numpy.sqrt(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'sqrt'>
Return the positive square-root of an array, element-wise.
Parameters: |
x : array_like The values whose square-roots are required. out : ndarray, None, or tuple of ndarray and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs. |
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Returns: |
y : ndarray An array of the same shape as |
See also
lib.scimath.sqrt
sqrt has–consistent with common convention–as its branch cut the real “interval” [-inf
, 0), and is continuous from above on it. A branch cut is a curve in the complex plane across which a given complex function fails to be continuous.
>>> 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, numpy.inf]) array([ 2., NaN, Inf])
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https://docs.scipy.org/doc/numpy-1.14.2/reference/generated/numpy.sqrt.html