https://github.com/nsailor/fastgraphlettransform.jl

Julia wrapper for the Fast Graphlet Transform.
https://github.com/nsailor/fastgraphlettransform.jl

Last synced: 19 days ago
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Julia wrapper for the Fast Graphlet Transform.

• Host: GitHub
• URL: https://github.com/nsailor/fastgraphlettransform.jl
• Owner: nsailor
• License: mpl-2.0
• Created: 2020-08-26T09:16:45.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2024-02-28T19:33:46.000Z (8 months ago)
• Last Synced: 2024-09-29T00:06:19.054Z (about 1 month ago)
• Language: Julia
• Size: 41 KB
• Stars: 2
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# FastGraphletTransform.jl

Julia wrapper for the [Fast Graphlet Transform](https://github.com/fcdimitr/fglt) C++/Cilk implementation.

[![Build Status](https://github.com/nsailor/FastGraphletTransform.jl/workflows/CI/badge.svg)](https://github.com/nsailor/FastGraphletTransform.jl/actions)

[![Coverage](https://codecov.io/gh/nsailor/FastGraphletTransform.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/nsailor/FastGraphletTransform.jl)

[![License: MPL-2.0](https://img.shields.io/badge/License-MPLv2-blue)](https://www.mozilla.org/en-US/MPL/)

## Installation

To add the package to your Julia environment, open a Julia prompt, enter the `pkg` mode by pressing `]`, and type:

```julia

add FastGraphletTransform

```

## Usage

To perform a fast graphlet transform, call the `fglt` function with the graph's adjacency matrix, for instance:

```julia

julia> using FastGraphletTransform

julia> using SparseArrays

julia> A = sparse([0 1 0 0 1 0; 1 0 1 1 1 0; 0 1 0 1 1 0; 0 1 1 0 1 1; 1 1 1 1 0 0; 0 0 0 1 0 0])

6×6 SparseMatrixCSC{Int64,Int64} with 18 stored entries:

 ⋅  1  ⋅  ⋅  1  ⋅

 1  ⋅  1  1  1  ⋅

 ⋅  1  ⋅  1  1  ⋅

 ⋅  1  1  ⋅  1  1

 1  1  1  1  ⋅  ⋅

 ⋅  ⋅  ⋅  1  ⋅  ⋅

julia> (f, fn) = fglt(A);

Total elapsed time: 0.0000 sec

julia> f # Raw frequencies (n x 16)

6×16 Matrix{Int64}:

 1  2  6  1  1  14   4  6  0  6   4  0  2  2  0  0

 1  4  9  6  4  12  19  7  4  3  12  8  5  3  5  1

 1  3  9  3  3  14  12  9  1  5  12  3  4  4  3  1

 1  4  8  6  3  12  18  7  4  5  10  6  4  4  3  1

 1  4  9  6  4  12  19  7  4  3  12  8  5  3  5  1

 1  1  3  0  0   8   0  3  0  3   0  0  0  0  0  0

julia> fn # Net frequencies (n x 16)

6×16 Matrix{Int64}:

 1  2  4  0  1  2  0  0  0  2  0  0  0  2  0  0

 1  4  1  2  4  0  1  0  0  0  2  1  0  0  2  1

 1  3  3  0  3  0  0  0  0  0  4  0  0  1  0  1

 1  4  2  3  3  0  2  0  0  0  2  3  0  1  0  1

 1  4  1  2  4  0  1  0  0  0  2  1  0  0  2  1

 1  1  3  0  0  2  0  0  0  3  0  0  0  0  0  0

```