├── examples └── temp.py ├── requirements.txt ├── requirements ├── doc.txt ├── extra.txt ├── test.txt ├── developer.txt └── default.txt ├── .coveragerc ├── MANIFEST.in ├── tests ├── data │ ├── target_predictions │ │ └── adamic_adar_with_name.csv │ └── inputs │ │ ├── id_labels.csv │ │ └── neighbour_matrix.csv └── unit │ └── tests.py ├── .travis.yml ├── docs ├── build │ ├── html │ │ ├── objects.inv │ │ ├── _static │ │ │ ├── file.png │ │ │ ├── minus.png │ │ │ ├── plus.png │ │ │ ├── fonts │ │ │ │ ├── Lato-Bold.ttf │ │ │ │ ├── Inconsolata.ttf │ │ │ │ ├── Lato-Regular.ttf │ │ │ │ ├── Lato │ │ │ │ │ ├── lato-bold.eot │ │ │ │ │ ├── lato-bold.ttf │ │ │ │ │ ├── lato-bold.woff │ │ │ │ │ ├── lato-bold.woff2 │ │ │ │ │ ├── lato-italic.eot │ │ │ │ │ ├── lato-italic.ttf │ │ │ │ │ ├── lato-italic.woff │ │ │ │ │ ├── lato-italic.woff2 │ │ │ │ │ ├── lato-regular.eot │ │ │ │ │ ├── lato-regular.ttf │ │ │ │ │ ├── lato-regular.woff │ │ │ │ │ ├── lato-regular.woff2 │ │ │ │ │ ├── lato-bolditalic.eot │ │ │ │ │ ├── lato-bolditalic.ttf │ │ │ │ │ ├── lato-bolditalic.woff │ │ │ │ │ └── lato-bolditalic.woff2 │ │ │ │ ├── Inconsolata-Bold.ttf │ │ │ │ ├── RobotoSlab-Bold.ttf │ │ │ │ ├── Inconsolata-Regular.ttf │ │ │ │ ├── RobotoSlab-Regular.ttf │ │ │ │ ├── fontawesome-webfont.eot │ │ │ │ ├── fontawesome-webfont.ttf │ │ │ │ ├── fontawesome-webfont.woff │ │ │ │ ├── fontawesome-webfont.woff2 │ │ │ │ └── RobotoSlab │ │ │ │ │ ├── roboto-slab-v7-bold.eot │ │ │ │ │ ├── roboto-slab-v7-bold.ttf │ │ │ │ │ ├── roboto-slab-v7-bold.woff │ │ │ │ │ ├── roboto-slab-v7-bold.woff2 │ │ │ │ │ ├── roboto-slab-v7-regular.eot │ │ │ │ │ ├── roboto-slab-v7-regular.ttf │ │ │ │ │ ├── roboto-slab-v7-regular.woff │ │ │ │ │ └── roboto-slab-v7-regular.woff2 │ │ │ ├── css │ │ │ │ ├── fonts │ │ │ │ │ ├── lato-bold.woff │ │ │ │ │ ├── lato-bold.woff2 │ │ │ │ │ ├── lato-normal.woff │ │ │ │ │ ├── lato-normal.woff2 │ │ │ │ │ ├── Roboto-Slab-Bold.woff │ │ │ │ │ ├── lato-bold-italic.woff │ │ │ │ │ ├── Roboto-Slab-Bold.woff2 │ │ │ │ │ ├── Roboto-Slab-Regular.woff │ │ │ │ │ ├── fontawesome-webfont.eot │ │ │ │ │ ├── fontawesome-webfont.ttf │ │ │ │ │ ├── fontawesome-webfont.woff │ │ │ │ │ ├── lato-bold-italic.woff2 │ │ │ │ │ ├── lato-normal-italic.woff │ │ │ │ │ ├── lato-normal-italic.woff2 │ │ │ │ │ ├── Roboto-Slab-Regular.woff2 │ │ │ │ │ └── fontawesome-webfont.woff2 │ │ │ │ └── badge_only.css │ │ │ ├── documentation_options.js │ │ │ ├── js │ │ │ │ ├── badge_only.js │ │ │ │ ├── html5shiv.min.js │ │ │ │ ├── html5shiv-printshiv.min.js │ │ │ │ └── theme.js │ │ │ ├── pygments.css │ │ │ ├── doctools.js │ │ │ ├── underscore.js │ │ │ └── language_data.js │ │ ├── _sources │ │ │ ├── modules.rst.txt │ │ │ ├── bigraph.evaluation.rst.txt │ │ │ ├── index.rst.txt │ │ │ ├── bigraph.rst.txt │ │ │ ├── bigraph.preprocessing.rst.txt │ │ │ └── intro.rst.txt │ │ ├── .buildinfo │ │ ├── searchindex.js │ │ ├── search.html │ │ ├── modules.html │ │ ├── py-modindex.html │ │ ├── intro.html │ │ ├── index.html │ │ ├── bigraph.evaluation.html │ │ └── genindex.html │ └── doctrees │ │ ├── index.doctree │ │ ├── intro.doctree │ │ ├── bigraph.doctree │ │ ├── modules.doctree │ │ ├── environment.pickle │ │ ├── bigraph.evaluation.doctree │ │ └── bigraph.preprocessing.doctree ├── source │ ├── modules.rst │ ├── bigraph.evaluation.rst │ ├── index.rst │ ├── bigraph.rst │ ├── bigraph.preprocessing.rst │ ├── intro.rst │ └── conf.py ├── Makefile └── make.bat ├── bigraph ├── evaluation │ └── __init__.py ├── __init__.py ├── preprocessing │ ├── __init__.py │ ├── get_adjacents.py │ ├── make_graph.py │ └── import_files.py ├── algorithms.py └── bigraph.py ├── main.py ├── pyproject.toml ├── License.txt ├── .gitignore ├── setup.py └── README.md /examples/temp.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | bluepy 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/docs/build/html/_static/fonts/RobotoSlab/roboto-slab-v7-regular.woff: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/bi-graph/Bigraph/HEAD/docs/build/html/_static/fonts/RobotoSlab/roboto-slab-v7-regular.woff -------------------------------------------------------------------------------- /docs/build/html/_static/fonts/RobotoSlab/roboto-slab-v7-regular.woff2: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/bi-graph/Bigraph/HEAD/docs/build/html/_static/fonts/RobotoSlab/roboto-slab-v7-regular.woff2 -------------------------------------------------------------------------------- /docs/build/html/.buildinfo: -------------------------------------------------------------------------------- 1 | # Sphinx build info version 1 2 | # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. 3 | config: f40406ceaf0dacf9203ef88d46b75d21 4 | tags: 645f666f9bcd5a90fca523b33c5a78b7 5 | -------------------------------------------------------------------------------- /bigraph/evaluation/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (C) 2017-2021 Bigraph developers 2 | # Author: Soran Ghadri 3 | # Contact: soran.gdr.cs@gmail.com 4 | 5 | __all__ = ["evaluation"] 6 | 7 | # import bigraph.evaluation.evaluation 8 | # from bigraph.evaluation import evaluation 9 | -------------------------------------------------------------------------------- /bigraph/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (C) 2017-2021 Bigraph developers 2 | # Author: Soran Ghadri 3 | # Contact: soran.gdr.cs@gmail.com 4 | 5 | """A package for link prediction in bipartite networks.""" 6 | from .bigraph import BiGraph 7 | 8 | __all__ = ["evaluation", "preprocessing", "BiGraph"] 9 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | import bigraph 2 | 3 | 4 | def main(): 5 | """ 6 | Link prediction on a bipartite network 7 | :return: 8 | """ 9 | 10 | bg = bigraph.BiGraph() 11 | 12 | bg.cn_predict() 13 | bg.jc_predict() 14 | bg.aa_predict() 15 | bg.pa_predict() 16 | 17 | 18 | if __name__ == "__main__": 19 | main() 20 | -------------------------------------------------------------------------------- /bigraph/preprocessing/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (C) 2017-2021 Bigraph developers 2 | # Author: Soran Ghadri 3 | # Contact: soran.gdr.cs@gmail.com 4 | 5 | from .get_adjacents import GetAdjacents 6 | from .import_files import ImportFiles 7 | from .make_graph import MakeGraph 8 | 9 | __all__ = [ 10 | "GetAdjacents", 11 | "ImportFiles", 12 | "MakeGraph", 13 | ] 14 | -------------------------------------------------------------------------------- /tests/unit/tests.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | 3 | import bigraph 4 | 5 | 6 | class TestAAPredict(unittest.TestCase): 7 | def test_aa_predict(self): 8 | bg = bigraph.BiGraph() 9 | output = bg.aa_predict() 10 | print(output) 11 | self.assertEqual(type(output), dict, "Not a dict") 12 | 13 | 14 | if __name__ == "__main__": 15 | unittest.main() 16 | -------------------------------------------------------------------------------- /docs/build/html/_static/documentation_options.js: -------------------------------------------------------------------------------- 1 | var DOCUMENTATION_OPTIONS = { 2 | URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), 3 | VERSION: 'rc1', 4 | LANGUAGE: 'english', 5 | COLLAPSE_INDEX: false, 6 | BUILDER: 'html', 7 | FILE_SUFFIX: '.html', 8 | LINK_SUFFIX: '.html', 9 | HAS_SOURCE: true, 10 | SOURCELINK_SUFFIX: '.txt', 11 | NAVIGATION_WITH_KEYS: false 12 | }; -------------------------------------------------------------------------------- /docs/source/bigraph.evaluation.rst: -------------------------------------------------------------------------------- 1 | bigraph.evaluation package 2 | ========================== 3 | 4 | Submodules 5 | ---------- 6 | 7 | bigraph.evaluation.evaluation module 8 | ------------------------------------ 9 | 10 | .. automodule:: bigraph.evaluation.evaluation 11 | :members: 12 | :undoc-members: 13 | :show-inheritance: 14 | 15 | Module contents 16 | --------------- 17 | 18 | .. automodule:: bigraph.evaluation 19 | :members: 20 | :undoc-members: 21 | :show-inheritance: 22 | -------------------------------------------------------------------------------- /docs/build/html/_sources/bigraph.evaluation.rst.txt: -------------------------------------------------------------------------------- 1 | bigraph.evaluation package 2 | ========================== 3 | 4 | Submodules 5 | ---------- 6 | 7 | bigraph.evaluation.evaluation module 8 | ------------------------------------ 9 | 10 | .. automodule:: bigraph.evaluation.evaluation 11 | :members: 12 | :undoc-members: 13 | :show-inheritance: 14 | 15 | Module contents 16 | --------------- 17 | 18 | .. automodule:: bigraph.evaluation 19 | :members: 20 | :undoc-members: 21 | :show-inheritance: 22 | -------------------------------------------------------------------------------- /docs/source/index.rst: -------------------------------------------------------------------------------- 1 | .. d documentation master file, created by 2 | sphinx-quickstart on Fri Jul 23 06:19:34 2021. 3 | You can adapt this file completely to your liking, but it should at least 4 | contain the root `toctree` directive. 5 | 6 | Welcome to d's documentation! 7 | ============================= 8 | 9 | .. toctree:: 10 | :maxdepth: 4 11 | :caption: Contents: 12 | 13 | intro 14 | bigraph 15 | 16 | 17 | Indices and tables 18 | ================== 19 | 20 | * :ref:`genindex` 21 | * :ref:`modindex` 22 | * :ref:`search` 23 | -------------------------------------------------------------------------------- /docs/build/html/_sources/index.rst.txt: -------------------------------------------------------------------------------- 1 | .. d documentation master file, created by 2 | sphinx-quickstart on Fri Jul 23 06:19:34 2021. 3 | You can adapt this file completely to your liking, but it should at least 4 | contain the root `toctree` directive. 5 | 6 | Welcome to d's documentation! 7 | ============================= 8 | 9 | .. toctree:: 10 | :maxdepth: 4 11 | :caption: Contents: 12 | 13 | intro 14 | bigraph 15 | 16 | 17 | Indices and tables 18 | ================== 19 | 20 | * :ref:`genindex` 21 | * :ref:`modindex` 22 | * :ref:`search` 23 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "bigraph" 3 | version = "0.1.0" 4 | description = "" 5 | authors = ["sigma1326 " ,"soran-ghaderi "] 6 | 7 | [tool.poetry.dependencies] 8 | python = ">=3.10,<3.11" 9 | networkx = "^2.6.3" 10 | tabulate = "^0.8.9" 11 | pandas = "^1.4.1" 12 | scipy = "^1.8.1" 13 | matplotlib = "^3.5.2" 14 | scikit-learn = "^1.1.1" 15 | numpy = "^1.22.4" 16 | Pygments = "^2.12.0" 17 | 18 | [tool.poetry.dev-dependencies] 19 | 20 | [build-system] 21 | requires = ["poetry-core>=1.0.0"] 22 | build-backend = "poetry.core.masonry.api" 23 | 24 | -------------------------------------------------------------------------------- /docs/Makefile: -------------------------------------------------------------------------------- 1 | # Minimal makefile for Sphinx documentation 2 | # 3 | 4 | # You can set these variables from the command line, and also 5 | # from the environment for the first two. 6 | SPHINXOPTS ?= 7 | SPHINXBUILD ?= sphinx-build 8 | SOURCEDIR = source 9 | BUILDDIR = build 10 | 11 | # Put it first so that "make" without argument is like "make help". 12 | help: 13 | @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) 14 | 15 | .PHONY: help Makefile 16 | 17 | # Catch-all target: route all unknown targets to Sphinx using the new 18 | # "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). 19 | %: Makefile 20 | @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) 21 | -------------------------------------------------------------------------------- /docs/source/bigraph.rst: -------------------------------------------------------------------------------- 1 | bigraph package 2 | =============== 3 | 4 | Subpackages 5 | ----------- 6 | 7 | .. toctree:: 8 | :maxdepth: 4 9 | 10 | bigraph.evaluation 11 | bigraph.preprocessing 12 | 13 | Submodules 14 | ---------- 15 | 16 | 17 | bigraph.algorithms module 18 | ------------------------- 19 | 20 | .. automodule:: bigraph.algorithms 21 | :members: 22 | :undoc-members: 23 | :show-inheritance: 24 | 25 | bigraph.bigraph module 26 | ---------------------- 27 | 28 | .. automodule:: bigraph.bigraph 29 | :members: 30 | :undoc-members: 31 | :show-inheritance: 32 | 33 | Module contents 34 | --------------- 35 | 36 | .. automodule:: bigraph 37 | :members: 38 | :undoc-members: 39 | :show-inheritance: 40 | -------------------------------------------------------------------------------- /docs/build/html/_sources/bigraph.rst.txt: -------------------------------------------------------------------------------- 1 | bigraph package 2 | =============== 3 | 4 | Subpackages 5 | ----------- 6 | 7 | .. toctree:: 8 | :maxdepth: 4 9 | 10 | bigraph.evaluation 11 | bigraph.preprocessing 12 | bigraph.algorithms 13 | bigraph.bigraph 14 | 15 | Submodules 16 | ---------- 17 | 18 | 19 | bigraph.algorithms module 20 | ------------------------- 21 | 22 | .. automodule:: bigraph.algorithms 23 | :members: 24 | :undoc-members: 25 | :show-inheritance: 26 | 27 | bigraph.bigraph module 28 | ---------------------- 29 | 30 | .. automodule:: bigraph.bigraph 31 | :members: 32 | :undoc-members: 33 | :show-inheritance: 34 | 35 | Module contents 36 | --------------- 37 | 38 | .. automodule:: bigraph 39 | :members: 40 | :undoc-members: 41 | :show-inheritance: 42 | -------------------------------------------------------------------------------- /docs/make.bat: -------------------------------------------------------------------------------- 1 | @ECHO OFF 2 | 3 | pushd %~dp0 4 | 5 | REM Command file for Sphinx documentation 6 | 7 | if "%SPHINXBUILD%" == "" ( 8 | set SPHINXBUILD=sphinx-build 9 | ) 10 | set SOURCEDIR=source 11 | set BUILDDIR=build 12 | 13 | if "%1" == "" goto help 14 | 15 | %SPHINXBUILD% >NUL 2>NUL 16 | if errorlevel 9009 ( 17 | echo. 18 | echo.The 'sphinx-build' command was not found. Make sure you have Sphinx 19 | echo.installed, then set the SPHINXBUILD environment variable to point 20 | echo.to the full path of the 'sphinx-build' executable. Alternatively you 21 | echo.may add the Sphinx directory to PATH. 22 | echo. 23 | echo.If you don't have Sphinx installed, grab it from 24 | echo.http://sphinx-doc.org/ 25 | exit /b 1 26 | ) 27 | 28 | %SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% 29 | goto end 30 | 31 | :help 32 | %SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% 33 | 34 | :end 35 | popd 36 | -------------------------------------------------------------------------------- /bigraph/preprocessing/get_adjacents.py: -------------------------------------------------------------------------------- 1 | import networkx 2 | 3 | 4 | class GetAdjacents: 5 | def _get_hop_2_neighbours( 6 | self, graph: networkx.Graph, input_list: list, hop_n: int 7 | ) -> list: 8 | """ 9 | Find hop_n neighbours of each item in input_list 10 | 11 | :param graph: NetworkX graph object 12 | :param input_list: Input list 13 | :param hop_n: Hop hop_n 14 | :return: hop_n hop neighbours of the input list's items 15 | """ 16 | full_list = [] 17 | while hop_n > 0: 18 | hop_n -= 1 19 | output_list = [] 20 | for node in graph.nbunch_iter(input_list): 21 | for neighbour in graph[node]: 22 | if neighbour not in full_list: 23 | full_list.append(neighbour) 24 | output_list.append(neighbour) 25 | return output_list 26 | -------------------------------------------------------------------------------- /docs/build/html/_static/js/badge_only.js: -------------------------------------------------------------------------------- 1 | !function(e){var t={};function r(n){if(t[n])return t[n].exports;var o=t[n]={i:n,l:!1,exports:{}};return e[n].call(o.exports,o,o.exports,r),o.l=!0,o.exports}r.m=e,r.c=t,r.d=function(e,t,n){r.o(e,t)||Object.defineProperty(e,t,{enumerable:!0,get:n})},r.r=function(e){"undefined"!=typeof Symbol&&Symbol.toStringTag&&Object.defineProperty(e,Symbol.toStringTag,{value:"Module"}),Object.defineProperty(e,"__esModule",{value:!0})},r.t=function(e,t){if(1&t&&(e=r(e)),8&t)return e;if(4&t&&"object"==typeof e&&e&&e.__esModule)return e;var n=Object.create(null);if(r.r(n),Object.defineProperty(n,"default",{enumerable:!0,value:e}),2&t&&"string"!=typeof e)for(var o in e)r.d(n,o,function(t){return e[t]}.bind(null,o));return n},r.n=function(e){var t=e&&e.__esModule?function(){return e.default}:function(){return e};return r.d(t,"a",t),t},r.o=function(e,t){return Object.prototype.hasOwnProperty.call(e,t)},r.p="",r(r.s=4)}({4:function(e,t,r){}}); -------------------------------------------------------------------------------- /docs/source/bigraph.preprocessing.rst: -------------------------------------------------------------------------------- 1 | bigraph.preprocessing package 2 | ============================= 3 | 4 | Submodules 5 | ---------- 6 | 7 | bigraph.preprocessing.get\_adjacents module 8 | ------------------------------------------- 9 | 10 | .. automodule:: bigraph.preprocessing.get_adjacents 11 | :members: 12 | :undoc-members: 13 | :show-inheritance: 14 | 15 | bigraph.preprocessing.import\_files module 16 | ------------------------------------------ 17 | 18 | .. automodule:: bigraph.preprocessing.import_files 19 | :members: 20 | :undoc-members: 21 | :show-inheritance: 22 | 23 | bigraph.preprocessing.make\_graph module 24 | ---------------------------------------- 25 | 26 | .. automodule:: bigraph.preprocessing.make_graph 27 | :members: 28 | :undoc-members: 29 | :show-inheritance: 30 | 31 | bigraph.preprocessing.pd\_to\_list module 32 | ----------------------------------------- 33 | 34 | .. automodule:: bigraph.preprocessing.pd_to_list 35 | :members: 36 | :undoc-members: 37 | :show-inheritance: 38 | 39 | Module contents 40 | --------------- 41 | 42 | .. automodule:: bigraph.preprocessing 43 | :members: 44 | :undoc-members: 45 | :show-inheritance: 46 | -------------------------------------------------------------------------------- /docs/build/html/_sources/bigraph.preprocessing.rst.txt: -------------------------------------------------------------------------------- 1 | bigraph.preprocessing package 2 | ============================= 3 | 4 | Submodules 5 | ---------- 6 | 7 | bigraph.preprocessing.get\_adjacents module 8 | ------------------------------------------- 9 | 10 | .. automodule:: bigraph.preprocessing.get_adjacents 11 | :members: 12 | :undoc-members: 13 | :show-inheritance: 14 | 15 | bigraph.preprocessing.import\_files module 16 | ------------------------------------------ 17 | 18 | .. automodule:: bigraph.preprocessing.import_files 19 | :members: 20 | :undoc-members: 21 | :show-inheritance: 22 | 23 | bigraph.preprocessing.make\_graph module 24 | ---------------------------------------- 25 | 26 | .. automodule:: bigraph.preprocessing.make_graph 27 | :members: 28 | :undoc-members: 29 | :show-inheritance: 30 | 31 | bigraph.preprocessing.pd\_to\_list module 32 | ----------------------------------------- 33 | 34 | .. automodule:: bigraph.preprocessing.pd_to_list 35 | :members: 36 | :undoc-members: 37 | :show-inheritance: 38 | 39 | Module contents 40 | --------------- 41 | 42 | .. automodule:: bigraph.preprocessing 43 | :members: 44 | :undoc-members: 45 | :show-inheritance: 46 | -------------------------------------------------------------------------------- /tests/data/inputs/id_labels.csv: -------------------------------------------------------------------------------- 1 | ID,Label 2 | 0,left_node_0 3 | 1,left_node_1 4 | 2,left_node_2 5 | 3,left_node_3 6 | 4,left_node_4 7 | 5,left_node_5 8 | 6,left_node_6 9 | 7,left_node_7 10 | 8,left_node_8 11 | 9,left_node_9 12 | 10,left_node_10 13 | 11,left_node_11 14 | 12,left_node_12 15 | 13,left_node_13 16 | 14,left_node_14 17 | 15,left_node_15 18 | 16,left_node_16 19 | 17,left_node_17 20 | 18,left_node_18 21 | 19,left_node_19 22 | 20,left_node_20 23 | 21,left_node_21 24 | 22,left_node_22 25 | 23,left_node_23 26 | 24,left_node_24 27 | 25,left_node_25 28 | 26,left_node_26 29 | 27,left_node_27 30 | 28,left_node_28 31 | 29,left_node_29 32 | 30,left_node_30 33 | 31,left_node_31 34 | 32,left_node_32 35 | 33,left_node_33 36 | 34,left_node_34 37 | 35,left_node_35 38 | 36,left_node_36 39 | 37,left_node_37 40 | 38,left_node_38 41 | 100,right_node_0 42 | 101,right_node_1 43 | 102,right_node_2 44 | 103,right_node_3 45 | 104,right_node_4 46 | 105,right_node_5 47 | 106,right_node_6 48 | 107,right_node_7 49 | 108,right_node_8 50 | 109,right_node_9 51 | 110,right_node_10 52 | 111,right_node_11 53 | 112,right_node_12 54 | 113,right_node_13 55 | 114,right_node_14 56 | 115,right_node_15 57 | 116,right_node_16 58 | 117,right_node_17 59 | 118,right_node_18 60 | 119,right_node_19 61 | 120,right_node_20 62 | 121,right_node_21 63 | 122,right_node_22 64 | 123,right_node_23 65 | 124,right_node_24 66 | 125,right_node_25 67 | 126,right_node_26 68 | -------------------------------------------------------------------------------- /docs/source/intro.rst: -------------------------------------------------------------------------------- 1 | Introduction 2 | ============ 3 | 4 | ``bigraph`` is a high-level OO Python package which aims to provide an easy and intuitive way of interacting with bipartite networks. In essence, this package is an extension of the ``NetworkX`` package (see `here `_) 5 | 6 | The aim here was to define an easy-to-use package which would allow developers to perform ``link pridiction``, ``evaluation``, and ``visualization`` of the results. 7 | 8 | The current implementation has been developed and tested in Python 3.6+, but should work with Python 2.7+ (maybe with minor modifications in terms of printing and error handling) and most Debian based OSs. 9 | 10 | Motivation 11 | ********** 12 | 13 | As a developer in the field of machine learning, I found it pretty hard to identify a Python package which would enable one to perform link pridiction algorithms over bipartite networks. 14 | 15 | This package is intended to provide a quick, as well as (hopefully) easy to undestand, way of dealing-with-bipartite-networks algorithm up and running, for all those out there, who, like myself, are hands-on learners and are eager to get their hands dirty from early on. 16 | 17 | Limitations 18 | *********** 19 | 20 | - Algorithms are quite a few, and thus have to be piled with new ones. 21 | - Evaluations used here are techniques used for unsupervised methods, however they may have to be modified. 22 | - There are more limitations for sure if you happened to encounter any issue, you are welcomed to make contributions or open and issue on github. -------------------------------------------------------------------------------- /docs/build/html/_sources/intro.rst.txt: -------------------------------------------------------------------------------- 1 | Introduction 2 | ============ 3 | 4 | ``bigraph`` is a high-level OO Python package which aims to provide an easy and intuitive way of interacting with bipartite networks. In essence, this package is an extension of the ``NetworkX`` package (see `here `_) 5 | 6 | The aim here was to define an easy-to-use package which would allow developers to perform ``link pridiction``, ``evaluation``, and ``visualization`` of the results. 7 | 8 | The current implementation has been developed and tested in Python 3.6+, but should work with Python 2.7+ (maybe with minor modifications in terms of printing and error handling) and most Debian based OSs. 9 | 10 | Motivation 11 | ********** 12 | 13 | As a developer in the field of machine learning, I found it pretty hard to identify a Python package which would enable one to perform link pridiction algorithms over bipartite networks. 14 | 15 | This package is intended to provide a quick, as well as (hopefully) easy to undestand, way of dealing-with-bipartite-networks algorithm up and running, for all those out there, who, like myself, are hands-on learners and are eager to get their hands dirty from early on. 16 | 17 | Limitations 18 | *********** 19 | 20 | - Algorithms are quite a few, and thus have to be piled with new ones. 21 | - Evaluations used here are techniques used for unsupervised methods, however they may have to be modified. 22 | - There are more limitations for sure if you happened to encounter any issue, you are welcomed to make contributions or open and issue on github. -------------------------------------------------------------------------------- /bigraph/preprocessing/make_graph.py: -------------------------------------------------------------------------------- 1 | import networkx as nx 2 | 3 | 4 | class MakeGraph: 5 | def make_graph( 6 | self, 7 | dataframe: dict, 8 | left_bipartite: str = "left_side", 9 | right_bipartite: str = "right_side", 10 | ): 11 | """ 12 | Make a graph based on the input dataframe 13 | 14 | :param left_bipartite: Left part of the graph 15 | :param right_bipartite: Right part of the graph 16 | :param dataframe: Bipartite graph dataframe 17 | :return: Generated networkx graph 18 | """ 19 | node_list = [] 20 | graph = nx.Graph() 21 | graph.add_nodes_from(dataframe[left_bipartite], bipartite=0) 22 | graph.add_nodes_from(dataframe[right_bipartite], bipartite=1) 23 | for node in dataframe.iterrows(): 24 | node_list.append(node[1][0]) 25 | node_list.append(node[1][1]) 26 | 27 | graph.add_edges_from(self._add_to_list(dataframe)) 28 | isolates = nx.isolates(graph) 29 | # TODO: make following line a choice to be able to remove isolates or not 30 | 31 | # graph.remove_nodes_from(isolates) 32 | print("Graph made successfully", "\n") 33 | return graph 34 | 35 | def _add_to_list(self, dataframe: dict) -> list: 36 | """ 37 | Generate link tuples and append them to a list 38 | 39 | :param dataframe: Dataframe containing links 40 | :return: Edge list 41 | """ 42 | edge_list = [] 43 | for edge_row in dataframe.iterrows(): 44 | tuples = edge_row[1][0], edge_row[1][1] 45 | edge_list.append(tuples) 46 | return edge_list 47 | -------------------------------------------------------------------------------- /License.txt: -------------------------------------------------------------------------------- 1 | License 2 | ======= 3 | 4 | BiGraph is distributed with the 3-clause BSD license. 5 | 6 | :: 7 | 8 | Copyright (C) 2019-2021, BiGraph Developers 9 | Soran Ghadri 10 | Taleb Zarhesh 11 | All rights reserved. 12 | 13 | Redistribution and use in source and binary forms, with or without 14 | modification, are permitted provided that the following conditions are 15 | met: 16 | 17 | * Redistributions of source code must retain the above copyright 18 | notice, this list of conditions and the following disclaimer. 19 | 20 | * Redistributions in binary form must reproduce the above 21 | copyright notice, this list of conditions and the following 22 | disclaimer in the documentation and/or other materials provided 23 | with the distribution. 24 | 25 | * Neither the name of the BiGraph Developers nor the names of its 26 | contributors may be used to endorse or promote products derived 27 | from this software without specific prior written permission. 28 | 29 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 30 | "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 31 | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR 32 | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT 33 | OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, 34 | SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT 35 | LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, 36 | DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY 37 | THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 38 | (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 39 | OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | /.idea/ 6 | 7 | # C extensions 8 | *.so 9 | 10 | # Distribution / packaging 11 | .Python 12 | build/ 13 | develop-eggs/ 14 | dist/ 15 | downloads/ 16 | eggs/ 17 | .eggs/ 18 | lib/ 19 | lib64/ 20 | parts/ 21 | sdist/ 22 | var/ 23 | wheels/ 24 | pip-wheel-metadata/ 25 | share/python-wheels/ 26 | *.egg-info/ 27 | .installed.cfg 28 | *.egg 29 | MANIFEST 30 | .idea 31 | 32 | # PyInstaller 33 | # Usually these files are written by a python script from a template 34 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 35 | *.manifest 36 | *.spec 37 | 38 | # Installer logs 39 | pip-log.txt 40 | pip-delete-this-directory.txt 41 | 42 | # Unit test / coverage reports 43 | htmlcov/ 44 | .tox/ 45 | .nox/ 46 | .coverage 47 | .coverage.* 48 | .cache 49 | nosetests.xml 50 | coverage.xml 51 | *.cover 52 | *.py,cover 53 | .hypothesis/ 54 | .pytest_cache/ 55 | 56 | # Translations 57 | *.mo 58 | *.pot 59 | 60 | # Django stuff: 61 | *.log 62 | local_settings.py 63 | db.sqlite3 64 | db.sqlite3-journal 65 | 66 | # Flask stuff: 67 | instance/ 68 | .webassets-cache 69 | 70 | # Scrapy stuff: 71 | .scrapy 72 | 73 | # Sphinx documentation 74 | #docs/_build/ 75 | 76 | # PyBuilder 77 | target/ 78 | 79 | # Jupyter Notebook 80 | .ipynb_checkpoints 81 | 82 | # IPython 83 | profile_default/ 84 | ipython_config.py 85 | 86 | # pyenv 87 | .python-version 88 | 89 | # pipenv 90 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 91 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 92 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 93 | # install all needed dependencies. 94 | #Pipfile.lock 95 | 96 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 97 | __pypackages__/ 98 | 99 | # Celery stuff 100 | celerybeat-schedule 101 | celerybeat.pid 102 | 103 | # SageMath parsed files 104 | *.sage.py 105 | 106 | # Environments 107 | .env 108 | .venv 109 | env/ 110 | venv/ 111 | ENV/ 112 | env.bak/ 113 | venv.bak/ 114 | 115 | # Spyder project settings 116 | .spyderproject 117 | .spyproject 118 | 119 | # Rope project settings 120 | .ropeproject 121 | 122 | # mkdocs documentation 123 | /site 124 | 125 | # mypy 126 | .mypy_cache/ 127 | .dmypy.json 128 | dmypy.json 129 | 130 | # Pyre type checker 131 | .pyre/ 132 | /predictions/ 133 | /inputs/ 134 | 135 | poetry.lock 136 | -------------------------------------------------------------------------------- /docs/build/html/_static/js/html5shiv.min.js: -------------------------------------------------------------------------------- 1 | /** 2 | * @preserve HTML5 Shiv 3.7.3 | @afarkas @jdalton @jon_neal @rem | MIT/GPL2 Licensed 3 | */ 4 | !function(a,b){function c(a,b){var c=a.createElement("p"),d=a.getElementsByTagName("head")[0]||a.documentElement;return c.innerHTML="x",d.insertBefore(c.lastChild,d.firstChild)}function d(){var a=t.elements;return"string"==typeof a?a.split(" "):a}function e(a,b){var c=t.elements;"string"!=typeof c&&(c=c.join(" ")),"string"!=typeof a&&(a=a.join(" ")),t.elements=c+" "+a,j(b)}function f(a){var b=s[a[q]];return 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19 | degree = set(graph[node]).__len__() 20 | if degree > 1: 21 | sum += (math.log(degree)) ** -1 22 | else: 23 | sum += 0 24 | return sum 25 | 26 | @staticmethod 27 | def common_neighbors(set_one: list, set_two: list) -> int: 28 | """ 29 | Calculate Common neighbors score for input lists 30 | 31 | :param set_one: A list of graph nodes -> part one 32 | :param set_two: A list of graph nodes -> part two 33 | :return: Common neighbours score 34 | """ 35 | return len(set(set_one) & set(set_two)) 36 | 37 | @staticmethod 38 | def preferential_attachment(set_one: list, set_two: list) -> int: 39 | """ 40 | Calculate Preferential attachment score for input lists 41 | 42 | :param set_one: A list of graph nodes -> part one 43 | :param set_two: A list of graph nodes -> part two 44 | :return: Preferential attachment score 45 | """ 46 | return len(set(set_one)) * len(set(set_two)) 47 | 48 | @staticmethod 49 | def jaccard(set_one: list, set_two: list) -> float: 50 | """ 51 | Calculate Jaccard score for input lists 52 | 53 | :param set_one: A list of graph nodes -> part one 54 | :param set_two: A list of graph nodes -> part two 55 | :return: Jaccard score 56 | """ 57 | intersection = len(set(set_one) & set(set_two)) 58 | union = len(set(set_one) | set(set_two)) 59 | return float(intersection) / float(union) 60 | 61 | @staticmethod 62 | def katz_similarity(node_i: int, node_j: int, graph) -> float: 63 | """ 64 | Calculate Katz score for input nodes 65 | 66 | :param node_i: Starting node 67 | :param node_j: Destination node 68 | :param graph: NetworkX bipartite graph 69 | :return: Katz similarity score 70 | """ 71 | length = 1 72 | neighbors = set(graph[node_i]) 73 | score = 0 74 | max_length = 2 75 | beta = 0.1 76 | 77 | while length <= max_length: 78 | number_of_paths = neighbors.count(node_j) 79 | if number_of_paths > 0: 80 | score += (beta**length) * number_of_paths 81 | 82 | neighbours_for_next_loop = [] 83 | for k in neighbors: 84 | neighbours_for_next_loop += set(graph[k]) 85 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of the most common options. For a full 4 | # list see the documentation: 5 | # https://www.sphinx-doc.org/en/master/usage/configuration.html 6 | 7 | # -- Path setup -------------------------------------------------------------- 8 | 9 | # If extensions (or modules to document with autodoc) are in another directory, 10 | # add these directories to sys.path here. If the directory is relative to the 11 | # documentation root, use os.path.abspath to make it absolute, like shown here. 12 | # 13 | import os 14 | import sys 15 | 16 | sys.path.insert(0, os.path.abspath("../../")) 17 | from datetime import datetime 18 | from pygments.styles import get_style_by_name 19 | 20 | 21 | # -- Project information ----------------------------------------------------- 22 | 23 | project = "Bigraph" 24 | copyright = f"2019-{datetime.now().year}, Soran Ghadri" 25 | author = "Soran Ghadri" 26 | 27 | style = get_style_by_name("friendly") 28 | style.background_color = "#f3f2f1" 29 | 30 | # The full version, including alpha/beta/rc tags 31 | release = "rc1" 32 | 33 | 34 | # -- General configuration --------------------------------------------------- 35 | 36 | # Add any Sphinx extension module names here, as strings. They can be 37 | # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom 38 | # ones. 39 | extensions = [ 40 | "sphinx_rtd_theme", 41 | "sphinx.ext.autodoc", 42 | "sphinx.ext.autosummary", 43 | "sphinx.ext.napoleon", 44 | "sphinx.ext.mathjax", 45 | ] 46 | 47 | # Add any paths that contain templates here, relative to this directory. 48 | templates_path = ["_templates"] 49 | 50 | napoleon_use_rtype = False 51 | 52 | napoleon_include_init_with_doc = True 53 | napoleon_google_docstring = True 54 | napoleon_use_param = True 55 | napoleon_use_ivar = True 56 | 57 | pygments_style = "friendly" 58 | 59 | 60 | # The language for content autogenerated by Sphinx. Refer to documentation 61 | # for a list of supported languages. 62 | # 63 | # This is also used if you do content translation via gettext catalogs. 64 | # Usually you set "language" from the command line for these cases. 65 | language = "english" 66 | 67 | # List of patterns, relative to source directory, that match files and 68 | # directories to ignore when looking for source files. 69 | # This pattern also affects html_static_path and html_extra_path. 70 | exclude_patterns = [] 71 | 72 | 73 | # -- Options for HTML output ------------------------------------------------- 74 | 75 | # The theme to use for HTML and HTML Help pages. See the documentation for 76 | # a list of builtin themes. 77 | # 78 | # html_theme = 'alabaster' 79 | html_theme = "sphinx_rtd_theme" 80 | html_title = "Bigraph Documentation" 81 | html_show_sourcelink = False 82 | html_baseurl = "https://github.com/bi-graph/bigraph" 83 | # html_show_copyright = False 84 | # Add any paths that contain custom static files (such as style sheets) here, 85 | # relative to this directory. They are copied after the builtin static files, 86 | # so a file named "default.css" will overwrite the builtin "default.css". 87 | html_static_path = ["_static"] 88 | 89 | html_theme_options = { 90 | "prev_next_buttons_location": "both", 91 | "style_nav_header_background": "#F5A603", 92 | "navigation_depth": 4, 93 | "collapse_navigation": True, 94 | "sticky_navigation": False, 95 | "logo_only": True, 96 | "display_version": True, 97 | "style_external_links": True, 98 | "titles_only": True, 99 | } 100 | 101 | napoleon_use_param = False 102 | -------------------------------------------------------------------------------- /docs/build/html/_static/js/html5shiv-printshiv.min.js: -------------------------------------------------------------------------------- 1 | /** 2 | * @preserve HTML5 Shiv 3.7.3-pre | @afarkas @jdalton @jon_neal @rem | MIT/GPL2 Licensed 3 | */ 4 | !function(a,b){function c(a,b){var c=a.createElement("p"),d=a.getElementsByTagName("head")[0]||a.documentElement;return 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stand for node 1, node 2, weight respectively 24 | :param label_id: A CSV file containing labels for nodes: 25 | 10,node_name which are ID,label for each node 26 | :param sep: A separator that is the boundary for distinct entities 27 | :return: links and label dataframes 28 | """ 29 | print("Importing files and making dataframes...") 30 | self._check_input_files(edge_csv, label_id) 31 | raw_adjacency_dictionary = pd.read_csv(edge_csv, sep=sep, *args, **kwargs) 32 | raw_label_dictionary = pd.read_csv(label_id, sep=sep, *args, **kwargs) 33 | # raw_adjacency_dictionary = raw_adjacency_dictionary.drop(['Weight'], axis=1) 34 | label_dictionary = {} 35 | for row in raw_label_dictionary.iterrows(): 36 | label_dictionary.update({row[1][0]: row[1][1]}) 37 | return raw_adjacency_dictionary, label_dictionary 38 | 39 | def _check_input_files(self, edge_csv: str, label_id: str) -> bool: 40 | """ 41 | Check if there is any input file. 42 | 43 | :param edge_csv: Path to the edge-list csv file 44 | :param label_id: Path to the label-id-list csv file 45 | :return: True on finishing successfully 46 | """ 47 | pathlib.Path("./inputs").mkdir(parents=True, exist_ok=True) 48 | right_nodes_count = random.randint(20, 30) 49 | left_nodes_count = random.randint(30, 40) 50 | if edge_csv == "./inputs/neighbour_matrix.csv": 51 | file_exists = os.path.isfile("./inputs/neighbour_matrix.csv") 52 | if not file_exists: 53 | self._generate_random_graph_edges(left_nodes_count, right_nodes_count) 54 | if label_id == "./inputs/id_labels.csv": 55 | file_exists = os.path.isfile("./inputs/id_labels.csv") 56 | if not file_exists: 57 | self._generate_random_graph_labels(left_nodes_count, right_nodes_count) 58 | return True 59 | 60 | def _generate_random_graph_labels( 61 | self, left_nodes_count: int, right_nodes_count: int 62 | ) -> bool: 63 | """ 64 | Generate Labels for randomly generated graph nodes by generate_random_graph_edges() function 65 | 66 | :param left_nodes_count: Number of the left-side nodes 67 | :param right_nodes_count: Number of the right-side nodes 68 | :return: True on success 69 | """ 70 | with open("./inputs/id_labels.csv", "w") as csvfile: 71 | file_writer = csv.writer( 72 | csvfile, delimiter=",", quotechar='"', quoting=csv.QUOTE_MINIMAL 73 | ) 74 | file_writer.writerow(["ID", "Label"]) 75 | for i in range(left_nodes_count): 76 | file_writer.writerow([i, f"left_node_{i}"]) 77 | for i in range(right_nodes_count): 78 | file_writer.writerow([i + 100, f"right_node_{i}"]) 79 | return True 80 | 81 | def _generate_random_graph_edges( 82 | self, left_nodes_count: int, right_nodes_count: int 83 | ) -> bool: 84 | """ 85 | Generate a random graph and write it to a CSV file 86 | 87 | :param left_nodes_count: Number of the left-side nodes 88 | :param right_nodes_count: Number of the right-side nodes 89 | :return: True on success 90 | """ 91 | with open("./inputs/neighbour_matrix.csv", "w") as csvfile: 92 | file_writer = csv.writer( 93 | csvfile, delimiter=",", 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Literal.Number.Integer.Long */ -------------------------------------------------------------------------------- /docs/build/html/search.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Search — Bigraph Documentation 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 |
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219 | 220 | 221 | 226 | 227 | 228 | 229 | 230 | 231 | 232 | 233 | -------------------------------------------------------------------------------- /docs/build/html/py-modindex.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Python Module Index — Bigraph Documentation 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 |
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Python Module Index

159 | 160 |
161 | b 162 |
163 | 164 | 165 | 166 | 168 | 169 | 171 | 174 | 175 | 176 | 179 | 180 | 181 | 184 | 185 | 186 | 189 | 190 | 191 | 194 | 195 | 196 | 199 | 200 | 201 | 204 | 205 | 206 | 209 | 210 | 211 | 214 | 215 | 216 | 219 |
 
167 | b
172 | bigraph 173 |
    177 | bigraph.algorithms 178 |
    182 | bigraph.bigraph 183 |
    187 | bigraph.evaluation 188 |
    192 | bigraph.evaluation.evaluation 193 |
    197 | bigraph.preprocessing 198 |
    202 | bigraph.preprocessing.get_adjacents 203 |
    207 | bigraph.preprocessing.import_files 208 |
    212 | bigraph.preprocessing.make_graph 213 |
    217 | bigraph.preprocessing.pd_to_list 218 |
220 | 221 | 222 |
223 | 224 |
225 |
226 | 227 |
228 | 229 |
230 |

231 | © Copyright 2019-2021, Soran Ghadri. 232 | 233 |

234 |
235 | 236 | 237 | 238 | Built with Sphinx using a 239 | 240 | theme 241 | 242 | provided by Read the Docs. 243 | 244 |
245 |
246 |
247 | 248 |
249 | 250 |
251 | 252 | 253 | 258 | 259 | 260 | 261 | 262 | 263 | 264 | 265 | -------------------------------------------------------------------------------- /docs/build/html/intro.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Introduction — Bigraph Documentation 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 |
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  • Introduction
    • 142 | 143 | 144 |
  • 145 | 146 | 147 | 148 |
    • 149 | 150 |
151 | 152 | 153 | 161 | 162 |
163 |
164 |
165 |
166 | 167 |
168 |

Introduction

169 |

bigraph is a high-level OO Python package which aims to provide an easy and intuitive way of interacting with bipartite networks. In essence, this package is an extension of the NetworkX package (see here)

170 |

The aim here was to define an easy-to-use package which would allow developers to perform link pridiction, evaluation, and visualization of the results.

171 |

The current implementation has been developed and tested in Python 3.6+, but should work with Python 2.7+ (maybe with minor modifications in terms of printing and error handling) and most Debian based OSs.

172 |
173 |

Motivation

174 |

As a developer in the field of machine learning, I found it pretty hard to identify a Python package which would enable one to perform link pridiction algorithms over bipartite networks.

175 |

This package is intended to provide a quick, as well as (hopefully) easy to undestand, way of dealing-with-bipartite-networks algorithm up and running, for all those out there, who, like myself, are hands-on learners and are eager to get their hands dirty from early on.

176 |
177 |
178 |

Limitations

179 |
    180 |

  • Algorithms are quite a few, and thus have to be piled with new ones.

    • 181 |

  • Evaluations used here are techniques used for unsupervised methods, however they may have to be modified.

    • 182 |

  • There are more limitations for sure if you happened to encounter any issue, you are welcomed to make contributions or open and issue on github.

    • 183 |
184 |
185 |
186 | 187 | 188 |
189 | 190 |
191 |
192 | 196 | 197 |
198 | 199 |
200 |

201 | © Copyright 2019-2021, Soran Ghadri. 202 | 203 |

204 |
205 | 206 | 207 | 208 | Built with Sphinx using a 209 | 210 | theme 211 | 212 | provided by Read the Docs. 213 | 214 |
215 |
216 |
217 | 218 |
219 | 220 |
221 | 222 | 223 | 228 | 229 | 230 | 231 | 232 | 233 | 234 | 235 | -------------------------------------------------------------------------------- /docs/build/html/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Welcome to d's documentation! — Bigraph Documentation 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 |
50 | 51 | 100 | 101 |
102 | 103 | 104 | 110 | 111 | 112 |
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115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 | 134 |
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    137 | 138 |
  • »
    • 139 | 140 |
  • Welcome to d's documentation!
    • 141 | 142 | 143 |
  • 144 | 145 | 146 | 147 |
    • 148 | 149 |
150 | 151 | 152 | 158 | 159 |
160 |
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163 | 164 | 202 |
203 |

Indices and tables

204 | 209 |
210 | 211 | 212 |
213 | 214 |
215 |
216 | 219 | 220 |
221 | 222 |
223 |

224 | © Copyright 2019-2021, Soran Ghadri. 225 | 226 |

227 |
228 | 229 | 230 | 231 | Built with Sphinx using a 232 | 233 | theme 234 | 235 | provided by Read the Docs. 236 | 237 |
238 |
239 |
240 | 241 |
242 | 243 |
244 | 245 | 246 | 251 | 252 | 253 | 254 | 255 | 256 | 257 | 258 | -------------------------------------------------------------------------------- /tests/data/inputs/neighbour_matrix.csv: -------------------------------------------------------------------------------- 1 | left_side,right_side,Weight 2 | 36,112,1 3 | 10,103,1 4 | 8,100,1 5 | 21,107,1 6 | 1,122,3 7 | 29,103,1 8 | 28,123,1 9 | 23,100,3 10 | 11,110,1 11 | 1,120,1 12 | 29,124,2 13 | 32,121,1 14 | 1,115,3 15 | 10,127,2 16 | 25,103,1 17 | 22,103,2 18 | 31,118,1 19 | 33,108,2 20 | 31,123,2 21 | 18,124,3 22 | 10,104,3 23 | 17,106,3 24 | 5,106,1 25 | 16,101,3 26 | 17,120,2 27 | 31,119,2 28 | 24,118,1 29 | 13,100,2 30 | 13,122,1 31 | 12,127,1 32 | 30,124,3 33 | 39,106,2 34 | 12,113,1 35 | 36,114,1 36 | 5,103,1 37 | 18,100,1 38 | 28,102,1 39 | 21,126,3 40 | 39,115,3 41 | 8,124,2 42 | 23,123,3 43 | 5,122,1 44 | 11,113,3 45 | 7,122,1 46 | 34,108,2 47 | 19,116,2 48 | 29,100,3 49 | 18,111,1 50 | 27,126,3 51 | 1,120,3 52 | 14,127,1 53 | 17,126,2 54 | 30,108,2 55 | 21,126,3 56 | 14,100,1 57 | 13,118,3 58 | 27,126,2 59 | 13,102,2 60 | 4,117,1 61 | 26,112,2 62 | 37,120,2 63 | 39,126,1 64 | 24,102,2 65 | 11,117,1 66 | 25,107,2 67 | 11,121,1 68 | 27,108,2 69 | 5,110,3 70 | 32,118,3 71 | 4,102,3 72 | 11,109,2 73 | 30,127,2 74 | 31,126,2 75 | 14,120,2 76 | 22,124,3 77 | 9,104,1 78 | 7,107,3 79 | 37,105,1 80 | 33,107,1 81 | 16,113,2 82 | 25,102,3 83 | 33,113,2 84 | 32,119,3 85 | 1,104,2 86 | 4,103,2 87 | 4,100,1 88 | 29,106,3 89 | 36,101,1 90 | 4,100,1 91 | 12,102,1 92 | 0,113,3 93 | 24,102,1 94 | 13,123,2 95 | 25,116,3 96 | 26,100,2 97 | 12,117,1 98 | 19,103,2 99 | 15,110,1 100 | 11,125,1 101 | 32,114,2 102 | 30,105,2 103 | 10,106,2 104 | 28,125,3 105 | 7,100,1 106 | 15,123,3 107 | 33,113,2 108 | 16,124,1 109 | 26,111,1 110 | 36,100,3 111 | 23,104,3 112 | 29,108,3 113 | 11,101,1 114 | 7,110,1 115 | 11,101,2 116 | 0,101,3 117 | 9,119,3 118 | 39,113,2 119 | 22,119,1 120 | 3,113,3 121 | 2,115,1 122 | 16,109,1 123 | 25,109,2 124 | 20,104,1 125 | 15,103,3 126 | 25,113,2 127 | 29,126,1 128 | 11,111,1 129 | 24,125,3 130 | 14,125,2 131 | 0,102,1 132 | 10,109,2 133 | 15,116,2 134 | 39,122,2 135 | 35,124,2 136 | 0,122,2 137 | 30,114,2 138 | 7,110,3 139 | 11,114,1 140 | 16,123,3 141 | 39,109,2 142 | 36,110,3 143 | 33,115,2 144 | 1,113,3 145 | 12,111,1 146 | 35,117,1 147 | 8,109,2 148 | 22,110,2 149 | 18,104,2 150 | 34,125,3 151 | 19,121,1 152 | 39,106,3 153 | 31,119,1 154 | 11,120,3 155 | 7,102,2 156 | 17,116,3 157 | 11,110,1 158 | 16,126,1 159 | 18,100,3 160 | 25,115,2 161 | 38,101,2 162 | 34,111,1 163 | 39,123,3 164 | 16,106,2 165 | 38,122,1 166 | 26,120,1 167 | 27,106,1 168 | 22,101,3 169 | 32,112,1 170 | 8,105,1 171 | 25,127,2 172 | 27,108,2 173 | 37,108,2 174 | 16,108,1 175 | 31,104,3 176 | 38,105,1 177 | 36,111,3 178 | 9,116,3 179 | 33,124,3 180 | 22,119,2 181 | 20,114,1 182 | 36,101,1 183 | 4,120,2 184 | 3,100,2 185 | 11,105,3 186 | 10,105,2 187 | 27,102,3 188 | 27,105,1 189 | 34,113,1 190 | 27,125,1 191 | 38,102,1 192 | 37,102,2 193 | 25,101,2 194 | 13,100,1 195 | 0,108,3 196 | 34,125,1 197 | 37,112,1 198 | 36,106,3 199 | 32,113,2 200 | 8,106,1 201 | 33,116,1 202 | 18,113,3 203 | 39,104,3 204 | 29,108,2 205 | 2,104,1 206 | 19,116,1 207 | 33,108,3 208 | 27,115,2 209 | 6,110,3 210 | 30,125,1 211 | 36,107,2 212 | 35,104,2 213 | 1,124,3 214 | 9,122,2 215 | 26,107,3 216 | 23,106,2 217 | 28,125,2 218 | 16,117,1 219 | 7,110,3 220 | 34,118,2 221 | 28,118,3 222 | 24,109,1 223 | 39,119,1 224 | 32,123,1 225 | 20,102,1 226 | 29,101,2 227 | 28,115,3 228 | 32,111,1 229 | 12,107,1 230 | 38,125,3 231 | 31,121,3 232 | 33,117,3 233 | 13,124,3 234 | 14,117,2 235 | 22,111,2 236 | 30,106,1 237 | 38,114,2 238 | 34,114,3 239 | 13,116,2 240 | 37,123,1 241 | 14,109,3 242 | 19,120,2 243 | 18,102,1 244 | 7,110,2 245 | 25,111,2 246 | 32,103,3 247 | 32,124,2 248 | 2,110,1 249 | 33,127,1 250 | 12,105,2 251 | 6,103,1 252 | 33,108,1 253 | 30,117,1 254 | 38,121,1 255 | 20,116,3 256 | 29,103,1 257 | 29,122,3 258 | 24,113,3 259 | 5,121,2 260 | 11,104,2 261 | 10,112,2 262 | 17,108,1 263 | 4,116,1 264 | 29,103,1 265 | 35,114,3 266 | 24,123,3 267 | 2,126,3 268 | 2,120,2 269 | 13,111,2 270 | 8,117,2 271 | 11,108,1 272 | 2,121,1 273 | 38,110,3 274 | 31,122,2 275 | 11,119,1 276 | 17,103,2 277 | 19,115,1 278 | 6,126,1 279 | 6,104,3 280 | 8,125,1 281 | 25,124,1 282 | 19,124,2 283 | 0,100,3 284 | 15,126,3 285 | 18,121,2 286 | 24,125,2 287 | 10,116,3 288 | 24,122,2 289 | 31,103,2 290 | 32,115,2 291 | 35,115,3 292 | 31,104,2 293 | 25,103,2 294 | 38,127,3 295 | 23,100,3 296 | 26,123,2 297 | 37,121,1 298 | 22,109,1 299 | 11,118,1 300 | 3,114,3 301 | 0,111,1 302 | 8,122,2 303 | 3,110,1 304 | 21,106,2 305 | 8,112,1 306 | 37,102,3 307 | 14,116,1 308 | 22,125,3 309 | 23,114,1 310 | 22,120,3 311 | 29,111,2 312 | 24,126,1 313 | 10,120,1 314 | 10,120,2 315 | 9,115,3 316 | 17,118,3 317 | 14,120,1 318 | 36,106,2 319 | 19,120,3 320 | 36,127,1 321 | 6,111,3 322 | 5,108,3 323 | 7,119,2 324 | 7,116,1 325 | 26,126,3 326 | 36,124,2 327 | 33,101,3 328 | 30,108,2 329 | 19,117,2 330 | 9,127,3 331 | 2,108,1 332 | 10,113,2 333 | 4,107,1 334 | 35,115,2 335 | 3,110,2 336 | 23,115,3 337 | 13,122,1 338 | 3,102,1 339 | 1,102,3 340 | 35,111,2 341 | 35,111,1 342 | 8,122,3 343 | 4,123,2 344 | 9,126,3 345 | 5,109,2 346 | 37,124,1 347 | 36,119,3 348 | 37,102,3 349 | 1,119,1 350 | 12,109,1 351 | 11,111,1 352 | 37,117,1 353 | 15,101,3 354 | 0,113,2 355 | 4,102,1 356 | 14,110,2 357 | 39,107,3 358 | 3,116,1 359 | 15,113,3 360 | 16,120,2 361 | 39,104,2 362 | 7,115,2 363 | 36,102,3 364 | 39,110,3 365 | 13,113,1 366 | 15,101,1 367 | 33,123,2 368 | 15,118,2 369 | 20,112,2 370 | 14,118,1 371 | 28,118,3 372 | 33,103,3 373 | 2,125,3 374 | 9,107,2 375 | 4,106,1 376 | 18,117,3 377 | 15,126,1 378 | 4,106,2 379 | 36,118,1 380 | 18,123,2 381 | 32,101,2 382 | 22,102,1 383 | 16,115,2 384 | 11,127,2 385 | 10,114,2 386 | 37,120,3 387 | 29,112,1 388 | 30,106,1 389 | 31,121,3 390 | 26,122,2 391 | 35,122,3 392 | 19,113,1 393 | 26,114,2 394 | 30,112,3 395 | 12,115,3 396 | 20,122,3 397 | 5,119,1 398 | 14,106,1 399 | 15,101,1 400 | 10,102,1 401 | 2,124,2 402 | 11,126,2 403 | 34,101,2 404 | 19,124,3 405 | 24,113,3 406 | 13,121,1 407 | 5,100,3 408 | 4,121,3 409 | 1,122,3 410 | 32,127,2 411 | 18,116,1 412 | 11,125,2 413 | 28,111,3 414 | 10,125,1 415 | 37,102,1 416 | 39,115,3 417 | 13,113,2 418 | 36,106,3 419 | 5,120,3 420 | 5,112,2 421 | 26,103,2 422 | 39,104,3 423 | 12,126,3 424 | 11,108,2 425 | 8,127,1 426 | 26,116,2 427 | 36,102,2 428 | 1,105,3 429 | 24,125,2 430 | 20,123,2 431 | 19,116,2 432 | 12,115,3 433 | 2,123,3 434 | 32,110,1 435 | 10,106,2 436 | 17,102,3 437 | 16,121,2 438 | 2,112,1 439 | 2,116,1 440 | 29,115,2 441 | 28,123,1 442 | 15,117,2 443 | 24,123,1 444 | 14,120,1 445 | 8,120,1 446 | 21,101,1 447 | 8,126,2 448 | 0,111,3 449 | 10,119,1 450 | 28,106,3 451 | 14,119,2 452 | 33,105,2 453 | 0,106,2 454 | 13,116,2 455 | 36,100,1 456 | 35,116,1 457 | 28,116,1 458 | 25,121,3 459 | 6,114,2 460 | 6,104,1 461 | 15,121,3 462 | 10,107,3 463 | 0,116,2 464 | 38,115,1 465 | 35,100,3 466 | 36,123,2 467 | 11,112,2 468 | 31,119,2 469 | 0,127,3 470 | 17,124,2 471 | 11,106,2 472 | 4,116,2 473 | 26,101,3 474 | 22,117,2 475 | 16,117,2 476 | 5,117,2 477 | 8,111,3 478 | 27,120,1 479 | 13,105,2 480 | 19,119,3 481 | 30,112,2 482 | 39,122,1 483 | 15,113,2 484 | 33,125,3 485 | 9,103,1 486 | 36,117,1 487 | 37,118,2 488 | 0,103,3 489 | 26,119,3 490 | 28,108,1 491 | 0,122,3 492 | 20,113,3 493 | 6,116,2 494 | 39,125,3 495 | 32,126,3 496 | 37,107,1 497 | 17,115,1 498 | 10,106,3 499 | 29,104,1 500 | 8,110,2 501 | 37,112,1 502 | 3,105,2 503 | 27,100,2 504 | 4,104,1 505 | 3,127,1 506 | 25,116,2 507 | 28,116,1 508 | 20,120,1 509 | 0,111,3 510 | 17,108,1 511 | 29,122,3 512 | 38,113,1 513 | 15,108,3 514 | 6,117,2 515 | 7,126,1 516 | 3,122,1 517 | 2,127,2 518 | 38,119,1 519 | 34,109,2 520 | 20,111,2 521 | 28,114,2 522 | 3,108,1 523 | 6,124,1 524 | 16,105,1 525 | 32,116,1 526 | 28,105,2 527 | 1,127,2 528 | 39,101,1 529 | 13,106,2 530 | 19,100,2 531 | 26,101,1 532 | 8,112,3 533 | 9,108,3 534 | 24,121,1 535 | 37,110,2 536 | 38,116,1 537 | 26,121,2 538 | 6,117,1 539 | 30,120,2 540 | 36,125,1 541 | 8,104,2 542 | 31,104,3 543 | 26,104,2 544 | 1,113,2 545 | 0,120,1 546 | 37,125,3 547 | 34,116,1 548 | 14,103,3 549 | 39,106,1 550 | 10,117,2 551 | 9,115,2 552 | 32,102,1 553 | 5,117,2 554 | 27,106,2 555 | 2,114,3 556 | 5,112,2 557 | 20,105,3 558 | 14,114,3 559 | 36,119,3 560 | 37,123,1 561 | 29,105,3 562 | 18,115,3 563 | 10,108,2 564 | 28,108,1 565 | 35,114,3 566 | 19,108,3 567 | 32,119,2 568 | 7,118,1 569 | 29,110,1 570 | 24,105,2 571 | 13,126,1 572 | 7,110,3 573 | 6,110,2 574 | 14,105,3 575 | 23,125,2 576 | 26,103,3 577 | 13,121,1 578 | 12,106,2 579 | 19,113,3 580 | 36,100,3 581 | 0,103,2 582 | 4,122,3 583 | 6,109,3 584 | 39,120,2 585 | 21,123,1 586 | 27,117,2 587 | 39,123,2 588 | 23,109,2 589 | 27,121,1 590 | 0,119,2 591 | 0,116,2 592 | 26,122,2 593 | 28,100,1 594 | 13,106,1 595 | 10,120,2 596 | 15,115,2 597 | 12,126,1 598 | 17,104,3 599 | 21,101,3 600 | 24,111,3 601 | 24,115,3 602 | 4,117,2 603 | 26,110,3 604 | 0,117,1 605 | 6,105,2 606 | 36,123,3 607 | 1,107,3 608 | 14,101,1 609 | 7,107,2 610 | 8,100,1 611 | 27,120,2 612 | 0,122,1 613 | 30,117,3 614 | 17,110,3 615 | 33,120,1 616 | 3,116,3 617 | 6,125,2 618 | 11,107,2 619 | 26,119,3 620 | 19,107,2 621 | 33,127,2 622 | 7,100,3 623 | 25,116,1 624 | 20,125,2 625 | 30,103,2 626 | 11,119,2 627 | 27,100,1 628 | 15,110,1 629 | 24,111,2 630 | 31,108,2 631 | 4,110,3 632 | 2,107,2 633 | 4,112,1 634 | 3,107,2 635 | 11,113,2 636 | 26,110,2 637 | 14,116,3 638 | 1,111,2 639 | 31,126,1 640 | 15,111,1 641 | 26,108,1 642 | 30,109,2 643 | 25,101,1 644 | 26,110,3 645 | 17,109,2 646 | 39,107,2 647 | 16,112,3 648 | 23,126,2 649 | 9,106,2 650 | 12,112,1 651 | 4,123,1 652 | 16,123,3 653 | 30,114,2 654 | 28,105,1 655 | 37,113,1 656 | 15,110,3 657 | 29,112,2 658 | 28,109,3 659 | 6,109,2 660 | 28,113,3 661 | 28,105,3 662 | 35,117,2 663 | 17,119,1 664 | 22,102,2 665 | 22,119,2 666 | 15,100,3 667 | 5,109,1 668 | 5,110,2 669 | 31,112,2 670 | 4,120,3 671 | 4,103,3 672 | 15,100,2 673 | 32,102,1 674 | 36,118,3 675 | 2,120,2 676 | 28,107,1 677 | 6,114,3 678 | 6,109,3 679 | 2,124,2 680 | 27,115,3 681 | 15,104,3 682 | 29,104,2 683 | 37,114,1 684 | 28,112,1 685 | 33,109,3 686 | 31,111,2 687 | 14,105,1 688 | 19,125,2 689 | 39,127,2 690 | 31,107,3 691 | 4,109,2 692 | 25,109,2 693 | 11,109,1 694 | 37,122,1 695 | 3,110,1 696 | 25,112,2 697 | 34,109,1 698 | 23,102,3 699 | 11,118,3 700 | 20,124,2 701 | 26,118,3 702 | 37,106,3 703 | 2,117,2 704 | -------------------------------------------------------------------------------- /docs/build/html/bigraph.evaluation.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | bigraph.evaluation package — Bigraph Documentation 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 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    • 144 | 145 |
  • bigraph package »
    • 146 | 147 |
  • bigraph.evaluation package
    • 148 | 149 | 150 |
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157 | 158 | 159 | 167 | 168 |
169 |
170 |
171 |
172 | 173 |
174 |

bigraph.evaluation package

175 |
176 |

Submodules

177 |
178 |
179 |

bigraph.evaluation.evaluation module

180 |
181 |
182 | bigraph.evaluation.evaluation.evaluate(G: object, k: int = 2, method: str = 'all')
183 |

Evaluation interface for evaluating algorithms

184 |
185 |
Parameters
186 |
    187 |

  • G -- Networkx bipartite graph

    • 188 |

  • k -- Number of folds (used in KFold)

    • 189 |

  • method -- Algorithm name

    • 190 |
191 |
192 |
Returns
193 |

Calculated metrics: overall_precision, overall_auc, fpr_algo, tpr_algo

194 |
195 |
196 |
197 | 198 |
199 |
200 | bigraph.evaluation.evaluation.plot_ROC(fpr: list, tpr: list, met: str)
201 |

Plot ROC curve for algorithms

202 |
203 |
Parameters
204 |
    205 |

  • fpr -- *type: list - False positive rate metric

    • 206 |

  • tpr -- *type: list - True positive rate metric

    • 207 |

  • met -- Metric

    • 208 |
209 |
210 |
Returns
211 |

True on success

212 |
213 |
214 |
215 | 216 |
217 |
218 |

Module contents

219 |
220 |
221 | 222 | 223 |
224 | 225 |
226 |
227 | 231 | 232 |
233 | 234 |
235 |

236 | © Copyright 2019-2021, Soran Ghadri. 237 | 238 |

239 |
240 | 241 | 242 | 243 | Built with Sphinx using a 244 | 245 | theme 246 | 247 | provided by Read the Docs. 248 | 249 |
250 |
251 |
252 | 253 |
254 | 255 |
256 | 257 | 258 | 263 | 264 | 265 | 266 | 267 | 268 | 269 | 270 | -------------------------------------------------------------------------------- /docs/build/html/_static/doctools.js: -------------------------------------------------------------------------------- 1 | /* 2 | * doctools.js 3 | * ~~~~~~~~~~~ 4 | * 5 | * Sphinx JavaScript utilities for all documentation. 6 | * 7 | * :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS. 8 | * :license: BSD, see LICENSE for details. 9 | * 10 | */ 11 | 12 | /** 13 | * select a different prefix for underscore 14 | */ 15 | $u = _.noConflict(); 16 | 17 | /** 18 | * make the code below compatible with browsers without 19 | * an installed firebug like debugger 20 | if (!window.console || !console.firebug) { 21 | var names = ["log", "debug", "info", "warn", "error", "assert", "dir", 22 | "dirxml", "group", "groupEnd", "time", "timeEnd", "count", "trace", 23 | "profile", "profileEnd"]; 24 | window.console = {}; 25 | for (var i = 0; i < names.length; ++i) 26 | window.console[names[i]] = function() {}; 27 | } 28 | */ 29 | 30 | /** 31 | * small helper function to urldecode strings 32 | */ 33 | jQuery.urldecode = function(x) { 34 | return decodeURIComponent(x).replace(/\+/g, ' '); 35 | }; 36 | 37 | /** 38 | * small helper function to urlencode strings 39 | */ 40 | jQuery.urlencode = encodeURIComponent; 41 | 42 | /** 43 | * This function returns the parsed url parameters of the 44 | * current request. 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params.highlight[0].split(/\s+/) : []; 222 | if (terms.length) { 223 | var body = $('div.body'); 224 | if (!body.length) { 225 | body = $('body'); 226 | } 227 | window.setTimeout(function() { 228 | $.each(terms, function() { 229 | body.highlightText(this.toLowerCase(), 'highlighted'); 230 | }); 231 | }, 10); 232 | $('

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BiGraph

2 |
3 | PyPI version 4 | PyPI version 5 | PyPI - Python Version 6 | 7 | [comment]: <> (PyPI - Downloads) 8 | 9 | [comment]: <> (PyPI - Downloads) 10 | 11 | [comment]: <> (GitHub search hit counter) 12 | 13 | [comment]: <> (GitHub search hit counter) 14 | 15 | [comment]: <> (PyPI - Implementation) 16 | 17 | [comment]: <> (GitHub commit activity) 18 | 19 | [comment]: <> (GitHub last commit) 20 | GitHub Repo stars 21 |
22 |

BiGraph is a Python package for Link prediction in bipartite networks.

23 | 24 |
    25 |
  • Bug reports: https://github.com/bi-graph/bigraph/issues
    • 26 |
27 | 28 | > Node based similarities and Katz has been implemented. you can find algorithms in bigraph module. Algorithms implemented so far: 29 | 30 |
31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 |
Algorithms table
NumberAlgorithm
1jaccard
2adamic adar
3common neighbors
4 preferential attachment
5katz similarity
58 |
59 | 60 |
61 |

Installation

62 |

Install the latest version of BiGraph:

63 | 
$ pip install bigraph
64 |
65 | 66 |
67 |

Documentation

68 |

https://bigraph.readthedocs.io/en/latest/

69 | 70 |
71 | 72 |

Simple example

73 |

Predicting new links in a randomly generated graph using 74 | Adamic-Adar algorithm:

75 | 76 | ```python 77 | from bigraph.predict import aa_predict 78 | from bigraph.preprocessing import import_files, make_graph 79 | 80 | 81 | def adamic_adar_prediction(): 82 | """ 83 | Link prediction on bipartite networks 84 | :return: A dictionary containing predicted links 85 | """ 86 | 87 | df, df_nodes = import_files() 88 | print(df) 89 | print(f"Graph Nodes: ", df_nodes) 90 | G = make_graph(df) 91 | print(G) 92 | predicted = aa_predict(G) # Here we have called Adamic Adar method from bigraph module 93 | return predicted 94 | 95 | 96 | # Executing the function 97 | 98 | if __name__ == '__main__': 99 | adamic_adar_prediction() 100 | ``` 101 | 102 |

Evaluating Adamic-Adar algorithm.
103 | You can try other provided prediction algorithms by replacing the "aa" argument.

104 | 105 | ```python 106 | from bigraph.evaluation.evaluation import evaluate 107 | from bigraph.preprocessing import import_files, make_graph 108 | 109 | 110 | def adamic_adar_evaluation(): 111 | """ 112 | Evaluate Adamic-Adar algorithm using 10-Fold cross-validation 113 | :return: A dictionary containing the evaluation results 114 | """ 115 | df, df_nodes = import_files() 116 | G = make_graph(df) 117 | results = evaluate(G, k=10, 118 | method='aa') # Here we have evaluated adamic-adar 119 | # methods using evaluation module. Methods are 'jc', 'aa', 'pa', 'cn' 120 | return results 121 | 122 | 123 | # Executing the function 124 | if __name__ == '__main__': 125 | adamic_adar_evaluation() 126 | ``` 127 |
128 |

Call for Contributions

129 |

The Bigraph project welcomes your expertise and enthusiasm!

130 | 131 |

Ways to contribute to Bigraph:

132 |
    133 |
  • Writing code
    • 134 |
  • Review pull requests
    • 135 |
  • Develop tutorials, presentations, and other educational materials
    • 136 |
  • Translate documentation and readme contents
    • 137 |
138 |
139 | 140 |
141 |

Issues

142 |

If you happened to encounter any issue in the codes, please report it 143 | here. 144 | A better way is to fork the repository on Github and/or create a pull request.

145 | 146 |
147 | 148 | 149 |

Metrics

150 |

Metrics that are calculated during evaluation:

151 | 152 |
153 | 154 | 155 | 156 | 157 | 158 | 159 | 160 | 161 | 162 | 163 | 164 | 165 | 166 | 167 | 168 | 169 | 170 | 171 | 172 | 173 | 174 | 175 | 176 | 177 | 178 | 179 |
Metrics table
NumberEvaluattion metrics
1Precision
2AUC
3ROC
4returns fpr*
5returns tpr*
180 |
181 | 182 | > * For further usages and calculating different metrics 183 | 184 |

Dataset format

185 |

Your dataset should be in the following format (Exclude the 'Row' column):

186 | 187 |
188 | 189 | 190 | 191 | 192 | 193 | 194 | 195 | 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 |
Sample edges (links) dataset
Rowleft_sideright_sideWeight*
1u0v11
2u2v11
3u1v21
4u3v31
5u4v32
227 |
228 | 229 | > * Note that running 
230 | from bigraph.preprocessing import import_files
231 | df, df_nodes = import_files()
will create a sample graph for you and will place it in the 232 | inputs directory. 233 | > * Although the weight has not been involved in current version, but, the format will be the same. 234 | 235 |

More examples

236 |

Predicting new links in a randomly generated graph using following algorithms:

237 |
    238 |
  • Preferential attachment
    • 239 |
  • Jaccard similarity
    • 240 |
  • Common neighbours
    • 241 |
242 | 243 | ```python 244 | from bigraph.predict import pa_predict, jc_predict, cn_predict 245 | from bigraph.preprocessing import import_files, make_graph 246 | 247 | 248 | def main(): 249 | """ 250 | Link prediction on bipartite networks 251 | :return: 252 | """ 253 | df, df_nodes = import_files() 254 | G = make_graph(df) 255 | pa_predict(G) # Preferential attachment 256 | jc_predict(G) # Jaccard coefficient 257 | cn_predict(G) # Common neighbors 258 | 259 | 260 | # Executing the function 261 | if __name__ == '__main__': 262 | main() 263 | ``` 264 | 265 |

References

266 | 267 |
268 | 269 | 270 | 271 | 272 | 273 | 274 | 275 | 276 | 277 | 279 | 280 | 281 | 282 | 283 | 285 | 286 | 287 | 288 | 289 | 290 | 291 | 292 |
References table
NumberReferenceYear
1Yang, Y., Lichtenwalter, R.N. & Chawla, N.V. Evaluating link prediction methods. Knowl Inf Syst 45, 751–782 (2015). https://doi.org/10.1007/s10115-014-0789-02015
2Liben-nowell, David & Kleinberg, Jon. (2003). The Link Prediction Problem for Social Networks. Journal of the American Society for Information Science and Technology.https://doi.org/58.10.1002/asi.205912003
2......
293 |
294 | 295 |

Future work

296 | 297 | - [x] Modulate the functions 298 | - [ ] Add more algorithms 299 | - [ ] Run on CUDA cores 300 | - [ ] Make it faster using vectorization etc. 301 | - [ ] Add more preprocessors 302 | - [ ] Add dataset, graph, and dataframe manipulations 303 | - [ ] Unify and reconstruct the architecture and eliminate redundancy 304 | 305 | 306 |

Notes

307 |
    308 |
  • 309 | It can export the graph in .json and .gexf format 310 | for further usages. For instance: Gephi etc. 311 |
    • 312 |
313 | 314 | 315 |

If you found it helpful, please give us a :star:

316 | 317 |

License

318 |

Released under the BSD license

319 | 
Copyright © 2017-2021 BiGraph Developers
320 | Soran Ghadri (soran.gdr.cs@gmail.com)
321 | Taleb Zarhesh (taleb.zarhesh@gmail.com)
322 |
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32 | -------------------------------------------------------------------------------- /docs/build/html/_static/language_data.js: -------------------------------------------------------------------------------- 1 | /* 2 | * language_data.js 3 | * ~~~~~~~~~~~~~~~~ 4 | * 5 | * This script contains the language-specific data used by searchtools.js, 6 | * namely the list of stopwords, stemmer, scorer and splitter. 7 | * 8 | * :copyright: Copyright 2007-2020 by the Sphinx team, see AUTHORS. 9 | * :license: BSD, see LICENSE for details. 10 | * 11 | */ 12 | 13 | var stopwords = ["a","and","are","as","at","be","but","by","for","if","in","into","is","it","near","no","not","of","on","or","such","that","the","their","then","there","these","they","this","to","was","will","with"]; 14 | 15 | 16 | /* Non-minified version JS is _stemmer.js if file is provided */ 17 | /** 18 | * Porter Stemmer 19 | */ 20 | var Stemmer = function() { 21 | 22 | var step2list = { 23 | ational: 'ate', 24 | tional: 'tion', 25 | enci: 'ence', 26 | anci: 'ance', 27 | izer: 'ize', 28 | bli: 'ble', 29 | alli: 'al', 30 | entli: 'ent', 31 | eli: 'e', 32 | ousli: 'ous', 33 | ization: 'ize', 34 | ation: 'ate', 35 | ator: 'ate', 36 | alism: 'al', 37 | iveness: 'ive', 38 | fulness: 'ful', 39 | ousness: 'ous', 40 | aliti: 'al', 41 | iviti: 'ive', 42 | biliti: 'ble', 43 | logi: 'log' 44 | }; 45 | 46 | var step3list = { 47 | icate: 'ic', 48 | ative: '', 49 | alize: 'al', 50 | iciti: 'ic', 51 | ical: 'ic', 52 | ful: '', 53 | ness: '' 54 | }; 55 | 56 | var c = "[^aeiou]"; // consonant 57 | var v = "[aeiouy]"; // vowel 58 | var C = c + "[^aeiouy]*"; // consonant sequence 59 | var V = v + "[aeiou]*"; // vowel sequence 60 | 61 | var mgr0 = "^(" + C + ")?" + V + C; // [C]VC... is m>0 62 | var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$"; // [C]VC[V] is m=1 63 | var mgr1 = "^(" + C + ")?" + V + C + V + C; // [C]VCVC... is m>1 64 | var s_v = "^(" + C + ")?" + v; // vowel in stem 65 | 66 | this.stemWord = function (w) { 67 | var stem; 68 | var suffix; 69 | var firstch; 70 | var origword = w; 71 | 72 | if (w.length < 3) 73 | return w; 74 | 75 | var re; 76 | var re2; 77 | var re3; 78 | var re4; 79 | 80 | firstch = w.substr(0,1); 81 | if (firstch == "y") 82 | w = firstch.toUpperCase() + w.substr(1); 83 | 84 | // Step 1a 85 | re = /^(.+?)(ss|i)es$/; 86 | re2 = /^(.+?)([^s])s$/; 87 | 88 | if (re.test(w)) 89 | w = w.replace(re,"$1$2"); 90 | else if (re2.test(w)) 91 | w = w.replace(re2,"$1$2"); 92 | 93 | // Step 1b 94 | re = /^(.+?)eed$/; 95 | re2 = /^(.+?)(ed|ing)$/; 96 | if (re.test(w)) { 97 | var fp = re.exec(w); 98 | re = new RegExp(mgr0); 99 | if (re.test(fp[1])) { 100 | re = /.$/; 101 | w = w.replace(re,""); 102 | } 103 | } 104 | else if (re2.test(w)) { 105 | var fp = re2.exec(w); 106 | stem = fp[1]; 107 | re2 = new RegExp(s_v); 108 | if (re2.test(stem)) { 109 | w = stem; 110 | re2 = /(at|bl|iz)$/; 111 | re3 = new RegExp("([^aeiouylsz])\\1$"); 112 | re4 = new RegExp("^" + C + v + "[^aeiouwxy]$"); 113 | if (re2.test(w)) 114 | w = w + "e"; 115 | else if (re3.test(w)) { 116 | re = /.$/; 117 | w = w.replace(re,""); 118 | } 119 | else if (re4.test(w)) 120 | w = w + "e"; 121 | } 122 | } 123 | 124 | // Step 1c 125 | re = /^(.+?)y$/; 126 | if (re.test(w)) { 127 | var fp = re.exec(w); 128 | stem = fp[1]; 129 | re = new RegExp(s_v); 130 | if (re.test(stem)) 131 | w = stem + "i"; 132 | } 133 | 134 | // Step 2 135 | re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/; 136 | if (re.test(w)) { 137 | var fp = re.exec(w); 138 | stem = fp[1]; 139 | suffix = fp[2]; 140 | re = new RegExp(mgr0); 141 | if (re.test(stem)) 142 | w = stem + step2list[suffix]; 143 | } 144 | 145 | // Step 3 146 | re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/; 147 | if (re.test(w)) { 148 | var fp = re.exec(w); 149 | stem = fp[1]; 150 | suffix = fp[2]; 151 | re = new RegExp(mgr0); 152 | if (re.test(stem)) 153 | w = stem + step3list[suffix]; 154 | } 155 | 156 | // Step 4 157 | re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/; 158 | re2 = /^(.+?)(s|t)(ion)$/; 159 | if (re.test(w)) { 160 | var fp = re.exec(w); 161 | stem = fp[1]; 162 | re = new RegExp(mgr1); 163 | if (re.test(stem)) 164 | w = stem; 165 | } 166 | else if (re2.test(w)) { 167 | var fp = re2.exec(w); 168 | stem = fp[1] + fp[2]; 169 | re2 = new RegExp(mgr1); 170 | if (re2.test(stem)) 171 | w = stem; 172 | } 173 | 174 | // Step 5 175 | re = /^(.+?)e$/; 176 | if (re.test(w)) { 177 | var fp = re.exec(w); 178 | stem = fp[1]; 179 | re = new RegExp(mgr1); 180 | re2 = new RegExp(meq1); 181 | re3 = new RegExp("^" + C + v + "[^aeiouwxy]$"); 182 | if (re.test(stem) || (re2.test(stem) && !(re3.test(stem)))) 183 | w = stem; 184 | } 185 | re = /ll$/; 186 | re2 = new RegExp(mgr1); 187 | if (re.test(w) && re2.test(w)) { 188 | re = /.$/; 189 | w = w.replace(re,""); 190 | } 191 | 192 | // and turn initial Y back to y 193 | if (firstch == "y") 194 | w = firstch.toLowerCase() + w.substr(1); 195 | return w; 196 | } 197 | } 198 | 199 | 200 | 201 | 202 | 203 | var splitChars = (function() { 204 | var result = {}; 205 | var singles = [96, 180, 187, 191, 215, 247, 749, 885, 903, 907, 909, 930, 1014, 1648, 206 | 1748, 1809, 2416, 2473, 2481, 2526, 2601, 2609, 2612, 2615, 2653, 2702, 207 | 2706, 2729, 2737, 2740, 2857, 2865, 2868, 2910, 2928, 2948, 2961, 2971, 208 | 2973, 3085, 3089, 3113, 3124, 3213, 3217, 3241, 3252, 3295, 3341, 3345, 209 | 3369, 3506, 3516, 3633, 3715, 3721, 3736, 3744, 3748, 3750, 3756, 3761, 210 | 3781, 3912, 4239, 4347, 4681, 4695, 4697, 4745, 4785, 4799, 4801, 4823, 211 | 4881, 5760, 5901, 5997, 6313, 7405, 8024, 8026, 8028, 8030, 8117, 8125, 212 | 8133, 8181, 8468, 8485, 8487, 8489, 8494, 8527, 11311, 11359, 11687, 11695, 213 | 11703, 11711, 11719, 11727, 11735, 12448, 12539, 43010, 43014, 43019, 43587, 214 | 43696, 43713, 64286, 64297, 64311, 64317, 64319, 64322, 64325, 65141]; 215 | var i, j, start, end; 216 | for (i = 0; i < singles.length; i++) { 217 | result[singles[i]] = true; 218 | } 219 | var ranges = [[0, 47], [58, 64], [91, 94], [123, 169], [171, 177], [182, 184], [706, 709], 220 | [722, 735], [741, 747], [751, 879], [888, 889], [894, 901], [1154, 1161], 221 | [1318, 1328], [1367, 1368], [1370, 1376], [1416, 1487], [1515, 1519], [1523, 1568], 222 | [1611, 1631], [1642, 1645], [1750, 1764], [1767, 1773], [1789, 1790], [1792, 1807], 223 | [1840, 1868], [1958, 1968], [1970, 1983], [2027, 2035], [2038, 2041], [2043, 2047], 224 | [2070, 2073], [2075, 2083], [2085, 2087], [2089, 2307], [2362, 2364], [2366, 2383], 225 | [2385, 2391], [2402, 2405], [2419, 2424], [2432, 2436], [2445, 2446], [2449, 2450], 226 | [2483, 2485], [2490, 2492], [2494, 2509], [2511, 2523], [2530, 2533], [2546, 2547], 227 | [2554, 2564], [2571, 2574], [2577, 2578], [2618, 2648], [2655, 2661], [2672, 2673], 228 | [2677, 2692], [2746, 2748], [2750, 2767], [2769, 2783], [2786, 2789], [2800, 2820], 229 | [2829, 2830], [2833, 2834], [2874, 2876], [2878, 2907], [2914, 2917], [2930, 2946], 230 | [2955, 2957], [2966, 2968], [2976, 2978], [2981, 2983], [2987, 2989], [3002, 3023], 231 | [3025, 3045], [3059, 3076], [3130, 3132], [3134, 3159], [3162, 3167], [3170, 3173], 232 | [3184, 3191], [3199, 3204], [3258, 3260], [3262, 3293], [3298, 3301], [3312, 3332], 233 | [3386, 3388], [3390, 3423], [3426, 3429], [3446, 3449], [3456, 3460], [3479, 3481], 234 | [3518, 3519], [3527, 3584], [3636, 3647], [3655, 3663], [3674, 3712], [3717, 3718], 235 | [3723, 3724], [3726, 3731], [3752, 3753], [3764, 3772], [3774, 3775], [3783, 3791], 236 | [3802, 3803], [3806, 3839], [3841, 3871], [3892, 3903], [3949, 3975], [3980, 4095], 237 | [4139, 4158], [4170, 4175], [4182, 4185], [4190, 4192], [4194, 4196], [4199, 4205], 238 | [4209, 4212], [4226, 4237], [4250, 4255], [4294, 4303], [4349, 4351], [4686, 4687], 239 | [4702, 4703], [4750, 4751], [4790, 4791], [4806, 4807], [4886, 4887], [4955, 4968], 240 | [4989, 4991], [5008, 5023], [5109, 5120], [5741, 5742], [5787, 5791], [5867, 5869], 241 | [5873, 5887], [5906, 5919], [5938, 5951], [5970, 5983], [6001, 6015], [6068, 6102], 242 | [6104, 6107], [6109, 6111], [6122, 6127], [6138, 6159], [6170, 6175], [6264, 6271], 243 | [6315, 6319], [6390, 6399], [6429, 6469], [6510, 6511], [6517, 6527], [6572, 6592], 244 | [6600, 6607], [6619, 6655], [6679, 6687], [6741, 6783], [6794, 6799], [6810, 6822], 245 | [6824, 6916], [6964, 6980], [6988, 6991], [7002, 7042], [7073, 7085], [7098, 7167], 246 | [7204, 7231], [7242, 7244], [7294, 7400], [7410, 7423], [7616, 7679], [7958, 7959], 247 | [7966, 7967], [8006, 8007], [8014, 8015], [8062, 8063], [8127, 8129], [8141, 8143], 248 | [8148, 8149], [8156, 8159], [8173, 8177], [8189, 8303], [8306, 8307], [8314, 8318], 249 | [8330, 8335], [8341, 8449], [8451, 8454], [8456, 8457], [8470, 8472], [8478, 8483], 250 | [8506, 8507], [8512, 8516], [8522, 8525], [8586, 9311], [9372, 9449], [9472, 10101], 251 | [10132, 11263], [11493, 11498], [11503, 11516], [11518, 11519], [11558, 11567], 252 | [11622, 11630], [11632, 11647], [11671, 11679], [11743, 11822], [11824, 12292], 253 | [12296, 12320], [12330, 12336], [12342, 12343], [12349, 12352], [12439, 12444], 254 | [12544, 12548], [12590, 12592], [12687, 12689], [12694, 12703], [12728, 12783], 255 | [12800, 12831], [12842, 12880], [12896, 12927], [12938, 12976], [12992, 13311], 256 | [19894, 19967], [40908, 40959], [42125, 42191], [42238, 42239], [42509, 42511], 257 | [42540, 42559], [42592, 42593], [42607, 42622], [42648, 42655], [42736, 42774], 258 | [42784, 42785], [42889, 42890], [42893, 43002], [43043, 43055], [43062, 43071], 259 | [43124, 43137], [43188, 43215], [43226, 43249], [43256, 43258], [43260, 43263], 260 | [43302, 43311], [43335, 43359], [43389, 43395], [43443, 43470], [43482, 43519], 261 | [43561, 43583], [43596, 43599], [43610, 43615], [43639, 43641], [43643, 43647], 262 | [43698, 43700], [43703, 43704], [43710, 43711], [43715, 43738], [43742, 43967], 263 | [44003, 44015], [44026, 44031], [55204, 55215], [55239, 55242], [55292, 55295], 264 | [57344, 63743], [64046, 64047], [64110, 64111], [64218, 64255], [64263, 64274], 265 | [64280, 64284], [64434, 64466], [64830, 64847], [64912, 64913], [64968, 65007], 266 | [65020, 65135], [65277, 65295], [65306, 65312], [65339, 65344], [65371, 65381], 267 | [65471, 65473], [65480, 65481], [65488, 65489], [65496, 65497]]; 268 | for (i = 0; i < ranges.length; i++) { 269 | start = ranges[i][0]; 270 | end = ranges[i][1]; 271 | for (j = start; j <= end; j++) { 272 | result[j] = true; 273 | } 274 | } 275 | return result; 276 | })(); 277 | 278 | function splitQuery(query) { 279 | var result = []; 280 | var start = -1; 281 | for (var i = 0; i < query.length; i++) { 282 | if (splitChars[query.charCodeAt(i)]) { 283 | if (start !== -1) { 284 | result.push(query.slice(start, i)); 285 | start = -1; 286 | } 287 | } else if (start === -1) { 288 | start = i; 289 | } 290 | } 291 | if (start !== -1) { 292 | result.push(query.slice(start)); 293 | } 294 | return result; 295 | } 296 | 297 | 298 | -------------------------------------------------------------------------------- /docs/build/html/genindex.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Index — Bigraph Documentation 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 |
49 | 50 | 99 | 100 |
101 | 102 | 103 | 109 | 110 | 111 |
112 | 113 |
114 | 115 | 116 | 117 | 118 | 119 | 120 | 121 | 122 | 123 | 124 | 125 | 126 | 127 | 128 | 129 | 130 | 131 | 132 | 133 |
134 | 135 |
    136 | 137 |
  • »
    • 138 | 139 |
  • Index
    • 140 | 141 | 142 |
  • 143 | 144 | 145 | 146 |
    • 147 | 148 |
149 | 150 | 151 |
152 |
153 |
154 |
155 | 156 | 157 |

Index

158 | 159 |
160 | A 161 | | B 162 | | C 163 | | E 164 | | G 165 | | I 166 | | J 167 | | K 168 | | M 169 | | P 170 | 171 |
172 |

A

173 | 174 | 178 | 184 |
185 | 186 |

B

187 | 188 | 225 | 262 |
    189 |
  • 190 | bigraph 191 | 192 |
    • 196 |
  • 197 | bigraph.algorithms 198 | 199 |
    • 203 |
  • 204 | bigraph.bigraph 205 | 206 |
    • 210 |
  • 211 | bigraph.evaluation 212 | 213 |
    • 217 |
  • 218 | bigraph.evaluation.evaluation 219 | 220 |
    • 224 |
    226 |
  • 227 | bigraph.preprocessing 228 | 229 |
    • 233 |
  • 234 | bigraph.preprocessing.get_adjacents 235 | 236 |
    • 240 |
  • 241 | bigraph.preprocessing.import_files 242 | 243 |
    • 247 |
  • 248 | bigraph.preprocessing.make_graph 249 | 250 |
    • 254 |
  • 255 | bigraph.preprocessing.pd_to_list 256 | 257 |
    • 261 |
263 | 264 |

C

265 | 266 | 270 | 276 |
277 | 278 |

E

279 | 280 | 284 |
285 | 286 |

G

287 | 288 | 292 | 298 |
299 | 300 |

I

301 | 302 | 306 |
307 | 308 |

J

309 | 310 | 314 | 318 |
319 | 320 |

K

321 | 322 | 326 | 330 |
331 | 332 |

M

333 | 334 | 363 |
364 | 365 |

P

366 | 367 | 371 | 377 |
378 | 379 | 380 | 381 |
382 | 383 |
384 |
385 | 386 |
387 | 388 |
389 |

390 | © Copyright 2019-2021, Soran Ghadri. 391 | 392 |

393 |
394 | 395 | 396 | 397 | Built with Sphinx using a 398 | 399 | theme 400 | 401 | provided by Read the Docs. 402 | 403 |
404 |
405 |
406 | 407 |
408 | 409 |
410 | 411 | 412 | 417 | 418 | 419 | 420 | 421 | 422 | 423 | 424 | -------------------------------------------------------------------------------- /bigraph/bigraph.py: -------------------------------------------------------------------------------- 1 | import collections 2 | import operator 3 | import pathlib 4 | import time 5 | 6 | import networkx as nx 7 | import tabulate 8 | 9 | from bigraph.preprocessing import ImportFiles 10 | from .algorithms import Algorithms 11 | from .preprocessing import GetAdjacents 12 | from .preprocessing import MakeGraph 13 | 14 | 15 | class BiGraph(Algorithms, ImportFiles, MakeGraph, GetAdjacents): 16 | def __init__(self): 17 | df, df_nodes = self.import_files() 18 | self.graph = self.make_graph(df) 19 | 20 | print(self.graph.__dict__) 21 | snp = len({n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 0}) 22 | cancer = len({n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 1}) 23 | headers = ["Number of nodes", "Number of edges", "SNP", "Cancer"] 24 | table = [[self.graph.nodes.__len__(), self.graph.edges.__len__(), snp, cancer]] 25 | print(tabulate.tabulate(table, headers, tablefmt="fancy_grid")) 26 | print(nx.number_connected_components(self.graph)) 27 | 28 | def jc_predict(self) -> dict: 29 | """ 30 | Compute the Jaccard-Needham dissimilarity between two 1-D arrays. 31 | 32 | :return: A dictionary containing the Jaccard distance between vectors `left_element` and `right_element`. 33 | """ 34 | start_jc = time.time() 35 | 36 | dictionary = {} 37 | pathlib.Path("./predictions").mkdir(parents=True, exist_ok=True) 38 | 39 | out = open("./predictions/jaccard.csv", "w") 40 | hop2s = dict() 41 | neighbors = dict() 42 | jaccard_sim = collections.defaultdict(dict) 43 | left_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 0] 44 | right_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 1] 45 | 46 | out.write("(left_element, right_element)") 47 | out.write(",") 48 | out.write("Score") 49 | out.write("\n") 50 | 51 | exception_count = 0 52 | for left_element in left_set: 53 | hop2s[left_element] = self._get_hop_2_neighbours( 54 | self.graph, list(set(self.graph[left_element])), 1 55 | ) 56 | for right_element in right_set: 57 | neighbors[right_element] = list(set(self.graph[right_element])) 58 | if not (left_element, right_element) in self.graph.edges: 59 | try: 60 | jaccard_sim[left_element][right_element] = self.jaccard( 61 | hop2s[(left_element)], neighbors[(right_element)] 62 | ) 63 | if jaccard_sim[left_element][right_element] > 0: 64 | dictionary.update( 65 | { 66 | (left_element, right_element): jaccard_sim[ 67 | left_element 68 | ][right_element] 69 | } 70 | ) 71 | except: 72 | exception_count += 1 73 | print(exception_count) 74 | for k, v in sorted( 75 | dictionary.items(), key=operator.itemgetter(1), reverse=True 76 | ): 77 | out.write(str((k[0], k[1]))) 78 | out.write(",") 79 | out.write(str(jaccard_sim[k[0]][k[1]])) 80 | out.write("\n") 81 | 82 | _time = time.time() - start_jc 83 | print("Jaccard Executed in {} seconds".format(_time), "\n") 84 | 85 | return dictionary 86 | 87 | def aa_predict(self) -> dict: 88 | """ 89 | Compute the Jaccard-Needham dissimilarity between two 1-D arrays. 90 | 91 | :return: A dictionary containing the Adamic-adar score for `left_element` and `right_element`. 92 | """ 93 | start_aa = time.time() 94 | 95 | print("Adamic_adar prediction starting...") 96 | pathlib.Path("./predictions").mkdir(parents=True, exist_ok=True) 97 | 98 | out = open("./predictions/adamic_adar.csv", "w") 99 | outN = open("./predictions/adamic_adar_with_name.csv", "w") 100 | hop2s = dict() 101 | neighbors = dict() 102 | aa_sim = collections.defaultdict(dict) 103 | sortDic = {} 104 | left_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 0] 105 | right_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 1] 106 | dictionary = {} 107 | 108 | out.write("(left_element, right_element)") 109 | out.write(",") 110 | out.write("Score") 111 | out.write("\n") 112 | 113 | exception_count = 0 114 | for left_element in left_set: 115 | hop2s[left_element] = self._get_hop_2_neighbours( 116 | self.graph, list(set(self.graph[left_element])), 1 117 | ) 118 | for right_element in right_set: 119 | neighbors[right_element] = list(set(self.graph[right_element])) 120 | if not (left_element, right_element) in self.graph.edges: 121 | try: 122 | aa_sim[left_element][right_element] = self.adamic_adar( 123 | hop2s[(left_element)], 124 | neighbors[(right_element)], 125 | self.graph, 126 | ) 127 | if aa_sim[left_element][right_element] > 0: 128 | dictionary.update( 129 | { 130 | (left_element, right_element): aa_sim[left_element][ 131 | right_element 132 | ] 133 | } 134 | ) 135 | except: 136 | exception_count += 1 137 | print(exception_count) 138 | 139 | for k, v in sorted( 140 | dictionary.items(), key=operator.itemgetter(1), reverse=True 141 | ): 142 | out.write(str((k[0], k[1]))) 143 | out.write(",") 144 | out.write(str(aa_sim[k[0]][k[1]])) 145 | out.write("\n") 146 | 147 | _time = time.time() - start_aa 148 | print("Adamic-adar Executed in {} seconds".format(_time), "\n") 149 | return dictionary 150 | 151 | def cn_predict(self) -> dict: 152 | """ 153 | Return the common neighbors of two nodes in a graph. 154 | 155 | :return: A dictionary containing the Common neighbours score for `left_element` and `right_element`. 156 | """ 157 | start_cn = time.time() 158 | 159 | pathlib.Path("./predictions").mkdir(parents=True, exist_ok=True) 160 | 161 | out = open("./predictions/common_neighbor.csv", "w") 162 | hop2s = dict() 163 | neighbors = dict() 164 | cn_sim = collections.defaultdict(dict) 165 | sortDic = {} 166 | 167 | left_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 0] 168 | right_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 1] 169 | 170 | dictionary = {} 171 | out.write("(left_element, right_element)") 172 | out.write(",") 173 | out.write("Score") 174 | out.write("\n") 175 | 176 | for left_element in left_set: 177 | hop2s[left_element] = self._get_hop_2_neighbours( 178 | self.graph, list(set(self.graph[left_element])), 1 179 | ) 180 | for right_element in right_set: 181 | # print('cancer {} -- '.format(len(G[right_element]))) 182 | neighbors[right_element] = list(set(self.graph[right_element])) 183 | if not (left_element, right_element) in self.graph.edges: 184 | cn_sim[left_element][right_element] = self.common_neighbors( 185 | hop2s[left_element], neighbors[right_element] 186 | ) 187 | 188 | if cn_sim[left_element][right_element] > 0: 189 | dictionary.update( 190 | { 191 | (left_element, right_element): cn_sim[left_element][ 192 | right_element 193 | ] 194 | } 195 | ) 196 | 197 | for k, v in sorted( 198 | dictionary.items(), key=operator.itemgetter(1), reverse=True 199 | ): 200 | # print(k[0],v) 201 | out.write(str((k[0], k[1]))) 202 | out.write(",") 203 | out.write(str(cn_sim[k[0]][k[1]])) 204 | out.write("\n") 205 | 206 | _time = time.time() - start_cn 207 | print("Common neighbours Executed in {} seconds".format(_time), "\n") 208 | 209 | return dictionary 210 | 211 | def pa_predict(self) -> dict: 212 | """ 213 | Compute the preferential attachment score of all node pairs. 214 | 215 | :return: A dictionary containing the Preferential attachment score for `left_element` and `right_element`. 216 | """ 217 | start_pa = time.time() 218 | # print('Preferential_attachment prediction starting...') 219 | dictionary = {} 220 | 221 | pathlib.Path("./predictions").mkdir(parents=True, exist_ok=True) 222 | out = open("./predictions/preferential_attachment.csv", "w") 223 | hop2s = dict() 224 | neighbors_right_element = dict() 225 | neighbors_left_element = dict() 226 | pa_sim = collections.defaultdict(dict) 227 | sortDic = {} 228 | left_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 0] 229 | right_set = [n for n, d in self.graph.nodes(data=True) if d["bipartite"] == 1] 230 | 231 | out.write("(left_element, right_element)") 232 | out.write(",") 233 | out.write("Score") 234 | out.write("\n") 235 | 236 | for left_element in left_set: 237 | neighbors_left_element[left_element] = list(set(self.graph[left_element])) 238 | for right_element in right_set: 239 | neighbors_right_element[right_element] = list( 240 | set(self.graph[right_element]) 241 | ) 242 | if not (left_element, right_element) in self.graph.edges: 243 | pa_sim[left_element][right_element] = self.preferential_attachment( 244 | neighbors_left_element[(left_element)], 245 | neighbors_right_element[(right_element)], 246 | ) 247 | if pa_sim[left_element][right_element] > 0: 248 | dictionary.update( 249 | { 250 | (left_element, right_element): pa_sim[left_element][ 251 | right_element 252 | ] 253 | } 254 | ) 255 | 256 | for k, v in sorted( 257 | dictionary.items(), key=operator.itemgetter(1), reverse=True 258 | ): 259 | out.write(str((k[0], k[1]))) 260 | out.write(",") 261 | out.write(str(pa_sim[k[0]][k[1]])) 262 | out.write("\n") 263 | 264 | _time = time.time() - start_pa 265 | print("Preferential attachment Executed in {} seconds".format(_time), "\n") 266 | 267 | return dictionary 268 | 269 | def katz_predict(self, df_nodes: dict) -> dict: 270 | """ 271 | Compute the Katz similarity score of all node pairs. 272 | 273 | :param df_nodes: Graph nodes 274 | :return: A dictionary containing the Preferential attachment score for `left_element` and `right_element`. 275 | """ 276 | start_katz = time.time() 277 | 278 | pathlib.Path("./predictions").mkdir(parents=True, exist_ok=True) 279 | 280 | out = open("./predictions/preferential_attachment.csv", "w") 281 | outN = open("./predictions/preferential_attachment_with_name.csv", "w") 282 | hop2s = dict() 283 | neighbors = dict() 284 | katz_sim = collections.defaultdict(dict) 285 | sortDic = {} 286 | left_set = list(set(nx.bipartite.sets(self.graph)[0])) 287 | right_set = list(set(nx.bipartite.sets(self.graph)[1])) 288 | 289 | out.write("(left_element, right_element)") 290 | out.write(",") 291 | out.write("Score") 292 | out.write("\n") 293 | 294 | outN.write("(left_element, right_element)") 295 | outN.write(",") 296 | outN.write("Score") 297 | outN.write("\n") 298 | 299 | for left_element in left_set: 300 | hop2s[left_element] = self._get_hop_2_neighbours( 301 | self.graph, list(set(self.graph[left_element])), 1 302 | ) 303 | for right_element in right_set: 304 | neighbors[right_element] = list(set(self.graph[right_element])) 305 | if not (left_element, right_element) in self.graph.edges: 306 | katz_sim[left_element][right_element] = self.katz_similarity( 307 | int(left_element), int(right_element), self.graph 308 | ) 309 | if katz_sim[left_element][right_element] > 0: 310 | out.write(str((left_element, right_element))) 311 | out.write(",") 312 | out.write(str(katz_sim[left_element][right_element])) 313 | out.write("\n") 314 | 315 | outN.write( 316 | str((df_nodes[left_element], df_nodes[right_element])) 317 | ) 318 | outN.write(",") 319 | outN.write(str(katz_sim[left_element][right_element])) 320 | outN.write("\n") 321 | 322 | _time = time.time() - start_katz 323 | print("Katz similarity Executed in {} seconds".format(_time), "\n") 324 | --------------------------------------------------------------------------------