8000 MEP12: Example clean-up for reference by tonysyu · Pull Request #2474 · matplotlib/matplotlib · GitHub
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MEP12: Example clean-up for reference #2474

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Merged
merged 21 commits into from
Jan 14, 2014
Merged

MEP12: Example clean-up for reference #2474

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8bec412
Remove she-bang line.
tonysyu Sep 29, 2013
c25ef1e
Use consistent imports
tonysyu Sep 29, 2013
7a59f9f
Remove unnecessary code comments.
tonysyu Sep 29, 2013
83dd0ea
Remove unnecessary calls to `show`
tonysyu Sep 29, 2013
ece3c57
Rmove unused variable
tonysyu Sep 29, 2013
5099675
Split up hist examples into two sections.
tonysyu Sep 29, 2013
768500d
Remove use of `setp` in favor of keyword args.
tonysyu Sep 29, 2013
44a577b
Replace multiple figures with subplots
tonysyu Sep 29, 2013
c80897d
Change bin edges to make the example clearer.
tonysyu Sep 29, 2013
bd2b13c
Add titles to clarify intent
tonysyu Sep 29, 2013
24aab97
Simplify example
tonysyu Sep 29, 2013
fc2ab07
Split demo that tried to do too much
tonysyu Sep 29, 2013
e57b5fc
Remove unnecessary second histogram
tonysyu Sep 29, 2013
1458aa8
Remove unnecessary parameters
tonysyu Sep 29, 2013
c3cce1c
PEP8 fixes
tonysyu Sep 29, 2013
6d1b8a2
Add example docstrings
tonysyu Sep 29, 2013
f7b2217
Simplify example.
tonysyu Sep 29, 2013
a2b5dcd
Clarify title of plot
tonysyu Sep 29, 2013
e62e51e
Move histogram examples to statistics directory
tonysyu Sep 29, 2013
2dc9a46
Fix example links.
tonysyu Sep 29, 2013
ef51dc3
Shorten color names for better gallery build
tonysyu Sep 29, 2013
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Remove unnecessary second histogram
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@tonysyu
tonysyu committed Sep 29, 2013
commit e57b5fc31fbad83ed9c43c77ef15368efdcb9ec1
11 changes: 0 additions & 11 deletions examples/pylab_examples/histogram_demo_cumulative.py
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Expand Up @@ -11,17 +11,6 @@
y /= y[-1]
plt.plot(bins, y, 'k--', linewidth=1.5)

# Create a second data-set with a smaller standard deviation.
sigma2 = 15.
x = mu + sigma2*np.random.randn(10000)

n, bins, patches = plt.hist(x, bins=bins, normed=1, histtype='step', cumulative=True)

# Add a line showing the expected distribution.
y = mlab.normpdf( bins, mu, sigma2).cumsum()
y /= y[-1]
plt.plot(bins, y, 'r--', linewidth=1.5)

# Overlay a reverted cumulative histogram.
n, bins, patches = plt.hist(x, bins=bins, normed=1,
histtype='step', cumulative=-1)
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