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Impaler343Impaler343
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Resolved edgecolor and facecolor setting
Minor fix Fix docs
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‎doc/users/next_whats_new/histogram_vectorized_parameters.rst

Lines changed: 18 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -1,13 +1,20 @@
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Vectorize ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` in *hist* methods
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---------------------------------------------------------------------------------------
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-------------------------------------------------------------------------------------
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The parameters ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` of the `~matplotlib.axes.Axes.hist` method are now vectorized.
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This means that you can pass in unique parameters for each histogram that is generated when the input *x* has multiple datasets.
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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.
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The parameters ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` of the
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`~matplotlib.axes.Axes.hist` method are now vectorized.
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This means that you can pass in unique parameters for each histogram that is generated
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when the input *x* has multiple datasets.
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Note that the ``facecolor`` parameter is not vectorized, but the required behavior can
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be achieved by passing a list of colors to the ``color`` parameter.
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.. plot::
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:include-source: true
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:alt: Three charts, identified as ax1, ax2 and ax3, show a stacking of three histograms representing Poisson distributions. 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.
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:alt: Three charts, identified as ax1, ax2 and ax3, show a stacking of three
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histograms representing Poisson distributions. The histograms in ax1, ax2,
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and ax3 are differentiated by linewidths, hatches and linestyles,
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respectively. In ax1, ax2 and ax3, each histogram is bordered by a different
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color.
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import matplotlib.pyplot as plt
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import numpy as np
@@ -21,15 +28,18 @@ Note that the ``facecolor`` parameter is not vectorized, but the required behavi
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labels = ["Data 1", "Data 2", "Data 3"]
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ax1.hist([data1, data2, data3], bins=range(17), histtype="barstacked", edgecolor=["red", "green", "blue"], linewidth=[1, 1.5, 2])
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ax1.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
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edgecolor=["red", "green", "blue"], linewidth=[1, 1.5, 2])
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ax1.set_title("Different linewidths")
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ax1.legend(labels, prop={"size": 8})
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ax2.hist([data1, data2, data3], bins=range(17), histtype="barstacked", edgecolor=["red", "green", "blue"], hatch=["/", ".", "*"])
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ax2.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
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edgecolor=["red", "green", "blue"], hatch=["/", ".", "*"])
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ax2.set_title("Different hatch patterns")
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ax2.legend(labels, prop={"size": 8})
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ax3.hist([data1, data2, data3], bins=range(17), histtype="barstacked", edgecolor=["red", "green", "blue"], linestyle=["--", "-.", ":"])
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ax3.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
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edgecolor=["red", "green", "blue"], linestyle=["--", "-.", ":"])
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ax3.set_title("Different linestyles")
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ax3.legend(labels, prop={"size": 8})
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‎galleries/examples/statistics/histogram_multihist.py

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Original file line numberDiff line numberDiff line change
@@ -74,7 +74,7 @@
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plt.show()
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# %%
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# Histograms with Hatches
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# .......................
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@@ -88,7 +88,7 @@
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plt.show()
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# %%
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# Histograms with Linewidths
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# ..........................
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@@ -106,9 +106,9 @@
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plt.show()
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# %%
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# Histograms with LineStyles
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# ...........................
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# ..........................
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fig, ax = plt.subplots()
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‎lib/matplotlib/axes/_axes.py

Lines changed: 15 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -6938,8 +6938,8 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
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**kwargs
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`~matplotlib.patches.Patch` properties. The following properties
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additionally accepts a sequence of properties values corresponding
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to the datasets in *x*:
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additionally accept a sequence of values corresponding to the
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datasets in *x*:
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*edgecolors*, *linewidths*, *linestyles*, *hatches*.
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See Also
@@ -7215,19 +7215,29 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
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labels = [] if label is None else np.atleast_1d(np.asarray(label, str))
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hatches = itertools.cycle(np.atleast_1d(kwargs.get('hatch', None)))
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edgecolors = itertools.cycle(np.atleast_1d(kwargs.get('edgecolor', None)))
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if histtype.startswith('bar') or histtype == 'stepfilled':
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edgecolors = itertools.cycle(np.atleast_1d(kwargs.get('edgecolor', None)))
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else:
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edgecolors = itertools.cycle(np.atleast_1d(kwargs.get('edgecolor',
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colors)))
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if histtype.startswith('bar'):
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facecolors = itertools.cycle(np.atleast_1d(kwargs.get('facecolor',
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colors)))
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else:
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facecolors = itertools.cycle(np.atleast_1d(kwargs.get('facecolor',
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colors)))
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linewidths = itertools.cycle(np.atleast_1d(kwargs.get('linewidth', None)))
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linestyles = itertools.cycle(np.atleast_1d(kwargs.get('linestyle', None)))
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for patch, lbl in itertools.zip_longest(patches, labels):
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if patch:
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p = patch[0]
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if 'edgecolor' in kwargs:
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kwargs['edgecolor'] = next(edgecolors)
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kwargs.update({
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'hatch': next(hatches),
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'linewidth': next(linewidths),
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'linestyle': next(linestyles),
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'edgecolor': next(edgecolors),
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'facecolor': next(facecolors),
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})
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p._internal_update(kwargs)
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if lbl is not None:

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