Handle unsigned integer dtype in datashader aggregate operation

holoviews/operation/datashader.py

@@ -420,15 +420,19 @@ def get_agg_data(cls, obj, category=None):
 
         is_custom = isinstance(df, dd.DataFrame) or cuDFInterface.applies(df)
         if any((not is_custom and len(df[d.name]) and isinstance(df[d.name].values[0], cftime_types)) or
-               df[d.name].dtype.kind == 'M' for d in (x, y)):
+               df[d.name].dtype.kind in ["M", "u"] for d in (x, y)):
             df = df.copy()
 
         for d in (x, y):
             vals = df[d.name]
             if not is_custom and len(vals) and isinstance(vals.values[0], cftime_types):
                 vals = cftime_to_timestamp(vals, 'ns')
-            elif df[d.name].dtype.kind == 'M':
+            elif vals.dtype.kind == 'M':
                 vals = vals.astype('datetime64[ns]')
+            elif vals.dtype == np.uint64:
+                raise TypeError(f"Dtype of uint64 for column {d.name} is not supported.")
+            elif vals.dtype.kind == 'u':
+                pass  # To convert to int64
             else:
                 continue
             df[d.name] = vals.astype('int64')

holoviews/tests/operation/test_datashader.py

@@ -3,6 +3,7 @@
 from unittest import SkipTest, skipIf
 
 import numpy as np
+import pytest
 
 from holoviews import (
     Dimension, Curve, Points, Image, Dataset, RGB, Path, Graph, TriMesh,
@@ -848,8 +849,6 @@ def test_regrid_upsampling(self):
         self.assertEqual(regridded, expected)
 
     def test_regrid_upsampling_linear(self):
-        ### This test causes a numba error using 0.35.0 - temporarily disabled ###
-        return
         img = Image(([0.5, 1.5], [0.5, 1.5], [[0, 1], [2, 3]]))
         regridded = regrid(img, width=4, height=4, upsample=True, interpolation='linear', dynamic=False)
         expected = Image(([0.25, 0.75, 1.25, 1.75], [0.25, 0.75, 1.25, 1.75],
@@ -1322,3 +1321,18 @@ def test_polys_inspection_1px_mask_miss(self):
         polys = inspect_polygons(self.polysrgb,
                                  max_indicators=3, dynamic=False, pixels=1, x=0, y=0)
         self.assertEqual(polys, Polygons([], vdims='z'))
+
+
+@pytest.mark.parametrize("dtype", [np.uint8, np.uint16, np.uint32])
+def test_uint_dtype(dtype):
+    df = pd.DataFrame(np.arange(2, dtype=dtype), columns=["A"])
+    curve = Curve(df)
+    img = rasterize(curve, dynamic=False, height=10, width=10)
+    assert (np.asarray(img.data["Count"]) == np.eye(10)).all()
+
+
+def test_uint64_dtype():
+    df = pd.DataFrame(np.arange(2, dtype=np.uint64), columns=["A"])
+    curve = Curve(df)
+    with pytest.raises(TypeError, match="Dtype of uint64 for column A is not supported."):
+        rasterize(curve, dynamic=False, height=10, width=10)