Replace all elements of Python NumPy Array that are greater than some value

I have a 2D NumPy array and would like to replace all values in it greater than or equal to a threshold T with 255.0. To my knowledge, the most fundamental way would be:

    shape = arr.shape
    result = np.zeros(shape)
    for x in range(0, shape[0]):
        for y in range(0, shape[1]):
            if arr[x, y] >= T:
                result[x, y] = 255
  1. What is the most concise and pythonic way to do this?

  2. Is there a faster (possibly less concise and/or less pythonic) way to do this?

This will be part of a window/level adjustment subroutine for MRI scans of the human head. The 2D numpy array is the image pixel data.

I think both the fastest and most concise way to do this is to use Numpy's builtin indexing. If you have a ndarray named arr you can replace all elements >255 with a value x as follows:

    arr[arr > 255] = x

I ran this on my machine with a 500 x 500 random matrix, replacing all values >0.5 with 5, and it took an average of 7.59ms.

    In [1]: import numpy as np
    In [2]: A = np.random.rand(500, 500)
    In [3]: timeit A[A > 0.5] = 5
    100 loops, best of 3: 7.59 ms per loop