Allow defining categorical axis ordering via Dimension.values

holoviews/plotting/bokeh/chart.py

@@ -803,7 +803,7 @@ def get_extents(self, element, ranges, range_type='combined'):
         return (x0, y0, x1, y1)
 
 
-    def _get_factors(self, element):
+    def _get_factors(self, element, ranges):
         """
         Get factors for categorical axes.
         """
@@ -817,11 +817,13 @@ def _get_factors(self, element):
             sdim = element.get_dimension(1)
 
         xdim, ydim = element.dimensions()[:2]
-        xvals = element.dimension_values(0, False)
+
+        xvals = np.asarray(xdim.values or element.dimension_values(0, False))
         xvals = [x if xvals.dtype.kind in 'SU' else xdim.pprint_value(x)
                  for x in xvals]
+
         if gdim and not sdim:
-            gvals = element.dimension_values(gdim, False)
+            gvals = np.asarray(gdim.values or element.dimension_values(gdim, False))
             xvals = sorted([(x, g) for x in xvals for g in gvals])
             is_str = gvals.dtype.kind in 'SU'
             xvals = [(x, g if is_str else gdim.pprint_value(g)) for (x, g) in xvals]

holoviews/plotting/bokeh/element.py

@@ -744,7 +744,7 @@ def _update_ranges(self, element, ranges):
 
         xfactors, yfactors = None, None
         if any(isinstance(ax_range, FactorRange) for ax_range in [x_range, y_range]):
-            xfactors, yfactors = self._get_factors(element)
+            xfactors, yfactors = self._get_factors(element, ranges)
         framewise = self.framewise
         streaming = (self.streaming and any(stream._triggering for stream in self.streaming))
         xupdate = ((not (self.model_changed(x_range) or self.model_changed(plot))
@@ -912,15 +912,15 @@ def get_aspect(self, xspan, yspan):
             return 1
 
 
-    def _get_factors(self, element):
+    def _get_factors(self, element, ranges):
         """
         Get factors for categorical axes.
         """
         xdim, ydim = element.dimensions()[:2]
-        xvals, yvals = [element.dimension_values(i, False)
-                        for i in range(2)]
+        xvals = np.asarray(xdim.values or element.dimension_values(0, False))
+        yvals = np.asarray(ydim.values or element.dimension_values(1, False))
         coords = tuple([v if vals.dtype.kind in 'SU' else dim.pprint_value(v) for v in vals]
-                  for dim, vals in [(xdim, xvals), (ydim, yvals)])
+                       for dim, vals in [(xdim, xvals), (ydim, yvals)])
         if self.invert_axes: coords = coords[::-1]
         return coords
 
@@ -2019,12 +2019,12 @@ def _merge_tools(self, subplot):
                 self.handles['hover'] = tool
 
 
-    def _get_factors(self, overlay):
+    def _get_factors(self, overlay, ranges):
         xfactors, yfactors = [], []
         for k, sp in self.subplots.items():
             el = overlay.data.get(k)
             if el is not None:
-                xfs, yfs = sp._get_factors(el)
+                xfs, yfs = sp._get_factors(el, ranges)
                 xfactors.append(xfs)
                 yfactors.append(yfs)
         if xfactors:

holoviews/plotting/bokeh/heatmap.py

@@ -63,8 +63,8 @@ def is_radial(cls, heatmap):
         return ((any(o in opts for o in ('start_angle', 'radius_inner', 'radius_outer'))
                  and not (opts.get('radial') == False)) or opts.get('radial', False))
 
-    def _get_factors(self, element):
-        return super(HeatMapPlot, self)._get_factors(element.gridded)
+    def _get_factors(self, element, ranges):
+        return super(HeatMapPlot, self)._get_factors(element.gridded, ranges)
 
     def get_data(self, element, ranges, style):
         x, y, z = [dimension_sanitizer(d) for d in element.dimensions(label=True)[:3]]

holoviews/plotting/bokeh/stats.py

@@ -109,7 +109,7 @@ def _apply_transforms(self, element, data, ranges, style, group=None):
                 element = element.clone([(agg,)])
         return super(BoxWhiskerPlot, self)._apply_transforms(element, data, ranges, style, group)
 
-    def _get_factors(self, element):
+    def _get_factors(self, element, ranges):
         """
         Get factors for categorical axes.
         """

holoviews/tests/plotting/bokeh/testelementplot.py

@@ -378,6 +378,12 @@ def test_hover_tooltip_update(self):
         plot.update(('b',))
         self.assertEqual(plot.handles['hover'].tooltips, [('x', '@{x}'), ('b', '@{b}')])
 
+    def test_categorical_dimension_values(self):
+        curve = Curve([('C', 1), ('B', 3)]).redim.values(x=['A', 'B', 'C'])
+        plot = bokeh_renderer.get_plot(curve)
+        x_range = plot.handles['x_range']
+        self.assertEqual(x_range.factors, ['A', 'B', 'C'])
+
     #################################################################
     # Aspect tests
     #################################################################
@@ -794,3 +800,17 @@ def test_active_tools_draw_stream(self):
         toolbar = plot.state.toolbar
         self.assertIsInstance(toolbar.active_tap, tools.PointDrawTool)
         self.assertIsInstance(toolbar.active_drag, tools.PointDrawTool)
+
+    def test_categorical_overlay_dimension_values(self):
+        curve = Curve([('C', 1), ('B', 3)]).redim.values(x=['A', 'B', 'C'])
+        scatter = Scatter([('A', 2)])
+        plot = bokeh_renderer.get_plot(curve*scatter)
+        x_range = plot.handles['x_range']
+        self.assertEqual(x_range.factors, ['A', 'B', 'C'])
+
+    def test_categorical_overlay_dimension_values_skip_factor(self):
+        curve = Curve([('C', 1), ('B', 3)])
+        scatter = Scatter([('A', 2)])
+        plot = bokeh_renderer.get_plot((curve*scatter).redim.values(x=['A', 'C']))
+        x_range = plot.handles['x_range']
+        self.assertEqual(x_range.factors, ['A', 'C'])