Spectral Derivatives

Documentation, How it works.

This repository is home to Python code that can take spectral derivatives with the Chebyshev basis or the Fourier basis, based on some pretty elegant, deep math. It's useful any time you want to take a derivative programmatically, such as for doing PDE simulations.

Installation and Usage

The package is a single module containing derivative functions. Before installing the module you will need numpy, scipy, scikit-learn, and matplotlib. To install, execute:

python3 -m pip install spectral-derivatives

or from the source code

python3 -m pip install .

You should now be able to

>>>from specderiv import *

For usage examples, see the Jupyter notebooks in the examples folder: Chebyshev and Fourier

References

Trefethen, N., 2000, Spectral Methods in Matlab, https://epubs.siam.org/doi/epdf/10.1137/1.9780898719598.ch8
Johnson, S., 2011, Notes on FFT-based differentiation, https://math.mit.edu/ stevenj/fft-deriv.pdf
Kutz, J.N., 2023, Data-Driven Modeling & Scientific Computation, Ch. 11, https://faculty.washington.edu/kutz/kutz_book_v2.pdf

Metadata

Release files for spectral-derivatives 0.1

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Source distribution (sdist)

Source distribution for spectral-derivatives 0.1
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Built distribution (wheel)

Table of built distributions (wheels) for spectral-derivatives 0.1
File	Interpreter	ABI	Platform	Reset
spectral_derivatives-0.1-py3-none-any.whl 6.4 kB Jan 13, 2025	Python 3	none	any	Details

Total release size: 12.0 kB

Release files / spectral_derivatives-0.1.tar.gz

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Release files / spectral_derivatives-0.1-py3-none-any.whl

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Size	6.4 kB
Tags	Python 3
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Uploaded via	`twine/6.0.1 CPython/3.12.8`