numpy.searchsorted(a, v, side='left', sorter=None)
[source]
Find indices where elements should be inserted to maintain order.
Find the indices into a sorted array a
such that, if the corresponding elements in v
were inserted before the indices, the order of a
would be preserved.
Parameters: |
a : 1-D array_like Input array. If v : array_like Values to insert into side : {‘left’, ‘right’}, optional If ‘left’, the index of the first suitable location found is given. If ‘right’, return the last such index. If there is no suitable index, return either 0 or N (where N is the length of sorter : 1-D array_like, optional Optional array of integer indices that sort array a into ascending order. They are typically the result of argsort. New in version 1.7.0. |
---|---|
Returns: |
indices : array of ints Array of insertion points with the same shape as |
Binary search is used to find the required insertion points.
As of NumPy 1.4.0 searchsorted
works with real/complex arrays containing nan
values. The enhanced sort order is documented in sort
.
>>> np.searchsorted([1,2,3,4,5], 3) 2 >>> np.searchsorted([1,2,3,4,5], 3, side='right') 3 >>> np.searchsorted([1,2,3,4,5], [-10, 10, 2, 3]) array([0, 5, 1, 2])
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https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.searchsorted.html