Metadata-Version: 2.1
Name: jgf
Version: 0.2.1
Summary: Python library to load JGF files
Home-page: https://github.com/filipinascimento/jgf
Author: Filipi N. Silva
Author-email: filipi@iu.edu
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.0
Description-Content-Type: text/markdown


# JGF(Z) format implementation
This package implements export and import functions for the JSON Graph Format (gZipped) `JGF(Z)` (https://jsongraphformat.info). Supported input formats/libraries are `networkx`, `igraph`, `numpy` matrices and `JXNF` files. All network, node and edges attributes are saved as well.

This project is being developed to support the new network datatype for (brainlife.io).

### Authors
- [Filipi N. Silva](filsilva@iu.edu)

<!-- ### Contributors
- Franco Pestilli (franpest@indiana.edu) -->

### Funding
[![NIH-1R01EB029272-01](https://img.shields.io/badge/NIH-1R01EB029272_01-blue.svg)](https://www.nibib.nih.gov/node/113361)


<!-- ### Citations

1. Adai, Alex T., Shailesh V. Date, Shannon Wieland, and Edward M. Marcotte. "LGL: creating a map of protein function with an algorithm for visualizing very large biological networks." Journal of molecular biology 340, no. 1 (2004): 179-190. [https://doi.org/10.1016/j.jmb.2004.04.047](https://doi.org/10.1016/j.jmb.2004.04.047) -->

## Installation 

You can install this package using `pip`:

```bash
pip install jgf
```

or install it from this git repository:

```bash
git clone <repository URL>
cd <repository PATH>
pip install -e ./
```

## API Reference

API reference can be found in (https://jgf.readthedocs.io/).

## Example of use

To use the library in igraph environment simply import the correct module and run `save` or `load` functions:

```python
import igraph as ig
import jgf.igraph as jig

g = ig.Graph.Famous("Zachary")

# will save a compressed file
jig.save(g,"zachary.jgfz")

g, = jig.load("zachary.jgfz")
```

You can also use it to save and load connectivity matrices as square numpy matrices:

```python
import numpy as np
import jgf.conmat as jcm

A = np.array([
  [  0, 0.1, 0.2,   0,   0],
  [  0,   0,   0, 0.5,   0],
  [  0,   0,   0,   0, 1.0],
  [1.0, 1.0,   0,   0,   0],
  [  0,   0, 0.5,   0,   0],
  ])

nodeProperties = {
  "name" : [
    "Node 1",
    "Node 2",
    "Node 3",
    "Node 4",
    "Node 5",
  ]
}
# will save a compressed file
jcm.save(A,"example.jgfz",label= "Example", nodeProperties=nodeProperties)

B,properties = jcm.load("example.jgfz",getExtraData=True)
```



