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Added log option to histogram operation #929

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Oct 12, 2016
Merged

Added log option to histogram operation #929

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c94c860
Fixed inverted axes on bokeh histogram
philippjfr Oct 12, 2016
01df7a9
Added log option to histogram operation
philippjfr Oct 12, 2016
cdd8292
Small fix to histogram log option docstring
philippjfr Oct 12, 2016
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12 changes: 10 additions & 2 deletions holoviews/operation/element.py
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Original file line number Diff line number Diff line change
Expand Up @@ -478,6 +478,9 @@ class histogram(ElementOperation):
individually = param.Boolean(default=True, doc="""
Specifies whether the histogram will be rescaled for each Raster in a UniformNdMapping.""")

log = param.Boolean(default=False, doc="""
Whether to use base 10 logarithmic samples for the bin edges.""")

mean_weighted = param.Boolean(default=False, doc="""
Whether the weighted frequencies are averaged.""")

Expand Down Expand Up @@ -518,16 +521,21 @@ def _process(self, view, key=None):
if hist_range == (0, 0):
hist_range = (0, 1)
data = data[np.invert(np.isnan(data))]
if self.p.log:
bin_min = max([abs(hist_range[0]), data[data>0].min()])
edges = np.logspace(np.log10(bin_min), np.log10(hist_range[1]),
self.p.num_bins+1)
else:
edges = np.linspace(hist_range[0], hist_range[1], self.p.num_bins + 1)
normed = False if self.p.mean_weighted and self.p.weight_dimension else self.p.normed
try:
hist, edges = np.histogram(data[np.isfinite(data)], normed=normed,
range=hist_range, weights=weights, bins=self.p.num_bins)
range=hist_range, weights=weights, bins=edges)
if not normed and self.p.weight_dimension and self.p.mean_weighted:
hist_mean, _ = np.histogram(data[np.isfinite(data)], normed=normed,
range=hist_range, bins=self.p.num_bins)
hist /= hist_mean
except:
edges = np.linspace(hist_range[0], hist_range[1], self.p.num_bins + 1)
hist = np.zeros(self.p.num_bins)

hist[np.isnan(hist)] = 0
Expand Down
2 changes: 1 addition & 1 deletion holoviews/plotting/bokeh/chart.py
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Expand Up @@ -265,7 +265,7 @@ class SideHistogramPlot(ColorbarPlot, HistogramPlot):

def get_data(self, element, ranges=None, empty=None):
if self.invert_axes:
mapping = dict(top='left', bottom='right', left=0, right='top')
mapping = dict(top='right', bottom='left', left=0, right='top')
else:
mapping = dict(top='top', bottom=0, left='left', right='right')

Expand Down