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Backport PR #9408: updating color cycle tutorial
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‎doc/users/prev_whats_new/whats_new_1.5.rst

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@@ -109,8 +109,8 @@ You can even multiply cyclers, which is like using `itertools.product()`
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on two or more property cycles. Remember to use parentheses if writing
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a multi-line `prop_cycle` parameter.
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.. figure:: ../../gallery/color/images/sphx_glr_color_cycle_001.png
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:target: ../../gallery/color/color_cycle.html
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.. figure:: ../../tutorials/intermediate/images/sphx_glr_color_cycle_001.png
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:target: ../../tutorials/intermediate/color_cycle.html
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:align: center
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:scale: 50
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‎examples/animation/histogram.py

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Animated histogram
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==================
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This example shows how to use a path patch to draw a bunch of
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rectangles for an animated histogram.
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Use a path patch to draw a bunch of rectangles for an animated histogram.
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"""
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import numpy as np
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import matplotlib.path as path
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import matplotlib.animation as animation
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fig, ax = plt.subplots()
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# Fixing random state for reproducibility
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np.random.seed(19680801)
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top = bottom + n
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nrects = len(left)
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# here comes the tricky part -- we have to set up the vertex and path
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# codes arrays using moveto, lineto and closepoly
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# for each rect: 1 for the MOVETO, 3 for the LINETO, 1 for the
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# CLOSEPOLY; the vert for the closepoly is ignored but we still need
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# it to keep the codes aligned with the vertices
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nverts = nrects*(1 + 3 + 1)
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###############################################################################
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# Here comes the tricky part -- we have to set up the vertex and path codes
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# arrays using ``plt.Path.MOVETO``, ``plt.Path.LINETO`` and
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# ``plt.Path.CLOSEPOLY`` for each rect.
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#
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# * We need 1 ``MOVETO`` per rectangle, which sets the initial point.
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# * We need 3 ``LINETO``'s, which tell Matplotlib to draw lines from
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# vertex 1 to vertex 2, v2 to v3, and v3 to v4.
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# * We then need one ``CLOSEPOLY`` which tells Matplotlib to draw a line from
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# the v4 to our initial vertex (the ``MOVETO`` vertex), in order to close the
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# polygon.
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#
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# .. note::
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#
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# The vertex for ``CLOSEPOLY`` is ignored, but we still need a placeholder
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# in the ``verts`` array to keep the codes aligned with the vertices.
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nverts = nrects * (1 + 3 + 1)
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verts = np.zeros((nverts, 2))
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codes = np.ones(nverts, int) * path.Path.LINETO
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codes[0::5] = path.Path.MOVETO
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verts[3::5, 0] = right
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verts[3::5, 1] = bottom
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barpath = path.Path(verts, codes)
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patch = patches.PathPatch(
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barpath, facecolor='green', edgecolor='yellow', alpha=0.5)
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ax.add_patch(patch)
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ax.set_xlim(left[0], right[-1])
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ax.set_ylim(bottom.min(), top.max())
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###############################################################################
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# To animate the histogram, we need an ``animate`` function, which generates
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# a random set of numbers and updates the locations of the vertices for the
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# histogram (in this case, only the heights of each rectangle). ``patch`` will
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# eventually be a ``Patch`` object.
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patch = None
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def animate(i):
@@ -68,5 +74,18 @@ def animate(i):
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verts[2::5, 1] = top
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return [patch, ]
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###############################################################################
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# And now we build the `Path` and `Patch` instances for the histogram using
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# our vertices and codes. We add the patch to the `Axes` instance, and setup
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# the `FuncAnimation` with our animate function.
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fig, ax = plt.subplots()
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barpath = path.Path(verts, codes)
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patch = patches.PathPatch(
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barpath, facecolor='green', edgecolor='yellow', alpha=0.5)
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ax.add_patch(patch)
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ax.set_xlim(left[0], right[-1])
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ax.set_ylim(bottom.min(), top.max())
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ani = animation.FuncAnimation(fig, animate, 100, repeat=False, blit=True)
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plt.show()

‎tutorials/intermediate/color_cycle.py

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"""
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===================
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Styling with cycler
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===================
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Demo of custom property-cycle settings to control colors and other style
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properties for multi-line plots.
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.. note::
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More complete documentation of the ``cycler`` API can be found
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`here <http://matplotlib.org/cycler/>`_.
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This example demonstrates two different APIs:
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1. Setting the default rc parameter specifying the property cycle.
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This affects all subsequent axes (but not axes already created).
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2. Setting the property cycle for a single pair of axes.
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"""
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from cycler import cycler
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import numpy as np
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import matplotlib.pyplot as plt
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###############################################################################
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# First we'll generate some sample data, in this case, four offset sine
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# curves.
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x = np.linspace(0, 2 * np.pi, 50)
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offsets = np.linspace(0, 2 * np.pi, 4, endpoint=False)
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yy = np.transpose([np.sin(x + phi) for phi in offsets])
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###############################################################################
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# Now ``yy`` has shape
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print(yy.shape)
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###############################################################################
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# So ``yy[:, i]`` will give you the ``i``-th offset sine curve. Let's set the
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# default prop_cycle using :func:`matplotlib.pyplot.rc`. We'll combine a color
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# cycler and a linestyle cycler by adding (``+``) two ``cycler``'s together.
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# See the bottom of this tutorial for more information about combining
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# different cyclers.
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default_cycler = cycler('color', ['r', 'g', 'b', 'y']) \
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+ cycler('linestyle', ['-', '--', ':', '-.'])
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plt.rc('lines', linewidth=4)
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plt.rc('axes', prop_cycle=default_cycler)
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###############################################################################
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# Now we'll generate a figure with two axes, one on top of the other. On the
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# first axis, we'll plot with the default cycler. On the second axis, we'll
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# set the prop_cycler using :func:`matplotlib.axes.Axes.set_prop_cycle`
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# which will only set the ``prop_cycle`` for this :mod:`matplotlib.axes.Axes`
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# instance. We'll use a second ``cycler`` that combines a color cycler and a
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# linewidth cycler.
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custom_cycler = cycler('color', ['c', 'm', 'y', 'k']) \
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+ cycler('lw', [1, 2, 3, 4])
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fig, (ax0, ax1) = plt.subplots(nrows=2)
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ax0.plot(yy)
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ax0.set_title('Set default color cycle to rgby')
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ax1.set_prop_cycle(custom_cycler)
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ax1.plot(yy)
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ax1.set_title('Set axes color cycle to cmyk')
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# Add a bit more space between the two plots.
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fig.subplots_adjust(hspace=0.3)
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plt.show()
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###############################################################################
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# Setting ``prop_cycler`` in the ``matplotlibrc`` file or style files
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# -------------------------------------------------------------------
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#
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# Remember, if you want to set a custom ``prop_cycler`` in your
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# ``.matplotlibrc`` file or a style file (``style.mplstyle``), you can set the
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# ``axes.prop_cycle`` property:
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#
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# ..code-block:: python
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#
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# axes.prop_cycle : cycler('color', 'bgrcmyk')
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#
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# Cycling through multiple properties
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# -----------------------------------
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#
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# You can add cyclers:
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#
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# .. code-block:: python
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#
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# from cycler import cycler
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# cc = (cycler(color=list('rgb')) +
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# cycler(linestyle=['-', '--', '-.']))
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# for d in cc:
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# print(d)
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#
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# Results in:
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#
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# .. code-block:: python
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#
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# {'color': 'r', 'linestyle': '-'}
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# {'color': 'g', 'linestyle': '--'}
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# {'color': 'b', 'linestyle': '-.'}
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#
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#
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# You can multiply cyclers:
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#
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# .. code-block:: python
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#
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# from cycler import cycler
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# cc = (cycler(color=list('rgb')) *
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# cycler(linestyle=['-', '--', '-.']))
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# for d in cc:
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# print(d)
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#
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# Results in:
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#
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# .. code-block:: python
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#
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# {'color': 'r', 'linestyle': '-'}
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# {'color': 'r', 'linestyle': '--'}
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# {'color': 'r', 'linestyle': '-.'}
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# {'color': 'g', 'linestyle': '-'}
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# {'color': 'g', 'linestyle': '--'}
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# {'color': 'g', 'linestyle': '-.'}
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# {'color': 'b', 'linestyle': '-'}
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# {'color': 'b', 'linestyle': '--'}
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# {'color': 'b', 'linestyle': '-.'}

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