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Collection of algorithms for numerically calculating fractional derivatives.

Project description

differint

This package is used for numerically calculating fractional derivatives and integrals (differintegrals). Options for varying definitions of the differintegral are available, including the Grunwald-Letnikov (GL), the ‘improved’ Grunwald-Letnikov (GLI), the Riemann-Liouville (RL), and the Caputo (coming soon!). Through the API, you can compute differintegrals at a point or over an array of function values.

Motivation

There is little in the way of readily available, easy-to-use code for numerical fractional calculus. What is currently available are functions that are generally either smart parts of a much larger package, or only offer one numerical algorithm. The differint package offers a variety of algorithms for computing differintegrals and several auxiliary functions relating to generalized binomial coefficients.

Installation

This project requires Python 3+ and NumPy to run.

Installation from the Python Packaging index (https://pypi.python.org/pypi) is simple using pip.

pip install differint

Example Usage

Taking a fractional derivative is easy with the differint package. Let’s take the 1/2 derivative of the square root function on the interval [0,1], using the Riemann-Liouville definition of the fractional derivative.

import numpy as np
import differint.differint as df

def f(x):
   return x**0.5

DF = df.RL(0.5, f)
print(DF)

You can also specify the endpoints of the domain and the number of points used as follows.

DF = df.RL(0.5, f, 0, 1, 128)

Tests

All tests can be run with nose from the command line. Setup will automatically install nose if it is not present on your machine.

python setup.py tests

Alternatively, you can run the test script directly.

cd <file_path>/differint/tests/
python test.py

API Reference

In this section we cover the usage of the various functions within the differint package.

Main Function Usage
GLpoint Computes the GL differintegral at a point
GL Computes the GL differintegral over an entire array of function values using the Fast Fourier Transform
GLI Computes the improved GL differintegral over an entire array of function values
RLpoint Computes the RL differintegral at a point
RL Computes the RL differintegral over an entire array of function values using matrix methods
Auxiliary Function Usage
isInteger Determine if a number is an integer
checkValues Used to check for valid algorithm input types
GLIinterpolat Define interpolatin g coefficients for the improved GL algorithm
functionCheck Determines if algorithm function input is callable or an array of numbers
test_func Testing function for docstring examples
poch Computes the Pochhammer symbol
GLcoeffs Determines the convolution filter composed of generalized binomial coefficients used in the GL algorithm
RLcoeffs Calculates the coefficients used in the RLpoint and RL algorithms
RLmatrix Determines the matrix used in the RL algorithm

Contribute

To contribute to this project, see the contributing guidelines.

Credits

Baleanu, D., Diethelm, K., Scalas, E., & Trujillo, J.J. (2012). Fractional Calculus: Models and Numerical Methods. World Scientific.

Oldham, K.B. & Spanier, J. (1974). The Fractional Calculus: Theory and Applications of Differentiation and Integration to Arbitrary Order. Academic Press Inc.

License

MIT © Matthew Adams

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