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numpy.searchsorted(a, v, side='left', sorter=None)
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Find indices where elements should be inserted to maintain order.
Find the indices into a sorted array
a
such that, if the corresponding elements inv
were inserted before the indices, the order ofa
would be preserved.Parameters: a : 1-D array_like
Input array. If
sorter
is None, then it must be sorted in ascending order, otherwisesorter
must be an array of indices that sort it.v : array_like
Values to insert into
a
.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
a
).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
v
.Notes
Binary search is used to find the required insertion points.
As of Numpy 1.4.0
searchsorted
works with real/complex arrays containingnan
values. The enhanced sort order is documented insort
.Examples
>>> 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])
numpy.searchsorted()
2017-01-10 18:18:37
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