Add support for multiple hatches, edgecolors and linewidths in histograms #28073

Impaler343 · 2024-04-13T17:59:17Z

PR summary

Closes #26718 Distributes keyword args passed to each Patch using a cycler. Probably not the best way to do this?

PR checklist

"closes #0000" is in the body of the PR description to link the related issue
new and changed code is tested
[N/A] Plotting related features are demonstrated in an example
[N/A] New Features and API Changes are noted with a directive and release note
[N/A] Documentation complies with general and docstring guidelines

jklymak · 2024-04-13T19:58:54Z

I'd suggest showing what this does with an example either in the GitHub pr description, or ideally in the gallery

Impaler343 · 2024-04-19T02:59:52Z

I'm not really sure if I need to add a new test or just modify an exisiting one(test_hist_stacked_bar) in test_axes.py

oscargus · 2024-04-25T10:02:27Z

I guess there are two things here:

Add/modify an example in the gallery to illustrate how it is used. (Will be easier for the reviewers to get an idea of how it is used etc.)
Add a test to get the code coverage up and make sure no one breaks it later. Maybe there is some old example that one can "hi-jack", but otherwise create a new test with all the bells and whistles turned on.

Impaler343 · 2024-05-13T05:19:20Z

pinging @story645 for review. The failing tests are unrelated

story645

also needs updated documentation that the patch properties are now vectorized (@timhoffm any concerns here?)

story645 · 2024-05-16T14:33:56Z

lib/matplotlib/axes/_axes.py

+                if 'hatch' in kwargs:
+                    kwargs['hatch'] = next(hatches)
+                if 'edgecolor' in kwargs:
+                    kwargs['edgecolor'] = next(edgecolors)
+                if 'linewidth' in kwargs:
+                    kwargs['linewidth'] = next(linewidths)


Can you use the kwarg names directly instead of this if chain? kinda like how it's implemented in pie

matplotlib/lib/matplotlib/axes/_axes.py

Lines 3339 to 3344 in 80b08bd

w = mpatches.Wedge((x, y), radius, 360. * min(theta1, theta2),

360. * max(theta1, theta2),

facecolor=get_next_color(),

hatch=next(hatch_cycle),

clip_on=False,

label=label)

yep, makes sense

After some deliberation, it doesn't seem like I can remove the if statements for edgecolor. The behavior of the edgecolor attribute is different when it is specified but None, from when it is not specified. Also, to specify kwarg names directly, I need to access the type of the object as it is sometimes BarContainer, sometimes list and sometimes Rectangle. Probably best to handle it via kwargs

Would the complications in edgecolor go away if #28104 was finished?

I don't think so, this isn't related to the hatchcolor, but is related to different fallbacks of the edgecolor to either black or blue. Probably an entirely new issue

Why is it doing those fallbacks?

Ok, so it appears that the edgecolor is being explicitly set to black which is the rcParam of patch.edgecolor, regardless of the edgecolor set previously. The setting of edgecolor is different when the histogram type is bar, step, stepfilled, stacked and becomes hard to handle

lib/matplotlib/axes/_axes.py

galleries/examples/statistics/histogram_multihist.py

timhoffm · 2024-05-19T20:25:31Z

also needs updated documentation that the patch properties are now vectorized (@timhoffm any concerns here?)

What should we be concerned about? We already have vectorized label and color. It's only fair to vectorize these inside hist() as well. This should be documented with **kwargs (can't immediately suggest, because that part has not been touched in the PR). Something like:

        **kwargs
            `~matplotlib.patches.Patch` properties. The following properties additionally
            accept lists of property values, one element for each dataset:
            *edgecolors*, *linewidths*, *linestyles*, *hatches*.

This should also get a what's new entry.

story645 · 2024-05-19T22:32:01Z

What should we be concerned about? We already have vectorized label and color.

My bias is vectorize everything so I don't have concerns, but in the past for some vectorization discussions there have been concerns about the tradeoffs. But if there isn't opposition, awesome!

timhoffm · 2024-05-19T22:47:12Z

I don't see any drawbacks for hist()

Impaler343 · 2024-05-25T19:12:07Z

So we are planning to vectorize all parameters of Patches? Like joinstyle, capstyle etc.

galleries/examples/statistics/histogram_multihist.py

story645 · 2024-05-26T15:09:35Z

So we are planning to vectorize all parameters of Patches? Like joinstyle, capstyle etc

Not at this time w/ the current architecture, especially because nobody has asked for those.

Specify extensions for test Added modified baseline images Modified test for histogram with single parameters Fixed test Add modified baseline images

Fix Docs

Added baseline images

Fix test Added baseline images

Impaler343 · 2024-05-29T08:40:26Z

Codecov is acting fishy, it passed once and failed again after squashing. Anything else to add/change?

story645 · 2024-05-31T18:25:32Z

lib/matplotlib/axes/_axes.py

+                if 'edgecolor' in kwargs:
+                    kwargs['edgecolor'] = next(edgecolors)


sorry, you may have told me before but why does edgecolor need to be special cased here? does edge color behave differently if it's passed in as none vs if it's not set?

story645 · 2024-05-31T18:36:20Z

lib/matplotlib/tests/test_axes.py

+def test_hist_vectorized_params():
+    fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(nrows=2, ncols=2)
+
+    np.random.seed(19680801)
+    x = [np.random.randn(n) for n in [2000, 5000, 10000]]
+
+    ax0.hist(x, bins=10, histtype="barstacked", edgecolor=["red", "black", "blue"],
+                linewidth=[1, 1.2, 1.5], hatch=["/", "\\", "."])
+    ax1.hist(x, bins=10, histtype="barstacked", linewidth=[1, 1.2, 1.5],
+                hatch=["/", "\\", "."], linestyle=["-", "--", ":"])
+    ax2.hist(x, bins=10, histtype="barstacked", edgecolor=["red", "black", "blue"],
+                    hatch=["/", "\\", "."], linestyle=["-", "--", ":"])
+    ax3.hist(x, bins=10, histtype="barstacked", edgecolor=["red", "black", "blue"],
+                linewidth=[1, 1.2, 1.5], linestyle=["-", "--", ":"])
+


So I'm a little unclear what the benefit of having these 4 panels is/what distinct thing each section is testing. Also, since all these images can already be made the long way, this might be better as a test figures equal: https://matplotlib.org/devdocs/devel/testing.html#compare-two-methods-of-creating-an-image

Mostly in terms of being able to isolate what went wrong, but also cause then you can maybe parametrize each keyword/parametrize the tests and use that to better identify what's being tested.

story645 · 2024-05-31T18:49:47Z

lib/matplotlib/axes/_axes.py

@@ -6937,7 +6937,9 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
            DATA_PARAMETER_PLACEHOLDER

        **kwargs
-            `~matplotlib.patches.Patch` properties
+            `~matplotlib.patches.Patch` properties. The following properties
+            additionally accept lists of property values, one element for each dataset:


Suggested change

additionally accept lists of property values, one element for each dataset:

additionally accepts a sequence of properties values corresponding to the datasets in *x*:

changed to sequence b/c that's the language we use through out, removed element b/c element and values are here being used to refer to the same thing

story645 · 2024-05-31T18:54:04Z

doc/users/next_whats_new/histogram_vectorized_parameters.rst

+---------------------------------------------------------------------------------------
+
+The parameters ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` of the `~matplotlib.axes.Axes.hist` method are now vectorized.
+This means that you can pass a list of values to these parameters, and the values will be applied to each dataset in the histogram.


Suggested change

This means that you can pass a list of values to these parameters, and the values will be applied to each dataset in the histogram.

This means that you can pass in unique parameters for each histogram that is generated when the input *x* has multiple datasets.

Not sure if it's a nit, but just trying to be super explicit that these are aesthetic parameters rather than computational.

story645 · 2024-05-31T18:54:43Z

doc/users/next_whats_new/histogram_vectorized_parameters.rst

+Note that the ``facecolor`` parameter is not vectorized, but the required behavior can be achieved by passing a list of colors to the ``color`` parameter.
+


Why can't we parametrize facecolor? Specifically the use case where I want face and edge to be different colors?

story645 · 2024-05-31T19:09:33Z

doc/users/next_whats_new/histogram_vectorized_parameters.rst

+
+.. plot::
+    :include-source: true
+    :alt: Three charts, identified as ax1, ax2 and ax3, include plots of three random datasets. The first, second and third plots have datasets differentiated by linewidths, hatches and linestyles, respectively. Edgecolors are used in all of the plots to accentuate the differences.


Suggested change

:alt: Three charts, identified as ax1, ax2 and ax3, include plots of three random datasets. The first, second and third plots have datasets differentiated by linewidths, hatches and linestyles, respectively. Edgecolors are used in all of the plots to accentuate the differences.

:alt: Three charts, identified as ax1, ax2 and ax3, show a stacking of three histograms. The histograms in ax1, ax2, and ax3 are differentiated by linewidths, hatches and linestyles, respectively. In ax1, ax2, and ax3, each histogram is bordered by a different color.

Since you've named the access, cleaner to just refer to it I think, and may as well be specific about the plot type being shown here.

story645 · 2024-05-31T19:11:16Z

galleries/examples/statistics/histogram_multihist.py

+hatches = ["-", "o", "x"]
+linewidths = [1, 2, 3]
+edgecolors = ["green", "red", "blue"]
+linestyles = ["-", ":", "--"]
+


I don't like this separated from where it's used in this exact case where you're trying to teach usage.

story645 · 2024-05-31T19:11:27Z

galleries/examples/statistics/histogram_multihist.py

+# Also, these parameters can be specified for all types of
+# histograms (stacked, step, etc.) and not just for the *bar*
+# type histogram as shown in the example.


you can just show this I think

story645 · 2024-05-31T19:11:47Z

galleries/examples/statistics/histogram_multihist.py

+    x, n_bins, density=True, fill=False, histtype="bar",
+    edgecolor=edgecolors, label=edgecolors
+)
+ax0.legend(prop={"size": 10})


any reason for setting the legend prop size?

story645 · 2024-05-31T19:12:25Z

galleries/examples/statistics/histogram_multihist.py

+# Plotting a bar chart with sample sets differentiated using:
+#
+# * edgecolors
+# * hatches
+# * linewidths
+# * linestyles


So especially in this case where I don't think things need to be interconnected, I think this may work better as subsections.

github-actions bot added the Documentation: examples files in galleries/examples label Apr 14, 2024

Impaler343 force-pushed the histogram branch from 229bfdb to 38fb47d Compare May 8, 2024 10:11

story645 added the New feature label May 16, 2024

story645 reviewed May 16, 2024

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Impaler343 force-pushed the histogram branch from ce563fd to 7d07fe2 Compare May 19, 2024 04:39

rcomer reviewed May 25, 2024

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galleries/examples/statistics/histogram_multihist.py Outdated Show resolved Hide resolved

Impaler343 added 2 commits May 28, 2024 12:38

Add support for multiple hatches, edgecolor and linewidth in histograms

49cbec6

Add hatch, linewidth and edgecolor parameters to multihist example

7d32ed0

Impaler343 force-pushed the histogram branch from 7aaf770 to dfceb33 Compare May 28, 2024 07:11

Impaler343 added 6 commits May 29, 2024 13:01

Add test for added parameters

fd45352

Specify extensions for test Added modified baseline images Modified test for histogram with single parameters Fixed test Add modified baseline images

Made changes concise according to suggestion

bdfc2e7

Made a more detailed gallery example

0f93187

Fix Docs

Added whats new note, documentation for vectorization, doc fix

0fa897a

Added new test, and reverted changes in old test

bd0ce7c

Added baseline images

Modified test to pass codecov, added plot in whats new entry

2351cbd

Fix test Added baseline images

Impaler343 force-pushed the histogram branch from 150c63b to 2351cbd Compare May 29, 2024 07:34

story645 reviewed May 31, 2024

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Add support for multiple hatches, edgecolors and linewidths in histograms #28073

Add support for multiple hatches, edgecolors and linewidths in histograms #28073

Impaler343 commented Apr 13, 2024 •

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jklymak commented Apr 13, 2024

Impaler343 commented Apr 19, 2024

oscargus commented Apr 25, 2024

Impaler343 commented May 13, 2024

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	w = mpatches.Wedge((x, y), radius, 360. * min(theta1, theta2),
	360. * max(theta1, theta2),
	facecolor=get_next_color(),
	hatch=next(hatch_cycle),
	clip_on=False,
	label=label)

		if 'edgecolor' in kwargs:
		kwargs['edgecolor'] = next(edgecolors)

	additionally accept lists of property values, one element for each dataset:
	additionally accepts a sequence of properties values corresponding to the datasets in x:

	This means that you can pass a list of values to these parameters, and the values will be applied to each dataset in the histogram.
	This means that you can pass in unique parameters for each histogram that is generated when the input x has multiple datasets.

		Note that the ``facecolor`` parameter is not vectorized, but the required behavior can be achieved by passing a list of colors to the ``color`` parameter.

	:alt: Three charts, identified as ax1, ax2 and ax3, include plots of three random datasets. The first, second and third plots have datasets differentiated by linewidths, hatches and linestyles, respectively. Edgecolors are used in all of the plots to accentuate the differences.
	:alt: Three charts, identified as ax1, ax2 and ax3, show a stacking of three histograms. The histograms in ax1, ax2, and ax3 are differentiated by linewidths, hatches and linestyles, respectively. In ax1, ax2, and ax3, each histogram is bordered by a different color.

Add support for multiple hatches, edgecolors and linewidths in histograms #28073

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Add support for multiple hatches, edgecolors and linewidths in histograms #28073

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Impaler343 commented Apr 13, 2024 • edited

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Impaler343 commented Apr 13, 2024 •

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Impaler343 May 19, 2024 •

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timhoffm commented May 19, 2024 •

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