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Replace 'normed' kwarg to hist by 'density' in tests and docs. #10258

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Replace 'normed' kwarg to hist by 'density' in tests and docs. #10258

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2 changes: 1 addition & 1 deletion examples/statistics/hist.py
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Expand Up @@ -63,7 +63,7 @@
thispatch.set_facecolor(color)

# We can also normalize our inputs by the total number of counts
axs[1].hist(x, bins=n_bins, normed=True)
axs[1].hist(x, bins=n_bins, density=True)

# Now we format the y-axis to display percentage
axs[1].yaxis.set_major_formatter(PercentFormatter(xmax=1))
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2 changes: 1 addition & 1 deletion examples/statistics/histogram_features.py
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Expand Up @@ -35,7 +35,7 @@
fig, ax = plt.subplots()

# the histogram of the data
n, bins, patches = ax.hist(x, num_bins, normed=1)
n, bins, patches = ax.hist(x, num_bins, density=True)

# add a 'best fit' line
y = mlab.normpdf(bins, mu, sigma)
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2 changes: 1 addition & 1 deletion lib/matplotlib/tests/test_axes.py
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Expand Up @@ -2932,7 +2932,7 @@ def test_hist_stacked_normed():
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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I think this should stay as it is, because we should still be testing that normed works until it is removed.

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In that case, shouldn't the test have two forms, one for 'normed' and the other for 'density'? At a more general level, we never have tested everything, and never will--there are too many possible combinations. We need to concentrate on the most useful tests, putting our resources, and those of the CI services, where they will be most effective in improving mpl. Testing that a deprecated kwarg still works seems very low priority, doesn't it? The time of deprecation seems like a perfectly reasonable time to switch a test to the non-deprecated alternative.

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  • There is a test directly below this one for density.
  • Sure we've never tested everything, but we should aim to test everything. This test definitely isn't a CI bottleneck.
  • In my opinion, something being deprecated means it is still supported, but there are plans for it to be removed. If it's supported, it should be tested.

I'm not going to block on removing the normed test, but I am -2 on it.

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Aiming to test everything doesn't make sense to me, for the reason stated above.

ax.hist((d1, d2), stacked=True, density=True)


@image_comparison(baseline_images=['hist_stacked_normed'], extensions=['png'])
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3 changes: 1 addition & 2 deletions tutorials/introductory/pyplot.py
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Expand Up @@ -333,8 +333,7 @@ def f(t):
x = mu + sigma * np.random.randn(10000)

# the histogram of the data
n, bins, patches = plt.hist(x, 50, normed=1, facecolor='g', alpha=0.75)

n, bins, patches = plt.hist(x, 50, density=True, facecolor='g', alpha=0.75)

plt.xlabel('Smarts')
plt.ylabel('Probability')
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