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# Defining colors manually

colored_line.py is a simple illustration of how to make the color of each segment of a line depend on some property of the data being plotted.

An up to date version of the script can be found here.

Here is the script:

```   1 #!/usr/bin/env python
2 '''
3 Color parts of a line based on its properties, e.g., slope.
4 '''
5 import numpy as np
6 import matplotlib.pyplot as plt
7 from matplotlib.collections import LineCollection
8 from matplotlib.colors import ListedColormap, BoundaryNorm
9
10 x = np.linspace(0, 3 * np.pi, 500)
11 y = np.sin(x)
12 z = np.cos(0.5 * (x[:-1] + x[1:]))  # first derivative
13
14 # Create a colormap for red, green and blue and a norm to color
15 # f' < -0.5 red, f' > 0.5 blue, and the rest green
16 cmap = ListedColormap(['r', 'g', 'b'])
17 norm = BoundaryNorm([-1, -0.5, 0.5, 1], cmap.N)
18
19 # Create a set of line segments so that we can color them individually
20 # This creates the points as a N x 1 x 2 array so that we can stack points
21 # together easily to get the segments. The segments array for line collection
22 # needs to be numlines x points per line x 2 (x and y)
23 points = np.array([x, y]).T.reshape(-1, 1, 2)
24 segments = np.concatenate([points[:-1], points[1:]], axis=1)
25
26 # Create the line collection object, setting the colormapping parameters.
27 # Have to set the actual values used for colormapping separately.
28 lc = LineCollection(segments, cmap=cmap, norm=norm)
29 lc.set_array(z)
30 lc.set_linewidth(3)
32
33 plt.xlim(x.min(), x.max())
34 plt.ylim(-1.1, 1.1)
35 plt.show()
```

Note that the number of segments is one less than the number of points.

An alternative strategy would be to generate one segment for each contiguous region of a given color.

# Using a smooth, builtin colormap

If you have a parametric curve to display, and want to represent the parameter using color.

```   1 import numpy as np
2 import matplotlib.pyplot as plt
3 from matplotlib.collections import LineCollection
4
5 t = np.linspace(0, 10, 200)
6 x = np.cos(np.pi * t)
7 y = np.sin(t)
8
9 # Create a set of line segments so that we can color them individually
10 # This creates the points as a N x 1 x 2 array so that we can stack points
11 # together easily to get the segments. The segments array for line collection
12 # needs to be numlines x points per line x 2 (x and y)
13 points = np.array([x, y]).T.reshape(-1, 1, 2)
14 segments = np.concatenate([points[:-1], points[1:]], axis=1)
15
16 # Create the line collection object, setting the colormapping parameters.
17 # Have to set the actual values used for colormapping separately.
18 lc = LineCollection(segments, cmap=plt.get_cmap('copper'),
19     norm=plt.Normalize(0, 10))
20 lc.set_array(t)
21 lc.set_linewidth(3)
22