Hybrid (Symbolic-Numeric) Integration Package (based on sympy)
Project description
hyint: Hybrid (Symbolic-Numeric) Integration Package
hyint is a Python package to computes indefinite integral of univariable expressions with constant coeficients using symbolic-numeric methodolgy. It is built on top of sympy symbolic manipulation ecosystem of Python, but applies numerical methods to solve integral problems.
hyint can solve a large subset of basic standard integrals (polynomials, exponential/logarithmic, trigonometric and hyperbolic, inverse trigonometric and hyperbolic, rational and square root) ( see The Basis of Symbolic-Numeric Integration for a brief introduction to the algorithm. It can even find some integrals not found by the current version of sympy.integrate.
The symbolic part of the algorithm is similar (but not identical) to the Risch-Bronstein's poor man's integrator and generates a list of ansatzes (candidate terms). The numerical part uses sparse regression adopted from the Sparse identification of nonlinear dynamics (SINDy) algorithm to prune down the ansatzes and find the corresponding coefficients.
Prerequisites
hyint requires numpy/scipy and sympy to have be installed.
Installation
Install hyint as
pip install hyint
Tutorial
The main function exported by hyint is integrate(eq, x)
. It accepts two arguments, where
eq
is a univariable expression in `x'. It results either the integral or 0 otherwise.
Some examples:
from sympy import *
import hyint
x = Symbol('x')
In: hyint.integrate(x**3 - x + 1, x)
Out: x**4/4 - x**2/2 + x
In: hyint.integrate(x**2 * sin(2*x), x)
Out: -x**2*cos(2*x)/2 + x*sin(2*x)/2 + cos(2*x)/4
In: hyint.integrate(sqrt(x**2 + x - 1), x)
Out: x*sqrt(x**2 + x - 1)/2 + sqrt(x**2 + x - 1)/4 - 5*log(2*x + 2*sqrt(x**2 + x - 1) + 1)/8
In: hyint.integrate(x/(x**2 + 4), x)
Out: log(x**2 + 4)/2
In: hyint.integrate(x**2*log(x)**2 , x)
Out: x**3*log(x)**2/3 - 2*x**3*log(x)/9 + 0.0740740740740739*x**3
In: hyint.integrate(1 / (x**3 - 2*x + 1), x)
Out: 2.17082039324994*log(x - 1) + 1.34164078649988*log(x + 1/2 + sqrt(5)/2) - 1.17082039324993*log(x**3 - 2*x + 1)
In: hyint.integrate(x*exp(x)*cos(2*x), x)
Out: 2*x*exp(x)*sin(2*x)/5 + x*exp(x)*cos(2*x)/5 - 0.16*exp(x)*sin(2*x) + 0.12*exp(x)*cos(2*x)
In: hyint.integrate(log(log(x))/x, x)
Out: log(x)*log(log(x)) - log(x)
In: hyint.integrate(log(cos(x))*tan(x), x)
Out: -log(cos(x))**2/2
In: hyint.integrate(exp(x + 1)/(x + 1), x)
Out: Ei(x + 1)
In: hyint.integrate(exp(x)/x - exp(x)/x**2 , x)
Out: exp(x)/x
In: hyint.integrate(exp(x**2) , x)
Out: 0.886226925452758*erfi(x)
# sympy.integrate does not solve this example:
In: hyint.integrate(sqrt(1 - sin(x)), x)
Out: 2*cos(x)/sqrt(1 - sin(x))
Citation
hyint is a adopted from and is a rewrite of SymbolicNumericIntegration.jl. Citation: Symbolic-Numeric Integration of Univariate Expressions based on Sparse Regression:
@article{Iravanian2022,
author = {Shahriar Iravanian and Carl Julius Martensen and Alessandro Cheli and Shashi Gowda and Anand Jain and Julia Computing and Yingbo Ma and Chris Rackauckas},
doi = {10.48550/arxiv.2201.12468},
month = {1},
title = {Symbolic-Numeric Integration of Univariate Expressions based on Sparse Regression},
url = {https://arxiv.org/abs/2201.12468v2},
year = {2022},
}
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