How to create a 2D numpy array from a block of strings

Question

With list comprehension, I am able to take a 20x20 block of numbers in string format, and convert it to a list of lists of integers. The numbers are seperated by white space and the lines are seperated by a newline.

grid = [[int(x) for x in line.split()] for line in nums.split('\n')]

However, what I want is to use numpy for its speed. I could use np.asarray() with my intermediate list, but I don't think that is efficient use of numpy.

I also tried using np.fromstring(), but I can't figure out the logic to make it work for a 2D array.

Is there any way to accomplish this task without the use of creating intermediate python lists?

Answer 1

You could use np.fromstring setting a space as separator and reshape to the desired shape:

np.fromstring(s, sep=' ').reshape(20, 20)

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Or as a more general solution:

rows = s.count('\n') + 1
np.fromstring(s, sep=' ').reshape(-1, rows)

Answer 2

More general for any 2D grid:

rows = s.count('\n') + 1
np.fromstring(s, sep=' ').reshape(rows, -1)