Add link_selections support

holoviews/plotting/bokeh/chart.py

@@ -8,6 +8,8 @@
 from bokeh.models.tools import BoxSelectTool
 from bokeh.transform import jitter
 
+from ...plotting.bokeh.selection import BokehOverlaySelectionDisplay
+from ...selection import NoOpSelectionDisplay
 from ...core.data import Dataset
 from ...core.dimension import dimension_name
 from ...core.util import (
@@ -58,6 +60,8 @@ class PointPlot(LegendPlot, ColorbarPlot):
     _plot_methods = dict(single='scatter', batched='scatter')
     _batched_style_opts = line_properties + fill_properties + ['size', 'marker', 'angle']
 
+    selection_display = BokehOverlaySelectionDisplay()
+
     def _get_size_data(self, element, ranges, style):
         data, mapping = {}, {}
         sdim = element.get_dimension(self.size_index)
@@ -396,6 +400,8 @@ class HistogramPlot(ColorbarPlot):
 
     _nonvectorized_styles = ['line_dash', 'visible']
 
+    selection_display = BokehOverlaySelectionDisplay()
+
     def get_data(self, element, ranges, style):
         if self.invert_axes:
             mapping = dict(top='right', bottom='left', left=0, right='top')
@@ -505,6 +511,10 @@ class ErrorPlot(ColorbarPlot):
 
     _plot_methods = dict(single=Whisker)
 
+    # selection_display should be changed to BokehOverlaySelectionDisplay
+    # when #3950 is fixed
+    selection_display = NoOpSelectionDisplay()
+
     def get_data(self, element, ranges, style):
         mapping = dict(self._mapping)
         if self.static_source:
@@ -664,6 +674,8 @@ class SpikesPlot(ColorbarPlot):
 
     _plot_methods = dict(single='segment')
 
+    selection_display = BokehOverlaySelectionDisplay()
+
     def get_extents(self, element, ranges, range_type='combined'):
         if len(element.dimensions()) > 1:
             ydim = element.get_dimension(1)
@@ -779,6 +791,8 @@ class BarPlot(ColorbarPlot, LegendPlot):
     # Declare that y-range should auto-range if not bounded
     _y_range_type = Range1d
 
+    selection_display = BokehOverlaySelectionDisplay()
+
     def get_extents(self, element, ranges, range_type='combined'):
         """
         Make adjustments to plot extents by computing

holoviews/plotting/bokeh/plot.py

@@ -10,6 +10,7 @@
 from bokeh.models import (ColumnDataSource, Column, Row, Div)
 from bokeh.models.widgets import Panel, Tabs
 
+from ...selection import NoOpSelectionDisplay
 from ...core import (
     OrderedDict, Store, AdjointLayout, NdLayout, Layout, Empty,
     GridSpace, HoloMap, Element
@@ -77,6 +78,8 @@ class BokehPlot(DimensionedPlot, CallbackPlot):
 
     backend = 'bokeh'
 
+    selection_display = NoOpSelectionDisplay()
+
     @property
     def id(self):
         return self.root.ref['id'] if self.root else None

holoviews/plotting/bokeh/selection.py

@@ -0,0 +1,33 @@
+from ...selection import OverlaySelectionDisplay
+from ...core.options import Store
+
+
+class BokehOverlaySelectionDisplay(OverlaySelectionDisplay):
+    """
+    Overlay selection display subclass for use with bokeh backend
+    """
+    def _build_element_layer(
+            self, element, layer_color, selection_expr=True
+    ):
+        element, visible = self._select(element, selection_expr)
+
+        backend_options = Store.options(backend='bokeh')
+        style_options = backend_options[(type(element).name,)]['style']
+
+        def alpha_opts(alpha):
+            options = dict()
+
+            for opt_name in style_options.allowed_keywords:
+                if 'alpha' in opt_name:
+                    options[opt_name] = alpha
+
+            return options
+
+        layer_alpha = 1.0 if visible else 0.0
+        layer_element = element.options(
+            tools=['box_select'],
+            **self._get_color_kwarg(layer_color),
+            **alpha_opts(layer_alpha)
+        )
+
+        return layer_element

holoviews/plotting/bokeh/stats.py

@@ -8,6 +8,7 @@
 
 from bokeh.models import FactorRange, Circle, VBar, HBar
 
+from .selection import BokehOverlaySelectionDisplay
 from ...core.dimension import Dimension, Dimensioned
 from ...core.ndmapping import sorted_context
 from ...core.util import (basestring, dimension_sanitizer, wrap_tuple,
@@ -34,6 +35,8 @@ class DistributionPlot(AreaPlot):
     filled = param.Boolean(default=True, doc="""
         Whether the bivariate contours should be filled.""")
 
+    selection_display = BokehOverlaySelectionDisplay()
+
 
 class BivariatePlot(PolygonPlot):
     """
@@ -55,7 +58,7 @@ class BivariatePlot(PolygonPlot):
     levels = param.ClassSelector(default=10, class_=(list, int), doc="""
         A list of scalar values used to specify the contour levels.""")
 
-
+    selection_display = BokehOverlaySelectionDisplay(color_prop='cmap', is_cmap=True)
 
 
 class BoxWhiskerPlot(CompositeElementPlot, ColorbarPlot, LegendPlot):
@@ -84,6 +87,8 @@ class BoxWhiskerPlot(CompositeElementPlot, ColorbarPlot, LegendPlot):
 
     _stream_data = False # Plot does not support streaming data
 
+    selection_display = BokehOverlaySelectionDisplay()
+
     def get_extents(self, element, ranges, range_type='combined'):
         return super(BoxWhiskerPlot, self).get_extents(
             element, ranges, range_type, 'categorical', element.vdims[0]
@@ -332,6 +337,8 @@ class ViolinPlot(BoxWhiskerPlot):
 
     _stat_fns = [partial(np.percentile, q=q) for q in [25, 50, 75]]
 
+    selection_display = BokehOverlaySelectionDisplay(color_prop='violin_fill_color')
+
     def _kde_data(self, el, key, **kwargs):
         vdim = el.vdims[0]
         values = el.dimension_values(vdim)

holoviews/plotting/plot.py

@@ -17,6 +17,7 @@
 from panel.io.notebook import push
 from panel.io.state import state
 
+from ..selection import NoOpSelectionDisplay
 from ..core import OrderedDict
 from ..core import util, traversal
 from ..core.element import Element, Element3D
@@ -947,6 +948,8 @@ class GenericElementPlot(DimensionedPlot):
     _propagate_options = []
     v17_option_propagation = True
 
+    _selection_display = NoOpSelectionDisplay()
+
     def __init__(self, element, keys=None, ranges=None, dimensions=None,
                  batched=False, overlaid=0, cyclic_index=0, zorder=0, style=None,
                  overlay_dims={}, stream_sources=[], streams=None, **params):

holoviews/plotting/plotly/chart.py

@@ -3,6 +3,7 @@
 import param
 import numpy as np
 
+from .selection import PlotlyOverlaySelectionDisplay
 from ...core.data import Dataset
 from ...core import util
 from ...element import Bars
@@ -44,6 +45,8 @@ class ScatterPlot(ChartPlot, ColorbarPlot):
 
     _style_key = 'marker'
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
     def graph_options(self, element, ranges, style):
         opts = super(ScatterPlot, self).graph_options(element, ranges, style)
         cdim = element.get_dimension(self.color_index)
@@ -148,6 +151,8 @@ class ErrorBarsPlot(ChartPlot, ColorbarPlot):
 
     _style_key = 'error_y'
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
     def get_data(self, element, ranges, style):
         x, y = ('y', 'x') if self.invert_axes else ('x', 'y')
         error_k = 'error_' + x if element.horizontal else 'error_' + y
@@ -188,6 +193,8 @@ class BarPlot(ElementPlot):
 
     trace_kwargs = {'type': 'bar'}
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
     def get_extents(self, element, ranges, range_type='combined'):
         """
         Make adjustments to plot extents by computing
@@ -297,10 +304,14 @@ class HistogramPlot(ElementPlot):
 
     trace_kwargs = {'type': 'bar'}
 
-    style_opts = ['visible', 'color', 'line_color', 'line_width', 'opacity']
+    style_opts = [
+        'visible', 'color', 'line_color', 'line_width', 'opacity', 'selectedpoints'
+    ]
 
     _style_key = 'marker'
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
     def get_data(self, element, ranges, style):
         xdim = element.kdims[0]
         ydim = element.vdims[0]

holoviews/plotting/plotly/chart3d.py

@@ -6,6 +6,7 @@
 from plotly import colors
 from plotly.figure_factory._trisurf import trisurf as trisurface
 
+from .selection import PlotlyOverlaySelectionDisplay
 from ...core.options import SkipRendering
 from .element import ElementPlot, ColorbarPlot
 from .chart import ScatterPlot, CurvePlot
@@ -58,6 +59,12 @@ class Scatter3DPlot(Chart3DPlot, ScatterPlot):
 
     trace_kwargs = {'type': 'scatter3d', 'mode': 'markers'}
 
+    style_opts = [
+        'visible', 'marker', 'color', 'cmap', 'alpha', 'opacity', 'size', 'sizemin'
+    ]
+
+    selection_display = PlotlyOverlaySelectionDisplay()
+
 
 class Path3DPlot(Chart3DPlot, CurvePlot):
 

holoviews/plotting/plotly/selection.py

@@ -0,0 +1,29 @@
+from __future__ import absolute_import
+from ...selection import OverlaySelectionDisplay
+from ...core.options import Store
+
+
+class PlotlyOverlaySelectionDisplay(OverlaySelectionDisplay):
+    """
+    Overlay selection display subclass for use with plotly backend
+    """
+    def _build_element_layer(
+            self, element, layer_color, selection_expr=True
+    ):
+        element, visible = self._select(element, selection_expr)
+
+        backend_options = Store.options(backend='plotly')
+        style_options = backend_options[(type(element).name,)]['style']
+
+        if 'selectedpoints' in style_options.allowed_keywords:
+            shared_opts = dict(selectedpoints=False)
+        else:
+            shared_opts = dict()
+
+        layer_element = element.options(
+            visible=visible,
+            **self._get_color_kwarg(layer_color),
+            **shared_opts
+        )
+
+        return layer_element

holoviews/plotting/plotly/stats.py

@@ -2,6 +2,7 @@
 
 import param
 
+from .selection import PlotlyOverlaySelectionDisplay
 from .chart import ChartPlot
 from .element import ElementPlot, ColorbarPlot
 
@@ -18,6 +19,8 @@ class BivariatePlot(ChartPlot, ColorbarPlot):
 
     _style_key = 'contours'
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
     def graph_options(self, element, ranges, style):
         opts = super(BivariatePlot, self).graph_options(element, ranges, style)
         copts = self.get_color_opts(element.vdims[0], element, ranges, style)
@@ -44,6 +47,9 @@ def graph_options(self, element, ranges, style):
 
         opts['showscale'] = copts.get('showscale', False)
 
+        # Add visible
+        opts['visible'] = style.get('visible', True)
+
         return opts
 
 
@@ -64,6 +70,8 @@ class DistributionPlot(ElementPlot):
 
     _style_key = 'line'
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
 
 class MultiDistributionPlot(ElementPlot):
 
@@ -118,6 +126,8 @@ class BoxWhiskerPlot(MultiDistributionPlot):
 
     _style_key = 'marker'
 
+    selection_display = PlotlyOverlaySelectionDisplay()
+
     def graph_options(self, element, ranges, style):
         options = super(BoxWhiskerPlot, self).graph_options(element, ranges, style)
         options['boxmean'] = self.mean

holoviews/plotting/plotly/tabular.py

@@ -2,6 +2,7 @@
 
 import param
 
+from ...selection import ColorListSelectionDisplay
 from .element import ElementPlot
 
 
@@ -17,12 +18,26 @@ class TablePlot(ElementPlot):
 
     _style_key = 'cells'
 
+    selection_display = ColorListSelectionDisplay(color_prop='fill')
+
     def get_data(self, element, ranges, style):
         header = dict(values=[d.pprint_label for d in element.dimensions()])
         cells = dict(values=[[d.pprint_value(v) for v in element.dimension_values(d)]
                               for d in element.dimensions()])
         return [{'header': header, 'cells': cells}]
 
+    def graph_options(self, element, ranges, style):
+        opts = super(TablePlot, self).graph_options(element, ranges, style)
+
+        # Transpose fill_color array so values apply by rows not column
+        if 'fill' in opts.get('cells', {}):
+            opts['cells']['fill_color'] = [opts['cells'].pop('fill')]
+
+        if 'line' in opts.get('cells', {}):
+            opts['cells']['line_color'] = [opts['cells']['line']]
+
+        return opts
+
     def init_layout(self, key, element, ranges):
         return dict(width=self.width, height=self.height,
                     title=self._format_title(key, separator=' '),