CH05_SEC02_1_Fig5p7_Fig5p8.ipynb

Kernel: Python 3

import numpy as np
import matplotlib.pyplot as plt
from matplotlib import rcParams

rcParams.update({'font.size': 18})
plt.rcParams['figure.figsize'] = [12, 12]

# Training and test set sizes
n1 = 100 # Training set size
n2 = 50  # Test set size

# Random ellipse 1 centered at (-2,0)
x = np.random.randn(n1+n2) - 2
y = 0.5*np.random.randn(n1+n2)

# Random ellipse 5 centered at (1,0)
x5 = 2*np.random.randn(n1+n2) + 1
y5 = 0.5*np.random.randn(n1+n2)

# Random ellipse 2 centered at (2,-2)
x2 = np.random.randn(n1+n2) + 2
y2 = 0.2*np.random.randn(n1+n2) - 2

# Rotate ellipse 2 by theta
theta = np.pi/4
A = np.zeros((2,2))
A[0,0] = np.cos(theta)
A[0,1] = -np.sin(theta)
A[1,0] = np.sin(theta)
A[1,1] = np.cos(theta)

x3 = A[0,0]*x2 + A[0,1]*y2
y3 = A[1,0]*x2 + A[1,1]*y2

fig,axs = plt.subplots(2,2)
axs = axs.reshape(-1)

axs[0].plot(x[:n1],y[:n1],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)
axs[0].plot(x3[:n1],y3[:n1],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)


axs[1].plot(x[:70],y[:70],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)
axs[1].plot(x3[:70],y3[:70],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)
axs[1].plot(x[70:100],y[70:100],'o',markerfacecolor=(0,1,0.2),markeredgecolor='k',ms=15)
axs[1].plot(x3[70:100],y3[70:100],'o',markerfacecolor=(0.9,0,1),markeredgecolor='k',ms=15)

axs[2].plot(x5[:n1],y5[:n1],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)
axs[2].plot(x3[:n1],y3[:n1],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)

axs[3].plot(x5[:70],y5[:70],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)
axs[3].plot(x3[:70],y3[:70],'o',markerfacecolor=(0.8,0.8,0.8),markeredgecolor='k',ms=15)
axs[3].plot(x5[70:100],y5[70:100],'o',markerfacecolor=(0,1,0.2),markeredgecolor='k',ms=15)
axs[3].plot(x3[70:100],y3[70:100],'o',markerfacecolor=(0.9,0,1),markeredgecolor='k',ms=15)

for ax in axs:
    ax.set_xlim(-6,6)
    ax.set_ylim(-2,2)

plt.show()

n1 = 300 # training set size
x1 = 1.5*np.random.randn(n1)-1.5
y1 = 1.2*np.random.randn(n1)+np.power(x1+1.5,2)-7
x2 = 1.5*np.random.randn(n1)+1.5
y2 = 1.2*np.random.randn(n1)-np.power(x2-1.5,2)+7

fig,axs = plt.subplots(2)
axs[0].plot(x1,y1,'o',markerfacecolor=(0,1,0.2),markeredgecolor='k',ms=15)
axs[0].plot(x2,y2,'o',markerfacecolor=(0.9,0,1),markeredgecolor='k',ms=15)
axs[0].set_xlim(-6,6)
axs[0].set_ylim(-12,12)

r = 7 + np.random.randn(n1)
th = 2*np.pi*np.random.randn(n1)
xr = r * np.cos(th)
yr = r * np.sin(th)

x5 = np.random.randn(n1)
y5 = np.random.randn(n1)

axs[1].plot(xr,yr,'o',markerfacecolor=(0,1,0.2),markeredgecolor='k',ms=15)
axs[1].plot(x5,y5,'o',markerfacecolor=(0.9,0,1),markeredgecolor='k',ms=15)
axs[1].set_xlim(-10,10)
axs[1].set_ylim(-10,10)

plt.show()