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3e589aa Feb 12, 2016
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#!/usr/bin/env python
(C) 2016 Nikolay Manchev, [CleverOwl blog](http://
This work is licensed under the Creative Commons Attribution 4.0 International
License. To view a copy of this license, visit
from math import pi
from math import sin
import matplotlib.pyplot as plt
import numpy as np
def corr_vars( start=-10, stop=10, step=0.5, mu=0, sigma=3, func=lambda x: x ):
Generates a data set of (x,y) pairs with an underlying regularity. y is a
function of x in the form of
y = f(x) + e
Where f(x) is specified by the *func* argument and e is a random Gaussian
noise specified by *mu* and *sigma*.
Keyword arguments:
*start* : number, optional
Start of the x interval. Defaults to -10.
*stop* : number, optional
End of the x interval. Defaults to 10.
*step* : number, optional
Spacing between x values. Defaults to 0.5.
*mu* : number, optional
Mean of the distribution generating the noise. Defaults to 0.
*sigma* : number, optional
Standard deviation of the distribution generating the noise.
Defaults to 3.
*func* : function, optional
Function for calculating the y values using x. Defaults to y = x.
x,y : tuple
- *x* is a Numpy array of values in [*start*, *stop*]
- *y* is calculated as y = *func* (x) + e
(x,y) = corr_vars(sigma=3, func=lambda x: 2*pi*sin(x))
# Generate x
x = np.arange(start, stop, step)
# Generate random noise
e = np.random.normal(mu, sigma, x.size)
# Generate y values as y = func(x) + e
y = np.zeros(x.size)
for ind in range(x.size):
y[ind] = func(x[ind]) + e[ind]
return (x,y)
def main():
(x0,y0) = corr_vars(sigma=3)
(x1,y1) = corr_vars(sigma=3, func=lambda x: 2*pi*sin(x))
f, axarr = plt.subplots(2, sharex=True, figsize=(7,7))
axarr[0].scatter(x0, y0)
axarr[0].plot(x0, x0, color='r')
axarr[0].set_title('y = x + e')
axarr[1].scatter(x1, y1)
axarr[1].plot(x1, 2*pi*np.sin(x1), color='r')
axarr[1].set_title('y = 2*π*sin(x) + e')
if __name__ == "__main__":