Modified files to include facecolor and added test

Impaler343 · Impaler343 · commit 36e8a647d579 · 2024-06-07T01:49:58.000+05:30
diff --git a/doc/users/next_whats_new/histogram_vectorized_parameters.rst b/doc/users/next_whats_new/histogram_vectorized_parameters.rst
@@ -1,46 +1,50 @@
-Vectorize ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` in *hist* methods
--------------------------------------------------------------------------------------
+Vectorize ``hatch``, ``edgecolor``, ``facecolor``, ``linewidth`` and ``linestyle`` in *hist* methods
+----------------------------------------------------------------------------------------------------
 
-The parameters ``hatch``, ``edgecolor``, ``linewidth`` and ``linestyle`` of the
-`~matplotlib.axes.Axes.hist` method are now vectorized.
+The parameters ``hatch``, ``edgecolor``, ``facecolor``, ``linewidth`` and ``linestyle``
+of the `~matplotlib.axes.Axes.hist` method are now vectorized.
 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.
+
 
 .. plot::
     :include-source: true
-    :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.
+    :alt: Four charts, each displaying stacked histograms of three Poisson
+          distributions. Each chart differentiates the histograms using various
+          parameters: ax1 uses different linewidths, ax2 uses different hatches, ax3
+          uses different edgecolors, and ax4 uses different facecolors. Edgecolors have
+          ax1 and ax3 as well to accentuate the differences between the histograms.
+
+   import matplotlib.pyplot as plt
+   import numpy as np
+   np.random.seed(19680801)
 
-    import matplotlib.pyplot as plt
-    import numpy as np
-    np.random.seed(19680801)
+   fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(9, 9))
 
-    fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(10,5))
+   data1 = np.random.poisson(5, 1000)
+   data2 = np.random.poisson(7, 1000)
+   data3 = np.random.poisson(10, 1000)
 
-    data1 = np.random.poisson(5, 1000)
-    data2 = np.random.poisson(7, 1000)
-    data3 = np.random.poisson(10, 1000)
+   labels = ["Data 1", "Data 2", "Data 3"]
 
-    labels = ["Data 1", "Data 2", "Data 3"]
+   ax1.hist([data1, data2, data3], bins=range(17), histtype="step", stacked=True,
+            edgecolor=["red", "green", "blue"], linewidth=[1, 2, 3])
+   ax1.set_title("Different linewidths")
+   ax1.legend(labels)
 
-    ax1.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
-             edgecolor=["red", "green", "blue"], linewidth=[1, 1.5, 2])
-    ax1.set_title("Different linewidths")
-    ax1.legend(labels, prop={"size": 8})
+   ax2.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
+            hatch=["/", ".", "*"])
+   ax2.set_title("Different hatch patterns")
+   ax2.legend(labels)
 
-    ax2.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
-             edgecolor=["red", "green", "blue"], hatch=["/", ".", "*"])
-    ax2.set_title("Different hatch patterns")
-    ax2.legend(labels, prop={"size": 8})
+   ax3.hist([data1, data2, data3], bins=range(17), histtype="bar", fill=False,
+            edgecolor=["red", "green", "blue"], linestyle=["--", "-.", ":"])
+   ax3.set_title("Different linestyles")
+   ax3.legend(labels)
 
-    ax3.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
-             edgecolor=["red", "green", "blue"], linestyle=["--", "-.", ":"])
-    ax3.set_title("Different linestyles")
-    ax3.legend(labels, prop={"size": 8})
+   ax4.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
+            facecolor=["red", "green", "blue"])
+   ax4.set_title("Different facecolors")
+   ax4.legend(labels)
 
-    plt.show()
+   plt.show()
diff --git a/galleries/examples/statistics/histogram_multihist.py b/galleries/examples/statistics/histogram_multihist.py
@@ -53,6 +53,7 @@
 # Plotting bar charts with datasets differentiated using:
 #
 # * edgecolors
+# * facecolors
 # * hatches
 # * linewidths
 # * linestyles
@@ -74,6 +75,20 @@
 
 plt.show()
 
+# %%
+# Histograms with Face-Colors
+# ...........................
+
+fig, ax = plt.subplots()
+
+facecolors = ['green', 'red', 'blue']
+
+ax.hist(x, n_bins, histtype="barstacked", facecolor=facecolors, label=facecolors)
+ax.legend()
+ax.set_title("Bars with different Facecolors")
+
+plt.show()
+
 # %%
 # Histograms with Hatches
 # .......................
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -7214,18 +7214,13 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
         # cast each element to str, but keep a single str as it.
         labels = [] if label is None else np.atleast_1d(np.asarray(label, str))
 
-        hatches = itertools.cycle(np.atleast_1d(kwargs.get('hatch', None)))
         if histtype.startswith('bar') or histtype == 'stepfilled':
             edgecolors = itertools.cycle(np.atleast_1d(kwargs.get('edgecolor', None)))
         else:
             edgecolors = itertools.cycle(np.atleast_1d(kwargs.get('edgecolor',
                                                                   colors)))
-        if histtype.startswith('bar'):
-            facecolors = itertools.cycle(np.atleast_1d(kwargs.get('facecolor',
-                                                                  colors)))
-        else:
-            facecolors = itertools.cycle(np.atleast_1d(kwargs.get('facecolor',
-                                                                  colors)))
+        facecolors = itertools.cycle(np.atleast_1d(kwargs.get('facecolor', colors)))
+        hatches = itertools.cycle(np.atleast_1d(kwargs.get('hatch', None)))
         linewidths = itertools.cycle(np.atleast_1d(kwargs.get('linewidth', None)))
         linestyles = itertools.cycle(np.atleast_1d(kwargs.get('linestyle', None)))
 
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -4603,22 +4603,27 @@ def test_hist_stacked_bar():
     ax.legend(loc='upper right', bbox_to_anchor=(1.0, 1.0), ncols=1)
 
 
-@image_comparison(['hist_vectorized_params'], extensions=["png", "pdf", "svg"],
-                  remove_text=True)
-def test_hist_vectorized_params():
-    fig, ((ax0, ax1), (ax2, ax3)) = plt.subplots(nrows=2, ncols=2)
+@pytest.mark.parametrize('histtype, fill', [('bar', False), ('bar', True),
+                                            ('step', False), ('step', True)])
+@image_comparison(['hist_vectorized_params'], extensions=["png"], remove_text=True)
+def test_hist_vectorized_params(histtype, fill):
+    fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots(1, 5, figsize=(18, 5))
 
     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=["-", "--", ":"])
+    # Only linestyle
+    ax1.hist(x, bins=10, histtype=histtype, fill=fill, linestyle=["-", "--", ":"])
+    # Only edgecolor
+    ax2.hist(x, bins=10, histtype=histtype, fill=fill,
+             edgecolor=["red", "black", "blue"])
+    # Only facecolor
+    ax3.hist(x, bins=10, histtype=histtype, fill=fill,
+             facecolor=["blue", "yellow", "brown"])
+    # Only linewidth
+    ax4.hist(x, bins=10, histtype=histtype, fill=fill, linewidth=[1, 1.5, 2])
+    # Only hatch
+    ax5.hist(x, bins=10, histtype=histtype, fill=fill, hatch=["/", "\\", "."])
 
 
 def test_hist_barstacked_bottom_unchanged():
