[](https://zenodo.org/badge/latestdoi/296102080)
# spynal: Simple Python Neural Analysis Library
Tools for preprocessing and basic analysis of systems/cognitive neurophysiology data in Python
Covers typical preprocessing and basic analysis steps in neural analysis workflows.
Intended users are anyone doing analysis of neurophysiology data, but we particularly aim to be
accessible and easy-to-use for people migrating to Python from Matlab or other similar
programming languages.
### Features include:
**Simplicity**: Easy-to-use procedural interface; no OOP or complicated data/params structures
**Consistency**: Consistent function signature ~ `analysis(data, labels, axis, extra_param=value)`
**Modularity**: Can use specific functionality without buy-in to an entire processing chain
**Foolproof**: Extensive documentation and checking for proper function inputs
**Flexibility**: Detailed parameterization allows customization of analysis to users' needs
**Vectorized analysis**: Runs in parallel across all channels, no loops or data reshaping needed
### Package includes the following modules:
**matIO** — Painless loading of MATLAB .mat data files into appropriate Python data structures
**spikes** — Preprocessing and analyses of spiking data
**spectra** — Spectral analysis and preprocessing of continuous data (LFP/EEG)
**sync** — Analysis of oscillatory neural synchrony (field-field and spike-field)
**info** — Measures of neural information about task/behavior variables
**randstats** — Nonparametric randomization, permutation, and bootstrap statistics
**plots** — Generation of common plot types; plotting utilities
**utils** — Numerical and general purpose utilities
Full documentation can be found at: https://spynal.readthedocs.io/en/latest/
## Download & installation instructions
NOTE: Currently, spynal can only be installed against Python<=3.11, due to changes in the Import
Manager in Python 3.12 that have not been accounted for in all dependent packages. For details,
see this Stack Overflow answer: https://stackoverflow.com/a/77364602.
Users can either install the most recent stable release using pip or
install the latest updates from the Github repository
### Option 1: pip install
Recommended for users who prefer a simple installation and don't require the latest updates
- Open a terminal window, navigate to folder you want repository to live under (cd "parent directory")
- Run: pip install spynal
### Option 2: Install from source (Github)
Recommended for developers and for users that would like access to the latest updates
#### 2a: Download repository
- Open a terminal window, navigate to folder you want repository to live under (cd "parent directory")
- Run: git clone https://github.com/sbrincat/spynal.git
#### 2b: Install package
- Navigate into the newly-created spynal folder (cd "parent directory"/spynal)
- For end users: at command line, run: python setup.py install
- For developers: at command line, run: python setup.py develop
(this will allow you to edit the library without reinstalling)
## Usage
You should now be able to directly import spynal and its modules/functions in your code/notebooks like so:
import spynal
import spynal as spy
import spynal.spectra as spectra
from spynal.spectra import spectrogram
## Contributions
We welcome any contributions of new/expanded functionality or more efficient implementations,
and all issues/bug reports.
Submit a pull request/issue on Github or email me at [Github handle] AT [institution] .edu
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"description": "[](https://zenodo.org/badge/latestdoi/296102080)\n\n# spynal: Simple Python Neural Analysis Library\nTools for preprocessing and basic analysis of systems/cognitive neurophysiology data in Python \n\nCovers typical preprocessing and basic analysis steps in neural analysis workflows.\nIntended users are anyone doing analysis of neurophysiology data, but we particularly aim to be\naccessible and easy-to-use for people migrating to Python from Matlab or other similar\nprogramming languages. \n\n### Features include:\n**Simplicity**: Easy-to-use procedural interface; no OOP or complicated data/params structures \n**Consistency**: Consistent function signature ~ `analysis(data, labels, axis, extra_param=value)` \n**Modularity**: Can use specific functionality without buy-in to an entire processing chain \n**Foolproof**: Extensive documentation and checking for proper function inputs \n**Flexibility**: Detailed parameterization allows customization of analysis to users' needs \n**Vectorized analysis**: Runs in parallel across all channels, no loops or data reshaping needed \n\n### Package includes the following modules:\n**matIO** \u2014 Painless loading of MATLAB .mat data files into appropriate Python data structures \n**spikes** \u2014 Preprocessing and analyses of spiking data \n**spectra** \u2014 Spectral analysis and preprocessing of continuous data (LFP/EEG) \n**sync** \u2014 Analysis of oscillatory neural synchrony (field-field and spike-field) \n**info** \u2014 Measures of neural information about task/behavior variables \n**randstats** \u2014 Nonparametric randomization, permutation, and bootstrap statistics \n**plots** \u2014 Generation of common plot types; plotting utilities \n**utils** \u2014 Numerical and general purpose utilities \n\nFull documentation can be found at: https://spynal.readthedocs.io/en/latest/ \n\n\n## Download & installation instructions\nNOTE: Currently, spynal can only be installed against Python<=3.11, due to changes in the Import\nManager in Python 3.12 that have not been accounted for in all dependent packages. For details,\nsee this Stack Overflow answer: https://stackoverflow.com/a/77364602.\n\nUsers can either install the most recent stable release using pip or\ninstall the latest updates from the Github repository\n\n### Option 1: pip install\nRecommended for users who prefer a simple installation and don't require the latest updates\n\n - Open a terminal window, navigate to folder you want repository to live under (cd \"parent directory\")\n - Run: pip install spynal\n\n### Option 2: Install from source (Github)\nRecommended for developers and for users that would like access to the latest updates\n\n#### 2a: Download repository\n - Open a terminal window, navigate to folder you want repository to live under (cd \"parent directory\")\n - Run: git clone https://github.com/sbrincat/spynal.git\n\n#### 2b: Install package\n - Navigate into the newly-created spynal folder (cd \"parent directory\"/spynal)\n - For end users: at command line, run: python setup.py install\n - For developers: at command line, run: python setup.py develop\n (this will allow you to edit the library without reinstalling)\n\n## Usage\nYou should now be able to directly import spynal and its modules/functions in your code/notebooks like so: \n import spynal \n import spynal as spy \n import spynal.spectra as spectra \n from spynal.spectra import spectrogram \n\n## Contributions\nWe welcome any contributions of new/expanded functionality or more efficient implementations, \nand all issues/bug reports. \nSubmit a pull request/issue on Github or email me at [Github handle] AT [institution] .edu \n",
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