Handle unsigned integer dtype in datashader aggregate operation (#5149)

holoviews/operation/datashader.py

@@ -415,15 +415,19 @@ 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] = cast_array_to_int64(vals)

holoviews/tests/operation/testdatashader.py

@@ -707,6 +707,26 @@ def test_multi_poly_rasterize(self):
         expected = Image((xs, ys, arr), vdims=Dimension('Count', nodata=0))
         self.assertEqual(agg, expected)
 
+    def test_uint_dtype(self):
+        df = pd.DataFrame(np.arange(2, dtype=np.uint8), columns=["A"])
+        curve = Curve(df)
+        img = rasterize(curve, dynamic=False, height=10, width=10)
+        assert (np.asarray(img.data["Count"]) == np.eye(10)).all()
+        df = pd.DataFrame(np.arange(2, dtype=np.uint16), columns=["A"])
+        curve = Curve(df)
+        img = rasterize(curve, dynamic=False, height=10, width=10)
+        assert (np.asarray(img.data["Count"]) == np.eye(10)).all()
+        df = pd.DataFrame(np.arange(2, dtype=np.uint32), 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(self):
+        df = pd.DataFrame(np.arange(2, dtype=np.uint64), columns=["A"])
+        curve = Curve(df)
+        with self.assertRaisesRegex(TypeError, match="Dtype of uint64 for column A is not supported"):
+            rasterize(curve, dynamic=False, height=10, width=10)
+
 
 
 class DatashaderCatAggregateTests(ComparisonTestCase):
@@ -840,8 +860,6 @@ 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],