matplotlib · tacaswell · Aug 25, 2017 · Jul 27, 2017
diff --git a/lib/matplotlib/mpl-data/stylelib/fast.mplstyle b/lib/matplotlib/mpl-data/stylelib/fast.mplstyle
@@ -0,0 +1,11 @@
+# a small set of changes that will make your plotting FAST (1).
+#
+# (1) in some cases
+
+# Maximally simplify lines.
+path.simplify: True
+path.simplify_threshold: 1.0
+
+# chunk up large lines into smaller lines!
+# simple trick to avoid those pesky O(>n) algorithms!
+agg.path.chunksize: 10000
diff --git a/lib/matplotlib/path.py b/lib/matplotlib/path.py
@@ -70,6 +70,9 @@ class Path(object):
     *codes* at all, but have a default one provided for them by
     :meth:`iter_segments`.
 
+    Some behavior of Path objects can be controlled by rcParams. See
+    the rcParams whose keys contain 'path.'.
+
     .. note::
 
         The vertices and codes arrays should be treated as
@@ -404,7 +407,8 @@ def iter_segments(self, transform=None, remove_nans=True, clip=None,
             If True, perform simplification, to remove
              vertices that do not affect the appearance of the path.  If
              False, perform no simplification.  If None, use the
-             should_simplify member variable.
+             should_simplify member variable.  See also the rcParams
+             path.simplify and path.simplify_threshold.
         curves : {True, False}, optional
             If True, curve segments will be returned as curve
             segments.  If False, all curves will be converted to line

diff --git a/tutorials/introductory/usage.py b/tutorials/introductory/usage.py
@@ -714,3 +714,58 @@ def my_plotter(ax, data1, data2, param_dict):
 # attempt at evenly spaced (along the *x* axis) sampling. See the
 # :ref:`sphx_glr_gallery_lines_bars_and_markers_markevery_demo.py`
 # for more information.
+#
+# Splitting lines into smaller chunks
+# -----------------------------------
+#
+# If you are using the Agg backend (see :ref:`what-is-a-backend`),
+# then you can make use of the ``agg.path.chunksize`` rc parameter.
+# This allows you to specify a chunk size, and any lines with
+# greater than that many vertices will be split into multiple
+# lines, each of which have no more than ``agg.path.chunksize``
+# many vertices. (Unless ``agg.path.chunksize`` is zero, in
+# which case there is no chunking.) For some kind of data,
+# chunking the line up into reasonable sizes can greatly
+# decrease rendering time.
+#
+# The following script will first display the data without any
+# chunk size restriction, and then display the same data with
+# a chunk size of 10,000. The difference can best be seen when
+# the figures are large, try maximizing the GUI and then
+# interacting with them::
+#
+#   import numpy as np
+#   import matplotlib.pyplot as plt
+#   import matplotlib as mpl
+#   mpl.rcParams['path.simplify_threshold'] = 1.0
+#
+#   # Setup, and create the data to plot
+#   y = np.random.rand(100000)
+#   y[50000:] *= 2
+#   y[np.logspace(1,np.log10(50000), 400).astype(int)] = -1
+#   mpl.rcParams['path.simplify'] = True
+#
+#   mpl.rcParams['agg.path.chunksize'] = 0
+#   plt.plot(y)
+#   plt.show()
+#
+#   mpl.rcParams['agg.path.chunksize'] = 10000
+#   plt.plot(y)
+#   plt.show()
+#
+# Using the *fast* style
+# ----------------------
+#
+# The *fast* style can be used to automatically set
+# simplification and chunking parameters to reasonable
+# settings to speed up plotting large amounts of data.
+# It can be used simply by running::
+#
+#   import matplotlib.style as mplstyle
+#   mplstyle.use('fast')
+#
+# It is very light weight, so it plays nicely with other
+# styles, just make sure the fast style is applied last
+# so that other styles do not overwrite the settings::
+#
+#   mplstyle.use(['dark_background', 'ggplot', 'fast'])