Python Plotting Colors & Labels For An Unknown Number Of Lines Without Loop
Solution 1:
You can access the Line2D objects that are created using the return value of plt.plot
, and set the legend directly based on that list:
labels = ['a', 'b', 'c']
lines = plt.plot(odata[:, 0], odata[:, 1:], '-')
plt.legend(lines, labels)
The number of labels and lines does not necessarily have to match. If there are fewer lines, some of the labels will be unused. If there are fewer labels, some of the lines will be unlabeled. Here is the legend guide in the documentation.
To seamlessly change the order of the colors, you would need to set the cycler in the global configuration via matplotlib.rc
as in this example from the docs, or use the object-oriented API to do your plotting. Then you can use set_prop_cycle
on your individual axes without messing around with the global settings.
Here are three approaches for setting the color cycler in order of increasing personal preference. Note that I am only showing how to set the color here, but you can also control the sequence of line styles and probably other attributes as well:
Set the global configuration:
import matplotlib as mpl from matplotlib import cycler from matplotlib import pyplot as plt labels = ['a', 'b', 'c'] colors = ['r', 'g', 'b'] mpl.rc('axes', prop_cycle=cycler('color', ['r', 'g', 'b', 'y'])) lines = plt.plot(odata[:, 0], odata[:, 1:], '-') plt.legend(lines, labels)
Set the global configuration, but using the
rc_context
context manager to make the changes effectively local to your plot:import matplotlib as mpl from matplotlib import cycler,rc_context from matplotlib import pyplot as plt labels = ['a', 'b', 'c'] colors = ['r', 'g', 'b'] with rc_context(rc={'axes.prop_cycle': cycler('color', ['r', 'g', 'b', 'y'])}): lines = plt.plot(odata[:, 0], odata[:, 1:], '-') plt.legend(lines, labels)
Set up the plot using the object-oriented API to begin with, and apply changes only to the Axes that you actually want to modify:
from matplotlib import pyplot as plt labels = ['a', 'b', 'c'] colors = ['r', 'g', 'b'] fig, ax = plt.subplots() ax.set_prop_cycle('color', colors) ax.plot(odata[:, 0], odata[:, 1:], '-') ax.legend(labels)
I would recommend the object-oriented API as a general rule, especially within standalone scripts because it offers much greater flexibility, and also clarity in terms of knowing exactly what objects will be operated on.
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