add dataset to docs, update test (#201)

* add dataset to docs, update test

* increment version

* increase test flexibility

Author: amy-defnet

docs/dataset_text.yaml

@@ -245,3 +245,14 @@ datasets:
       February 2017. Several days are missing from select years due to `MODIS outages <https://modaps.modaps.eosdis.nasa.gov/services/production/outages_terra.html>`_.
 
       The data included in this dataset have been geospatially transformed from the 0.05 by 0.05 degree grid to the 1km by 1km CONUS2 grid.
+
+  "ma_2023":
+    summary: >
+      Water table depth estimates provided by a random forest model trained on historical USGS observations 
+      and `Fan et al. 2013 water table depth dataset <https://hf-hydrodata.readthedocs.io/en/latest/gen_fan_2013.html>`_. 
+      This dataset includes long-term mean water table estimates and uncertainty at 1km resolution for the CONUS1 domain. 
+
+    processing_notes: >
+      Long-term mean water table depth estimates were obtained using the median of tree outputs from the trained random 
+      forest model. The uncertainty was assessed based on the coefficient of variation of the tree outputs from the random 
+      forest model, which was calculated as the standard deviation of the tree outputs divided by their mean.

docs/source/available_data.rst

@@ -11,6 +11,7 @@ We have the following categories of datasets:
    4. **Static model inputs and domain files**: Gridded datasets that contain static model inputs that are used directly in model definition (e.g. soil properties, land cover, and hydraulic conductivity) as well as additional domain files that are used in pre and post processing (e.g. distance to streams and watershed boundaries).
    5. **Current conditions**: Current hydrologic conditions generated by the `HydroGEN project <https://hydro-generation.org>`_
    6. **Remote sensing**: Gridded observation products that are generated from remote sensing. 
+   7. **ML simulation outputs**: Gridded outputs from machine learning (ML) simulations of the contiguous US.
 
 Within each category you will find multiple datasets. Each dataset contains a collection of variables (refer to the 
 variable table on each dataset page for more details).

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "hf_hydrodata"
-version = "1.3.12"
+version = "1.3.13"
 description = "hydroframe tools and utilities"
 authors = ["William M. Hasling", "Laura Condon", "Reed Maxwell",  "George Artavanis", "Amy M. Johnson", "Amy C. Defnet"]
 license = "MIT"

tests/hf_hydrodata/test_gridded.py

@@ -1188,7 +1188,7 @@ def test_get_variables():
     """Test get_variables."""
 
     variables = hf.get_variables()
-    assert len(variables) == 79
+    assert len(variables) >= 80
     assert variables[0] == "air_temp"
     variables = hf.get_variables(dataset="CW3E")
     assert len(variables) == 8