Generalized concept of implicit categories

holoviews/plotting/bokeh/annotation.py

@@ -138,6 +138,7 @@ class LineAnnotationPlot(ElementPlot, AnnotationPlot):
     apply_ranges = param.Boolean(default=False, doc="""
         Whether to include the annotation in axis range calculations.""")
 
+    _allow_implicit_categories = False
     _plot_methods = dict(single='Span')
 
     def get_data(self, element, ranges, style):
@@ -171,9 +172,6 @@ def get_extents(self, element, ranges=None, range_type='combined'):
         ranges[dim]['soft'] = loc, loc
         return super(LineAnnotationPlot, self).get_extents(element, ranges, range_type)
 
-    def _get_factors(self, element, ranges):
-        return [], []
-
 
 class BoxAnnotationPlot(ElementPlot, AnnotationPlot):
 
@@ -182,6 +180,7 @@ class BoxAnnotationPlot(ElementPlot, AnnotationPlot):
 
     style_opts = line_properties + fill_properties + ['level', 'visible']
 
+    _allow_implicit_categories = False
     _plot_methods = dict(single='BoxAnnotation')
 
     def get_data(self, element, ranges, style):
@@ -207,9 +206,6 @@ def _init_glyph(self, plot, mapping, properties):
         plot.renderers.append(box)
         return None, box
 
-    def _get_factors(self, element, ranges):
-        return [], []
-
 
 class SlopePlot(ElementPlot, AnnotationPlot):
 

holoviews/plotting/bokeh/element.py

@@ -177,6 +177,7 @@ class ElementPlot(BokehPlot, GenericElementPlot):
         Formatter for ticks along the x-axis.""")
 
     _categorical = False
+    _allow_implicit_categories = True
 
     # Declare which styles cannot be mapped to a non-scalar dimension
     _nonvectorized_styles = []
@@ -953,6 +954,9 @@ def _get_factors(self, element, ranges):
         else:
             yvals = element.dimension_values(1, False)
         xvals, yvals = np.asarray(xvals), np.asarray(yvals)
+        if not self._allow_implicit_categories:
+            xvals = xvals if xvals.dtype.kind in 'SU' else []
+            yvals = yvals if yvals.dtype.kind in 'SU' else []
         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)])
         if self.invert_axes: coords = coords[::-1]

holoviews/plotting/bokeh/geometry.py

@@ -23,6 +23,7 @@ class SegmentPlot(GeomMixin, ColorbarPlot):
 
     style_opts = base_properties + line_properties + ['cmap']
 
+    _allow_implicit_categories = False
     _nonvectorized_styles = base_properties + ['cmap']
     _plot_methods = dict(single='segment')
 
@@ -33,9 +34,6 @@ def get_data(self, element, ranges, style):
         mapping = dict(x0='x0', x1='x1', y0='y0', y1='y1')
         return (data, mapping, style)
 
-    def _get_factors(self, element, ranges):
-        return [], []
-
 
 class RectanglesPlot(GeomMixin, LegendPlot, ColorbarPlot):
 
@@ -48,6 +46,7 @@ class RectanglesPlot(GeomMixin, LegendPlot, ColorbarPlot):
     style_opts = (base_properties + line_properties + fill_properties +
                   ['cmap'])
 
+    _allow_implicit_categories = False
     _nonvectorized_styles = base_properties + ['cmap']
     _plot_methods = dict(single='rect')
     _batched_style_opts = line_properties + fill_properties
@@ -61,6 +60,3 @@ def get_data(self, element, ranges, style):
         data = {'x': (x1+x0)/2., 'y': (y1+y0)/2., 'width': x1-x0, 'height': y1-y0}
         mapping = {'x': 'x', 'y': 'y', 'width': 'width', 'height': 'height'}
         return data, mapping, style
-
-    def _get_factors(self, element, ranges):
-        return [], []