Metadata-Version: 2.4
Name: pyCLINE
Version: 0.1.9
Summary: This package is the Python implementation of the CLINE method
Author-email: Bartosz Prokop <bartosz.prokop@kuleuven.be>, Nikita Frolov <nikita.frolov@kuleuven.be>, Lendert Gelens <lendert.gelens@kuleuven.be>
Project-URL: Homepage, https://pycline-ec8369.pages.gitlab.kuleuven.be/
Project-URL: Issues, https://gitlab.kuleuven.be/gelenslab/publications/pycline/-/issues
Keywords: model,model identification,nullcline,data-driven,machine learning,deep learning,torch,dynamics,oscillator,nonlinear dynamics,complex systems
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib>=3.6.2
Requires-Dist: numpy<1.25.0,>=1.24.1
Requires-Dist: pandas~=1.5.2
Requires-Dist: torch>=2.4.1
Requires-Dist: tqdm>=4.66.1
Requires-Dist: jitcdde>=1.8.1
Requires-Dist: scipy>=1.9.3
Dynamic: license-file

# PyCLINE - python package for CLINE

The `pyCLINE` package is the python package based on the CLINE (**C**omputational **L**earning and **I**dentification of **N**ullclin**E**s).
It can be downloaded from PyPI with pip by using
    
    pip install pyCLINE

The package allows to recreate all data, models and results shown in [Prokop, Billen, Frolov and Gelens (2025)](https://arxiv.org/abs/2503.16240), and to apply CLINE to other data sets. 
In order to generate data used in [Prokop, Billen, Frolov and Gelens (2025)](https://arxiv.org/abs/2503.16240), a set of different models is being provided under `pyCLINE.model`. 
Data from these models can be generated using `pyCLINE.generate_data()`.
For setting up the data prepartion and adjacent training a neural network, the submodule `pyCLINE.recovery_methods` is used. 
The submodule contains the module for data_preparation `pyCLINE.recovery_methods.data_preparation` and for neural network training `pyCLINE.recovery_methods.nn_training`. 

For a better understanding, `pyCLINE` also contains the module `pyCLINE.example` which provides four examples also found in XXX with step by step instructions on how to setup a CLINE pipeline. 

The structure of `pyCLINE` is shown here: 

![PyCLINE structure](pycline_structure.png)
