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Note

Click here to download the full example code

Plotting lines with Matplotlib.

`LineCollection`

allows one to plot multiple
lines on a figure. Below we show off some of its properties.

```
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
ys = x[:50, np.newaxis] + x[np.newaxis, :]
segs = np.zeros((50, 100, 2), float)
segs[:, :, 1] = ys
segs[:, :, 0] = x
# 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.
fig, ax = plt.subplots()
ax.set_xlim(x.min(), x.max())
ax.set_ylim(ys.min(), ys.max())
# 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 :class:`matplotlib.collections.LineCollection` for more information
colors = [mcolors.to_rgba(c)
for c in plt.rcParams['axes.prop_cycle'].by_key()['color']]
line_segments = LineCollection(segs, linewidths=(0.5, 1, 1.5, 2),
colors=colors, linestyle='solid')
ax.add_collection(line_segments)
ax.set_title('Line collection with masked arrays')
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.

```
N = 50
x = np.arange(N)
# Here are many sets of y to plot vs x
ys = [x + i for i in x]
# 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 :class:`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],
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')
ax.set_title('Line Collection with mapped colors')
plt.sci(line_segments) # This allows interactive changing of the colormap.
plt.show()
```

The use of the following functions, methods, classes and modules is shown in this example:

```
import matplotlib
matplotlib.collections
matplotlib.collections.LineCollection
matplotlib.cm.ScalarMappable.set_array
matplotlib.axes.Axes.add_collection
matplotlib.figure.Figure.colorbar
matplotlib.pyplot.colorbar
matplotlib.pyplot.sci
```

Out:

```
<function sci at 0x7fd7572c5a60>
```

Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery