I have a 2D numpy array "bigrams" of shape (851, 851) with float values inside. I want to get the top ten values from this array and I want their coordinates.
I know that np.amax(bigrams) can return the single highest value, so that's basically what I want but then for the top ten.
As a numpy-noob, I wrote some code using a loop to get the top values per row and then using np.where() to get the coordinates, but i feel there must be a smarter way to solve this..
You can flatten and use argsort.
idxs = np.argsort(bigrams.ravel())[-10:]
rows, cols = idxs//851, idxs%851
print(bigrams[rows,cols])
An alternative would be to do a partial sorting with argpartition.
partition = np.argpartition(bigrams.ravel(),-10)[-10:]
max_ten = bigrams[partition//851,partition%851]
You will get the top ten values and their coordinates, but they won't be sorted. You can sort this smaller array of ten values later if you want.
np.unravel_index() to get back to the original 2D array's coordinates. That feels a bit more descriptive to me.