Metadata-Version: 2.1
Name: PynamicGain
Version: 0.0.9
Summary: Dynamic Gain input generation for distributed PClamp setups.
Author: Andreas Neef, Stefan Pommer
Author-email: Friedrich Schwarz <friedrichschwarz@unigoettingen.de>
Maintainer-email: Friedrich Schwarz <friedrichschwarz@unigoettingen.de>
Project-URL: Repository, https://github.com/fschwar4/pynamicgain
Project-URL: Documentation, https://fschwar4.github.io/pynamicgain/
Project-URL: Homepage, https://fschwar4.github.io/pynamicgain/
Project-URL: Bug Tracker, https://github.com/fschwar4/pynamicgain/issues
Project-URL: Changelog, https://github.com/fschwar4/pynamicgain/blob/main/CHANGELOG.md
Keywords: neuroscience,electrophysiology,patch clamp,scientific software,data analysis,dynamic gain
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: matplotlib
Requires-Dist: scipy
Requires-Dist: numpy
Requires-Dist: tomli
Requires-Dist: numba
Requires-Dist: pyyaml
Requires-Dist: pyabf
Requires-Dist: tomli-w
Requires-Dist: tqdm
Requires-Dist: docopt
Provides-Extra: docs
Requires-Dist: myst-parser ; extra == 'docs'
Requires-Dist: pydata-sphinx-theme ; extra == 'docs'
Requires-Dist: pylint ; extra == 'docs'
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: sphinx-autodoc-typehints ; extra == 'docs'
Provides-Extra: interactive
Requires-Dist: jupyterlab ; extra == 'interactive'
Requires-Dist: ipykernel ; extra == 'interactive'

# Pynamic Gain

Python-based Dynamic Gain inputs for distributed patch clamp setup.


## Installation

Easiest way to install is via conda and pip:

```bash
conda create -n pydg_analysis python=3.11
conda activate pydg_analysis
pip install pynamicgain
```

Verify the installation with:

```bash
pydg_help
```

See the [documentation](https://fschwar4.github.io/pynamicgain/) for more information.

