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Make logscale bar/hist autolimits more consistents. #14581

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Aug 12, 2019
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Make logscale bar/hist autolimits more consistents. #14581

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10 changes: 10 additions & 0 deletions doc/api/next_api_changes/2019-06-19-AL.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1,10 @@
log-scale bar() / hist() autolimits change
``````````````````````````````````````````

The autolimits computation in `~.Axes.bar` and `~.Axes.hist` when the axes
already uses log-scale has changed to match the computation when the axes is
switched to log-scale after the call to `~.Axes.bar` and `~.Axes.hist`, and
when calling ``bar(..., log=True)`` / ``hist(..., log=True)``: if there are
at least two different bar heights, add the normal axes margins to them (in
log-scale); if there is only a single bar height, expand the axes limits by one
order of magnitude around it and then apply axes margins.
53 changes: 3 additions & 50 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -2303,20 +2303,12 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
label = kwargs.pop('label', '')
tick_labels = kwargs.pop('tick_label', None)

adjust_ylim = False
adjust_xlim = False

y = bottom # Matches barh call signature.
if orientation == 'vertical':
if bottom is None:
if self.get_yscale() == 'log':
adjust_ylim = True
if y is None:
y = 0

elif orientation == 'horizontal':
if x is None:
if self.get_xscale() == 'log':
adjust_xlim = True
x = 0

if orientation == 'vertical':
Expand Down Expand Up @@ -2429,21 +2421,6 @@ def bar(self, x, height, width=0.8, bottom=None, *, align="center",
else:
errorbar = None

if adjust_xlim:
xmin, xmax = self.dataLim.intervalx
xmin = min(w for w in width if w > 0)
if xerr is not None:
xmin = xmin - np.max(xerr)
xmin = max(xmin * 0.9, 1e-100)
self.dataLim.intervalx = (xmin, xmax)

if adjust_ylim:
ymin, ymax = self.dataLim.intervaly
ymin = min(h for h in height if h > 0)
if yerr is not None:
ymin = ymin - np.max(yerr)
ymin = max(ymin * 0.9, 1e-100)
self.dataLim.intervaly = (ymin, ymax)
self._request_autoscale_view()

bar_container = BarContainer(patches, errorbar, label=label)
Expand Down Expand Up @@ -6741,30 +6718,8 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
if log:
if orientation == 'horizontal':
self.set_xscale('log', nonposx='clip')
logbase = self.xaxis._scale.base
else: # orientation == 'vertical'
self.set_yscale('log', nonposy='clip')
logbase = self.yaxis._scale.base

# Setting a minimum of 0 results in problems for log plots
if np.min(bottom) > 0:
minimum = np.min(bottom)
elif density or weights is not None:
# For data that is normed to form a probability density,
# set to minimum data value / logbase
# (gives 1 full tick-label unit for the lowest filled bin)
ndata = np.array(tops)
minimum = (np.min(ndata[ndata > 0])) / logbase
else:
# For non-normed (density = False) data,
# set the min to 1 / log base,
# again so that there is 1 full tick-label unit
# for the lowest bin
minimum = 1.0 / logbase

y[0], y[-1] = minimum, minimum
else:
minimum = 0

if align == 'left':
x -= 0.5*(bins[1]-bins[0])
Expand All @@ -6785,8 +6740,6 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
# set the top of this polygon
y[1:2*len(bins)-1:2], y[2:2*len(bins):2] = (m + bottom,
m + bottom)
if log:
y[y < minimum] = minimum
if orientation == 'horizontal':
xvals.append(y.copy())
yvals.append(x.copy())
Expand All @@ -6809,9 +6762,9 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
for patch_list in patches:
for patch in patch_list:
if orientation == 'vertical':
patch.sticky_edges.y.append(minimum)
patch.sticky_edges.y.append(0)
elif orientation == 'horizontal':
patch.sticky_edges.x.append(minimum)
patch.sticky_edges.x.append(0)

# we return patches, so put it back in the expected order
patches.reverse()
Expand Down
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