Fix CI to use correct python versions (#463)

* Fix CI to use correct python versions

* Remove broken test - remove pydap from env dev - pin python >= 3.11

* Adapt ci to latest pins

* rewrite gen_mask_from_weights without scipy

* Fix spatialaverager test - add doc to gen mask - fix coverage conf

* update changes

* Fix the fix

Author: aulemahal

.github/workflows/ci.yaml

@@ -22,16 +22,12 @@ jobs:
       matrix:
         include:
           # Warning: Unless in quotations, numbers below are read as floats. 3.10 < 3.2
-          - python-version: "3.9"
-            esmf-version: 8.3
-          - python-version: "3.10"
-            esmf-version: 8.4
           - python-version: "3.11"
-            esmf-version: 8.6
+            esmf-version: 8.4
           - python-version: "3.12"
-            esmf-version: 8.7
+            esmf-version: 8.6
           - python-version: "3.13"
-            esmf-version: 8.8
+            esmf-version: 8.9
     steps:
       - name: Cancel previous runs
         uses: styfle/[email protected]
@@ -45,7 +41,7 @@ jobs:
           cache-downloads: true
           micromamba-version: "latest"
           environment-file: ci/environment.yml
-          extra-specs: |
+          create-args: >-
             python=${{ matrix.python-version }}
             esmpy=${{ matrix.esmf-version }}
       - name: Fix env for esmpy 8.4
@@ -66,7 +62,7 @@ jobs:
       - name: Upload coverage to Codecov
         uses: codecov/[email protected]
         with:
-          file: ./coverage.xml
+          files: ./coverage.xml
           fail_ci_if_error: false
 
   upstream-dev:
@@ -87,8 +83,6 @@ jobs:
           cache-downloads: true
           micromamba-version: "latest"
           environment-file: ci/environment-upstream-dev.yml
-          extra-specs: |
-            python=3.10
       - name: Install Xesmf (editable)
         run: |
           python -m pip install -e .

CHANGES.rst

@@ -1,6 +1,14 @@
 What's new
 ==========
 
+0.9.2 (2025-11-27)
+------------------
+This release drops support for Python < 3.11. xESMF aims to preserve support for older python and ESMF version as long as possible with its reduced maintaining team. The most recent windows release of ESMF is currently 8.4.2 and new versions of xESMF will support it as long as it is not updated. All fixes in :pull:`463`, by `Pascal Bourgault <https://github.com/aulemahal>`_.
+
+* Rewrote ``xe.smm.gen_mask_from_weights`` to remove scipy-dependent code.
+* Fix the CI reenable testing with previous python versions.
+* Avoid a ``SpatialAverager`` bug that happens when polygon segments have a length of exactly 1 on ESMF 8.4.2. The bug is not actually fixed in xESMF, but "segmentizing" the polygons with 0.99 seems to fix the issue.
+
 0.9.1 (2025-11-25)
 ------------------
 * Rewrote ``xe.smm.add_nans_to_weight`` (called when ``unmapped_to_nan`` is True)to remove scipy-dependent code, which also resulted in a significant (>=4x) speedup of that step (:pull:`461`). By `Pascal Bourgault <https://github.com/aulemahal>`_.

ci/environment-upstream-dev.yml

@@ -6,11 +6,11 @@ dependencies:
   - codecov
   - dask
   - esmpy
+  - netcdf4
   - numba
   - numpy
   - pip
   - pre-commit
-  - pydap
   - pytest
   - pytest-cov
   - shapely

ci/environment.yml

@@ -2,8 +2,9 @@ name: xesmf
 channels:
   - conda-forge
 dependencies:
-  - python>=3.8
+  - python>=3.11
   - cf_xarray>=0.5.1
+  - dask
   - esmpy
   - numba >=0.55.2
   - numpy >=1.16
@@ -13,9 +14,8 @@ dependencies:
   # Testing and extras
   - cftime
   - codecov
-  - dask
+  - netcdf4
   - pip
   - pre-commit
-  - pydap
   - pytest
   - pytest-cov

pyproject.toml

@@ -13,17 +13,14 @@ license = { text = "MIT" }
 authors = [
   { name = "Jiawei Zhuang", email = "[email protected]" },
 ]
-requires-python = ">=3.8"
+requires-python = ">=3.11"
 classifiers = [
   "Development Status :: 4 - Beta",
   "Intended Audience :: Science/Research",
   "License :: OSI Approved :: MIT License",
   "Operating System :: OS Independent",
   "Programming Language :: Python",
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.8",
-  "Programming Language :: Python :: 3.9",
-  "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",
   "Programming Language :: Python :: 3.13",

xesmf/smm.py

@@ -354,30 +354,34 @@ def mask_source_indices(weights, source_indices_to_mask):
 
 def gen_mask_from_weights(weights, nlat, nlon):
     """Generate a 2D mask from the regridding weights sparse matrix.
+
     This function will generate a 2D binary mask out of a regridding weights sparse matrix.
+    The mask shows which pixels of the output grid are mapped in the input grid.
+    This is only feasible when the regridder weights have been created with ``unmapped_to_nan=True``.
+
 
     Parameters
     ----------
     weights : DataArray backed by a sparse.COO array
-      Sparse weights matrix.
+      Sparse weights matrix, as computed by the `Regridder`.
+    nlat, nlon: int
+      Shape of the final matrix.
+      nlat * nlon must be equal to the size of the `out_dim` dimension of the weights.
 
     Returns
     -------
     numpy.ndarray of type numpy.int32 and of shape (nlat, nlon)
         Binary mask.
+
+    Examples
+    --------
+    This function acts on lower level inputs, but the regridder has all information needed to construct a DataArray.
+
+    >>> reg = xe.Regridder(ds_in, ds_out, 'bilinear', unmapped_to_nan=True)
+    >>> mask = xe.smm.gen_mask_from_weights(reg.weights, *reg.shape_out)
+    >>> mask_da = xr.DataArray(mask, dims=reg.out_horiz_dims, coords=reg.out_coords.coords)
     """
-    # Taken from @trondkr and adapted by @raphaeldussin to use `lil`.
-    # lil matrix is better than CSR when changing sparsity
-    m = weights.data.to_scipy_sparse().tolil()
-
-    # Create mask ndarray of ones and fill with 0-elements
-    mask = np.ones((nlat, nlon), dtype=np.int32).ravel()
-    for krow in range(len(m.rows)):
-        if any([np.isnan(x) for x in m.data[krow]]):
-            mask[krow] = 0
-
-    # Reshape and return
-    return mask.reshape((nlat, nlon))
+    return 1 * (~weights.isnull().any('in_dim').data.todense().reshape(nlat, nlon))
 
 
 def _combine_weight_multipoly(weights, areas, indexes):

xesmf/tests/test_frontend.py

@@ -100,7 +100,7 @@
 def _segmentize(p):
     if isinstance(p, list):
         return list(map(_segmentize, p))
-    return segmentize(p, 1)
+    return segmentize(p, 0.99)
 
 
 polys = list(map(_segmentize, polys_raw))

xesmf/tests/test_oceanmodels.py

@@ -78,28 +78,3 @@ def test_mom6like_to_5x5():
     with pytest.warns(UserWarning, match=r"Using dimensions \('yh', 'xh'\)"):
         tos_regridded = regrid_to_5x5(mom6like['tos'])
     assert tos_regridded.shape == ((2, 36, 72))
-
-
-@pytest.mark.testcases
-def test_mom6_to_1x1():
-    """check regridding of MOM6 to regular lon/lat"""
-
-    dataurl = 'http://35.188.34.63:8080/thredds/dodsC/OM4p5/'
-    mom6 = xr.open_dataset(
-        f'{dataurl}/ocean_monthly_z.200301-200712.nc4',
-        chunks={'time': 1, 'z_l': 1},
-        drop_variables=['average_DT', 'average_T1', 'average_T2'],
-        decode_times=False,
-        engine='pydap',
-    )
-
-    grid_1x1 = xr.Dataset()
-    grid_1x1['lon'] = xr.DataArray(data=0.5 + np.arange(360), dims=('x'))
-    grid_1x1['lat'] = xr.DataArray(data=0.5 - 90 + np.arange(180), dims=('y'))
-
-    regrid_to_1x1 = xesmf.Regridder(
-        mom6.rename({'geolon': 'lon', 'geolat': 'lat'}), grid_1x1, 'bilinear', periodic=True
-    )
-
-    thetao_1x1 = regrid_to_1x1(mom6['thetao'])
-    assert np.allclose(thetao_1x1.isel(time=0, z_l=0, x=200, y=100).values, 27.15691922)