{ "info": { "author": "Mikio Shiga, Atsuya Matsubara", "author_email": "m-shiga@ist.osaka-u.ac.jp, at-matbr@ist.osaka-u.ac.jp", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: Implementation :: CPython", "Programming Language :: Python :: Implementation :: PyPy" ], "description": "Automatic Graph Visualizer (AGVIZ)\n==================================\n\n**An automatic graph visualize package for\n`Cytoscape `__.**\n\nMore Details\n------------\n\nAutomatic Graph Visualizer[AGVIZ] is one of the Cytoscape Projects.\nAGVIZ attaches some visualize information for the Cytoscape to the\nnetwork structure information (`CX\nformat `__).\n\nSystem Requirements\n-------------------\n\nTo use AGVIZ, you need the following:\n\n- Ubuntu (Recommend >=18.04) or macOS (Recommend >=10.14)\n\n - **Windows is not supported**\n\n- Python 3.x\n\nInstalling\n----------\n\nDownload or clone this repository\n\n::\n\n $ git clone https://github.com/idekerlab/auto-graph-visualizer\n\nIn the downloaded (cloned) directory, install using setup.py\n\n::\n\n $ python3 setup.py install\n\nKnown issues in installing\n^^^^^^^^^^^^^^^^^^^^^^^^^^\n\n- Perhaps, you have some error in ``python-igraph`` installation\n depending on some environments. In such case, try the following\n installation before setup.\n\n ::\n\n $ apt install build-essential python3-dev libxml2 libxml2-dev zlib1g-dev\n\n .. rubric:: Usage\n :name: usage\n\n ::\n\n $ cat your_file | agviz\n\n Options:\n\n- -n : Output graph name (.cx). (default : 'test\\_out')\n- -p : Output directory path. (default : './')\n- -a : Community detection algorithm. (default : 'greedy')\n\n - greedy : Based on the greedy optimization of modularity\n `detail `__\n - eigenvec : Newman's eigenvector community structure detection.\n `detail `__\n - labelprop : The label propagation method of Raghavan et al.\n `detail `__\n - rest : Community Detection Rest service.\n `detail `__\n (`github `__)\n **See the\n `example `__\n how to use.**\n\n- -cp : Base color palette. (default : 'hls')\n\n - hls\n\n - Accent\n\n - Set1\n\n - brg\n\n - hsv\n\n - gnuplot\n\n- -ns : The standard of nodesize. (default : 'betweenness')\n\n - closeness\n - degree\n - pagerank\n - betweenness\n - diversity\n\n- -maxns : Value of criterion which maximum the node size. (default :\n 100 \\*you may need adjust this value according to the criterion and\n the network)\n\n- -d : Density of output graph.(default : 'normal')\n\n - density\n - normal\n - sparse\n\n- -pos : Algorithm of node positioning for graph layout.(default :\n 'fa')\n\n - fa :\n `forceatras2 `__\n - kk : kamada-kawai >Tomihisa Kamada and Satoru Kawai. An Algorithm\n for Drawing General Undirected Graphs. Information Processing\n Letters 31:7-15, 1989.\n\n- -dln : The number of display labels. (default : 20)\n\nAuthors\n-------\n\n- **Keiichiro Ono** (`Github `__)\n- **Atsuya Matsubara** (`Github `__)\n- **Mikio Shiga** (`Github `__)\n\nLicense\n-------\n\nThis project is licensed under the MIT License - see the\n`LICENSE `__ file for details", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/idekerlab/auto-graph-visualizer", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "auto-graph-visualizer", "package_url": "https://pypi.org/project/auto-graph-visualizer/", "platform": "", "project_url": "https://pypi.org/project/auto-graph-visualizer/", "project_urls": { "Homepage": "https://github.com/idekerlab/auto-graph-visualizer" }, "release_url": "https://pypi.org/project/auto-graph-visualizer/0.1.1/", "requires_dist": null, "requires_python": "", "summary": "Automatic graph visualization package", "version": "0.1.1" }, "last_serial": 5876643, "releases": { "0.1.0": [ { "comment_text": "", "digests": { "md5": "0fb01443249b3ccc76c1f5968d4fbc11", "sha256": "6f2160b51b0c68a11b0ec09cd0f2728833dabd584f11d7754595a53d4e83197a" }, "downloads": -1, "filename": "auto-graph-visualizer-0.1.0.tar.gz", "has_sig": false, "md5_digest": "0fb01443249b3ccc76c1f5968d4fbc11", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11467, "upload_time": "2019-09-23T09:18:42", "url": "https://files.pythonhosted.org/packages/4d/ea/993f23ef9b95f5af4833b0013543dcd342093cd8643d4234448fb0b1b072/auto-graph-visualizer-0.1.0.tar.gz" } ], "0.1.1": [ { "comment_text": "", "digests": { "md5": "9f1e26fe75d5a5ec381372166e996ebf", "sha256": "e1e7bd982cc092ed609ad5251102bedfc9c9437d2bffac907e111a51dba76bbb" }, "downloads": -1, "filename": "auto-graph-visualizer-0.1.1.tar.gz", "has_sig": false, "md5_digest": "9f1e26fe75d5a5ec381372166e996ebf", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11471, "upload_time": "2019-09-23T23:57:42", "url": "https://files.pythonhosted.org/packages/d8/ed/ec8602b9965bf58bf7d52a4aba50824268d2e70362047e69a45e933d35ad/auto-graph-visualizer-0.1.1.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "9f1e26fe75d5a5ec381372166e996ebf", "sha256": "e1e7bd982cc092ed609ad5251102bedfc9c9437d2bffac907e111a51dba76bbb" }, "downloads": -1, "filename": "auto-graph-visualizer-0.1.1.tar.gz", "has_sig": false, "md5_digest": "9f1e26fe75d5a5ec381372166e996ebf", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11471, "upload_time": "2019-09-23T23:57:42", "url": "https://files.pythonhosted.org/packages/d8/ed/ec8602b9965bf58bf7d52a4aba50824268d2e70362047e69a45e933d35ad/auto-graph-visualizer-0.1.1.tar.gz" } ] }