numpy.ma.indices — NumPy v1.11 Manual (original) (raw)
numpy.ma.indices(dimensions, dtype=<type 'int'>)[source]¶
Return an array representing the indices of a grid.
Compute an array where the subarrays contain index values 0,1,... varying only along the corresponding axis.
| Parameters: | dimensions : sequence of ints The shape of the grid. dtype : dtype, optional Data type of the result. |
|---|---|
| Returns: | grid : ndarray The array of grid indices,grid.shape = (len(dimensions),) + tuple(dimensions). |
Notes
The output shape is obtained by prepending the number of dimensions in front of the tuple of dimensions, i.e. if dimensions is a tuple(r0, ..., rN-1) of length N, the output shape is(N,r0,...,rN-1).
The subarrays grid[k] contains the N-D array of indices along thek-th axis. Explicitly:
grid[k,i0,i1,...,iN-1] = ik
Examples
grid = np.indices((2, 3)) grid.shape (2, 2, 3) grid[0] # row indices array([[0, 0, 0], [1, 1, 1]]) grid[1] # column indices array([[0, 1, 2], [0, 1, 2]])
The indices can be used as an index into an array.
x = np.arange(20).reshape(5, 4) row, col = np.indices((2, 3)) x[row, col] array([[0, 1, 2], [4, 5, 6]])
Note that it would be more straightforward in the above example to extract the required elements directly with x[:2, :3].