Metadata-Version: 2.1
Name: complex-network-tools
Version: 0.1.0
Summary: A Python package for generating, learning, and analysis of complex networks.
Home-page: https://github.com/chengpei-wu/ComplexNetwork
Author: Chengpei Wu
Author-email: chengpei.wu@hotmail.com
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6.0
Description-Content-Type: text/markdown
License-File: LICENSE


# ComplexNetwork

complex-network-tools is a Python package for generating, learning, and analysis of complex networks.

# Examples

##### Synthetic network generating 

```python
from complex-network-tools.generator import erdos_renyi_graph

# generate a Erdos Renyi(ER) random graph
G = erdos_renyi_graph(num_nodes=100, num_edges=400, is_directed=False, is_weighted=False) 

# generate a Barabasi Albert(BA) scale-free graph
G = barabasi_albert_graph(num_nodes=100, num_edges=400, is_directed=False, is_weighted=False) 
```

##### Network attack

```python
from complex-network-tools.robustness.network_attack import network_attack

# get attack sequence of nodes
G = erdos_renyi_graph(num_nodes=100, num_edges=400, is_directed=False, is_weighted=False)
# node-removal based network attacks, use the targeted-degree based node-removal strategy
attack_sequence = network_attack(graph=G, attack='node', strategy='degree')
```

##### Spectral measure

```python
from complex-network-tools.spectral_measure.robustness_spectral_measure import spectral_gap

# calculate spectral gap for a graph
G = erdos_renyi_graph(num_nodes=100, num_edges=400, is_directed=False, is_weighted=False)
spectral_gap(G)
```



# Install

To be added.
