First row of numpy.ones is still populated after referencing another matrix

Question

I have a matrix \'A\' whose values are shown below. After creating a matrix \'B\' of ones using numpy.ones and assigning the values from \'A\' to \'B\' by indexing \'i\' rows an

Answer 1

For one thing, as others have mentioned, NumPy uses 0-based indexing. But even once you fix that, this is not what you want to use:

for i in np.arange(9):
    for j in np.arange(9):
        B[i:j] = A[i:j]

The : indicates slicing, so i:j means "all items from the i-th, up to the j-th, excluding the last one." So your code is copying every row over several times, which is not a very efficient way of doing things.

You probable wanted to use ,:

for i in np.arange(8): # Notice the range only goes up to 8
    for j in np.arange(8): # ditto
        B[i, j] = A[i, j]

This will work, but is also pretty wasteful performancewise when using NumPy. A much faster approach is to simply ask for:

B[:] = A