matplotlib · timhoffm · Jun 8, 2025 · May 24, 2025 · May 24, 2025 · May 25, 2025
diff --git a/galleries/examples/color/colorbar_histogram.py b/galleries/examples/color/colorbar_histogram.py
@@ -0,0 +1,48 @@
+"""
+=====================
+Histogram as colorbar
+=====================
+
+This example demonstrates how to use a colored histogram instead of a colorbar
+to not only show the color-to-value mapping, but also visualize the
+distribution of values.
+"""
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import matplotlib.colors as mcolors
+
+# surface data
+delta = 0.025
+x = y = np.arange(-2.0, 2.0, delta)
+X, Y = np.meshgrid(x, y)
+Z1 = np.exp(-(((X + 1) * 1.3) ** 2) - ((Y + 1) * 1.3) ** 2)
+Z2 = 2.5 * np.exp(-((X - 1) ** 2) - (Y - 1) ** 2)
+Z = Z1**0.25 - Z2**0.5
+
+# colormap & normalization
+bins = 30
+cmap = plt.get_cmap("RdYlBu_r")
+bin_edges = np.linspace(Z.min(), Z.max(), bins + 1)
+norm = mcolors.BoundaryNorm(bin_edges, cmap.N)
+
+# main plot
+fig, ax = plt.subplots(layout="constrained")
+im = ax.imshow(Z, cmap=cmap, origin="lower", extent=[-3, 3, -3, 3], norm=norm)
+
+# inset histogram
+cax = ax.inset_axes([1.18, 0.02, 0.25, 0.95])  # left, bottom, width, height
+
+# plot histogram
+counts, _ = np.histogram(Z, bins=bin_edges)
+midpoints = (bin_edges[:-1] + bin_edges[1:]) / 2
+distance = midpoints[1] - midpoints[0]
+cax.barh(midpoints, counts, height=0.8 * distance, color=cmap(norm(midpoints)))
+
+# styling
+cax.spines[:].set_visible(False)
+cax.set_yticks(bin_edges)
+cax.tick_params(axis="both", which="both", length=0)
+
+plt.show()