Add operation for group-wise normalisation

holoviews/operation/normalization.py

@@ -12,13 +12,15 @@
 normalizations result in transformations to the stored data within
 each element.
 """
+from collections import defaultdict
 
+import numpy as np
 import param
 
 from ..core import Overlay
 from ..core.operation import Operation
 from ..core.util import match_spec
-from ..element import Raster
+from ..element import Chart, Raster
 
 
 class Normalization(Operation):
@@ -175,3 +177,38 @@ def _normalize_raster(self, raster, key):
                 if range:
                     norm_raster.data[:,:,depth] /= range
         return norm_raster
+
+
+class subcoordinate_group_ranges(Operation):
+    """
+    Compute the data range group-wise in a subcoordinate_y overlay,
+    and set the dimension range of each Chart element based on the
+    value computed for its group.
+
+    This operation is useful to visually apply a group-wise min-max
+    normalisation.
+    """
+
+    def _process(self, overlay, key=None):
+        vmins = defaultdict(list)
+        vmaxs = defaultdict(list)
+        for el in overlay:
+            if not isinstance(el, Chart):
+                continue
+            vmin, vmax = el.range(1)
+            vmins[el.group].append(vmin)
+            vmaxs[el.group].append(vmax)
+
+        minmax = {
+            group: (np.min(vmins[group]), np.max(vmaxs[group]))
+            for group in vmins
+        }
+        new = []
+        for el in overlay:
+            if not isinstance(el, Chart):
+                new.append(el)
+                continue
+            y_dimension = el.vdims[0]
+            y_dimension = y_dimension.clone(range=minmax[el.group])
+            new.append(el.redim(**{y_dimension.name: y_dimension}))
+        return overlay.clone(data=new)

holoviews/plotting/bokeh/element.py

@@ -486,10 +486,15 @@ def _axis_props(self, plots, subplots, element, ranges, pos, *, dim=None,
 
         range_el = el if self.batched and not isinstance(self, OverlayPlot) else element
 
+        if pos == 1 and 'subcoordinate_y' in range_tags_extras and dim and dim.range != (None, None):
+            dims = [dim]
+            v0, v1 = dim.range
+            axis_label = str(dim)
+            specs = ((dim.name, dim.label, dim.unit),)
         # For y-axes check if we explicitly passed in a dimension.
         # This is used by certain plot types to create an axis from
         # a synthetic dimension and exclusively supported for y-axes.
-        if pos == 1 and dim:
+        elif pos == 1 and dim:
             dims = [dim]
             v0, v1 = util.max_range([
                 elrange.get(dim.name, {'combined': (None, None)})['combined']

holoviews/tests/plotting/bokeh/test_subcoordy.py

@@ -5,6 +5,7 @@
 from holoviews.core import Overlay
 from holoviews.element import Curve
 from holoviews.element.annotation import VSpan
+from holoviews.operation.normalization import subcoordinate_group_ranges
 
 from .test_plot import TestBokehPlot, bokeh_renderer
 
@@ -250,3 +251,33 @@ def test_tools_instance_zoom_untouched(self):
                     break
             else:
                 raise AssertionError('Provided zoom not found.')
+
+    def test_norm_subcoordinate_group_ranges(self):
+        x = np.linspace(0, 10 * np.pi, 21)
+        curves = []
+        j = 0
+        for group in ['A', 'B']:
+            for i in range(2):
+                yvals = j * np.sin(x)
+                curves.append(
+                    Curve((x + np.pi/2, yvals), label=f'{group}{i}', group=group).opts(subcoordinate_y=True)
+                )
+                j += 1
+
+        overlay = Overlay(curves)
+        noverlay = subcoordinate_group_ranges(overlay)
+
+        expected = [
+            (-1.0, 1.0),
+            (-1.0, 1.0),
+            (-3.0, 3.0),
+            (-3.0, 3.0),
+        ]
+        for i, el in enumerate(noverlay):
+            assert el.get_dimension('y').range == expected[i]
+
+        plot = bokeh_renderer.get_plot(noverlay)
+
+        for i, sp in enumerate(plot.subplots.values()):
+                y_source = sp.handles['glyph_renderer'].coordinates.y_source
+                assert (y_source.start, y_source.end) == expected[i]