Minor changes (#29)

.github/workflows/main.yaml

@@ -18,7 +18,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ['3.9', '3.10']
+        python-version: ['3.8', '3.9', '3.10']
     timeout-minutes: 20
     defaults:
       run:

ci/environment.yml

@@ -3,10 +3,12 @@ channels:
   - conda-forge
   - nodefaults
 dependencies:
-  - esmpy>=8.2.0
   - dask
+  - esmpy>=8.2.0
+  - mpich
   - netcdf4
   - numpy
+  - pip
   - pooch
   - pytest
   - pytest-cov
@@ -15,9 +17,6 @@ dependencies:
   - rioxarray
   - scipy
   - xarray
+  - xarray-datatree>=0.0.4
   - xesmf
   - zarr
-  - pip
-  - mpich
-  - pip:
-      - xarray-datatree==0.0.3

ndpyramid/regrid.py

@@ -1,5 +1,6 @@
 from __future__ import annotations  # noqa: F401
 
+import itertools
 import pathlib
 
 import datatree as dt
@@ -52,22 +53,19 @@ def make_grid_ds(level: int, pixels_per_tile: int = 128) -> xr.Dataset:
 
     # calc grid cell center coordinates
     ii, jj = np.meshgrid(np.arange(dim) + 0.5, np.arange(dim) + 0.5)
-    for i in range(grid_shape[0]):
-        for j in range(grid_shape[1]):
-            locs = [ii[i, j], jj[i, j]]
-            xs[i, j], ys[i, j] = transform * locs
-            lon[i, j], lat[i, j] = p(xs[i, j], ys[i, j], inverse=True)
+    for i, j in itertools.product(range(grid_shape[0]), range(grid_shape[1])):
+        locs = [ii[i, j], jj[i, j]]
+        xs[i, j], ys[i, j] = transform * locs
+        lon[i, j], lat[i, j] = p(xs[i, j], ys[i, j], inverse=True)
 
     # calc grid cell bounds
     iib, jjb = np.meshgrid(np.arange(dim + 1), np.arange(dim + 1))
-    for i in range(bounds_shape[0]):
-        for j in range(bounds_shape[1]):
-            locs = [iib[i, j], jjb[i, j]]
-            x, y = transform * locs
-            lon_b[i, j], lat_b[i, j] = p(x, y, inverse=True)
-
-    # pack data into xarray.Dataset
-    ds = xr.Dataset(
+    for i, j in itertools.product(range(bounds_shape[0]), range(bounds_shape[1])):
+        locs = [iib[i, j], jjb[i, j]]
+        x, y = transform * locs
+        lon_b[i, j], lat_b[i, j] = p(x, y, inverse=True)
+
+    return xr.Dataset(
         {
             'x': xr.DataArray(xs[0, :], dims=['x']),
             'y': xr.DataArray(ys[:, 0], dims=['y']),
@@ -79,8 +77,6 @@ def make_grid_ds(level: int, pixels_per_tile: int = 128) -> xr.Dataset:
         attrs=dict(title='Web Mercator Grid', Convensions='CF-1.8'),
     )
 
-    return ds
-
 
 def make_grid_pyramid(levels: int = 6) -> dt.DataTree:
     """helper function to create a grid pyramid for use with xesmf

ndpyramid/utils.py

@@ -1,22 +1,31 @@
 from __future__ import annotations  # noqa: F401
 
-import importlib
+from ._version import __version__
 
 
-def get_version():
-    try:
-        return importlib.import_module('ndpyramid').__version__
-    except ModuleNotFoundError:
-        return '-9999'
+def get_version() -> str:
+    return __version__
 
 
-def multiscales_template(datasets=[], type='', method='', version='', args=[], kwargs={}):
+def multiscales_template(
+    datasets: list = None,
+    type: str = '',
+    method: str = '',
+    version: str = '',
+    args: list = None,
+    kwargs: dict = None,
+):
+    if datasets is None:
+        datasets = []
+    if args is None:
+        args = []
+    if kwargs is None:
+        kwargs = {}
     # https://forum.image.sc/t/multiscale-arrays-v0-1/37930
-    d = [
+    return [
         {
             'datasets': datasets,
             'type': type,
             'metadata': {'method': method, 'version': version, 'args': args, 'kwargs': kwargs},
         }
     ]
-    return d

requirements.txt

@@ -1,4 +1,4 @@
 numpy
 xarray
-xarray-datatree >= 0.0.3
+xarray-datatree >= 0.0.4
 zarr

setup.py

@@ -11,7 +11,7 @@
     INSTALL_REQUIRES = f.read().strip().split('\n')
 
 LONG_DESCRIPTION = pathlib.Path('README.md').read_text()
-PYTHON_REQUIRES = '>=3.9'
+PYTHON_REQUIRES = '>=3.8'
 
 description = 'A small utility for generating ND array pyramids using Xarray and Zarr.'