how to generate an np.array with values uniformly distributed in a certain range

Question

I want to generate an array called T with K points on this plot (in this case, K is 3). What I have so far is an array that has both x and y coordinates randomly generated in a certain range.

T = np.random.uniform(low=0.5, high=13.3, size=(K,N))

What I want, however, is to have the x coordinates be generated in a different range from the y coordinates such that the region populated by T is defined by (-15 < x < 0) and (-6 < y < 12). The context here is that T (shown in blue) is the initial centroids in K-means clustering and I want my initial centroids to start off close to my data which happens to lie in the (-15 < x < 0) and (-6 < y < 12) region.

ThomasL · Accepted Answer · 2021-03-21 17:12:50Z

1

The function numpy.random.uniform can have different ranges :

import numpy as np 

N = 3
K = 2

T = np.random.uniform([-15,-6],[0,12],(N,K)).T
print(T)

>> [[-12.43132509  -4.86842272  -3.60063107]
    [1.88880676   4.14855554   6.34750037]]

answered Mar 21, 2021 at 17:12

ThomasL

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