{"id":442,"date":"2021-02-28T21:01:55","date_gmt":"2021-02-28T15:01:55","guid":{"rendered":"http:\/\/www.jichangqing.net\/wordpress\/?p=442"},"modified":"2021-02-28T21:04:39","modified_gmt":"2021-02-28T15:04:39","slug":"%e7%94%a8-networksx-%e7%bb%98%e5%88%b6%e5%b8%a6%e6%9d%83%e5%9b%be","status":"publish","type":"post","link":"http:\/\/www.jichangqing.net\/wordpress\/?p=442","title":{"rendered":"\u7528 networksx \u7ed8\u5236\u5e26\u6743\u56fe"},"content":{"rendered":"

Weighted Graph<\/h1>\n

An example using Graph as a weighted network.<\/p>\n

\"plot<\/p>\n

\n
\n
import<\/span> matplotlib.pyplot<\/span> as<\/span> plt<\/span>\r\nimport<\/span> networkx<\/span> as<\/span> nx<\/span>\r\n\r\nG<\/span> =<\/span> nx<\/span>.<\/span>Graph<\/span>()<\/span>\r\n\r\nG<\/span>.<\/span>add_edge<\/span>(<\/span>\"a\"<\/span>,<\/span> \"b\"<\/span>,<\/span> weight<\/span>=<\/span>0.6<\/span>)<\/span>\r\nG<\/span>.<\/span>add_edge<\/span>(<\/span>\"a\"<\/span>,<\/span> \"c\"<\/span>,<\/span> weight<\/span>=<\/span>0.2<\/span>)<\/span>\r\nG<\/span>.<\/span>add_edge<\/span>(<\/span>\"c\"<\/span>,<\/span> \"d\"<\/span>,<\/span> weight<\/span>=<\/span>0.1<\/span>)<\/span>\r\nG<\/span>.<\/span>add_edge<\/span>(<\/span>\"c\"<\/span>,<\/span> \"e\"<\/span>,<\/span> weight<\/span>=<\/span>0.7<\/span>)<\/span>\r\nG<\/span>.<\/span>add_edge<\/span>(<\/span>\"c\"<\/span>,<\/span> \"f\"<\/span>,<\/span> weight<\/span>=<\/span>0.9<\/span>)<\/span>\r\nG<\/span>.<\/span>add_edge<\/span>(<\/span>\"a\"<\/span>,<\/span> \"d\"<\/span>,<\/span> weight<\/span>=<\/span>0.3<\/span>)<\/span>\r\n\r\nelarge<\/a> =<\/span> [(<\/span>u<\/span>,<\/span> v<\/span>)<\/span> for<\/span> (<\/span>u<\/span>,<\/span> v<\/span>,<\/span> d<\/span>)<\/span> in<\/span> G<\/span>.<\/span>edges<\/span>(<\/span>data<\/span>=<\/span>True<\/span>)<\/span> if<\/span> d<\/span>[<\/span>\"weight\"<\/span>]<\/span> ><\/span> 0.5<\/span>]<\/span>\r\nesmall<\/a> =<\/span> [(<\/span>u<\/span>,<\/span> v<\/span>)<\/span> for<\/span> (<\/span>u<\/span>,<\/span> v<\/span>,<\/span> d<\/span>)<\/span> in<\/span> G<\/span>.<\/span>edges<\/span>(<\/span>data<\/span>=<\/span>True<\/span>)<\/span> if<\/span> d<\/span>[<\/span>\"weight\"<\/span>]<\/span> <=<\/span> 0.5<\/span>]<\/span>\r\n\r\npos<\/a> =<\/span> nx<\/span>.<\/span>spring_layout<\/span>(<\/span>G<\/span>,<\/span> seed<\/span>=<\/span>7<\/span>)<\/span>  # positions for all nodes - seed for reproducibility<\/span>\r\n\r\n# nodes<\/span>\r\nnx<\/span>.<\/span>draw_networkx_nodes<\/span>(<\/span>G<\/span>,<\/span> pos<\/a>,<\/span> node_size<\/span>=<\/span>700<\/span>)<\/span>\r\n\r\n# edges<\/span>\r\nnx<\/span>.<\/span>draw_networkx_edges<\/span>(<\/span>G<\/span>,<\/span> pos<\/a>,<\/span> edgelist<\/span>=<\/span>elarge<\/a>,<\/span> width<\/span>=<\/span>6<\/span>)<\/span>\r\nnx<\/span>.<\/span>draw_networkx_edges<\/span>(<\/span>\r\n    G<\/span>,<\/span> pos<\/a>,<\/span> edgelist<\/span>=<\/span>esmall<\/a>,<\/span> width<\/span>=<\/span>6<\/span>,<\/span> alpha<\/span>=<\/span>0.5<\/span>,<\/span> edge_color<\/span>=<\/span>\"b\"<\/span>,<\/span> style<\/span>=<\/span>\"dashed\"<\/span>\r\n)<\/span>\r\n\r\n# labels<\/span>\r\nnx<\/span>.<\/span>draw_networkx_labels<\/span>(<\/span>G<\/span>,<\/span> pos<\/a>,<\/span> font_size<\/span>=<\/span>20<\/span>,<\/span> font_family<\/span>=<\/span>\"sans-serif\"<\/span>)<\/span>\r\n\r\nax<\/span> =<\/span> plt<\/span>.<\/span>gca<\/span><\/a>()<\/span>\r\nax<\/span>.<\/span>margins<\/span><\/a>(<\/span>0.08<\/span>)<\/span>\r\nplt<\/span>.<\/span>axis<\/span><\/a>(<\/span>\"off\"<\/span>)<\/span>\r\nplt<\/span>.<\/span>tight_layout<\/span><\/a>()<\/span>\r\nplt<\/span>.<\/span>show<\/span><\/a>()<\/span><\/pre>\n<\/div>\n<\/div>\n
from: https:\/\/networkx.org\/documentation\/latest\/auto_examples\/drawing\/plot_weighted_graph.html<\/p>\n","protected":false},"excerpt":{"rendered":"
Weighted Graph An example using Graph as a weighted network. import matplotlib.pyplot as plt import networkx as nx G = n …<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[],"class_list":["post-442","post","type-post","status-publish","format-standard","hentry","category-python"],"_links":{"self":[{"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/442","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=442"}],"version-history":[{"count":1,"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/442\/revisions"}],"predecessor-version":[{"id":443,"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/442\/revisions\/443"}],"wp:attachment":[{"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=442"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=442"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.jichangqing.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=442"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}