Generate Random Number within range using Numpy

Question

I have ranges, where each tuple represents the range of a random number. e.g:

ranges = [(-1,100), (0,1), (50, 5000)]

Now, I want to create a numpy array where each element of array is randomly generated from the corresponding tuple of ranges.

Pseudo code:

rand_array = numpy.array[randomly generate element1 from (-1,100), randomly generate element2 from (0,1), randomly generate element3 from (50,500)]

Of course, naive way to do this is:

rand_array = [random.uniform(coord[0], coord[1]) for coord in ranges]

But I want to do it in numpy way, as my whole code accepts numpy array data-types. Another solution can be to convert naively generated rand_array to numpy array. But I think it is not efficient. Is there a numpy way of doing this?

Paul Panzer · Accepted Answer · 2020-07-06 08:05:21Z

4

Most random functions accept array parameters. So you can do

np.random.uniform(*np.transpose(ranges))

The usual broadcasting rules apply, for example, to get 10 triplets

np.random.uniform(*np.transpose(ranges),(10,3))

edited Jul 6, 2020 at 8:05

answered Jul 6, 2020 at 7:53

Paul Panzer

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1 Comment

foobar Over a year ago

thanks. How to generate x number of elements in this way? is there a way to do this like this: np.random.uniform(x, *np.transpose(ranges)) (where x is an integer specifying numebr of elements or rows of numpy array). Sorry, I forgot to include that in question.

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