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Commit 64535a6

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DOC: Update broken_barh example
IMHO this is more realistic and better looking. I've always been wondering what the previous plot should mean. Note: There's precedence for a similar special-casing on polar Axes for errorbars: https://github.com/matplotlib/matplotlib/blob/3fb9c0961b5c8d5753c88ac37c08cda58a4b7839/lib/matplotlib/axes/_axes.py#L3798
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‎galleries/examples/lines_bars_and_markers/broken_barh.py

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"""
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===========
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Broken Barh
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===========
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======================
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Broken horizontal bars
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======================
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Make a "broken" horizontal bar plot, i.e., one with gaps
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`~.Axes.broken_barh` creates sequences of horizontal bars. This example shows
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a timing diagram.
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"""
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import matplotlib.pyplot as plt
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import numpy as np
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# data is a sequence of (start, duration) tuples
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cpu_1 = [(0, 3), (3.5, 1), (5, 5)]
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cpu_2 = np.column_stack([np.linspace(0, 9, 10), np.full(10, 0.5)])
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cpu_3 = np.column_stack([10*np.random.random(61), np.full(61, 0.05)])
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cpu_4 = [(2, 1.7), (7, 1.2)]
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disk = [(1, 1.5)]
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network = np.column_stack([10*np.random.random(10), np.full(10, 0.05)])
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# Horizontal bar plot with gaps
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fig, ax = plt.subplots()
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ax.broken_barh([(110, 30), (150, 10)], (10, 9), facecolors='tab:blue')
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ax.broken_barh([(10, 50), (100, 20), (130, 10)], (20, 9),
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facecolors=('tab:orange', 'tab:green', 'tab:red'))
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ax.set_ylim(5, 35)
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ax.set_xlim(0, 200)
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ax.set_xlabel('seconds since start')
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ax.set_yticks([15, 25], labels=['Bill', 'Jim']) # Modify y-axis tick labels
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ax.grid(True) # Make grid lines visible
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ax.annotate('race interrupted', (61, 25),
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xytext=(0.8, 0.9), textcoords='axes fraction',
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arrowprops=dict(facecolor='black', shrink=0.05),
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fontsize=16,
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horizontalalignment='right', verticalalignment='top')
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# broken_barh(xranges, (ymin, height))
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ax.broken_barh(cpu_1, (5.8, 0.4))
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ax.broken_barh(cpu_2, (4.8, 0.4))
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ax.broken_barh(cpu_3, (3.8, 0.4))
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ax.broken_barh(cpu_4, (2.8, 0.4))
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ax.broken_barh(disk, (1.8, 0.4), color="tab:orange")
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ax.broken_barh(network, (0.8, 0.4), color="tab:green")
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ax.set_xlim(0, 10)
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ax.set_yticks([6, 5, 4, 3, 2, 1],
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labels=["CPU 1", "CPU 2", "CPU 3", "CPU 4", "disk", "network"])
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ax.set_title("Resource usage")
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plt.show()
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