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demo_corr.py
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# This code is supporting material for the book
# Building Machine Learning Systems with Python
# by Willi Richert and Luis Pedro Coelho
# published by PACKT Publishing
#
# It is made available under the MIT License
import os
from matplotlib import pylab
import numpy as np
import scipy
from scipy.stats import norm, pearsonr
from utils import CHART_DIR
def _plot_correlation_func(x, y):
r, p = pearsonr(x, y)
title = "Cor($X_1$, $X_2$) = %.3f" % r
pylab.scatter(x, y)
pylab.title(title)
pylab.xlabel("$X_1$")
pylab.ylabel("$X_2$")
f1 = scipy.poly1d(scipy.polyfit(x, y, 1))
pylab.plot(x, f1(x), "r--", linewidth=2)
# pylab.xticks([w*7*24 for w in [0,1,2,3,4]], ['week %i'%(w+1) for w in
# [0,1,2,3,4]])
def plot_correlation_demo():
np.random.seed(0) # to reproduce the data later on
pylab.clf()
pylab.figure(num=None, figsize=(8, 8))
x = np.arange(0, 10, 0.2)
pylab.subplot(221)
y = 0.5 * x + norm.rvs(1, scale=.01, size=len(x))
_plot_correlation_func(x, y)
pylab.subplot(222)
y = 0.5 * x + norm.rvs(1, scale=.1, size=len(x))
_plot_correlation_func(x, y)
pylab.subplot(223)
y = 0.5 * x + norm.rvs(1, scale=1, size=len(x))
_plot_correlation_func(x, y)
pylab.subplot(224)
y = norm.rvs(1, scale=10, size=len(x))
_plot_correlation_func(x, y)
pylab.autoscale(tight=True)
pylab.grid(True)
filename = "corr_demo_1.png"
pylab.savefig(os.path.join(CHART_DIR, filename), bbox_inches="tight")
pylab.clf()
pylab.figure(num=None, figsize=(8, 8))
x = np.arange(-5, 5, 0.2)
pylab.subplot(221)
y = 0.5 * x ** 2 + norm.rvs(1, scale=.01, size=len(x))
_plot_correlation_func(x, y)
pylab.subplot(222)
y = 0.5 * x ** 2 + norm.rvs(1, scale=.1, size=len(x))
_plot_correlation_func(x, y)
pylab.subplot(223)
y = 0.5 * x ** 2 + norm.rvs(1, scale=1, size=len(x))
_plot_correlation_func(x, y)
pylab.subplot(224)
y = 0.5 * x ** 2 + norm.rvs(1, scale=10, size=len(x))
_plot_correlation_func(x, y)
pylab.autoscale(tight=True)
pylab.grid(True)
filename = "corr_demo_2.png"
pylab.savefig(os.path.join(CHART_DIR, filename), bbox_inches="tight")
if __name__ == '__main__':
plot_correlation_demo()