numpy.ravel_multi_index#

numpy.ravel_multi_index(multi_index, dims, mode='raise', order='C')#

Converts a tuple of index arrays into an array of flat indices, applying boundary modes to the multi-index.

Parameters:
multi_indextuple of array_like

A tuple of integer arrays, one array for each dimension.

dimstuple of ints

The shape of array into which the indices from multi_index apply.

mode{‘raise’, ‘wrap’, ‘clip’}, optional

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 (default)

  • ‘wrap’ – wrap around

  • ‘clip’ – clip to the range

In ‘clip’ mode, a negative index which would normally wrap will clip to 0 instead.

order{‘C’, ‘F’}, optional

Determines whether the multi-index should be viewed as indexing in row-major (C-style) or column-major (Fortran-style) order.

Returns:
raveled_indicesndarray

An array of indices into the flattened version of an array of dimensions dims.

See also

unravel_index

Examples

>>> import numpy as np
>>> arr = np.array([[3,6,6],[4,5,1]])
>>> np.ravel_multi_index(arr, (7,6))
array([22, 41, 37])
>>> np.ravel_multi_index(arr, (7,6), order='F')
array([31, 41, 13])
>>> np.ravel_multi_index(arr, (4,6), mode='clip')
array([22, 23, 19])
>>> np.ravel_multi_index(arr, (4,4), mode=('clip','wrap'))
array([12, 13, 13])

>>> np.ravel_multi_index((3,1,4,1), (6,7,8,9))
1621
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