Kernel Current Source Density
This 2.0 version of kCSD method.
Only supported for python 3.
Relevant Papers
Paper 1: “Kernel Current Source Density Method”, J. Potworowski, W. Jakuczun, S. Łȩski, D. K. Wójcik; Neural Comput 2012; 24 (2): 541–575, doi: https://doi.org/10.1162/NECO_a_00236
Paper 2 : “What we can and what we cannot see with extracellular multielectrodes”, C. Chintaluri, M. Bejtka, W. Średniawa, M. Czerwiński, J. M. Dzik, J. Jędrzejewska-Szmek, K. Kondrakiewicz, E. Kublik, D. K. Wójcik; PLoS Computational Biology (2021), 17(5): e1008615, doi: https://doi.org/10.1371/journal.pcbi.1008615
Paper 3 : “kCSD-python, reliable current source density estimation with quality control”, C. Chintaluri, M. Bejtka, W. Średniawa, M. Czerwiński, J. M. Dzik, J. Jędrzejewska-Szmek, D. K. Wójcik; bioRxiv, doi: https://doi.org/10.1101/708511
Paper 1 is the original paper with software code in Matlab. Paper 2 is an improvement and development of the paper 1. Paper 3 is a feature showcase and walk-through of the method and its applications.
Tutorials
This library comes with three tutorials and does not require any installation.
More information on the tutorials is provided here Tutorials!
You can also save these tutorials on your desktop, for this you will need to install jupyter-notebook. Do this by
pip install jupyter notebook
Figures
This library includes all the necessary scripts to generate the figures for papers 2 and 3.
Installation
user:~/$ pip install kcsd
Documentation
Autogenerated documentation available from readthedocs:
Also included here are authors and their contributions, citation policy, contacts etc.,
Earlier Stable versions
Please see git tags for earlier versions. These are not available as packages unfortunately.
v1.2 corresponds to the first time kCSD-python released as a python package
v1.0 corresponds to the version with the test cases written inside tests folder
v1.1 corresponds to the elephant python library version - no tests here
Health Report
Continuous Integration (Travis):
Test Coverage :
Documentation Status:
License
Metadata
Release files for kcsd 2.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kcsd-2.0.1.tar.gz | 3.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kcsd-2.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.5 MB
Release files / kcsd-2.0.1.tar.gz
| Download URL | kcsd-2.0.1.tar.gz |
|---|---|
| Size | 3.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.9
|
Release files / kcsd-2.0.1-py3-none-any.whl
| Download URL | kcsd-2.0.1-py3-none-any.whl |
|---|---|
| Size | 1.4 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.9
|