xarray.ufuncs.conj#
- xarray.ufuncs.conj = <xarray.ufuncs._unary_ufunc object>#
xarray specific variant of
numpy.conj()
. Handles xarray objects by dispatching to the appropriate function for the underlying array type.Documentation from numpy:
Return the complex conjugate, element-wise.
The complex conjugate of a complex number is obtained by changing the sign of its imaginary part.
- Parameters
x (array_like) – Input value.
out (
ndarray
,None
, ortuple
ofndarray
andNone
, 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 None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.where (array_like, optional) – This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default
out=None
, locations within it where the condition is False will remain uninitialized.**kwargs – For other keyword-only arguments, see the ufunc docs.
- Returns
y (
ndarray
) – The complex conjugate of x, with same dtype as y. This is a scalar if x is a scalar.
Notes
conj is an alias for conjugate:
>>> np.conj is np.conjugate True
Examples
>>> np.conjugate(1+2j) (1-2j)
>>> x = np.eye(2) + 1j * np.eye(2) >>> np.conjugate(x) array([[ 1.-1.j, 0.-0.j], [ 0.-0.j, 1.-1.j]])