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Fix behavior of hist function when passed empty dataset #2551

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Merged
merged 4 commits into from
Jan 13, 2014
Merged

Fix behavior of hist function when passed empty dataset #2551

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5a2c9af
Allow empty datasets to be passed to hist, as long as at least one da…
neggert Oct 27, 2013
2786e39
Fixed another location where empty datasets in hist caused exceptions
neggert Oct 28, 2013
03a960d
Add test for histogram with empty dataset
neggert Jan 6, 2014
7a5ec9f
Add cleanup to test
Jan 10, 2014
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26 changes: 18 additions & 8 deletions lib/matplotlib/axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8245,6 +8245,17 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
if histtype == 'barstacked' and not stacked:
stacked = True

# Check whether bins or range are given explicitly.
binsgiven = (cbook.iterable(bins) or bin_range is not None)

# basic input validation
flat = np.ravel(x)
if len(flat) == 0:
raise ValueError("x must have at least one data point")
elif len(flat) == 1 and not binsgiven:
raise ValueError(
"x has only one data point. bins or range kwarg must be given")

# Massage 'x' for processing.
# NOTE: Be sure any changes here is also done below to 'weights'
if isinstance(x, np.ndarray) or not iterable(x[0]):
Expand Down Expand Up @@ -8299,19 +8310,16 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
# Save the datalimits for the same reason:
_saved_bounds = self.dataLim.bounds

# Check whether bins or range are given explicitly. In that
# case use those values for autoscaling.
binsgiven = (cbook.iterable(bins) or bin_range is not None)

# If bins are not specified either explicitly or via range,
# we need to figure out the range required for all datasets,
# and supply that to np.histogram.
if not binsgiven:
xmin = np.inf
xmax = -np.inf
for xi in x:
xmin = min(xmin, xi.min())
xmax = max(xmax, xi.max())
if len(xi) > 0:
xmin = min(xmin, xi.min())
xmax = max(xmax, xi.max())
bin_range = (xmin, xmax)

#hist_kwargs = dict(range=range, normed=bool(normed))
Expand Down Expand Up @@ -8503,15 +8511,17 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
xmin0 = max(_saved_bounds[0]*0.9, minimum)
xmax = self.dataLim.intervalx[1]
for m in n:
xmin = np.amin(m[m != 0]) # filter out the 0 height bins
if np.sum(m) > 0: # make sure there are counts
xmin = np.amin(m[m != 0]) # filter out the 0 height bins
xmin = max(xmin*0.9, minimum)
xmin = min(xmin0, xmin)
self.dataLim.intervalx = (xmin, xmax)
elif orientation == 'vertical':
ymin0 = max(_saved_bounds[1]*0.9, minimum)
ymax = self.dataLim.intervaly[1]
for m in n:
ymin = np.amin(m[m != 0]) # filter out the 0 height bins
if np.sum(m) > 0: # make sure there are counts
ymin = np.amin(m[m != 0]) # filter out the 0 height bins
ymin = max(ymin*0.9, minimum)
ymin = min(ymin0, ymin)
self.dataLim.intervaly = (ymin, ymax)
Expand Down
6 changes: 6 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -1162,6 +1162,12 @@ def test_hist_stacked_bar():
ax.hist(d, bins=10, histtype='barstacked', align='mid', color=colors, label=labels)
ax.legend(loc='upper right', bbox_to_anchor = (1.0, 1.0), ncol=1)

@cleanup
def test_hist_emptydata():
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This should be "clearup"-ed.

fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist([[], range(10), range(10)], histtype="step")

@image_comparison(baseline_images=['transparent_markers'], remove_text=True)
def test_transparent_markers():
np.random.seed(0)
Expand Down