from math import ceil
import numpy as np
from matplotlib import pyplot as plt
# Sample from a bivariate Gaussian distribution
mean = [0,0]
cov = [[0,1],[1,0]]
x, y = np.random.multivariate_normal(mean, cov, 10000).T
size = len(plt.cm.datad.keys())
all_maps = list(plt.cm.datad.keys())
new_maps = ['viridis', 'inferno', 'magma', 'plasma']
counter = 0
for i in xrange(4):
plt.subplot(1, 4, counter + 1)
plt.imshow(hist, cmap=new_maps[counter])
plt.title(new_maps[counter])
counter += 1
plt.tight_layout()
plt.show()
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