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Description
This is a tracker for a number of requests for making working with complex numbers a bit easier/faster
- Get just the normalized number
z/|z|(the sgn function) (see API,ENH: Change definition of complex sign #25441, which changes the behaviour ofnp.signto match the Array API and extends it tocopysign) - Get the squared modulus of a complex number
z * z.conj()(instead of the slownp.abs(z)**2).squaremight be logical but is already defined to just doz*z... (see abs() is slow for complex, add abs2() #3994) - A fast way to get the inverse of
angle, i.e.,exp(1j * a) = cos(a) + 1j * sin(a). Note that for large angle arrays,exp(1j*a)needlessly triples memory use for the input (see Have anexpfor pure imaginary numbers #5625; somewhat related:sincosfunction, see Implement sincos() (Trac #2034) #2626; discussion moved to ENH: Create a place for "optimization" ufuncs #18483) - Possibly, combined
absandangleand their inverse, perhaps most logical as part of providing polar to cartesian transformations (see ENH: Add to numpy simple functions for transform coordinate systems #5228)
EDIT (2021-Jun-25): if there is worry about making the numpy API too big, one option might be to make this part of numpy.lib.scimath (which I must admit I didn't know about until today; I see now that it should be np.emath - https://numpy.org/devdocs/reference/routines.emath.html). Though perhaps that should stay reserved for complex continuations real->complex like for sqrt.