View difference between Paste ID: bNVcQt4x and xrabXgrk

 #!/usr/bin/env python
 
 import numpy as np
 from matplotlib import pyplot as plt
 
 data_fname = 'knot_points.csv'
 # x1,y1
 # x2,y2
 # ...
 
 def read_data(fname):
     X = []
     Y = []
     with open(fname, 'r') as f:
         for line in f:
             (x, y) = line.split(',')
             X.append(float(x))
             Y.append(float(y))
     return (X, Y)
 
 def langrange_polynomial(X, Y):
     def L(i):
         return lambda x: np.prod([(x-X[j])/(X[i]-X[j]) for j in range(len(X)) if i != j]) * Y[i]
     Sx = [L(i) for i in range(len(X))]  # summands
     return lambda x: np.sum([s(x) for s in Sx])
 
 # F = langrange_polynomial(*read_data(data_fname))
 (X, Y) = read_data(data_fname)
 F = langrange_polynomial(X, Y)
 
 x_range = np.linspace(X[0], X[-1], 100)
 plt.plot(X, Y, 'ro')
 plt.plot(x_range, map(F, x_range))
 plt.xlabel(r'$x$')
 plt.ylabel(r'$F(x)$')
 plt.title('Lagrange polynomial interpolation')
 plt.grid(True)
 plt.show()