Delete Bk4_Ch14_04.py

Book4_Ch14_Python_Codes/Bk4_Ch14_04.py

@@ -1,70 +0,0 @@
-
-###############
-# Authored by Weisheng Jiang
-# Book 4  |  From Basic Arithmetic to Machine Learning
-# Published and copyrighted by Tsinghua University Press
-# Beijing, China, 2022
-###############
-
-# Bk4_Ch14_04.py
-
-import numpy as np
-import matplotlib.pyplot as plt
-
-theta = np.deg2rad(30)
-
-r = 0.8 # 1.2, scaling factor
-
-R = np.array([[np.cos(theta), -np.sin(theta)],
-              [np.sin(theta),  np.cos(theta)]])
-
-S = np.array([[r, 0],
-              [0, r]])
-
-A = R@S
-
-# A = np.array([[1, -1],
-#               [1, 1]])
-
-Lamb, V = np.linalg.eig(A)
-
-theta_array = np.arange(0,np.pi*2,np.pi*2/18)
-
-
-colors = plt.cm.rainbow(np.linspace(0,1,len(theta_array)))
-
-
-fig, ax = plt.subplots()
-
-for j, theat_i in enumerate(theta_array):
-    
-    # initial point
-    x = np.array([[5*np.cos(theat_i)],
-                  [5*np.sin(theat_i)]])
-
-    plt.plot(x[0],x[1], 
-             marker = 'x',color = colors_j,
-             markersize = 15)
-    # plot the initial point
-    
-    x_array = x
-
-    for i in np.arange(20):
-
-        x = A@x
-        x_array = np.column_stack((x_array,x))
-
-
-    colors_j = colors[j,:]
-    plt.plot(x_array[0,:],x_array[1,:], 
-             marker = '.',color = colors_j)
-
-
-plt.axis('scaled')
-
-ax.spines['top'].set_visible(False)
-ax.spines['right'].set_visible(False)
-ax.spines['bottom'].set_visible(False)
-ax.spines['left'].set_visible(False)
-ax.axvline(x=0,color = 'k')
-ax.axhline(y=0,color = 'k')