Remove old normalising code from plt.hist #9121
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| for i in xrange(nx): | ||
| # 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 density and not stacked: |
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This is the old normalising code
| if stacked: | ||
| if mlast is None: |
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This if statement is never used due to the same statement on line 6097
lib/matplotlib/tests/test_axes.py
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| @@ -1464,6 +1464,14 @@ def test_hist_step_filled(): | |||
| assert all([p.get_facecolor() == p.get_edgecolor() for p in patches]) | |||
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| @image_comparison(baseline_images=['hist_density'], extensions=['png']) | |||
| def test_hist_density(): | |||
| np.random.seed(0) | |||
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Can you use 19680801 (JDH's birthday) as the seed?
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| np.random.seed(19680801) | ||
| data = np.random.standard_normal(2000) | ||
| fig, ax = plt.subplots() | ||
| ax.hist(data, density=True) |
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Does this actually need an image test, or can we just test that np.histogram properly applies the density kwarg?
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I don't think there was ever any image test that used the 'density' or 'norm' kwargs, so I thought it would be a good idea to add one.
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I think we are trying to keep image tests to things where the actual image appearance might change if code changes. So sure if there is no hist image test there should be one. If such a test does exist then this just tests the value of the bars, and I think you can do that w/o an image comparison. But I’m not passionate about it or anything.
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Beating a dead horse, but:
np.random.seed(19680801)
data = np.random.standard_normal(2000)
fig, ax = plt.subplots()
n, bins, patches = ax.hist(data, density=True)
assert np.isclose(np.sum(n * np.diff(bins)), 1.0)|
@meeseeksdev backport to v2.1.x |
Backport PR #9121 on branch v2.1.x
This PR does a few things:
ntotopsto make the code more readable