(dp684 -g16 -g675 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp685 -(I1 -(I3 -tg6 -I00 -S'\xaaV\xb2\xb1u\x04(@\xde\x19K0\xab8\xd4?s\xe9_\xc7\x197K@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp686 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp687 -(dp688 -g16 -g675 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp689 -(I1 -(I3 -tg6 -I00 -S'\x9f\xe0\xa6\x06fM)@^cypU\xc2\xc5\xbf\xe0\x8e\xcfqK\xe7\xde\xf7V@' -tRp21 -ag2 -(g4 -S'\xda\xd3\x1b\x81\x13\xf6V@' -tRp22 -ag2 -(g4 -S'&\x14\x17k\x00;Y@' -tRp23 -ag2 -(g4 -S'i\xe5\xbe\x1c\xd9][@' -tRp24 -ag2 -(g4 -S'\xc2/\xe9\xe0\x1a\xf2V@' -tRp25 -ag2 -(g4 -S'\xe5\x18\xb2*\x92r`@' -tRp26 -asg2 -(g4 -S'\x17b\xfe\xf8V}\xb1@' -tRp27 -(lp28 -g2 -(g4 -S'\xad\xc1\xe3y$MZ@' -tRp29 -ag2 -(g4 -S'D\x93~\xaa\xc3\xc1h@' -tRp30 -ag2 -(g4 -S'l\xde\x19S\xd5\x08c@' -tRp31 -ag2 -(g4 -S'\\\x87\x83\xc1\xfa\xf3X@' -tRp32 -ag2 -(g4 -S'I\xf4xA\xa6tg@' -tRp33 -ag2 -(g4 -S't\xd1T\x1e\xfaiW@' -tRp34 -ag2 -(g4 -S'\xb9\x8e\xea\x86\xe5\xd9W@' -tRp35 -ag2 -(g4 -S'\xe7\xf1\x94\xed+\x1eW@' -tRp36 -ag2 -(g4 -S'\xc2\xaa\xe6\xa6\xda\xbdW@' -tRp37 -ag2 -(g4 -S'\x88#\xf8A#\xf9W@' -tRp38 -ag2 -(g4 -S'\x9c\xa2\x06\xcb\x8c\x91X@' -tRp39 -ag2 -(g4 -S'a\x95\x0c\xc7\xdc~W@' -tRp40 -ag2 -(g4 -S'm\xf0\xbe\xf5\xae\xdfZ@' -tRp41 -ag2 -(g4 -S'\xe0\xab\x8c\xf8\x15\xd6Z@' -tRp42 -ag2 -(g4 -S'\xf8.zql\xb8Y@' -tRp43 -ag2 -(g4 -S'(o\xbe\x11Z\x8aZ@' -tRp44 -ag2 -(g4 -S'Z4\xf9\xba\x14\x11^@' -tRp45 -ag2 -(g4 -S'\x1a5\xf4\xf2\xc8\x1ba@' -tRp46 -ag2 -(g4 -S'\x84r\x9aH.\x84Z@' -tRp47 -ag2 -(g4 -S'q\xaeX\xd5nge@' -tRp48 -asg2 -(g4 -S'B\x1f2\xd9W\xd5\x9a@' -tRp49 -(lp50 -g2 -(g4 -S'\xf1\x17,\x02B\xd2c@' -tRp51 -ag2 -(g4 -S'\xec\x01\xc3\x0b\xc6\xc3\x89@' -tRp52 -ag2 -(g4 -S"O}\xbe'k\n\x80@" -tRp53 -ag2 -(g4 -S'\xda<\xcc{O\xefg@' -tRp54 -ag2 -(g4 -S'\xc5_\xd9Zrw\x86@' -tRp55 -ag2 -(g4 -S'\xe9\xf4N\x00d@' -tRp134 -ag2 -(g4 -S'\x9epUw\x10\x88]@' -tRp135 -ag2 -(g4 -S't\xb0q\xa2\xe9\x96i@' -tRp136 -asg2 -(g4 -S'\xfa6\xee\xb2\xac\xae\xc5@' -tRp137 -(lp138 -g2 -(g4 -S'\x9a3?\xe6\xd4_X@' -tRp139 -ag2 -(g4 -S'NG\xdal\xe6\xe4Z@' -tRp140 -ag2 -(g4 -S'>\xf9\x16\xf7Q\x08Y@' -tRp141 -ag2 -(g4 -S'6M<\x8e\x9c\xa4U@' -tRp142 -ag2 -(g4 -S'\xd7\x7fR\x10\x11\xba[@' -tRp143 -ag2 -(g4 -S'lqq\x9e\x85dU@' -tRp144 -ag2 -(g4 -S'p\xbc\x82\x8e05T@' -tRp145 -ag2 -(g4 -S'\x04W\x00^\xa7\x16T@' -tRp146 -ag2 -(g4 -S's\xdc]<\x17\xefR@' -tRp147 -ag2 -(g4 -S"\xdc.'\xe8\xbb\xf8R@" -tRp148 -ag2 -(g4 -S'\xde\x1f\xf9\x9c\x86\x11S@' -tRp149 -ag2 -(g4 -S"\xa3!i'\xd8\xe4R@" -tRp150 -ag2 -(g4 -S'\xb3\xd0\xcf1\xfb/R@' -tRp151 -ag2 -(g4 -S'\xd2H\x97\x88k.R@' -tRp152 -ag2 -(g4 -S'9\x8c\xab\xa7}AS@' -tRp153 -ag2 -(g4 -S'\xd7\x7f@\xd7\x19"R@' -tRp154 -ag2 -(g4 -S'\x81\x92>\x06\xf1\xb4R@' -tRp155 -ag2 -(g4 -S'\x8b\xd5cK; R@' -tRp156 -ag2 -(g4 -S'\xf3\xd5F\xde\x18!R@' -tRp157 -ag2 -(g4 -S'\xdf\xb7D\xbc\xf9\x85S@' -tRp158 -asg2 -(g4 -S'\x8f\x15\x08#\xadZ\xaa@' -tRp159 -(lp160 -g2 -(g4 -S'\n\x15\xfaS\xdd\r\\@' -tRp161 -ag2 -(g4 -S'n\xe1\xc4\xb4\xb0\x85q@' -tRp162 -ag2 -(g4 -S'\xe8*D8\xae\xf6h@' -tRp163 -ag2 -(g4 -S'\xb2\x08.\xb3\xc1\xf6[@' -tRp164 -ag2 -(g4 -S"\x8cQ\xf7\xb9'\x17p@" -tRp165 -ag2 -(g4 -S'C\xda98\xa9@Y@' -tRp166 -ag2 -(g4 -S'<\xe9\x11\x95L*[@' -tRp167 -ag2 -(g4 -S'\x87E*\xc6\x97\xdfY@' -tRp168 -ag2 -(g4 -S'f\x01\x18l_\x1d\\@' -tRp169 -ag2 -(g4 -S'\xc2\riU\xcf\x85\\@' -tRp170 -ag2 -(g4 -S'\xad\x9e\x0c\xb0N\x92]@' -tRp171 -ag2 -(g4 -S'Z\x9c\x9a:g\xae[@' -tRp172 -ag2 -(g4 -S'!su:2ca@' -tRp173 -ag2 -(g4 -S'\xd4\xe4#\x0c\xbeZa@' -tRp174 -ag2 -(g4 -S'Z\xfd\x9a\xb9\xc5\x99_@' -tRp175 -ag2 -(g4 -S'\xd6\xa3\xc4\xab\x08\x18a@' -tRp176 -ag2 -(g4 -S'\x90-\xbb{.3d@' -tRp177 -ag2 -(g4 -S'\x1b\xd9\x80\x8bImh@' -tRp178 -ag2 -(g4 -S"\xef\xa4h'\x99\x12a@" -tRp179 -ag2 -(g4 -S'U\xe39?|\xfeo@' -tRp180 -asg2 -(g4 -S'\xaa\xdfsK\xac^\xc1@' -tRp181 -(lp182 -g2 -(g4 -S'\xdb\x0b\xa5\xfbR\x95X@' -tRp183 -ag2 -(g4 -S'0\xf4X\xa0\xcfX]@' -tRp184 -ag2 -(g4 -S'\x8e\xd5\x1b-5rZ@' -tRp185 -ag2 -(g4 -S'\x0ewc\x1a\x7f\x00V@' -tRp186 -ag2 -(g4 -S'`p\xfd\x9f\x9e\xce]@' -tRp187 -ag2 -(g4 -S'\x00\xe8n\xef\xa1\x9cU@' -tRp188 -ag2 -(g4 -S'\x8f/\x03\x13T\x9aT@' -tRp189 -ag2 -(g4 -S'A\xc8!c\xbfjT@' -tRp190 -ag2 -(g4 -S'I\xf8\xe1\xa9\x8ctS@' -tRp191 -ag2 -(g4 -S',w T\x93\x83S@' -tRp192 -ag2 -(g4 -S'A\xd39\xb84\xaaS@' -tRp193 -ag2 -(g4 -S';\xf6\x93e\x95dS@' -tRp194 -ag2 -(g4 -S'L\n\xbd&\x1c!S@' -tRp195 -ag2 -(g4 -S'\xa02\x08g\xad\x1eS@' -tRp196 -ag2 -(g4 -S'<*\xff\xd4\xf1\xf4S@' -tRp197 -ag2 -(g4 -S'\x92\x07zW{\x0bS@' -tRp198 -ag2 -(g4 -S'U#\x95\xa5I\xf0S@' -tRp199 -ag2 -(g4 -S'\xdc(\x0f>\xea\xdeS@' -tRp200 -ag2 -(g4 -S'v/\xd0\xed\xea\tS@' -tRp201 -ag2 -(g4 -S'\xb2\xae\xa3SY\x0cV@' -tRp202 -asg2 -(g4 -S'@\xbe\x8d\xbb\xac\n\xa6@' -tRp203 -(lp204 -g2 -(g4 -S'\x80\xafz\xf6\xb6\xcb]@' -tRp205 -ag2 -(g4 -S'-r\xbf\x07\x12\xa2v@' -tRp206 -ag2 -(g4 -S'c\xa5j+\xd0\xdan@' -tRp207 -ag2 -(g4 -S'\xfe \xe9\xbf\x99\xf4^@' -tRp208 -ag2 -(g4 -S'h\xfd\xdfn\xd6lt@' -tRp209 -ag2 -(g4 -S'\x8d\xe0\xa7\x1eU\x14[@' -tRp210 -ag2 -(g4 -S'\xbe8t\x8eEu^@' -tRp211 -ag2 -(g4 -S'\xb8\x062\xcf\x7f\x9c\\@' -tRp212 -ag2 -(g4 -S'-t\xb5\xf2\xdc:`@' -tRp213 -ag2 -(g4 -S'\xec\xdb\xb5\x90\x83\x85`@' -tRp214 -ag2 -(g4 -S'\xaf%\xf6\x0coEa@' -tRp215 -ag2 -(g4 -S'\x12||\xfe\x15\xd7_@' -tRp216 -ag2 -(g4 -S'\x10\xb8i\xe7\x13Pe@' -tRp217 -ag2 -(g4 -S'5\x8cw\x06\xfeCe@' -tRp218 -ag2 -(g4 -S'\xf6\xbc\x17E\xbe\xb8b@' -tRp219 -ag2 -(g4 -S'\x9ee\xa3z\xa0\xe4d@' -tRp220 -ag2 -(g4 -S'\x12\x12\xcc~[Ui@' -tRp221 -ag2 -(g4 -S'\xf4Q8w\xcc\xb2o@' -tRp222 -ag2 -(g4 -S'(w;0\xdb\xdcd@' -tRp223 -ag2 -(g4 -S'*\x90\xc7\xd7\x17Bu@' -tRp224 -asg2 -(g4 -S'\xf0f\x13T\xac\xba\xa1@' -tRp225 -(lp226 -g2 -(g4 -S'0\x8b\t\x94\xa7z`@' -tRp227 -ag2 -(g4 -S'/\x0b\xb0\xa5\xe2\xe9\x7f@' -tRp228 -ag2 -(g4 -S'\xdc\x87\x11y\xac\xc6t@' -tRp229 -ag2 -(g4 -S'\xd6V\xba\x85\xa01b@' -tRp230 -ag2 -(g4 -S'VP\x05/\xd9K|@' -tRp231 -ag2 -(g4 -S'\xd5\xa0@\x1a\x8de^@' -tRp232 -ag2 -(g4 -S'J\xb8!H\xfd7b@' -tRp233 -ag2 -(g4 -S'\x16/d=\x9e\xca`@' -tRp234 -ag2 -(g4 -S'\x04\xb0\x7f!\xcb,d@' -tRp235 -ag2 -(g4 -S'|\xe18\x87-\xa0d@' -tRp236 -ag2 -(g4 -S't\xd8\x1a\xcb\xd1\xc8e@' -tRp237 -ag2 -(g4 -S'\x9aUG)1\xb2c@' -tRp238 -ag2 -(g4 -S'\x9f \x7fN\xc9pl@' -tRp239 -ag2 -(g4 -S'\xcaJ\xcb=\x1b^l@' -tRp240 -ag2 -(g4 -S'On(@\xbc\x06h@' -tRp241 -ag2 -(g4 -S'\xd0\xce\x12Z\xb4\xcak@' -tRp242 -ag2 -(g4 -S'4\xa0\x1a!\xd9Sq@' -tRp243 -ag2 -(g4 -S'S\x00\xa9\xc7\x81sv@' -tRp244 -ag2 -(g4 -S'\x17\n\xe7\x98\xb1\xbek@' -tRp245 -ag2 -(g4 -S'\xbdx.\x9d\xc3\xcf~@' -tRp246 -asg2 -(g4 -S'\xbe\x8d\xbb,W\xa5\xb3@' -tRp247 -(lp248 -g2 -(g4 -S'\xd4\xd6\xe2b\xea\xd2Y@' -tRp249 -ag2 -(g4 -S'^4\xfe\x80e\xf4e@' -tRp250 -ag2 -(g4 -S'\xf7\x1dkxcka@' -tRp251 -ag2 -(g4 -S'\xa6\xf0\x01D\x07"X@' -tRp252 -ag2 -(g4 -S'\xa4\t\x16\x999\x14e@' -tRp253 -ag2 -(g4 -S'R\xf7\x1f\x97\xc4\xe9V@' -tRp254 -ag2 -(g4 -S'\x93-\x1e\x18\xcd\xf2V@' -tRp255 -ag2 -(g4 -S'x_\x9d\xcd\x05^V@' -tRp256 -ag2 -(g4 -S'\xff\xa7k\xdf\xe8\x8cV@' -tRp257 -ag2 -(g4 -S'\xf1\xc7\x16\xda\xe4\xbbV@' -tRp258 -ag2 -(g4 -S'R\xb7T\x95\xaf4W@' -tRp259 -ag2 -(g4 -S'\x9a\xff\xce\x90\xfcZV@' -tRp260 -ag2 -(g4 -S'\x01\xec\x8dO\xb8\xb8X@' -tRp261 -ag2 -(g4 -S'U\xe6\x19\x10\x1d\xb1X@' -tRp262 -ag2 -(g4 -S'\x1ce\xd3 b\x1eX@' -tRp263 -ag2 -(g4 -S'\xa2\x94\xda|\x17uX@' -tRp264 -ag2 -(g4 -S'\x12@\xde\x14\x89@[@' -tRp265 -ag2 -(g4 -S'\xc2\x1acl\xed:^@' -tRp266 -ag2 -(g4 -S'i\xa2\x18t3pX@' -tRp267 -ag2 -(g4 -S'&\x05\xa0\xec\xf8\x84b@' -tRp268 -asg2 -(g4 -S'\xcd\xcc\xcc\xcc\xac\xc2\xc6@' -tRp269 -(lp270 -g2 -(g4 -S'z\xa9\xae\xc6\xf7VX@' -tRp271 -ag2 -(g4 -S'R\n\x00\xc9\xda|Z@' -tRp272 -ag2 -(g4 -S'\xfd\xe7\x8d\xe4Z\xccX@' -tRp273 -ag2 -(g4 -S'\xeex\x96\xd8b\x95U@' -tRp274 -ag2 -(g4 -S'\xd1\x9d\xeft\xd2a[@' -tRp275 -ag2 -(g4 -S'N\x15\xf8o9[U@' -tRp276 -ag2 -(g4 -S'i\x03qNn$T@' -tRp277 -ag2 -(g4 -S"\x16\xd8\x1e'\xb8\x08T@" -tRp278 -ag2 -(g4 -S'\x96\xbf\x88\xfd\xf9\xd8R@' -tRp279 -ag2 -(g4 -S'\xa9"\x91S\xba\xe1R@' -tRp280 -ag2 -(g4 -S'U\x08\xa2\x01:\xf8R@' -tRp281 -ag2 -(g4 -S'\xfe\x9b\x81\x86\xad\xcfR@' -tRp282 -ag2 -(g4 -S'F[\x19\xa5\x06\x08R@' -tRp283 -ag2 -(g4 -S'/\x82$\xf3\x9b\x06R@' -tRp284 -ag2 -(g4 -S'\r\xaecR\xc1#S@' -tRp285 -ag2 -(g4 -S'\xdb\x0b\xa8\xf3m\xfbQ@' -tRp286 -ag2 -(g4 -S'\xef\xd4\x106\xb0\x80R@' -tRp287 -ag2 -(g4 -S'\xfdZ{:7\xd6Q@' -tRp288 -ag2 -(g4 -S'/\xf8U\xbf\x84\xfaQ@' -tRp289 -ag2 -(g4 -S'Ur\x85\xed\xde\x1aS@' -tRp290 -asg2 -(g4 -S'~uRe\xacr\xc2@' -tRp291 -(lp292 -g2 -(g4 -S'\x80\xdb\x81ta\x84X@' -tRp293 -ag2 -(g4 -S'\xea\x87 q\xec\x91\\@' -tRp294 -ag2 -(g4 -S'[\xb7\x01\xef\x94\xffY@' -tRp295 -ag2 -(g4 -S'\x02\x963vd\xe3U@' -tRp296 -ag2 -(g4 -S'\\\xf5x\xb2\xef%]@' -tRp297 -ag2 -(g4 -S'\x0b2`\x1d\xdc\x8aU@' -tRp298 -ag2 -(g4 -S'8\x97\x03\x13KzT@' -tRp299 -ag2 -(g4 -S'\xe3\xb7u\x80\x1cPT@' -tRp300 -ag2 -(g4 -S'\xd5\xe0[\xf2FJS@' -tRp301 -ag2 -(g4 -S'\xb7\xe3\xb5#\x99WS@' -tRp302 -ag2 -(g4 -S'\xefRog\xd8yS@' -tRp303 -ag2 -(g4 -S'\x8e\x16\xe2s\x1f\xb6B\x87\xf6\xbf|)\x8e\xbc\x04\xff\xe0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp194 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp195 -(dp196 -g16 -g139 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp197 -(I1 -(I3 -tg6 -I00 -S'\x8f[\xcd\xb18\xa4\x1a@\x03\xff\x8a\xeb\x90A\xe1\xbftB\x91Q\xc8x\x00A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp198 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp199 -(dp200 -g16 -g139 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp201 -(I1 -(I3 -tg6 -I00 -S'\xdb\xed\xe2\xb0\xd4\x1a\x1c@\x90\xc2/\x83@\xcb\xef\xbf\xbbUD\x8ap\xa3\xe4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp202 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp203 -a(dp204 -g60 -g61 -(g62 -(I0 -tS'b' -tRp205 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp206 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S'0\xb2\x9d\xef\xa7\xc6\xc1?' -tRp207 -aa(lp208 -g4 -(g6 -S'\xf0f\x13T\xac\xba\xa1@' -tRp209 -ag8 -(g9 -g10 -(lp210 -g8 -(g12 -g13 -NtRp211 -(dp212 -g16 -g8 -(g17 -g13 -NtRp213 -(dp214 -g20 -F5 -sg21 -(dp215 -g20 -(F5 -g23 -tp216 -sg25 -(F21.299999 -g23 -tp217 -sg27 -(F4 -g23 -tp218 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp219 -(I1 -(I3 -tg6 -I00 -S'!\xdf\x92\x11j\x0e\xf6?<\x9a\xecd;\x08\xf5\xbf2\xadRXk\n\xce@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp220 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp221 -(dp222 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp223 -(I1 -(I3 -tg6 -I00 -S'~\xd9\xb2n%\xba\xf7?\xcb\xfc`\x97UU\xf7\xbf\xb4\xcd\x89\n\xc1a\xd8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp224 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp225 -(dp226 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp227 -(I1 -(I3 -tg6 -I00 -S'\xef\xa6o\x9d\xe5\x14\x02@\xf3\xf9\x90\x1fq\x87\xf7\xbf7\xb9\xe4\x0e\xd9(\xbb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp228 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp229 -(dp230 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp231 -(I1 -(I3 -tg6 -I00 -S'\xe9\x180\x95\x95\x94\x03@/\xd8\x8a\x90\tU\xf2\xbf\x85/<\xc5\xf51\xf0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp232 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp233 -(dp234 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp235 -(I1 -(I3 -tg6 -I00 -S'-\x97A\xb3)\xb4\x06@\xa7misXM\xf2\xbf\xc6\x00%\xcd\x08\xe3\xd6@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp236 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp237 -(dp238 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp239 -(I1 -(I3 -tg6 -I00 -S'\xe0\x08\xc3\xfd\xb1\xea\x0c@{\xe9G\xfc&\r\xf0\xbf0y\xb3\xc0?\xc2\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp240 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp241 -(dp242 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp243 -(I1 -(I3 -tg6 -I00 -S'S\x99\x7f/\x1dy\x10@\xf6\x16\t\xef(c\xeb\xbf6\xe9k=G!\xee@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp244 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp245 -(dp246 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp247 -(I1 -(I3 -tg6 -I00 -S'\xe0\xcaFN,\x12\x12@\x1c{\xcf<\xad\x04\xf6\xbft\xde\xfa\xcc\x0c\xe8\xe9@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp248 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp249 -(dp250 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp251 -(I1 -(I3 -tg6 -I00 -S'A!cC\xd4\xff\x12@#s\xc6\xc2\xe2\xbd\xea\xbf\x1c\x1ds\xf7\nR\xe7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp252 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp253 -(dp254 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp255 -(I1 -(I3 -tg6 -I00 -S'V\xb2\xaf\xf7<\x9c\x14@q\xc0\x1e-\x0b\x9c\xf0\xbf\xe8\xaf:\xdc\xe8\x1c\xd7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp256 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp257 -(dp258 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp259 -(I1 -(I3 -tg6 -I00 -S'\xab\xc4\x057h\xc5\x15@\xbf$\xb2\xa5B\xf4\xea\xbf\xc3S\x01\xe7\xb4\xed\xf7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp260 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp261 -(dp262 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp263 -(I1 -(I3 -tg6 -I00 -S'iV|X$(\x17@\xb1\x8e\x89\xdd\x19\xd4\xec\xbf\x02\xcd\xfd\xff\xf3:\xf0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp264 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp265 -(dp266 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp267 -(I1 -(I3 -tg6 -I00 -S'\xe5\xaeQ\x06\xb6w\x18@\xac\xabs\x01\xd4\x88\xed\xbf\x00=E\x0bq\x05\xf5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp268 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp269 -(dp270 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp271 -(I1 -(I3 -tg6 -I00 -S'\xc7x\xba\x8b\x9f\x96\x1a@A\xa7b\xfe\xa8L\xe2\xbf\xee\x1cLS\xbb3\x00A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp272 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp273 -(dp274 -g16 -g213 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp275 -(I1 -(I3 -tg6 -I00 -S'\x89\x85uz\xd1\x0f\x1c@\x10\x96\x15\x06m\x1e\xeb\xbf\x1b\xf1\x1f\xaf\xcc\x14\xe8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp276 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp277 -a(dp278 -g60 -g61 -(g62 -(I0 -tS'b' -tRp279 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp280 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S'0\xb2\x9d\xef\xa7\xc6\xc1?' -tRp281 -aa(lp282 -g4 -(g6 -S'@\xbe\x8d\xbb\xac\n\xa6@' -tRp283 -ag8 -(g9 -g10 -(lp284 -g8 -(g12 -g13 -NtRp285 -(dp286 -g16 -g8 -(g17 -g13 -NtRp287 -(dp288 -g20 -F5 -sg21 -(dp289 -g20 -(F5 -g23 -tp290 -sg25 -(F21.299999 -g23 -tp291 -sg27 -(F4 -g23 -tp292 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp293 -(I1 -(I3 -tg6 -I00 -S'\x16\x8b\x81\xe7\xa8\x0e\xf7?\x9b\xdf\xc3"\xe5\x1e\xf3\xbf\xb6\xa5\xcd\x94\xc1\x89\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp294 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp295 -(dp296 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp297 -(I1 -(I3 -tg6 -I00 -S'\x11\x02|<\xc6\x82\x03@tp\x85C\xddy\xee\xbf\xdd\x0b\x82\x0fR\xca\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp298 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp299 -(dp300 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp301 -(I1 -(I3 -tg6 -I00 -S'\xa0\t\xa0\xfa\xd5\xc1\x06@\x02&\x9f\t\xbe\xf0\xf7\xbf\x8d\xfcc\xfa_\xd4\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp302 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp303 -(dp304 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp305 -(I1 -(I3 -tg6 -I00 -S'\x9a\xcc\x96\xbe2\xed\x0c@\xcf?\xd1\x92v\x84\xed\xbf"m\x12)\xb8\x86\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp306 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp307 -(dp308 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp309 -(I1 -(I3 -tg6 -I00 -S'\xb8\xd6 .\x0e0\x10@3\x15\x9e\xdc\xc9|\xf7\xbff-\xe7W\xcb5\xda@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp310 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp311 -(dp312 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp313 -(I1 -(I3 -tg6 -I00 -S'\xe9\x05\x9f\x95\xec\xe4\x10@\xa0i\x999\xdc\x17\xf7\xbf\xdc\xa7\x8cw7&\xda@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp314 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp315 -(dp316 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp317 -(I1 -(I3 -tg6 -I00 -S'Q\xf8\xe5yz+\x12@/u,\xa7\xe4E\xf3\xbf2\x1f\xc7kEA\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp318 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp319 -(dp320 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp321 -(I1 -(I3 -tg6 -I00 -S'\xcb\x9c\x9bU\xfb>\x13@+\xc7\xc9a/\x9e\xf6\xbf\xea*\xfe\xf3\xd7\x18\xdd@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp322 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp323 -(dp324 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp325 -(I1 -(I3 -tg6 -I00 -S'u\xfeq\x86\xbb\x81\x14@\xd8]\\2\xe8\x95\xf6\xbf\x8e\xc5\tP{\xc3\xd1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp326 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp327 -(dp328 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp329 -(I1 -(I3 -tg6 -I00 -S'e\x05\xd8\x06\xf8\x9c\x15@\x11\xd9n\\\x90\xe8\xf0\xbftQ\xde\xa4\x14p\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp330 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp331 -(dp332 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp333 -(I1 -(I3 -tg6 -I00 -S'I{\xd8\x03w+\x17@\xd5\xc5\xae\xa1+.\xec?\x17.\xa5\xc8\x9d{\x03A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp334 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp335 -(dp336 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp337 -(I1 -(I3 -tg6 -I00 -S'\x11\x80\x9d\x95\x08\x91\x18@\xe8\x1eS\x8b\x04\xb9\xf3\xbft\xa1,\xf3\xb7;\xe4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp338 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp339 -(dp340 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp341 -(I1 -(I3 -tg6 -I00 -S'\xa11\xd5\xe3\x90\x9c\x1a@\x9a\xac\x1a\x07\x81t\xe2\xbfK\xb9\x00\x03n\x0e\x00A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp342 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp343 -(dp344 -g16 -g287 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp345 -(I1 -(I3 -tg6 -I00 -S'\xb8\xae6,\xe1\x11\x1c@,\xc4\xc98\xbe\xb5\xec\xbfI\xb1;i=\r\xe7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp346 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp347 -a(dp348 -g60 -g61 -(g62 -(I0 -tS'b' -tRp349 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp350 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp351 -aa(lp352 -g4 -(g6 -S'\x8f\x15\x08#\xadZ\xaa@' -tRp353 -ag8 -(g9 -g10 -(lp354 -g8 -(g12 -g13 -NtRp355 -(dp356 -g16 -g8 -(g17 -g13 -NtRp357 -(dp358 -g20 -F5 -sg21 -(dp359 -g20 -(F5 -g23 -tp360 -sg25 -(F21.299999 -g23 -tp361 -sg27 -(F4 -g23 -tp362 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp363 -(I1 -(I3 -tg6 -I00 -S'\xd1\x1c\xdc\xcc\xd6\x12\xf7?+ M\xc0\xa0\xb7\xf2\xbf\xfe\x88:]\x94\xaa\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp364 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp365 -(dp366 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp367 -(I1 -(I3 -tg6 -I00 -S'\xc1\x07x\xe2\xe5\x14\xfe?\xbc)\xf4,IZ\xf8\xbf\xed\x1d\xbe\x1d\xa1\x82\xb6@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp368 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp369 -(dp370 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp371 -(I1 -(I3 -tg6 -I00 -S'\x02\\Q\xae7\xe3\x02@\xf1V\x8fZ\x94M\xef\xbfev\xa3\x86H\x96\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp372 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp373 -(dp374 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp375 -(I1 -(I3 -tg6 -I00 -S'\x05\x12\x8cb\xc0\xc8\x03@jJ\xbc\xa4\xa8\x85\xf6\xbf\xddl\xf2\x05\xcb\xc1\xe2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp376 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp377 -(dp378 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp379 -(I1 -(I3 -tg6 -I00 -S"K'\xad\xcfS\xa3\x06@\xda\xe55\xa9\x8e>\xf1\xbf\x82\xd3\x16\xa6\xe1\x0e\xd8@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp380 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp381 -(dp382 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp383 -(I1 -(I3 -tg6 -I00 -S'rA+\x9fv\x06\x0c@\xddX\xf1C\x80\x02\xf7\xbf\xa9\x96\xa9|+\xec\xd6@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp384 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp385 -(dp386 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp387 -(I1 -(I3 -tg6 -I00 -S'\x98\xfe\x00\xf7=2\r@\xf1W[G\xe6\xd6\xf5\xbf:] \xd1r\x1b\xe8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp388 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp389 -(dp390 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp391 -(I1 -(I3 -tg6 -I00 -S'\xad\xc9\x8eS\xcaz\x10@A\xb6S]\x1f\x97\xe7\xbf\xa7\xee\xc3u\x08\x11\xf0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp392 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp393 -(dp394 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp395 -(I1 -(I3 -tg6 -I00 -S')\xec=\x08\xb5&\x12@\xde\x03\xcci\xc7\x97\xf5\xbf\x81\xdc\x1c\x8f&s\xef@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp396 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp397 -(dp398 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp399 -(I1 -(I3 -tg6 -I00 -S'\x9ay\x1f\x08\xd9+\x13@S\xccg\x87jP\xf7\xbf\xb7@p\xaf\xa8\xe4\xe3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp400 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp401 -(dp402 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp403 -(I1 -(I3 -tg6 -I00 -S'S\xa2\x19\xddUf\x14@\xef\xf0;i\x04(\xf6\xbf\xb8:\x81\x87O\xb0\xd2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp404 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp405 -(dp406 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp407 -(I1 -(I3 -tg6 -I00 -S'H\xe4\x86S\xd0\x98\x15@\x97\xeb\x96\xb6\x12.\xee\xbf\xf3\x1aa&\xa0\x07\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp408 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp409 -(dp410 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp411 -(I1 -(I3 -tg6 -I00 -S'\xe6\xf2\xbbL\r&\x17@!\xee\xd8 \xccI\xb7?\xce\x8d9\xa4H\x04\xff@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp412 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp413 -(dp414 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp415 -(I1 -(I3 -tg6 -I00 -S'Uv\xf0i\xa9\x92\x18@\x00\xae\x98*\x9a*\xf1\xbf<\rn\xa4(\x99\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp416 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp417 -(dp418 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp419 -(I1 -(I3 -tg6 -I00 -S'\xd0\xa7\xf5\x03[\x92\x1a@\x14_\xc0\xc8w\x05\xe3\xbfR~\x83\x93J\xa1\xff@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp420 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp421 -(dp422 -g16 -g357 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp423 -(I1 -(I3 -tg6 -I00 -S'\xe6\xeb[;\xdb\x08\x1c@|0\x01U\x99\x07\xe9\xbf\xf5\xe4\x95\xe2\x04\xc3\xe9@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp424 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp425 -a(dp426 -g60 -g61 -(g62 -(I0 -tS'b' -tRp427 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp428 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S'\x08\xd7\xa3p=\xaa\xc0?' -tRp429 -aa(lp430 -g4 -(g6 -S'\xdel\x82\x8a\xad\xaa\xae@' -tRp431 -ag8 -(g9 -g10 -(lp432 -g8 -(g12 -g13 -NtRp433 -(dp434 -g16 -g8 -(g17 -g13 -NtRp435 -(dp436 -g20 -F5 -sg21 -(dp437 -g20 -(F5 -g23 -tp438 -sg25 -(F21.299999 -g23 -tp439 -sg27 -(F4 -g23 -tp440 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp441 -(I1 -(I3 -tg6 -I00 -S'J\xff\x13\x83\xc2\x0e\xf7?\x90\x92\xc0\x04\xb1\xe6\xf2\xbf\xa5\t\xa5\x05]\xad\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp442 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp443 -(dp444 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp445 -(I1 -(I3 -tg6 -I00 -S'z\x19\xe0b\xe2\xbe\xfd?\xde\xea\x90\xfd\xce\xc3\xf7\xbf\x8fKImv\x07\xb9@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp446 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp447 -(dp448 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp449 -(I1 -(I3 -tg6 -I00 -S'\xb3b \x92\xdb\x82\x03@\xfb\x8fH1\xd3\x8f\xef\xbf"\xe3\xce\xd4\x9a\x80\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp450 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp451 -(dp452 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp453 -(I1 -(I3 -tg6 -I00 -S'\xda\xddC\x96H\xbe\x06@E\xb0\x82\xe6CZ\xf5\xbfe\xb4\xcc\xbf\xf0\xba\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp454 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp455 -(dp456 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp457 -(I1 -(I3 -tg6 -I00 -S'\xef\xe5\x83\xb3O\xea\x0c@&N;l\xc2\x95\xef\xbff zI\x0f\xec\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp458 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp459 -(dp460 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp461 -(I1 -(I3 -tg6 -I00 -S'\xbb\xff<8[t\x10@x\xf4C\xda\xb5\xc4\xed\xbfzl\x1b\x95+\xcb\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp462 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp463 -(dp464 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp465 -(I1 -(I3 -tg6 -I00 -S'\xf0[\xe3\x96\r,\x12@\xf5\x11\x88\x87\xf5A\xf1\xbf\x8f0\xf3t\xd6?\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp466 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp467 -(dp468 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp469 -(I1 -(I3 -tg6 -I00 -S'\xe2\x1a\x08\xb0eE\x13@\xe0\xe6\x0e_v9\xf5\xbf#:^Qg\x95\xda@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp470 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp471 -(dp472 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp473 -(I1 -(I3 -tg6 -I00 -S'\xca\x1d\xd3\x15=\x84\x14@\x8709B\x11F\xf3\xbf\xdb\x02\xcf]\x1c\x18\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp474 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp475 -(dp476 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp477 -(I1 -(I3 -tg6 -I00 -S'Sg\xe3\xb7\x07\xb8\x15@\xbc\x7f\x1d\xaf1\x05\xeb\xbf\xb4\xe8\xf2+\x92\xab\xf7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp478 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp479 -(dp480 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp481 -(I1 -(I3 -tg6 -I00 -S'\xf6\xfd\x88=\xd1,\x17@3\xc6c\xd2\xb8\x84\xe7\xbf-\t\x82(\x88\x01\xf3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp482 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp483 -(dp484 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp485 -(I1 -(I3 -tg6 -I00 -S'\x1aa\xc6\xb0L\x80\x18@C\xad\xd4\x8b\\\xd3\xef\xbf\xda\xf9k\x1c\x12"\xf3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp486 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp487 -(dp488 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp489 -(I1 -(I3 -tg6 -I00 -S'\x80\xf3\x8b\xee\xd7\x9a\x1a@/B j\xb6\xd4\xe0\xbf\x9eBq\x12\xd7\xc6\x00A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp490 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp491 -(dp492 -g16 -g435 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp493 -(I1 -(I3 -tg6 -I00 -S'S\x7f\x91\x87D\x17\x1c@\x0fK\xbf\xaa\xe8\xdd\xed\xbf.\x7f>7U\xec\xe5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp494 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp495 -a(dp496 -g60 -g61 -(g62 -(I0 -tS'b' -tRp497 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp498 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp499 -aa(lp500 -g4 -(g6 -S'\x17b\xfe\xf8V}\xb1@' -tRp501 -ag8 -(g9 -g10 -(lp502 -g8 -(g12 -g13 -NtRp503 -(dp504 -g16 -g8 -(g17 -g13 -NtRp505 -(dp506 -g20 -F5 -sg21 -(dp507 -g20 -(F5 -g23 -tp508 -sg25 -(F21.299999 -g23 -tp509 -sg27 -(F4 -g23 -tp510 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp511 -(I1 -(I3 -tg6 -I00 -S'\xb3\x80E\x14f\x0c\xf7?C\xbb\x8b\xcb\x96C\xf3\xbf\xde\xf7\x80\xc3Si\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp512 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp513 -(dp514 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp515 -(I1 -(I3 -tg6 -I00 -S'\xe8\x8a5\n\xfcH\x03@\xd79\x99\xd9\r\xba\xed\xbf]\x07\xfbB\xb0\xd1\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp516 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp517 -(dp518 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp519 -(I1 -(I3 -tg6 -I00 -S'/\x19v\t^\xec\x03@LE\xf5\xe2\x0ev\xf7\xbf\x94\xb9`\xe8\x88>\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp520 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp521 -(dp522 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp523 -(I1 -(I3 -tg6 -I00 -S'\xcc(|\x9c\xf6\xb5\x06@\xd4\xb7\x03\xea\x86v\xf3\xbf\xd0\xc8\xa2\x1b\xe3\xf5\xd5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp524 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp525 -(dp526 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp527 -(I1 -(I3 -tg6 -I00 -S'\x9d.\xb76\xfd\xe9\x0c@dG\r\xfc0I\xf0\xbf\x93\xc0\xff\xfc\x8b\x9a\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp528 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp529 -(dp530 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp531 -(I1 -(I3 -tg6 -I00 -S'\xd5\xb6\x8a&.{\x10@\xc7 \xb0\xe8J\xb9\xeb\xbf\xe0\xbd\x81\xaeu\xfc\xed@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp532 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp533 -(dp534 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp535 -(I1 -(I3 -tg6 -I00 -S'\xc0\xdfu(\xa9\x05\x12@;_\xda\xf9\x80\x07\xf7\xbf9\x961\x99)R\xe8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp536 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp537 -(dp538 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp539 -(I1 -(I3 -tg6 -I00 -S'%\xdc\xe9\x18\xd6\xde\x12@.~b\xe5\xeb\xd6\xe8\xbf\x80\x0bc\xbe\xb3v\xea@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp540 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp541 -(dp542 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp543 -(I1 -(I3 -tg6 -I00 -S'\xa7|\xbeW\xbe\xcd\x15@\x85F-\x89[\xd0\xc8\xbfK\x0e\xfd\xf3\xa8\xfc\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp544 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp545 -(dp546 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp547 -(I1 -(I3 -tg6 -I00 -S'y\x97g\x19YC\x17@\x87\xbb\x10\xfb\xa2`\xf6\xbf0\x12\xe0\xee]K\xe0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp548 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp549 -(dp550 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp551 -(I1 -(I3 -tg6 -I00 -S'%\xc9\xe3\xe3\xa6k\x18@?}H\xf8\xf6\xc1\xec\xbfM\x0e#\xc4\x0bN\xf6@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp552 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp553 -(dp554 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp555 -(I1 -(I3 -tg6 -I00 -S'\xb1M9MY\x9e\x1a@;;3\xd1;X\xe0\xbf\xeeA\xbc*7\x00\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp556 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp557 -(dp558 -g16 -g505 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp559 -(I1 -(I3 -tg6 -I00 -S'\x0e\x9d\x97\xe1\xef\x1a\x1c@\x95\xbf>\xdb\x19[\xef\xbf=\xcd0\xa41\xbb\xe4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp560 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp561 -a(dp562 -g60 -g61 -(g62 -(I0 -tS'b' -tRp563 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp564 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp565 -aa(lp566 -g4 -(g6 -S'\xbe\x8d\xbb,W\xa5\xb3@' -tRp567 -ag8 -(g9 -g10 -(lp568 -g8 -(g12 -g13 -NtRp569 -(dp570 -g16 -g8 -(g17 -g13 -NtRp571 -(dp572 -g20 -F5 -sg21 -(dp573 -g20 -(F5 -g23 -tp574 -sg25 -(F21.299999 -g23 -tp575 -sg27 -(F4 -g23 -tp576 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp577 -(I1 -(I3 -tg6 -I00 -S'\xabf@\xf8[\x11\xf7?\xab\x90\xff\xff\xd6\xd9\xf2\xbf\x80\x92i\x1c\x18\xbc\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp578 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp579 -(dp580 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp581 -(I1 -(I3 -tg6 -I00 -S'-{W`\xaf\x81\x03@|/\xba\xb1\x19\x9b\xef\xbf\xd5m*Q\x93`\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp582 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp583 -(dp584 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp585 -(I1 -(I3 -tg6 -I00 -S'|\xd1\xf9\xa4\x97\xc0\x06@g\xd2&\x1dOf\xf6\xbf\xea\xf6\xbcUN\xd1\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp586 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp587 -(dp588 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp589 -(I1 -(I3 -tg6 -I00 -S'F[\xbcJF\xeb\x0c@~N[~\xbb\x19\xef\xbf\x18\x12\x1c\xe2\x8c\x11\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp590 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp591 -(dp592 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp593 -(I1 -(I3 -tg6 -I00 -S'F\x14N\xe1\x85r\x10@\x84\x04\x9fg\xddL\xee\xbfV\x11|\xfc\xe3k\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp594 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp595 -(dp596 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp597 -(I1 -(I3 -tg6 -I00 -S'\xcc\xb3\x7fo\x1b,\x12@\xba\x17q\x81i\xa6\xf0\xbf3\xfe\xadl]\x8a\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp598 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp599 -(dp600 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp601 -(I1 -(I3 -tg6 -I00 -S'j\x13D\xf5\xfaU\x13@\xc3\x102\xea\xe8\xc1\xf1\xbf\xa6V\x86\xe3%\x80\xdd@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp602 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp603 -(dp604 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp605 -(I1 -(I3 -tg6 -I00 -S'\x91\xf2\x92\xb8\xcd\xb0\x14@\xbck\x86\xbb\x05B\xf5\xbfB\xd0\x05a\xc1\x96\xd8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp606 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp607 -(dp608 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp609 -(I1 -(I3 -tg6 -I00 -S'\x1eJ\tav\xbd\x15@:kL\xf0s\xc9\xf0\xbf6vD\xf2\xee\x7f\xf4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp610 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp611 -(dp612 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp613 -(I1 -(I3 -tg6 -I00 -S'\xc6\xda\x98id\x05\x17@\x12d\xd0\x1f\x85\xeb\xeb\xbfh-\xe1b\xf0\x1e\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp614 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp615 -(dp616 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp617 -(I1 -(I3 -tg6 -I00 -S'\xaa\xd3\xb2vop\x18@\x10\x8b\x90\xd2P9\xea\xbf\xd7!\x98\xc9\x8f\x04\xf7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp618 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp619 -(dp620 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp621 -(I1 -(I3 -tg6 -I00 -S'm\x05\x0f\xa7s\x8d\x1a@\x84\xdd\xd5\xc9$h\xe5\xbf*\xbd\xa0\xc8\xa3\xd2\xfd@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp622 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp623 -(dp624 -g16 -g571 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp625 -(I1 -(I3 -tg6 -I00 -S'95i\xa7%\xfb\x1b@I6\t\xfe\x19^\xe7\xbf\x15 ;h\x05{\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp626 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp627 -a(dp628 -g60 -g61 -(g62 -(I0 -tS'b' -tRp629 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp630 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp631 -aa(lp632 -g4 -(g6 -S'f\xb9x`W\xcd\xb5@' -tRp633 -ag8 -(g9 -g10 -(lp634 -g8 -(g12 -g13 -NtRp635 -(dp636 -g16 -g8 -(g17 -g13 -NtRp637 -(dp638 -g20 -F5 -sg21 -(dp639 -g20 -(F5 -g23 -tp640 -sg25 -(F21.299999 -g23 -tp641 -sg27 -(F4 -g23 -tp642 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp643 -(I1 -(I3 -tg6 -I00 -S'\x82\xf7\xa5\xc6I\x11\xf7?\xef@\xe3_\x9c\xd2\xf2\xbf\xdf\xb6]\\\xd6\xc2\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp644 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp645 -(dp646 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp647 -(I1 -(I3 -tg6 -I00 -S'n\xee1D\xab\x81\x03@Em\xb0\x86"\x9d\xef\xbfq\xeaKn)`\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp648 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp649 -(dp650 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp651 -(I1 -(I3 -tg6 -I00 -S'\xfd6\x832\xa6\xc0\x06@\xdf\xf9P\xfe\xcck\xf6\xbf\xb1\xe74JS\xdc\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp652 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp653 -(dp654 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp655 -(I1 -(I3 -tg6 -I00 -S'\xc9\xfb\x83\xeeB\xeb\x0c@J\x99eWF\x1a\xef\xbfC}\xfa\xee\x99\x11\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp656 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp657 -(dp658 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp659 -(I1 -(I3 -tg6 -I00 -S'W\xd8\n\xee\x1et\x10@\xbd\x1b\xc3\x15~\x8c\xee\xbf\xc9\xf6\x01\xb4KN\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp660 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp661 -(dp662 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp663 -(I1 -(I3 -tg6 -I00 -S's\xeb\xcaj\xd6%\x12@\xa7c$g/U\xf1\xbf\xfb\x82\x1b\xf5\xca\xc0\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp664 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp665 -(dp666 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp667 -(I1 -(I3 -tg6 -I00 -S'\xdc\xc3\xb9\x03t=\x13@\x94\xf7\x88\xca\xa8\x9a\xf1\xbf{\xedQY\x14 \xde@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp668 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp669 -(dp670 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp671 -(I1 -(I3 -tg6 -I00 -S'\xcd\x18\x18\xcf\x8c\xc9\x15@\xa3\xd4\xc6,\xb4\xcd\xcd\xbfp\x83\xee\x80\xfe\xa6\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp672 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp673 -(dp674 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp675 -(I1 -(I3 -tg6 -I00 -S';\xd8[\x82\x951\x17@I\xba\xfb0\x1bZ\xf7\xbfO:.PB-\xe3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp676 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp677 -(dp678 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp679 -(I1 -(I3 -tg6 -I00 -S'\x8dz\xe1\x8c\xc4h\x18@\x03\xbb\x97\x8b\x995\xea\xbf\x12\x96G\xe7\xe1\xc3\xf7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp680 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp681 -(dp682 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp683 -(I1 -(I3 -tg6 -I00 -S'\xe9l\xda\xe8l\x8d\x1a@g=r{\x03j\xe5\xbf\xf0\xe1\x8a\xec\xd8\xd0\xfd@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp684 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp685 -(dp686 -g16 -g637 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp687 -(I1 -(I3 -tg6 -I00 -S'\xa5\xc8tp\x16\xfb\x1b@@w\xbe-;[\xe7\xbf\x84\x1f\x04y\x10~\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp688 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp689 -a(dp690 -g60 -g61 -(g62 -(I0 -tS'b' -tRp691 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp692 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp693 -aa(lp694 -g4 -(g6 -S'\x0e\xe55\x94W\xf5\xb7@' -tRp695 -ag8 -(g9 -g10 -(lp696 -g8 -(g12 -g13 -NtRp697 -(dp698 -g16 -g8 -(g17 -g13 -NtRp699 -(dp700 -g20 -F5 -sg21 -(dp701 -g20 -(F5 -g23 -tp702 -sg25 -(F21.299999 -g23 -tp703 -sg27 -(F4 -g23 -tp704 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp705 -(I1 -(I3 -tg6 -I00 -S'$\x90\xde\xf3\x96\x0e\xf7?\x94\xc4\xfc\xeaT\xde\xf2\xbf\x11\x1d\x08\x97\x15\xd7\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp706 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp707 -(dp708 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp709 -(I1 -(I3 -tg6 -I00 -S'\xcd\xab\xaef\x83\x82\x03@E\xe8S\xa3g\xb6\xef\xbf\xf7&!2\xf4\\\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp710 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp711 -(dp712 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp713 -(I1 -(I3 -tg6 -I00 -S'16U\x1aq\xc0\x06@\xb6a\xd4gU\x10\xf6\xbf\x1b\xd0\x9a\x9dw\x7f\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp714 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp715 -(dp716 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp717 -(I1 -(I3 -tg6 -I00 -S'6\x0b\x98\xb5\x01\xea\x0c@\x93J\xb5&c!\xef\xbf\xd6\x9d\x9b\x9a|\x0f\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp718 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp719 -(dp720 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp721 -(I1 -(I3 -tg6 -I00 -S'\xdb\x88\xae\x97ss\x10@\xdf\xe8\xca5\xed\xeb\xee\xbf\xc7\xb5\\p\n\x18\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp722 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp723 -(dp724 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp725 -(I1 -(I3 -tg6 -I00 -S'=\x0e\x02\xc9\xcb(\x12@\xd6[L_\x1b\xdc\xf0\xbf\xb5%\x90\x91\xfcK\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp726 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp727 -(dp728 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp729 -(I1 -(I3 -tg6 -I00 -S'\xa3t}lCD\x13@\x8c\xed\xdd\xf6Br\xf2\xbf`a\x9f2\xc4-\xdc@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp730 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp731 -(dp732 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp733 -(I1 -(I3 -tg6 -I00 -S'\x18E\x0b\x8a\xc7\xca\x15@0F\x1b\xa3~\x90\xcd\xbf\xe3mM%\xdb\xaf\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp734 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp735 -(dp736 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp737 -(I1 -(I3 -tg6 -I00 -S'\xd1\r\x8a\xbf\xf76\x17@3\xcd^P=\x92\xf6\xbfF\x0e\xacb\xde\x85\xdf@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp738 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp739 -(dp740 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp741 -(I1 -(I3 -tg6 -I00 -S'A.\xaf=Ui\x18@&]\xc6\x9co\x08\xea\xbfx\x9b\xc35\x19\xcf\xf7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp742 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp743 -(dp744 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp745 -(I1 -(I3 -tg6 -I00 -S'<%$\xf8\xab\x8c\x1a@\xb0\xc8;\xad\x9a\x9f\xe5\xbfJK>\xffm\x95\xfd@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp746 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp747 -(dp748 -g16 -g699 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp749 -(I1 -(I3 -tg6 -I00 -S'\xbfM\x94:\x83\xf9\x1b@*\x88\xb583\x16\xe7\xbf\xbbxw\xf5\xe3\xe8\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp750 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp751 -a(dp752 -g60 -g61 -(g62 -(I0 -tS'b' -tRp753 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp754 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp755 -aa(lp756 -g4 -(g6 -S'\xb5\x10\xf3\xc7W\x1d\xba@' -tRp757 -ag8 -(g9 -g10 -(lp758 -g8 -(g12 -g13 -NtRp759 -(dp760 -g16 -g8 -(g17 -g13 -NtRp761 -(dp762 -g20 -F5 -sg21 -(dp763 -g20 -(F5 -g23 -tp764 -sg25 -(F21.299999 -g23 -tp765 -sg27 -(F4 -g23 -tp766 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp767 -(I1 -(I3 -tg6 -I00 -S'w\xe5\x14\x8e\xff\x1d\xf7?\xc9\x82\x08\xd3x\xb7\xf2\xbf\xa9\xe0\xc3}\x1a\xca\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp768 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp769 -(dp770 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp771 -(I1 -(I3 -tg6 -I00 -S'\xf8\x869\xf5\x89\x81\x03@\x9e\xff\xfa|7\x93\xef\xbfXl\tT\xabc\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp772 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp773 -(dp774 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp775 -(I1 -(I3 -tg6 -I00 -S'\x99\xf8eT\x13\xbe\x06@\xc5\xfe\xf5\x13\xf3\x0e\xf6\xbfC\xc2Ow\xdd\x9e\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp776 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp777 -(dp778 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp779 -(I1 -(I3 -tg6 -I00 -S'Tr\xd4+\x88\xeb\x0c@"k\x92-\x82\x1b\xef\xbf\xf0\xa5\xb3$\xaa\x12\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp780 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp781 -(dp782 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp783 -(I1 -(I3 -tg6 -I00 -S'\x0bc{\x92Xs\x10@\x1d\xc0\x08*\x0f\xc9\xed\xbfG\x1d\xcd\x83}\xa6\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp784 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp785 -(dp786 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp787 -(I1 -(I3 -tg6 -I00 -S'O/\xeb\xad\xfd-\x12@\xbdi\x12\x87f\xe1\xf0\xbf\x92M0Y\x93\xaf\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp788 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp789 -(dp790 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp791 -(I1 -(I3 -tg6 -I00 -S'\xf9\xf6k^\xbdC\x13@\xff.\xa3w\x03\xed\xf6\xbf\xdb\xc63\xdb\xf7\xfd\xd7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp792 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp793 -(dp794 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp795 -(I1 -(I3 -tg6 -I00 -S'\t\x10B\\\x0b\xc0\x15@\xcb\xbd\xf2\xcca\xfe\xd7\xbfEoH\xf7\xc6\x82\x00A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp796 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp797 -(dp798 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp799 -(I1 -(I3 -tg6 -I00 -S'h\x9a\x15\x0f\x0e"\x17@-\xf7D\xf3\xe1+\xf7\xbf\xb6\xbe\xc7\x1b\x16\xe1\xe0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp800 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp801 -(dp802 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp803 -(I1 -(I3 -tg6 -I00 -S'\xf1\x01\xa6w\x16a\x18@Q\xec[/iC\xe7\xbfO;\xc8@\x89g\xf9@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp804 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp805 -(dp806 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp807 -(I1 -(I3 -tg6 -I00 -S'\xda%$\x92[\x8c\x1a@\xd7\xaf\xa6\xa2m\xdb\xe5\xbfR\x13\x14P\xcbx\xfd@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp808 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp809 -(dp810 -g16 -g761 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp811 -(I1 -(I3 -tg6 -I00 -S'\xf6\x95$\x17 \xf8\x1b@\xe1g\xa0V\xbd\xcb\xe6\xbfY\xaa\xa0\xfb\\\x16\xed@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp812 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp813 -a(dp814 -g60 -g61 -(g62 -(I0 -tS'b' -tRp815 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp816 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp817 -aa(lp818 -g4 -(g6 -S']<\xb0\xfbWE\xbc@' -tRp819 -ag8 -(g9 -g10 -(lp820 -g8 -(g12 -g13 -NtRp821 -(dp822 -g16 -g8 -(g17 -g13 -NtRp823 -(dp824 -g20 -F5 -sg21 -(dp825 -g20 -(F5 -g23 -tp826 -sg25 -(F21.299999 -g23 -tp827 -sg27 -(F4 -g23 -tp828 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp829 -(I1 -(I3 -tg6 -I00 -S'8\xc0\xb3P\xc7\x0e\xf7?\xefe\xd2[\xe7\xce\xf2\xbf\x81\xb9h\x88\xa8\xcf\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp830 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp831 -(dp832 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp833 -(I1 -(I3 -tg6 -I00 -S"S;\xe0y\xcf\x82\x03@l\x00\x0b\xf4\xbf\x14\xf0\xbf4\xc7\xb6'*>\xf2@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp834 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp835 -(dp836 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp837 -(I1 -(I3 -tg6 -I00 -S'\x11*f\\\xc5\xbd\x06@\xe9i\xa7\xad\x89\x7f\xf4\xbf\x89\xde\xbf\n\xd2:\xd5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp838 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp839 -(dp840 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp841 -(I1 -(I3 -tg6 -I00 -S'9[5U\x96\xe9\x0c@.u\x03U\xdco\xef\xbfY\x83\xc0E\xe2\xf6\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp842 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp843 -(dp844 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp845 -(I1 -(I3 -tg6 -I00 -S'\x1eKBV\x1ev\x10@IS\xed~\xb1\x03\xee\xbf\x9d4&\\B\xb2\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp846 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp847 -(dp848 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp849 -(I1 -(I3 -tg6 -I00 -S'\xfe\xfe\x9c<,\x13\x12@\x8c\xfd\xa8ULV\xf3\xbf\xe0\xd5\x96\xea\x95\xfb\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp850 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp851 -(dp852 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp853 -(I1 -(I3 -tg6 -I00 -S'\xce%\xcahJ\x0b\x13@\x85\x04e\xe4o\xc2\xe6\xbf\x1fI\xc6,\xadO\xe7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp854 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp855 -(dp856 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp857 -(I1 -(I3 -tg6 -I00 -S'\x7fU\x1a\xdf\xec\xca\x15@Y%\xb9\r\xc8\xd8\xd3\xbf\x07(\x0ehs#\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp858 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp859 -(dp860 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp861 -(I1 -(I3 -tg6 -I00 -S'c0\xa8\xee\xe04\x17@\x84\xc3C\xb2\x160\xf7\xbf\xf6\xf7\xc7\xf1\x14?\xe2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp862 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp863 -(dp864 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp865 -(I1 -(I3 -tg6 -I00 -S'\xc7\xb6\x1cq!h\x18@\x92\xacU\xc8K&\xeb\xbfk\x16\xaf5@P\xf7@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp866 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp867 -(dp868 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp869 -(I1 -(I3 -tg6 -I00 -S'*k\xa6\xf8u\x95\x1a@\xe1\x18l-y\xe7\xe2\xbft\xc8}\x86\xec\xf6\xff@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp870 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp871 -(dp872 -g16 -g823 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp873 -(I1 -(I3 -tg6 -I00 -S'f\xd4\xff=\x97\x0c\x1c@Q\xee~2\xf7R\xeb\xbf\xc5\x85\xb6\xb1U\xa9\xe8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp874 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp875 -a(dp876 -g60 -g61 -(g62 -(I0 -tS'b' -tRp877 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp878 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp879 -aa(lp880 -g4 -(g6 -S'\x05hm/Xm\xbe@' -tRp881 -ag8 -(g9 -g10 -(lp882 -g8 -(g12 -g13 -NtRp883 -(dp884 -g16 -g8 -(g17 -g13 -NtRp885 -(dp886 -g20 -F5 -sg21 -(dp887 -g20 -(F5 -g23 -tp888 -sg25 -(F21.299999 -g23 -tp889 -sg27 -(F4 -g23 -tp890 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp891 -(I1 -(I3 -tg6 -I00 -S'\x80\xd6\x1e\xf1\x84\x11\xf7?p\x98m\\A\xaf\xf2\xbf\xfa\x00\xf3\x80i\xec\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp892 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp893 -(dp894 -g16 -g885 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp895 -(I1 -(I3 -tg6 -I00 -S'?-/j\xbb\x81\x03@\x87s@\x19x\xe4\xef\xbfS/\xbd\x83PL\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp896 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp897 -(dp898 -g16 -g885 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp899 -(I1 -(I3 -tg6 -I00 -S'\x84J\x80\xc6\xf1\xbd\x06@\x88\xf6)\xa1L\xa8\xf5\xbf\x8e\x16\x1eH\n\x88\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp900 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp901 -(dp902 -g16 -g885 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp903 -(I1 -(I3 -tg6 -I00 -S'\xe8\xdfpD\xbe\xea\x0c@\xfc\x11\xe9\xe9\xb5\xbc\xef\xbf\x92p\xcbN\xff\xeb\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp904 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp905 -(dp906 -g16 -g885 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp907 -(I1 -(I3 -tg6 -I00 -S'.{\n\x8f\x03y\x10@\x1e\xe9Q\xad\xac\xd1\xeb\xbf\xa1\x9a\x96\xfcE\n\xee@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp908 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp909 -(dp910 -g16 -g885 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp911 -(I1 -(I3 -tg6 -I00 -S'uo\xb0e\xbd\x11\x12@\xfeDG>E\x88\xf5\xbf\xb1\x14\xb6B\xd6j\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp912 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp913 -(dp914 -g16 -g885 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp915 -(I1 -(I3 -tg6 -I00 -S'\xf6P\xc3\x08\xe6\xff\x12@\xad\xf8q\xc1\x00\xee\xee\xbf]\xa3W\xd6?_\x1d\x01\x10\xff\xab\x07A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp932 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp933 -a(dp934 -g60 -g61 -(g62 -(I0 -tS'b' -tRp935 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp936 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp937 -aa(lp938 -g4 -(g6 -S'\xd6I\x951\xacJ\xc0@' -tRp939 -ag8 -(g9 -g10 -(lp940 -g8 -(g12 -g13 -NtRp941 -(dp942 -g16 -g8 -(g17 -g13 -NtRp943 -(dp944 -g20 -F5 -sg21 -(dp945 -g20 -(F5 -g23 -tp946 -sg25 -(F21.299999 -g23 -tp947 -sg27 -(F4 -g23 -tp948 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp949 -(I1 -(I3 -tg6 -I00 -S'\x0f\r\x8d\xb4\x03\x12\xf7?\xa4\xc4v\x1b\xa2\xb4\xf2\xbf\xab\xa1\xbf\xe6x\xe8\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp950 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp951 -(dp952 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp953 -(I1 -(I3 -tg6 -I00 -S'\x1d;6(\xd0\x81\x03@\x06\xe9YIW\xd0\xef\xbf\x93\xc8\x8ct\xbbS\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp954 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp955 -(dp956 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp957 -(I1 -(I3 -tg6 -I00 -S'\xc9\x12\x1f1\xc1\xbd\x06@\xf2j\x81Q|\xaa\xf5\xbfg\x1d\x0e\xa6\xbd\x87\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp958 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp959 -(dp960 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp961 -(I1 -(I3 -tg6 -I00 -S'\x9b\xf42A\xf4\xea\x0c@z;\x8882\x93\xef\xbf%\xd1\xaf J\xfc\xf1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp962 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp963 -(dp964 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp965 -(I1 -(I3 -tg6 -I00 -S'd\x88\xd1p\xe0x\x10@(\xa5<\xce\x14\xdc\xeb\xbf\xbfC\x1e\xd3v\xfe\xed@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp966 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp967 -(dp968 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp969 -(I1 -(I3 -tg6 -I00 -S'\xc4\xf0\xa9\xb1\xac\x11\x12@G\xb4\xbf\xf8yR\xf5\xbf\xb9\x0e\xc8N^\x94\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp970 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp971 -(dp972 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp973 -(I1 -(I3 -tg6 -I00 -S'\xc5\xd55(\xa1\x01\x13@\xb7"I\x82\x94T\xee\xbf\xd5N%\xb6p\xf7\xe4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp974 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp975 -(dp976 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp977 -(I1 -(I3 -tg6 -I00 -S'\xc7\xef\x19\xe85\xc6\x15@\x9a\x85m0\xe1&\xd0\xbf\xfcd5\xa6\xabV\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp978 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp979 -(dp980 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp981 -(I1 -(I3 -tg6 -I00 -S'\x991\xf4qTp\x17@\xdc\xd1\xde\xc1\x03\xa1\xee\xbf\x86K\xe7\xe6\x8f7\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp982 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp983 -(dp984 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp985 -(I1 -(I3 -tg6 -I00 -S'J\x0b\xfch\x1e|\x18@\xe8\x8a\xdc\x1b\x88C\xf5\xbf\t7\x90\x92Z\xaf\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp986 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp987 -(dp988 -g16 -g943 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp989 -(I1 -(I3 -tg6 -I00 -S'\x02\xaa\x01\x93[\xd3\x1a@\x03:u\xb9ip\xd4?;\xb18)\xe0}\x07A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp990 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp991 -a(dp992 -g60 -g61 -(g62 -(I0 -tS'b' -tRp993 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp994 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp995 -aa(lp996 -g4 -(g6 -S'\xaa\xdfsK\xac^\xc1@' -tRp997 -ag8 -(g9 -g10 -(lp998 -g8 -(g12 -g13 -NtRp999 -(dp1000 -g16 -g8 -(g17 -g13 -NtRp1001 -(dp1002 -g20 -F5 -sg21 -(dp1003 -g20 -(F5 -g23 -tp1004 -sg25 -(F21.299999 -g23 -tp1005 -sg27 -(F4 -g23 -tp1006 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp1007 -(I1 -(I3 -tg6 -I00 -S'\xb1\xb3\x90\xb2\x95\x10\xf7?\xb3\xf3\xf8nF\xba\xf2\xbf\xbc\xc2\xf1\xd8\xb0\xdc\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1008 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1009 -(dp1010 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1011 -(I1 -(I3 -tg6 -I00 -S'g\xb50J\n\x82\x03@\xaa*\xd1\x14j\xc4\xef\xbf\x97\xb6~\xfdWV\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1012 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1013 -(dp1014 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1015 -(I1 -(I3 -tg6 -I00 -S'hc)\xd6\xae\xbd\x06@\xed\xbfbW\x0b\xae\xf5\xbf&B\xd1W\xad\x8b\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1016 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1017 -(dp1018 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1019 -(I1 -(I3 -tg6 -I00 -S'\xad\x9c\xe2\xcb\xec\xea\x0c@q\x10h_\x1aN\xef\xbf\xed\xa4=\x94O\x01\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1020 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1021 -(dp1022 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1023 -(I1 -(I3 -tg6 -I00 -S'\xc6\x10\x01\xac\x9bs\x10@\xcd\xcfX~\xb6\xe3\xed\xbf\x8d\xf1C\xc8\xb2\xb5\xec@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1024 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1025 -(dp1026 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1027 -(I1 -(I3 -tg6 -I00 -S'd\x16\xe8\xf3\xb9)\x12@*\xc3U\xa1\xc7,\xf1\xbf\xa0\xb8\x807\xc9\x0b\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1028 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1029 -(dp1030 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1031 -(I1 -(I3 -tg6 -I00 -S'\xfe\xc1\xf5\xb9.L\x13@%\xf9;\xe5\xa3\xb6\xf1\xbfm\x081B\xc3R\xde@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1032 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1033 -(dp1034 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1035 -(I1 -(I3 -tg6 -I00 -S"\xfe\xe5\xb9\x07\xfd\xae\x14@\xab\xc9\xc6&'\xdf\xf4\xbf\xa8\x98\xfd\xde\xab\xe6\xd8@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1036 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1037 -(dp1038 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1039 -(I1 -(I3 -tg6 -I00 -S'\x80=\xe4l\x96\xac\x15@r\xc4C\x0e\x9d\x1d\xf2\xbf\x98\x99\x84Fk\x1f\xf0@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1040 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1041 -(dp1042 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1043 -(I1 -(I3 -tg6 -I00 -S'\x1ba\x83\x88I\x19\x17@pJL\x96\x93\xff\xc6\xbf#\x07?Z|O\xfc@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1044 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1045 -(dp1046 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1047 -(I1 -(I3 -tg6 -I00 -S'%\xe6\xb8\xbfs\x83\x18@\xe0$\x81\x1bi4\xf2\xbf\xb0\xe4mR\xb0\xea\xea@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1048 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1049 -(dp1050 -g16 -g1001 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1051 -(I1 -(I3 -tg6 -I00 -S'\xa3\xf3\xec^C\xd7\x1a@;\x00N\n<\xd2\xd1?\x91\xf1\r\xb4\x83L\x07A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1052 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp1053 -a(dp1054 -g60 -g61 -(g62 -(I0 -tS'b' -tRp1055 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1056 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp1057 -aa(lp1058 -g4 -(g6 -S'~uRe\xacr\xc2@' -tRp1059 -ag8 -(g9 -g10 -(lp1060 -g8 -(g12 -g13 -NtRp1061 -(dp1062 -g16 -g8 -(g17 -g13 -NtRp1063 -(dp1064 -g20 -F5 -sg21 -(dp1065 -g20 -(F5 -g23 -tp1066 -sg25 -(F21.299999 -g23 -tp1067 -sg27 -(F4 -g23 -tp1068 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp1069 -(I1 -(I3 -tg6 -I00 -S'\xb2R\xa6\xb2\xdb\x11\xf7?-\x14.%\x07"\xf3\xbfB\xa7\x1d\xf9\x94\x84\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1070 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1071 -(dp1072 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1073 -(I1 -(I3 -tg6 -I00 -S'3\xf9x\xdf~\x81\x03@.7O\x97\xc8\x96\xee\xbf\x82\xb6\x07\n\xc9\xbd\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1074 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1075 -(dp1076 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1077 -(I1 -(I3 -tg6 -I00 -S'Q\xca\x8d@&\xc2\x06@\xce\x11\xd0\xc0^\xaf\xf6\xbf\x11(z\xb2\xa0\xf7\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1078 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1079 -(dp1080 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1081 -(I1 -(I3 -tg6 -I00 -S'\xd6\xab:\x14R\xea\x0c@2YH\x06\x9e\xed\xee\xbf\xda:r\xf1$\x19\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1082 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1083 -(dp1084 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1085 -(I1 -(I3 -tg6 -I00 -S'CmA Yp\x10@#K\x0cg\x8f?\xf0\xbfW\xf5\x05k\xa9-\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1086 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1087 -(dp1088 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1089 -(I1 -(I3 -tg6 -I00 -S'F\xf4\xef&\xeb2\x12@\xf3\xeekd&\x0c\xee\xbfD\x93\xfa\xc5\x88<\xf4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1090 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1091 -(dp1092 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1093 -(I1 -(I3 -tg6 -I00 -S'\xe8\xa6\xa5\xfa\x8a_\x13@\xbd%b \x0c\x19\xf7\xbf\xf0\xcdr\x91\xb5\xde\xd3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1094 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1095 -(dp1096 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1097 -(I1 -(I3 -tg6 -I00 -S'\x03\x9c\xf5\x02_\xcb\x15@\xe3\x12rx\x86\xcd\xca\xbf\xc6\xb1O\xc7,\xde\x01A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1098 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1099 -(dp1100 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1101 -(I1 -(I3 -tg6 -I00 -S'@\x0c\xc6\xfd\xd4@\x17@/\x96W\x82m\xcb\xf6\xbfLl\x7f&\xc7\x17\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1102 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1103 -(dp1104 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1105 -(I1 -(I3 -tg6 -I00 -S'Y9Dg\x9f]\x18@\xa5~\xbeh\xe2J\xf0\xbf6;]\xa7\xf6s\xf3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1106 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1107 -(dp1108 -g16 -g1063 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1109 -(I1 -(I3 -tg6 -I00 -S'\xcc+\xd6.\x0b\xd6\x1a@\xa8\x86v\xa02\x99\xd3?4\x9c\x05<\xcdu\x07A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1110 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp1111 -a(dp1112 -g60 -g61 -(g62 -(I0 -tS'b' -tRp1113 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1114 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp1115 -aa(lp1116 -g4 -(g6 -S'R\x0b1\x7f\xac\x86\xc3@' -tRp1117 -ag8 -(g9 -g10 -(lp1118 -g8 -(g12 -g13 -NtRp1119 -(dp1120 -g16 -g8 -(g17 -g13 -NtRp1121 -(dp1122 -g20 -F5 -sg21 -(dp1123 -g20 -(F5 -g23 -tp1124 -sg25 -(F21.299999 -g23 -tp1125 -sg27 -(F4 -g23 -tp1126 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp1127 -(I1 -(I3 -tg6 -I00 -S'}\xdbDUV\r\xf7?&P\xf6\x95\xdf1\xf3\xbf&q\x98\xe8V\x93\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1128 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1129 -(dp1130 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1131 -(I1 -(I3 -tg6 -I00 -S'\xc0dh\x80\xca\x82\x03@\x02?\x1a\xe3\xda\x07\xef\xbf\xb0\x96\xae\xcb\x82\xaf\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1132 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1133 -(dp1134 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1135 -(I1 -(I3 -tg6 -I00 -S'\xe2-\xdb\x10\xa6\xc0\x06@\xcc\xd1\xb2\x05\xa8\xaf\xf6\xbfA]-t.\xea\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1136 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1137 -(dp1138 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1139 -(I1 -(I3 -tg6 -I00 -S'\x9b\xfe\xde\x85,\xea\x0c@\x88\xbeB\xb92\x14\xef\xbf\xd0E\x98\xad\x1f\x18\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1140 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1141 -(dp1142 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1143 -(I1 -(I3 -tg6 -I00 -S'\xd3\x0f\xca\x13\xbfq\x10@\xbd\x84~\x1cqc\xef\xbf\xd2\xa9Y<]\xa3\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1144 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1145 -(dp1146 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1147 -(I1 -(I3 -tg6 -I00 -S'\xfb\xc9\x88\xb1\xde1\x12@\x9c*\xcd\xf6\x9fW\xef\xbf\xd6\x98\x87\x1e*\xd6\xf3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1148 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1149 -(dp1150 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1151 -(I1 -(I3 -tg6 -I00 -S'7t{\x80\xa8]\x13@\xccu\xfa\xaa\x83\x16\xf7\xbf\xc5\x08\t\xe6\xe8\x16\xd5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1152 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1153 -(dp1154 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1155 -(I1 -(I3 -tg6 -I00 -S":\x02Lt\xa2\x97\x15@\xe1\xac>\x02'd\xf6\xbfe\x8f\x1aX\xcb\x81\xd9@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1156 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1157 -(dp1158 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1159 -(I1 -(I3 -tg6 -I00 -S'\xba\x1f\x86|J~\x16@\x95\xb1\xfa\x9d\xca\xfd\xf8?=N\x05\x81\xf16\x06A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1160 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1161 -(dp1162 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1163 -(I1 -(I3 -tg6 -I00 -S'h\x07\r\x1a\x02{\x18@Q\r.\x08?\x9f\xf4\xbf\x02\xbf(\xe4\x9f\x8e\xe8@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1164 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1165 -(dp1166 -g16 -g1121 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1167 -(I1 -(I3 -tg6 -I00 -S'\xa8\x97\xe4\xf2\xb0\xd7\x1a@\xee`)@\xe1\xd3\xd3?\xd2\xd54~Cd\x07A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1168 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp1169 -a(dp1170 -g60 -g61 -(g62 -(I0 -tS'b' -tRp1171 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1172 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp1173 -aa(lp1174 -g4 -(g6 -S'&\xa1\x0f\x99\xac\x9a\xc4@' -tRp1175 -ag8 -(g9 -g10 -(lp1176 -g8 -(g12 -g13 -NtRp1177 -(dp1178 -g16 -g8 -(g17 -g13 -NtRp1179 -(dp1180 -g20 -F5 -sg21 -(dp1181 -g20 -(F5 -g23 -tp1182 -sg25 -(F21.299999 -g23 -tp1183 -sg27 -(F4 -g23 -tp1184 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp1185 -(I1 -(I3 -tg6 -I00 -S'\x91\x1b\xfa\x12\xda\x12\xf7?i\x9aX\xf0\x9f"\xf3\xbf\x7f\xef\x8f\xce\x07\x7f\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1186 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1187 -(dp1188 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1189 -(I1 -(I3 -tg6 -I00 -S'/w\xb6\x99k\x81\x03@\xa5Z\xb8\xf06\x92\xee\xbfUE\xa1Z\xab\xbc\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1190 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1191 -(dp1192 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1193 -(I1 -(I3 -tg6 -I00 -S'\xd5\x1a\xd2o\xdd\xc0\x06@p\xd0\x96\x19B\xaf\xf6\xbf\x8a\xa0\x82\x0e&\x18\xd5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1194 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1195 -(dp1196 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1197 -(I1 -(I3 -tg6 -I00 -S'\x80\x08\xb6Q\x82\xea\x0c@\xbd\x01\xc1\xdd\\\xf6\xee\xbf4\xeb\xe0?q\x19\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1198 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1199 -(dp1200 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1201 -(I1 -(I3 -tg6 -I00 -S'\x08\xa2\xfe0Aq\x10@{\x0f\xfe\x8bU\xbe\xef\xbf<_$o\xb0\xb2\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1202 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1203 -(dp1204 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1205 -(I1 -(I3 -tg6 -I00 -S'\x8a2\xc0H\xcc1\x12@\x84\x1c\xba\xc3\xb1\x13\xef\xbf\x99\xf1\xd32I\xad\xf3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1206 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1207 -(dp1208 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1209 -(I1 -(I3 -tg6 -I00 -S'V0\xeb8\x7f_\x13@\xdb\xe9\xe0/\x98\x03\xf7\xbf\xcbC\t.\xf9f\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1210 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1211 -(dp1212 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1213 -(I1 -(I3 -tg6 -I00 -S'\xb4W\x1fb\x16M\x16@\xae\x12j\x0c\xfb \xf9?\x0c\xc7%\xea>1\nA' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1214 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1215 -(dp1216 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1217 -(I1 -(I3 -tg6 -I00 -S'\xb4\x1e,,\xe1\x85\x18@P\x1c\xf4r{\xd4\xf6\xbfEm\xa2\xf72\xea\xe5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1218 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1219 -(dp1220 -g16 -g1179 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1221 -(I1 -(I3 -tg6 -I00 -S'\xe9=\x16\xc0\x8f\xd4\x1a@Q\xef\x81H\xfbc\xd8?\xb0v0\xbf\xce\xb6\x07A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1222 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp1223 -a(dp1224 -g60 -g61 -(g62 -(I0 -tS'b' -tRp1225 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1226 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp1227 -aa(lp1228 -g4 -(g6 -S'\xfa6\xee\xb2\xac\xae\xc5@' -tRp1229 -ag8 -(g9 -g10 -(lp1230 -g8 -(g12 -g13 -NtRp1231 -(dp1232 -g16 -g8 -(g17 -g13 -NtRp1233 -(dp1234 -g20 -F5 -sg21 -(dp1235 -g20 -(F5 -g23 -tp1236 -sg25 -(F21.299999 -g23 -tp1237 -sg27 -(F4 -g23 -tp1238 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp1239 -(I1 -(I3 -tg6 -I00 -S'\xfb\xe4\xd6\xb5\xb9\x14\xf7?5\xba\x9b]\x18\x1c\xf3\xbf\xe3\xc7\xb4!\x0f\x84\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1240 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1241 -(dp1242 -g16 -g1233 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1243 -(I1 -(I3 -tg6 -I00 -S'\xc8\x12\xfa\x0eO\x81\x03@AcZd\xfe\x87\xee\xbf\xee^\xa2\xd56\xbd\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1244 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1245 -(dp1246 -g16 -g1233 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1247 -(I1 -(I3 -tg6 -I00 -S'\xf5\xcf\xef_A\xc1\x06@\xef\xbc\xed-\xac\xae\xf6\xbf\x8b7\xea\xfd\xd6\x0b\xd5@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1248 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1249 -(dp1250 -g16 -g1233 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1251 -(I1 -(I3 -tg6 -I00 -S'\xe6\x13\xd6\x9e\x9b\xea\x0c@\n-;\xab\xa9\xed\xee\xbf\xb2<)\xed\x07\x1a\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1252 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1253 -(dp1254 -g16 -g1233 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1255 -(I1 -(I3 -tg6 -I00 -S'\xbeU\x9e\xd9^p\x10@\xa0\xe2Z`t<\xf0\xbf\xb8\xea5\xf3\xe4.\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1256 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1257 -(dp1258 -g16 -g1233 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1259 -(I1 -(I3 -tg6 -I00 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-g23 -tp1294 -sg25 -(F21.299999 -g23 -tp1295 -sg27 -(F4 -g23 -tp1296 -ssg27 -F4 -sg29 -I3 -sg25 -F21.299999 -sg30 -g32 -sg41 -g42 -sg48 -g49 -sg53 -g54 -sbsg60 -g61 -(g62 -(I0 -tS'b' -tRp1297 -(I1 -(I3 -tg6 -I00 -S'\x84;\x10\xda0\x0e\xf7?G\xdf\xee\x89\x1c<\xf3\xbf\xc0\x9fq\xf1X\x7f\xe1@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1298 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1299 -(dp1300 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1301 -(I1 -(I3 -tg6 -I00 -S'U\xdd2\xb5\xbb\x82\x03@\xb0g\xa4h\x07\xd0\xee\xbfl\xae\x19\xe2\xb6\xbb\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1302 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1303 -(dp1304 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1305 -(I1 -(I3 -tg6 -I00 -S"d\xad'\t|\xc2\x06@\x16hB\x12I\x08\xf6\xbf\xff-S\x07*u\xd4@" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1306 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1307 -(dp1308 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1309 -(I1 -(I3 -tg6 -I00 -S'\x15\x99\x0f.x\xea\x0c@\xa3N\xc0p\xc5\xf2\xee\xbf\x1a\xb0\xe4.\xed"\xf2@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1310 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1311 -(dp1312 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1313 -(I1 -(I3 -tg6 -I00 -S'<\xca^\xc6cq\x10@\xfd\xecO1\xce}\xef\xbfwN\xdb\x91\xbey\xeb@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1314 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1315 -(dp1316 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1317 -(I1 -(I3 -tg6 -I00 -S'-2\x16\x98\x992\x12@\xbb)\xbf\xe7w8\xef\xbf\xd2\x8d\xe6\xe9"\xf2\xf3@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1318 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1319 -(dp1320 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1321 -(I1 -(I3 -tg6 -I00 -S'\xd5\xadwJ\xff[\x13@\xffCjJ\xc9/\xf7\xbf\x81\xfbVR\xe5\xbc\xd4@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1322 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1323 -(dp1324 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1325 -(I1 -(I3 -tg6 -I00 -S' \xa0\x84\xe2R\xa8\x15@\x9d\xcd\x0f\xfe\xca\xcd\xf1\xbf/\x81u\xc4l\x0e\xef@' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1326 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1327 -(dp1328 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1329 -(I1 -(I3 -tg6 -I00 -S"\xde\x03/&[\xb2\x17@0\x01=#\n\x1d\xf9?'\xa8\xfc\xfb}\xd4\x07A" -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1330 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbag8 -(g12 -g13 -NtRp1331 -(dp1332 -g16 -g1291 -sg60 -g61 -(g62 -(I0 -tS'b' -tRp1333 -(I1 -(I3 -tg6 -I00 -S'\x86\xe1\xce\xec\x1e\xf4\x1a@g\x1e\xa1\xb0\xa5+\xad?\x95\xef\xa1\xfb\x90\x9b\x04A' -tbsg64 -I01 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1334 -(I1 -(I3 -tg67 -I00 -S'\x01\x01\x01' -tbsg68 -I00 -sbatRp1335 -a(dp1336 -g60 -g61 -(g62 -(I0 -tS'b' -tRp1337 -(I1 -(I0 -tg6 -I00 -S'' -tbsg64 -I00 -sg65 -g61 -(g62 -(I0 -tS'b' -tRp1338 -(I1 -(I0 -tg67 -I00 -S'' -tbsg68 -I00 -sag4 -(g6 -S"`\xa6'\xc5\t\xe1\xc2?" -tRp1339 -aaaS"History written: Wed Jul 1 10:01:37 2015\nproduced by luke\ndiffpy.srmise version 0.5.2\n##### PDF Peak Extraction\n## BaselineFunctions\n# BaselineFunction 0\nfunction='FromSequence'\nmodule='diffpy.srmise.baselines.fromsequence'\nbase=None\ny=[-1475.0325650706627, -2950.0651301413254, -4425.0976952119881, -5900.1302602826509, -7375.1628253533127, -8850.1953904239745, -10325.227955494638, -11800.260520565302, -13275.293085635964, -14750.325650706625, -16225.358215777289, -17700.390780847953, -19175.423345918618, -20650.455910989276, -22125.488476059942, -23600.521041130603, -25075.553606201265, -26550.586171271931, -28025.459933459599, -29490.66450359999, -30922.864389112267, -32298.695523408274, -33596.022711102938, -34793.92402828217, -35872.675222770908, -36813.734114401064, -37599.724995279517, -38214.42303005611, -38643.368779986711, -38890.463187607907, -38978.523165803032, -38930.29758324947, -38767.462434741778, -38510.636440923663, -38179.39664801996, -37792.294027568765, -37366.869076153373, -36919.66741513431, -36465.762314723048, -36011.685031151355, -35557.60774757967, -35103.530464007978, -34649.453180436292, -34195.375896864593, -33741.298613292922, -33287.221329721207, -32833.144046149522, -32379.066762577819, -31924.989479006141, -31470.912195434459, -31016.83491186277, -30562.757628291063, -30108.680344719356, -29654.603061147711, -29200.525777575986, -28746.448494004322, -28292.371210432615, -27838.293926860926, -27384.216643289248, -26930.139359411234, -26474.542488478357, -26010.083575850655, -25528.358372275903, -25021.398910324362, -24481.667989050857, -23902.053658656267, -23275.863705149979, -22596.820135010832, -21859.053659849822, -21057.103538030915, -20189.157506289514, -19262.2608478449, -18284.582204221027, -17263.909088500266, -16207.653400662406, -15122.856942922259, -14016.196935068139, -12893.991529799485, -11762.205328065833, -10626.439769837914, -9490.3191584519027, -8354.1985470658783, -7218.0779356797575, -6081.9573242938068, -4945.8367129076605, -3809.7161015215393, -2673.5954901353934, -1537.4748787493209, -401.35426736339457, 734.76028191512512, 1862.3074495985777, 2947.158200990089, 3960.1884858314311, 4888.6048315275966, 5719.7202101002222, 6439.2477046714184, 7031.3497219455321, 7478.6872046947792, 7762.4688442382803, 7862.653161699448]\nx=[0.10000000000000001, 0.20000000000000001, 0.30000000000000004, 0.40000000000000002, 0.5, 0.59999999999999998, 0.70000000000000007, 0.80000000000000004, 0.90000000000000002, 1.0, 1.1000000000000001, 1.2000000000000002, 1.3000000000000003, 1.4000000000000001, 1.5000000000000002, 1.6000000000000001, 1.7000000000000002, 1.8000000000000003, 1.9000000000000001, 2.0, 2.1000000000000001, 2.2000000000000002, 2.3000000000000003, 2.4000000000000004, 2.5000000000000004, 2.6000000000000001, 2.7000000000000002, 2.8000000000000003, 2.9000000000000004, 3.0000000000000004, 3.1000000000000001, 3.2000000000000002, 3.3000000000000003, 3.4000000000000004, 3.5000000000000004, 3.6000000000000001, 3.7000000000000002, 3.8000000000000003, 3.9000000000000004, 4.0, 4.0999999999999996, 4.2000000000000002, 4.2999999999999998, 4.3999999999999995, 4.5, 4.5999999999999996, 4.7000000000000002, 4.7999999999999998, 4.9000000000000004, 5.0, 5.0999999999999996, 5.2000000000000002, 5.2999999999999998, 5.4000000000000004, 5.5, 5.5999999999999996, 5.7000000000000002, 5.7999999999999998, 5.9000000000000004, 6.0, 6.0999999999999996, 6.2000000000000002, 6.2999999999999998, 6.4000000000000004, 6.5, 6.5999999999999996, 6.7000000000000002, 6.7999999999999998, 6.9000000000000004, 7.0, 7.0999999999999996, 7.2000000000000002, 7.2999999999999998, 7.4000000000000004, 7.5, 7.5999999999999996, 7.7000000000000002, 7.7999999999999998, 7.9000000000000004, 8.0, 8.0999999999999996, 8.1999999999999993, 8.3000000000000007, 8.4000000000000004, 8.5, 8.5999999999999996, 8.6999999999999993, 8.8000000000000007, 8.9000000000000004, 9.0, 9.0999999999999996, 9.1999999999999993, 9.3000000000000007, 9.4000000000000004, 9.5, 9.5999999999999996, 9.7000000000000011, 9.8000000000000007, 9.9000000000000004, 10.0]\n\n## PeakFunctions\n# PeakFunction 0\nfunction='GaussianOverR'\nmodule='diffpy.srmise.peaks.gaussianoverr'\nbase=None\nmaxwidth=0.7\n\n# PeakFunction 1\nfunction='TerminationRipples'\nmodule='diffpy.srmise.peaks.terminationripples'\nbase=0\nsupersample=5.0\nqmax=21.299999\nextension=4.0\n\n# BaselineObject\nowner=0\npars=[]\nfree=[]\nremovable=False\nstatic_owner=False\n\n## InitialPeaks\n# SrMiseMetadata\npf=[0]\ncres=0.05\nModelEvaluator=AIC\nRange=[1.0, 7.25]\n# Metadata\nfilename='/home/luke/Workspaces/MSU_Research/diffpy.srmise/doc/examples/data/C60_fine_qmax21.gr'\nnyquist=True\nqmax=21.299999\nqmax_reportedbypdf=21.299999\nqmax_fromdata=20.755266780473114\nscale=False\nsupersample=4.0\n\n##### start data\n#L x y dx dy edy\n0.01 18942.6 0 8.53691 11653.4\n0.02 37722.7 0 16.7546 11653.4\n0.03 56177.6 0 24.347 11653.4\n0.04 74143.9 0 31.0336 11653.4\n0.05 91457.9 0 36.571 11653.4\n0.06 107956 0 40.7633 11653.4\n0.07 123476 0 43.4706 11653.4\n0.08 137856 0 44.6161 11653.4\n0.09 150940 0 44.191 11653.4\n0.1 162578 0 42.2588 11653.4\n0.11 172629 0 38.9611 11653.4\n0.12 180964 0 34.5282 11653.4\n0.13 187472 0 29.307 11653.4\n0.14 192060 0 23.8359 11653.4\n0.15 194658 0 19.0276 11653.4\n0.16 195226 0 16.3851 11653.4\n0.17 193750 0 17.2383 11653.4\n0.18 190254 0 20.9462 11653.4\n0.19 184793 0 25.822 11653.4\n0.2 177460 0 30.698 11653.4\n0.21 168386 0 34.9379 11653.4\n0.22 157737 0 38.1842 11653.4\n0.23 145712 0 40.2361 11653.4\n0.24 132543 0 41.0033 11653.4\n0.25 118488 0 40.4884 11653.4\n0.26 103827 0 38.7838 11653.4\n0.27 88856.5 0 36.0754 11653.4\n0.28 73881.6 0 32.6565 11653.4\n0.29 59209 0 28.9558 11653.4\n0.3 45139.3 0 25.5728 11653.4\n0.31 31959.2 0 23.2628 11653.4\n0.32 19933.4 0 22.7026 11653.4\n0.33 9297.65 0 24.0285 11653.4\n0.34 251.704 0 26.7081 11653.4\n0.35 -7046.27 0 29.9659 11653.4\n0.36 -12484.5 0 33.1496 11653.4\n0.37 -16000.8 0 35.809 11653.4\n0.38 -17584.8 0 37.6619 11653.4\n0.39 -17278 0 38.5549 11653.4\n0.4 -15172.9 0 38.4411 11653.4\n0.41 -11410.1 0 37.3693 11653.4\n0.42 -6173.99 0 35.4819 11653.4\n0.43 312.641 0 33.0201 11653.4\n0.44 7795.7 0 30.331 11653.4\n0.45 15997.5 0 27.8677 11653.4\n0.46 24625.2 0 26.1426 11653.4\n0.47 33380 0 25.5822 11653.4\n0.48 41966.4 0 26.3124 11653.4\n0.49 50100.7 0 28.0791 11653.4\n0.5 57520.3 0 30.4057 11653.4\n0.51 63990.9 0 32.8044 11653.4\n0.52 69313.7 0 34.886 11653.4\n0.53 73330.8 0 36.3811 11653.4\n0.54 75929.5 0 37.131 11653.4\n0.55 77044.7 0 37.0761 11653.4\n0.56 76660.3 0 36.2478 11653.4\n0.57 74808.1 0 34.7652 11653.4\n0.58 71565.9 0 32.8355 11653.4\n0.59 67053.6 0 30.7514 11653.4\n0.6 61428.1 0 28.8765 11653.4\n0.61 54877.1 0 27.5925 11653.4\n0.62 47611.7 0 27.1928 11653.4\n0.63 39858.8 0 27.7571 11653.4\n0.64 31853 0 29.1121 11653.4\n0.65 23828 0 30.9201 11653.4\n0.66 16008.6 0 32.8095 11653.4\n0.67 8603.69 0 34.4622 11653.4\n0.68 1798.99 0 35.646 11653.4\n0.69 -4248.35 0 36.2199 11653.4\n0.7 -9414.3 0 36.1298 11653.4\n0.71 -13611.1 0 35.4048 11653.4\n0.72 -16789.1 0 34.1541 11653.4\n0.73 -18936.8 0 32.5637 11653.4\n0.74 -20079.9 0 30.8888 11653.4\n0.75 -20278.6 0 29.4309 11653.4\n0.76 -19624.1 0 28.4858 11653.4\n0.77 -18233.7 0 28.2603 11653.4\n0.78 -16245 0 28.7926 11653.4\n0.79 -13810.2 0 29.9374 11653.4\n0.8 -11089.1 0 31.4287 11653.4\n0.81 -8242.85 0 32.9701 11653.4\n0.82 -5427.21 0 34.3007 11653.4\n0.83 -2786.99 0 35.2261 11653.4\n0.84 -450.548 0 35.6277 11653.4\n0.85 1474.5 0 35.4644 11653.4\n0.86 2904.71 0 34.7693 11653.4\n0.87 3783.01 0 33.6482 11653.4\n0.88 4079.74 0 32.2736 11653.4\n0.89 3792.54 0 30.8738 11653.4\n0.9 2944.99 0 29.7056 11653.4\n0.91 1584.28 0 29.0051 11653.4\n0.92 -222.159 0 28.9205 11653.4\n0.93 -2390.68 0 29.4595 11653.4\n0.94 -4826.07 0 30.4869 11653.4\n0.95 -7426.55 0 31.7771 11653.4\n0.96 -10088.8 0 33.0821 11653.4\n0.97 -12713 0 34.1826 11653.4\n0.98 -15207.3 0 34.9156 11653.4\n0.99 -17492 0 35.1842 11653.4\n1 -19503 0 34.9606 11653.4\n1.01 -21193.7 0 34.2847 11653.4\n1.02 -22537 0 33.2613 11653.4\n1.03 -23525.9 0 32.053 11653.4\n1.04 -24172 0 30.8661 11653.4\n1.05 -24504.7 0 29.9216 11653.4\n1.06 -24568.6 0 29.4096 11653.4\n1.07 -24419.8 0 29.435 11653.4\n1.08 -24122.2 0 29.9825 11653.4\n1.09 -23743.2 0 30.9231 11653.4\n1.1 -23349 0 32.0586 11653.4\n1.11 -23000.1 0 33.1763 11653.4\n1.12 -22747 0 34.0897 11653.4\n1.13 -22626 0 34.6619 11653.4\n1.14 -22656.6 0 34.8154 11653.4\n1.15 -22838.5 0 34.5356 11653.4\n1.16 -23150.5 0 33.8694 11653.4\n1.17 -23550 0 32.922 11653.4\n1.18 -23973.8 0 31.8483 11653.4\n1.19 -24339.8 0 30.8363 11653.4\n1.2 -24550.2 0 30.0775 11653.4\n1.21 -24495 0 29.7246 11653.4\n1.22 -24056.8 0 29.8486 11653.4\n1.23 -23116.2 0 30.4155 11653.4\n1.24 -21557.6 0 31.2994 11653.4\n1.25 -19274.7 0 32.3219 11653.4\n1.26 -16176.8 0 33.2965 11653.4\n1.27 -12193.8 0 34.0627 11653.4\n1.28 -7281.75 0 34.5058 11653.4\n1.29 -1426.42 0 34.5652 11653.4\n1.3 5353.3 0 34.2379 11653.4\n1.31 13003.6 0 33.5775 11653.4\n1.32 21435 0 32.6893 11653.4\n1.33 30523.3 0 31.7209 11653.4\n1.34 40111.4 0 30.8441 11653.4\n1.35 50013.2 0 30.225 11653.4\n1.36 60017.9 0 29.9866 11653.4\n1.37 69896.1 0 30.1742 11653.4\n1.38 79406.9 0 30.7413 11653.4\n1.39 88304.8 0 31.5659 11653.4\n1.4 96348 0 32.4856 11653.4\n1.41 103306 0 33.3355 11653.4\n1.42 108970 0 33.9764 11653.4\n1.43 113155 0 34.312 11653.4\n1.44 115713 0 34.2965 11653.4\n1.45 116534 0 33.9373 11653.4\n1.46 115552 0 33.2933 11653.4\n1.47 112750 0 32.4696 11653.4\n1.48 108158 0 31.6062 11653.4\n1.49 101857 0 30.8589 11653.4\n1.5 93973.5 0 30.3705 11653.4\n1.51 84679 0 30.2374 11653.4\n1.52 74183.6 0 30.4828 11653.4\n1.53 62730.5 0 31.0503 11653.4\n1.54 50588.5 0 31.8217 11653.4\n1.55 38044 0 32.6485 11653.4\n1.56 25391.8 0 33.3847 11653.4\n1.57 12926.4 0 33.9104 11653.4\n1.58 932.466 0 34.1461 11653.4\n1.59 -10323.7 0 34.0596 11653.4\n1.6 -20602.4 0 33.668 11653.4\n1.61 -29697.7 0 33.0355 11653.4\n1.62 -37443.6 0 32.2668 11653.4\n1.63 -43718.3 0 31.4948 11653.4\n1.64 -48447.8 0 30.8606 11653.4\n1.65 -51607 0 30.486 11653.4\n1.66 -53219.5 0 30.444 11653.4\n1.67 -53355.7 0 30.7394 11653.4\n1.68 -52129.5 0 31.3074 11653.4\n1.69 -49693 0 32.033 11653.4\n1.7 -46230.6 0 32.7797 11653.4\n1.71 -41951.5 0 33.4173 11653.4\n1.72 -37082.2 0 33.8426 11653.4\n1.73 -31857.8 0 33.9912 11653.4\n1.74 -26513.5 0 33.8433 11653.4\n1.75 -21276.4 0 33.4249 11653.4\n1.76 -16357.9 0 32.805 11653.4\n1.77 -11945.9 0 32.0878 11653.4\n1.78 -8199.74 0 31.3994 11653.4\n1.79 -5244.58 0 30.8672 11653.4\n1.8 -3168.44 0 30.5942 11653.4\n1.81 -2020.1 0 30.6332 11653.4\n1.82 -1808.73 0 30.9733 11653.4\n1.83 -2505.02 0 31.5432 11653.4\n1.84 -4043.73 0 32.2308 11653.4\n1.85 -6327.61 0 32.9098 11653.4\n1.86 -9232.41 0 33.464 11653.4\n1.87 -12612.9 0 33.8044 11653.4\n1.88 -16309.4 0 33.8798 11653.4\n1.89 -20154.9 0 33.6813 11653.4\n1.9 -23982.3 0 33.2426 11653.4\n1.91 -27631.4 0 32.6362 11653.4\n1.92 -30955 0 31.9652 11653.4\n1.93 -33825.5 0 31.3483 11653.4\n1.94 -36139.1 0 30.9002 11653.4\n1.95 -37819.9 0 30.7067 11653.4\n1.96 -38822.6 0 30.804 11653.4\n1.97 -39133.3 0 31.1691 11653.4\n1.98 -38769.7 0 31.7268 11653.4\n1.99 -37779.1 0 32.3689 11653.4\n2 -36236.3 0 32.979 11653.4\n2.01 -34239.2 0 33.4534 11653.4\n2.02 -31903.8 0 33.7162 11653.4\n2.03 -29358.9 0 33.7281 11653.4\n2.04 -26739.8 0 33.4898 11653.4\n2.05 -24181.7 0 33.0417 11653.4\n2.06 -21813.7 0 32.4591 11653.4\n2.07 -19752.2 0 31.8427 11653.4\n2.08 -18095.5 0 31.3035 11653.4\n2.09 -16919.2 0 30.943 11653.4\n2.1 -16272 0 30.8304 11653.4\n2.11 -16173 0 30.9862 11653.4\n2.12 -16610.4 0 31.3767 11653.4\n2.13 -17541.3 0 31.9234 11653.4\n2.14 -18892.7 0 32.5224 11653.4\n2.15 -20564 0 33.0666 11653.4\n2.16 -22430.5 0 33.4642 11653.4\n2.17 -24348.5 0 33.6515 11653.4\n2.18 -26160.4 0 33.6004 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32.1323 11653.4\n16.85 3234.49 0 32.1165 11653.4\n16.86 3373.33 0 32.1334 11653.4\n16.87 3538.79 0 32.1799 11653.4\n16.88 3724.52 0 32.2476 11653.4\n16.89 3923.38 0 32.3243 11653.4\n16.9 4127.8 0 32.3962 11653.4\n16.91 4330.1 0 32.4506 11653.4\n16.92 4522.83 0 32.4779 11653.4\n16.93 4699.11 0 32.4733 11653.4\n16.94 4852.94 0 32.4376 11653.4\n16.95 4979.41 0 32.3772 11653.4\n16.96 5074.99 0 32.3027 11653.4\n16.97 5137.62 0 32.2275 11653.4\n16.98 5166.82 0 32.165 11653.4\n16.99 5163.7 0 32.1265 11653.4\n17 5130.92 0 32.1189 11653.4\n17.01 5072.51 0 32.1435 11653.4\n17.02 4993.77 0 32.1959 11653.4\n17.03 4900.94 0 32.2666 11653.4\n17.04 4800.96 0 32.3428 11653.4\n17.05 4701.17 0 32.4109 11653.4\n17.06 4608.91 0 32.4589 11653.4\n17.07 4531.26 0 32.4783 11653.4\n17.08 4474.64 0 32.4657 11653.4\n17.09 4444.59 0 32.4234 11653.4\n17.1 4445.46 0 32.3589 11653.4\n17.11 4480.21 0 32.2836 11653.4\n17.12 4550.3 0 32.2109 11653.4\n17.13 4655.56 0 32.1539 11653.4\n17.14 4794.25 0 32.1229 11653.4\n17.15 4963.06 0 32.1234 11653.4\n17.16 5157.31 0 32.1553 11653.4\n17.17 5371.1 0 32.2128 11653.4\n17.18 5597.56 0 32.2855 11653.4\n17.19 5829.21 0 32.3604 11653.4\n17.2 6058.21 0 32.424 11653.4\n17.21 6276.74 0 32.4652 11653.4\n17.22 6477.37 0 32.4767 11653.4\n17.23 6653.33 0 32.4564 11653.4\n17.24 6798.86 0 32.4081 11653.4\n17.25 6909.46 0 32.3403 11653.4\n17.26 6982.07 0 32.265 11653.4\n17.27 7015.24 0 32.1957 11653.4\n17.28 7009.22 0 32.1448 11653.4\n17.29 6965.88 0 32.1215 11653.4\n17.3 6888.73 0 32.1299 11653.4\n17.31 6782.71 0 32.1686 11653.4\n17.32 6654.01 0 32.2305 11653.4\n17.33 6509.79 0 32.3044 11653.4\n17.34 6357.86 0 32.3771 11653.4\n17.35 6206.37 0 32.4355 11653.4\n17.36 6063.4 0 32.4695 11653.4\n17.37 5936.64 0 32.4731 11653.4\n17.38 5833.03 0 32.4455 11653.4\n17.39 5758.45 0 32.3918 11653.4\n17.4 5717.45 0 32.3215 11653.4\n17.41 5713.02 0 32.2471 11653.4\n17.42 5746.44 0 32.1818 11653.4\n17.43 5817.25 0 32.1375 11653.4\n17.44 5923.2 0 32.1221 11653.4\n17.45 6060.34 0 32.1384 11653.4\n17.46 6223.18 0 32.1834 11653.4\n17.47 6404.92 0 32.2489 11653.4\n17.48 6597.72 0 32.3231 11653.4\n17.49 6793 0 32.3928 11653.4\n17.5 6981.85 0 32.4456 11653.4\n17.51 7155.4 0 32.4721 11653.4\n17.52 7305.13 0 32.4678 11653.4\n17.53 7423.35 0 32.4333 11653.4\n17.54 7503.45 0 32.3749 11653.4\n17.55 7540.2 0 32.3029 11653.4\n17.56 7530.04 0 32.2301 11653.4\n17.57 7471.15 0 32.1696 11653.4\n17.58 7363.65 0 32.1322 11653.4\n17.59 7209.5 0 32.1246 11653.4\n17.6 7012.5 0 32.1483 11653.4\n17.61 6778.14 0 32.1989 11653.4\n17.62 6513.31 0 32.2672 11653.4\n17.63 6226.12 0 32.341 11653.4\n17.64 5925.47 0 32.407 11653.4\n17.65 5620.74 0 32.4536 11653.4\n17.66 5321.38 0 32.4726 11653.4\n17.67 5036.49 0 32.4606 11653.4\n17.68 4774.49 0 32.4199 11653.4\n17.69 4542.73 0 32.3576 11653.4\n17.7 4347.18 0 32.2848 11653.4\n17.71 4192.2 0 32.2145 11653.4\n17.72 4080.32 0 32.1593 11653.4\n17.73 4012.21 0 32.1291 11653.4\n17.74 3986.57 0 32.1294 11653.4\n17.75 4000.26 0 32.1601 11653.4\n17.76 4048.38 0 32.2155 11653.4\n17.77 4124.56 0 32.2857 11653.4\n17.78 4221.17 0 32.358 11653.4\n17.79 4329.7 0 32.4195 11653.4\n17.8 4441.1 0 32.4594 11653.4\n17.81 4546.23 0 32.4706 11653.4\n17.82 4636.2 0 32.4513 11653.4\n17.83 4702.82 0 32.4048 11653.4\n17.84 4738.91 0 32.3394 11653.4\n17.85 4738.67 0 32.2667 11653.4\n17.86 4697.91 0 32.1998 11653.4\n17.87 4614.25 0 32.1506 11653.4\n17.88 4487.23 0 32.128 11653.4\n17.89 4318.34 0 32.1361 11653.4\n17.9 4110.96 0 32.1734 11653.4\n17.91 3870.24 0 32.2331 11653.4\n17.92 3602.85 0 32.3043 11653.4\n17.93 3316.7 0 32.3744 11653.4\n17.94 3020.63 0 32.4309 11653.4\n17.95 2723.97 0 32.4637 11653.4\n17.96 2436.18 0 32.4671 11653.4\n17.97 2166.41 0 32.4406 11653.4\n17.98 1923.05 0 32.3888 11653.4\n17.99 1713.45 0 32.321 11653.4\n18 1543.49 0 32.2492 11653.4\n18.01 1417.33 0 32.1863 11653.4\n18.02 1337.24 0 32.1436 11653.4\n18.03 1303.42 0 32.1288 11653.4\n18.04 1314.04 0 32.1445 11653.4\n18.05 1365.2 0 32.188 11653.4\n18.06 1451.16 0 32.2512 11653.4\n18.07 1564.51 0 32.3229 11653.4\n18.08 1696.51 0 32.3901 11653.4\n18.09 1837.41 0 32.4409 11653.4\n18.1 1976.88 0 32.4665 11653.4\n18.11 2104.46 0 32.4622 11653.4\n18.12 2209.97 0 32.4288 11653.4\n18.13 2284.02 0 32.3724 11653.4\n18.14 2318.33 0 32.3028 11653.4\n18.15 2306.2 0 32.2326 11653.4\n18.16 2242.75 0 32.1742 11653.4\n18.17 2125.18 0 32.1382 11653.4\n18.18 1952.94 0 32.1311 11653.4\n18.19 1727.77 0 32.1542 11653.4\n18.2 1453.66 0 32.2032 11653.4\n18.21 1136.76 0 32.2692 11653.4\n18.22 785.087 0 32.3405 11653.4\n18.23 408.306 0 32.4042 11653.4\n18.24 17.3 0 32.4491 11653.4\n18.25 -376.231 0 32.4673 11653.4\n18.26 -760.244 0 32.4555 11653.4\n18.27 -1122.84 0 32.4159 11653.4\n18.28 -1452.72 0 32.3556 11653.4\n18.29 -1739.72 0 32.2851 11653.4\n18.3 -1975.13 0 32.2172 11653.4\n18.31 -2152.17 0 32.1639 11653.4\n18.32 -2266.2 0 32.1349 11653.4\n18.33 -2314.98 0 32.1354 11653.4\n18.34 -2298.75 0 32.1652 11653.4\n18.35 -2220.3 0 32.219 11653.4\n18.36 -2084.82 0 32.287 11653.4\n18.37 -1899.76 0 32.3571 11653.4\n18.38 -1674.56 0 32.4166 11653.4\n18.39 -1420.26 0 32.4552 11653.4\n18.4 -1149.12 0 32.4659 11653.4\n18.41 -874.14 0 32.447 11653.4\n18.42 -608.556 0 32.4017 11653.4\n18.43 -365.325 0 32.3382 11653.4\n18.44 -156.631 0 32.2677 11653.4\n18.45 6.5947 0 32.2027 11653.4\n18.46 115.092 0 32.155 11653.4\n18.47 161.637 0 32.1331 11653.4\n18.48 141.321 0 32.141 11653.4\n18.49 51.7431 0 32.1772 11653.4\n18.5 -106.9 0 32.2351 11653.4\n18.51 -331.821 0 32.3043 11653.4\n18.52 -617.751 0 32.3723 11653.4\n18.53 -957.147 0 32.4272 11653.4\n18.54 -1340.49 0 32.4592 11653.4\n18.55 -1756.63 0 32.4626 11653.4\n18.56 -2193.27 0 32.437 11653.4\n18.57 -2637.39 0 32.3869 11653.4\n18.58 -3075.76 0 32.3212 11653.4\n18.59 -3495.46 0 32.2515 11653.4\n18.6 -3884.37 0 32.1903 11653.4\n18.61 -4231.6 0 32.1487 11653.4\n18.62 -4527.93 0 32.134 11653.4\n18.63 -4766.13 0 32.149 11653.4\n18.64 -4941.21 0 32.1908 11653.4\n18.65 -5050.61 0 32.2518 11653.4\n18.66 -5094.26 0 32.3211 11653.4\n18.67 -5074.55 0 32.3862 11653.4\n18.68 -4996.22 0 32.4357 11653.4\n18.69 -4866.15 0 32.4606 11653.4\n18.7 -4693.06 0 32.4567 11653.4\n18.71 -4487.17 0 32.4248 11653.4\n18.72 -4259.77 0 32.3704 11653.4\n18.73 -4022.79 0 32.3033 11653.4\n18.74 -3788.29 0 32.2355 11653.4\n18.75 -3568.06 0 32.1789 11653.4\n18.76 -3373.12 0 32.144 11653.4\n18.77 -3213.32 0 32.1369 11653.4\n18.78 -3097.01 0 32.1588 11653.4\n18.79 -3030.69 0 32.2058 11653.4\n18.8 -3018.83 0 32.2694 11653.4\n18.81 -3063.72 0 32.3381 11653.4\n18.82 -3165.45 0 32.3996 11653.4\n18.83 -3321.89 0 32.443 11653.4\n18.84 -3528.87 0 32.4607 11653.4\n18.85 -3780.35 0 32.4496 11653.4\n18.86 -4068.7 0 32.4116 11653.4\n18.87 -4385.04 0 32.3535 11653.4\n18.88 -4719.58 0 32.2857 11653.4\n18.89 -5062.05 0 32.2202 11653.4\n18.9 -5402.09 0 32.1688 11653.4\n18.91 -5729.65 0 32.1408 11653.4\n18.92 -6035.4 0 32.1412 11653.4\n18.93 -6311.02 0 32.1698 11653.4\n18.94 -6549.56 0 32.2215 11653.4\n18.95 -6745.62 0 32.2869 11653.4\n18.96 -6895.57 0 32.3543 11653.4\n18.97 -6997.59 0 32.4115 11653.4\n18.98 -7051.75 0 32.4486 11653.4\n18.99 -7059.89 0 32.459 11653.4\n19 -7025.57 0 32.4408 11653.4\n19.01 -6953.81 0 32.3973 11653.4\n19.02 -6850.9 0 32.3362 11653.4\n19.03 -6724.11 0 32.2685 11653.4\n19.04 -6581.35 0 32.2062 11653.4\n19.05 -6430.86 0 32.1605 11653.4\n19.06 -6280.88 0 32.1397 11653.4\n19.07 -6139.3 0 32.1474 11653.4\n19.08 -6013.41 0 32.1823 11653.4\n19.09 -5909.57 0 32.238 11653.4\n19.1 -5833.05 0 32.3045 11653.4\n19.11 -5787.81 0 32.3698 11653.4\n19.12 -5776.44 0 32.4223 11653.4\n19.13 -5800.06 0 32.4527 11653.4\n19.14 -5858.34 0 32.4556 11653.4\n19.15 -5949.59 0 32.4306 11653.4\n19.16 -6070.85 0 32.3822 11653.4\n19.17 -6218.05 0 32.3188 11653.4\n19.18 -6386.23 0 32.2518 11653.4\n19.19 -6569.75 0 32.1932 11653.4\n19.2 -6762.56 0 32.1536 11653.4\n19.21 -6958.4 0 32.14 11653.4\n19.22 -7151.1 0 32.155 11653.4\n19.23 -7334.79 0 32.1957 11653.4\n19.24 -7504.11 0 32.2548 11653.4\n19.25 -7654.38 0 32.3217 11653.4\n19.26 -7781.76 0 32.3843 11653.4\n19.27 -7883.34 0 32.4316 11653.4\n19.28 -7957.17 0 32.4551 11653.4\n19.29 -8002.34 0 32.4508 11653.4\n19.3 -8018.88 0 32.4194 11653.4\n19.31 -8007.73 0 32.3666 11653.4\n19.32 -7970.65 0 32.3016 11653.4\n19.33 -7910.05 0 32.2361 11653.4\n19.34 -7828.9 0 32.1818 11653.4\n19.35 -7730.54 0 32.1485 11653.4\n19.36 -7618.5 0 32.1423 11653.4\n19.37 -7496.39 0 32.1641 11653.4\n19.38 -7367.73 0 32.21 11653.4\n19.39 -7235.81 0 32.2718 11653.4\n19.4 -7103.58 0 32.3383 11653.4\n19.41 -6973.61 0 32.3976 11653.4\n19.42 -6847.96 0 32.4392 11653.4\n19.43 -6728.22 0 32.4557 11653.4\n19.44 -6615.48 0 32.4444 11653.4\n19.45 -6510.36 0 32.407 11653.4\n19.46 -6413.05 0 32.3505 11653.4\n19.47 -6323.38 0 32.2846 11653.4\n19.48 -6240.9 0 32.2213 11653.4\n19.49 -6164.97 0 32.1719 11653.4\n19.5 -6094.82 0 32.1452 11653.4\n19.51 -6029.64 0 32.1461 11653.4\n19.52 -5968.68 0 32.1745 11653.4\n19.53 -5911.26 0 32.225 11653.4\n19.54 -5856.84 0 32.2887 11653.4\n19.55 -5805.05 0 32.3541 11653.4\n19.56 -5755.67 0 32.4095 11653.4\n19.57 -5708.63 0 32.4451 11653.4\n19.58 -5663.99 0 32.4547 11653.4\n19.59 -5621.85 0 32.4365 11653.4\n19.6 -5582.34 0 32.3939 11653.4\n19.61 -5545.55 0 32.3343 11653.4\n19.62 -5511.44 0 32.2684 11653.4\n19.63 -5479.79 0 32.2079 11653.4\n19.64 -5450.16 0 32.1637 11653.4\n19.65 -5421.84 0 32.1438 11653.4\n19.66 -5393.8 0 32.1517 11653.4\n19.67 -5364.75 0 32.186 11653.4\n19.68 -5333.07 0 32.2404 11653.4\n19.69 -5296.92 0 32.3052 11653.4\n19.7 -5254.27 0 32.3687 11653.4\n19.71 -5202.97 0 32.4196 11653.4\n19.72 -5140.85 0 32.4489 11653.4\n19.73 -5065.84 0 32.4515 11653.4\n19.74 -4976.03 0 32.427 11653.4\n19.75 -4869.85 0 32.3796 11653.4\n19.76 -4746.15 0 32.3179 11653.4\n19.77 -4604.26 0 32.2528 11653.4\n19.78 -4444.13 0 32.1959 11653.4\n19.79 -4266.32 0 32.1575 11653.4\n19.8 -4072.09 0 32.1446 11653.4\n19.81 -3863.38 0 32.1593 11653.4\n19.82 -3642.76 0 32.1991 11653.4\n19.83 -3413.38 0 32.2566 11653.4\n19.84 -3178.89 0 32.3216 11653.4\n19.85 -2943.31 0 32.3824 11653.4\n19.86 -2710.89 0 32.4282 11653.4\n19.87 -2485.95 0 32.4509 11653.4\n19.88 -2272.7 0 32.4465 11653.4\n19.89 -2075.1 0 32.4158 11653.4\n19.9 -1896.62 0 32.3643 11653.4\n19.91 -1740.17 0 32.3011 11653.4\n19.92 -1607.88 0 32.2375 11653.4\n19.93 -1501.07 0 32.1849 11653.4\n19.94 -1420.09 0 32.1527 11653.4\n19.95 -1364.33 0 32.1469 11653.4\n19.96 -1332.23 0 32.1683 11653.4\n19.97 -1321.27 0 32.2131 11653.4\n19.98 -1328.11 0 32.2732 11653.4\n19.99 -1348.67 0 32.3378 11653.4\n##### Results\nextraction_type='extract'\n### ModelCluster\npeak_funcs=[0]\nModelEvaluator=AIC\nslice=slice(None, 43, None)\n# BaselineObject\nowner=0\npars=[]\nfree=[]\nremovable=False\nstatic_owner=False\n\n## ModelPeaks\n# ModelPeak\nowner=1\npars=[1.4409645574666863, -1.2021756542216779, 35834.779473125469]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[2.438834586729778, -0.96289415777140697, 76731.43020027288]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[2.8449631419404557, -1.377022811246666, 20948.656697077673]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[3.6144870375166058, -0.96713516256064158, 74286.823948562524]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[4.1107321734767162, -0.98410710936823842, 56269.955304768802]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[4.5494140399501193, -0.9756431127837496, 81698.18210463904]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[4.8398410449548992, -1.4491665751304479, 21235.583150621042]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[5.4143786805580305, -1.1127424167906164, 63603.398981811821]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[5.9241758314319366, 1.5695897461410588, 195215.74804049844]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n# ModelPeak\nowner=1\npars=[6.7383992196340667, 0.05697362691040269, 168818.12286746191]\nfree=[True, True, True]\nremovable=True\nstatic_owner=False\n\n### start data\n#L r y dy\n1 -19502.9 11653.4\n1.14749 -22788.9 11653.4\n1.29499 1852.19 11653.4\n1.44248 116074 11653.4\n1.58997 -10291.9 11653.4\n1.73746 -27861.6 11653.4\n1.88496 -18215.1 11653.4\n2.03245 -28714 11653.4\n2.17994 -26150.2 11653.4\n2.32743 34592.3 11653.4\n2.47493 94708.1 11653.4\n2.62242 -34046.8 11653.4\n2.76991 -6095.59 11653.4\n2.9174 -9022.01 11653.4\n3.0649 -47692.9 11653.4\n3.21239 -39823.5 11653.4\n3.35988 -45615.1 11653.4\n3.50737 13411.8 11653.4\n3.65487 42196.6 11653.4\n3.80236 -28611.3 11653.4\n3.94985 -21093.7 11653.4\n4.09735 22420.5 11653.4\n4.24484 -12021.5 11653.4\n4.39233 -17934.3 11653.4\n4.53982 45713.7 11653.4\n4.68732 -9106.12 11653.4\n4.83481 459.793 11653.4\n4.9823 -30024.4 11653.4\n5.12979 -6029.52 11653.4\n5.27729 -3788.41 11653.4\n5.42478 38601.6 11653.4\n5.57227 5401.92 11653.4\n5.71976 12241.1 11653.4\n5.86726 6715.96 11653.4\n6.01475 11253.1 11653.4\n6.16224 26161.1 11653.4\n6.30973 -15451.2 11653.4\n6.45723 -45.4651 11653.4\n6.60472 29243.8 11653.4\n6.75221 20789.5 11653.4\n6.8997 3686.4 11653.4\n7.0472 6321.19 11653.4\n7.19469 -14234.2 11653.4\n\n" -p1340 -a. diff --git a/doc/examples/parameter_summary.py b/doc/examples/parameter_summary.py deleted file mode 100644 index 1d4095c..0000000 --- a/doc/examples/parameter_summary.py +++ /dev/null @@ -1,236 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""Demonstrate setting all major SrMise peak exactraction parameters. - -This example shows how to explicitly set all major SrMise peak extraction -parameters in the context of a crystalline PDF with unreliable uncertainties. -This is illustrative, as the default values for many parameters are sufficient. - -The parameters covered are: -rng (Extraction range) -dg (PDF uncertainty) -baseline (PDF baseline) -pf (peak function used during extraction) -qmax (maximum momentum transfer Q) -nyquist (whether to use Nyquist sampling) -supersample (minimum amount to oversample during initial stages) -cres (clustering resolution) -initial_peaks (peaks already assumed to exist during extraction)""" - -import matplotlib.pyplot as plt - -from diffpy.srmise.applications.plot import makeplot -from diffpy.srmise.baselines.polynomial import Polynomial -from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction -from diffpy.srmise.peaks.gaussianoverr import GaussianOverR - - -def run(plot=True): - - # Initialize peak extraction - # Create peak extraction object - ppe = PDFPeakExtraction() - - # Load the PDF from a file - ppe.loadpdf("data/TiO2_fine_qmax26.gr") - - # Set up extraction parameters. - # In this section we'll examine the major extraction parameters in detail. - # diffpy.srmise strives to provide reasonable default values for these - # parameters. For normal use setting the range, baseline, and uncertainty - # should be sufficient. - kwds = {} - - # Range - # Range defaults to the entire PDF if not specified. - kwds["rng"] = [1.5, 10.0] - - # dg - # diffpy.srmise selects model complexity based primarily on the uncertainty - # of the PDF. Note that very small uncertainties (<1%) can make peak - # extraction excessively slow. In general, the smaller the uncertainty the - # more complex the model. PDFs which report no uncertainty, or report - # unreliable values must be assigned one. By default, a PDF which does not - # report uncertainties uses 5% the maximum minus minimum values. Common - # causes of unreliable uncertainties include oversampling (uncertainties in - # nearby data are strongly correlated, as for this PDF) and/or - # integrated diffraction patterns obtained by a method that also introduces - # correlation to the 1D diffraction pattern. Consequently, the assumption - # of both least-squares fitting and the Akaike Information Criterion that - # the data are at least approximately independently distributed is not - # valid. In this case results obtained by diffpy.srmise may be useful, - # especially when they can be intrepreted in light of prior knowledge, but - # strong statistical conclusions cannot be drawn. For additional - # discussion of this subtle yet important issue see: - # [1] Egami and Billinge. (2012). Underneath the Bragg Peaks: Structural - # Analysis of Complex Materials (2nd ed.). Oxford: Pergamon Press. - # [2] Granlund, et al. (2015) Acta Crystallographica A, 71(4), 392-409. - # doi:10.1107/S2053273315005276 - # [3] Yang, et al. (2014). Journal of Applied Crystallography, 47(4), - # 1273-1283. doi:10.1107/S1600576714010516 - kwds["dg"] = 0.35 # Play with this value! - - # baseline - # As a crystal PDF, a linear baseline crossing the origin is appropriate. - # Here we define the linear baseline B(r) = -.5*r + 0, and explicitly set - # the y-intercept as a fixed parameter which will not be fit. For - # crystal PDFs the theoretical value of the slope is -4*pi*rho0, where - # rho0 is the number density. Nevertheless, imperfect normalization of the - # PDF means the experimental baseline is proportional to that value. - blfunc = Polynomial(degree=1) - slope = -0.65 # Play with this value! - y_intercept = 0.0 - kwds["baseline"] = blfunc.actualize([slope, y_intercept], free=[True, False]) - # pf - # The pf (peakfunction) parameter allows setting the shape of peaks to be - # extracted. Termination effects are added automatically to the peak - # function during extraction. In the harmonic approximation of atomic - # interactions peaks in the PDF are well approximated by a Gaussian/r. - # (Note, however, that the values used for peak parameters -- namely - # position, width, and area -- are for the Gaussian itself). diffpy.srmise - # uses width-limited peaks to reduce the likelihood of extracting - # unphysically wide peaks in regions of high overlap. The parameter - # indicates the max fwhm permitted. By default, diffpy.srmise uses a - # maximum width of 0.7, which is generally reasonable if the r-axis of the - # PDF is given in angstroms. Models where many peaks reach the maximum - # width, and models that are very sensitive to the choice in maximum width, - # are strong signs that diffpy.srmise is having difficulty finding peaks - # which are sufficiently constrained by the data. - pf = GaussianOverR(0.7) - kwds["pf"] = [pf] # Despite the list, only one entry is currently supported. - - # qmax - # PDFs typically report the value of qmax (i.e. the maximum momentum - # transfer q in the measurement), but it can be specified explicitly also. - # If the PDF does not report qmax, diffpy.srmise attempts to estimate it - # directly from the data. This estimate can also be used by setting qmax - # to "automatic". An infinite qmax can be specified by setting qmax to 0, - # In that case the Nyquist rate is 0 (infinite resolution), and - # diffpy.srmise does not consider Nyquist sampling or termination effects. - kwds["qmax"] = 26.0 - - # nyquist - # This parameter governs whether diffpy.srmise attempts to find a model - # on a Nyquist-sampled grid with dr=pi/qmax, which is a grid where data - # uncertainties are least correlated without loss of information. By - # default this parameter is True whenever qmax > 0, and generally it - # should not need to be changed. Setting it to False allows extracted - # models retain more complexity because the data appear to have more - # statistically independent points than they truly do. For a detailed - # discussion of Nyquist sampling and the PDF see: - # [4] Farrow et al. (2011). Physical Review B, 84(13), 134105. - # doi:10.1103/PhysRevB.84.134105 - kwds["nyquist"] = True - - # supersample - # This parameter dictates the data be oversampled by at least this factor - # (relative to the Nyquist rate) during the early stages of peak - # extraction. If the input PDF is even more finely sampled, that level of - # sampling is used instead. The default value of 4.0 is ad hoc, but has - # been empirically sufficient. Increasing this value may help the peak- - # finding and clustering process, but reduces speed. - kwds["supersample"] = 4.0 - - # cres - # The cres (clustering resolution) parameter governs the sensitivity of the - # clustering method used by diffpy.srmise. In short, when the data are - # being clustered, data which are further than the clustering resolution - # from any other cluster (measured along the r-axis) are considered to be a - # new cluster rather than a member of an existing one. The default value - # is the Nyquist sampling interval pi/qmax, and on most data it should not - # greatly impact model complexity. In some cases making it smaller may - # help the peak-finding process. Here it is roughly half the Nyquist - # interval. - kwds["cres"] = 0.05 - - # Apply peak extraction parameters. - ppe.setvars(**kwds) - - # initial_peaks - # Initial peaks are peaks which are kept fixed during the early stages of - # peak extraction, effectively condition results upon their values. Since - # initial peaks are sometimes dependent on other SrMise parameters (e.g. - # the peak function used) it is good practice to set them after other - # parameters. Although the "initial_peaks" parameter can be set as with - # the parameters above, SrMise provides helper functions to do so more - # easily. There are two basic ways to quickly specify initial peaks: - # 1) Supplying the approximate position of the peak, and letting - # diffpy.srmise estimate the peak parameters. - # 2) Explicit specification of peak parameters. - - # Initial peaks from approximate positions. - # This routine estimates peak parameters by finding the peak-like cluster - # containing the specified point. It does not search for occluded peaks, - # so works best on well-separated peaks. It does, however, take any - # existing initial peaks into account during estimation. - positions = [2.0, 4.5] - for p in positions: - ppe.estimate_peak(p) # adds to initial_peaks - - # Initial peaks from explicit parameters. - # Adding initial peaks explicitly is similar to defining a baseline. - # Namely, choosing a peak function and then actualizing it with given - # parameters. For this example peaks are created from the same GaussianOverR - # used during extraction, but one could use a different peak function from - # diffpy.srmise.peaks if desired. The peak parameters are given in terms - # terms of position, width (fwhm), and area, and it is important to specify - # that format is being used so they are correctly changed into the - # internal parameterization. Here two peaks are added in a region of - # overlap, and the width parameter is fixed at a reasonable value to aid - # convergence in this region. - pars = [[6.2, 0.25, 2.6], [6.45, 0.25, 2.7], [7.15, 0.25, 5]] - peaks = [] - for p in pars: - peaks.append(pf.actualize(p, free=[True, False, True], in_format="pwa")) - ppe.add_peaks(peaks) # adds to initial_peaks - - # Initial peaks and pruning - # While initial peaks condition what other peaks can be extracted, by - # default they can also be pruned if a simpler model appears better. To - # prevent this, they can be set as non-removable. - for ip in ppe.initial_peaks: - ip.removable = False - - # Plot initial parameters - if plot: - makeplot(ppe) - plt.title("Initial Peaks") - - # Perform peak extraction - ppe.extract() - - # Save output - # The write() method saves a file which preserves all aspects of peak - # extraction and its results, by convention using the .srmise extension, - # and which can later be read by diffpy.srmise. - # - # The writepwa() method saves a file intended as a human-readable summary. - # In particular, it reports the position, width (as full-width - # half-maximum), and area of of extracted peaks. The reported values - # are for Gaussians in the radial distribution function (RDF) corresponding - # to this PDF. - ppe.write("output/parameter_summary.srmise") - ppe.writepwa("output/parameter_summary.pwa") - - # Plot results. - # Display plot of extracted peak. It is also possible to plot an existing - # .srmise file from the command line using - # srmise output/TiO2_parameterdetail.srmise --no-extract --plot - if plot: - plt.figure() - makeplot(ppe) - plt.show() - - -if __name__ == "__main__": - run() diff --git a/doc/examples/query_results.py b/doc/examples/query_results.py deleted file mode 100644 index 8b90d4b..0000000 --- a/doc/examples/query_results.py +++ /dev/null @@ -1,222 +0,0 @@ -#!/usr/bin/env python -############################################################################## -# -# diffpy.srmise by Luke Granlund -# (c) 2015 trustees of the Michigan State University. -# All rights reserved. -# -# File coded by: Luke Granlund -# -# See LICENSE.txt for license information. -# -############################################################################## -"""Example of extracting multiple peaks and accessing results programmatically. - -This example shows how to extract a range of peaks from a simple crystalline -PDF using a crystalline baseline obtained from an existing trial. It shows -how to access the value and uncertainty of peak parameters, including -transforming between different peak parameterizations. Finally, it shows how -to evaluate the model on an arbitrary grid. - -The peaks extracted by this script are equivalent to those obtained running -srmise data/Ag_nyquist_qmax30.gr --range 2. 10. \ - --bsrmise output/extract_single_peak.srmise \ - --save output/query_results.srmise \ - --pwa output/query_results.pwa --plot -at the command line. -""" - -import matplotlib.pyplot as plt -import numpy as np - -from diffpy.srmise.modelcluster import ModelCovariance -from diffpy.srmise.pdfpeakextraction import PDFPeakExtraction - - -def run(plot=True): - - # Initialize peak extraction - # Create peak extraction object - ppe = PDFPeakExtraction() - - # Load the PDF from a file - ppe.loadpdf("data/Ag_nyquist_qmax30.gr") - - # Obtain baseline from a saved diffpy.srmise trial. This is not the - # initial baseline estimate from the previous example, but the baseline - # after both it and the extracted peaks have been fit to the data. - ppebl = PDFPeakExtraction() - ppebl.read("output/extract_single_peak.srmise") - baseline = ppebl.extracted.baseline - - # Set up extraction parameters. - # Peaks are extracted between 2 and 10 angstroms, using the baseline - # from the isolated peak example. - kwds = {} - kwds["rng"] = [2.0, 10.0] - kwds["baseline"] = baseline - - # Apply peak extraction parameters. - ppe.setvars(**kwds) - - # Perform peak extraction, and retain object containing a copy of the - # model and the full covariance matrix. - cov = ppe.extract() - - print("\n======= Accessing SrMise Results ========") - # Accessing results of extraction - # - # Model parameters are organized using a nested structure, with a list - # of peaks each of which is a list of parameters, similar to the the - # following schematic. - # Peak - # Position - # Width - # Area - # Peak - # Position - # Width - # Area* - # ... - # Baseline - # Slope - # Intercept - # By convention, the baseline is the final "peak." The ModelCovariance - # object returned by extract() can return information about any peak by - # using the appropriate tuple of indices (i,j). That is, (i,j) denotes - # the jth parameter of the ith peak. For example, the starred parameter - # above is the area (index = 2) of the next nearest neighbor (index = 1) - # peak. Thus, this parameter can be referenced as (1,2). Several examples - # are presented below. - - print("\n------ Parameter values and uncertainties ------") - # ModelCovariance.get() returns a (value, uncertainty) tuple for a given - # parameter. These are the results for the nearest-neighbor peak. - p0 = cov.get((0, 0)) - w0 = cov.get((0, 1)) - a0 = cov.get((0, 2)) - print("Nearest-neighbor peak: ") - print(" position = %f +/- %f" % p0) - print(" width = %f +/- %f" % w0) - print(" area = %f +/- %f" % a0) - print(" Covariance(width, area) = ", cov.getcovariance((0, 1), (0, 2))) - - # Baseline parameters. By convention, baseline is final element in cov. - (slope, intercept) = cov.model[-1] - print("\nThe linear baseline B(r)=%f*r + %f" % tuple(par for par in cov.model[-1])) - - print("\n ------ Uncertainties from a Saved File --------") - # A .srmise file does not save the full covariance matrix, so it must be - # recalculated when loading from these files. For example, here is the - # nearest-neighbor peak in the file which we used to define the initial - # baseline. - cov2 = ModelCovariance() - ppebl.extracted.fit(fitbaseline=True, cov=cov2, cov_format="default_output") - p0_saved = cov2.get((0, 0)) - w0_saved = cov2.get((0, 1)) - a0_saved = cov2.get((0, 2)) - print("Nearest-neighbor peak:") - print(" position = %f +/- %f" % p0_saved) - print(" width == %f +/- %f" % w0_saved) - print(" area = = %f +/- %f" % a0_saved) - print(" Covariance(width, area) = ", cov2.getcovariance((0, 1), (0, 2))) - - print("\n ---------- Alternate Parameterizations ---------") - # Different Parameterizations - # Peaks and baselines may have equivalent parameterizations that are useful - # in different situations. For example, the types defined by the - # GaussianOverR peak function are: - # "internal" - Used in diffpy.srmise calculations, explicitly enforces a - # maximum peak width - # "pwa" - The position, width (full-width at half-maximum), area. - # "mu_sigma_area" - The position, width (the distribution standard - # deviation sigma), area. - # "default_output" - Defines default format to use in most user-facing - # scenarios. Maps to the "pwa" parameterization. - # "default_input" - Defines default format to use when specifying peak - # parameters. Maps to the "internal" parameterization. - # All diffpy.srmise peak and baseline functions are required to have the - # "internal", "default_output", and "default_input" formats. In many - # cases, such as polynomial baselines, all of these are equivalent. - # - # Suppose you want to know peak widths in terms of the standard deviation - # sigma of the Gaussian distribution. It is then appropriate to convert - # all peaks to the "mu_sigma_area" format. Valid options for the "parts" - # keyword are "peaks", "baseline", or a sequence of indices (e.g. [1,2,3] - # would transform the second, third, and fourth peaks). If the keyword - # is omitted, the transformation is attempted for all parts of the fit. - cov.transform(in_format="pwa", out_format="mu_sigma_area", parts="peaks") - print("Width (sigma) of nearest-neighbor peak: %f +/- %f" % cov.get((0, 1))) - - print("\n ------------ Highly Correlated Parameters ------------") - # Highly-correlated parameters can indicate difficulties constraining the - # fit. This function lists all pairs of parameters with an absolute value - # of correlation which exceeds a given threshold. - print("|Correlation| > 0.9:") - print("par1 par2 corr(par1, par2)") - print("\n".join(str(c) for c in cov.correlationwarning(0.9))) - - print("\n-------- Estimate coordination shell occupancy ---------") - # Estimate the scale factor and its uncertainty from first peak's intensity. - # G_normalized = scale * G_observed - # dscale = scale * dG_observed/G_observed - scale = 12.0 / a0[0] - dscale = scale * a0[1] / a0[0] - print("Estimate scale factor assuming nearest-neighbor intensity = 12") - print("Scale factor is %f +/- %f" % (scale, dscale)) - - # Reference for number of atoms in coordination shells for FCC. - # http://chem-faculty.lsu.edu/watkins/MERLOT/cubic_neighbors/cubic_near_neighbors.html - ideal_intensity = [12, 6, 24, 12, 24, 8, 48, 6, 36, 24, 24, 24] - - # Calculated the scaled intensities and uncertainties. - intensity = [] - for i in range(0, len(cov.model) - 1): - (area, darea) = cov.get((i, 2)) - area *= scale - darea = area * np.sqrt((dscale / scale) ** 2 + (darea / area) ** 2) - intensity.append((ideal_intensity[i], area, darea)) - - print("\nIntensity") - print("Ideal: Estimated") - for i in intensity: - print("%i: %f +/- %f" % i) - - print("\nTotal intensity") - # It is possible to iterate over peaks directly without using indices. - # In addition, peak parameters can be accessed using string keys. For the - # Gaussian over r all of "position", "width", and "area" are valid. - total_observed_intensity = 0 - total_ideal_intensity = 0 - for peak, ii in zip(cov.model[:-1], ideal_intensity): - total_observed_intensity += scale * peak["area"] - total_ideal_intensity += ii - print("Ideal: Observed (using estimated scale factor)") - print("%i: %f" % (total_ideal_intensity, total_observed_intensity)) - - # Save output - ppe.write("output/query_results.srmise") - ppe.writepwa("output/query_results.pwa") - - # Evaluating a model. - # Although the ModelCovariance object is useful, the model used for fitting - # can be directly accessed through PDFPeakExtraction as well, albeit - # without uncertainties. This is particularly helpful when evaluating a - # model since the parameters stay in the "internal" format used for - # calculations. For example, here we plot the data and every second peak - # on an arbitrary grid. Unlike with ModelCovariance, the baseline and - # peaks are kept separate. - if plot: - plt.figure() - grid = np.arange(2, 10, 0.01) - bl = ppe.extracted.baseline - everysecondpeak = ppe.extracted.model[::2] - plt.plot(ppe.x, ppe.y, "o") - for peak in everysecondpeak: - plt.plot(grid, bl.value(grid) + peak.value(grid)) - plt.xlim(2, 10) - plt.show() - - -if __name__ == "__main__": - run() diff --git a/doc/source/api/diffpy.srmise.applications.rst b/doc/source/api/diffpy.srmise.applications.rst deleted file mode 100644 index 87413c9..0000000 --- a/doc/source/api/diffpy.srmise.applications.rst +++ /dev/null @@ -1,28 +0,0 @@ -:tocdepth: -1 - -diffpy.srmise.applications package -================================== - -.. automodule:: diffpy.srmise.applications - :members: - :undoc-members: - :show-inheritance: - -Submodules ----------- - -diffpy.srmise.applications.plot module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.applications.plot - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.applications.extract module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.applications.extract - :members: - :undoc-members: - :show-inheritance: diff --git a/doc/source/api/diffpy.srmise.baselines.rst b/doc/source/api/diffpy.srmise.baselines.rst deleted file mode 100644 index 5e9b791..0000000 --- a/doc/source/api/diffpy.srmise.baselines.rst +++ /dev/null @@ -1,52 +0,0 @@ -:tocdepth: -1 - -diffpy.srmise.baselines package -=============================== - -.. automodule:: diffpy.srmise.baselines - :members: - :undoc-members: - :show-inheritance: - -Submodules ----------- - -diffpy.srmise.baselines.nanospherical module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.baselines.nanospherical - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.baselines.arbitrary module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.baselines.arbitrary - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.baselines.fromsequence module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.baselines.fromsequence - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.baselines.polynomial module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.baselines.polynomial - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.baselines.base module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.baselines.base - :members: - :undoc-members: - :show-inheritance: diff --git a/doc/source/api/diffpy.srmise.modelevaluators.rst b/doc/source/api/diffpy.srmise.modelevaluators.rst deleted file mode 100644 index 012c60a..0000000 --- a/doc/source/api/diffpy.srmise.modelevaluators.rst +++ /dev/null @@ -1,36 +0,0 @@ -:tocdepth: -1 - -diffpy.srmise.modelevaluators package -===================================== - -.. automodule:: diffpy.srmise.modelevaluators - :members: - :undoc-members: - :show-inheritance: - -Submodules ----------- - -diffpy.srmise.modelevaluators.aic module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.modelevaluators.aic - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.modelevaluators.aicc module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.modelevaluators.aicc - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.modelevaluators.base module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.modelevaluators.base - :members: - :undoc-members: - :show-inheritance: diff --git a/doc/source/api/diffpy.srmise.peaks.rst b/doc/source/api/diffpy.srmise.peaks.rst deleted file mode 100644 index b88e831..0000000 --- a/doc/source/api/diffpy.srmise.peaks.rst +++ /dev/null @@ -1,44 +0,0 @@ -:tocdepth: -1 - -diffpy.srmise.peaks package -=========================== - -.. automodule:: diffpy.srmise.peaks - :members: - :undoc-members: - :show-inheritance: - -Submodules ----------- - -diffpy.srmise.peaks.gaussianoverr module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.peaks.gaussianoverr - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.peaks.terminationripples module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.peaks.terminationripples - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.peaks.base module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.peaks.base - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.peaks.gaussian module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.peaks.gaussian - :members: - :undoc-members: - :show-inheritance: diff --git a/doc/source/api/diffpy.srmise.rst b/doc/source/api/diffpy.srmise.rst deleted file mode 100644 index 98ea790..0000000 --- a/doc/source/api/diffpy.srmise.rst +++ /dev/null @@ -1,111 +0,0 @@ -:tocdepth: -1 - -diffpy.srmise package -===================== - -.. automodule:: diffpy.srmise - :members: - :undoc-members: - :show-inheritance: - -Subpackages ------------ - -.. toctree:: - :titlesonly: - - diffpy.srmise.peaks - diffpy.srmise.modelevaluators - diffpy.srmise.applications - diffpy.srmise.baselines - -Submodules ----------- - -diffpy.srmise.multimodelselection module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.multimodelselection - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.srmiselog module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.srmiselog - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.modelparts module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.modelparts - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.peakstability module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.peakstability - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.basefunction module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.basefunction - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.pdfpeakextraction module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.pdfpeakextraction - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.modelcluster module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.modelcluster - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.dataclusters module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.dataclusters - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.srmiseerrors module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.srmiseerrors - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.peakextraction module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.peakextraction - :members: - :undoc-members: - :show-inheritance: - -diffpy.srmise.pdfdataset module -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -.. automodule:: diffpy.srmise.pdfdataset - :members: - :undoc-members: - :show-inheritance: diff --git a/doc/source/api/diffpy_srmise.example_package.rst b/doc/source/api/diffpy_srmise.example_package.rst new file mode 100644 index 0000000..026b577 --- /dev/null +++ b/doc/source/api/diffpy_srmise.example_package.rst @@ -0,0 +1,31 @@ +.. _example_package documentation: + +|title| +======= + +.. |title| replace:: diffpy_srmise.example_package package + +.. automodule:: diffpy_srmise.example_package + :members: + :undoc-members: + :show-inheritance: + +|foo| +----- + +.. |foo| replace:: diffpy_srmise.example_package.foo module + +.. automodule:: diffpy_srmise.example_package.foo + :members: + :undoc-members: + :show-inheritance: + +|bar| +----- + +.. |bar| replace:: diffpy_srmise.example_package.bar module + +.. automodule:: diffpy_srmise.example_package.foo + :members: + :undoc-members: + :show-inheritance: diff --git a/doc/source/api/diffpy_srmise.rst b/doc/source/api/diffpy_srmise.rst new file mode 100644 index 0000000..e7d508c --- /dev/null +++ b/doc/source/api/diffpy_srmise.rst @@ -0,0 +1,30 @@ +:tocdepth: -1 + +|title| +======= + +.. |title| replace:: diffpy-srmise package + +.. automodule:: diffpy_srmise + :members: + :undoc-members: + :show-inheritance: + +Subpackages +----------- + +.. toctree:: + diffpy_srmise.example_package + +Submodules +---------- + +|module| +-------- + +.. |module| replace:: diffpy_srmise.example_submodule module + +.. automodule:: diffpy_srmise.example_submodule + :members: + :undoc-members: + :show-inheritance: diff --git a/doc/source/conf.py b/doc/source/conf.py index 65d3685..cb22e44 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -1,7 +1,7 @@ #!/usr/bin/env python # -*- coding: utf-8 -*- # -# diffpy.srmise documentation build configuration file, created by +# diffpy-srmise documentation build configuration file, created by # noqa: E501 # sphinx-quickstart on Thu Jan 30 15:49:41 2014. # # This file is execfile()d with the current directory set to its @@ -18,15 +18,21 @@ from importlib.metadata import version from pathlib import Path +# Attempt to import the version dynamically from GitHub tag. +try: + fullversion = version("diffpy_srmise") +except Exception: + fullversion = "No version found. The correct version will appear in the released version." # noqa: E501 + # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the -# documentation root, use Path().resolve() to make it absolute, like shown here. +# documentation root, use Path().resolve() to make it absolute, like shown here. # noqa: E501 # sys.path.insert(0, str(Path(".").resolve())) sys.path.insert(0, str(Path("../..").resolve())) sys.path.insert(0, str(Path("../../src").resolve())) # abbreviations -ab_authors = "Billinge Group members and community contributors" +ab_authors = "Simon Billinge, Billinge Group members" # -- General configuration ------------------------------------------------ @@ -43,6 +49,7 @@ "sphinx.ext.viewcode", "sphinx.ext.intersphinx", "sphinx_rtd_theme", + "sphinx_copybutton", "m2r", ] @@ -61,14 +68,13 @@ master_doc = "index" # General information about the project. -project = "diffpy.srmise" +project = "diffpy-srmise" copyright = "%Y, The Trustees of Columbia University in the City of New York" # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. -fullversion = version(project) # The short X.Y version. version = "".join(fullversion.split(".post")[:1]) # The full version, including alpha/beta/rc tags. @@ -88,6 +94,11 @@ # substitute YEAR in the copyright string copyright = copyright.replace("%Y", year) +# For sphinx_copybutton extension. +# Do not copy "$" for shell commands in code-blocks. +copybutton_prompt_text = r"^\$ " +copybutton_prompt_is_regexp = True + # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ["build"] @@ -111,7 +122,7 @@ pygments_style = "sphinx" # A list of ignored prefixes for module index sorting. -modindex_common_prefix = ["diffpy.srmise"] +modindex_common_prefix = ["diffpy-srmise"] # Display all warnings for missing links. nitpicky = True @@ -123,6 +134,14 @@ # html_theme = "sphinx_rtd_theme" +html_context = { + "display_github": True, + "github_user": "diffpy", + "github_repo": "diffpy-srmise", + "github_version": "main", + "conf_py_path": "/doc/source/", +} + # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. @@ -202,7 +221,7 @@ # html_file_suffix = None # Output file base name for HTML help builder. -basename = "diffpy.srmise".replace(" ", "").replace(".", "") +basename = "diffpy-srmise".replace(" ", "").replace(".", "") htmlhelp_basename = basename + "doc" @@ -221,7 +240,13 @@ # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ - ("index", "diffpy.srmise.tex", "diffpy.srmise Documentation", ab_authors, "manual"), + ( + "index", + "diffpy-srmise.tex", + "diffpy-srmise Documentation", + ab_authors, + "manual", + ), ] # The name of an image file (relative to this directory) to place at the top of @@ -249,7 +274,15 @@ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). -man_pages = [("index", "diffpy.srmise", "diffpy.srmise Documentation", ab_authors, 1)] +man_pages = [ + ( + "index", + "diffpy-srmise", + "diffpy-srmise Documentation", + ab_authors, + 1, + ) +] # If true, show URL addresses after external links. # man_show_urls = False @@ -263,10 +296,10 @@ texinfo_documents = [ ( "index", - "diffpy.srmise", - "diffpy.srmise Documentation", + "diffpy-srmise", + "diffpy-srmise Documentation", ab_authors, - "diffpy.srmise", + "diffpy-srmise", "One line description of project.", "Miscellaneous", ), diff --git a/doc/source/extending.rst b/doc/source/extending.rst deleted file mode 100644 index 4c274f3..0000000 --- a/doc/source/extending.rst +++ /dev/null @@ -1,146 +0,0 @@ -.. index:: extending-srmise - -=================== -Extending SrMise -=================== - -The :ref:`tutorial` gives an overview of how to use SrMise with the existing -peak and baseline functions. These inherit from classes providing generic peak -and baseline functionality, and from which additional peaks and baselines can be -implemented. The process for adding new peaks and baselines is summarized -below, but see the source code for additional details. - -If you implement a peak or baseline likely to be of broad interest to the PDF -community, please consider submitting a pull request to the GitHub -`SrMise repository `_. - -Organization of Functions -------------------------- - -The ``BaseFunction`` class in ``diffpy.srmise.basefunction`` implements the -functionality common to all SrMise baseline and peak functions, which are -separately implemented in the ``diffpy.srmise.baselines`` and -``diffpy.srmise.peaks`` subpackages. Specific baseline and peak functions -inherit from the ``BaselineFunction`` and ``PeakFunction`` classes in those -subpackages, as shown below. - -* .. py:class:: BaseFunction - - + .. py:class:: BaselineFunction - - - .. py:class:: FromSequence - - .. py:class:: NanoSpherical - - .. py:class:: Polynomial - - *etc.* - - + .. py:class:: PeakFunction - - - .. py:class:: Gaussian - - .. py:class:: GaussianOverR - - *etc.* - -Adding Baselines -------------------------------------- - -To add a baseline, create a new module which defines a class inheriting from -``diffpy.srmise.baselines.base.BaselineFunction``. The class data and methods -which need to be implemented are summarized in the source code. - - -.. literalinclude:: ../../src/diffpy/srmise/baselines/base.py - :pyobject: BaselineFunction - :end-before: __init__ - -The class methods should follow these specifications. See existing baselines -for examples. - -.. py:method:: estimate_parameters(r, y) - - Return a Numpy array of parameters estimated from the data. - - :param r: Grid on which the data are defined. - :param y: The data. - :type r: `Sequence` - :type y: `Sequence` - :returns: Estimated parameters - :rtype: `numpy.ndarray` - :raises: NotImplementedError if estimation has not been implemented. - :raises: SrMiseEstimationError if estimation fails. - - -.. py:method:: _jacobian_raw(pars, r, free) - - Return Jacobian for parameters evaluated over `r`. - - :param pars: The parameters of the baseline. - :param r: Scalar or grid on which to calculate the Jacobian. - :param free: Boolean values indicating if corresponding parameter is free (True) or fixed (False). - :type pars: `Sequence(float)` - :type r: `int`, `float`, or `Sequence(int` or `float)` - :type free: `Sequence(boolean)` - :returns: List of Jacobian values (or None if parameter is not free) for each parameter evaluated at `r`. - :rtype: `list(numpy.ndarray(float) or float or None)` - -.. py:method:: _transform_derivativesraw(pars, in_format, out_format) - - Return the gradient matrix of `pars` represented in format 'out_format'. - - :param pars: The parameters of the baseline. - :param in_format: The format of `pars`. - :param out_format: The desired format of `pars`. - :type pars: `Sequence(float)` - :type in_format: `str` - :type out_format: `str` - :returns: The gradient matrix for the transformation. - :rtype: `numpy.ndarray` - -.. py:method:: _transform_parametersraw(pars, in_format, out_format) - - Return parameters transformed into format 'out_format'. - - :param pars: The parameters of the baseline. - :param in_format: The format of `pars`. - :param out_format: The desired format of `pars`. - :type pars: `Sequence(float)` - :type in_format: `str` - :type out_format: `str` - :returns: The transformed parameters. - :rtype: `numpy.ndarray` - -.. py:method:: _valueraw(pars, r) - - Return value of baseline with given parameters at r. - - :param pars: The parameters of the baseline. - :param r: Scalar or grid on which to calculate the baseline. - :type pars: `Sequence(float)` - :type r: `int`, `float`, or `Sequence(int` or `float)` - :returns: The value of the baseline. - :rtype: `float` or `numpy.ndarray(float)`. - - -Adding Peaks --------------------------- - -To add a new peak function, create a new module which defines a class -inheriting from ``diffpy.srmise.peaks.base.PeakFunction``. Implementing a peak -function is nearly identical to implementing a baseline function, with the -following differences: - -1) The ``estimate_parameters`` method is required. -2) The "position" key must be defined in the ``parameterdict`` class member. -3) Peak functions must implement the additional method ``scale_at``. - -.. py:method:: scale_at(pars, r, scale) - - Return peak parameters such that the value at ``r`` is scaled by ``scale`` - while the position of the peak's maxima remains unchanged. - - :param pars: The parameters of the peak. - :param r: Position where the peak will be rescaled. - :param scale: A scale factor > 0. - :type pars: `Sequence(float)` - :type r: `int` or `float` - :type scale: `float` - :returns: The adjusted peak parameters. - :rtype: `numpy.ndarray(float)`. diff --git a/doc/source/getting-started.rst b/doc/source/getting-started.rst new file mode 100644 index 0000000..ac7d510 --- /dev/null +++ b/doc/source/getting-started.rst @@ -0,0 +1,79 @@ +:tocdepth: -1 + +.. index:: getting-started + +.. _getting-started: + +================ +Getting started +================ + +Here are some example templates provided to help you get started with writing your documentation. You can use these templates to create your own documentation. + +Reuse ``.rst`` files across multiple pages +------------------------------------------ + +Here is how you can reuse a reusable block of ``.rst`` files across multiple pages: + +.. include:: snippets/example-table.rst + +.. warning:: + + Ensure that the ``.rst`` file you are including is not too long. If it is too long, it may be better to split it into multiple files and include them separately. + +Refer to a specific section in the documentation +------------------------------------------------ + +You can use the ``ref`` tag to refer to a specific section in the documentation. For example, you can refer to the section below using the ``:ref:`` tag as shown :ref:`here `. + +.. note:: + + Please check the raw ``.rst`` file of this page to see the exact use of the ``:ref:`` tag. + +Embed your code snippets in the documentation +--------------------------------------------- + +Here is how you can write a block of code in the documentation. You can use the ``code-block`` directive to write a block of code in the documentation. For example, you can write a block of code as shown below: + +.. code-block:: bash + + # Create a new environment, without build dependencies (pure Python package) + conda create -n -env python=3.13 \ + --file requirements/test.txt \ + --file requirements/conda.txt + + # Create a new environment, with build dependencies (non-pure Python package) + conda create -n -env python=3.13 \ + --file requirements/test.txt \ + --file requirements/conda.txt \ + --file requirements/build.txt + + # Activate the environment + conda activate _env + + # Install your package locally + # `--no-deps` to NOT install packages again from `requirements.pip.txt` + pip install -e . --no-deps + + # Run pytest locally + pytest + + # ... run example tutorials + +.. _attach-image: + +Attach an image to the documentation +------------------------------------ + +Here is how you attach an image to the documentation. The ``/doc/source/img/scikit-package-logo-text.png`` example image is provided in the template. + +.. image:: ./img/scikit-package-logo-text.png + :alt: codecov-in-pr-comment + :width: 400px + :align: center + + +Other useful directives +----------------------- + +Here is how you can do menu selection :menuselection:`Admin --> Settings` and display labels for buttons like :guilabel:`Privacy level`. diff --git a/doc/source/img/scikit-package-logo-text.png b/doc/source/img/scikit-package-logo-text.png new file mode 100644 index 0000000..823178d Binary files /dev/null and b/doc/source/img/scikit-package-logo-text.png differ diff --git a/doc/source/index.rst b/doc/source/index.rst index 417085e..afafa50 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -2,40 +2,49 @@ |title| ####### -.. |title| replace:: diffpy.srmise documentation +.. |title| replace:: diffpy-srmise documentation -diffpy.srmise - Peak extraction and peak fitting tool for atomic pair distribution functions.. +``diffpy-srmise`` - Peak extraction and peak fitting tool for atomic pair distribution functions. -| Software version |release|. +| Software version |release| | Last updated |today|. +=============== +Getting started +=============== + +Welcome to the ``diffpy-srmise`` documentation! + +To get started, please visit the :ref:`Getting started ` page. + ======= Authors ======= -diffpy.srmise is developed by Billinge Group -and its community contributors. - -For a detailed list of contributors see -https://github.com/diffpy/diffpy.srmise/graphs/contributors. +``diffpy-srmise`` is developed by Simon Billinge, Billinge Group members. The maintainer for this project is Simon Billinge. For a detailed list of contributors see +https://github.com/diffpy/diffpy-srmise/graphs/contributors. ============ Installation ============ -See the `README `_ +See the `README `_ file included with the distribution. +================ +Acknowledgements +================ + +``diffpy-srmise`` is built and maintained with `scikit-package `_. + ================= Table of contents ================= .. toctree:: - :maxdepth: 1 - :titlesonly: + :maxdepth: 2 - tutorial/index - extending - Package API + getting-started + Package API release license diff --git a/doc/source/license.rst b/doc/source/license.rst index 75f0bdd..5e751f7 100644 --- a/doc/source/license.rst +++ b/doc/source/license.rst @@ -9,25 +9,8 @@ OPEN SOURCE LICENSE AGREEMENT ============================= BSD 3-Clause License -Copyright 2014-2015, Board of Trustees of Michigan State University - -Copyright 2016-2024, The Trustees of Columbia University in the City of New York. - -All rights reserved. - -If you use this program to do productive scientific research that -leads to publication, we ask that you acknowledge use of the -program by citing the following paper in your publication: - - L. Granlund, S.J.L. Billinge, P.M. Duxbury, Algorithm for - systematic peak extraction from atomic pair distribution - functions, Acta Crystallographica A 71(4), 392-409 (2015). - doi:10.1107/S2053273315005276 - -For more information please visit the diffpy web-page at - http://www.diffpy.org -or email Luke Granlund at luke.r.granlund@gmail.com, or Prof. Simon -Billinge at sb2896@columbia.edu. +Copyright (c) 2025, The Trustees of Columbia University in the City of New York. +All Rights Reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: @@ -39,9 +22,9 @@ modification, are permitted provided that the following conditions are met: this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. -3. Neither the name of the copyright holder nor the names of its contributors - may be used to endorse or promote products derived from this software - without specific prior written permission. +3. Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE diff --git a/doc/source/snippets/example-table.rst b/doc/source/snippets/example-table.rst new file mode 100644 index 0000000..7c4c11d --- /dev/null +++ b/doc/source/snippets/example-table.rst @@ -0,0 +1,28 @@ +.. list-table:: 5 levels of reusing/sharing code + :widths: 5 15 40 40 + :header-rows: 1 + + * - Level + - Name + - Scope + - How to setup + * - 1 + - ``function`` + - Reuse code in the single file. + - See Level 1 tutorial + * - 2 + - ``module`` + - Reuse code across files. + - See Level 2 tutorial + * - 3 + - ``workspace`` + - Reuse code across project folders. + - ``package create workspace`` + * - 4 + - ``system`` + - Reuse code across any files in the computer. + - ``package create system`` + * - 5 + - ``public`` + - Share code as publicly installable package. + - ``package create public`` diff --git a/doc/source/tutorial/abbreviations.txt b/doc/source/tutorial/abbreviations.txt deleted file mode 100644 index 032313e..0000000 --- a/doc/source/tutorial/abbreviations.txt +++ /dev/null @@ -1,42 +0,0 @@ -.. Abbreviations and definitions for SrMise tutorial. - -.. The README file in the doc/examples directory of the SrMise source - distribution should be readable without generating the full Sphinx docs. - To do this, the amount of markup is kept to a bare minimum, and the markup - that does appear shouldn't get in the way of understanding. - -.. Substitutions point to SrMise sources matching this version of the docs. -.. |zip| replace:: :source-release:`zip` -.. |tar.gz| replace:: :source-release:`tar.gz` - -.. Image substitutions -.. |images/extract_single_peak1.png| image:: ../../examples/images/extract_single_peak1.png -.. |images/extract_single_peak2.png| image:: ../../examples/images/extract_single_peak2.png -.. |images/extract_single_peak3.png| image:: ../../examples/images/extract_single_peak3.png -.. |images/parameter_summary1.png| image:: ../../examples/images/parameter_summary1.png -.. |images/parameter_summary2.png| image:: ../../examples/images/parameter_summary2.png -.. |images/parameter_summary3.png| image:: ../../examples/images/parameter_summary3.png -.. |images/parameter_summary4.png| image:: ../../examples/images/parameter_summary4.png -.. |images/fit_initial1.png| image:: ../../examples/images/fit_initial1.png -.. |images/fit_initial2.png| image:: ../../examples/images/fit_initial2.png -.. |images/query_results1.png| image:: ../../examples/images/query_results1.png -.. |images/query_results2.png| image:: ../../examples/images/query_results2.png -.. |images/query_results3.png| image:: ../../examples/images/query_results3.png - -.. External links -.. _ParSCAPE algorithm: https://dx.doi.org/10.1107/S2053273315005276 -.. _PDFgetX2: http://www.pa.msu.edu/cmp/billinge-group/programs/PDFgetX2/ -.. _FIT2D: http://www.esrf.eu/computing/scientific/FIT2D/ -.. _SrXplanar: http://github.com/diffpy/diffpy.srxplanar - -.. Math defs -.. |C60| replace:: C\ :sub:`60` -.. |TiO2| replace:: TiO\ :sub:`2` -.. |angstrom^-1| replace:: Å\ :sup:`-1` -.. |Qmax| replace:: Q\ :sub:`max` -.. |Qmin| replace:: Q\ :sub:`min` -.. |d_c| replace:: d\ :sub:`c` -.. |pi/Qmax| replace:: π/Q\ :sub:`max` - -.. Links to PDF information defined in sample_links.txt -.. |Extending SrMise| replace:: :ref:`extending-srmise` diff --git a/doc/source/tutorial/extract_single_peak.rst b/doc/source/tutorial/extract_single_peak.rst deleted file mode 100644 index cd3d459..0000000 --- a/doc/source/tutorial/extract_single_peak.rst +++ /dev/null @@ -1,16 +0,0 @@ -.. include:: abbreviations.txt - -.. include:: sample_links.txt - - -.. include:: ../../examples/README.rst - :start-after: ~Example 1~ - :end-before: ~Example 2~ - - -.. _extract_single_peak.py: - -Script (extract_single_peak.py) -------------------------------- - -.. literalinclude:: ../../examples/extract_single_peak.py diff --git a/doc/source/tutorial/fit_initial.rst b/doc/source/tutorial/fit_initial.rst deleted file mode 100644 index 5b95906..0000000 --- a/doc/source/tutorial/fit_initial.rst +++ /dev/null @@ -1,16 +0,0 @@ -.. include:: abbreviations.txt - -.. include:: sample_links.txt - - -.. include:: ../../examples/README.rst - :start-after: ~Example 3~ - :end-before: ~Example 4~ - - -.. _fit_initial.py: - -Script (fit_initial.py) ---------------------------- - -.. literalinclude:: ../../examples/fit_initial.py diff --git a/doc/source/tutorial/index.rst b/doc/source/tutorial/index.rst deleted file mode 100644 index 78ea9c1..0000000 --- a/doc/source/tutorial/index.rst +++ /dev/null @@ -1,29 +0,0 @@ -.. include:: abbreviations.txt - -.. _tutorial: - -=================== -Tutorial -=================== - -.. include:: ../../examples/README.rst - :end-before: ~List of Examples~ - - -.. Replace bare list from README - -.. toctree:: - :maxdepth: 1 - - extract_single_peak - parameter_summary - fit_initial - query_results - multimodel_known_uncertainties - multimodel_unknown_uncertainties - - -.. Now add information about the samples - -.. include:: ../../examples/README - :start-after: ~PDF Info~ diff --git a/doc/source/tutorial/multimodel_known_uncertainties.rst b/doc/source/tutorial/multimodel_known_uncertainties.rst deleted file mode 100644 index 665bf60..0000000 --- a/doc/source/tutorial/multimodel_known_uncertainties.rst +++ /dev/null @@ -1,25 +0,0 @@ -.. include:: abbreviations.txt - -.. include:: sample_links.txt - - -.. include:: ../../examples/README.rst - :start-after: ~Example 5~ - :end-before: ~Example 6~ - - - -.. _multimodel_known_dG1.py: - -Extraction Script (multimodel_known_dG1.py) ---------------------------------------------- - -.. literalinclude:: ../../examples/multimodel_known_dG1.py - - -.. _multimodel_known_dG2.py: - -Analysis Script (multimodel_known_dG2.py) ------------------------------------------ - -.. literalinclude:: ../../examples/multimodel_known_dG2.py diff --git a/doc/source/tutorial/multimodel_unknown_uncertainties.rst b/doc/source/tutorial/multimodel_unknown_uncertainties.rst deleted file mode 100644 index 11f346c..0000000 --- a/doc/source/tutorial/multimodel_unknown_uncertainties.rst +++ /dev/null @@ -1,25 +0,0 @@ -.. include:: abbreviations.txt - -.. include:: sample_links.txt - - -.. include:: ../../examples/README.rst - :start-after: ~Example 6~ - :end-before: ~PDF Info~ - - - -.. _multimodel_unknown_dG1.py: - -Extraction Script (multimodel_unknown_dG1.py) ---------------------------------------------- - -.. literalinclude:: ../../examples/multimodel_unknown_dG1.py - - -.. _multimodel_unknown_dG2.py: - -Analysis Script (multimodel_unknown_dG2.py) -------------------------------------------- - -.. literalinclude:: ../../examples/multimodel_unknown_dG2.py diff --git a/doc/source/tutorial/parameter_summary.rst b/doc/source/tutorial/parameter_summary.rst deleted file mode 100644 index b67a1d4..0000000 --- a/doc/source/tutorial/parameter_summary.rst +++ /dev/null @@ -1,16 +0,0 @@ -.. include:: abbreviations.txt - -.. include:: sample_links.txt - - -.. include:: ../../examples/README.rst - :start-after: ~Example 2~ - :end-before: ~Example 3~ - - -.. _parameter_summary.py: - -Script (parameter_summary.py) ------------------------------ - -.. literalinclude:: ../../examples/parameter_summary.py diff --git a/doc/source/tutorial/query_results.rst b/doc/source/tutorial/query_results.rst deleted file mode 100644 index 324c0a8..0000000 --- a/doc/source/tutorial/query_results.rst +++ /dev/null @@ -1,16 +0,0 @@ -.. include:: abbreviations.txt - -.. include:: sample_links.txt - - -.. include:: ../../examples/README.rst - :start-after: ~Example 4~ - :end-before: ~Example 5~ - - -.. _query_results.py: - -Script (query_results.py) -------------------------- - -.. literalinclude:: ../../examples/query_results.py diff --git a/doc/source/tutorial/sample_links.txt b/doc/source/tutorial/sample_links.txt deleted file mode 100644 index bf24f54..0000000 --- a/doc/source/tutorial/sample_links.txt +++ /dev/null @@ -1,5 +0,0 @@ -.. Links to PDF information. Compatible with chemical formula substitutions. - -.. _Ag: index.html#ag -.. _C60: index.html#c60 -.. _TiO2: index.html#tio2 diff --git a/environment.yml b/environment.yml deleted file mode 100644 index b467ca2..0000000 --- a/environment.yml +++ /dev/null @@ -1,6 +0,0 @@ -name: diffpy.srmise -channels: - - conda-forge -dependencies: - - python=3 - - pip diff --git a/news/codecov.rst b/news/codecov.rst deleted file mode 100644 index 1c91077..0000000 --- a/news/codecov.rst +++ /dev/null @@ -1,24 +0,0 @@ -**Added:** - -* Spelling check via Codespell in pre-commit -* Coverage report in each PR - -**Changed:** - -* - -**Deprecated:** - -* - -**Removed:** - -* - -**Fixed:** - -* - -**Security:** - -* diff --git a/news/codespell.rst b/news/codespell.rst deleted file mode 100644 index 1a99783..0000000 --- a/news/codespell.rst +++ /dev/null @@ -1,23 +0,0 @@ -**Added:** - -* Codespell for automatic spelling check, configured in pre-commit - -**Changed:** - -* - -**Deprecated:** - -* - -**Removed:** - -* - -**Fixed:** - -* Typos in the source code and documentation - -**Security:** - -* diff --git a/pyproject.toml b/pyproject.toml index ce2f2b1..e668d16 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,25 +3,23 @@ requires = ["setuptools>=62.0", "setuptools-git-versioning>=2.0"] build-backend = "setuptools.build_meta" [project] -name = "diffpy.srmise" +name = "diffpy-srmise" dynamic=['version', 'dependencies'] authors = [ - { name="Simon J.L. Billinge group", email="simon.billinge@gmail.com" }, - {name="Luke Granlund", email="granlund@pa.msu.edu"}, + { name="Simon Billinge", email="sb2896@columbia.edu" }, ] maintainers = [ - { name="Simon J.L. Billinge group", email="simon.billinge@gmail.com" }, + { name="Simon Billinge", email="sb2896@columbia.edu" }, ] description = "Peak extraction and peak fitting tool for atomic pair distribution functions." -keywords = ['peak extraction fitting PDF AIC multimodeling'] +keywords = ['peak extraction', 'ftitting', 'PDF', 'AIC', 'multimodeling'] readme = "README.rst" requires-python = ">=3.11, <3.14" classifiers = [ - 'Development Status :: 3 - Alpha', + 'Development Status :: 5 - Production/Stable', 'Environment :: Console', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', - 'Intended Audience :: Education', 'License :: OSI Approved :: BSD License', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Microsoft :: Windows', @@ -32,12 +30,11 @@ classifiers = [ 'Programming Language :: Python :: 3.13', 'Topic :: Scientific/Engineering :: Physics', 'Topic :: Scientific/Engineering :: Chemistry', - 'Topic :: Software Development :: Libraries', ] [project.urls] -Homepage = "https://github.com/diffpy/diffpy.srmise/" -Issues = "https://github.com/diffpy/diffpy.srmise/issues/" +Homepage = "https://github.com/diffpy/diffpy-srmise/" +Issues = "https://github.com/diffpy/diffpy-srmise/issues/" [tool.setuptools-git-versioning] enabled = true @@ -45,9 +42,6 @@ template = "{tag}" dev_template = "{tag}" dirty_template = "{tag}" -[project.scripts] -srmise = "diffpy.srmise.applications.extract:main" - [tool.setuptools.packages.find] where = ["src"] # list of folders that contain the packages (["."] by default) include = ["*"] # package names should match these glob patterns (["*"] by default) diff --git a/requirements/build.txt b/requirements/build.txt index f72d870..e69de29 100644 --- a/requirements/build.txt +++ b/requirements/build.txt @@ -1,2 +0,0 @@ -python -setuptools diff --git a/requirements/conda.txt b/requirements/conda.txt index 1b57b14..24ce15a 100644 --- a/requirements/conda.txt +++ b/requirements/conda.txt @@ -1,3 +1 @@ numpy -scipy -matplotlib-base diff --git a/requirements/docs.txt b/requirements/docs.txt index ab17b1c..5f34c6e 100644 --- a/requirements/docs.txt +++ b/requirements/docs.txt @@ -1,4 +1,5 @@ sphinx sphinx_rtd_theme +sphinx-copybutton doctr m2r diff --git a/requirements/pip.txt b/requirements/pip.txt index f23634b..24ce15a 100644 --- a/requirements/pip.txt +++ b/requirements/pip.txt @@ -1,3 +1 @@ numpy -scipy -matplotlib diff --git a/src/diffpy/__init__.py b/src/diffpy/__init__.py index 377a0f9..1fd9c20 100644 --- a/src/diffpy/__init__.py +++ b/src/diffpy/__init__.py @@ -12,7 +12,6 @@ # See LICENSE.rst for license information. # ############################################################################## - """Blank namespace package for module diffpy.""" diff --git a/src/diffpy/srmise/__init__.py b/src/diffpy/srmise/__init__.py index 65eb42b..52fd6a9 100644 --- a/src/diffpy/srmise/__init__.py +++ b/src/diffpy/srmise/__init__.py @@ -12,8 +12,8 @@ # See LICENSE.rst for license information. # ############################################################################## - -"""Peak extraction and peak fitting tool for atomic pair distribution functions.""" +"""Peak extraction and peak fitting tool for atomic pair distribution +functions.""" # package version from diffpy.srmise.version import __version__ diff --git a/src/diffpy/srmise/applications/plot.py b/src/diffpy/srmise/applications/plot.py index 0399565..25fea0b 100755 --- a/src/diffpy/srmise/applications/plot.py +++ b/src/diffpy/srmise/applications/plot.py @@ -11,7 +11,7 @@ # See LICENSE.txt for license information. # ############################################################################## -"""plot extracted peaks and comparison to ideal distances (if given)""" +"""Plot extracted peaks and comparison to ideal distances (if given)""" import optparse import sys @@ -175,7 +175,7 @@ def labelallsubplots(): def makeplot(ppe_or_stability, ip=None, **kwds): - """Plot stuff""" + """Plot stuff.""" if isinstance(ppe_or_stability, PeakStability): stability = ppe_or_stability ppe = stability.ppe diff --git a/src/diffpy/srmise/basefunction.py b/src/diffpy/srmise/basefunction.py index 7a955f0..cea8d92 100644 --- a/src/diffpy/srmise/basefunction.py +++ b/src/diffpy/srmise/basefunction.py @@ -11,7 +11,8 @@ # See LICENSE.txt for license information. # ############################################################################## -"""Defines BaseFunction, the base class for mathematical functions in srmise.""" +"""Defines BaseFunction, the base class for mathematical functions in +srmise.""" import logging import re @@ -76,7 +77,7 @@ def __init__( base=None, Cache=None, ): - """Set parameterdict defined by subclass + """Set parameterdict defined by subclass. Parameters ---------- @@ -159,32 +160,50 @@ def __init__( # "Virtual" class methods #### def actualize(self, *args, **kwds): - """Create ModelPart instance of self with given parameters. ("Virtual" method)""" + """Create ModelPart instance of self with given parameters. + + ("Virtual" method) + """ emsg = "actualize() must be implemented in a BaseFunction subclass." raise NotImplementedError(emsg) def estimate_parameters(self, *args, **kwds): - """Estimate BaseFunction parameters from supplied data. ("Virtual" method)""" + """Estimate BaseFunction parameters from supplied data. + + ("Virtual" method) + """ emsg = "estimate_parameters() must be implemented in a BaseFunction subclass." raise NotImplementedError(emsg) def _jacobianraw(self, *args, **kwds): - """Calculate the jacobian. ("Virtual" method)""" + """Calculate the jacobian. + + ("Virtual" method) + """ emsg = "_jacobianraw() must be implemented in a BaseFunction subclass." raise NotImplementedError(emsg) def _transform_derivativesraw(self, *args, **kwds): - """Convert BaseFunction parameters to another form. ("Virtual" method)""" + """Convert BaseFunction parameters to another form. + + ("Virtual" method) + """ emsg = "transform_parameters() must be implemented in a BaseFunction subclass." raise NotImplementedError(emsg) def _transform_parametersraw(self, *args, **kwds): - """Convert BaseFunction parameters to another form. ("Virtual" method)""" + """Convert BaseFunction parameters to another form. + + ("Virtual" method) + """ emsg = "transform_parameters() must be implemented in a BaseFunction subclass." raise NotImplementedError(emsg) def _valueraw(self, *args, **kwds): - """Calculate value of function. ("Virtual" method)""" + """Calculate value of function. + + ("Virtual" method) + """ emsg = "_valueraw must() be implemented in a BaseFunction subclass." raise NotImplementedError(emsg) @@ -225,7 +244,8 @@ def jacobian(self, p, r, rng=None): return self._jacobianraw(p.pars, r, p.free) def transform_derivatives(self, pars, in_format=None, out_format=None): - """Return gradient matrix for pars converted from in_format to out_format. + """Return gradient matrix for pars converted from in_format to + out_format. Parameters ---------- @@ -266,7 +286,8 @@ def transform_derivatives(self, pars, in_format=None, out_format=None): return self._transform_derivativesraw(pars, in_format=in_format, out_format=out_format) def transform_parameters(self, pars, in_format=None, out_format=None): - """Return new sequence with pars converted from in_format to out_format. + """Return new sequence with pars converted from in_format to + out_format. Also restores parameters to a preferred range if it permits multiple values that correspond to the same physical result. @@ -345,7 +366,8 @@ def value(self, p, r, rng=None): return self._valueraw(p.pars, r) def pgradient(self, p, format): - """Return gradient matrix of parameterization in specified format wrt "internal" format at p. + """Return gradient matrix of parameterization in specified format wrt + "internal" format at p. Consider the "internal" parameterization given by (i0, i1, ..., in). Each parameter in a different format, say (o0, o1, ..., om), is a @@ -373,7 +395,7 @@ def pgradient(self, p, format): return def getmodule(self): - """Return 'diffpy.srmise.basefunction'""" + """Return 'diffpy.srmise.basefunction'.""" return "diffpy.srmise.basefunction" def writestr(self, baselist): @@ -473,14 +495,16 @@ def factory(functionstr, baselist): @staticmethod def safefunctionlist(fs): - """Return list of BaseFunction instances where any dependencies occur earlier in list. + """Return list of BaseFunction instances where any dependencies occur + earlier in list. Any functions with hidden dependent functions (i.e. those not in fs) are included in the returned list. This list provides an order that is guaranteed to be safe for saving/reinstantiating peak functions. Parameters - fs: List of BaseFunction instances.""" + fs: List of BaseFunction instances. + """ fsafe = [] for f in fs: BaseFunction.safefunction(f, fsafe) @@ -488,7 +512,8 @@ def safefunctionlist(fs): @staticmethod def safefunction(f, fsafe): - """Append BaseFunction instance f to fsafe, but adding dependent functions first. + """Append BaseFunction instance f to fsafe, but adding dependent + functions first. Does not handle circular dependencies. diff --git a/src/diffpy/srmise/baselines/arbitrary.py b/src/diffpy/srmise/baselines/arbitrary.py index 80c1055..c67ec4d 100644 --- a/src/diffpy/srmise/baselines/arbitrary.py +++ b/src/diffpy/srmise/baselines/arbitrary.py @@ -26,17 +26,16 @@ class Arbitrary(BaselineFunction): """Methods for evaluating a baseline from an arbitrary function. - Supports baseline calculations with arbitrary functions. These functions, - if implemented, must have the following signatures and return values: - valuef(pars, x) ==> numpy.array of length x if x is a sequence - ==> number if x is a number - jacobianf(pars, x, free) ==> list, each element a numpy.array of length x if - x is a sequence or None if value of free for - that parameter is False. - ==> list, each element a number if x is a number - or None if value of free for that parameter is - False - estimatef(x, y) ==> numpy.array of length npars + Supports baseline calculations with arbitrary functions. These + functions, if implemented, must have the following signatures and + return values: valuef(pars, x) ==> numpy.array of length x if x is a + sequence ==> number if x is a number jacobianf(pars, + x, free) ==> list, each element a numpy.array of length x if + x is a sequence or None if value of free for + that parameter is False. ==> list, each + element a number if x is a number or + None if value of free for that parameter is + False estimatef(x, y) ==> numpy.array of length npars """ def __init__(self, npars, valuef, jacobianf=None, estimatef=None, Cache=None): @@ -117,7 +116,8 @@ def estimate_parameters(self, r, y): The numpy array of parameters in the default internal format. we raise NotImplementedError if no estimation routine is defined, and - SrMiseEstimationError if parameters cannot be estimated for any other.""" + SrMiseEstimationError if parameters cannot be estimated for any other. + """ if self.estimatef is None: emsg = "No estimation routine provided to Arbitrary." raise NotImplementedError(emsg) @@ -211,7 +211,8 @@ def _transform_parametersraw(self, pars, in_format, out_format): return temp def _valueraw(self, pars, r): - """Compute the value of the polynomial given a set of parameters and evaluation points. + """Compute the value of the polynomial given a set of parameters and + evaluation points. This method ensures that the input parameters conform to the expected count and then delegates the computation to an internal method `valuef`. diff --git a/src/diffpy/srmise/baselines/base.py b/src/diffpy/srmise/baselines/base.py index c1ecf0e..47074f4 100644 --- a/src/diffpy/srmise/baselines/base.py +++ b/src/diffpy/srmise/baselines/base.py @@ -71,7 +71,7 @@ def __init__( base=None, Cache=None, ): - """Set parameterdict defined by subclass + """Set parameterdict defined by subclass. parameterdict : dict The dictionary mapping string keys to their index in a @@ -91,7 +91,8 @@ def __init__( additional functionality. Cache : class The class (not instance) which implements caching of BaseFunction - evaluations.""" + evaluations. + """ BaseFunction.__init__(self, parameterdict, parformats, default_formats, metadict, base, Cache) # "Virtual" class methods #### @@ -120,7 +121,8 @@ class Baseline(ModelPart): """Represents a baseline associated with a BaselineFunction subclass.""" def __init__(self, owner, pars, free=None, removable=False, static_owner=False): - """Initialize the BaselineComponent instance with specified configurations. + """Initialize the BaselineComponent instance with specified + configurations. Parameters ---------- diff --git a/src/diffpy/srmise/baselines/fromsequence.py b/src/diffpy/srmise/baselines/fromsequence.py index 1866441..cf3ab12 100644 --- a/src/diffpy/srmise/baselines/fromsequence.py +++ b/src/diffpy/srmise/baselines/fromsequence.py @@ -23,11 +23,14 @@ class FromSequence(BaselineFunction): - """Methods for evaluation of a baseline from discrete data via interpolation. + """Methods for evaluation of a baseline from discrete data via + interpolation. - FromSequence uses cubic spline interpolation (no smoothing) on discrete - points to approximate the baseline at arbitrary points within the - interpolation domain. This baseline function permits no free parameters.""" + FromSequence uses cubic spline interpolation (no smoothing) on + discrete points to approximate the baseline at arbitrary points + within the interpolation domain. This baseline function permits no + free parameters. + """ def __init__(self, *args, **kwds): """Initialize a baseline object based on input sequences `x` and `y`. @@ -233,7 +236,7 @@ def xyrepr(self, var): return "[%s]" % ", ".join([repr(v) for v in var]) def readxy(self, filename): - """ """ + """""" from diffpy.srmise.srmiseerrors import SrMiseDataFormatError # TODO: Make this safer diff --git a/src/diffpy/srmise/baselines/nanospherical.py b/src/diffpy/srmise/baselines/nanospherical.py index a76719f..f87f7f0 100644 --- a/src/diffpy/srmise/baselines/nanospherical.py +++ b/src/diffpy/srmise/baselines/nanospherical.py @@ -22,7 +22,8 @@ class NanoSpherical(BaselineFunction): - """Methods for evaluation of baseline of spherical nanoparticle of uniform density. + """Methods for evaluation of baseline of spherical nanoparticle of uniform + density. Allowed formats are internal: [scale, radius] @@ -212,7 +213,8 @@ def _transform_parametersraw(self, pars, in_format, out_format): return temp def _valueraw(self, pars, r): - """Return value of spherical baseline for the given parameters and r values. + """Return value of spherical baseline for the given parameters and r + values. Outside the interval [0, radius] the baseline is 0. @@ -245,7 +247,8 @@ def _valueraw(self, pars, r): return out def _valueraw2(self, pars, r): - """Return value of spherical baseline without bounds checking for given parameters and r values. + """Return value of spherical baseline without bounds checking for given + parameters and r values. Parameters ---------- @@ -267,7 +270,7 @@ def _valueraw2(self, pars, r): return -s * r * (1 - (3.0 / 4.0) * rdivR + (1.0 / 16.0) * rdivR**3) def _getdomain(self, pars, r): - """Return slice object for which r > 0 and r < twice the radius + """Return slice object for which r > 0 and r < twice the radius. Parameters ---------- diff --git a/src/diffpy/srmise/baselines/polynomial.py b/src/diffpy/srmise/baselines/polynomial.py index 6ec155e..239b2c2 100644 --- a/src/diffpy/srmise/baselines/polynomial.py +++ b/src/diffpy/srmise/baselines/polynomial.py @@ -23,7 +23,8 @@ class Polynomial(BaselineFunction): - """Methods for evaluation and parameter estimation of a polynomial baseline.""" + """Methods for evaluation and parameter estimation of a polynomial + baseline.""" def __init__(self, degree, Cache=None): """Initialize a polynomial function of degree d. diff --git a/src/diffpy/srmise/dataclusters.py b/src/diffpy/srmise/dataclusters.py index 4a057c3..aad0d23 100644 --- a/src/diffpy/srmise/dataclusters.py +++ b/src/diffpy/srmise/dataclusters.py @@ -11,7 +11,8 @@ # See LICENSE.txt for license information. # ############################################################################## -"""Defines class to partition sequences representing the x and y axis into peak-like clusters.""" +"""Defines class to partition sequences representing the x and y axis into +peak-like clusters.""" import logging @@ -53,7 +54,7 @@ class DataClusters: """ def __init__(self, x, y, res): - """Constructor + """Constructor. Parameters ---------- @@ -102,8 +103,8 @@ def __eq__(self, other): ) def _clear(self): - """ - Clear all data and reset the cluster object to a transient initial state. + """Clear all data and reset the cluster object to a transient initial + state. The purpose of this method is to provide a clean state before creating new clustering operations. The object is updated in-place and no new instance is returned. @@ -176,7 +177,8 @@ def __next__(self): """Cluster point with largest y-coordinate left, returning self. next() always adds at least one additional point to the existing - cluster, or raises an exception if all points have been clustered. + cluster, or raises an exception if all points have been + clustered. """ if self.status == self.INIT: raise Exception("Cannot cluster next point while status is INIT.") @@ -465,7 +467,10 @@ def plot(self, *args, **kwds): return def animate(self): - """Animate clustering. Restores state when complete.""" + """Animate clustering. + + Restores state when complete. + """ clusters = self.clusters current_idx = self.current_idx lastcluster_idx = self.lastcluster_idx diff --git a/src/diffpy/srmise/modelcluster.py b/src/diffpy/srmise/modelcluster.py index 1525ddc..2c4c46d 100644 --- a/src/diffpy/srmise/modelcluster.py +++ b/src/diffpy/srmise/modelcluster.py @@ -40,7 +40,8 @@ class ModelCovariance(object): - """Helper class preserves uncertainty info (full covariance matrix) for a fit model. + """Helper class preserves uncertainty info (full covariance matrix) for a + fit model. This object preserves a light-weight "frozen" version of a model which can be used to interrogate the model about the uncertainties of its parameters. @@ -137,7 +138,8 @@ def setcovariance(self, model, cov): rawi += 1 def transform(self, in_format, out_format, **kwds): - """Transform parameters and covariance matrix under specified change of variables. + """Transform parameters and covariance matrix under specified change of + variables. By default this change applies to all parameters of the model. If the specified transformation is invalid for a given ModelPart the original parameterization is maintained for that part. @@ -226,7 +228,8 @@ def transform(self, in_format, out_format, **kwds): return def getcorrelation(self, i, j): - """Return the correlation between variables i and j, Corr_ij=Cov_ij/(sigma_i sigma_j) + """Return the correlation between variables i and j, + Corr_ij=Cov_ij/(sigma_i sigma_j) The variables may be specified as integers, or as a two-component tuple of integers (l, m) which indicate the mth parameter in peak l. @@ -262,8 +265,9 @@ def getcorrelation(self, i, j): def getvalue(self, i): """Return value of parameter i. - The variable may be specified as an integer, or as a two-component tuple of integers (l, m) - which indicate the mth parameter of modelpart l. + The variable may be specified as an integer, or as a two- + component tuple of integers (l, m) which indicate the mth + parameter of modelpart l. """ (l, m) = i if i in self.pmap else self.ipmap[i] return self.model[l][m] @@ -334,7 +338,8 @@ def get(self, i): return (self.getvalue(i), self.getuncertainty(i)) def correlationwarning(self, threshold=0.8): - """Report distinct variables with magnitude of correlation greater than threshold. + """Report distinct variables with magnitude of correlation greater than + threshold. Returns a list of tuples (i, j, c), where i and j are tuples indicating the modelpart and parameter indices of the correlated variables, and @@ -426,7 +431,6 @@ class ModelCluster(object): value: Return value of the model plus baseline valuebl: Return value of the baseline writestr: Return string representation of self. - """ def __init__(self, model, *args, **kwds): @@ -501,7 +505,8 @@ def __init__(self, model, *args, **kwds): def copy(self): """Return copy of this ModelCluster. - Equivalent to ModelCluster(self)""" + Equivalent to ModelCluster(self) + """ return ModelCluster(self) def addexternalpeaks(self, peaks): @@ -964,7 +969,8 @@ def deletepeak(self, idx): self.replacepeaks([], slice(idx, idx + 1)) def estimatepeak(self): - """Attempt to add single peak to empty cluster. Return True if successful. + """Attempt to add single peak to empty cluster. Return True if + successful. Returns ------- @@ -1149,7 +1155,10 @@ def contingent_fit(self, minpoints, growth_threshold): return None def cleanfit(self): - """Remove poor-quality peaks in the fit. Return number removed.""" + """Remove poor-quality peaks in the fit. + + Return number removed. + """ # Find peaks located outside the cluster pos = np.array([p["position"] for p in self.model]) left_idx = pos.searchsorted(self.r_cluster[0]) @@ -1219,7 +1228,8 @@ def reduce_to(self, x, y): Returns ------- ModelEvaluator or None - Return ModelEvaluator instance if fit changed, otherwise None.""" + Return ModelEvaluator instance if fit changed, otherwise None. + """ # No reduction necessary if self.model.value(x) < y: logger.debug("reduce_to: No reduction necessary.") @@ -1295,7 +1305,8 @@ def residual(self): return self.y_cluster - self.value() def quality(self, evaluator=None, **kwds): - """Return ModelEvaluator instance containing calculated quality of the model. + """Return ModelEvaluator instance containing calculated quality of the + model. ModelEvaluator objects may be compared as though they were numerical quantities. Its raw value is given by the 'stat' member. For more @@ -1323,7 +1334,8 @@ def quality(self, evaluator=None, **kwds): return evaluator_inst def plottable(self, joined=False): - """Return sequence suitable for plotting cluster model+baseline with matplotlib. + """Return sequence suitable for plotting cluster model+baseline with + matplotlib. Parameters ---------- @@ -1346,7 +1358,8 @@ def plottable(self, joined=False): return toreturn def plottable_residual(self): - """Return sequence suitable for plotting cluster residual with matplotlib. + """Return sequence suitable for plotting cluster residual with + matplotlib. Returns ------- @@ -1427,14 +1440,15 @@ def __str__(self): def prune(self): """Remove peaks until model quality no longer improves. - Peaks are removed in a greedy fashion, and the best possible model is - by no means guaranteed. + Peaks are removed in a greedy fashion, and the best possible + model is by no means guaranteed. - Due to the somewhat exploratory nature of prune many non-convergent - fits will generally be performed, but it severely restricts the number - of function evaluations permitted during fitting, and so fits that do - not converge rapidly are abandoned. Nevertheless, occasionally this - method will take an unusually long time to complete. + Due to the somewhat exploratory nature of prune many non- + convergent fits will generally be performed, but it severely + restricts the number of function evaluations permitted during + fitting, and so fits that do not converge rapidly are abandoned. + Nevertheless, occasionally this method will take an unusually + long time to complete. """ if len(self.model) == 0: return diff --git a/src/diffpy/srmise/modelevaluators/aic.py b/src/diffpy/srmise/modelevaluators/aic.py index 1a1973b..78fe6b8 100644 --- a/src/diffpy/srmise/modelevaluators/aic.py +++ b/src/diffpy/srmise/modelevaluators/aic.py @@ -46,12 +46,13 @@ class AIC(ModelEvaluator): """ def __init__(self): - """ """ + """""" ModelEvaluator.__init__(self, "AIC", False) return def evaluate(self, fit, count_fixed=False, kshift=0): - """Return quality of fit for given ModelCluster using AIC (Akaike's Information Criterion). + """Return quality of fit for given ModelCluster using AIC (Akaike's + Information Criterion). Parameters ---------- @@ -66,7 +67,8 @@ def evaluate(self, fit, count_fixed=False, kshift=0): Returns ------- quality : float - The quality of fit for given ModelCluster.""" + The quality of fit for given ModelCluster. + """ # Number of parameters. By default, fixed parameters are ignored. k = fit.model.npars(count_fixed=count_fixed) + kshift if k < 0: @@ -88,7 +90,8 @@ def evaluate(self, fit, count_fixed=False, kshift=0): return self.stat def minpoints(self, npars): - """Calculates the minimum number of points required to make an estimate of a model's quality. + """Calculates the minimum number of points required to make an estimate + of a model's quality. Parameters ---------- @@ -104,7 +107,8 @@ def minpoints(self, npars): return 1 def parpenalty(self, k): - """Returns the cost for adding k parameters to the current model cluster. + """Returns the cost for adding k parameters to the current model + cluster. Parameters ---------- @@ -124,8 +128,8 @@ def parpenalty(self, k): return (2 * k) * fudgefactor def growth_justified(self, fit, k_prime): - """Returns whether adding k_prime parameters to the given model (ModelCluster) is justified - given the current quality of the fit. + """Returns whether adding k_prime parameters to the given model + (ModelCluster) is justified given the current quality of the fit. The assumption is that adding k_prime parameters will result in "effectively 0" chiSquared cost, and so adding it is justified if the cost of adding @@ -170,7 +174,7 @@ def growth_justified(self, fit, k_prime): @staticmethod def akaikeweights(aics): - """Return sequence of Akaike weights for sequence of AICs + """Return sequence of Akaike weights for sequence of AICs. Parameters ---------- @@ -189,7 +193,7 @@ def akaikeweights(aics): @staticmethod def akaikeprobs(aics): - """Return sequence of Akaike probabilities for sequence of AICs + """Return sequence of Akaike probabilities for sequence of AICs. Parameters ---------- @@ -199,7 +203,8 @@ def akaikeprobs(aics): Returns ------- array-like - The sequence of Akaike probabilities""" + The sequence of Akaike probabilities + """ aic_weights = AIC.akaikeweights(aics) return aic_weights / np.sum(aic_weights) diff --git a/src/diffpy/srmise/modelevaluators/aicc.py b/src/diffpy/srmise/modelevaluators/aicc.py index b2a9286..3db773b 100644 --- a/src/diffpy/srmise/modelevaluators/aicc.py +++ b/src/diffpy/srmise/modelevaluators/aicc.py @@ -45,13 +45,13 @@ class AICc(ModelEvaluator): """ def __init__(self): - """ """ + """""" ModelEvaluator.__init__(self, "AICc", False) return def evaluate(self, fit, count_fixed=False, kshift=0): - """Return quality of fit for given ModelCluster using AICc (Akaike's Information Criterion - with 2nd order correction for small sample size). + """Return quality of fit for given ModelCluster using AICc (Akaike's + Information Criterion with 2nd order correction for small sample size). Parameters fit: A ModelCluster @@ -65,7 +65,8 @@ def evaluate(self, fit, count_fixed=False, kshift=0): Returns ------- float - Quality of AICc""" + Quality of AICc + """ # Number of parameters. By default, fixed parameters are ignored. k = fit.model.npars(count_fixed=count_fixed) + kshift if k < 0: @@ -87,7 +88,8 @@ def evaluate(self, fit, count_fixed=False, kshift=0): return self.stat def minpoints(self, npars): - """Calculates the minimum number of points required to make an estimate of a model's quality. + """Calculates the minimum number of points required to make an estimate + of a model's quality. Parameters ---------- @@ -105,7 +107,8 @@ def minpoints(self, npars): return npars + 2 def parpenalty(self, k, n): - """Returns the cost for adding k parameters to the current model cluster. + """Returns the cost for adding k parameters to the current model + cluster. Parameters ---------- @@ -128,7 +131,8 @@ def parpenalty(self, k, n): return (2 * k + float(2 * k * (k + 1)) / (n - k - 1)) * fudgefactor def growth_justified(self, fit, k_prime): - """Is adding k_prime parameters to ModelCluster justified given the current quality of the fit. + """Is adding k_prime parameters to ModelCluster justified given the + current quality of the fit. The assumption is that adding k_prime parameters will result in "effectively 0" chiSquared cost, and so adding it is justified if the cost of adding these parameters is less than the current @@ -171,7 +175,7 @@ def growth_justified(self, fit, k_prime): @staticmethod def akaikeweights(aics): - """Return sequence of Akaike weights for sequence of AICs + """Return sequence of Akaike weights for sequence of AICs. Parameters ---------- @@ -190,7 +194,7 @@ def akaikeweights(aics): @staticmethod def akaikeprobs(aics): - """Return sequence of Akaike probabilities for sequence of AICs + """Return sequence of Akaike probabilities for sequence of AICs. Parameters ---------- @@ -200,7 +204,8 @@ def akaikeprobs(aics): Returns ------- array-like - The sequence of Akaike probabilities""" + The sequence of Akaike probabilities + """ aic_weights = AICc.akaikeweights(aics) return aic_weights / np.sum(aic_weights) diff --git a/src/diffpy/srmise/modelevaluators/base.py b/src/diffpy/srmise/modelevaluators/base.py index 179e082..f190e27 100644 --- a/src/diffpy/srmise/modelevaluators/base.py +++ b/src/diffpy/srmise/modelevaluators/base.py @@ -48,12 +48,14 @@ class ModelEvaluator: - """Class for evaluating the quality of a fit. Comparison between different - models of the same type is defined so that better models are 'greater than' - worse models.""" + """Class for evaluating the quality of a fit. + + Comparison between different models of the same type is defined so + that better models are 'greater than' worse models. + """ def __init__(self, method, higher_is_better): - """Constructor of ModelEvaluator + """Constructor of ModelEvaluator. Parameters ---------- @@ -69,7 +71,7 @@ def __init__(self, method, higher_is_better): return def __lt__(self, other): - """ """ + """""" assert self.method == other.method # Comparison between same types required assert self.stat is not None and other.stat is not None # The statistic must already be calculated @@ -80,7 +82,7 @@ def __lt__(self, other): return other.stat < self.stat def __le__(self, other): - """ """ + """""" assert self.method == other.method # Comparison between same types required assert self.stat is not None and other.stat is not None # The statistic must already be calculated @@ -91,7 +93,7 @@ def __le__(self, other): return other.stat <= self.stat def __eq__(self, other): - """ """ + """""" assert self.method == other.method # Comparison between same types required assert self.stat is not None and other.stat is not None # The statistic must already be calculated @@ -99,7 +101,7 @@ def __eq__(self, other): return self.stat == other.stat def __ne__(self, other): - """ """ + """""" assert self.method == other.method # Comparison between same types required assert self.stat is not None and other.stat is not None # The statistic must already be calculated @@ -107,7 +109,7 @@ def __ne__(self, other): return self.stat != other.stat def __gt__(self, other): - """ """ + """""" assert self.method == other.method # Comparison between same types required assert self.stat is not None and other.stat is not None # The statistic must already be calculated @@ -118,7 +120,7 @@ def __gt__(self, other): return other.stat > self.stat def __ge__(self, other): - """ """ + """""" assert self.method == other.method # Comparison between same types required assert self.stat is not None and other.stat is not None # The statistic must already be calculated @@ -138,7 +140,8 @@ def chi_squared(self, expected, observed, error): observed : float The observed value. error : float - The error statistic.""" + The error statistic. + """ self.chisq = np.sum((expected - observed) ** 2 / error**2) return self.chisq diff --git a/src/diffpy/srmise/modelparts.py b/src/diffpy/srmise/modelparts.py index 43a2141..652d9ea 100644 --- a/src/diffpy/srmise/modelparts.py +++ b/src/diffpy/srmise/modelparts.py @@ -569,7 +569,8 @@ def compress(self): Returns ------- pars : array-like - The compressed parameters of the model part.""" + The compressed parameters of the model part. + """ return self.pars[self.free] def jacobian(self, r, range=None): @@ -596,7 +597,8 @@ def owner(self): Returns ------- BaseFunction subclass - The BaseFunction subclass which owns this part.""" + The BaseFunction subclass which owns this part. + """ return self._owner def update(self, freepars): @@ -727,7 +729,8 @@ def npars(self, count_fixed=True): Returns ------- int - The number of parameters in all parts.""" + The number of parameters in all parts. + """ if count_fixed: return self._owner.npars else: @@ -738,7 +741,7 @@ def __str__(self): return str(self._owner.transform_parameters(self.pars, in_format="internal", out_format="default_output")) def __eq__(self, other): - """ """ + """""" if hasattr(other, "_owner"): return ( (self._owner is other._owner) @@ -750,7 +753,7 @@ def __eq__(self, other): return False def __ne__(self, other): - """ """ + """""" return not self == other def writestr(self, ownerlist): diff --git a/src/diffpy/srmise/multimodelselection.py b/src/diffpy/srmise/multimodelselection.py index c4c7b74..a29edd8 100644 --- a/src/diffpy/srmise/multimodelselection.py +++ b/src/diffpy/srmise/multimodelselection.py @@ -36,7 +36,7 @@ class MultimodelSelection(PeakStability): """Quick and dirty multimodel selection using AIC and its offspring.""" def __init__(self): - """ """ + """""" self.dgs = np.array([]) self.dgs_idx = {} @@ -203,7 +203,8 @@ def animate_probs(self, step=False, duration=0.0, **kwds): duration : float Minimum time in seconds to complete animation. Default is 0. - Keywords passed to pyplot.plot()""" + Keywords passed to pyplot.plot() + """ if duration > 0: import time @@ -248,7 +249,8 @@ def animate_classprobs(self, step=False, duration=0.0, **kwds): duration : float Minimum time in seconds to complete animation. Default is 0. - Keywords passed to pyplot.plot()""" + Keywords passed to pyplot.plot() + """ if duration > 0: import time @@ -461,7 +463,8 @@ def dg_key(self, dg_in): Returns ------- float - The dg value usable as a key nearest to dg_in.""" + The dg value usable as a key nearest to dg_in. + """ idx = (np.abs(self.dgs - dg_in)).argmin() return self.dgs[idx] @@ -476,7 +479,8 @@ def bestclasses(self, dgs=None): Returns ------- array-like - The best classes for all models.""" + The best classes for all models. + """ if dgs is None: dgs = self.dgs best = [] @@ -518,7 +522,8 @@ def classbestdgs(self, cls, dgs=None): Returns ------- array-like - Sequence of best uncertainties for the models.""" + Sequence of best uncertainties for the models. + """ if dgs is None: dgs = self.dgs bestdgs = [] @@ -528,7 +533,8 @@ def classbestdgs(self, cls, dgs=None): return bestdgs def modelbestdgs(self, model, dgs=None): - """Return uncertainties where given model has greatest Akaike probability. + """Return uncertainties where given model has greatest Akaike + probability. Parameters ---------- @@ -587,7 +593,8 @@ def plot3dclassprobs(self, **kwds): "fig" - The figure "axis" - The image axis "cbaxis" - The colorbar axis, if it exists. - "cb" - The colorbar, if it exists.""" + "cb" - The colorbar, if it exists. + """ from matplotlib import cm, colorbar, colors from matplotlib.collections import PolyCollection @@ -807,7 +814,8 @@ def get_prob(self, dG, **kwds): return self.classprobs[dG][cls_idx] def get_nfree(self, dG, **kwds): - """Return number of free parameters of best model of best class at given dG. + """Return number of free parameters of best model of best class at + given dG. Parameters ---------- @@ -832,7 +840,8 @@ def get_nfree(self, dG, **kwds): return model.npars(count_fixed=False) + baseline.npars(count_fixed=False) def get_aic(self, dG, **kwds): - """Return number of free parameters of best model of best class at given dG. + """Return number of free parameters of best model of best class at + given dG. Parameters ---------- @@ -855,7 +864,8 @@ def get_aic(self, dG, **kwds): return self.aics[dG][idx].stat def get(self, dG, *args, **kwds): - """Return tuple of values corresponding to string arguments for best model of best class at given dG. + """Return tuple of values corresponding to string arguments for best + model of best class at given dG. Parameters ---------- @@ -891,7 +901,8 @@ def get(self, dG, *args, **kwds): return tuple(values) def maxprobdG_byclass(self, model): - """Return the post-hoc dG for which the given model's Akaike probability is maximized. + """Return the post-hoc dG for which the given model's Akaike + probability is maximized. Each model is mapped to its class' best member. @@ -911,8 +922,8 @@ def maxprobdG_byclass(self, model): return self.dgs[prob_idx] def maxprobdG_bymodel(self, model): - """Return the post-hoc dG for which the given model's Akaike probability is maximized. - Classes are not considered. + """Return the post-hoc dG for which the given model's Akaike + probability is maximized. Classes are not considered. Parameters ---------- @@ -941,14 +952,15 @@ def maxprobmodel_byclass(self, dG): Returns ------- float - The model mapped by class which maximizes probability at given dG.""" + The model mapped by class which maximizes probability at given dG. + """ cls = self.sortedclassprobs[dG][-1] m = self.sortedclasses[dG][cls][-1] return m def maxprobmodel_bymodel(self, dG): - """Return the model which maximizes probability at given dG. - Classes are not considered. + """Return the model which maximizes probability at given dG. Classes + are not considered. Parameters ---------- @@ -958,6 +970,7 @@ def maxprobmodel_bymodel(self, dG): Returns ------- model : array-like - The model which maximizes probability at given dG.""" + The model which maximizes probability at given dG. + """ # Note that if there are identical models this returns the one of greatest dg. return self.sortedprobs[dG][-1] diff --git a/src/diffpy/srmise/pdfdataset.py b/src/diffpy/srmise/pdfdataset.py index 6f41d30..a668828 100644 --- a/src/diffpy/srmise/pdfdataset.py +++ b/src/diffpy/srmise/pdfdataset.py @@ -14,10 +14,7 @@ # LICENSE_PDFgui.txt for the full PDFgui license. # ############################################################################## - - -"""class PDFDataSet for experimental PDF data. -""" +"""Class PDFDataSet for experimental PDF data.""" import os.path @@ -32,7 +29,7 @@ class PDFComponent(object): """Common base class.""" def __init__(self, name): - """initialize the object + """Initialize the object. Parameter --------- @@ -42,7 +39,7 @@ def __init__(self, name): self.name = name def close(self, force=False): - """close myself + """Close myself. Parameter --------- @@ -122,9 +119,11 @@ def __init__(self, name): return def clear(self): - """reset all data members to initial empty values + """Reset all data members to initial empty values. - The purpose of this method is to set the PDF dataset to initial empty values.""" + The purpose of this method is to set the PDF dataset to initial + empty values. + """ self.robs = [] self.Gobs = [] self.drobs = [] @@ -143,8 +142,8 @@ def clear(self): return def setvar(self, var, value): - """Assign a data member using PdfFit-style variable notation. - This method is typically utilized by the `applyParameters()` function. + """Assign a data member using PdfFit-style variable notation. This + method is typically utilized by the `applyParameters()` function. Parameters ---------- @@ -169,8 +168,8 @@ def setvar(self, var, value): return def getvar(self, var): - """Obtain value corresponding to PdfFit dataset variable. - Used by findParameters(). + """Obtain value corresponding to PdfFit dataset variable. Used by + findParameters(). Parameters ---------- @@ -192,7 +191,7 @@ def getvar(self, var): return value def read(self, filename): - """load data from PDFGetX2 or PDFGetN gr file + """Load data from PDFGetX2 or PDFGetN gr file. filename : str file to read from @@ -217,7 +216,7 @@ def read(self, filename): return self def readStr(self, datastring): - """read experimental PDF data from a string + """Read experimental PDF data from a string. Parameter --------- @@ -364,7 +363,6 @@ def write(self, filename): def writeStr(self): """String representation of experimental PDF data. - Returns ------- str @@ -411,7 +409,7 @@ def writeStr(self): return datastring def copy(self, other=None): - """copy self to other. if other is None, create new instance + """Copy self to other. if other is None, create new instance. Parameters ---------- diff --git a/src/diffpy/srmise/pdfpeakextraction.py b/src/diffpy/srmise/pdfpeakextraction.py index 6142e68..a914eb8 100644 --- a/src/diffpy/srmise/pdfpeakextraction.py +++ b/src/diffpy/srmise/pdfpeakextraction.py @@ -36,8 +36,8 @@ class PDFPeakExtraction(PeakExtraction): - """PDFPeakExtraction extends the PeakExtraction class to specialize in extracting - peaks from PDF (Probability Density Function) data. + """PDFPeakExtraction extends the PeakExtraction class to specialize in + extracting peaks from PDF (Probability Density Function) data. Parameters ---------- @@ -77,7 +77,6 @@ def loadpdf(self, pdf): ---------- pdf: PDFDataSet instance or str The PDFDataSet instance or a PDF file name. - """ self.clear() if isinstance(pdf, PDFDataSet): @@ -98,7 +97,8 @@ def setdata(self, x, y, dx=None, dy=None): x : array-like The x-coordinates of the data. y : array-like - The y-coordinates of the data.""" + The y-coordinates of the data. + """ PeakExtraction.setdata(self, x, y, dx, dy) try: self.qmax_fromdata = find_qmax(self.x, self.y)[0] @@ -108,7 +108,9 @@ def setdata(self, x, y, dx=None, dy=None): def clear(self): """Clear all members. - The purpose of the method is to ensure the object is in a clean state.""" + The purpose of the method is to ensure the object is in a clean + state. + """ # TODO: Clear additional members self.filename = None self.nyquist = None @@ -190,7 +192,8 @@ def defaultvars(self, *args): Parameters ---------- *args : argparse.Namespace - Arguments passed to PeakExtraction.setdata().""" + Arguments passed to PeakExtraction.setdata(). + """ nargs = list(args) # qmax preference: reported, then fromdata, then 0. @@ -250,7 +253,8 @@ def defaultvars(self, *args): PeakExtraction.defaultvars(self, *nargs) def resampledata(self, dr, **kwds): - """Return (x, y, error in x, effective error in y) resampled by interval dr. + """Return (x, y, error in x, effective error in y) resampled by + interval dr. Uses values of self.x, self.y, self.dx, self.effective_dy. The range is constrained by self.rng. @@ -276,7 +280,8 @@ def resampledata(self, dr, **kwds): Returns ------- tuple of ndarray - A tuple containing the resampled (x, y, error in x, effective error in y).""" + A tuple containing the resampled (x, y, error in x, effective error in y). + """ self.defaultvars() # Find correct range if necessary. eps = kwds.get("eps", 10**-6) @@ -318,7 +323,8 @@ def errorscale(self, dr): Returns ------- float - The uncertainties scaled.""" + The uncertainties scaled. + """ if self.qmax > 0 and self.nyquist and self.scale: dr_nyquist = np.pi / self.qmax return np.max([np.sqrt(dr_nyquist / dr), 1.0]) @@ -326,7 +332,8 @@ def errorscale(self, dr): return 1.0 def extract(self, **kwds): - """Extract peaks from the PDF. Returns ModelCovariance instance summarizing results. + """Extract peaks from the PDF. Returns ModelCovariance instance + summarizing results. Parameters ---------- @@ -540,7 +547,8 @@ def extract(self, **kwds): return cov def fit(self, **kwds): - """Fit peaks in the PDF. Returns ModelCovariance instance summarizing results. + """Fit peaks in the PDF. Returns ModelCovariance instance summarizing + results. Parameters ---------- @@ -1047,7 +1055,8 @@ def stdratio(data): ------- array-like an array of length floor(len(data)/2)-1. The ith element is - equivalent to std(data[:i+2])/std(data[i+2:2i+4]).""" + equivalent to std(data[:i+2])/std(data[i+2:2i+4]). + """ limit = int(np.floor(len(data) / 2)) std_left = np.zeros(limit) diff --git a/src/diffpy/srmise/peakextraction.py b/src/diffpy/srmise/peakextraction.py index dd0b0cd..645e406 100644 --- a/src/diffpy/srmise/peakextraction.py +++ b/src/diffpy/srmise/peakextraction.py @@ -70,7 +70,8 @@ def __init__(self, newvars=[]): Parameters newvars : array-like - Sequence of strings that represent additional extraction parameters.""" + Sequence of strings that represent additional extraction parameters. + """ self.clear() self.extractvars = dict.fromkeys( ( @@ -94,7 +95,9 @@ def __init__(self, newvars=[]): def clear(self): """Clear all members. - The purpose of the method is to ensure the object is in initialized state.""" + The purpose of the method is to ensure the object is in + initialized state. + """ self.x = None self.y = None self.dx = None @@ -263,7 +266,8 @@ def __str__(self): return "\n".join(out) + "\n" def plot(self, **kwds): - """Convenience function to plot data and extracted peaks with matplotlib. + """Convenience function to plot data and extracted peaks with + matplotlib. Uses initial peaks instead if no peaks have been extracted. @@ -299,7 +303,7 @@ def plot(self, **kwds): plt.plot(*mcluster.plottable(kwds)) def read(self, filename): - """load PeakExtraction object from file + """Load PeakExtraction object from file. Parameters ---------- @@ -785,7 +789,8 @@ def estimate_peak(self, x, add=True): return None def add_peaks(self, peaks): - """Add peaks to extracted peaks, or initial_peaks if no extracted peaks exist. + """Add peaks to extracted peaks, or initial_peaks if no extracted peaks + exist. Parameters ---------- @@ -801,14 +806,16 @@ def add_peaks(self, peaks): self.initial_peaks.sort(key="position") def extract_single(self, recursion_depth=1): - """Find ModelCluster with peaks extracted from data. Return ModelCovariance instance at top level. + """Find ModelCluster with peaks extracted from data. Return + ModelCovariance instance at top level. Every extracted peak is one of the peak functions supplied. All comparisons of different peak models are performed with the class specified by error_method. Parameters - recursion_depth: (1) Tracks recursion with extract_single.""" + recursion_depth: (1) Tracks recursion with extract_single. + """ self.clearcalc() tracer = srmiselog.tracer tracer.pushc() @@ -1319,8 +1326,10 @@ def extract_single(self, recursion_depth=1): return cov def fit_single(self): - """Fit peaks in initial_peaks with baseline. Return ModelCovariance - instance summarizing results.""" + """Fit peaks in initial_peaks with baseline. + + Return ModelCovariance instance summarizing results. + """ self.clearcalc() diff --git a/src/diffpy/srmise/peaks/base.py b/src/diffpy/srmise/peaks/base.py index 44c7963..c106332 100644 --- a/src/diffpy/srmise/peaks/base.py +++ b/src/diffpy/srmise/peaks/base.py @@ -70,7 +70,7 @@ def __init__( base=None, Cache=None, ): - """Set parameterdict defined by subclass + """Set parameterdict defined by subclass. parameterdict: A dictionary mapping string keys to their index in a sequence of parameters for this PeakFunction subclass. @@ -85,7 +85,8 @@ def __init__( base: A basefunction subclass instance which this one decorates with additional functionality. Cache: A class (not instance) which implements caching of BaseFunction - evaluations.""" + evaluations. + """ if "position" not in parameterdict: emsg = "Argument parameterdict missing required key 'position'." raise ValueError(emsg) @@ -125,7 +126,8 @@ def __init__(self, *args, **kwds): ModelParts.__init__(self, *args, **kwds) def argsort(self, key="position"): - """Return sequence of indices which sort peaks in order specified by key.""" + """Return sequence of indices which sort peaks in order specified by + key.""" keypars = np.array([p[key] for p in self]) # In normal use the peaks will already be sorted, so check for it. sorted = True diff --git a/src/diffpy/srmise/peaks/gaussian.py b/src/diffpy/srmise/peaks/gaussian.py index c23358e..9f4f98f 100644 --- a/src/diffpy/srmise/peaks/gaussian.py +++ b/src/diffpy/srmise/peaks/gaussian.py @@ -23,7 +23,8 @@ class Gaussian(PeakFunction): - """Methods for evaluation and parameter estimation of width-limited Gaussian. + """Methods for evaluation and parameter estimation of width-limited + Gaussian. Allowed formats are internal: [position, parameterized width-squared, area] @@ -44,8 +45,8 @@ class Gaussian(PeakFunction): # which the function is considered 0. By default this distance is # equivalent to 3 standard deviations. def __init__(self, maxwidth, Cache=None): - """maxwidth defined as full width at half maximum for the - corresponding Gaussian, which is physically relevant.""" + """Maxwidth defined as full width at half maximum for the corresponding + Gaussian, which is physically relevant.""" parameterdict = {"position": 0, "width": 1, "area": 2} formats = ["internal", "pwa", "mu_sigma_area"] default_formats = {"default_input": "internal", "default_output": "pwa"} @@ -172,7 +173,8 @@ def scale_at(self, pars, x, scale): Returns ------- tuple - mu, area, and sigma that are scaled.""" + mu, area, and sigma that are scaled. + """ if scale <= 0: emsg = "".join(["Cannot scale by ", str(scale), "."]) raise SrMiseScalingError(emsg) @@ -346,7 +348,8 @@ def _transform_parametersraw(self, pars, in_format, out_format): return temp def _valueraw(self, pars, r): - """Compute the value of a width-limited Gaussian for the specified parameters at given radial distances. + """Compute the value of a width-limited Gaussian for the specified + parameters at given radial distances. This function calculates the value of a Gaussian distribution, where its effective width is constrained and related to the maxwidth. As `pars[1]` approaches infinity, @@ -383,6 +386,7 @@ def getmodule(self): def max(self, pars): """Return position and height of the peak maximum. + Parameters ---------- pars : array_like @@ -391,7 +395,8 @@ def max(self, pars): Returns ------- array_like - The position and height of the peak maximum.""" + The position and height of the peak maximum. + """ # TODO: Reconsider this behavior if len(pars) == 0: return None diff --git a/src/diffpy/srmise/peaks/gaussianoverr.py b/src/diffpy/srmise/peaks/gaussianoverr.py index 6e108e6..9d7a66f 100644 --- a/src/diffpy/srmise/peaks/gaussianoverr.py +++ b/src/diffpy/srmise/peaks/gaussianoverr.py @@ -23,7 +23,8 @@ class GaussianOverR(PeakFunction): - """Methods for evaluation and parameter estimation of width-limited Gaussian/r. + """Methods for evaluation and parameter estimation of width-limited + Gaussian/r. Allowed formats are internal: [position, parameterized width-squared, area] @@ -44,8 +45,8 @@ class GaussianOverR(PeakFunction): # which the function is considered 0. By default this distance is # equivalent to 3 standard deviations. def __init__(self, maxwidth, Cache=None): - """maxwidth defined as full width at half maximum for the - corresponding Gaussian, which is physically relevant.""" + """Maxwidth defined as full width at half maximum for the corresponding + Gaussian, which is physically relevant.""" parameterdict = {"position": 0, "width": 1, "area": 2} formats = ["internal", "pwa", "mu_sigma_area"] default_formats = {"default_input": "internal", "default_output": "pwa"} @@ -221,8 +222,7 @@ def scale_at(self, pars, x, scale): return tpars def _jacobianraw(self, pars, r, free): - """ - Compute the Jacobian of a width-limited Gaussian/r function. + """Compute the Jacobian of a width-limited Gaussian/r function. This method calculates the partial derivatives of a Gaussian/r function with respect to its parameters, considering a limiting width. The Gaussian/r's @@ -285,7 +285,8 @@ def _jacobianraw(self, pars, r, free): return jacobian def _transform_derivativesraw(self, pars, in_format, out_format): - """Return gradient matrix for the pars converted from in_format to out_format. + """Return gradient matrix for the pars converted from in_format to + out_format. Parameters pars: Sequence of parameters @@ -412,7 +413,8 @@ def _transform_parametersraw(self, pars, in_format, out_format): return temp def _valueraw(self, pars, r): - """Compute the value of a width-limited Gaussian/r for the specified parameters at given radial distances. + """Compute the value of a width-limited Gaussian/r for the specified + parameters at given radial distances. This function calculates the value of a Gaussian/r distribution, where its effective width is constrained and related to the maxwidth. As `pars[1]` approaches infinity, @@ -456,7 +458,8 @@ def max(self, pars): Returns ------- array-like - The sequence of position and height of the peak maximum.""" + The sequence of position and height of the peak maximum. + """ # TODO: Reconsider this behavior if len(pars) == 0: return None diff --git a/src/diffpy/srmise/peaks/terminationripples.py b/src/diffpy/srmise/peaks/terminationripples.py index c516c96..bf2bfb9 100644 --- a/src/diffpy/srmise/peaks/terminationripples.py +++ b/src/diffpy/srmise/peaks/terminationripples.py @@ -23,10 +23,12 @@ class TerminationRipples(PeakFunction): - """Methods for evaluation and parameter estimation of a peak function with termination ripples.""" + """Methods for evaluation and parameter estimation of a peak function with + termination ripples.""" def __init__(self, base, qmax, extension=4.0, supersample=5.0, Cache=None): - """Peak function constructor which adds termination ripples to existing function. + """Peak function constructor which adds termination ripples to existing + function. Unlike other peak functions, TerminationRipples can only be evaluated over a uniform grid, or at a single value using an ad hoc uniform grid @@ -46,7 +48,8 @@ def __init__(self, base, qmax, extension=4.0, supersample=5.0, Cache=None): cannot be determined while extending calculations. Default is 5.0. Cache : class The class (not instance) which implements caching of PeakFunction - evaluations.""" + evaluations. + """ parameterdict = base.parameterdict formats = base.parformats default_formats = base.default_formats @@ -131,7 +134,8 @@ def _jacobianraw(self, pars, r, free): return self.base._jacobianraw(pars, r, free) def _transform_derivativesraw(self, pars, in_format, out_format): - """Return gradient matrix for the pars converted from in_format to out_format. + """Return gradient matrix for the pars converted from in_format to + out_format. Parameters ---------- @@ -169,7 +173,8 @@ def _transform_parametersraw(self, pars, in_format, out_format): return self.base._transform_parametersraw(pars, in_format, out_format) def _valueraw(self, pars, r): - """Return value of base peak function for the given parameters and r values. + """Return value of base peak function for the given parameters and r + values. pars : array-like The sequence of parameters for a single peak @@ -179,7 +184,8 @@ def _valueraw(self, pars, r): Returns ------- float - The value of base peak function for the given parameters and r.""" + The value of base peak function for the given parameters and r. + """ return self.base._valueraw(pars, r) # Overridden PeakFunction functions #### @@ -205,7 +211,8 @@ def jacobian(self, peak, r, rng=None): Returns ------- jac : array-like - The Jacobian of base function with termination ripples.""" + The Jacobian of base function with termination ripples. + """ if self is not peak._owner: raise ValueError( "Argument 'peak' must be evaluated by the " @@ -361,7 +368,8 @@ def extend_grid(self, r, dr): Returns ------- tuple - The extended r, slice giving original range.""" + The extended r, slice giving original range. + """ ext = self.extension * 2 * np.pi / self.qmax left_ext = np.arange(r[0] - dr, max(0.0, r[0] - ext - dr), -dr)[::-1] right_ext = np.arange(r[-1] + dr, r[-1] + ext + dr, dr) diff --git a/src/diffpy/srmise/peakstability.py b/src/diffpy/srmise/peakstability.py index 28c9517..f95774b 100644 --- a/src/diffpy/srmise/peakstability.py +++ b/src/diffpy/srmise/peakstability.py @@ -29,7 +29,8 @@ class PeakStability: """Utility to test robustness of peaks. results: [error scalar, model, bl, dr] - ppe: a PDFPeakExtraction instance""" + ppe: a PDFPeakExtraction instance + """ def __init__(self): self.results = [] @@ -106,7 +107,10 @@ def plotseries(self, style="o", **kwds): plt.draw() def plot(self, **kwds): - """Plot the current model. Keywords passed to pyplot.plot()""" + """Plot the current model. + + Keywords passed to pyplot.plot() + """ plt.clf() plt.plot(*self.ppe.extracted.plottable(), **kwds) q = self.ppe.extracted.quality() @@ -187,7 +191,8 @@ def run(self, err, savecovs=False): The sequence of uncertainties to run at. savecovs : bool boolean to determine to save covariance matrix. Default is False. - If savecovs is True, return the covariance matrix for each final fit.""" + If savecovs is True, return the covariance matrix for each final fit. + """ self.results = [] covs = [] diff --git a/src/diffpy/srmise/srmiseerrors.py b/src/diffpy/srmise/srmiseerrors.py index 62953d5..22e8948 100644 --- a/src/diffpy/srmise/srmiseerrors.py +++ b/src/diffpy/srmise/srmiseerrors.py @@ -13,20 +13,20 @@ ############################################################################## """Defines all custom exceptions used by diffpy.srmise. - Classes - ------- - SrMiseError: Subclass of Exception, and superclass of all diffpy.srmise exceptions. - SrMiseDataFormatError: Error in format of diffpy.srmise data. - SrMiseEstimationError: Parameter estimation error. - SrMiseFileError: Error while reading/writing files. - SrMiseFitError: Error while fitting. - SrMiseLogError: Error while logging. - SrMiseModelEvaluatorError: Error while computing or comparing model quality. - SrMisePDFKeyError: Error in key referencing component of PDF dataset. - SrMiseQmaxError: Error in value of Qmax. - SrMiseScalingError: Error while scaling a peak function. - SrMiseStaticOwnerError: Error when changing ModelPart instance owner. - """ +Classes +------- +SrMiseError: Subclass of Exception, and superclass of all diffpy.srmise exceptions. +SrMiseDataFormatError: Error in format of diffpy.srmise data. +SrMiseEstimationError: Parameter estimation error. +SrMiseFileError: Error while reading/writing files. +SrMiseFitError: Error while fitting. +SrMiseLogError: Error while logging. +SrMiseModelEvaluatorError: Error while computing or comparing model quality. +SrMisePDFKeyError: Error in key referencing component of PDF dataset. +SrMiseQmaxError: Error in value of Qmax. +SrMiseScalingError: Error while scaling a peak function. +SrMiseStaticOwnerError: Error when changing ModelPart instance owner. +""" # Superclass class for diffpy.srmise.mise @@ -34,9 +34,10 @@ class SrMiseError(Exception): """Superclass of all diffpy.srmise exceptions.""" def __init__(self, info): - """initialize + """initialize. - info: description string""" + info: description string + """ Exception.__init__(self) self.info = info @@ -48,120 +49,168 @@ def __str__(self): class SrMiseDataFormatError(SrMiseError): - """diffpy.srmise exception class. Error in formatted data.""" + """diffpy.srmise exception class. + + Error in formatted data. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseEstimationError(SrMiseError): - """diffpy.srmise.modelevaluator exception class. Parameter estimation error.""" + """diffpy.srmise.modelevaluator exception class. + + Parameter estimation error. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseFileError(SrMiseError): - """diffpy.srmise exception class. Error while reading/writing files.""" + """diffpy.srmise exception class. + + Error while reading/writing files. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseFitError(SrMiseError): - """diffpy.srmise exception class. Error occurred during fitting.""" + """diffpy.srmise exception class. + + Error occurred during fitting. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseLogError(SrMiseError): - """diffpy.srmise exception class. Error while handling logging capabilities.""" + """diffpy.srmise exception class. + + Error while handling logging capabilities. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseModelEvaluatorError(SrMiseError): - """diffpy.srmise.modelevaluator exception class. Error when comparing models.""" + """diffpy.srmise.modelevaluator exception class. + + Error when comparing models. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseQmaxError(SrMiseError): - """diffpy.srmise.modelevaluator exception class. Error when setting qmax.""" + """diffpy.srmise.modelevaluator exception class. + + Error when setting qmax. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseScalingError(SrMiseError): - """diffpy.srmise.peaks exception class. Error when scaling a peak function.""" + """diffpy.srmise.peaks exception class. + + Error when scaling a peak function. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseStaticOwnerError(SrMiseError): - """diffpy.srmise exception class. Attempt to change owner of static model part.""" + """diffpy.srmise exception class. + + Attempt to change owner of static model part. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseTransformationError(SrMiseError): - """diffpy.srmise exception class. Error transforming model/covariance parameters.""" + """diffpy.srmise exception class. + + Error transforming model/covariance parameters. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMiseUndefinedCovarianceError(SrMiseError): - """diffpy.srmise exception class. Attempted to perform on undefined covariance.""" + """diffpy.srmise exception class. + + Attempted to perform on undefined covariance. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) class SrMisePDFKeyError(SrMiseError): - """diffpy.srmise exception class. Requested PDF key can't be found.""" + """diffpy.srmise exception class. + + Requested PDF key can't be found. + """ def __init__(self, info): - """initialize + """initialize. - info -- description string""" + info -- description string + """ SrMiseError.__init__(self, info) diff --git a/src/diffpy/srmise/srmiselog.py b/src/diffpy/srmise/srmiselog.py index e4311a0..5393475 100644 --- a/src/diffpy/srmise/srmiselog.py +++ b/src/diffpy/srmise/srmiselog.py @@ -95,7 +95,8 @@ def setfilelevel(level): """Set level of file logger. Parameters - level: The logging level.""" + level: The logging level. + """ global fh if fh is not None: level = LEVELS.get(level, level) @@ -111,7 +112,8 @@ def setlevel(level): """Set level of default (stdout) logger. Parameters - level: The logging level.""" + level: The logging level. + """ global ch level = LEVELS.get(level, level) ch.setLevel(level) @@ -127,7 +129,8 @@ def liveplotting(lp, w=False): Parameters lp: Use live plotting (True) or not (False). - w: (False) Whether to wait for user after plotting.""" + w: (False) Whether to wait for user after plotting. + """ global liveplots global wait if lp is True or lp is False: @@ -172,8 +175,8 @@ def __init__(self, **kwds): def emit(self, *args, **kwds): """Write current trace to file. - Parameters - Any number of ModelCluster instances""" + Parameters Any number of ModelCluster instances + """ if not eval(self.filter): return else: @@ -236,7 +239,8 @@ def read(self, filename): "clusters" - List of cluster regions [[r0,r1],[r2,r3],...] "counter" - The count when object was created "mc" - A ModelCluster instance - "recursion" - The recursion level of mc""" + "recursion" - The recursion level of mc + """ try: return self.readstr(open(filename, "rb").read()) except SrMiseDataFormatError as err: @@ -258,7 +262,8 @@ def readstr(self, datastring): "clusters" - List of cluster regions [[r0,r1],[r2,r3],...] "counter" - The count when object was created "mc" - A ModelCluster instance - "recursion" - The recursion level of mc""" + "recursion" - The recursion level of mc + """ # find where the ModelCluster section starts res = re.search(r"^#+ ModelCluster\s*(?:#.*\s+)*", datastring, re.M) diff --git a/src/diffpy/srmise/version.py b/src/diffpy/srmise/version.py index 304027c..129ef83 100644 --- a/src/diffpy/srmise/version.py +++ b/src/diffpy/srmise/version.py @@ -12,7 +12,6 @@ # See LICENSE.rst for license information. # ############################################################################## - """Definition of __version__.""" # We do not use the other three variables, but can be added back if needed. diff --git a/src/diffpy_srmise/__init__.py b/src/diffpy_srmise/__init__.py new file mode 100644 index 0000000..59379bf --- /dev/null +++ b/src/diffpy_srmise/__init__.py @@ -0,0 +1,24 @@ +#!/usr/bin/env python +############################################################################## +# +# (c) 2025 The Trustees of Columbia University in the City of New York. +# All rights reserved. +# +# File coded by: Simon Billinge, Billinge Group members. +# +# See GitHub contributions for a more detailed list of contributors. +# https://github.com/diffpy/diffpy-srmise/graphs/contributors +# +# See LICENSE.rst for license information. +# +############################################################################## +"""Peak extraction and peak fitting tool for atomic pair distribution +functions.""" + +# package version +from diffpy_srmise.version import __version__ # noqa + +# silence the pyflakes syntax checker +assert __version__ or True + +# End of file diff --git a/src/diffpy_srmise/functions.py b/src/diffpy_srmise/functions.py new file mode 100644 index 0000000..e7e2c8e --- /dev/null +++ b/src/diffpy_srmise/functions.py @@ -0,0 +1,31 @@ +import numpy as np + + +def dot_product(a, b): + """Compute the dot product of two vectors of any size. + + Ensure that the inputs, a and b, are of the same size. + The supported types are "array_like" objects, which can + be converted to a NumPy array. Examples include lists and tuples. + + Parameters + ---------- + a : array_like + The first input vector. + b : array_like + The second input vector. + + Returns + ------- + float + The dot product of the two vectors. + + Examples + -------- + Compute the dot product of two lists: + >>> a = [1, 2, 3] + >>> b = [4, 5, 6] + >>> dot_product(a, b) + 32.0 + """ + return float(np.dot(a, b)) diff --git a/src/diffpy_srmise/version.py b/src/diffpy_srmise/version.py new file mode 100644 index 0000000..13ca6a1 --- /dev/null +++ b/src/diffpy_srmise/version.py @@ -0,0 +1,25 @@ +#!/usr/bin/env python +############################################################################## +# +# (c) 2025 The Trustees of Columbia University in the City of New York. +# All rights reserved. +# +# File coded by: Simon Billinge, Billinge Group members. +# +# See GitHub contributions for a more detailed list of contributors. +# https://github.com/diffpy/diffpy-srmise/graphs/contributors # noqa: E501 +# +# See LICENSE.rst for license information. +# +############################################################################## +"""Definition of __version__.""" + +# We do not use the other three variables, but can be added back if needed. +# __all__ = ["__date__", "__git_commit__", "__timestamp__", "__version__"] + +# obtain version information +from importlib.metadata import version + +__version__ = version("diffpy_srmise") + +# End of file diff --git a/tests/test_functions.py b/tests/test_functions.py new file mode 100644 index 0000000..4598d68 --- /dev/null +++ b/tests/test_functions.py @@ -0,0 +1,40 @@ +import numpy as np +import pytest + +from diffpy_srmise import functions # noqa + + +def test_dot_product_2D_list(): + a = [1, 2] + b = [3, 4] + expected = 11.0 + actual = functions.dot_product(a, b) + assert actual == expected + + +def test_dot_product_3D_list(): + a = [1, 2, 3] + b = [4, 5, 6] + expected = 32.0 + actual = functions.dot_product(a, b) + assert actual == expected + + +@pytest.mark.parametrize( + "a, b, expected", + [ + # Test whether the dot product function works with 2D and 3D vectors + # C1: lists, expect correct float output + ([1, 2], [3, 4], 11.0), + ([1, 2, 3], [4, 5, 6], 32.0), + # C2: tuples, expect correct float output + ((1, 2), (3, 4), 11.0), + ((1, 2, 3), (4, 5, 6), 32.0), + # C3: numpy arrays, expect correct float output + (np.array([1, 2]), np.array([3, 4]), 11.0), + (np.array([1, 2, 3]), np.array([4, 5, 6]), 32.0), + ], +) +def test_dot_product(a, b, expected): + actual = functions.dot_product(a, b) + assert actual == expected diff --git a/tests/test_version.py b/tests/test_version.py index 1bc10c2..3d214d5 100644 --- a/tests/test_version.py +++ b/tests/test_version.py @@ -1,10 +1,10 @@ -"""Unit tests for __version__.py -""" +"""Unit tests for __version__.py.""" -import diffpy.srmise +import diffpy_srmise # noqa def test_package_version(): - """Ensure the package version is defined and not set to the initial placeholder.""" - assert hasattr(diffpy.srmise, "__version__") - assert diffpy.srmise.__version__ != "0.0.0" + """Ensure the package version is defined and not set to the initial + placeholder.""" + assert hasattr(diffpy_srmise, "__version__") + assert diffpy_srmise.__version__ != "0.0.0"