Implement multi-yaxis support

examples/user_guide/Customizing_Plots.ipynb

@@ -44,7 +44,8 @@
     "    - [Inverting axes](#inverting-axes): Flipping the x-/y-axes and inverting an axis\n",
     "    - [Axis labels](#axis-labels): Setting axis labels using dimensions and options\n",
     "    - [Axis ranges](#axis-ranges): Controlling axes ranges using dimensions, padding and options\n",
-    "    - [Axis ticks](#axis-ticks): Controlling axis tick locations, labels and formatting"
+    "    - [Axis ticks](#axis-ticks): Controlling axis tick locations, labels and formatting\n",
+    "    - [Twin axes](#twin-axes): Enabling twin axes"
    ]
   },
   {
@@ -689,6 +690,80 @@
    "source": [
     "bars.opts(xrotation=45)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Twin axes\n",
+    "*(Available in HoloViews > 1.17)*\n",
+    "\n",
+    "HoloViews now supports displaying overlays containing two different value dimensions as twin axes for chart elements. To maintain backwards compatibility, this feature is only enabled by setting the `multi_y=True` option on the overlay:\n",
+    "\n",
+    "To illustrate, here is an overlay containing three curves with two value dimensions ('A' and 'B'). The following shows the default, backwards compatible behavior:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "overlay = hv.Curve([1, 2, 3], vdims=['A']) * hv.Curve([2, 3, 4], vdims=['A']) * hv.Curve([3, 2, 1], vdims=['B'])\n",
+    "overlay"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Additional value dimensions do map to additional axes but be aware that support of multi axes beyond twin axes is currently considered experimental.\n",
+    "\n",
+    "#### Setting `multi_y=True`\n",
+    "\n",
+    "We can now enable twin axes by setting `multi_y=True` on the overlay:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "overlay.opts(multi_y=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The first value dimension is mapped to the left-hand axis and the second value dimension maps to the right axis. Note that the two axes are individually zoomable by hovering over them and using the Bokeh wheelzoom tool.\n",
+    "\n",
+    "\n",
+    "#### Supported `multi_y` options\n",
+    "\n",
+    "When `multi_y` is enabled, you can set individual axis options on the elements of the overlay.\n",
+    "\n",
+    "In this example, the left axis uses the default options while the right axis is an inverted, autoranged, log axis with a set `ylim`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "(hv.Curve([1, 2, 3], vdims=['A']) * hv.Curve([2, 3, 4], vdims=['B']).opts(autorange='y', invert_yaxis=True, logy=True, ylim=(1,10))).opts(multi_y=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Supported options for customizing individual axes are `apply_ranges`, `autorange='y'`, `invert_yaxis`, `logy` and `ylim`.\n",
+    "\n",
+    "Note that as of HoloViews 1.17.0, `multi_y` does not have streaming plot support and that linked streams are not yet aware of additional y-axes."
+   ]
   }
  ],
  "metadata": {
@@ -698,5 +773,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }

holoviews/plotting/bokeh/annotation.py

@@ -64,7 +64,7 @@ def get_batched_data(self, element, ranges=None):
                 data[k].extend(eld)
         return data, elmapping, style
 
-    def get_extents(self, element, ranges=None, range_type='combined'):
+    def get_extents(self, element, ranges=None, range_type='combined', **kwargs):
         return None, None, None, None
 
 
@@ -161,7 +161,7 @@ def _init_glyph(self, plot, mapping, properties):
         plot.renderers.append(box)
         return None, box
 
-    def get_extents(self, element, ranges=None, range_type='combined'):
+    def get_extents(self, element, ranges=None, range_type='combined', **kwargs):
         loc = element.data
         if isinstance(element, VLine):
             dim = 'x'
@@ -241,7 +241,7 @@ def _init_glyph(self, plot, mapping, properties):
         plot.add_layout(slope)
         return None, slope
 
-    def get_extents(self, element, ranges=None, range_type='combined'):
+    def get_extents(self, element, ranges=None, range_type='combined', **kwargs):
         return None, None, None, None
 
 
@@ -366,7 +366,7 @@ def _init_glyph(self, plot, mapping, properties, key):
         plot.renderers.append(renderer)
         return renderer, glyph
 
-    def get_extents(self, element, ranges=None, range_type='combined'):
+    def get_extents(self, element, ranges=None, range_type='combined', **kwargs):
         return None, None, None, None
 
 

holoviews/plotting/bokeh/chart.py

@@ -434,7 +434,7 @@ def get_data(self, element, ranges, style):
             self._get_hover_data(data, element)
         return (data, mapping, style)
 
-    def get_extents(self, element, ranges, range_type='combined'):
+    def get_extents(self, element, ranges, range_type='combined', **kwargs):
         ydim = element.get_dimension(1)
         s0, s1 = ranges[ydim.name]['soft']
         s0 = min(s0, 0) if isfinite(s0) else 0
@@ -693,11 +693,6 @@ class SpikesPlot(SpikesMixin, ColorbarPlot):
     _nonvectorized_styles = base_properties + ['cmap']
     _plot_methods = dict(single='segment')
 
-    def _get_axis_dims(self, element):
-        if 'spike_length' in self.lookup_options(element, 'plot').options:
-            return  [element.dimensions()[0], None, None]
-        return super()._get_axis_dims(element)
-
     def get_data(self, element, ranges, style):
         dims = element.dimensions()
 
@@ -815,13 +810,6 @@ def _axis_properties(self, axis, key, plot, dimension=None,
                 props['group_text_baseline'] = 'middle'
         return props
 
-    def _get_axis_dims(self, element):
-        if element.ndims > 1 and not (self.stacked or not self.multi_level):
-            xdims = element.kdims
-        else:
-            xdims = element.kdims[0]
-        return (xdims, element.vdims[0])
-
     def _get_factors(self, element, ranges):
         xvals, gvals = self._get_coords(element, ranges)
         if gvals is not None: