Only merge changed instance params with rasterize (#5767)

holoviews/core/util.py

@@ -803,6 +803,20 @@ def isnumeric(val):
         return False
 
 
+def isequal(value1, value2):
+    """Compare two values, returning a boolean.
+
+    Will apply the comparison to all elements of an array/dataframe.
+    """
+    try:
+        check = (value1 is value2) or (value1 == value2)
+        if not isinstance(check, bool) and hasattr(check, "all"):
+            check = check.all()
+        return bool(check)
+    except Exception:
+        return False
+
+
 def asarray(arraylike, strict=True):
     """
     Converts arraylike objects to NumPy ndarray types. Errors if

holoviews/operation/datashader.py

@@ -1374,12 +1374,23 @@ class rasterize(AggregationOperation):
                    (type(None), shade) # To handle parameters of datashade
     ]
 
+    __instance_params = set()
+
+    @bothmethod
+    def instance(self_or_cls, **params):
+        inst = super().instance(**params)
+        inst.__instance_params = set(params)
+        return inst
+
     def _process(self, element, key=None):
         # Potentially needs traverse to find element types first?
         all_allowed_kws = set()
         all_supplied_kws = set()
+        instance_params = {
+            k: getattr(self, k) for k in self.__instance_params
+        }
         for predicate, transform in self._transforms:
-            merged_param_values = dict(self.param.values(), **self.p)
+            merged_param_values = dict(instance_params, **self.p)
 
             # If aggregator or interpolation are 'default', pop parameter so
             # datashader can choose the default aggregator itself

holoviews/tests/operation/test_datashader.py

@@ -1150,6 +1150,24 @@ def test_rasterize_image_string_aggregator(self):
         expected = Image(([2., 7.], [0.75, 3.25], [[1, 5], [6, 22]]))
         self.assertEqual(regridded, expected)
 
+    def test_rasterize_image_expand_default(self):
+        # Should use expand=False by default
+        assert not regrid.expand
+
+        data = np.arange(100.0).reshape(10, 10)
+        c = np.arange(10.0)
+        da = xr.DataArray(data, coords=dict(x=c, y=c))
+        rast_input = dict(x_range=(-1, 10), y_range=(-1, 10), precompute=True, dynamic=False)
+        img = rasterize(Image(da), **rast_input)
+        output = img.data["z"].to_numpy()
+
+        np.testing.assert_array_equal(output, data.T)
+        assert not np.isnan(output).any()
+
+        # Setting expand=True with the {x,y}_ranges will expand the data with nan's
+        img = rasterize(Image(da), expand=True, **rast_input)
+        output = img.data["z"].to_numpy()
+        assert np.isnan(output).any()
 
 class DatashaderSpreadTests(ComparisonTestCase):