import matplotlib.pylab as plt
import numpy as np
import pandas as pd
from scipy.stats import norm
import seaborn as sns
from mpl_toolkits.mplot3d import Axes3D
from math import cos, sin, log, tan, gamma, pi, exp, sqrt
p = plt.figure(figsize=(14, 14), facecolor='black', dpi=400)
p = plt.axis('off')
p = plt.xlim(-1, 1)
p = plt.ylim(-1, 1)
for z in np.linspace(0, 2 * pi, 91):
    plt.fill_between([0, cos(z - pi / 2)], [0, sin(z - pi / 2)], alpha=0.3,
        color=plt.cm.RdYlBu(z / (2 * pi)), lw=0.2)
plt.savefig(f'C:/Users/Alejandro/Pictures/RandomPlots/12022020.png',
    facecolor='black')

d934afe5b7dd33103a8a0ebaeeae9d0304cd4607
<mask token>

<mask token>
for z in np.linspace(0, 2 * pi, 91):
    plt.fill_between([0, cos(z - pi / 2)], [0, sin(z - pi / 2)], alpha=0.3,
        color=plt.cm.RdYlBu(z / (2 * pi)), lw=0.2)
plt.savefig(f'C:/Users/Alejandro/Pictures/RandomPlots/12022020.png',
    facecolor='black')

<mask token>
p = plt.figure(figsize=(14, 14), facecolor='black', dpi=400)
p = plt.axis('off')
p = plt.xlim(-1, 1)
p = plt.ylim(-1, 1)
for z in np.linspace(0, 2 * pi, 91):
    plt.fill_between([0, cos(z - pi / 2)], [0, sin(z - pi / 2)], alpha=0.3,
        color=plt.cm.RdYlBu(z / (2 * pi)), lw=0.2)
plt.savefig(f'C:/Users/Alejandro/Pictures/RandomPlots/12022020.png',
    facecolor='black')

import matplotlib.pylab as plt
import numpy as np
import pandas as pd
from scipy.stats import norm
import seaborn as sns
from mpl_toolkits.mplot3d import Axes3D
from math import cos, sin, log, tan, gamma, pi, exp, sqrt
p = plt.figure(figsize=(14, 14), facecolor='black', dpi=400)
p = plt.axis('off')
p = plt.xlim(-1, 1)
p = plt.ylim(-1, 1)
for z in np.linspace(0, 2 * pi, 91):
    plt.fill_between([0, cos(z - pi / 2)], [0, sin(z - pi / 2)], alpha=0.3,
        color=plt.cm.RdYlBu(z / (2 * pi)), lw=0.2)
plt.savefig(f'C:/Users/Alejandro/Pictures/RandomPlots/12022020.png',
    facecolor='black')
