Skip to main content

A Python package to check the similarity of two graphs using nanotopology.

Project description

Nanotopology

The Python project to check the similarity of two graphs using nano sets.

nanosets.py file is used to find nanosets of graph

Input data

1.List of all vertices of graph.

2.Dictionary that contains vertices of graph as key and adjacent vertices as value.

Function explanation

  1. Parameters of function vh is the list of all vertices of graph(s).
  2. Parameters of function lower_approximation and upper_approximation are dictionary and the value returned by function vh.
  3. Parameters of function boundary_region are the values returned from lower-approximation and upper_approximation.
  4. nanoset is obtained by passing the values returned from lower_approximation, upper_approximation and boundary_region.

graph_euivalence.py file is used to check whether two graphs are isomorphic or not.

Dictionary that contains nodes(key) and adjacent nodes(values) of each graphs are directly passed to the equality function.

Final result will be isomorphic vertices of second graph to the first graph if two graphs are similar else false statement(graphs are not similar) will be returned.

Example

Input

d1 = { 1: [1,2,4,6], 2: [1,2,3], 3: [2,3,4], 4:[1,2,4,6], 5:[4,5,6], 6:[1,5,6] }

d2 = { a: [a,b,c,f], b: [b,e,d,a], c:[a,d,c], d:[b,c,d], e:[b,f,e], f:[e,f,a] }

Output

two graphs are similar

matching nodes

[['a', 'c', 'd', 'b', 'e', 'f'], ['a', 'd', 'c', 'b', 'f', 'e'], ['a', 'e', 'f', 'b', 'c', 'd'], ['a', 'f', 'e', 'b', 'd', 'c'], ['b', 'c', 'd', 'a', 'e', 'f'], ['b', 'd', 'c', 'a', 'f', 'e'], ['b', 'e', 'f', 'a', 'c', 'd'], ['b', 'f', 'e', 'a', 'd', 'c']]

Dependencies

1.Python >= 2.6

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

nanotopology-1.0.1.tar.gz (3.4 kB view hashes)

Uploaded source

Built Distribution

nanotopology-1.0.1-py3-none-any.whl (4.2 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page