diff --git a/examples/misc/demo_ribbon_box.py b/examples/misc/demo_ribbon_box.py
index 9e350182e3dd..ea4fa579e8c5 100644
--- a/examples/misc/demo_ribbon_box.py
+++ b/examples/misc/demo_ribbon_box.py
@@ -24,7 +24,7 @@ class RibbonBox:
nx = original_image.shape[1]
def __init__(self, color):
- rgb = mcolors.to_rgba(color)[:3]
+ rgb = mcolors.to_rgb(color)
self.im = np.dstack(
[self.b_and_h - self.color * (1 - np.array(rgb)), self.alpha])
diff --git a/examples/shapes_and_collections/collections.py b/examples/shapes_and_collections/collections.py
index 161e2f1d28e5..b7ce0d6340ac 100644
--- a/examples/shapes_and_collections/collections.py
+++ b/examples/shapes_and_collections/collections.py
@@ -11,14 +11,14 @@
The third subplot will make regular polygons, with the same
type of scaling and positioning as in the first two.
-The last subplot illustrates the use of "offsets=(xo, yo)",
+The last subplot illustrates the use of ``offsets=(xo, yo)``,
that is, a single tuple instead of a list of tuples, to generate
successively offset curves, with the offset given in data
units. This behavior is available only for the LineCollection.
"""
import matplotlib.pyplot as plt
-from matplotlib import collections, colors, transforms
+from matplotlib import collections, transforms
import numpy as np
nverts = 50
@@ -38,8 +38,7 @@
xyo = rs.randn(npts, 2)
# Make a list of colors cycling through the default series.
-colors = [colors.to_rgba(c)
- for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]
+colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
fig.subplots_adjust(top=0.92, left=0.07, right=0.97,
diff --git a/examples/shapes_and_collections/line_collection.py b/examples/shapes_and_collections/line_collection.py
index 9adfd8024e5b..c0c44a7d8b8b 100644
--- a/examples/shapes_and_collections/line_collection.py
+++ b/examples/shapes_and_collections/line_collection.py
@@ -1,23 +1,17 @@
"""
-===============
-Line Collection
-===============
+=============================================
+Plotting multiple lines with a LineCollection
+=============================================
-Plotting lines with Matplotlib.
-
-`~matplotlib.collections.LineCollection` allows one to plot multiple
-lines on a figure. Below we show off some of its properties.
+Matplotlib can efficiently draw multiple lines at once using a
+`~.LineCollection`, as showcased below.
"""
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
-from matplotlib import colors as mcolors
import numpy as np
-# In order to efficiently plot many lines in a single set of axes,
-# Matplotlib has the ability to add the lines all at once. Here is a
-# simple example showing how it is done.
x = np.arange(100)
# Here are many sets of y to plot vs. x
@@ -30,7 +24,7 @@
# Mask some values to test masked array support:
segs = np.ma.masked_where((segs > 50) & (segs < 60), segs)
-# We need to set the plot limits.
+# We need to set the plot limits, they will not autoscale
fig, ax = plt.subplots()
ax.set_xlim(x.min(), x.max())
ax.set_ylim(ys.min(), ys.max())
@@ -41,8 +35,7 @@
# onoffseq is an even length tuple of on and off ink in points. If linestyle
# is omitted, 'solid' is used.
# See `matplotlib.collections.LineCollection` for more information.
-colors = [mcolors.to_rgba(c)
- for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]
+colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
line_segments = LineCollection(segs, linewidths=(0.5, 1, 1.5, 2),
colors=colors, linestyle='solid')
@@ -51,32 +44,22 @@
plt.show()
###############################################################################
-# In order to efficiently plot many lines in a single set of axes,
-# Matplotlib has the ability to add the lines all at once. Here is a
-# simple example showing how it is done.
+# In the following example, instead of passing a list of colors
+# (``colors=colors``), we pass an array of values (``array=x``) that get
+# colormapped.
N = 50
x = np.arange(N)
-# Here are many sets of y to plot vs. x
-ys = [x + i for i in x]
+ys = [x + i for i in x] # Many sets of y to plot vs. x
+segs = [np.column_stack([x, y]) for y in ys]
-# We need to set the plot limits, they will not autoscale
fig, ax = plt.subplots()
ax.set_xlim(np.min(x), np.max(x))
ax.set_ylim(np.min(ys), np.max(ys))
-# colors is sequence of rgba tuples
-# linestyle is a string or dash tuple. Legal string values are
-# solid|dashed|dashdot|dotted. The dash tuple is (offset, onoffseq)
-# where onoffseq is an even length tuple of on and off ink in points.
-# If linestyle is omitted, 'solid' is used
-# See `matplotlib.collections.LineCollection` for more information
-
-# Make a sequence of (x, y) pairs.
-line_segments = LineCollection([np.column_stack([x, y]) for y in ys],
+line_segments = LineCollection(segs, array=x,
linewidths=(0.5, 1, 1.5, 2),
linestyles='solid')
-line_segments.set_array(x)
ax.add_collection(line_segments)
axcb = fig.colorbar(line_segments)
axcb.set_label('Line Number')
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