<jupyter_start><jupyter_text>Styling with cyclerDemo of custom property-cycle settings to control colors and other styleproperties for multi-line plots.NoteMore complete documentation of the ``cycler`` API can be found    `here `_.This example demonstrates two different APIs:1. Setting the default rc parameter specifying the property cycle.   This affects all subsequent axes (but not axes already created).2. Setting the property cycle for a single pair of axes.<jupyter_code>from cycler import cycler
import numpy as np
import matplotlib.pyplot as plt<jupyter_output><empty_output><jupyter_text>First we'll generate some sample data, in this case, four offset sinecurves.<jupyter_code>x = np.linspace(0, 2 * np.pi, 50)
offsets = np.linspace(0, 2 * np.pi, 4, endpoint=False)
yy = np.transpose([np.sin(x + phi) for phi in offsets])<jupyter_output><empty_output><jupyter_text>Now ``yy`` has shape<jupyter_code>print(yy.shape)<jupyter_output><empty_output><jupyter_text>So ``yy[:, i]`` will give you the ``i``-th offset sine curve. Let's set thedefault prop_cycle using :func:`matplotlib.pyplot.rc`. We'll combine a colorcycler and a linestyle cycler by adding (``+``) two ``cycler``'s together.See the bottom of this tutorial for more information about combiningdifferent cyclers.<jupyter_code>default_cycler = (cycler(color=['r', 'g', 'b', 'y']) +
                  cycler(linestyle=['-', '--', ':', '-.']))

plt.rc('lines', linewidth=4)
plt.rc('axes', prop_cycle=default_cycler)<jupyter_output><empty_output><jupyter_text>Now we'll generate a figure with two axes, one on top of the other. On thefirst axis, we'll plot with the default cycler. On the second axis, we'llset the prop_cycler using :func:`matplotlib.axes.Axes.set_prop_cycle`which will only set the ``prop_cycle`` for this :mod:`matplotlib.axes.Axes`instance. We'll use a second ``cycler`` that combines a color cycler and alinewidth cycler.<jupyter_code>custom_cycler = (cycler(color=['c', 'm', 'y', 'k']) +
                 cycler(lw=[1, 2, 3, 4]))

fig, (ax0, ax1) = plt.subplots(nrows=2)
ax0.plot(yy)
ax0.set_title('Set default color cycle to rgby')
ax1.set_prop_cycle(custom_cycler)
ax1.plot(yy)
ax1.set_title('Set axes color cycle to cmyk')

# Add a bit more space between the two plots.
fig.subplots_adjust(hspace=0.3)
plt.show()<jupyter_output><empty_output>
StarcoderdataJupyterStructuredCleanDedup