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I am dealing with arrays created via numpy.array(), and I need to draw points on a canvas simulating an image. Since there is a lot of zero values around the central part of the array which contains the meaningful data, I would like to "trim" the array, erasing columns that only contain zeros and rows that only contain zeros.
So, I would like to know of some native numpy function or even a code snippet to "trim" or find a "bounding box" to slice only the data-containing part of the array.
(since it is a conceptual question, I did not put any code, sorry if I should, I'm very fresh to posting at SO.)
Thanks for reading
744
nonzero() function is used to Compute the indices of the elements that are non-zero. It returns a tuple of arrays, one for each dimension of arr, containing the indices of the non-zero elements in that dimension. The corresponding non-zero values in the array can be obtained with arr[nonzero(arr)] .
The array object in NumPy is called ndarray . We can create a NumPy ndarray object by using the array() function.
numpy. array is just a convenience function to create an ndarray ; it is not a class itself. You can also create an array using numpy. ndarray , but it is not the recommended way.
This should do it:
from numpy import array, argwhere A = array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]]) B = argwhere(A) (ystart, xstart), (ystop, xstop) = B.min(0), B.max(0) + 1 Atrim = A[ystart:ystop, xstart:xstop] If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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