Add support for multiple hatches, edgecolors and linewidths in histograms

doc/users/next_whats_new/histogram_vectorized_parameters.rst

@@ -0,0 +1,46 @@
+Vectorize ``hatch``, ``edgecolor``, ``facecolor``, ``linewidth`` and ``linestyle`` in *hist* methods
+----------------------------------------------------------------------------------------------------
+
+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.
+
+
+.. plot::
+    :include-source: true
+    :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)
+
+    fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, figsize=(9, 9))
+
+    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"]
+
+    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)
+
+    ax2.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
+             hatch=["/", ".", "*"])
+    ax2.set_title("Different hatch patterns")
+    ax2.legend(labels)
+
+    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)
+
+    ax4.hist([data1, data2, data3], bins=range(17), histtype="barstacked",
+             facecolor=["red", "green", "blue"])
+    ax4.set_title("Different facecolors")
+    ax4.legend(labels)
+
+    plt.show()

galleries/examples/statistics/histogram_multihist.py

@@ -15,7 +15,7 @@
 select these parameters:
 http://docs.astropy.org/en/stable/visualization/histogram.html
 """
-
+# %%
 import matplotlib.pyplot as plt
 import numpy as np
 
@@ -45,6 +45,93 @@
 fig.tight_layout()
 plt.show()
 
+# %%
+# -----------------------------------
+# Setting properties for each dataset
+# -----------------------------------
+#
+# Plotting bar charts with datasets differentiated using:
+#
+# * edgecolors
+# * facecolors
+# * hatches
+# * linewidths
+# * linestyles
+#
+#
+# Histograms with Edge-Colors
+# ...........................
+
+fig, ax = plt.subplots()
+
+edgecolors = ['green', 'red', 'blue']
+
+ax.hist(x, n_bins, fill=False, histtype="step", stacked=True,
+        edgecolor=edgecolors, label=edgecolors)
+ax.legend()
+ax.set_title('Stacked Steps with Edgecolors')
+
+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
+# .......................
+
+fig, ax = plt.subplots()
+
+hatches = [".", "o", "x"]
+
+ax.hist(x, n_bins, histtype="barstacked", hatch=hatches, label=hatches)
+ax.legend()
+ax.set_title("Hatches on Stacked Bars")
+
+plt.show()
+
+# %%
+# Histograms with Linewidths
+# ..........................
+
+fig, ax = plt.subplots()
+
+linewidths = [1, 2, 3]
+edgecolors = ["green", "red", "blue"]
+
+ax.hist(x, n_bins, fill=False, histtype="bar", linewidth=linewidths,
+        edgecolor=edgecolors, label=linewidths)
+ax.legend()
+ax.set_title("Bars with Linewidths")
+
+plt.show()
+
+# %%
+# Histograms with LineStyles
+# ..........................
+
+fig, ax = plt.subplots()
+
+linestyles = ['-', ':', '--']
+
+ax.hist(x, n_bins, fill=False, histtype='bar', linestyle=linestyles,
+        edgecolor=edgecolors, label=linestyles)
+ax.legend()
+ax.set_title('Bars with Linestyles')
+
+plt.show()
+
 # %%
 #
 # .. admonition:: References

lib/matplotlib/axes/_axes.py

@@ -6937,7 +6937,10 @@ 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 a sequence of values corresponding to the
+            datasets in *x*:
+            *edgecolors*, *linewidths*, *linestyles*, *hatches*.
 
         See Also
         --------
@@ -7011,7 +7014,7 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
             if len_xi:
                 input_empty = False
 
-        if color is None:
+        if not any(np.atleast_1d(color)):
             colors = [self._get_lines.get_next_color() for i in range(nx)]
         else:
             colors = mcolors.to_rgba_array(color)
@@ -7210,9 +7213,28 @@ def hist(self, x, bins=None, range=None, density=False, weights=None,
         # If None, make all labels None (via zip_longest below); otherwise,
         # 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))
+
+        if histtype == "step":
+            edgecolors = itertools.cycle(np.atleast_1d(kwargs.get('edgecolor',
+                                                                  colors)))
+        else:
+            edgecolors = itertools.cycle(np.atleast_1d(kwargs.get("edgecolor", None)))
+
+        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)))
+
         for patch, lbl in itertools.zip_longest(patches, labels):
             if patch:
                 p = patch[0]
+                kwargs.update({
+                    'hatch': next(hatches),
+                    'linewidth': next(linewidths),
+                    'linestyle': next(linestyles),
+                    'edgecolor': next(edgecolors),
+                    'facecolor': next(facecolors),
+                })
                 p._internal_update(kwargs)
                 if lbl is not None:
                     p.set_label(lbl)

lib/matplotlib/tests/test_axes.py

@@ -4603,6 +4603,36 @@ def test_hist_stacked_bar():
     ax.legend(loc='upper right', bbox_to_anchor=(1.0, 1.0), ncols=1)
 
 
+@pytest.mark.parametrize("histtype", ["step", "stepfilled"])
+@pytest.mark.parametrize("color", [["blue", "green", "brown"], [None]*3])
+@pytest.mark.parametrize("edgecolor", [["red", "black", "blue"], [None]*3])
+@pytest.mark.parametrize("facecolor", [["blue", "green", "brown"], [None]*3])
+@pytest.mark.parametrize("linewidth", [[1, 1.5, 2], [None]*3])
+@pytest.mark.parametrize("hatch", [["/", "\\", "."], [None]*3])
+@pytest.mark.parametrize("linestyle", [["-", "--", ":"], [None]*3])
+@check_figures_equal(extensions=["png"])
+def test_hist_vectorized_params(fig_test, fig_ref, histtype, color, edgecolor,
+                                facecolor, linewidth, hatch, linestyle):
+    np.random.seed(19680801)
+    x = [np.random.randn(n) for n in [2000, 5000, 10000]]
+
+    facecolor = facecolor if facecolor[0] is not None else color
+    if histtype == "step":
+        edgecolor = edgecolor if edgecolor[0] is not None else color
+
+    _, bins, _ = fig_test.subplots().hist(x, bins=10, histtype=histtype, color=color,
+                                          edgecolor=edgecolor, facecolor=facecolor,
+                                          linewidth=linewidth, hatch=hatch,
+                                          linestyle=linestyle)
+    ref_ax = fig_ref.subplots()
+
+    for i in range(2, -1, -1):
+        ref_ax.hist(x[i], bins=bins, histtype=histtype, color=color[i],
+                    edgecolor=edgecolor[i], facecolor=facecolor[i],
+                    linewidth=linewidth[i], hatch=hatch[i],
+                    linestyle=linestyle[i])
+
+
 def test_hist_barstacked_bottom_unchanged():
     b = np.array([10, 20])
     plt.hist([[0, 1], [0, 1]], 2, histtype="barstacked", bottom=b)