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Fix ValueError being raised when plotting hist and hexbin on empty dataset (Fix #3886) #4119

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Merged
merged 7 commits into from
Mar 30, 2015
Merged

Fix ValueError being raised when plotting hist and hexbin on empty dataset (Fix #3886) #4119

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e864d94
Fix hexbin raising ValueError on empty dataset
Feb 17, 2015
287a815
Fix hist raising ValueError on empty dataset
Feb 17, 2015
6deba68
Add explanation for test_hist_empty
Feb 17, 2015
74a4266
Fix test_hist_empty and test_hexbin_empty test cases. Improve docstri…
Feb 18, 2015
a567658
Fix hist to return correct patches on empty input. Add test for hist …
Feb 18, 2015
2bf9777
Fix width and weights for hist on empty input. Update tests for empty…
Mar 14, 2015
22c6c7f
Fix hexbin to use len instead of any. Fix hist to pass in bin_range a…
Mar 19, 2015
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Fix hist to return correct patches on empty input. Add test for hist … 
…step on empty input.
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Umair Idris committed Mar 17, 2015
commit a567658a790cb5b9d5e310b9bcc766ecaf98ed37
27 changes: 18 additions & 9 deletions 27 lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5394,7 +5394,7 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
Compute and draw the histogram of *x*. The return value is a
tuple (*n*, *bins*, *patches*) or ([*n0*, *n1*, ...], *bins*,
[*patches0*, *patches1*,...]) if the input contains multiple
data or ([], [], []) if input is an empty array.
data.

Multiple data can be provided via *x* as a list of datasets
of potentially different length ([*x0*, *x1*, ...]), or as
Expand Down Expand Up @@ -5605,12 +5605,14 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,

# basic input validation
flat = np.ravel(x)
if len(flat) == 0:
return [], [], cbook.silent_list('No Patches')

input_empty = len(flat) == 0

# 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]):
if input_empty:
x = np.asarray([[]])
elif isinstance(x, np.ndarray) or not iterable(x[0]):
# TODO: support masked arrays;
x = np.asarray(x)
if x.ndim == 2:
Expand Down Expand Up @@ -5677,7 +5679,7 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
#hist_kwargs = dict(range=range, normed=bool(normed))
# We will handle the normed kwarg within mpl until we
# get to the point of requiring numpy >= 1.5.
hist_kwargs = dict(range=bin_range)
hist_kwargs = dict(range=bin_range) if not input_empty else dict()
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Why is this change needed?

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The bin_range was (np.inf, -np.inf) when binsgiven was false due to the block above this line; I have changed that block to not be entered if input is empty and reverted this change via 22c6c7f.

Thanks!


n = []
mlast = None
Expand Down Expand Up @@ -5760,6 +5762,8 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
for m, c in zip(n, color):
if bottom is None:
bottom = np.zeros(len(m), np.float)
if input_empty:
width = 0
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Do we need this?

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As per @efiring 's comment: "I think we should follow that logic, which implies that we should be drawing zero-height (or width) patches."

Without setting width to 0, the patches for bar have size 0.1 and thus an empty graph (as desired) is not drawn.

Before (width 0.1, non empty graph):
bar_width_nonzero

After (width 0, empty graph):
bar_width_zero

However, currently the code still calculates the original width of 0.1 and then overwrites it, I will send a commit which moves it into a more appropriate place (where width, dw and boffset are originally calculated) in a future commit if this is the desired result.

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Done via 40cf945

if stacked:
height = m - bottom
else:
Expand Down Expand Up @@ -5842,6 +5846,8 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
xvals.append(x.copy())
yvals.append(y.copy())

fill_kwargs = dict() if not input_empty else dict(linewidth=0)
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Again. do we need this?

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As above, it draws one patch with linewidth 1 if it is not manually set to 0 and thus is not an empty graph.

Before (linewidth 1, non empty graph):
step_linewidth_nonzero

After (linewidth 0, empty graph):
step_linewidth_zero

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Again. I think showing the line is the correct thing to do. My main motivation is that if some one now wants to update the histogram artists, this will cause a great deal of trouble.

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Just making sure, is autoscaling in the x still working even with
zero-height elements on the edges?

On Fri, Mar 13, 2015 at 7:31 PM, Thomas A Caswell notifications@github.com
wrote:

In lib/matplotlib/axes/_axes.py
#4119 (comment):

@@ -5843,6 +5846,8 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
xvals.append(x.copy())
yvals.append(y.copy())

  •        fill_kwargs = dict() if not input_empty else dict(linewidth=0)

Again. I think showing the line is the correct thing to do. My main
motivation is that if some one now wants to update the histogram artists,
this will cause a great deal of trouble.

—
Reply to this email directly or view it on GitHub
https://github.com/matplotlib/matplotlib/pull/4119/files#r26430425.

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Done via 40cf945


if fill:
# add patches in reverse order so that when stacking,
# items lower in the stack are plottted on top of
Expand All @@ -5850,14 +5856,16 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
patches.append(self.fill(
x, y,
closed=True,
facecolor=c))
facecolor=c,
**fill_kwargs))
else:
for x, y, c in reversed(list(zip(xvals, yvals, color))):
split = 2 * len(bins)
patches.append(self.fill(
x[:split], y[:split],
closed=False, edgecolor=c,
fill=False))
fill=False,
**fill_kwargs))

# we return patches, so put it back in the expected order
patches.reverse()
Expand All @@ -5870,17 +5878,18 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
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 = max(xmin*0.9, minimum) if not input_empty else minimum
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This discards the _saved_bounds information. I am not strictly sure that this is the best place to do this, but this bit of code is convoluted enough....

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Yup, never mind my last comment.

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:
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 = max(ymin*0.9, minimum) if not input_empty else minimum
ymin = min(ymin0, ymin)
self.dataLim.intervaly = (ymin, ymax)

Expand Down
31 changes: 29 additions & 2 deletions 31 lib/matplotlib/tests/test_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1007,10 +1007,37 @@ def test_hist_log():
ax.hist(data, fill=False, log=True)

@cleanup
def test_hist_empty():
def test_hist_bar_empty():
# From #3886: creating hist from empty dataset raises ValueError
ax = plt.gca()
ax.hist([])

n, bins, patches = ax.hist([], histtype='bar')

# empty hist should match empty numpy histogram
n1, bins1 = np.histogram([])
assert_array_equal(n, n1)
assert_array_equal(bins, bins1)

# check zero size patches
assert_true(len(patches) == 10)
for patch in patches:
assert_false(patch._height)
assert_false(patch._width)

@cleanup
def test_hist_step_empty():
# From #3886: creating hist from empty dataset raises ValueError
ax = plt.gca()

n, bins, patches = ax.hist([], histtype='step')

# empty hist should match empty numpy histogram
n1, bins1 = np.histogram([])
assert_array_equal(n, n1)
assert_array_equal(bins, bins1)

# check zero size patches
assert_true(len(patches) == 1 and not patches[0]._linewidth)

@image_comparison(baseline_images=['hist_steplog'], remove_text=True)
def test_hist_steplog():
Expand Down
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