cupy.ravel_multi_index#
- cupy.ravel_multi_index(multi_index, dims, mode='wrap', order='C')[source]#
Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index.
- Parameters:
multi_index (tuple of cupy.ndarray) – A tuple of integer arrays, one array for each dimension.
dims (tuple of ints) – The shape of array into which the indices from
multi_index
apply.mode ('raise', 'wrap' or 'clip') –
Specifies how out-of-bounds indices are handled. Can specify either one mode or a tuple of modes, one mode per index:
’raise’ – raise an error
’wrap’ – wrap around (default)
’clip’ – clip to the range
In ‘clip’ mode, a negative index which would normally wrap will clip to 0 instead.
order ('C' or 'F') – Determines whether the multi-index should be viewed as indexing in row-major (C-style) or column-major (Fortran-style) order.
- Returns:
An array of indices into the flattened version of an array of dimensions
dims
.- Return type:
raveled_indices (cupy.ndarray)
Warning
This function may synchronize the device when
mode == 'raise'
.Notes
Note that the default mode (
'wrap'
) is different than in NumPy. This is done to avoid potential device synchronization.Examples
>>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (7,6)) array([22, 41, 37]) >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (7,6), ... order='F') array([31, 41, 13]) >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (4,6), ... mode='clip') array([22, 23, 19]) >>> cupy.ravel_multi_index(cupy.asarray([[3,6,6],[4,5,1]]), (4,4), ... mode=('clip', 'wrap')) array([12, 13, 13]) >>> cupy.ravel_multi_index(cupy.asarray((3,1,4,1)), (6,7,8,9)) array(1621)
See also