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https://github.com/Visualize-ML/Book4_Power-of-Matrix.git
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53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
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###############
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# Authored by Weisheng Jiang
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# Book 4 | From Basic Arithmetic to Machine Learning
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# Published and copyrighted by Tsinghua University Press
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# Beijing, China, 2022
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###############
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# Bk4_Ch3_01.py
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import matplotlib.pyplot as plt
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import numpy as np
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p_values = [0.05, 0.2, 0.5, 1, 1.5, 2, 4, 8, np.inf]
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x1 = np.linspace(-2.5, 2.5, num=101);
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x2 = x1;
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xx1, xx2 = np.meshgrid(x1,x2)
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fig, axes = plt.subplots(ncols=3,nrows=3,
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figsize=(12, 12))
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for p, ax in zip(p_values, axes.flat):
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if np.isinf(p):
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zz = np.maximum(np.abs(xx1),np.abs(xx2))
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else:
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zz = ((np.abs((xx1))**p) + (np.abs((xx2))**p))**(1./p)
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# plot contour of Lp
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ax.contourf(xx1, xx2, zz, 20, cmap='RdYlBu_r')
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# plot contour of Lp = 1
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ax.contour (xx1, xx2, zz, [1], colors='k', linewidths = 2)
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# decorations
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ax.axhline(y=0, color='k', linewidth = 0.25)
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ax.axvline(x=0, color='k', linewidth = 0.25)
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ax.set_xlim(-2.5, 2.5)
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ax.set_ylim(-2.5, 2.5)
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ax.spines['top'].set_visible(False)
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ax.spines['right'].set_visible(False)
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ax.spines['bottom'].set_visible(False)
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ax.spines['left'].set_visible(False)
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ax.set_xlabel('$x_1$')
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ax.set_ylabel('$x_2$')
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ax.set_title('p = ' + str(p))
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ax.set_aspect('equal', adjustable='box')
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plt.show()
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