Merge branch 'main' into add-pyglpk

.github/workflows/build_docs.yml

@@ -20,11 +20,12 @@ jobs:
 
       # Create environment using micromamba
       - name: Install Conda environment with Micromamba
-        uses: mamba-org/[email protected].0
+        uses: mamba-org/[email protected].1
         with:
           environment-file: doc/environment.yml
+          micromamba-version: '2.0.0-0'
           environment-name: pyart-docs
-          cache-downloads: true
+          cache-downloads: false
 
       - name: Fetch all history for all tags and branches
         run: |

.github/workflows/ci.yml

@@ -27,15 +27,15 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12"]
         os: [macos, ubuntu, windows]
 
     steps:
       - uses: actions/checkout@v4
 
       # Install dependencies
       - name: Setup Conda Environment
-        uses: mamba-org/[email protected].0
+        uses: mamba-org/[email protected].1
         with:
           environment-file: continuous_integration/environment-ci.yml
           micromamba-version: '2.0.0-0'
@@ -66,7 +66,7 @@ jobs:
           python -m pytest -v --cov=./ --cov-report=xml
 
       - name: Upload code coverage to Codecov
-        uses: codecov/codecov-action@v4.6.0
+        uses: codecov/codecov-action@v5.0.2
         with:
           file: ./coverage.xml
           flags: unittests

.github/workflows/wheels.yml

@@ -26,8 +26,8 @@ jobs:
     strategy:
       matrix:
         os: [
-          ubuntu-20.04,
-          windows-2019,
+          ubuntu-latest,
+          windows-latest,
           macos-14,
           macos-13,
         ]
@@ -49,7 +49,7 @@ jobs:
         with:
           output-dir: dist
         env:
-          CIBW_BUILD: "cp39-* cp310-* cp311-* cp312*"
+          CIBW_BUILD: "cp310-* cp311-* cp312*"
           CIBW_SKIP: "*-musllinux_*"  #  numpy doesn't have wheels for musllinux so we can't build some quickly and without bloating
           CIBW_ARCHS_LINUX: "x86_64"
           MACOSX_DEPLOYMENT_TARGET: "10.9" # as of CIBW 2.9, this is the default value, pin it so it can't be bumped silently
@@ -99,7 +99,7 @@ jobs:
           merge-multiple: true
 
       - name: Publish to PyPI
-        uses: pypa/gh-action-pypi-publish@v1.10.3
+        uses: pypa/gh-action-pypi-publish@v1.12.2
         with:
           user: __token__
           password: ${{ secrets.PYPI_TOKEN }}

continuous_integration/environment-ci.yml

@@ -12,7 +12,7 @@ dependencies:
   - wradlib
   - cartopy
   - cvxopt
-  - xarray
+  - xarray>=2024.10.0
   - metpy
   - pytest-cov
   - pytest-mpl
@@ -24,11 +24,10 @@ dependencies:
   - cftime
   - setuptools
   - shapely
-  - ruff==0.4.2
+  - ruff
   - mda-xdrlib
-  - xradar
+  - xradar>=0.8.0
   - pooch
   - versioneer
   - black
   - open-radar-data
-  - glpk

doc/environment.yml

@@ -1,7 +1,6 @@
 name: pyart-docs
 channels:
   - conda-forge
-  - defaults
 dependencies:
   - gdal
   - numpy
@@ -14,8 +13,8 @@ dependencies:
   - metpy
   - cartopy
   - cvxopt
-  - xarray
-  - sphinx<7.2
+  - xarray>=2024.10.0
+  - sphinx==7.1.2
   - ipython
   - pandoc
   - pkg-config
@@ -35,10 +34,11 @@ dependencies:
   - pre_commit
   - cmweather
   - mda-xdrlib
-  - xradar
+  - xradar>=0.8.0
+  - dask
+  - ablog
   - pip
   - pip:
       - pooch
       - versioneer
-      - ablog
       - -e ..

examples/plotting/radar-cross-section.ipynb

@@ -7,6 +7,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "import cartopy.crs as ccrs\n",
     "import matplotlib.pyplot as plt\n",
     "\n",
     "import pyart\n",

pyart/graph/radarmapdisplay_basemap.py

@@ -288,7 +288,7 @@ def plot_ppi_map(
             data = np.ma.masked_outside(data, vmin, vmax)
 
         # create the basemap if not provided
-        if type(basemap) != Basemap:
+        if not isinstance(basemap, Basemap):
             using_corners = None not in [min_lon, min_lat, max_lon, max_lat]
             if using_corners:
                 basemap = Basemap(

pyart/map/gates_to_grid.py

@@ -114,9 +114,9 @@ def map_gates_to_grid(
         skip_transform = True
 
     if grid_origin_alt is None:
-        try:
-            grid_origin_alt = float(radars[0].altitude["data"])
-        except TypeError:
+        if len(radars[0].altitude["data"]) == 1:
+            grid_origin_alt = float(radars[0].altitude["data"].item())
+        else:
             grid_origin_alt = np.mean(radars[0].altitude["data"])
 
     # convert input h_factor and dist_factor from scalar, tuple, or list to array
@@ -242,10 +242,10 @@ def _find_projparams(grid_origin, radars, grid_projection):
 
     # parse grid_origin
     if grid_origin is None:
-        try:
-            lat = float(radars[0].latitude["data"])
-            lon = float(radars[0].longitude["data"])
-        except TypeError:
+        if len(radars[0].latitude["data"]) == 1 & len(radars[0].longitude["data"]) == 1:
+            lat = float(radars[0].latitude["data"].item())
+            lon = float(radars[0].longitude["data"].item())
+        else:
             lat = np.mean(radars[0].latitude["data"])
             lon = np.mean(radars[0].longitude["data"])
         grid_origin = (lat, lon)
@@ -293,10 +293,15 @@ def _find_offsets(radars, projparams, grid_origin_alt):
         x_disp, y_disp = geographic_to_cartesian(
             radar.longitude["data"], radar.latitude["data"], projparams
         )
-        try:
-            z_disp = float(radar.altitude["data"]) - grid_origin_alt
-            offsets.append((z_disp, float(y_disp), float(x_disp)))
-        except TypeError:
+        if (
+            len(radar.latitude["data"])
+            == 1 & len(radar.longitude["data"])
+            == 1 & len(radar.altitude["data"])
+            == 1
+        ):
+            z_disp = float(radar.altitude["data"].item()) - grid_origin_alt
+            offsets.append((z_disp, float(y_disp.item()), float(x_disp.item())))
+        else:
             z_disp = np.mean(radar.altitude["data"]) - grid_origin_alt
             offsets.append((z_disp, np.mean(y_disp), np.mean(x_disp)))
     return offsets

pyart/map/grid_mapper.py

@@ -481,19 +481,19 @@ def map_to_grid(
 
     # find the grid origin if not given
     if grid_origin is None:
-        try:
-            lat = float(radars[0].latitude["data"])
-            lon = float(radars[0].longitude["data"])
-        except TypeError:
+        if len(radars[0].latitude["data"]) == 1 & len(radars[0].longitude["data"]) == 1:
+            lat = float(radars[0].latitude["data"].item())
+            lon = float(radars[0].longitude["data"].item())
+        else:
             lat = np.mean(radars[0].latitude["data"])
             lon = np.mean(radars[0].longitude["data"])
         grid_origin = (lat, lon)
     grid_origin_lat, grid_origin_lon = grid_origin
 
     if grid_origin_alt is None:
-        try:
-            grid_origin_alt = float(radars[0].altitude["data"])
-        except TypeError:
+        if len(radars[0].altitude["data"]) == 1:
+            grid_origin_alt = float(radars[0].altitude["data"].item())
+        else:
             grid_origin_alt = np.mean(radars[0].altitude["data"])
 
     # fields which should be mapped, None for fields which are in all radars
@@ -544,10 +544,15 @@ def map_to_grid(
         x_disp, y_disp = geographic_to_cartesian(
             radar.longitude["data"], radar.latitude["data"], projparams
         )
-        try:
-            z_disp = float(radar.altitude["data"]) - grid_origin_alt
-            offsets.append((z_disp, float(y_disp), float(x_disp)))
-        except TypeError:
+        if (
+            len(radar.latitude["data"])
+            == 1 & len(radar.longitude["data"])
+            == 1 & len(radar.altitude["data"])
+            == 1
+        ):
+            z_disp = float(radar.altitude["data"].item()) - grid_origin_alt
+            offsets.append((z_disp, float(y_disp.item()), float(x_disp.item())))
+        else:
             z_disp = np.mean(radar.altitude["data"]) - grid_origin_alt
             offsets.append((z_disp, np.mean(y_disp), np.mean(x_disp)))
 

pyart/retrieve/kdp_proc.py

@@ -301,7 +301,7 @@ def _kdp_estimation_backward_fixed(
         p = np.dot((identity_i - np.dot(k, h_plus)), p_pred)
 
         # Fill the output
-        kdp[ii] = s[0]
+        kdp[ii] = s[0].item()
         kdp_error[ii] = p[0, 0]
 
     # Shift
@@ -407,9 +407,9 @@ def _kdp_estimation_forward_fixed(
         p = np.dot((identity_i - np.dot(k, h_plus)), p_pred)
 
         # Fill the output
-        kdp[ii] = s[0]
+        kdp[ii] = s[0].item()
         kdp_error[ii] = p[0, 0]
-        phidp[ii] = s[2]
+        phidp[ii] = s[2].item()
 
     # Shift
     dummy = np.copy(kdp)

pyart/util/radar_utils.py

@@ -573,12 +573,12 @@ def join_radar(radar1, radar2):
         == 1 & len(radar2.altitude["data"])
         == 1
     ):
-        lat1 = float(radar1.latitude["data"])
-        lon1 = float(radar1.longitude["data"])
-        alt1 = float(radar1.altitude["data"])
-        lat2 = float(radar2.latitude["data"])
-        lon2 = float(radar2.longitude["data"])
-        alt2 = float(radar2.altitude["data"])
+        lat1 = float(radar1.latitude["data"].item())
+        lon1 = float(radar1.longitude["data"].item())
+        alt1 = float(radar1.altitude["data"].item())
+        lat2 = float(radar2.latitude["data"].item())
+        lon2 = float(radar2.longitude["data"].item())
+        alt2 = float(radar2.altitude["data"].item())
 
         if (lat1 != lat2) or (lon1 != lon2) or (alt1 != alt2):
             ones1 = np.ones(len(radar1.time["data"]), dtype="float32")

pyart/xradar/accessor.py

@@ -5,11 +5,23 @@
 
 import copy
 
-import datatree
 import numpy as np
 import pandas as pd
-from datatree import DataTree, formatting, formatting_html
-from datatree.treenode import NodePath
+
+try:
+    from xarray.core import formatting, formatting_html
+    from xarray.core.datatree import DataTree
+    from xarray.core.extensions import register_datatree_accessor
+    from xarray.core.treenode import NodePath
+except ImportError:
+    from datatree import (
+        DataTree,
+        formatting,
+        formatting_html,
+    )
+    from datatree.extensions import register_datatree_accessor
+    from datatree.treenode import NodePath
+
 from xarray import DataArray, Dataset, concat
 from xarray.core import utils
 from xradar.accessors import XradarAccessor
@@ -807,7 +819,7 @@ def _point_altitude_data():
     return _point_altitude_data
 
 
-@datatree.register_datatree_accessor("pyart")
+@register_datatree_accessor("pyart")
 class XradarDataTreeAccessor(XradarAccessor):
     """Adds a number of pyart specific methods to datatree.DataTree objects."""
 

requirements.txt

@@ -1,15 +1,15 @@
 numpy
 scipy
-netCDF4>=1.7.0
+netCDF4
 matplotlib
 pooch
 cftime
 fsspec
 s3fs
 open_radar_data
-xradar>=0.5.0
+xradar>=0.8.0
 pandas
 mda-xdrlib
-xarray!=0.21.0
+xarray>=2024.10.0
 cartopy
 pint

tests/core/test_grid.py

@@ -92,7 +92,7 @@ def test_grid_to_xarray():
     time = np.array([netCDF4.num2date(grid.time["data"][0], grid.time["units"])])
 
     # Check dimensions
-    assert ds.dims == {"time": 1, "z": 2, "y": 400, "x": 320, "nradar": 1}
+    assert ds.sizes == {"time": 1, "z": 2, "y": 400, "x": 320, "nradar": 1}
 
     # Check coordinate data
     assert np.array_equal(ds.x.data, grid.x["data"])

tests/io/test_cfradial.py

@@ -486,7 +486,7 @@ def attribute_equal(class1, class2, key, allow_str_case_diff=True):
     a1 = getattr(class1, key)
     a2 = getattr(class2, key)
 
-    assert type(a1) == type(a2)
+    assert type(a1) == type(a2)  # noqa
 
     if isinstance(a1, str) and allow_str_case_diff:
         assert a1.upper() == a2.upper()