How to generate random colors in matplotlib?

Question

What's the trivial example of how to generate random colors for passing to plotting functions?

I'm calling scatter inside a loop and want each plot a different color.

for X,Y in data:    scatter(X, Y, c=??) 

c: a color. c can be a single color format string, or a sequence of color specifications of length N, or a sequence of N numbers to be mapped to colors using the cmap and norm specified via kwargs (see below). Note that c should not be a single numeric RGB or RGBA sequence because that is indistinguishable from an array of values to be colormapped. c can be a 2-D array in which the rows are RGB or RGBA, however.

Answer 1

I'm calling scatter inside a loop and want each plot in a different color.

Based on that, and on your answer: It seems to me that you actually want n distinct colors for your datasets; you want to map the integer indices 0, 1, ..., n-1 to distinct RGB colors. Something like:

Here is the function to do it:

import matplotlib.pyplot as plt  def get_cmap(n, name='hsv'):     '''Returns a function that maps each index in 0, 1, ..., n-1 to a distinct      RGB color; the keyword argument name must be a standard mpl colormap name.'''     return plt.cm.get_cmap(name, n) 

Usage in your pseudo-code snippet in the question:

cmap = get_cmap(len(data)) for i, (X, Y) in enumerate(data):    scatter(X, Y, c=cmap(i)) 

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I generated the figure in my answer with the following code:

import matplotlib.pyplot as plt  def get_cmap(n, name='hsv'):     '''Returns a function that maps each index in 0, 1, ..., n-1 to a distinct      RGB color; the keyword argument name must be a standard mpl colormap name.'''     return plt.cm.get_cmap(name, n)  def main():     N = 30     fig=plt.figure()     ax=fig.add_subplot(111)        plt.axis('scaled')     ax.set_xlim([ 0, N])     ax.set_ylim([-0.5, 0.5])     cmap = get_cmap(N)     for i in range(N):         rect = plt.Rectangle((i, -0.5), 1, 1, facecolor=cmap(i))         ax.add_artist(rect)     ax.set_yticks([])     plt.show()  if __name__=='__main__':     main() 

Tested with both Python 2.7 & matplotlib 1.5, and with Python 3.5 & matplotlib 2.0. It works as expected.

Answer 2

for X,Y in data:    scatter(X, Y, c=numpy.random.rand(3,))