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Delete Book4_Ch09_Python_Codes directory

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Iris Series: Visualize Math -- From Arithmetic Basics to Machine Learning
2025-02-01 17:01:17 +08:00
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parent 5fae920671
commit 639f1ed2f3
2 changed files with 0 additions and 105 deletions
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36
Book4_Ch09_Python_Codes/Bk4_Ch9_01.py
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###############
# Authored by Weisheng Jiang
# Book 4 | From Basic Arithmetic to Machine Learning
# Published and copyrighted by Tsinghua University Press
# Beijing, China, 2022
###############
# Bk4_Ch9_01.py
import numpy as np
import matplotlib.pyplot as plt
thetas = np.linspace(0,np.pi,25)
x = np.array([[4],
[3]])
fig, axes = plt.subplots()
for theta in thetas:
v = np.array([[np.cos(theta)],
[np.sin(theta)]])
proj = v.T@x
print(proj)
plt.plot([-v[0]*6, v[0]*6], [-v[1]*6, v[1]*6])
plt.plot([x[0], v[0]*proj], [x[1], v[1]*proj], color = 'k')
plt.plot(v[0]*proj, v[1]*proj, color = 'k', marker = 'x')
plt.quiver (0, 0, v[0], v[1],
angles='xy', scale_units='xy',scale=1)
plt.plot(x[0],x[1], marker = 'x', color = 'r')
plt.axis('scaled')

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Book4_Ch09_Python_Codes/Bk4_Ch9_02.py
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###############
# Authored by Weisheng Jiang
# Book 4 | From Basic Arithmetic to Machine Learning
# Published and copyrighted by Tsinghua University Press
# Beijing, China, 2022
###############
# Bk4_Ch9_02.py
import numpy as np
import matplotlib.pyplot as plt
thetas = np.array([0, 15, 30, 45, 60, 75, 90, 120, 135])
x = np.array([[4],
[3]])
i = 1
fig = plt.figure()
for theta in thetas:
theta = theta/180*np.pi
ax = fig.add_subplot(3, 3, i)
v1 = np.array([[np.cos(theta)],
[np.sin(theta)]])
proj = v1.T@x
print(proj)
plt.plot([-v1[0]*6, v1[0]*6], [-v1[1]*6, v1[1]*6])
plt.plot([x[0], v1[0]*proj], [x[1], v1[1]*proj],
color = 'k', linestyle = '--')
plt.plot(v1[0]*proj, v1[1]*proj, color = 'k', marker = 'x')
plt.quiver (0, 0, v1[0], v1[1],
angles='xy', scale_units='xy',
scale=1, color = 'b')
v2 = np.array([[-np.sin(theta)],
[np.cos(theta)]])
proj = v2.T@x
print(proj)
plt.plot([-v2[0]*6, v2[0]*6], [-v2[1]*6, v2[1]*6])
plt.plot([x[0], v2[0]*proj], [x[1], v2[1]*proj],
color = 'k', linestyle = '--')
plt.plot(v2[0]*proj, v2[1]*proj, color = 'k', marker = 'x')
plt.quiver (0, 0, v2[0], v2[1],
angles='xy', scale_units='xy',
scale=1,color = 'r')
plt.axhline(y = 0, color = 'k')
plt.axvline(x = 0, color = 'k')
plt.plot(x[0],x[1], marker = 'x', color = 'r')
plt.quiver(0, 0, x[0],x[1],
angles='xy', scale_units='xy',
scale=1, color = 'k')
plt.axis('scaled')
ax.grid(linestyle='--', linewidth=0.25, color=[0.75,0.75,0.75])
plt.xlim([-6, 6])
plt.ylim([-6, 6])
plt.xticks(np.linspace(-6,6,13))
plt.yticks(np.linspace(-6,6,13))
i = i + 1