import random
import numpy as np
import scipy.interpolate as sp
import matplotlib.pyplot as plt
from scipy import interpolate

class Spline_Interpolation():
    def __init__(self):
        self.x_points = [2, 3, 4, 7]
        self.y_points = [2, 1, 3, 8]
        self.derivative_1 = -2
        self.derivative_2 = 2

    def plot_the_graph(self, list_with_x, list_with_y):
        pass

    def calculate_the_h_delta(self):
        list_h = [self.x_points[iterable] - self.x_points[iterable - 1] for iterable in range(1, len(self.x_points), 1)]
        list_delta = [(self.y_points[iterable] - self.y_points[iterable - 1])/list_h[iterable - 1] for iterable in range(1, len(self.y_points), 1)]
        #print(list_h, '\n', list_delta)
        return list_h, list_delta

    def calculate_the_list(self):
        list_h, list_delta = self.calculate_the_h_delta()
        list_of_unsolved_equations = [[] for tmp in range(0, len(self.y_points),1)]
        for tmp_rows in range(0, len(list_of_unsolved_equations),1):
            for tmp_columns in range(0, len(list_of_unsolved_equations),1):
                if 0 < (tmp_rows == tmp_columns) < len(list_of_unsolved_equations) :
                    list_of_unsolved_equations[tmp_rows][tmp_columns].append(list_h[tmp_rows] + list_h[tmp_rows + 1])
                elif tmp_rows == tmp_columns == 0:
                    list_of_unsolved_equations[tmp_rows][tmp_columns].append(2*list_h[tmp_rows])
                elif tmp_rows == tmp_columns == len(list_of_unsolved_equations) - 1:
                    list_of_unsolved_equations[tmp_rows][tmp_columns].append(2*list_h[len(list_h) - 1])
                elif (tmp_rows - tmp_columns) == 1:
                    list_of_unsolved_equations[tmp_rows][tmp_columns].append(list_h[tmp_rows])
                    list_of_unsolved_equations[tmp_columns][tmp_rows].append(list_h[tmp_rows])
                else:
                    list_of_unsolved_equations[tmp_columns][tmp_rows].append(0)
        print(list_of_unsolved_equations)
        return 0

a = Spline_Interpolation().calculate_the_list()


def calculate():
    x_points = [ 2, 3, 4, 7]
    y_points = [ 2, 1, 3, 8]
    cs = interpolate.CubicSpline(x_points, y_points, bc_type = ((1, -2), (1, 2)))
    xnew=np.linspace(np.min(x_points),np.max(x_points),100)
    ynew=cs(xnew)
    plt.plot(xnew,ynew, label = 'S')
    plt.plot(xnew,cs(xnew,1), label = 'S\'')
    plt.plot(x_points, y_points, 'o');
    plt.show();
#a = calculate()