Example for normal distribution

README.md

Зависимости

• python 2.7 или >=3.0
• matplotlib

Результат данного скрипта

main.py

from matplotlib import pyplot as plt
from matplotlib import mlab
from random import seed, gauss

SEED = 20
MU = 0
SIGMA = 1
RANGE = 10000
# Count of bars on the histogram.
NUM_BINS = 100


def main():
    # Initialize the random number generator.
    # If a is omitted or None, the current system time is used.
    seed(a=20)
    # Using gauss function to generate normal distribution.
    x = [gauss(MU, SIGMA) for _ in range(RANGE)]

    # The histogram of the data.
    n, bins, patches = plt.hist(x, NUM_BINS, normed=1, facecolor='green', alpha=0.5)

    # Add a 'best fit' line.
    y = mlab.normpdf(bins, MU, SIGMA)
    plt.plot(bins, y, 'r--')

    # Labels.
    plt.xlabel('Values')
    plt.ylabel('Probability')
    plt.title('Gaussian')

    # Tweak spacing to prevent clipping of ylabel.
    plt.subplots_adjust(left=0.15)
    plt.show()

if __name__ == '__main__':
    main()