如何在matplotlib中为线图迭代的子集设置不同的颜色？

Question

I am iteratively plotting the np.exp results of 12 rows of data from a 2D array (12,5000) , out_array . All data share the same x values, ( x_d ). I want the first 4 iterations to all plot as the same color, the next 4 to be a different color, and next 4 a different color...such that I have 3 different colors each corresponding to the 1st-4th, 5th-8th, and 9th-12th iterations respectively. In the end, it would also be nice to define these sets with their corresponding colors in a legend.

I have researched cycler ( https://matplotlib.org/examples/color/color_cycle_demo.html ), but I can't figure out how to assign colors into sets of iterations > 1. (ie 4 in my case). As you can see in my code example, I can have all 12 lines plotted with different (default) colors -or- I know how to make them all the same color (ie ...,color = 'r',... )

plt.figure()
for i in range(out_array.shape[0]):
    plt.plot(x_d, np.exp(out_array[i]),linewidth = 1, alpha = 0.6)
plt.xlim(-2,3)

I expect a plot like this, only with a total of 3 different colors, each corresponding to the chunks of iterations described above.

Answer 1

plt.figure()
n = 0
color = ['r','g','b']
for i in range(out_array.shape[0]):
    n = n+1
    if n/4 <= 1:
        c = 1
    elif n/4 >1 and n/4 <= 2:
        c = 2
    elif n/4 >2:
        c = 3
    else:
        print(n)
    plt.plot(x_d, np.exp(out_array[i]),color = color[c-1])
plt.show()

Answer 2

An other solution

import matplotlib.pyplot as plt
import numpy as np

x = np.arange(10)

color = ['r', 'g', 'b', 'p']

for i in range(12):

    plt.plot(x, i*x, color[i//4])

plt.show()