Filtering digital signals using a front end to scipy filters
Project description
A collection of digital signal filter front end for scipy
A collection of signal processing tools, utilities and class for signal processing
Description
The signal processing tool box has the following topics
- filters: Definition of three digital signal filters (all with low, high, -band-pass mode)
Ideal block filter
Butterworth filter
Kaiser filter
Phase shift removal
- utils: Classes and function to support signal processing
SignalGenerator: class to generated signal with multiple harmonic components and noise for testing purposes
get_peaks: Extract the peaks from a power spectral density
Notes
The SciPy provides most signal processing tool, such as as power spectral density estimator welch, which uses an equivalent algorithm as the specdens function from the Matlab tool box
The filters defined in this package are in fact front ends to the Scipy filters, however, in this package the filters have a more user-friendly interface.
For peak finding either the PeakUtils or the PyWafo package is recommended.
The function get_peaks is a front end to the peakutils.peaks function
Examples
Examples of using filtering with the SignalFilters package: example_filtering
Note
This project has been set up using PyScaffold 4.5.0. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.
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