Metadata-Version: 2.1
Name: SBMLDiagrams
Version: 0.1.7
Summary: Visualize, edit and write SBML files.
Home-page: https://github.com/SunnyXu/SBMLDiagrams
Author: Jin Xu, Jessie Jiang, Herbert M. Sauro
Author-email: jxu2019@uw.edu
License: MIT License
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: coverage
Requires-Dist: pip (>20)
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: python-libsbml
Requires-Dist: simplesbml
Requires-Dist: skia-python
Requires-Dist: Ipython
Requires-Dist: Pillow
Requires-Dist: setuptools
Requires-Dist: openpyxl
Requires-Dist: opencv-python

# SBMLDiagrams
[![Coverage](https://codecov.io/gh/sunnyXu/SBMLDiagrams/branch/main/graph/badge.svg)](https://codecov.io/gh/sunnyXu/SBMLDiagrams)

## Introduction
SBMLDiagrams is a Python package to visualize the networks embedded in SBML Level 3 models. If the SBML layout and render extension are used, the package will use this data to display the network. SBMLDiagrams can export PNG, JPG, PDF files. SBMLDiagrams can be used to add SBML layout and render to an existing SBML model which can subsequently be exported. If you use this python package, please cite the Gihub website (https://github.com/SunnyXu/SBMLDiagrams).

We also plan to interface SBMLDiagrams to NetworkX to exploit the variety of layout algorithms as well as SBbadger which is a tool for generating realistic but random biochemical networks. 

## Installation

``pip install SBMLDiagrams``

## A Figure Example

Here is a figure example visualized by SBMLDiagrams:

<img src="https://github.com/SunnyXu/SBMLDiagrams/blob/main/docs/Figures/Jana_WolfGlycolysis.png" width="350" height="450">

Please see more figure examples in the documentation.

## Documentation
Please see the documentation at https://sunnyxu.github.io/SBMLDiagrams/ for details.




