lab1

lab1

from math import sqrt
import matplotlib.pyplot as plt
import numpy as np


RANDOM_POINTS_COUNT = 10


def get_euclidean_distance(point_one, point_two):
    dx = (point_one[0] - point_two[0]) ** 2
    dy = (point_one[1] - point_two[1]) ** 2
    return sqrt(dx + dy)


def get_average_class_value(point, array_points):
    average_value = 0.0
    for array_point in array_points:
        average_value += get_euclidean_distance(point, array_point)
    return average_value / len(array_points)


def get_random_point():
    array = [float('%.2f' % i) for i in np.random.rand(2)]
    return np.array(array)


def main():
    class_red = np.array([[0.05, 0.91], 
                          [0.14, 0.96],
                          [0.16, 0.9],
                          [0.07, 0.7],
                          [0.2, 0.63]])

    class_blue = np.array([[0.49, 0.89],
                          [0.34, 0.81],
                          [0.36, 0.67],
                          [0.47, 0.49],
                          [0.52, 0.53]])

    p1 = plt.plot(class_red[:, 0], class_red[:, 1], '*r')
    p2 = plt.plot(class_blue[:, 0], class_blue[:, 1], '+b')
    plt.legend([p1, p2], ["classred", "classblue"])
    plt.grid(True)

    for i in range(RANDOM_POINTS_COUNT):
        random_point = get_random_point()
        red_average = get_average_class_value(random_point, class_red)
        blue_average = get_average_class_value(random_point, class_blue)
        color = 'r' if red_average < blue_average else 'b'

        plt.scatter(random_point[0], random_point[1], color=color)
        plt.pause(0.2)

    plt.show()


if __name__ == '__main__':
    main()