Update 7542, ENH: Add polyrootval to numpy.polynomial
#7734
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As one can easily encounter when working with high-order signal processing filters, converting a high-order polynomial from its roots to its polynomial coefficients can be quite lossy, leading to inaccuracies in the filter's properties. This PR adds a new function, `polyrootval` - based on `polyval` - that evaluates a polynomial given a list of its roots. The benefit of calculating it this way can be seen at scipy/scipy:6059. Some tests are included, as well.
Simplify the logic a bit and make behavior consistent with polyval. Note that this adds a check that the number of dimensions of the array of the evaluation points is less than the number of dimensions of the array of roots when tensor=False. That check is missing from polyval and needs to be added.
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Thanks @e-q . |
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Thank you for your help and patience! |
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Small fixups for #7542.
As one can easily encounter when working with high-order signal processing
filters, converting a high-order polynomial from its roots to its polynomial
coefficients can be quite lossy, leading to inaccuracies in the filter's
properties.
I'm proposing a new function,
polyrootval- based onpolyval- thatevaluates a polynomial given a list of its roots. The benefit of calculating it
this way can be seen at scipy Issue #6059. Some tests are included, as well.
There are a few things where I'm not 100% sure what the best choice is, though
zeros_like(x); maybe there's another value that makes more sense, or even an error?-x**n?roots=[0]*ncan only give youx**n.