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Fix #6448: set xmin/ymin even without non-zero bins in 'step' hist #7323

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Merged
merged 1 commit into from
Oct 22, 2016
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Fix #6448: set xmin/ymin even without non-zero bins in 'step' hist #7323

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18 changes: 13 additions & 5 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6390,7 +6390,7 @@ def _normalize_input(inp, ename='input'):
xvals.append(x.copy())
yvals.append(y.copy())

#stepfill is closed, step is not
# stepfill is closed, step is not
split = -1 if fill else 2 * len(bins)
# add patches in reverse order so that when stacking,
# items lower in the stack are plottted on top of
Expand All @@ -6412,9 +6412,13 @@ def _normalize_input(inp, ename='input'):
xmin0 = max(_saved_bounds[0]*0.9, minimum)
xmax = self.dataLim.intervalx[1]
for m in n:
if np.sum(m) > 0: # make sure there are counts
xmin = np.amin(m[m != 0])
# make sure there are counts
if np.sum(m) > 0:
# filter out the 0 height bins
xmin = np.amin(m[m != 0])
# If no counts, set min to zero
else:
xmin = 0.0
xmin = max(xmin*0.9, minimum) if not input_empty else minimum
xmin = min(xmin0, xmin)
self.dataLim.intervalx = (xmin, xmax)
Expand All @@ -6423,9 +6427,13 @@ def _normalize_input(inp, ename='input'):
ymax = self.dataLim.intervaly[1]

for m in n:
if np.sum(m) > 0: # make sure there are counts
ymin = np.amin(m[m != 0])
# make sure there are counts
if np.sum(m) > 0:
# filter out the 0 height bins
ymin = np.amin(m[m != 0])
# If no counts, set min to zero
else:
ymin = 0.0
ymin = max(ymin*0.9, minimum) if not input_empty else minimum
ymin = min(ymin0, ymin)
self.dataLim.intervaly = (ymin, ymax)
Expand Down