How to plot a lot of legends by changing the color of the graph continuously with matplotlib

I want to change the color with matplotlib and display a lot of legends

Usage

I want to display a lot of graphs using matplotlib, but by default I can only get a finite number of colors. I would like to introduce an easy way to solve this. In that case, I often want to display a lot of legends, which was difficult with the old matplotlib, but now it's very easy, so I'll show you how to do it as a bonus.

sample

Overview

For the two functions y = arctan ((n + 1) x) and y = x ^ n, we will introduce an example of overlaying a graph with n shifted by 20.

colormap points

usercmap = plt.get_cmap('jet')
cNorm  = colors.Normalize(vmin=0, vmax=num)
scalarMap = cm.ScalarMappable(norm=cNorm, cmap=usercmap)

Now select jet with colormap, declare color coding with 0 to num (20) number of data, and generate scalarMap with cm.ScalarMappable. In the for loop Select a color as c = scalarMap.to_rgba (i).

Points for displaying a lot of legends

python

plt.legend(bbox_to_anchor=(0., 1.01, 1., 0.01), loc='lower left',ncol=10, mode="expand", borderaxespad=0.,fontsize=8)

Specify the location with bbox_to_anchor = (X coordinate, Y coordinate, X size, Y size), and adjust the number of columns to fold with ncol.

Sample code

python

#!/usr/bin/env python 
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
plt.rcParams['font.family'] = 'serif'
import optparse
import matplotlib.pylab as plab
from matplotlib.colors import LogNorm
import matplotlib.colors as colors

### plot 1D plot : shifted 
F = plt.figure(figsize=(12,8.))
plt.subplots_adjust(wspace=0.3, hspace=0.6)

ax = plt.subplot(2,1,1)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)             
plt.figtext(0.02,0.02,"[matplotlib legend test]")
plt.xscale('linear')
plt.yscale('linear')
plt.grid(linestyle='dotted',alpha=0.5)
plt.xlabel(r'x-axis (a.u.)')
plt.ylabel(r'y-axis')        
x = np.arange(-1,1,0.1)
num=20
y = []
for j in range(num):
    y.append(np.arctan(x*(j+1)))

usercmap = plt.get_cmap('jet')
cNorm  = colors.Normalize(vmin=0, vmax=num)
scalarMap = cm.ScalarMappable(norm=cNorm, cmap=usercmap)

for i,oney in enumerate(y):
    c = scalarMap.to_rgba(i)
    plt.errorbar(x, oney, fmt="o-", color = c, alpha = 0.8, linewidth = 1, label=str(i))        

plt.legend(bbox_to_anchor=(0., 1.01, 1., 0.01), loc='lower left',ncol=10, mode="expand", borderaxespad=0.,fontsize=8)


ax = plt.subplot(2,1,2)
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)             
plt.xscale('linear')
plt.yscale('linear')
plt.grid(linestyle='dotted',alpha=0.5)
plt.xlabel(r'x-axis (a.u.)')
plt.ylabel(r'y-axis')        
x = np.arange(-1,1,0.1)
num=20
y = []
for j in range(num):
    y.append(np.power(x,j+1))

usercmap = plt.get_cmap('jet')
cNorm  = colors.Normalize(vmin=0, vmax=num)
scalarMap = cm.ScalarMappable(norm=cNorm, cmap=usercmap)

for i,oney in enumerate(y):
    c = scalarMap.to_rgba(i)
    plt.errorbar(x, oney, fmt="o-", color = c, alpha = 0.8, linewidth = 1, label=str(i))        

plt.legend(bbox_to_anchor=(-0.1, 1.0, 1.2, 0.01), loc='lower left',ncol=10, mode="expand", borderaxespad=0.,fontsize=8)

plt.savefig("qiita_legend_sample.png ")
plt.show()

Click here for the generated figure.

Notes

It's now easier to expand the legend horizontally and display it outside the graph, but the expand option only supports horizontal, not vertical (as of 2019.1.8). I think time will be settled.