Bump xarray to 2022.12.0 and reorganize environment.yml file (#33)

Bump xarray from 2022.11.0 to 2022.12.0 which contains a
[bugfix](pydata/xarray#7304) useful for reading
multiple groups from ICESat-2 HDF5 files in AWS S3 buckets.

Also taking the opportunity to sort packages alphabetically in the
`environment.yml` and reorganize some sections originally added in #2.
Hopefully this will make it clearer on where new conda packages can be
added in the future!

conda-linux-64.lock

@@ -1,6 +1,6 @@
 # Generated by conda-lock.
 # platform: linux-64
-# input_hash: 7efb415e782c55b744d6fbf5b8387bbeed511c5171e226d36dbb1d8deea41a96
+# input_hash: e3d7853d37e01bcbac52a6d84f259ca43e059739fbd9dc7275f466b912462e04
 @EXPLICIT
 https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
 https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2022.9.24-ha878542_0.tar.bz2#41e4e87062433e283696cf384f952ef6
@@ -66,12 +66,12 @@ https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.2.4-h166bdaf_0.ta
 https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.2.13-h166bdaf_4.tar.bz2#f3f9de449d32ca9b9c66a22863c96f41
 https://conda.anaconda.org/conda-forge/linux-64/libzopfli-1.0.3-h9c3ff4c_0.tar.bz2#c66fe2d123249af7651ebde8984c51c2
 https://conda.anaconda.org/conda-forge/linux-64/lz4-c-1.9.3-h9c3ff4c_1.tar.bz2#fbe97e8fa6f275d7c76a09e795adc3e6
-https://conda.anaconda.org/conda-forge/linux-64/mpg123-1.30.2-h27087fc_1.tar.bz2#2fe2a839394ef3a1825a5e5e296060bc
+https://conda.anaconda.org/conda-forge/linux-64/mpg123-1.31.1-h27087fc_0.tar.bz2#0af513b75f78a701a152568a31303bdf
 https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.3-h27087fc_1.tar.bz2#4acfc691e64342b9dae57cf2adc63238
 https://conda.anaconda.org/conda-forge/linux-64/nitro-2.7.dev6-h27087fc_5.tar.bz2#18a745069e7057a03c747e7ff87107a9
 https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda#da0ec11a6454ae19bff5b02ed881a2b1
 https://conda.anaconda.org/conda-forge/linux-64/ocl-icd-2.3.1-h7f98852_0.tar.bz2#a9b00e3aa7ecf158ed8e34ef91915f16
-https://conda.anaconda.org/conda-forge/linux-64/openssl-1.1.1s-h166bdaf_0.tar.bz2#e17553617ce05787d97715177be014d1
+https://conda.anaconda.org/conda-forge/linux-64/openssl-1.1.1s-h0b41bf4_1.conda#c5405eccf20334e57a80c1c3a9e68266
 https://conda.anaconda.org/conda-forge/linux-64/pcre-8.45-h9c3ff4c_0.tar.bz2#c05d1820a6d34ff07aaaab7a9b7eddaa
 https://conda.anaconda.org/conda-forge/linux-64/pixman-0.40.0-h36c2ea0_0.tar.bz2#660e72c82f2e75a6b3fe6a6e75c79f19
 https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-h36c2ea0_1001.tar.bz2#22dad4df6e8630e8dff2428f6f6a7036
@@ -132,7 +132,7 @@ https://conda.anaconda.org/conda-forge/linux-64/libgcrypt-1.10.1-h166bdaf_0.tar.
 https://conda.anaconda.org/conda-forge/linux-64/libglib-2.74.1-h606061b_1.tar.bz2#ed5349aa96776e00b34eccecf4a948fe
 https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.9.0-16_linux64_openblas.tar.bz2#955d993f41f9354bf753d29864ea20ad
 https://conda.anaconda.org/conda-forge/linux-64/libllvm15-15.0.6-h63197d8_0.conda#201168ef66095bbd565e124ee2c56a20
-https://conda.anaconda.org/conda-forge/linux-64/libsndfile-1.1.0-h27087fc_0.tar.bz2#02fa0b56a57c8421d1195bf0c021e682
+https://conda.anaconda.org/conda-forge/linux-64/libsndfile-1.1.0-hcb278e6_1.conda#d7a07b1f5974bce4735112aaef0c1467
 https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.4.0-h55922b4_4.tar.bz2#901791f0ec7cddc8714e76e273013a91
 https://conda.anaconda.org/conda-forge/linux-64/libxkbcommon-1.0.3-he3ba5ed_0.tar.bz2#f9dbabc7e01c459ed7a1d1d64b206e9b
 https://conda.anaconda.org/conda-forge/linux-64/libxslt-1.1.37-h873f0b0_0.tar.bz2#ed0d77d947ddeb974892de8df7224d12
@@ -437,7 +437,7 @@ https://conda.anaconda.org/conda-forge/noarch/pytest-cov-4.0.0-pyhd8ed1ab_0.tar.
 https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.12.1-pyhd8ed1ab_0.tar.bz2#f87b94dc53178574eedd09c317c2318f
 https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.13.5-py310hde88566_2.tar.bz2#521b762fdb5e47915251d460a8fc5814
 https://conda.anaconda.org/conda-forge/noarch/tifffile-2022.10.10-pyhd8ed1ab_0.tar.bz2#1c126ff5b4643785bbc16e44e6327e41
-https://conda.anaconda.org/conda-forge/noarch/xarray-2022.11.0-pyhd8ed1ab_0.tar.bz2#e31faa046a8c85791005c842c1f6138f
+https://conda.anaconda.org/conda-forge/noarch/xarray-2022.12.0-pyhd8ed1ab_0.conda#fd0b8bb7c8df27e09fdee6c893f2ba9d
 https://conda.anaconda.org/conda-forge/noarch/zarr-2.13.3-pyhd8ed1ab_0.tar.bz2#7e212240cf03e35a6b3201010a1a1e12
 https://conda.anaconda.org/conda-forge/noarch/certipy-0.1.3-py_0.tar.bz2#23486713ef5712923e7c57cae609b22e
 https://conda.anaconda.org/conda-forge/linux-64/gdal-3.5.2-py310hb7951cf_4.tar.bz2#0718fb374a35356197ab51f57e99b9ea

environment.yml

@@ -23,36 +23,6 @@ dependencies:
   # https://blog.jupyter.org/securely-pushing-to-github-from-a-jupyterhub-3ee42dfdc54f has
   # some more information
   - gh-scoped-creds==4.1
-  # needed for Linux desktop to work
-  - websockify>=0.10
-  # Cloud access tools and libraries
-  # Access S3 easily from python
-  - s3fs==2022.11.0
-  # handle login and similar details for accessing earthdata protected data
-  # https://github.com/nsidc/earthaccess
-  - earthdata==0.4.1
-  # Access datasets exposed via STAC
-  - pystac-client==0.5.1
-  # Access datasets exposed via intake catalogs
-  - intake==0.6.6
-  - intake-esm==2022.9.18
-  - intake-xarray==0.6.1
-  - intake-stac==0.4.0
-
-  # Core scientific python stack
-  - numpy==1.23.5
-  - scipy==1.9.3
-  - matplotlib==3.6.2
-  - pandas==1.5.2
-  - networkx==2.8.8
-  - scikit-image==0.19.3
-  - scikit-learn==1.1.3
-  - sympy==1.11.1
-  - statsmodels==0.13.5
-  - xarray==2022.11.0
-  - hypothesis==6.58.0 # needed by numpy testing tools
-  - cython==0.29.32 # optimization, C API access
-  - numba==0.56.4 # high-performance numerics
 
   # Jupyter tools
   - ipython==8.6.0
@@ -71,15 +41,30 @@ dependencies:
   - nbconvert==6.5.3
   - nbdime==3.1.1
 
+  # Core scientific python stack
+  - cython==0.29.32 # optimization, C API access
+  - hypothesis==6.58.0 # needed by numpy testing tools
+  - networkx==2.8.8
+  - numba==0.56.4 # high-performance numerics
+  - numpy==1.23.5
+  - pandas==1.5.2
+  - scikit-image==0.19.3
+  - scikit-learn==1.1.3
+  - scipy==1.9.3
+  - statsmodels==0.13.5
+  - sympy==1.11.1
+  - xarray==2022.12.0
+
   # Visualization packages
-  - cartopy==0.21.0 # geospatial plotting with matplotlib
-  - seaborn==0.12.1 # statistical plotting with matplotlib
-  - ipympl==0.9.2 # This enables matplotlib interaction with jupyter widgets
-  - ipyleaflet==0.17.2
   - bokeh==2.4.3
+  - cartopy==0.21.0 # geospatial plotting with matplotlib
   - geoviews==1.9.5
   - hvplot==0.8.2
+  - ipyleaflet==0.17.2
+  - ipympl==0.9.2 # This enables matplotlib interaction with jupyter widgets
+  - matplotlib==3.6.2
   - plotly==5.11.0
+  - seaborn==0.12.1 # statistical plotting with matplotlib
 
   # Geospatial data packages
   - geopandas==0.12.1
@@ -93,18 +78,31 @@ dependencies:
   - h5netcdf==1.1.0
   - pooch==1.6.0
 
-  # Distributed computing and cloud tools
+  # Cloud access tools and libraries
   - boto3
+  - s3fs==2022.11.0
+  # handle login and similar details for accessing earthdata protected data
+  # https://github.com/nsidc/earthaccess
+  - earthdata==0.4.1
+  # Access datasets exposed via STAC
+  - pystac-client==0.5.1
+  # Access datasets exposed via intake catalogs
+  - intake==0.6.6
+  - intake-esm==2022.9.18
+  - intake-stac==0.4.0
+  - intake-xarray==0.6.1
+
+  # Distributed computing
   - dask==2022.11.0
   - dask-labextension==6.0.0
 
   # Other useful generic python packages
   - pillow==9.2.0 # Python imaging library, useful for many image-related tasks
-  - tqdm==4.64.1 # progress bars, with notebook support
   - pytest==7.2.0
   - pytest-cov==4.0.0
   - pep8==1.7.1
   - flake8==5.0.4
+  - tqdm==4.64.1 # progress bars, with notebook support
 
   # Packages specific to cryo work
   - icepyx==0.6.4
@@ -113,6 +111,8 @@ dependencies:
   - qgis==3.22.11
   # Maybe needed for qgis? https://github.com/conda-forge/qgis-feedstock/issues/263
   - pyopencl
+  # needed for Linux desktop to work
+  - websockify>=0.10
 
   # Not all packages will be available from conda-forge, we install from pip when we need to.
   - pip==22.3.1