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Use style package from pyplot
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doc/users/style_sheets.rst

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@@ -13,12 +13,12 @@ example, there's a pre-defined style called "ggplot", which emulates the
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aesthetics of ggplot_ (a popular plotting package for R_). To use this style,
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just add::
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>>> from matplotlib import style
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>>> style.use('ggplot')
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>>> import matplotlib.pyplot as plt
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>>> plt.style.use('ggplot')
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To list all available styles, use::
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>>> print style.available
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>>> print plt.style.available
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Defining your own style
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Then, when you want to adapt a plot designed for a paper to one that looks
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good in a presentation, you can just add::
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>>> from matplotlib import style
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>>> style.use('presentation')
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>>> import matplotlib.pyplot as plt
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>>> plt.style.use('presentation')
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Composing styles
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sizes for presentations. These styles can easily be combined by passing
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a list of styles::
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>>> from matplotlib import style
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>>> style.use(['dark_background', 'presentation'])
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>>> import matplotlib.pyplot as plt
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>>> plt.style.use(['dark_background', 'presentation'])
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Note that styles further to the right will overwrite values that are already
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defined by styles on the right.
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>>> import numpy as np
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>>> import matplotlib.pyplot as plt
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>>> from matplotlib import style
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>>>
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>>> with style.context(('dark_background')):
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>>> with plt.style.context(('dark_background')):
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>>> plt.plot(np.sin(np.linspace(0, 2*np.pi)), 'r-o')
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>>>
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>>> # Some plotting code with the default style

examples/style_sheets/plot_dark_background.py

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@@ -7,9 +7,8 @@
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import style
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style.use('dark_background')
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plt.style.use('dark_background')
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L = 6
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x = np.linspace(0, L)

examples/style_sheets/plot_ggplot.py

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"""
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import style
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style.use('ggplot')
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plt.style.use('ggplot')
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fig, axes = plt.subplots(ncols=2, nrows=2)
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ax1, ax2, ax3, ax4 = axes.ravel()

examples/style_sheets/plot_grayscale.py

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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import style
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def color_cycle_example(ax):
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L = 6
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ax.add_patch(c)
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style.use('grayscale')
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plt.style.use('grayscale')
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fig, (ax1, ax2) = plt.subplots(ncols=2)
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