naplib-python
Tools and functions for neural data processing and analysis in python
Science Score: 49.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 2 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
3 of 5 committers (60.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (19.4%) to scientific vocabulary
Keywords
Scientific Fields
Repository
Tools and functions for neural data processing and analysis in python
Basic Info
- Host: GitHub
- Owner: naplab
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://naplib-python.readthedocs.io/en/latest/index.html
- Size: 259 MB
Statistics
- Stars: 28
- Watchers: 4
- Forks: 10
- Open Issues: 13
- Releases: 0
Topics
Metadata Files
README.md
naplib-python
Tools and functions for neural acoustic data processing and analysis in python. The documentation can be acccessed at the link below. It contains the API reference as well as example notebooks.
Installation
naplib-python is available on PyPi. To install or update this package with pip, run the following command:
bash
pip install naplib
To upgrade the version, run:
bash
pip install --upgrade naplib
API
The basic data structure for storing neural recording data is the Data object, which contains neural recordings and other variables associated with different trials such as stimuli and other metadata. Examples of loading and using this data structure can be found in the documentation and the docs/examples/ folder.
Brain Plotting
In addition to analysis and processing tools, naplib-python contains a suite of visualization tools, including brain plotting for ECoG and intracranial EEG electrodes. The backend can use either pure matplotlib for static plots, or plotly for 3D interactive plots.
Data Structure Schematic
Contributions
naplib-python is built by the Neural Acoustic Processing Lab at Columbia University. We primarily use it for processing neural data coming from electrocorticography (ECoG) and electroencephalography (EEG) along with paired audio stimuli in order to study the auditory cortex. You are free to use the software according to its license, and we welcome contributions if you would like to propose changes, additions, or fixes. See our contribution guide for more details.
Citing naplib-python
If you find naplib-python useful for your research, please cite the following paper (link):
Gavin Mischler, Vinay Raghavan, Menoua Keshishian, & Nima Mesgarani (2023). naplib-python: Neural acoustic data processing and analysis tools in python. Software Impacts, 17, 100541.
Backlog
The following items are ToDo items on the backlog:
- Look into data parallelization methods for the Data object and associated methods
- Consider making the Data object a dataclass
- Implement functionality to write Data objects to MATLAB formats (possibly EEGLab formats)
Owner
- Name: naplab
- Login: naplab
- Kind: organization
- Repositories: 4
- Profile: https://github.com/naplab
GitHub Events
Total
- Issues event: 4
- Watch event: 8
- Delete event: 6
- Issue comment event: 15
- Push event: 69
- Pull request review event: 18
- Pull request review comment event: 13
- Pull request event: 24
- Fork event: 1
- Create event: 10
Last Year
- Issues event: 4
- Watch event: 8
- Delete event: 6
- Issue comment event: 15
- Push event: 69
- Pull request review event: 18
- Pull request review comment event: 13
- Pull request event: 24
- Fork event: 1
- Create event: 10
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 193
- Total Committers: 5
- Avg Commits per committer: 38.6
- Development Distribution Score (DDS): 0.155
Top Committers
| Name | Commits | |
|---|---|---|
| Gavin Mischler | g****r@g****m | 163 |
| Vinay Raghavan | 4****n@u****m | 23 |
| gm2944 | g****4@a****u | 4 |
| Menoua Keshishian | m****1@c****u | 2 |
| gm2944 | g****4@a****u | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 41
- Total pull requests: 125
- Average time to close issues: 26 days
- Average time to close pull requests: 3 days
- Total issue authors: 3
- Total pull request authors: 4
- Average comments per issue: 0.44
- Average comments per pull request: 0.9
- Merged pull requests: 111
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 3
- Pull requests: 20
- Average time to close issues: 20 days
- Average time to close pull requests: 1 day
- Issue authors: 2
- Pull request authors: 3
- Average comments per issue: 0.0
- Average comments per pull request: 1.0
- Merged pull requests: 15
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- gavinmischler (36)
- menoua (4)
- vinaysraghavan (1)
Pull Request Authors
- gavinmischler (87)
- menoua (24)
- vinaysraghavan (13)
- arsalanfiroozi (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 68 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 31
- Total maintainers: 1
pypi.org: naplib
Tools and functions for neural data processing and analysis in python
- Homepage: https://github.com/naplab/naplib-python
- Documentation: https://naplib.readthedocs.io/
- License: MIT
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Latest release: 2.6.0
published 4 months ago
Rankings
Maintainers (1)
Dependencies
- ipykernel >=5.1.0
- ipython >=7.4
- nbsphinx ==0.8.8
- numpydoc >=1.1.0
- recommonmark ==0.5.0
- sphinx >=4.2.0
- sphinx_rtd_theme >=1.0.0
- actions/checkout v3 composite
- actions/setup-python v3 composite
- codecov/codecov-action v3 composite
- TextGrid *
- h5py *
- hdf5storage >=0.1.1
- joblib *
- matplotlib >=3.1.0
- mne *
- numpy >=1.15.0
- pandas >=1.0.0
- patsy *
- pynwb >=2.3.0
- pyyaml *
- scikit-learn *
- scipy >=1.5.0
- seaborn >=0.12.0
- statsmodels >=0.13.0
- tdt >=0.5.0