Added unit tests for redim method

tests/testdataset.py

@@ -83,6 +83,17 @@ def test_dataset_sort_vdim_hm(self):
                                  kdims=['x'], vdims=['y'])
         self.assertEqual(dataset.sort('y'), dataset_sorted)
 
+
+    def test_dataset_redim_hm_kdim(self):
+        redimmed = self.dataset_hm.redim(x='Time')
+        self.assertEqual(redimmed.dimension_values('Time'),
+                         self.dataset_hm.dimension_values('x'))
+
+    def test_dataset_redim_hm_vdim(self):
+        redimmed = self.dataset_hm.redim(y='Value')
+        self.assertEqual(redimmed.dimension_values('Value'),
+                         self.dataset_hm.dimension_values('y'))
+
     def test_dataset_sample_hm(self):
         samples = self.dataset_hm.sample([0, 5, 10]).dimension_values('y')
         self.assertEqual(samples, np.array([0, 10, 20]))

tests/testdimensions.py

@@ -1,7 +1,7 @@
 """
 Test cases for Dimension and Dimensioned object behaviour.
 """
-from holoviews.core import Dimensioned
+from holoviews.core import Dimensioned, Dimension
 from holoviews.element.comparison import ComparisonTestCase
 
 
@@ -18,3 +18,22 @@ def test_dimensioned_constant_label(self):
             view.label = 'another label'
             raise AssertionError("Label should be a constant parameter.")
         except TypeError: pass
+
+    def test_dimensionsed_redim_string(self):
+        dimensioned = Dimensioned('Arbitrary Data', kdims=['x'])
+        redimensioned = dimensioned.clone(kdims=['Test'])
+        self.assertEqual(redimensioned, dimensioned.redim(x='Test'))
+
+    def test_dimensionsed_redim_dimension(self):
+        dimensioned = Dimensioned('Arbitrary Data', kdims=['x'])
+        redimensioned = dimensioned.clone(kdims=['Test'])
+        self.assertEqual(redimensioned, dimensioned.redim(x=Dimension('Test')))
+
+    def test_dimensionsed_redim_dict(self):
+        dimensioned = Dimensioned('Arbitrary Data', kdims=['x'])
+        redimensioned = dimensioned.clone(kdims=['Test'])
+        self.assertEqual(redimensioned, dimensioned.redim(x={'name': 'Test'}))
+
+    def test_dimensionsed_redim_dict_range(self):
+        redimensioned = Dimensioned('Arbitrary Data', kdims=['x']).redim(x={'range': (0, 10)})
+        self.assertEqual(redimensioned.kdims[0].range, (0, 10))

tests/testndmapping.py

@@ -97,6 +97,12 @@ def test_idxmapping_reindex(self):
 
         self.assertEqual([d.name for d in reduced_ndmap.kdims], reduced_dims)
 
+    def test_idxmapping_redim(self):
+        data = [((0, 0.5), 'a'), ((1, 0.5), 'b')]
+        ndmap = MultiDimensionalMapping(data, kdims=[self.dim1, self.dim2])
+        redimmed = ndmap.redim(intdim='Integer')
+        self.assertEqual(redimmed.kdims, [Dimension('Integer'), Dimension('floatdim')])
+
     def test_idxmapping_add_dimension(self):
         ndmap = MultiDimensionalMapping(self.init_items_1D_list, kdims=[self.dim1])
         ndmap2d = ndmap.add_dimension(self.dim2, 0, 0.5)
@@ -136,6 +142,21 @@ def setUp(self):
         self.columns = Dataset(np.column_stack([self.xs, self.y_ints]),
                                kdims=['x'], vdims=['y'])
 
+    def test_holomap_redim(self):
+        hmap = HoloMap({i: Dataset({'x':self.xs, 'y': self.ys * i},
+                                   kdims=['x'], vdims=['y'])
+                        for i in range(10)}, kdims=['z'])
+        redimmed = hmap.redim(x='Time')
+        self.assertEqual(redimmed.dimensions('all', True),
+                         ['z', 'Time', 'y'])
+
+    def test_holomap_redim_nested(self):
+        hmap = HoloMap({i: Dataset({'x':self.xs, 'y': self.ys * i},
+                                   kdims=['x'], vdims=['y'])
+                        for i in range(10)}, kdims=['z'])
+        redimmed = hmap.redim(x='Time', z='Magnitude')
+        self.assertEqual(redimmed.dimensions('all', True),
+                         ['Magnitude', 'Time', 'y'])
 
     def test_columns_collapse_heterogeneous(self):
         collapsed = HoloMap({i: Dataset({'x':self.xs, 'y': self.ys * i},