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
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What is the most concise and pythonic way to do this?
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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.