polyhorner
This package will:
- build univariate polynomials using an optimized Horner's method and fast numba loops
- build multivariate polynomials using a somewhat optimized Horner's method and fast numba loops
univariate polynomial example
Suppose you have x, and y data, and you want to model y = a0 + a1 x + a2 x^2 + a3 x^3 + a4 x^4 Let Mat be a numpy matrix of size (N,1), where N is the number of data points. X = polyhorner.horner(Mat, 4) will build your X matrix ready for the regression (optimized using Horner's method)
multivaraite polynomial example
Suppose you have x, y, and z data, and you want to model using apolynomial of order 3 in x, and 2 in y, with cross-products z = a0 + a1 x + a2 x^2 + a3 x^3 + a4 y + a5 y^2 + a6 xy + a7 x^2y + a8 x^3y + a9 xy^2 + a10 x^2y^2 + a11 x^3y^2 let Mat be a numpy matrix of size (N,2), where N is the number of data points. let Expo be a numpy matrix of size (2,1) = (3,2) X = polyhorner.horner(Mat, Expo) will build your X matrix ready for the regression (semi-optimized using Horner's method)
I use some functions distributed under the GNU LGPL license from https://people.sc.fsu.edu/~jburkardt/py_src/monomial
Thanks to Pssolanki for helping fix issues
1 maintainer
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Release files for polyhorner 1.1.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| polyhorner-1.1.0.tar.gz | 5.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| polyhorner-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.7 kB
Release files / polyhorner-1.1.0.tar.gz
| Download URL | polyhorner-1.1.0.tar.gz |
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Release files / polyhorner-1.1.0-py3-none-any.whl
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