StatRed: finished multivariate (question 21).

parent c35ec4b5
from pylab import array, eig, diagflat, dot, sqrt, randn, tile from pylab import array, eig, diagflat, dot, sqrt, randn, tile, \
from pylab import plot, axis, show, figure, clf plot, subplot, axis, show, figure, clf
mean = array([[3], mean = array([[3],
[4], [4],
...@@ -15,7 +15,7 @@ cov = array( ...@@ -15,7 +15,7 @@ cov = array(
samples = 1000 samples = 1000
vector_size = 4 vector_size = 4
figure(1) figure(16)
clf() clf()
d, U = eig(cov) d, U = eig(cov)
...@@ -24,21 +24,11 @@ A = dot(U, sqrt(L)) ...@@ -24,21 +24,11 @@ A = dot(U, sqrt(L))
X = randn(vector_size, samples) X = randn(vector_size, samples)
Y = dot(A,X) + tile(mean, samples) Y = dot(A,X) + tile(mean, samples)
#import matplotlib.pyplot as plt for i in range(1, 5):
for i in range(4): for j in range(1, 5):
for j in range(4):
if i != j: if i != j:
plot(Y[i], Y[j], 'x') subplot(4, 4, i+(j-1)*4)
plot(Y[i-1], Y[j-1], 'x')
axis('equal')
axis('equal')
#plt.plot(x,y,'x');
#plt.axis('equal');
#plt.show()
show() show()
#import numpy as np
#x,y = np.random.multivariate_normal(mean, cov, 5000).T
#print 'x:', x
#print 'y:', y
#plt.plot(x,y,'x'); plt.axis('equal'); plt.show()
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