Change .data to .values call in get_statistics_from_mask to prevent p…

…assing dask array to get_statistics, and added test for dask array input

tobac/tests/test_utils_bulk_statistics.py

@@ -1,8 +1,11 @@
 from datetime import datetime
+
 import numpy as np
+import dask.array as da
 import pandas as pd
-import pytest
 import xarray as xr
+import pytest
+
 import tobac
 import tobac.utils as tb_utils
 import tobac.testing as tb_test
@@ -702,3 +705,85 @@ def test_get_statistics_from_mask_collapse_dim():
             statistic=statistics_sum,
             collapse_dim="not_a_dim",
         )
+
+
+def test_bulk_statistics_dask():
+    """
+    Test dask input for labels and fields is handled correctly
+    """
+
+    test_labels = da.array(
+        [
+            [
+                [0, 0, 0, 0, 0],
+                [0, 1, 0, 2, 0],
+                [0, 1, 0, 2, 0],
+                [0, 1, 0, 0, 0],
+                [0, 0, 0, 0, 0],
+            ],
+            [
+                [0, 0, 0, 0, 0],
+                [0, 3, 0, 0, 0],
+                [0, 3, 0, 4, 0],
+                [0, 3, 0, 4, 0],
+                [0, 0, 0, 0, 0],
+            ],
+        ],
+        dtype=int,
+    )
+
+    test_labels = xr.DataArray(
+        test_labels,
+        dims=("time", "y", "x"),
+        coords={
+            "time": [datetime(2000, 1, 1), datetime(2000, 1, 1, 0, 5)],
+            "y": np.arange(5),
+            "x": np.arange(5),
+        },
+    )
+
+    test_values = da.array(
+        [
+            [
+                [0, 0, 0, 0, 0],
+                [0, 1, 0, 2, 0],
+                [0, 2, 0, 2, 0],
+                [0, 3, 0, 0, 0],
+                [0, 0, 0, 0, 0],
+            ],
+            [
+                [0, 0, 0, 0, 0],
+                [0, 2, 0, 0, 0],
+                [0, 3, 0, 3, 0],
+                [0, 4, 0, 2, 0],
+                [0, 0, 0, 0, 0],
+            ],
+        ]
+    )
+
+    test_values = xr.DataArray(
+        test_values, dims=test_labels.dims, coords=test_labels.coords
+    )
+
+    test_features = pd.DataFrame(
+        {
+            "feature": [1, 2, 3, 4],
+            "frame": [0, 0, 1, 1],
+            "time": [
+                datetime(2000, 1, 1),
+                datetime(2000, 1, 1),
+                datetime(2000, 1, 1, 0, 5),
+                datetime(2000, 1, 1, 0, 5),
+            ],
+        }
+    )
+
+    statistics_size = {"size": np.size}
+
+    expected_size_result = np.array([3, 2, 3, 2])
+
+    bulk_statistics_output = tb_utils.get_statistics_from_mask(
+        test_features, test_labels, test_values, statistic=statistics_size
+    )
+
+    assert np.all(bulk_statistics_output["size"] == expected_size_result)

tobac/utils/bulk_statistics.py

@@ -301,7 +301,7 @@ def get_statistics_from_mask(
 
     for tt in pd.to_datetime(segmentation_mask.time):
         # select specific timestep
-        segmentation_mask_t = segmentation_mask.sel(time=tt, method="nearest").data
+        segmentation_mask_t = segmentation_mask.sel(time=tt, method="nearest").values
         fields_t = (
             (
                 field.sel(