Skip to main content
Help us improve PyPI by participating in user testing. All experience levels needed!

Finite Impulse Response package for time series analysis.

Project description

# FIRDeconvolution FIRDeconvolution is a python class that performs finite impulse response fitting on time series data, in order to estimate event-related signals.

Example use cases are fMRI and pupil size analysis. The package performs the linear least squares analysis using numpy.linalg as a backend, but can switch between different backends, such as statsmodels (which is implemented). For very collinear design matrices ridge regression is implemented through the sklearn RidgeCV function. Bootstrap estimates of error regions are implemented through residual reshuffling.

It is possible to add covariates to the events to estimate not just the impulse response function, but also correlation timecourses with secondary variables. Furthermore, one can add the duration each event should have in the designmatrix, for designs in which the durations of the events vary.

In neuroscience, the inspection of the event-related signals such as those estimated by FIRDeconvolution is essential for a thorough understanding of one’s data. Researchers may overlook essential patterns in their data when blindly running GLM analyses without looking at the impulse response shapes.

The test notebook explains how the package can be used for data analysis, by creating toy signals and then using FIRDeconvolution to fit the impulse response functions from the toy data.

## Dependencies numpy, scipy, matplotlib, statsmodels, sklearn

TODO - temporal autocorrelation correction


Project details

Release history Release notifications

This version
History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


History Node


Download files

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

Filename, size & hash SHA256 hash help File type Python version Upload date
fir-0.1.tar.gz (10.0 kB) Copy SHA256 hash SHA256 Source None Oct 21, 2017

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging CloudAMQP CloudAMQP RabbitMQ AWS AWS Cloud computing Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page