Pypsy¶
Pypsy is a library for the analysis of of psychophysiological data. Currently, Pypsy provides a suite of tools for the decomposition and analysis of electrodermal activity (EDA) signals. Much of this functionality is a port of the Ledalab software from the MATLAB programming language.
There are two main subpackages in Pypsy: Pypsy.signal and
Pypsy.optimization. The Pypsy.signal module contains
resources for representing a psychophysiological signal time series. The
Pypsy.optimization module contains facilities for optimization, used
primarily in decomposing EDA signals.
The most interesting class in Pypsy:, by far, is
EDASignal. This is the class to be used for
representing and decomposing EDA signals. The documentation of this class
demonstrates just how to do so in its examples.
Pypsy is being deceloped in conjunction with my own Ph.D. dissertation work. As such, it is very much a work in progress, and features and the overall architecture change often. If you are interested in using Pypsy, please feel free to do so. If in doing so, you find yourself needing help, please create an issue.
Contents:
Pypsy Modules¶
Pypsy package¶
Subpackages¶
Pypsy.optimization¶
The internals of the optimization module are a
quick-and-dirty implementation of conjugate gradient descent, that is used
in decomposing a Pypsy.signal.EDASignal into its constituent
tonic and phasic components. These methods are used internally by the
EDASignal class.
Pypsy.signal¶
Objects of the Signal class (and its subclasses) are
used to represent psychophysiological signal time series. The
Signal class can be used to represent any signal with
data and associated time points, while the EDASignal
class contains special functionality for decomposing EDA signals into their
tonic and phasic components.
You likely won’t need to access the following submodules directly, but they are documented, nevertheless:
Pypsy.signal.analysis¶
The Pypsy.signal.filter module provides most of the signal processing
and analysis functionality required by the Signal
class and its subclasses, especially for EDA signal decomposition.
Pypsy.signal.conversion¶
The Pypsy.signal.conversion module provides resources for converting
between a number of different commonly-used measures in Pypsy
(e.g., amplitude, power, and frequency).
Pypsy.signal.filter¶
The Pypsy.signal.filter module provides resources for the creation
of filters for use by the Signal class and its
subclasses.
Pypsy.signal.utilities¶
The Pypsy.signal.utilities module provides resources for calculating
the sampling rate of a signal, constraining values, and resampling signals,
among other things. Most of what is documented here is intended to be used
internally by the Signal class and its subclasses.