Directed graph builder12/5/2023 (That class also has a self-loop for 1-dimension dims => whereas here that is no edges as described above.) FUNCTIONS $graph = Graph::Maker->new('knight_grid', key => value. This is the same as the 1-vertex cyclic case in Graph::Maker::Grid. 2 dimensions like dims => can be given and in that case the effect with cyclic is steps +/-1 and +/-2 along the row of vertices cycling at the ends.įor a 1x1 cyclic grid dims =>, or any higher 1x1x1 etc, there is a self-loop edge since the knight move wraps around from the single vertex to itself. When there is only 1 dimension there is no second dimension for the second step. A knight move 2,1 means move 2 in one dimension and 1 in another. For 2 dimensions this is knight moves on a torus.įor 1 dimension like dims => there are no edges. CyclicĬyclic => 1 makes the grid wrap-around at its sides. +-+-+-+-+ dims => įor 3 or more dimensions the moves are step by 2 in some coordinate and 1 in another different coordinate. The dims and cyclic parameters are the same as Graph::Maker::Grid but the edges here are steps 2,1. Graph::Maker::KnightGrid creates a Graph.pm graph for a grid of squares with edges connecting squares as a chess knight moves. $graph = Graph::Maker->new ('knight_grid', dims => ) DESCRIPTION If your query returns one row for each of these connections, the graph will sum the edge_size of each row into a single value, and use that value to determine the size of the link.Graph::Maker::KnightGrid - create Knight grid graph SYNOPSIS use Graph::Maker::KnightGrid Note that for the force-directed graphs, there's no way to distinguish between connections from node A to node B and connections from node B to node A. edge_size: A value representing the strength of the connection.The query should include at least three columns: This query should return one row per edge in your network. If you want all the nodes to be the same size, you can return the same value for each node. node_size: A value representing the size of your node.node_group: The name of the group the node belongs to.This query should return one row for each node in your network. Unlike most of the other examples in the Gallery, force-directed graphs require two queries. Guidelines for force-directed graph queries If you're experiencing performance troubles with your graph, try showing fewer links. The graph will order links from largest to smallest, so if you choose 1000, it will show the 1000 strongest links. links_to_show: The number of links you want to show.group_colors: Hex codes for the colors of each group.chart_height: Height of the chart in pixels.chart_width: Width of the chart in pixels.title: The force-directed graph's title.Details about what should be in this query are shown below. edge_query: The name of the query that returns the dataset you want to use as your edges.node_query: The name of the query that returns the dataset you want to use as your nodes.To place it elsewhere, select an element in your report with this parameter. html_element: If not provided, the map will be added as the last element in the report.You can customize the force-directed graph by editing each of these parameters in the snippet: This tag calls back to an open-source library called alamode.js, which provides an easy way to build some of our users' favorite visualizations.Īdd the customizable snippet at the bottom of the HTML: Learn more about using HTML to customize your reports.Īdd the stylesheet link and script tag to the top of the HTML: The thicker the bar, the more rides connect the two stations.Ĭlick Powered by Mode to duplicate this report and add links to your tables. The rides between stations are represented by the grey bars. The color of the circle shows the city the station is in, and the size of the circle shows how many rides start from that station. This force-directed graph shows the connections between bike share stations in the San Francisco Bay Area. Because force-directed graphs naturally cluster objects that are well connected, they can be both visually interesting and help uncover relationships between groups that may not be obvious otherwise. Force-directed graphs can help visualize connections between objects in a network.
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