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Histograms with stacked=True, normed=True now normalize sum of histog…
…rams rather than each histogram individually.
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neggert committed May 8, 2013
commit 6917f4fab3916e30bf83adcd2925c907d44747c0
10 changes: 8 additions & 2 deletions lib/matplotlib/axes.py
Original file line number Diff line number Diff line change
Expand Up @@ -8088,7 +8088,8 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
If `True`, the first element of the return tuple will
be the counts normalized to form a probability density, i.e.,
``n/(len(x)`dbin)``, ie the integral of the histogram will sum to
1.
1. If *stacked* is also *True*, the sum of the histograms is
normalized to 1.

weights : array_like, shape (n, ), optional, default: None
An array of weights, of the same shape as `x`. Each value in `x`
Expand Down Expand Up @@ -8300,16 +8301,21 @@ def hist(self, x, bins=10, range=None, normed=False, weights=None,
# this will automatically overwrite bins,
# so that each histogram uses the same bins
m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
m = m.astype(float) # causes problems later if it's an int
if mlast is None:
mlast = np.zeros(len(bins)-1, m.dtype)
if normed:
if normed and not stacked:
db = np.diff(bins)
m = (m.astype(float) / db) / m.sum()
if stacked:
m += mlast
mlast[:] = m
n.append(m)

if stacked and normed:
db = np.diff(bins)
for m in n:
m[:] = (m.astype(float) / db) / n[-1].sum()
if cumulative:
slc = slice(None)
if cbook.is_numlike(cumulative) and cumulative < 0:
Expand Down
9 changes: 9 additions & 0 deletions lib/matplotlib/tests/test_axes.py
Original file line number Diff line number Diff line change
Expand Up @@ -1072,6 +1072,15 @@ def test_hist_stacked_step():
ax = fig.add_subplot(111)
ax.hist( (d1, d2), histtype="step", stacked=True)

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PEP8 : can you add another blank line before and after the new test? There should be two blank lines between functions.

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Nelle,

I fixed this instance, but that mistake occurs for almost every test in that file.

@image_comparison(baseline_images=['hist_stacked_normed'])
def test_hist_stacked_normed():
# make some data
d1 = np.linspace(1, 3, 20)
d2 = np.linspace(0, 10, 50)
fig = plt.figure()
ax = fig.add_subplot(111)
ax.hist( (d1, d2), stacked=True, normed=True)
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PEP8 : there should be no space inbetween the two parenthesis.


@image_comparison(baseline_images=['hist_stacked_bar'])
def test_hist_stacked_bar():
# make some data
Expand Down