import numpy as np
import matplotlib.pyplot as plt

n = 12
x_coordinates = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
y_coordinates = [2, 4, 9, 12, 15, 19, 21, 19, 16, 12, 8, 4]

def DrawFunction(x_points, y_points, degree):
    # show function
    plt.plot(x_points, y_points, color='green', label='Aproksimuota kreive')

    # show starting points
    plt.plot(x_coordinates, y_coordinates, color='blue', linestyle='None', marker='.', markerSize=12, label='Pradiniai taskai')

    plt.xlabel('x asis')
    plt.ylabel('y asis')
    plt.title(str(degree) + ' eiles daugianaris')
    plt.legend()
    plt.show()

def GetG(x, degree):
    G = []
    for i in range(len(x)):
        g = []
        for j in range(degree):
            g.append(np.power(x[i], j))
        G.append(g)

    return G

def GetApproximationFunction(degree):
    G = GetG(x_coordinates, degree)
    c = np.linalg.solve(np.matmul(np.transpose(G), G), np.matmul(np.transpose(G), y_coordinates))
    print(c)

    x_points = []
    for x in np.arange(0, n, 0.1):
        x_points.append(x)

    GForResults = GetG(x_points, degree)
    y_points = np.matmul(GForResults, c)

    DrawFunction(x_points, y_points, degree)