Scattered plot Numpy Matplot

Question

I'm trying to make a line with scattered points around the function y = 2x. The points should have a random deviation between -0.5 and 0.5 compared to the normal function (which is f(x)):

def f(x):
    return 2 * x

def g(x):
    return f(x) - np.random.uniform(-0.5, 0.5)

x = np.linspace(0, 5, 51)
y = f(x)
y2 = g(x)

# plot
plt.plot(t, y, 'b-')
plt.plot(t, y, 'ro')
plt.show()

And ofcourse, y2 will now be a scattered line where all the points have the same deviation because the random number is the same for all the points. Now I wonder how I could make it so each point will have a random deviation (so how can I perform an action on each point individualy). Thanks in advance!

xnx · Accepted Answer · 2016-01-10 13:57:15Z

1

Yes: pass size=(51,) (or better, use the shape of the x array) to np.random.uniform() to draw that many samples from the uniform distribution:

import numpy as np
import matplotlib.pyplot as plt
def f(x):
    return 2 * x

def g(x):
    return f(x) - np.random.uniform(-0.5, 0.5, size=x.shape)

x = np.linspace(0, 5, 51)
y = f(x)
y2 = g(x)

# plot
plt.plot(x, y, 'b-')
plt.plot(x, y2, 'ro')
plt.show()

answered Jan 10, 2016 at 13:57

xnx

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