{"id":22344734,"url":"https://github.com/languagemachines/knngraph","last_synced_at":"2025-03-26T10:13:31.385Z","repository":{"id":146793947,"uuid":"73699080","full_name":"LanguageMachines/knngraph","owner":"LanguageMachines","description":"KNN graph software originally in TiCC SVN","archived":false,"fork":false,"pushed_at":"2016-11-14T11:43:37.000Z","size":2,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":5,"default_branch":"master","last_synced_at":"2025-01-31T11:32:48.694Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/LanguageMachines.png","metadata":{"files":{"readme":"README","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-11-14T11:40:52.000Z","updated_at":"2016-11-14T11:43:38.000Z","dependencies_parsed_at":null,"dependency_job_id":"e13e08ee-b0e4-4264-9b90-b3d368afb77b","html_url":"https://github.com/LanguageMachines/knngraph","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LanguageMachines%2Fknngraph","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LanguageMachines%2Fknngraph/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LanguageMachines%2Fknngraph/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LanguageMachines%2Fknngraph/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LanguageMachines","download_url":"https://codeload.github.com/LanguageMachines/knngraph/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245632418,"owners_count":20647194,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-04T09:14:55.800Z","updated_at":"2025-03-26T10:13:31.380Z","avatar_url":"https://github.com/LanguageMachines.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"This is the README file for knngraph, version 1.0 beta.\n\n--------------------------------------------------------------------------------\nDescription\n--------------------------------------------------------------------------------\n\nknngraph is a set of rather trivial command line tools, written in\nPython, to visualize the nearest neighbours relations in a Timbl\ninstance base. It uses neato (part of the graphviz package for\nautomatic graph layout) to draw the instance base as a graph with the\ninstances as nodes and their nearest neighbour relations as arcs. It\nconsists of two files:\n\n- indexcol: adds an index as the first column to an instances file\n\n- timblout2graph: transforms Timbl output to a neato graph\n\n--------------------------------------------------------------------------------\nPlatform\n--------------------------------------------------------------------------------\n\nTested on Linux and OS X (10.3, Panther). Should work on any OS with a Python\ninterpreter and neato. (Will probably run on MS windows as well,\nalthough I have not tested it.)\n\n--------------------------------------------------------------------------------\nRequirements\n--------------------------------------------------------------------------------\n\n- a recent version of Timbl (5.0 or later) \n- neato, which is part of the grapviz package\n- a recent version of Python (2.3 or later)\n\n--------------------------------------------------------------------------------\nLicense\n--------------------------------------------------------------------------------\n\nYou are free to use, copy, distribute and modify this software. \n\n--------------------------------------------------------------------------------\nAuthor:\n--------------------------------------------------------------------------------\n\nErwin Marsi (see the file CONTACT)\n\n--------------------------------------------------------------------------------\nInstall\n--------------------------------------------------------------------------------\n\nUnzip the zip file anywhere you like\n\n--------------------------------------------------------------------------------\nUsage\n--------------------------------------------------------------------------------\n\nGenerating a graph requires 4 steps.\n\n1. Index your instance base\n\nYou have to add a unique number to each instance. This can be\naccomplished by simply numbering the instances. For example,\n\n  indexcol -d, \u003cdimin.train \u003eindexed.dimin.train\n\nWill add a number as the first column to my_instance_base and write\nthe result numbered_instance_base. By default the column delimiter is\nassumed to be a single space, hence the \"-d,\" is used here to force a\ncomma as the delimiter.\n\n\n2. Classification\n\nRun Timbl, using the instance base both as training and test\nmaterial. Use the \"+vn\" trace option to dump the nearest neighours to\nthe output\n\n  Timbl -k2 -f indexed.dimin.train -t indexed.dimin.train -o indexed.dimin.train.out +vn\n\n\n3. Generating a graph specification \n\nUse timblout2graph to generate a graph specification for neato.\n\n  ./timblout2graph \u003cindexed.dimin.train.out -d, \u003egraph.spec \n\n\nOptionally, you can edit this file to modify the format of the nodes\nand arcs. For instance, to give all nodes for class \"T\" the colour red, replace\n\n  [label=T];\n\nwith\n\n  [label=T,style=filled,color=red];\n\nSee the neato (or dot) manual for all formatting options.\n\n\n4. Generating a graph\n\nFinally, use neato to produce a drawing. To write a postscript file:\n  \n  neato -Tps -o graph.ps \u003cgraph.spec\n\nYou can use ghostview (or 'gv') to view grap.ps. See the neato (or\ndot) manual for other graphic formats.\n\n\n--------------------------------------------------------------------------------\nDocumentation\n--------------------------------------------------------------------------------\n\nAll scripts all self-documenting: use the '-h' options. \n\n\n--------------------------------------------------------------------------------\nPS\n--------------------------------------------------------------------------------\n\nIf you find knngraph useful, encounter bugs, or make improvements, please let\nme know.\n\ngood luck!\n\nErwin\n\n$Id$","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flanguagemachines%2Fknngraph","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flanguagemachines%2Fknngraph","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flanguagemachines%2Fknngraph/lists"}