Metadata-Version: 2.1
Name: neurodsp
Version: 1.1.2
Summary: Digital Signal Processing for Neural time series
Home-page: https://github.com/neurodsp-tools/neurodsp
Author: The Voytek Lab
Author-email: voyteklab@gmail.com
License: MIT
Download-URL: https://github.com/neurodsp-tools/neurodsp/releases
Keywords: neuroscience,neural oscillations,time series analysis,spectral analysis,LFP
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: matplotlib
Requires-Dist: pandas
Requires-Dist: scikit-learn


========
Neurodsp
========

A package for digital signal processing of neural time series.

Neurodsp contains several modules:

- burst : Detect bursting oscillators in neural signals
- filt : Filter data with bandpass, highpass, lowpass, or notch filters
- laggedcoherence : Estimate rhythmicity using the lagged coherence measure
- sim : Simulate bursting or stationary oscillators with brown noise
- spectral : Compute spectral domain features (PSD and 1/f slope, etc)
- swm : Identify recurrent patterns in a signal using sliding window matching
- timefrequency : Estimate instantaneous measures of oscillatory activity


