Add step_curve operation and Curve interpolation plot option

holoviews/operation/element.py

@@ -605,6 +605,53 @@ def _process(self, element, key=None):
         return sliced
 
 
+def pts_to_prestep(x, y):
+    steps = np.zeros((2, 2 * len(x) - 1))
+    steps[0, 0::2] = x
+    steps[0, 1::2] = steps[0, 0:-2:2]
+    steps[1:, 0::2] = y
+    steps[1:, 1::2] = steps[1:, 2::2]
+    return steps
+
+def pts_to_poststep(x, y):
+    steps = np.zeros((2, 2 * len(x) - 1))
+    steps[0, 0::2] = x
+    steps[0, 1::2] = steps[0, 2::2]
+    steps[1:, 0::2] = y
+    steps[1:, 1::2] = steps[1:, 0:-2:2]
+    return steps
+
+def pts_to_midstep(x, y):
+    steps = np.zeros((2, 2 * len(x)))
+    x = np.asanyarray(x)
+    steps[0, 1:-1:2] = steps[0, 2::2] = (x[:-1] + x[1:]) / 2
+    steps[0, 0], steps[0, -1] = x[0], x[-1]
+    steps[1:, 0::2] = y
+    steps[1:, 1::2] = steps[1:, 0::2]
+    return steps
+
+
+class step_curve(ElementOperation):
+    """
+    Resamples a Curve to represent changes in y-values as steps.
+    The transition point of the step along the x-axis is configurable
+    via the ``where`` parameter.
+    """
+
+    where = param.ObjectSelector(objects=['pre', 'mid', 'post'],
+                                 default='mid', doc="""
+       Controls the transition point of the step along the x-axis""")
+
+    STEP_FUNCS = {'pre': pts_to_prestep, 'mid': pts_to_midstep,
+                  'post': pts_to_poststep}
+
+    def _process(self, element, key=None):
+        x, y = element.dimension_values(0), element.dimension_values(1)
+        array = self.STEP_FUNCS[self.p.where](x, y)
+        dvals = tuple(element.dimension_values(d) for d in element.dimensions()[2:])
+        return element.clone((array[0, :], array[1, :])+dvals)
+
+
 #==================#
 # Other operations #
 #==================#

holoviews/plotting/bokeh/chart.py

@@ -13,6 +13,7 @@
 from ...element import Raster, Points, Polygons, Spikes
 from ...core.util import max_range, basestring, dimension_sanitizer
 from ...core.options import abbreviated_exception
+from ...operation import step_curve
 from ..util import compute_sizes, get_sideplot_ranges, match_spec, map_colors
 from .element import ElementPlot, ColorbarPlot, LegendPlot, line_properties, fill_properties
 from .path import PathPlot, PolygonPlot
@@ -138,11 +139,20 @@ def _init_glyph(self, plot, mapping, properties):
 
 class CurvePlot(ElementPlot):
 
+    interpolation = param.ObjectSelector(objects=['linear', 'steps-mid',
+                                                  'steps-pre', 'steps-post'],
+                                         default='linear', doc="""
+        Defines how the samples of the Curve are interpolated,
+        default is 'linear', other options include 'steps-mid',
+        'steps-pre' and 'steps-post'.""")
+
     style_opts = ['color'] + line_properties
     _plot_methods = dict(single='line', batched='multi_line')
     _mapping = {p: p for p in ['xs', 'ys', 'color', 'line_alpha']}
 
     def get_data(self, element, ranges=None, empty=False):
+        if 'steps' in self.interpolation:
+            element = step_curve(element, where=self.interpolation.split('-')[1])
         xidx, yidx = (1, 0) if self.invert_axes else (0, 1)
         x = element.get_dimension(xidx).name
         y = element.get_dimension(yidx).name
@@ -562,9 +572,7 @@ def _update_chart(self, key, element, ranges):
 
     @property
     def current_handles(self):
-        plot = self.handles['plot']
-        sources = plot.select(type=ColumnDataSource)
-        return sources
+        return self.state.select(type=(ColumnDataSource, Range1d))
 
 
 class BoxPlot(ChartPlot):
@@ -596,6 +604,15 @@ def _init_chart(self, element, ranges):
                             **properties)
 
 
+    def _update_chart(self, key, element, ranges):
+        super(BoxPlot, self)._update_chart(key, element, ranges)
+        vdim = element.vdims[0].name
+        start, end = ranges[vdim]
+        self.state.y_range.start = start
+        self.state.y_range.end = end
+
+
+
 class BarPlot(ChartPlot):
     """
     BarPlot allows generating single- or multi-category

holoviews/plotting/mpl/chart.py

@@ -14,6 +14,7 @@
 from ...core.util import (match_spec, unique_iterator, safe_unicode,
                           basestring, max_range, unicode)
 from ...element import Points, Raster, Polygons, HeatMap
+from ...operation import step_curve
 from ..util import compute_sizes, get_sideplot_ranges, map_colors
 from .element import ElementPlot, ColorbarPlot, LegendPlot
 from .path  import PathPlot
@@ -41,6 +42,13 @@ class CurvePlot(ChartPlot):
         Whether to let matplotlib automatically compute tick marks
         or to allow the user to control tick marks.""")
 
+    interpolation = param.ObjectSelector(objects=['linear', 'steps-mid',
+                                                  'steps-pre', 'steps-post'],
+                                         default='linear', doc="""
+        Defines how the samples of the Curve are interpolated,
+        default is 'linear', other options include 'steps-mid',
+        'steps-pre' and 'steps-post'.""")
+
     relative_labels = param.Boolean(default=False, doc="""
         If plotted quantity is cyclic and center_cyclic is enabled,
         will compute tick labels relative to the center.""")
@@ -59,6 +67,8 @@ class CurvePlot(ChartPlot):
     _plot_methods = dict(single='plot')
 
     def get_data(self, element, ranges, style):
+        if 'steps' in self.interpolation:
+            element = step_curve(element, where=self.interpolation.split('-')[1])
         xs = element.dimension_values(0)
         ys = element.dimension_values(1)
         dims = element.dimensions()

holoviews/plotting/plotly/chart.py

@@ -3,6 +3,7 @@
 from plotly.tools import FigureFactory as FF
 
 from ...core import util
+from ...operation import step_curve
 from .element import ElementPlot, ColorbarPlot
 
 
@@ -41,11 +42,20 @@ def get_data(self, element, ranges):
 
 class CurvePlot(ElementPlot):
 
+    interpolation = param.ObjectSelector(objects=['linear', 'steps-mid',
+                                                  'steps-pre', 'steps-post'],
+                                         default='linear', doc="""
+        Defines how the samples of the Curve are interpolated,
+        default is 'linear', other options include 'steps-mid',
+        'steps-pre' and 'steps-post'.""")
+
     graph_obj = go.Scatter
 
     style_opts = ['color', 'dash', 'width']
 
     def graph_options(self, element, ranges):
+        if 'steps' in self.interpolation:
+            element = step_curve(element, where=self.interpolation.split('-')[1])
         opts = super(CurvePlot, self).graph_options(element, ranges)
         opts['mode'] = 'lines'
         style = self.style[self.cyclic_index]