This release is a pre-release and may not be stable for production use.
Gradec
A Python library for meta-analytic functional decoding of cortical gradient of functional connectivity.
Currently, gradec implements a range of gradient segmentation, and meta-analytic decoding algorithms.
Installation
Please see our installation instructions for information on how to install gradec.
Installation with pip
pip install gradec
Local installation (development version)
pip install git+https://github.com/JulioAPeraza/gradec.git
Citing gradec
If you use gradec in your research, we recommend citing the Zenodo DOI associated with the gradec version you used, as well as the Imaging Neuroscience journal article: https://doi.org/10.1162/imag_a_00081. You can find the Zenodo DOI associated with each gradec release at https://zenodo.org/record/8161766.
Contributing
Please see our contributing guidelines for more information on contributing to gradec.
We ask that all contributions to gradec respect our code of conduct.
1 maintainer
Metadata
1 maintainer
Release files for gradec 0.0.1rc5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| gradec-0.0.1rc5.tar.gz | 51.8 kB | Without provenance | Details for gradec-0.0.1rc5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| gradec-0.0.1rc5-py3-none-any.whl | Python 3 | none | any | Details for gradec-0.0.1rc5-py3-none-any.whl |
Total release size: 85.8 kB
Release files / gradec-0.0.1rc5.tar.gz
| Download URL | gradec-0.0.1rc5.tar.gz |
|---|---|
| Size | 51.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
63db04ce6929aafbb520dbf27aa87b542d45412d93b794d50b682c5161ff45aa
|
|
BLAKE2b-256 checksum How to use checksums |
9c2e1fe498073153c258307628baa52acf74bf0b015f7aa848df3a14db1dac15
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.18
|
Release files / gradec-0.0.1rc5-py3-none-any.whl
| Download URL | gradec-0.0.1rc5-py3-none-any.whl |
|---|---|
| Size | 34.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
d2ce91b44876526264ea41c7f6c3b02dca3a6bc47728ec0f89022d12711aab27
|
|
BLAKE2b-256 checksum How to use checksums |
c9a281eb83d4f2fce47d111ad8e2ae771114f94089b2c184fae1344bfd84d2ff
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.9.18
|
Security for gradec 0.0.1rc5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
