If a is an n-dimensional numpy array a[..., j] will return an (n-1)-dimensional numpy array where each innermost subarray is replaced by its jth element. So for example if a is 2-dimensional, a[..., j] will be a 1-dimensional array containing the jth column of each row.
Nothing in Python, looks like pseudo code.
Actually, ... is perfectly valid Python syntax - it's just not used anywhere except by numpy and scipy.
I'm not sure I understand your question. The values for j and k will not affect the size of the resulting arrays. If a is an array of size n*m then a[ ..., j ] is an array of size n, no matter what the value of j is.
Or more generally: a[ ..., j ].shape == a.shape[ : -1 ] for all multi-dimensional arrays a and all valid indices j.
I have a 2d matrix with dimension (3, n) called A, I want to calculate the normalization and cross product of two arrays (b,z) (see the code please) for each column (for the first column, then the second one and so on).
the function that I created to find the ...
Write a C program that should create a 10 element array of random integers (0 to 9). The program should total all of the numbers in the odd positions of the array and compare them with the total of the numbers in the even positions of the array and indicate ...