Skip to main content
This is a pre-production deployment of Warehouse. Changes made here affect the production instance of PyPI (
Help us improve Python packaging - Donate today!

Perform FFT on data set that does not fit into memory

Project Description

# out_of_core_fft <a href=””><img align=”right” hspace=”3” alt=”Status of automatic build and test suite” src=””></a> <a href=””><img align=”right” hspace=”3” alt=”Code distributed under the open-source MIT license” src=””></a>

Fourier transforms are highly nonlocal, which can cause problems when dealing with very large data sets. In particular, standard algorithms cannot work with data sets too large to fit into memory. On the other hand, the classic Cooley-Tukey FFT algorithm shows that discrete Fourier transforms can be split up into smaller sub-problems. This module provides functions for FFTs that can work with the data directly on disk, extracting small subsets that fit into memory, working on each individually, and then combining back onto disk to get the final result. This implementation is based on the algorithm presented by Thomas H. Cormen in “Algorithms for parallel processing” (1999). A nontrivial part of the implementation involves transposing the data on disk, for which I created a relatively simple, but fairly fast, function included here simply as transpose.

## Usage

These functions assume that the data to be manipulated are stored in HDF5 files. The FFT and inverse FFT are called with something like

`python import out_of_core_fft out_of_core_fft.fft('input.h5', 'x', 'output.h5', 'X') out_of_core_fft.ifft('input2.h5', 'X', 'output2.h5', 'x') `

Here, x and X are names for the datasets within the HDF5 files. Note that nothing is returned, because the result is stored on disk, as requested.

See the docstrings for more details.

## Acknowledgments

The work of creating this code was supported in part by the Sherman Fairchild Foundation and by NSF Grants No. PHY-1306125 and AST-1333129.

Release History

Release History

This version
History Node


Download Files

Download Files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
out-of-core-fft-1.0.tar.gz (11.5 kB) Copy SHA256 Checksum SHA256 Source Jan 27, 2016

Supported By

WebFaction WebFaction Technical Writing Elastic Elastic Search Pingdom Pingdom Monitoring Dyn Dyn DNS Sentry Sentry Error Logging CloudAMQP CloudAMQP RabbitMQ Heroku Heroku PaaS Kabu Creative Kabu Creative UX & Design Fastly Fastly CDN DigiCert DigiCert EV Certificate Rackspace Rackspace Cloud Servers DreamHost DreamHost Log Hosting