A package for approximating SciPy functions
Project description
ApproxSciMate
A python library for approximating SciPy functions with different levels of accuracy. The library is intended to bring awareness to the energy usage of computer systems, and to give users a choice in how much they consume.
Read the descriptions of the functions and their levels of approximation below, pick what is best for your use case.
Functions
cbrt(n, level=0)
Calculates the cube root of the provided number n with the accuracy specified at the level.
level = 0
: The default SciPycbrt
function providing maximum accuracy.level = 1
: Halley's method for approximating cube roots, for moderate accuracy.level = 2
: Newton's method for approximating cube roots, for low accuracy.
comb(n, k, level=0)
Calculates the amount of possible selections of k items from a set of size n where the order of selection does not matter. Approximates the value based on the defined level of accuracy.
level = 0
: The default SciPycomb
function providing maximum accuracy.level = 1
: The approximated lower bound of the calculation.level = 2
: The approximated upper bound of the calculation.level = 3
: Uses Stirling's method of approximating factorials which converges to the real value when n is very large.
perm(n, k, level=0)
Calculates the amount of possible selections of k items from a set of size n where the order of selection does matter. Approximates the value based on the defined level of accuracy.
level = 0
: The default SciPyperm
function providing maximum accuracy.level = 1
: The approximated lower bound of the calculation.level = 2
: The approximated upper bound of the calculation.level = 3
: Uses Stirling's method of approximating factorials which converges to the real value when n is very large.
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