numpy.sqrt()

numpy.sqrt(x[, out]) =

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

Parameters:

Parameters:	x : array_like The values whose square-roots are required. out : ndarray, optional Alternate array object in which to put the result; if provided, it must have the same shape as `x`
Returns:	y : ndarray An array of the same shape as `x`, containing the positive square-root of each element in `x`. If any element in `x` is complex, a complex array is returned (and the square-roots of negative reals are calculated). If all of the elements in `x` are real, so is `y`, with negative elements returning `nan`. If `out` was provided, `y` is a reference to it.

x : array_like

The values whose square-roots are required.

out : ndarray, optional

Alternate array object in which to put the result; if provided, it must have the same shape as x

Returns:

y : ndarray

An array of the same shape as x, containing the positive square-root of each element in x. If any element in x is complex, a complex array is returned (and the square-roots of negative reals are calculated). If all of the elements in x are real, so is y, with negative elements returning nan. If out was provided, y is a reference to it.

Notes

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.

Examples

>>> 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])

Links:

https://docs.scipy.org/doc/numpy-1.11.0/reference/generated/numpy.sqrt.html

doc_NumPy

2025-01-10 15:47:30

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