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import numpy as np;

import matplotlib.pyplot as plt;

from UnaryLinearRegression import *;

def __run(x, y):

lr = UnaryLinearRegression();

lr.fit(x, y);

lr.sigLevel = None;

return lr;

def __show(x, y, line):

plt.figure(1, (16, 10));

plt.scatter(x.A.flatten().tolist(), y.A.flatten().tolist(), marker = "x");

plt.plot([x.min(), x.max()], [line.predictValue(x.min()), line.predictValue(x.max())], color = "r");

plt.show();

def testUnaryLinearRegression():

data = np.mat(np.loadtxt("data/advertising.txt", delimiter = ","));

y = data[:, -1];

x = data[:, 1];

tv = __run(x, y);

tv.predictInterval(x[0, 0]);

tv.predictInterval(x);

__show(x, y, tv);

print("tv: ");

print(tv);

print("");

x = data[:, 2];

radio = __run(x, y);

radio.predictInterval(x[0, 0]);

radio.predictInterval(x);

__show(x, y, radio);

print("radio: ");

print(radio);

print("");

x = data[:, 3];

newspaper = __run(x, y);

newspaper.predictInterval(x[0, 0]);

newspaper.predictInterval(x);

__show(x, y, newspaper);

print("newspaper: ");

print(newspaper);

print("");