Add a subsampling interpolation method

weatherbenchX/interpolations.py

@@ -433,3 +433,39 @@ def interpolate_data_array(
         ),
     )
     return out
+
+
+class Subsample(Interpolation):
+  """Subsample a DataArray along specified dimensions.
+
+  This is useful for reducing the resolution of a dataset without interpolation,
+  e.g. for faster evaluation at lower resolution.
+  """
+
+  def __init__(
+      self,
+      dims: Sequence[str],
+      stride: int,
+  ):
+    """Init.
+
+    Args:
+      dims: Dimensions along which to subsample.
+      stride: Stride for subsampling. Must be a positive integer.
+    """
+    if stride < 1:
+      raise ValueError(f'stride must be >= 1, got {stride}')
+    self._dims = dims
+    self._stride = stride
+
+  def interpolate_data_array(
+      self,
+      da: xr.DataArray,
+      reference: Optional[xr.DataArray] = None,
+  ) -> xr.DataArray:
+    isel_kwargs = {
+        dim: slice(None, None, self._stride)
+        for dim in self._dims
+        if dim in da.dims
+    }
+    return da.isel(**isel_kwargs)

weatherbenchX/interpolations_test.py

@@ -220,6 +220,90 @@ def test_crop_to_box_invalid_lat(self):
       interpolations.CropToBox(lat_min=10, lat_max=-10, lon_min=0, lon_max=10)
 
 
+class SubsampleTest(absltest.TestCase):
+
+  def test_subsample_basic(self):
+    lats = np.arange(0, 100, 1.0)
+    lons = np.arange(0, 200, 1.0)
+    da = xr.DataArray(
+        name='t2m',
+        data=np.random.rand(len(lats), len(lons)),
+        coords={'latitude': lats, 'longitude': lons},
+        dims=['latitude', 'longitude'],
+    )
+    subsampler = interpolations.Subsample(
+        dims=['latitude', 'longitude'], stride=10
+    )
+    result = subsampler.interpolate_data_array(da)
+    self.assertEqual(result.sizes['latitude'], 10)
+    self.assertEqual(result.sizes['longitude'], 20)
+    np.testing.assert_equal(result.latitude.values, lats[::10])
+    np.testing.assert_equal(result.longitude.values, lons[::10])
+
+  def test_subsample_stride_1_is_noop(self):
+    lats = np.arange(0, 10, 1.0)
+    lons = np.arange(0, 20, 1.0)
+    da = xr.DataArray(
+        name='t2m',
+        data=np.random.rand(len(lats), len(lons)),
+        coords={'latitude': lats, 'longitude': lons},
+        dims=['latitude', 'longitude'],
+    )
+    subsampler = interpolations.Subsample(
+        dims=['latitude', 'longitude'], stride=1
+    )
+    result = subsampler.interpolate_data_array(da)
+    xr.testing.assert_equal(result, da)
+
+  def test_subsample_missing_dim_is_skipped(self):
+    lats = np.arange(0, 10, 1.0)
+    da = xr.DataArray(
+        name='t2m',
+        data=np.random.rand(len(lats)),
+        coords={'latitude': lats},
+        dims=['latitude'],
+    )
+    subsampler = interpolations.Subsample(
+        dims=['latitude', 'longitude'], stride=2
+    )
+    result = subsampler.interpolate_data_array(da)
+    self.assertEqual(result.sizes['latitude'], 5)
+    self.assertNotIn('longitude', result.dims)
+
+  def test_subsample_single_dim(self):
+    lats = np.arange(0, 12, 1.0)
+    lons = np.arange(0, 20, 1.0)
+    da = xr.DataArray(
+        name='t2m',
+        data=np.random.rand(len(lats), len(lons)),
+        coords={'latitude': lats, 'longitude': lons},
+        dims=['latitude', 'longitude'],
+    )
+    subsampler = interpolations.Subsample(dims=['latitude'], stride=3)
+    result = subsampler.interpolate_data_array(da)
+    self.assertEqual(result.sizes['latitude'], 4)
+    self.assertEqual(result.sizes['longitude'], 20)
+
+  def test_subsample_invalid_stride(self):
+    with self.assertRaisesRegex(ValueError, 'stride must be >= 1'):
+      interpolations.Subsample(dims=['latitude'], stride=0)
+
+  def test_subsample_via_interpolate(self):
+    lats = np.arange(0, 10, 1.0)
+    lons = np.arange(0, 20, 1.0)
+    ds = {
+        't2m': xr.DataArray(
+            data=np.random.rand(len(lats), len(lons)),
+            coords={'latitude': lats, 'longitude': lons},
+            dims=['latitude', 'longitude'],
+        ),
+    }
+    subsampler = interpolations.Subsample(
+        dims=['latitude', 'longitude'], stride=2
+    )
+    result = subsampler.interpolate(ds)
+    self.assertEqual(result['t2m'].sizes['latitude'], 5)
+    self.assertEqual(result['t2m'].sizes['longitude'], 10)
 
 
 if __name__ == '__main__':