numpy.sqrt#

numpy.sqrt(x,/,out=None,*,where=True,casting='same_kind',order='K',dtype=None,subok=True[,signature])=<ufunc'sqrt'>#

Return the non-negative square-root of an array, element-wise.

Parameters:
xarray_like

The values whose square-roots are required.

outndarray, None, or tuple of ndarray and None, optional

A location into which the result is stored. If provided, it must havea shape that the inputs broadcast to. If not provided or None,a freshly-allocated array is returned. A tuple (possible only as akeyword argument) must have length equal to the number of outputs.

wherearray_like, optional

This condition is broadcast over the input. At locations where thecondition is True, theout array will be set to the ufunc result.Elsewhere, theout array will retain its original value.Note that if an uninitializedout array is created via the defaultout=None, locations within it where the condition is False willremain uninitialized.

**kwargs

For other keyword-only arguments, see theufunc docs.

Returns:
yndarray

An array of the same shape asx, containing the positivesquare-root of each element inx. If any element inx iscomplex, a complex array is returned (and the square-roots ofnegative reals are calculated). If all of the elements inxare real, so isy, with negative elements returningnan.Ifout was provided,y is a reference to it.This is a scalar ifx is a scalar.

See also

emath.sqrt

A version which returns complex numbers when given negative reals. Note that 0.0 and -0.0 are handled differently for complex inputs.

Notes

sqrt has–consistent with common convention–as its branch cut thereal “interval” [-inf, 0), and is continuous from above on it.A branch cut is a curve in the complex plane across which a givencomplex function fails to be continuous.

Examples

>>>importnumpyasnp>>>np.sqrt([1,4,9])array([ 1.,  2.,  3.])
>>>np.sqrt([4,-1,-3+4J])array([ 2.+0.j,  0.+1.j,  1.+2.j])
>>>np.sqrt([4,-1,np.inf])array([ 2., nan, inf])
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