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Update banner link for PyPI compatibility #336

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Dec 8, 2023
Merged

Update banner link for PyPI compatibility #336

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380f4cf
Update banner link for PyPI compatibility
Dec 7, 2023
bd42cf4
update copyright year
Dec 8, 2023
cd2adde
include README in setup.py as long description
Dec 8, 2023
bd62343
add alt text to banner img tag
Dec 8, 2023
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32 changes: 16 additions & 16 deletions README.md
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
<img src="docs/source/logo/eFELBanner.png"/>
<img src="https://raw.githubusercontent.com/BlueBrain/eFEL/master/docs/source/logo/eFELBanner.png" alt="eFEL banner" />

<table>
<tr>
Expand Down Expand Up @@ -73,7 +73,7 @@ the values to the user.

The core of the library is written in C++, and a Python wrapper is included.
At the moment we provide a way to automatically compile and install the library
as a Python module. Instructions on how to compile the eFEL as a standalone C++
as a Python module. Instructions on how to compile the eFEL as a standalone C++
library can be found [here](http://efel.readthedocs.io/en/latest/installation.html#installing-the-c-standalone-library).


Expand All @@ -83,12 +83,12 @@ Citation
When you use this eFEL software for your research, we ask you to cite the following publications (this includes poster presentations):

```
@article{efel,
title={eFEL},
@article{efel,
title={eFEL},
DOI={10.5281/zenodo.593869},
url={https://doi.org/10.5281/zenodo.593869}
abstractNote={The Electrophys Feature Extraction Library (eFEL) allows neuroscientists to automatically extract features from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the features to be calculated. The library will then extract the requested features and return the values to the user.},
publisher={Zenodo},
url={https://doi.org/10.5281/zenodo.593869}
abstractNote={The Electrophys Feature Extraction Library (eFEL) allows neuroscientists to automatically extract features from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the features to be calculated. The library will then extract the requested features and return the values to the user.},
publisher={Zenodo},
author={Ranjan, Rajnish and
Van Geit, Werner and
Moor, Ruben and
Expand All @@ -97,8 +97,8 @@ When you use this eFEL software for your research, we ask you to cite the follow
Damart, Tanguy and
Jaquier, Aurélien and
Tuncel, Anil},
year={2023},
month={Jul}
year={2023},
month={Jul}
}
```

Expand Down Expand Up @@ -235,16 +235,16 @@ Results are in mV.

Full documentation
==================
The full documentation can be found [here](http://efel.readthedocs.io)
The full documentation can be found [here](http://efel.readthedocs.io)

Funding
=======
This work has been partially funded by the European Union Seventh Framework Program (FP7/2007­2013) under grant agreement no. 604102 (HBP),
the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 720270, 785907
(Human Brain Project SGA1/SGA2) and by the EBRAINS research infrastructure, funded from the European Union’s Horizon 2020 Framework
Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3).
This project/research was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de
This work has been partially funded by the European Union Seventh Framework Program (FP7/2007­2013) under grant agreement no. 604102 (HBP),
the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 720270, 785907
(Human Brain Project SGA1/SGA2) and by the EBRAINS research infrastructure, funded from the European Union’s Horizon 2020 Framework
Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3).
This project/research was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de
Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.

Copyright (c) 2009-2022 Blue Brain Project/EPFL
Copyright (c) 2009-2024 Blue Brain Project/EPFL

13 changes: 5 additions & 8 deletions setup.py
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Expand Up @@ -73,6 +73,9 @@
extra_compile_args=coverage_flags + ['-std=c++17'],
extra_link_args=coverage_flags)

with open("README.md", encoding="utf-8") as f:
README = f.read()

setup(
name="efel",
version=versioneer.get_version(),
Expand All @@ -84,14 +87,8 @@
maintainer="Werner Van Geit",
maintainer_email="[email protected]",
description="Electrophys Feature Extract Library (eFEL)",
long_description="The Electrophys Feature Extract Library (eFEL) allows "
"neuroscientists to automatically extract features from time series data "
"recorded from neurons (both in vitro and in silico). "
"Examples are the action potential width and amplitude in "
"voltage traces recorded during whole-cell patch clamp experiments. "
"The user of the library provides a set of traces and selects the "
"features to be calculated. The library will then extract the requested "
"features and return the values to the user.",
long_description=README,
long_description_content_type="text/markdown",
license="LGPLv3",
keywords=[
'feature',
Expand Down
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