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python package implementing a multivariate Horner scheme for efficiently evaluating multivariate polynomials
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multivar_horner
is a python package implementing a multivariate
Horner scheme ("Horner's method", "Horner's rule") <https://en.wikipedia.org/wiki/Horner%27s_method>
__
for efficiently evaluating multivariate polynomials.
Quick Guide:
.. code-block:: console
pip install multivar_horner
For efficiency this package is compiling the instructions required for polynomial evaluation to C by default.
If you don't have a C compiler (gcc
or cc
) installed you also need to install numba for using an alternative method:
.. code-block:: console
pip install multivar_horner[numba]
Simple example:
.. code-block:: python
import numpy as np
from multivar_horner import HornerMultivarPolynomial
# input parameters defining the polynomial
# p(x) = 5.0 + 1.0 x_1^3 x_2^1 + 2.0 x_1^2 x_3^1 + 3.0 x_1^1 x_2^1 x_3^1
coefficients = np.array([[5.0], [1.0], [2.0], [3.0]], dtype=np.float64)
exponents = np.array([[0, 0, 0], [3, 1, 0], [2, 0, 1], [1, 1, 1]], dtype=np.uint32)
# [#ops=7] p(x) = x_1 (x_1 (x_1 (1.0 x_2) + 2.0 x_3) + 3.0 x_2 x_3) + 5.0
horner_polynomial = HornerMultivarPolynomial(coefficients, exponents)
x = np.array([-2.0, 3.0, 1.0], dtype=np.float64)
p_x = horner_polynomial(x)
For more refer to the documentation <https://multivar_horner.readthedocs.io/en/latest/>
__.
Also see:
GitHub <https://github.com/jannikmi/multivar_horner>
,
PyPI <https://pypi.python.org/pypi/multivar_horner/>
,
arXiv paper <https://arxiv.org/abs/2007.13152>
__
FAQs
python package implementing a multivariate Horner scheme for efficiently evaluating multivariate polynomials
We found that multivar-horner demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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