# Implementation of matplotlib function
from matplotlib import colors
from matplotlib.ticker import PercentFormatter
import numpy as np
import matplotlib.pyplot as plt

 
N_points = 100000
x = np.random.randn(N_points)
y = 4 * x + np.random.randn(100000) + 50
 
plt.hist2d(x, y,
           bins = 100, 
           norm = colors.LogNorm(), 
           cmap ="gray")

plt.title('matplotlib.pyplot.hist2d() function \
Example\n\n', fontweight ="bold")

plt.show()

#Implementation of matplotlib function
from matplotlib import colors
import numpy as np
from numpy.random import multivariate_normal
import matplotlib.pyplot as plt

  
result = np.vstack([
    multivariate_normal([10, 10],
            [[3, 2], [2, 3]], size=1000000),
    multivariate_normal([30, 20],
            [[2, 3], [1, 3]], size=100000)
])

plt.hist2d(result[:, 0],
           result[:, 1],
           bins = 100, 
           cmap = "Greens",
           norm = colors.LogNorm())
plt.title('matplotlib.pyplot.hist2d function \
Example')
plt.show()

plt.hist2d(result[:, 0], 
           result[:, 1],
           bins = 100, 
           cmap = "RdYlGn_r",
           norm = colors.LogNorm())
plt.show()