(function(f){if(typeof exports==="object"&&typeof module!=="undefined"){module.exports=f()}else if(typeof define==="function"&&define.amd){define([],f)}else{var g;if(typeof window!=="undefined"){g=window}else if(typeof global!=="undefined"){g=global}else if(typeof self!=="undefined"){g=self}else{g=this}g.dagre=f()}})(function(){var define,module,exports;return function(){function r(e,n,t){function o(i,f){if(!n[i]){if(!e[i]){var c="function"==typeof require&&require;if(!f&&c)return c(i,!0);if(u)return u(i,!0);var a=new Error("Cannot find module '"+i+"'");throw a.code="MODULE_NOT_FOUND",a}var p=n[i]={exports:{}};e[i][0].call(p.exports,function(r){var n=e[i][1][r];return o(n||r)},p,p.exports,r,e,n,t)}return n[i].exports}for(var u="function"==typeof require&&require,i=0;i{let label=g.edge(e);g.removeEdge(e);label.forwardName=e.name;label.reversed=true;g.setEdge(e.w,e.v,label,uniqueId("rev"))});function weightFn(g){return e=>{return g.edge(e).weight}}}function dfsFAS(g){let fas=[];let stack={};let visited={};function dfs(v){if(visited.hasOwnProperty(v)){return}visited[v]=true;stack[v]=true;g.outEdges(v).forEach(e=>{if(stack.hasOwnProperty(e.w)){fas.push(e)}else{dfs(e.w)}});delete stack[v]}g.nodes().forEach(dfs);return fas}function undo(g){g.edges().forEach(e=>{let label=g.edge(e);if(label.reversed){g.removeEdge(e);let forwardName=label.forwardName;delete label.reversed;delete label.forwardName;g.setEdge(e.w,e.v,label,forwardName)}})}},{"./greedy-fas":7,"./util":27}],3:[function(require,module,exports){let util=require("./util");module.exports=addBorderSegments;function addBorderSegments(g){function dfs(v){let children=g.children(v);let node=g.node(v);if(children.length){children.forEach(dfs)}if(node.hasOwnProperty("minRank")){node.borderLeft=[];node.borderRight=[];for(let rank=node.minRank,maxRank=node.maxRank+1;rankswapWidthHeightOne(g.node(v)));g.edges().forEach(e=>swapWidthHeightOne(g.edge(e)))}function swapWidthHeightOne(attrs){let w=attrs.width;attrs.width=attrs.height;attrs.height=w}function reverseY(g){g.nodes().forEach(v=>reverseYOne(g.node(v)));g.edges().forEach(e=>{let edge=g.edge(e);edge.points.forEach(reverseYOne);if(edge.hasOwnProperty("y")){reverseYOne(edge)}})}function reverseYOne(attrs){attrs.y=-attrs.y}function swapXY(g){g.nodes().forEach(v=>swapXYOne(g.node(v)));g.edges().forEach(e=>{let edge=g.edge(e);edge.points.forEach(swapXYOne);if(edge.hasOwnProperty("x")){swapXYOne(edge)}})}function swapXYOne(attrs){let x=attrs.x;attrs.x=attrs.y;attrs.y=x}},{}],5:[function(require,module,exports){ /* * Simple doubly linked list implementation derived from Cormen, et al., * "Introduction to Algorithms". */ class List{constructor(){let sentinel={};sentinel._next=sentinel._prev=sentinel;this._sentinel=sentinel}dequeue(){let sentinel=this._sentinel;let entry=sentinel._prev;if(entry!==sentinel){unlink(entry);return entry}}enqueue(entry){let sentinel=this._sentinel;if(entry._prev&&entry._next){unlink(entry)}entry._next=sentinel._next;sentinel._next._prev=entry;sentinel._next=entry;entry._prev=sentinel}toString(){let strs=[];let sentinel=this._sentinel;let curr=sentinel._prev;while(curr!==sentinel){strs.push(JSON.stringify(curr,filterOutLinks));curr=curr._prev}return"["+strs.join(", ")+"]"}}function unlink(entry){entry._prev._next=entry._next;entry._next._prev=entry._prev;delete entry._next;delete entry._prev}function filterOutLinks(k,v){if(k!=="_next"&&k!=="_prev"){return v}}module.exports=List},{}],6:[function(require,module,exports){let util=require("./util");let Graph=require("@dagrejs/graphlib").Graph;module.exports={debugOrdering:debugOrdering}; /* istanbul ignore next */function debugOrdering(g){let layerMatrix=util.buildLayerMatrix(g);let h=new Graph({compound:true,multigraph:true}).setGraph({});g.nodes().forEach(v=>{h.setNode(v,{label:v});h.setParent(v,"layer"+g.node(v).rank)});g.edges().forEach(e=>h.setEdge(e.v,e.w,{},e.name));layerMatrix.forEach((layer,i)=>{let layerV="layer"+i;h.setNode(layerV,{rank:"same"});layer.reduce((u,v)=>{h.setEdge(u,v,{style:"invis"});return v})});return h}},{"./util":27,"@dagrejs/graphlib":29}],7:[function(require,module,exports){let Graph=require("@dagrejs/graphlib").Graph;let List=require("./data/list"); /* * A greedy heuristic for finding a feedback arc set for a graph. A feedback * arc set is a set of edges that can be removed to make a graph acyclic. * The algorithm comes from: P. Eades, X. Lin, and W. F. Smyth, "A fast and * effective heuristic for the feedback arc set problem." This implementation * adjusts that from the paper to allow for weighted edges. */module.exports=greedyFAS;let DEFAULT_WEIGHT_FN=()=>1;function greedyFAS(g,weightFn){if(g.nodeCount()<=1){return[]}let state=buildState(g,weightFn||DEFAULT_WEIGHT_FN);let results=doGreedyFAS(state.graph,state.buckets,state.zeroIdx); // Expand multi-edges return results.flatMap(e=>g.outEdges(e.v,e.w))}function doGreedyFAS(g,buckets,zeroIdx){let results=[];let sources=buckets[buckets.length-1];let sinks=buckets[0];let entry;while(g.nodeCount()){while(entry=sinks.dequeue()){removeNode(g,buckets,zeroIdx,entry)}while(entry=sources.dequeue()){removeNode(g,buckets,zeroIdx,entry)}if(g.nodeCount()){for(let i=buckets.length-2;i>0;--i){entry=buckets[i].dequeue();if(entry){results=results.concat(removeNode(g,buckets,zeroIdx,entry,true));break}}}}return results}function removeNode(g,buckets,zeroIdx,entry,collectPredecessors){let results=collectPredecessors?[]:undefined;g.inEdges(entry.v).forEach(edge=>{let weight=g.edge(edge);let uEntry=g.node(edge.v);if(collectPredecessors){results.push({v:edge.v,w:edge.w})}uEntry.out-=weight;assignBucket(buckets,zeroIdx,uEntry)});g.outEdges(entry.v).forEach(edge=>{let weight=g.edge(edge);let w=edge.w;let wEntry=g.node(w);wEntry["in"]-=weight;assignBucket(buckets,zeroIdx,wEntry)});g.removeNode(entry.v);return results}function buildState(g,weightFn){let fasGraph=new Graph;let maxIn=0;let maxOut=0;g.nodes().forEach(v=>{fasGraph.setNode(v,{v:v,in:0,out:0})}); // Aggregate weights on nodes, but also sum the weights across multi-edges // into a single edge for the fasGraph. g.edges().forEach(e=>{let prevWeight=fasGraph.edge(e.v,e.w)||0;let weight=weightFn(e);let edgeWeight=prevWeight+weight;fasGraph.setEdge(e.v,e.w,edgeWeight);maxOut=Math.max(maxOut,fasGraph.node(e.v).out+=weight);maxIn=Math.max(maxIn,fasGraph.node(e.w)["in"]+=weight)});let buckets=range(maxOut+maxIn+3).map(()=>new List);let zeroIdx=maxIn+1;fasGraph.nodes().forEach(v=>{assignBucket(buckets,zeroIdx,fasGraph.node(v))});return{graph:fasGraph,buckets:buckets,zeroIdx:zeroIdx}}function assignBucket(buckets,zeroIdx,entry){if(!entry.out){buckets[0].enqueue(entry)}else if(!entry["in"]){buckets[buckets.length-1].enqueue(entry)}else{buckets[entry.out-entry["in"]+zeroIdx].enqueue(entry)}}function range(limit){const range=[];for(let i=0;i{let layoutGraph=time(" buildLayoutGraph",()=>buildLayoutGraph(g));time(" runLayout",()=>runLayout(layoutGraph,time));time(" updateInputGraph",()=>updateInputGraph(g,layoutGraph))})}function runLayout(g,time){time(" makeSpaceForEdgeLabels",()=>makeSpaceForEdgeLabels(g));time(" removeSelfEdges",()=>removeSelfEdges(g));time(" acyclic",()=>acyclic.run(g));time(" nestingGraph.run",()=>nestingGraph.run(g));time(" rank",()=>rank(util.asNonCompoundGraph(g)));time(" injectEdgeLabelProxies",()=>injectEdgeLabelProxies(g));time(" removeEmptyRanks",()=>removeEmptyRanks(g));time(" nestingGraph.cleanup",()=>nestingGraph.cleanup(g));time(" normalizeRanks",()=>normalizeRanks(g));time(" assignRankMinMax",()=>assignRankMinMax(g));time(" removeEdgeLabelProxies",()=>removeEdgeLabelProxies(g));time(" normalize.run",()=>normalize.run(g));time(" parentDummyChains",()=>parentDummyChains(g));time(" addBorderSegments",()=>addBorderSegments(g));time(" order",()=>order(g));time(" insertSelfEdges",()=>insertSelfEdges(g));time(" adjustCoordinateSystem",()=>coordinateSystem.adjust(g));time(" position",()=>position(g));time(" positionSelfEdges",()=>positionSelfEdges(g));time(" removeBorderNodes",()=>removeBorderNodes(g));time(" normalize.undo",()=>normalize.undo(g));time(" fixupEdgeLabelCoords",()=>fixupEdgeLabelCoords(g));time(" undoCoordinateSystem",()=>coordinateSystem.undo(g));time(" translateGraph",()=>translateGraph(g));time(" assignNodeIntersects",()=>assignNodeIntersects(g));time(" reversePoints",()=>reversePointsForReversedEdges(g));time(" acyclic.undo",()=>acyclic.undo(g))} /* * Copies final layout information from the layout graph back to the input * graph. This process only copies whitelisted attributes from the layout graph * to the input graph, so it serves as a good place to determine what * attributes can influence layout. */function updateInputGraph(inputGraph,layoutGraph){inputGraph.nodes().forEach(v=>{let inputLabel=inputGraph.node(v);let layoutLabel=layoutGraph.node(v);if(inputLabel){inputLabel.x=layoutLabel.x;inputLabel.y=layoutLabel.y;inputLabel.rank=layoutLabel.rank;if(layoutGraph.children(v).length){inputLabel.width=layoutLabel.width;inputLabel.height=layoutLabel.height}}});inputGraph.edges().forEach(e=>{let inputLabel=inputGraph.edge(e);let layoutLabel=layoutGraph.edge(e);inputLabel.points=layoutLabel.points;if(layoutLabel.hasOwnProperty("x")){inputLabel.x=layoutLabel.x;inputLabel.y=layoutLabel.y}});inputGraph.graph().width=layoutGraph.graph().width;inputGraph.graph().height=layoutGraph.graph().height}let graphNumAttrs=["nodesep","edgesep","ranksep","marginx","marginy"];let graphDefaults={ranksep:50,edgesep:20,nodesep:50,rankdir:"tb"};let graphAttrs=["acyclicer","ranker","rankdir","align"];let nodeNumAttrs=["width","height"];let nodeDefaults={width:0,height:0};let edgeNumAttrs=["minlen","weight","width","height","labeloffset"];let edgeDefaults={minlen:1,weight:1,width:0,height:0,labeloffset:10,labelpos:"r"};let edgeAttrs=["labelpos"]; /* * Constructs a new graph from the input graph, which can be used for layout. * This process copies only whitelisted attributes from the input graph to the * layout graph. Thus this function serves as a good place to determine what * attributes can influence layout. */function buildLayoutGraph(inputGraph){let g=new Graph({multigraph:true,compound:true});let graph=canonicalize(inputGraph.graph());g.setGraph(Object.assign({},graphDefaults,selectNumberAttrs(graph,graphNumAttrs),util.pick(graph,graphAttrs)));inputGraph.nodes().forEach(v=>{let node=canonicalize(inputGraph.node(v));const newNode=selectNumberAttrs(node,nodeNumAttrs);Object.keys(nodeDefaults).forEach(k=>{if(newNode[k]===undefined){newNode[k]=nodeDefaults[k]}});g.setNode(v,newNode);g.setParent(v,inputGraph.parent(v))});inputGraph.edges().forEach(e=>{let edge=canonicalize(inputGraph.edge(e));g.setEdge(e,Object.assign({},edgeDefaults,selectNumberAttrs(edge,edgeNumAttrs),util.pick(edge,edgeAttrs)))});return g} /* * This idea comes from the Gansner paper: to account for edge labels in our * layout we split each rank in half by doubling minlen and halving ranksep. * Then we can place labels at these mid-points between nodes. * * We also add some minimal padding to the width to push the label for the edge * away from the edge itself a bit. */function makeSpaceForEdgeLabels(g){let graph=g.graph();graph.ranksep/=2;g.edges().forEach(e=>{let edge=g.edge(e);edge.minlen*=2;if(edge.labelpos.toLowerCase()!=="c"){if(graph.rankdir==="TB"||graph.rankdir==="BT"){edge.width+=edge.labeloffset}else{edge.height+=edge.labeloffset}}})} /* * Creates temporary dummy nodes that capture the rank in which each edge's * label is going to, if it has one of non-zero width and height. We do this * so that we can safely remove empty ranks while preserving balance for the * label's position. */function injectEdgeLabelProxies(g){g.edges().forEach(e=>{let edge=g.edge(e);if(edge.width&&edge.height){let v=g.node(e.v);let w=g.node(e.w);let label={rank:(w.rank-v.rank)/2+v.rank,e:e};util.addDummyNode(g,"edge-proxy",label,"_ep")}})}function assignRankMinMax(g){let maxRank=0;g.nodes().forEach(v=>{let node=g.node(v);if(node.borderTop){node.minRank=g.node(node.borderTop).rank;node.maxRank=g.node(node.borderBottom).rank;maxRank=Math.max(maxRank,node.maxRank)}});g.graph().maxRank=maxRank}function removeEdgeLabelProxies(g){g.nodes().forEach(v=>{let node=g.node(v);if(node.dummy==="edge-proxy"){g.edge(node.e).labelRank=node.rank;g.removeNode(v)}})}function translateGraph(g){let minX=Number.POSITIVE_INFINITY;let maxX=0;let minY=Number.POSITIVE_INFINITY;let maxY=0;let graphLabel=g.graph();let marginX=graphLabel.marginx||0;let marginY=graphLabel.marginy||0;function getExtremes(attrs){let x=attrs.x;let y=attrs.y;let w=attrs.width;let h=attrs.height;minX=Math.min(minX,x-w/2);maxX=Math.max(maxX,x+w/2);minY=Math.min(minY,y-h/2);maxY=Math.max(maxY,y+h/2)}g.nodes().forEach(v=>getExtremes(g.node(v)));g.edges().forEach(e=>{let edge=g.edge(e);if(edge.hasOwnProperty("x")){getExtremes(edge)}});minX-=marginX;minY-=marginY;g.nodes().forEach(v=>{let node=g.node(v);node.x-=minX;node.y-=minY});g.edges().forEach(e=>{let edge=g.edge(e);edge.points.forEach(p=>{p.x-=minX;p.y-=minY});if(edge.hasOwnProperty("x")){edge.x-=minX}if(edge.hasOwnProperty("y")){edge.y-=minY}});graphLabel.width=maxX-minX+marginX;graphLabel.height=maxY-minY+marginY}function assignNodeIntersects(g){g.edges().forEach(e=>{let edge=g.edge(e);let nodeV=g.node(e.v);let nodeW=g.node(e.w);let p1,p2;if(!edge.points){edge.points=[];p1=nodeW;p2=nodeV}else{p1=edge.points[0];p2=edge.points[edge.points.length-1]}edge.points.unshift(util.intersectRect(nodeV,p1));edge.points.push(util.intersectRect(nodeW,p2))})}function fixupEdgeLabelCoords(g){g.edges().forEach(e=>{let edge=g.edge(e);if(edge.hasOwnProperty("x")){if(edge.labelpos==="l"||edge.labelpos==="r"){edge.width-=edge.labeloffset}switch(edge.labelpos){case"l":edge.x-=edge.width/2+edge.labeloffset;break;case"r":edge.x+=edge.width/2+edge.labeloffset;break}}})}function reversePointsForReversedEdges(g){g.edges().forEach(e=>{let edge=g.edge(e);if(edge.reversed){edge.points.reverse()}})}function removeBorderNodes(g){g.nodes().forEach(v=>{if(g.children(v).length){let node=g.node(v);let t=g.node(node.borderTop);let b=g.node(node.borderBottom);let l=g.node(node.borderLeft[node.borderLeft.length-1]);let r=g.node(node.borderRight[node.borderRight.length-1]);node.width=Math.abs(r.x-l.x);node.height=Math.abs(b.y-t.y);node.x=l.x+node.width/2;node.y=t.y+node.height/2}});g.nodes().forEach(v=>{if(g.node(v).dummy==="border"){g.removeNode(v)}})}function removeSelfEdges(g){g.edges().forEach(e=>{if(e.v===e.w){var node=g.node(e.v);if(!node.selfEdges){node.selfEdges=[]}node.selfEdges.push({e:e,label:g.edge(e)});g.removeEdge(e)}})}function insertSelfEdges(g){var layers=util.buildLayerMatrix(g);layers.forEach(layer=>{var orderShift=0;layer.forEach((v,i)=>{var node=g.node(v);node.order=i+orderShift;(node.selfEdges||[]).forEach(selfEdge=>{util.addDummyNode(g,"selfedge",{width:selfEdge.label.width,height:selfEdge.label.height,rank:node.rank,order:i+ ++orderShift,e:selfEdge.e,label:selfEdge.label},"_se")});delete node.selfEdges})})}function positionSelfEdges(g){g.nodes().forEach(v=>{var node=g.node(v);if(node.dummy==="selfedge"){var selfNode=g.node(node.e.v);var x=selfNode.x+selfNode.width/2;var y=selfNode.y;var dx=node.x-x;var dy=selfNode.height/2;g.setEdge(node.e,node.label);g.removeNode(v);node.label.points=[{x:x+2*dx/3,y:y-dy},{x:x+5*dx/6,y:y-dy},{x:x+dx,y:y},{x:x+5*dx/6,y:y+dy},{x:x+2*dx/3,y:y+dy}];node.label.x=node.x;node.label.y=node.y}})}function selectNumberAttrs(obj,attrs){return util.mapValues(util.pick(obj,attrs),Number)}function canonicalize(attrs){var newAttrs={};if(attrs){Object.entries(attrs).forEach(([k,v])=>{if(typeof k==="string"){k=k.toLowerCase()}newAttrs[k]=v})}return newAttrs}},{"./acyclic":2,"./add-border-segments":3,"./coordinate-system":4,"./nesting-graph":9,"./normalize":10,"./order":15,"./parent-dummy-chains":20,"./position":22,"./rank":24,"./util":27,"@dagrejs/graphlib":29}],9:[function(require,module,exports){let util=require("./util");module.exports={run:run,cleanup:cleanup}; /* * A nesting graph creates dummy nodes for the tops and bottoms of subgraphs, * adds appropriate edges to ensure that all cluster nodes are placed between * these boundaries, and ensures that the graph is connected. * * In addition we ensure, through the use of the minlen property, that nodes * and subgraph border nodes to not end up on the same rank. * * Preconditions: * * 1. Input graph is a DAG * 2. Nodes in the input graph has a minlen attribute * * Postconditions: * * 1. Input graph is connected. * 2. Dummy nodes are added for the tops and bottoms of subgraphs. * 3. The minlen attribute for nodes is adjusted to ensure nodes do not * get placed on the same rank as subgraph border nodes. * * The nesting graph idea comes from Sander, "Layout of Compound Directed * Graphs." */function run(g){let root=util.addDummyNode(g,"root",{},"_root");let depths=treeDepths(g);let height=Math.max(...Object.values(depths))-1;// Note: depths is an Object not an array let nodeSep=2*height+1;g.graph().nestingRoot=root; // Multiply minlen by nodeSep to align nodes on non-border ranks. g.edges().forEach(e=>g.edge(e).minlen*=nodeSep); // Calculate a weight that is sufficient to keep subgraphs vertically compact let weight=sumWeights(g)+1; // Create border nodes and link them up g.children().forEach(child=>dfs(g,root,nodeSep,weight,height,depths,child)); // Save the multiplier for node layers for later removal of empty border // layers. g.graph().nodeRankFactor=nodeSep}function dfs(g,root,nodeSep,weight,height,depths,v){let children=g.children(v);if(!children.length){if(v!==root){g.setEdge(root,v,{weight:0,minlen:nodeSep})}return}let top=util.addBorderNode(g,"_bt");let bottom=util.addBorderNode(g,"_bb");let label=g.node(v);g.setParent(top,v);label.borderTop=top;g.setParent(bottom,v);label.borderBottom=bottom;children.forEach(child=>{dfs(g,root,nodeSep,weight,height,depths,child);let childNode=g.node(child);let childTop=childNode.borderTop?childNode.borderTop:child;let childBottom=childNode.borderBottom?childNode.borderBottom:child;let thisWeight=childNode.borderTop?weight:2*weight;let minlen=childTop!==childBottom?1:height-depths[v]+1;g.setEdge(top,childTop,{weight:thisWeight,minlen:minlen,nestingEdge:true});g.setEdge(childBottom,bottom,{weight:thisWeight,minlen:minlen,nestingEdge:true})});if(!g.parent(v)){g.setEdge(root,top,{weight:0,minlen:height+depths[v]})}}function treeDepths(g){var depths={};function dfs(v,depth){var children=g.children(v);if(children&&children.length){children.forEach(child=>dfs(child,depth+1))}depths[v]=depth}g.children().forEach(v=>dfs(v,1));return depths}function sumWeights(g){return g.edges().reduce((acc,e)=>acc+g.edge(e).weight,0)}function cleanup(g){var graphLabel=g.graph();g.removeNode(graphLabel.nestingRoot);delete graphLabel.nestingRoot;g.edges().forEach(e=>{var edge=g.edge(e);if(edge.nestingEdge){g.removeEdge(e)}})}},{"./util":27}],10:[function(require,module,exports){"use strict";let util=require("./util");module.exports={run:run,undo:undo}; /* * Breaks any long edges in the graph into short segments that span 1 layer * each. This operation is undoable with the denormalize function. * * Pre-conditions: * * 1. The input graph is a DAG. * 2. Each node in the graph has a "rank" property. * * Post-condition: * * 1. All edges in the graph have a length of 1. * 2. Dummy nodes are added where edges have been split into segments. * 3. The graph is augmented with a "dummyChains" attribute which contains * the first dummy in each chain of dummy nodes produced. */function run(g){g.graph().dummyChains=[];g.edges().forEach(edge=>normalizeEdge(g,edge))}function normalizeEdge(g,e){let v=e.v;let vRank=g.node(v).rank;let w=e.w;let wRank=g.node(w).rank;let name=e.name;let edgeLabel=g.edge(e);let labelRank=edgeLabel.labelRank;if(wRank===vRank+1)return;g.removeEdge(e);let dummy,attrs,i;for(i=0,++vRank;vRank{let node=g.node(v);let origLabel=node.edgeLabel;let w;g.setEdge(node.edgeObj,origLabel);while(node.dummy){w=g.successors(v)[0];g.removeNode(v);origLabel.points.push({x:node.x,y:node.y});if(node.dummy==="edge-label"){origLabel.x=node.x;origLabel.y=node.y;origLabel.width=node.width;origLabel.height=node.height}v=w;node=g.node(v)}})}},{"./util":27}],11:[function(require,module,exports){module.exports=addSubgraphConstraints;function addSubgraphConstraints(g,cg,vs){let prev={},rootPrev;vs.forEach(v=>{let child=g.parent(v),parent,prevChild;while(child){parent=g.parent(child);if(parent){prevChild=prev[parent];prev[parent]=child}else{prevChild=rootPrev;rootPrev=child}if(prevChild&&prevChild!==child){cg.setEdge(prevChild,child);return}child=parent}}); /* function dfs(v) { var children = v ? g.children(v) : g.children(); if (children.length) { var min = Number.POSITIVE_INFINITY, subgraphs = []; children.forEach(function(child) { var childMin = dfs(child); if (g.children(child).length) { subgraphs.push({ v: child, order: childMin }); } min = Math.min(min, childMin); }); _.sortBy(subgraphs, "order").reduce(function(prev, curr) { cg.setEdge(prev.v, curr.v); return curr; }); return min; } return g.node(v).order; } dfs(undefined); */}},{}],12:[function(require,module,exports){module.exports=barycenter;function barycenter(g,movable=[]){return movable.map(v=>{let inV=g.inEdges(v);if(!inV.length){return{v:v}}else{let result=inV.reduce((acc,e)=>{let edge=g.edge(e),nodeU=g.node(e.v);return{sum:acc.sum+edge.weight*nodeU.order,weight:acc.weight+edge.weight}},{sum:0,weight:0});return{v:v,barycenter:result.sum/result.weight,weight:result.weight}}})}},{}],13:[function(require,module,exports){let Graph=require("@dagrejs/graphlib").Graph;let util=require("../util");module.exports=buildLayerGraph; /* * Constructs a graph that can be used to sort a layer of nodes. The graph will * contain all base and subgraph nodes from the request layer in their original * hierarchy and any edges that are incident on these nodes and are of the type * requested by the "relationship" parameter. * * Nodes from the requested rank that do not have parents are assigned a root * node in the output graph, which is set in the root graph attribute. This * makes it easy to walk the hierarchy of movable nodes during ordering. * * Pre-conditions: * * 1. Input graph is a DAG * 2. Base nodes in the input graph have a rank attribute * 3. Subgraph nodes in the input graph has minRank and maxRank attributes * 4. Edges have an assigned weight * * Post-conditions: * * 1. Output graph has all nodes in the movable rank with preserved * hierarchy. * 2. Root nodes in the movable layer are made children of the node * indicated by the root attribute of the graph. * 3. Non-movable nodes incident on movable nodes, selected by the * relationship parameter, are included in the graph (without hierarchy). * 4. Edges incident on movable nodes, selected by the relationship * parameter, are added to the output graph. * 5. The weights for copied edges are aggregated as need, since the output * graph is not a multi-graph. */function buildLayerGraph(g,rank,relationship){let root=createRootNode(g),result=new Graph({compound:true}).setGraph({root:root}).setDefaultNodeLabel(v=>g.node(v));g.nodes().forEach(v=>{let node=g.node(v),parent=g.parent(v);if(node.rank===rank||node.minRank<=rank&&rank<=node.maxRank){result.setNode(v);result.setParent(v,parent||root); // This assumes we have only short edges! g[relationship](v).forEach(e=>{let u=e.v===v?e.w:e.v,edge=result.edge(u,v),weight=edge!==undefined?edge.weight:0;result.setEdge(u,v,{weight:g.edge(e).weight+weight})});if(node.hasOwnProperty("minRank")){result.setNode(v,{borderLeft:node.borderLeft[rank],borderRight:node.borderRight[rank]})}}});return result}function createRootNode(g){var v;while(g.hasNode(v=util.uniqueId("_root")));return v}},{"../util":27,"@dagrejs/graphlib":29}],14:[function(require,module,exports){"use strict";let zipObject=require("../util").zipObject;module.exports=crossCount; /* * A function that takes a layering (an array of layers, each with an array of * ordererd nodes) and a graph and returns a weighted crossing count. * * Pre-conditions: * * 1. Input graph must be simple (not a multigraph), directed, and include * only simple edges. * 2. Edges in the input graph must have assigned weights. * * Post-conditions: * * 1. The graph and layering matrix are left unchanged. * * This algorithm is derived from Barth, et al., "Bilayer Cross Counting." */function crossCount(g,layering){let cc=0;for(let i=1;ii));let southEntries=northLayer.flatMap(v=>{return g.outEdges(v).map(e=>{return{pos:southPos[e.w],weight:g.edge(e).weight}}).sort((a,b)=>a.pos-b.pos)}); // Build the accumulator tree let firstIndex=1;while(firstIndex{let index=entry.pos+firstIndex;tree[index]+=entry.weight;let weightSum=0;while(index>0){if(index%2){weightSum+=tree[index+1]}index=index-1>>1;tree[index]+=entry.weight}cc+=entry.weight*weightSum});return cc}},{"../util":27}],15:[function(require,module,exports){"use strict";let initOrder=require("./init-order");let crossCount=require("./cross-count");let sortSubgraph=require("./sort-subgraph");let buildLayerGraph=require("./build-layer-graph");let addSubgraphConstraints=require("./add-subgraph-constraints");let Graph=require("@dagrejs/graphlib").Graph;let util=require("../util");module.exports=order; /* * Applies heuristics to minimize edge crossings in the graph and sets the best * order solution as an order attribute on each node. * * Pre-conditions: * * 1. Graph must be DAG * 2. Graph nodes must be objects with a "rank" attribute * 3. Graph edges must have the "weight" attribute * * Post-conditions: * * 1. Graph nodes will have an "order" attribute based on the results of the * algorithm. */function order(g,opts){if(opts&&typeof opts.customOrder==="function"){opts.customOrder(g,order);return}let maxRank=util.maxRank(g),downLayerGraphs=buildLayerGraphs(g,util.range(1,maxRank+1),"inEdges"),upLayerGraphs=buildLayerGraphs(g,util.range(maxRank-1,-1,-1),"outEdges");let layering=initOrder(g);assignOrder(g,layering);if(opts&&opts.disableOptimalOrderHeuristic){return}let bestCC=Number.POSITIVE_INFINITY,best;for(let i=0,lastBest=0;lastBest<4;++i,++lastBest){sweepLayerGraphs(i%2?downLayerGraphs:upLayerGraphs,i%4>=2);layering=util.buildLayerMatrix(g);let cc=crossCount(g,layering);if(cclg.node(v).order=i);addSubgraphConstraints(lg,cg,sorted.vs)})}function assignOrder(g,layering){Object.values(layering).forEach(layer=>layer.forEach((v,i)=>g.node(v).order=i))}},{"../util":27,"./add-subgraph-constraints":11,"./build-layer-graph":13,"./cross-count":14,"./init-order":16,"./sort-subgraph":18,"@dagrejs/graphlib":29}],16:[function(require,module,exports){"use strict";let util=require("../util");module.exports=initOrder; /* * Assigns an initial order value for each node by performing a DFS search * starting from nodes in the first rank. Nodes are assigned an order in their * rank as they are first visited. * * This approach comes from Gansner, et al., "A Technique for Drawing Directed * Graphs." * * Returns a layering matrix with an array per layer and each layer sorted by * the order of its nodes. */function initOrder(g){let visited={};let simpleNodes=g.nodes().filter(v=>!g.children(v).length);let maxRank=Math.max(...simpleNodes.map(v=>g.node(v).rank));let layers=util.range(maxRank+1).map(()=>[]);function dfs(v){if(visited[v])return;visited[v]=true;let node=g.node(v);layers[node.rank].push(v);g.successors(v).forEach(dfs)}let orderedVs=simpleNodes.sort((a,b)=>g.node(a).rank-g.node(b).rank);orderedVs.forEach(dfs);return layers}},{"../util":27}],17:[function(require,module,exports){"use strict";let util=require("../util");module.exports=resolveConflicts; /* * Given a list of entries of the form {v, barycenter, weight} and a * constraint graph this function will resolve any conflicts between the * constraint graph and the barycenters for the entries. If the barycenters for * an entry would violate a constraint in the constraint graph then we coalesce * the nodes in the conflict into a new node that respects the contraint and * aggregates barycenter and weight information. * * This implementation is based on the description in Forster, "A Fast and * Simple Hueristic for Constrained Two-Level Crossing Reduction," thought it * differs in some specific details. * * Pre-conditions: * * 1. Each entry has the form {v, barycenter, weight}, or if the node has * no barycenter, then {v}. * * Returns: * * A new list of entries of the form {vs, i, barycenter, weight}. The list * `vs` may either be a singleton or it may be an aggregation of nodes * ordered such that they do not violate constraints from the constraint * graph. The property `i` is the lowest original index of any of the * elements in `vs`. */function resolveConflicts(entries,cg){let mappedEntries={};entries.forEach((entry,i)=>{let tmp=mappedEntries[entry.v]={indegree:0,in:[],out:[],vs:[entry.v],i:i};if(entry.barycenter!==undefined){tmp.barycenter=entry.barycenter;tmp.weight=entry.weight}});cg.edges().forEach(e=>{let entryV=mappedEntries[e.v];let entryW=mappedEntries[e.w];if(entryV!==undefined&&entryW!==undefined){entryW.indegree++;entryV.out.push(mappedEntries[e.w])}});let sourceSet=Object.values(mappedEntries).filter(entry=>!entry.indegree);return doResolveConflicts(sourceSet)}function doResolveConflicts(sourceSet){let entries=[];function handleIn(vEntry){return uEntry=>{if(uEntry.merged){return}if(uEntry.barycenter===undefined||vEntry.barycenter===undefined||uEntry.barycenter>=vEntry.barycenter){mergeEntries(vEntry,uEntry)}}}function handleOut(vEntry){return wEntry=>{wEntry["in"].push(vEntry);if(--wEntry.indegree===0){sourceSet.push(wEntry)}}}while(sourceSet.length){let entry=sourceSet.pop();entries.push(entry);entry["in"].reverse().forEach(handleIn(entry));entry.out.forEach(handleOut(entry))}return entries.filter(entry=>!entry.merged).map(entry=>{return util.pick(entry,["vs","i","barycenter","weight"])})}function mergeEntries(target,source){let sum=0;let weight=0;if(target.weight){sum+=target.barycenter*target.weight;weight+=target.weight}if(source.weight){sum+=source.barycenter*source.weight;weight+=source.weight}target.vs=source.vs.concat(target.vs);target.barycenter=sum/weight;target.weight=weight;target.i=Math.min(source.i,target.i);source.merged=true}},{"../util":27}],18:[function(require,module,exports){let barycenter=require("./barycenter");let resolveConflicts=require("./resolve-conflicts");let sort=require("./sort");module.exports=sortSubgraph;function sortSubgraph(g,v,cg,biasRight){let movable=g.children(v);let node=g.node(v);let bl=node?node.borderLeft:undefined;let br=node?node.borderRight:undefined;let subgraphs={};if(bl){movable=movable.filter(w=>w!==bl&&w!==br)}let barycenters=barycenter(g,movable);barycenters.forEach(entry=>{if(g.children(entry.v).length){let subgraphResult=sortSubgraph(g,entry.v,cg,biasRight);subgraphs[entry.v]=subgraphResult;if(subgraphResult.hasOwnProperty("barycenter")){mergeBarycenters(entry,subgraphResult)}}});let entries=resolveConflicts(barycenters,cg);expandSubgraphs(entries,subgraphs);let result=sort(entries,biasRight);if(bl){result.vs=[bl,result.vs,br].flat(true);if(g.predecessors(bl).length){let blPred=g.node(g.predecessors(bl)[0]),brPred=g.node(g.predecessors(br)[0]);if(!result.hasOwnProperty("barycenter")){result.barycenter=0;result.weight=0}result.barycenter=(result.barycenter*result.weight+blPred.order+brPred.order)/(result.weight+2);result.weight+=2}}return result}function expandSubgraphs(entries,subgraphs){entries.forEach(entry=>{entry.vs=entry.vs.flatMap(v=>{if(subgraphs[v]){return subgraphs[v].vs}return v})})}function mergeBarycenters(target,other){if(target.barycenter!==undefined){target.barycenter=(target.barycenter*target.weight+other.barycenter*other.weight)/(target.weight+other.weight);target.weight+=other.weight}else{target.barycenter=other.barycenter;target.weight=other.weight}}},{"./barycenter":12,"./resolve-conflicts":17,"./sort":19}],19:[function(require,module,exports){let util=require("../util");module.exports=sort;function sort(entries,biasRight){let parts=util.partition(entries,entry=>{return entry.hasOwnProperty("barycenter")});let sortable=parts.lhs,unsortable=parts.rhs.sort((a,b)=>b.i-a.i),vs=[],sum=0,weight=0,vsIndex=0;sortable.sort(compareWithBias(!!biasRight));vsIndex=consumeUnsortable(vs,unsortable,vsIndex);sortable.forEach(entry=>{vsIndex+=entry.vs.length;vs.push(entry.vs);sum+=entry.barycenter*entry.weight;weight+=entry.weight;vsIndex=consumeUnsortable(vs,unsortable,vsIndex)});let result={vs:vs.flat(true)};if(weight){result.barycenter=sum/weight;result.weight=weight}return result}function consumeUnsortable(vs,unsortable,index){let last;while(unsortable.length&&(last=unsortable[unsortable.length-1]).i<=index){unsortable.pop();vs.push(last.vs);index++}return index}function compareWithBias(bias){return(entryV,entryW)=>{if(entryV.barycenterentryW.barycenter){return 1}return!bias?entryV.i-entryW.i:entryW.i-entryV.i}}},{"../util":27}],20:[function(require,module,exports){module.exports=parentDummyChains;function parentDummyChains(g){let postorderNums=postorder(g);g.graph().dummyChains.forEach(v=>{let node=g.node(v);let edgeObj=node.edgeObj;let pathData=findPath(g,postorderNums,edgeObj.v,edgeObj.w);let path=pathData.path;let lca=pathData.lca;let pathIdx=0;let pathV=path[pathIdx];let ascending=true;while(v!==edgeObj.w){node=g.node(v);if(ascending){while((pathV=path[pathIdx])!==lca&&g.node(pathV).maxRanklow||lim>postorderNums[parent].lim));lca=parent; // Traverse from w to LCA parent=w;while((parent=g.parent(parent))!==lca){wPath.push(parent)}return{path:vPath.concat(wPath.reverse()),lca:lca}}function postorder(g){let result={};let lim=0;function dfs(v){let low=lim;g.children(v).forEach(dfs);result[v]={low:low,lim:lim++}}g.children().forEach(dfs);return result}},{}],21:[function(require,module,exports){"use strict";let Graph=require("@dagrejs/graphlib").Graph;let util=require("../util"); /* * This module provides coordinate assignment based on Brandes and Köpf, "Fast * and Simple Horizontal Coordinate Assignment." */module.exports={positionX:positionX,findType1Conflicts:findType1Conflicts,findType2Conflicts:findType2Conflicts,addConflict:addConflict,hasConflict:hasConflict,verticalAlignment:verticalAlignment,horizontalCompaction:horizontalCompaction,alignCoordinates:alignCoordinates,findSmallestWidthAlignment:findSmallestWidthAlignment,balance:balance}; /* * Marks all edges in the graph with a type-1 conflict with the "type1Conflict" * property. A type-1 conflict is one where a non-inner segment crosses an * inner segment. An inner segment is an edge with both incident nodes marked * with the "dummy" property. * * This algorithm scans layer by layer, starting with the second, for type-1 * conflicts between the current layer and the previous layer. For each layer * it scans the nodes from left to right until it reaches one that is incident * on an inner segment. It then scans predecessors to determine if they have * edges that cross that inner segment. At the end a final scan is done for all * nodes on the current rank to see if they cross the last visited inner * segment. * * This algorithm (safely) assumes that a dummy node will only be incident on a * single node in the layers being scanned. */function findType1Conflicts(g,layering){let conflicts={};function visitLayer(prevLayer,layer){let // last visited node in the previous layer that is incident on an inner // segment. k0=0, // Tracks the last node in this layer scanned for crossings with a type-1 // segment. scanPos=0,prevLayerLength=prevLayer.length,lastNode=layer[layer.length-1];layer.forEach((v,i)=>{let w=findOtherInnerSegmentNode(g,v),k1=w?g.node(w).order:prevLayerLength;if(w||v===lastNode){layer.slice(scanPos,i+1).forEach(scanNode=>{g.predecessors(scanNode).forEach(u=>{let uLabel=g.node(u),uPos=uLabel.order;if((uPos{v=south[i];if(g.node(v).dummy){g.predecessors(v).forEach(u=>{let uNode=g.node(u);if(uNode.dummy&&(uNode.ordernextNorthBorder)){addConflict(conflicts,u,v)}})}})}function visitLayer(north,south){let prevNorthPos=-1,nextNorthPos,southPos=0;south.forEach((v,southLookahead)=>{if(g.node(v).dummy==="border"){let predecessors=g.predecessors(v);if(predecessors.length){nextNorthPos=g.node(predecessors[0]).order;scan(south,southPos,southLookahead,prevNorthPos,nextNorthPos);southPos=southLookahead;prevNorthPos=nextNorthPos}}scan(south,southPos,south.length,nextNorthPos,north.length)});return south}layering.length&&layering.reduce(visitLayer);return conflicts}function findOtherInnerSegmentNode(g,v){if(g.node(v).dummy){return g.predecessors(v).find(u=>g.node(u).dummy)}}function addConflict(conflicts,v,w){if(v>w){let tmp=v;v=w;w=tmp}let conflictsV=conflicts[v];if(!conflictsV){conflicts[v]=conflictsV={}}conflictsV[w]=true}function hasConflict(conflicts,v,w){if(v>w){let tmp=v;v=w;w=tmp}return!!conflicts[v]&&conflicts[v].hasOwnProperty(w)} /* * Try to align nodes into vertical "blocks" where possible. This algorithm * attempts to align a node with one of its median neighbors. If the edge * connecting a neighbor is a type-1 conflict then we ignore that possibility. * If a previous node has already formed a block with a node after the node * we're trying to form a block with, we also ignore that possibility - our * blocks would be split in that scenario. */function verticalAlignment(g,layering,conflicts,neighborFn){let root={},align={},pos={}; // We cache the position here based on the layering because the graph and // layering may be out of sync. The layering matrix is manipulated to // generate different extreme alignments. layering.forEach(layer=>{layer.forEach((v,order)=>{root[v]=v;align[v]=v;pos[v]=order})});layering.forEach(layer=>{let prevIdx=-1;layer.forEach(v=>{let ws=neighborFn(v);if(ws.length){ws=ws.sort((a,b)=>pos[a]-pos[b]);let mp=(ws.length-1)/2;for(let i=Math.floor(mp),il=Math.ceil(mp);i<=il;++i){let w=ws[i];if(align[v]===v&&prevIdx{return Math.max(acc,xs[e.v]+blockG.edge(e))},0)} // Second pass, assign greatest coordinates function pass2(elem){let min=blockG.outEdges(elem).reduce((acc,e)=>{return Math.min(acc,xs[e.w]-blockG.edge(e))},Number.POSITIVE_INFINITY);let node=g.node(elem);if(min!==Number.POSITIVE_INFINITY&&node.borderType!==borderType){xs[elem]=Math.max(xs[elem],min)}}iterate(pass1,blockG.predecessors.bind(blockG));iterate(pass2,blockG.successors.bind(blockG)); // Assign x coordinates to all nodes Object.keys(align).forEach(v=>xs[v]=xs[root[v]]);return xs}function buildBlockGraph(g,layering,root,reverseSep){let blockGraph=new Graph,graphLabel=g.graph(),sepFn=sep(graphLabel.nodesep,graphLabel.edgesep,reverseSep);layering.forEach(layer=>{let u;layer.forEach(v=>{let vRoot=root[v];blockGraph.setNode(vRoot);if(u){var uRoot=root[u],prevMax=blockGraph.edge(uRoot,vRoot);blockGraph.setEdge(uRoot,vRoot,Math.max(sepFn(g,v,u),prevMax||0))}u=v})});return blockGraph} /* * Returns the alignment that has the smallest width of the given alignments. */function findSmallestWidthAlignment(g,xss){return Object.values(xss).reduce((currentMinAndXs,xs)=>{let max=Number.NEGATIVE_INFINITY;let min=Number.POSITIVE_INFINITY;Object.entries(xs).forEach(([v,x])=>{let halfWidth=width(g,v)/2;max=Math.max(x+halfWidth,max);min=Math.min(x-halfWidth,min)});const newMin=max-min;if(newMin{["l","r"].forEach(horiz=>{let alignment=vert+horiz,xs=xss[alignment];if(xs===alignTo)return;let xsVals=Object.values(xs);let delta=alignToMin-Math.min(...xsVals);if(horiz!=="l"){delta=alignToMax-Math.max(...xsVals)}if(delta){xss[alignment]=util.mapValues(xs,x=>x+delta)}})})}function balance(xss,align){return util.mapValues(xss.ul,(num,v)=>{if(align){return xss[align.toLowerCase()][v]}else{let xs=Object.values(xss).map(xs=>xs[v]).sort((a,b)=>a-b);return(xs[1]+xs[2])/2}})}function positionX(g){let layering=util.buildLayerMatrix(g);let conflicts=Object.assign(findType1Conflicts(g,layering),findType2Conflicts(g,layering));let xss={};let adjustedLayering;["u","d"].forEach(vert=>{adjustedLayering=vert==="u"?layering:Object.values(layering).reverse();["l","r"].forEach(horiz=>{if(horiz==="r"){adjustedLayering=adjustedLayering.map(inner=>{return Object.values(inner).reverse()})}let neighborFn=(vert==="u"?g.predecessors:g.successors).bind(g);let align=verticalAlignment(g,adjustedLayering,conflicts,neighborFn);let xs=horizontalCompaction(g,adjustedLayering,align.root,align.align,horiz==="r");if(horiz==="r"){xs=util.mapValues(xs,x=>-x)}xss[vert+horiz]=xs})});let smallestWidth=findSmallestWidthAlignment(g,xss);alignCoordinates(xss,smallestWidth);return balance(xss,g.graph().align)}function sep(nodeSep,edgeSep,reverseSep){return(g,v,w)=>{let vLabel=g.node(v);let wLabel=g.node(w);let sum=0;let delta;sum+=vLabel.width/2;if(vLabel.hasOwnProperty("labelpos")){switch(vLabel.labelpos.toLowerCase()){case"l":delta=-vLabel.width/2;break;case"r":delta=vLabel.width/2;break}}if(delta){sum+=reverseSep?delta:-delta}delta=0;sum+=(vLabel.dummy?edgeSep:nodeSep)/2;sum+=(wLabel.dummy?edgeSep:nodeSep)/2;sum+=wLabel.width/2;if(wLabel.hasOwnProperty("labelpos")){switch(wLabel.labelpos.toLowerCase()){case"l":delta=wLabel.width/2;break;case"r":delta=-wLabel.width/2;break}}if(delta){sum+=reverseSep?delta:-delta}delta=0;return sum}}function width(g,v){return g.node(v).width}},{"../util":27,"@dagrejs/graphlib":29}],22:[function(require,module,exports){"use strict";let util=require("../util");let positionX=require("./bk").positionX;module.exports=position;function position(g){g=util.asNonCompoundGraph(g);positionY(g);Object.entries(positionX(g)).forEach(([v,x])=>g.node(v).x=x)}function positionY(g){let layering=util.buildLayerMatrix(g);let rankSep=g.graph().ranksep;let prevY=0;layering.forEach(layer=>{const maxHeight=layer.reduce((acc,v)=>{const height=g.node(v).height;if(acc>height){return acc}else{return height}},0);layer.forEach(v=>g.node(v).y=prevY+maxHeight/2);prevY+=maxHeight+rankSep})}},{"../util":27,"./bk":21}],23:[function(require,module,exports){"use strict";var Graph=require("@dagrejs/graphlib").Graph;var slack=require("./util").slack;module.exports=feasibleTree; /* * Constructs a spanning tree with tight edges and adjusted the input node's * ranks to achieve this. A tight edge is one that is has a length that matches * its "minlen" attribute. * * The basic structure for this function is derived from Gansner, et al., "A * Technique for Drawing Directed Graphs." * * Pre-conditions: * * 1. Graph must be a DAG. * 2. Graph must be connected. * 3. Graph must have at least one node. * 5. Graph nodes must have been previously assigned a "rank" property that * respects the "minlen" property of incident edges. * 6. Graph edges must have a "minlen" property. * * Post-conditions: * * - Graph nodes will have their rank adjusted to ensure that all edges are * tight. * * Returns a tree (undirected graph) that is constructed using only "tight" * edges. */function feasibleTree(g){var t=new Graph({directed:false}); // Choose arbitrary node from which to start our tree var start=g.nodes()[0];var size=g.nodeCount();t.setNode(start,{});var edge,delta;while(tightTree(t,g){var edgeV=e.v,w=v===edgeV?e.w:edgeV;if(!t.hasNode(w)&&!slack(g,e)){t.setNode(w,{});t.setEdge(v,w,{});dfs(w)}})}t.nodes().forEach(dfs);return t.nodeCount()} /* * Finds the edge with the smallest slack that is incident on tree and returns * it. */function findMinSlackEdge(t,g){const edges=g.edges();return edges.reduce((acc,edge)=>{let edgeSlack=Number.POSITIVE_INFINITY;if(t.hasNode(edge.v)!==t.hasNode(edge.w)){edgeSlack=slack(g,edge)}if(edgeSlackg.node(v).rank+=delta)}},{"./util":26,"@dagrejs/graphlib":29}],24:[function(require,module,exports){"use strict";var rankUtil=require("./util");var longestPath=rankUtil.longestPath;var feasibleTree=require("./feasible-tree");var networkSimplex=require("./network-simplex");module.exports=rank; /* * Assigns a rank to each node in the input graph that respects the "minlen" * constraint specified on edges between nodes. * * This basic structure is derived from Gansner, et al., "A Technique for * Drawing Directed Graphs." * * Pre-conditions: * * 1. Graph must be a connected DAG * 2. Graph nodes must be objects * 3. Graph edges must have "weight" and "minlen" attributes * * Post-conditions: * * 1. Graph nodes will have a "rank" attribute based on the results of the * algorithm. Ranks can start at any index (including negative), we'll * fix them up later. */function rank(g){switch(g.graph().ranker){case"network-simplex":networkSimplexRanker(g);break;case"tight-tree":tightTreeRanker(g);break;case"longest-path":longestPathRanker(g);break;default:networkSimplexRanker(g)}} // A fast and simple ranker, but results are far from optimal. var longestPathRanker=longestPath;function tightTreeRanker(g){longestPath(g);feasibleTree(g)}function networkSimplexRanker(g){networkSimplex(g)}},{"./feasible-tree":23,"./network-simplex":25,"./util":26}],25:[function(require,module,exports){"use strict";var feasibleTree=require("./feasible-tree");var slack=require("./util").slack;var initRank=require("./util").longestPath;var preorder=require("@dagrejs/graphlib").alg.preorder;var postorder=require("@dagrejs/graphlib").alg.postorder;var simplify=require("../util").simplify;module.exports=networkSimplex; // Expose some internals for testing purposes networkSimplex.initLowLimValues=initLowLimValues;networkSimplex.initCutValues=initCutValues;networkSimplex.calcCutValue=calcCutValue;networkSimplex.leaveEdge=leaveEdge;networkSimplex.enterEdge=enterEdge;networkSimplex.exchangeEdges=exchangeEdges; /* * The network simplex algorithm assigns ranks to each node in the input graph * and iteratively improves the ranking to reduce the length of edges. * * Preconditions: * * 1. The input graph must be a DAG. * 2. All nodes in the graph must have an object value. * 3. All edges in the graph must have "minlen" and "weight" attributes. * * Postconditions: * * 1. All nodes in the graph will have an assigned "rank" attribute that has * been optimized by the network simplex algorithm. Ranks start at 0. * * * A rough sketch of the algorithm is as follows: * * 1. Assign initial ranks to each node. We use the longest path algorithm, * which assigns ranks to the lowest position possible. In general this * leads to very wide bottom ranks and unnecessarily long edges. * 2. Construct a feasible tight tree. A tight tree is one such that all * edges in the tree have no slack (difference between length of edge * and minlen for the edge). This by itself greatly improves the assigned * rankings by shorting edges. * 3. Iteratively find edges that have negative cut values. Generally a * negative cut value indicates that the edge could be removed and a new * tree edge could be added to produce a more compact graph. * * Much of the algorithms here are derived from Gansner, et al., "A Technique * for Drawing Directed Graphs." The structure of the file roughly follows the * structure of the overall algorithm. */function networkSimplex(g){g=simplify(g);initRank(g);var t=feasibleTree(g);initLowLimValues(t);initCutValues(t,g);var e,f;while(e=leaveEdge(t)){f=enterEdge(t,g,e);exchangeEdges(t,g,e,f)}} /* * Initializes cut values for all edges in the tree. */function initCutValues(t,g){var vs=postorder(t,t.nodes());vs=vs.slice(0,vs.length-1);vs.forEach(v=>assignCutValue(t,g,v))}function assignCutValue(t,g,child){var childLab=t.node(child);var parent=childLab.parent;t.edge(child,parent).cutvalue=calcCutValue(t,g,child)} /* * Given the tight tree, its graph, and a child in the graph calculate and * return the cut value for the edge between the child and its parent. */function calcCutValue(t,g,child){var childLab=t.node(child);var parent=childLab.parent; // True if the child is on the tail end of the edge in the directed graph var childIsTail=true; // The graph's view of the tree edge we're inspecting var graphEdge=g.edge(child,parent); // The accumulated cut value for the edge between this node and its parent var cutValue=0;if(!graphEdge){childIsTail=false;graphEdge=g.edge(parent,child)}cutValue=graphEdge.weight;g.nodeEdges(child).forEach(e=>{var isOutEdge=e.v===child,other=isOutEdge?e.w:e.v;if(other!==parent){var pointsToHead=isOutEdge===childIsTail,otherWeight=g.edge(e).weight;cutValue+=pointsToHead?otherWeight:-otherWeight;if(isTreeEdge(t,child,other)){var otherCutValue=t.edge(child,other).cutvalue;cutValue+=pointsToHead?-otherCutValue:otherCutValue}}});return cutValue}function initLowLimValues(tree,root){if(arguments.length<2){root=tree.nodes()[0]}dfsAssignLowLim(tree,{},1,root)}function dfsAssignLowLim(tree,visited,nextLim,v,parent){var low=nextLim;var label=tree.node(v);visited[v]=true;tree.neighbors(v).forEach(w=>{if(!visited.hasOwnProperty(w)){nextLim=dfsAssignLowLim(tree,visited,nextLim,w,v)}});label.low=low;label.lim=nextLim++;if(parent){label.parent=parent}else{ // TODO should be able to remove this when we incrementally update low lim delete label.parent}return nextLim}function leaveEdge(tree){return tree.edges().find(e=>tree.edge(e).cutvalue<0)}function enterEdge(t,g,edge){var v=edge.v;var w=edge.w; // For the rest of this function we assume that v is the tail and w is the // head, so if we don't have this edge in the graph we should flip it to // match the correct orientation. if(!g.hasEdge(v,w)){v=edge.w;w=edge.v}var vLabel=t.node(v);var wLabel=t.node(w);var tailLabel=vLabel;var flip=false; // If the root is in the tail of the edge then we need to flip the logic that // checks for the head and tail nodes in the candidates function below. if(vLabel.lim>wLabel.lim){tailLabel=wLabel;flip=true}var candidates=g.edges().filter(edge=>{return flip===isDescendant(t,t.node(edge.v),tailLabel)&&flip!==isDescendant(t,t.node(edge.w),tailLabel)});return candidates.reduce((acc,edge)=>{if(slack(g,edge)!g.node(v).parent);var vs=preorder(t,root);vs=vs.slice(1);vs.forEach(v=>{var parent=t.node(v).parent,edge=g.edge(v,parent),flipped=false;if(!edge){edge=g.edge(parent,v);flipped=true}g.node(v).rank=g.node(parent).rank+(flipped?edge.minlen:-edge.minlen)})} /* * Returns true if the edge is in the tree. */function isTreeEdge(tree,u,v){return tree.hasEdge(u,v)} /* * Returns true if the specified node is descendant of the root node per the * assigned low and lim attributes in the tree. */function isDescendant(tree,vLabel,rootLabel){return rootLabel.low<=vLabel.lim&&vLabel.lim<=rootLabel.lim}},{"../util":27,"./feasible-tree":23,"./util":26,"@dagrejs/graphlib":29}],26:[function(require,module,exports){"use strict";module.exports={longestPath:longestPath,slack:slack}; /* * Initializes ranks for the input graph using the longest path algorithm. This * algorithm scales well and is fast in practice, it yields rather poor * solutions. Nodes are pushed to the lowest layer possible, leaving the bottom * ranks wide and leaving edges longer than necessary. However, due to its * speed, this algorithm is good for getting an initial ranking that can be fed * into other algorithms. * * This algorithm does not normalize layers because it will be used by other * algorithms in most cases. If using this algorithm directly, be sure to * run normalize at the end. * * Pre-conditions: * * 1. Input graph is a DAG. * 2. Input graph node labels can be assigned properties. * * Post-conditions: * * 1. Each node will be assign an (unnormalized) "rank" property. */function longestPath(g){var visited={};function dfs(v){var label=g.node(v);if(visited.hasOwnProperty(v)){return label.rank}visited[v]=true;var rank=Math.min(...g.outEdges(v).map(e=>{if(e==null){return Number.POSITIVE_INFINITY}return dfs(e.w)-g.edge(e).minlen}));if(rank===Number.POSITIVE_INFINITY){rank=0}return label.rank=rank}g.sources().forEach(dfs)} /* * Returns the amount of slack for the given edge. The slack is defined as the * difference between the length of the edge and its minimum length. */function slack(g,e){return g.node(e.w).rank-g.node(e.v).rank-g.edge(e).minlen}},{}],27:[function(require,module,exports){ /* eslint "no-console": off */ "use strict";let Graph=require("@dagrejs/graphlib").Graph;module.exports={addBorderNode:addBorderNode,addDummyNode:addDummyNode,asNonCompoundGraph:asNonCompoundGraph,buildLayerMatrix:buildLayerMatrix,intersectRect:intersectRect,mapValues:mapValues,maxRank:maxRank,normalizeRanks:normalizeRanks,notime:notime,partition:partition,pick:pick,predecessorWeights:predecessorWeights,range:range,removeEmptyRanks:removeEmptyRanks,simplify:simplify,successorWeights:successorWeights,time:time,uniqueId:uniqueId,zipObject:zipObject}; /* * Adds a dummy node to the graph and return v. */function addDummyNode(g,type,attrs,name){let v;do{v=uniqueId(name)}while(g.hasNode(v));attrs.dummy=type;g.setNode(v,attrs);return v} /* * Returns a new graph with only simple edges. Handles aggregation of data * associated with multi-edges. */function simplify(g){let simplified=(new Graph).setGraph(g.graph());g.nodes().forEach(v=>simplified.setNode(v,g.node(v)));g.edges().forEach(e=>{let simpleLabel=simplified.edge(e.v,e.w)||{weight:0,minlen:1};let label=g.edge(e);simplified.setEdge(e.v,e.w,{weight:simpleLabel.weight+label.weight,minlen:Math.max(simpleLabel.minlen,label.minlen)})});return simplified}function asNonCompoundGraph(g){let simplified=new Graph({multigraph:g.isMultigraph()}).setGraph(g.graph());g.nodes().forEach(v=>{if(!g.children(v).length){simplified.setNode(v,g.node(v))}});g.edges().forEach(e=>{simplified.setEdge(e,g.edge(e))});return simplified}function successorWeights(g){let weightMap=g.nodes().map(v=>{let sucs={};g.outEdges(v).forEach(e=>{sucs[e.w]=(sucs[e.w]||0)+g.edge(e).weight});return sucs});return zipObject(g.nodes(),weightMap)}function predecessorWeights(g){let weightMap=g.nodes().map(v=>{let preds={};g.inEdges(v).forEach(e=>{preds[e.v]=(preds[e.v]||0)+g.edge(e).weight});return preds});return zipObject(g.nodes(),weightMap)} /* * Finds where a line starting at point ({x, y}) would intersect a rectangle * ({x, y, width, height}) if it were pointing at the rectangle's center. */function intersectRect(rect,point){let x=rect.x;let y=rect.y; // Rectangle intersection algorithm from: // http://math.stackexchange.com/questions/108113/find-edge-between-two-boxes let dx=point.x-x;let dy=point.y-y;let w=rect.width/2;let h=rect.height/2;if(!dx&&!dy){throw new Error("Not possible to find intersection inside of the rectangle")}let sx,sy;if(Math.abs(dy)*w>Math.abs(dx)*h){ // Intersection is top or bottom of rect. if(dy<0){h=-h}sx=h*dx/dy;sy=h}else{ // Intersection is left or right of rect. if(dx<0){w=-w}sx=w;sy=w*dy/dx}return{x:x+sx,y:y+sy}} /* * Given a DAG with each node assigned "rank" and "order" properties, this * function will produce a matrix with the ids of each node. */function buildLayerMatrix(g){let layering=range(maxRank(g)+1).map(()=>[]);g.nodes().forEach(v=>{let node=g.node(v);let rank=node.rank;if(rank!==undefined){layering[rank][node.order]=v}});return layering} /* * Adjusts the ranks for all nodes in the graph such that all nodes v have * rank(v) >= 0 and at least one node w has rank(w) = 0. */function normalizeRanks(g){let min=Math.min(...g.nodes().map(v=>{let rank=g.node(v).rank;if(rank===undefined){return Number.MAX_VALUE}return rank}));g.nodes().forEach(v=>{let node=g.node(v);if(node.hasOwnProperty("rank")){node.rank-=min}})}function removeEmptyRanks(g){ // Ranks may not start at 0, so we need to offset them let offset=Math.min(...g.nodes().map(v=>g.node(v).rank));let layers=[];g.nodes().forEach(v=>{let rank=g.node(v).rank-offset;if(!layers[rank]){layers[rank]=[]}layers[rank].push(v)});let delta=0;let nodeRankFactor=g.graph().nodeRankFactor;Array.from(layers).forEach((vs,i)=>{if(vs===undefined&&i%nodeRankFactor!==0){--delta}else if(vs!==undefined&&delta){vs.forEach(v=>g.node(v).rank+=delta)}})}function addBorderNode(g,prefix,rank,order){let node={width:0,height:0};if(arguments.length>=4){node.rank=rank;node.order=order}return addDummyNode(g,"border",node,prefix)}function maxRank(g){return Math.max(...g.nodes().map(v=>{let rank=g.node(v).rank;if(rank===undefined){return Number.MIN_VALUE}return rank}))} /* * Partition a collection into two groups: `lhs` and `rhs`. If the supplied * function returns true for an entry it goes into `lhs`. Otherwise it goes * into `rhs. */function partition(collection,fn){let result={lhs:[],rhs:[]};collection.forEach(value=>{if(fn(value)){result.lhs.push(value)}else{result.rhs.push(value)}});return result} /* * Returns a new function that wraps `fn` with a timer. The wrapper logs the * time it takes to execute the function. */function time(name,fn){let start=Date.now();try{return fn()}finally{console.log(name+" time: "+(Date.now()-start)+"ms")}}function notime(name,fn){return fn()}let idCounter=0;function uniqueId(prefix){var id=++idCounter;return toString(prefix)+id}function range(start,limit,step=1){if(limit==null){limit=start;start=0}let endCon=i=>ilimitval[funcOrProp]}return Object.entries(obj).reduce((acc,[k,v])=>{acc[k]=func(v,k);return acc},{})}function zipObject(props,values){return props.reduce((acc,key,i)=>{acc[key]=values[i];return acc},{})}},{"@dagrejs/graphlib":29}],28:[function(require,module,exports){module.exports="1.1.2"},{}],29:[function(require,module,exports){ /** * Copyright (c) 2014, Chris Pettitt * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * 1. Redistributions of source code must retain the above copyright notice, this * list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and/or other materials provided with the distribution. * * 3. Neither the name of the copyright holder nor the names of its contributors * may be used to endorse or promote products derived from this software without * specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ var lib=require("./lib");module.exports={Graph:lib.Graph,json:require("./lib/json"),alg:require("./lib/alg"),version:lib.version}},{"./lib":45,"./lib/alg":36,"./lib/json":46}],30:[function(require,module,exports){module.exports=components;function components(g){var visited={};var cmpts=[];var cmpt;function dfs(v){if(visited.hasOwnProperty(v))return;visited[v]=true;cmpt.push(v);g.successors(v).forEach(dfs);g.predecessors(v).forEach(dfs)}g.nodes().forEach(function(v){cmpt=[];dfs(v);if(cmpt.length){cmpts.push(cmpt)}});return cmpts}},{}],31:[function(require,module,exports){module.exports=dfs; /* * A helper that preforms a pre- or post-order traversal on the input graph * and returns the nodes in the order they were visited. If the graph is * undirected then this algorithm will navigate using neighbors. If the graph * is directed then this algorithm will navigate using successors. * * If the order is not "post", it will be treated as "pre". */function dfs(g,vs,order){if(!Array.isArray(vs)){vs=[vs]}var navigation=g.isDirected()?v=>g.successors(v):v=>g.neighbors(v);var orderFunc=order==="post"?postOrderDfs:preOrderDfs;var acc=[];var visited={};vs.forEach(v=>{if(!g.hasNode(v)){throw new Error("Graph does not have node: "+v)}orderFunc(v,navigation,visited,acc)});return acc}function postOrderDfs(v,navigation,visited,acc){var stack=[[v,false]];while(stack.length>0){var curr=stack.pop();if(curr[1]){acc.push(curr[0])}else{if(!visited.hasOwnProperty(curr[0])){visited[curr[0]]=true;stack.push([curr[0],true]);forEachRight(navigation(curr[0]),w=>stack.push([w,false]))}}}}function preOrderDfs(v,navigation,visited,acc){var stack=[v];while(stack.length>0){var curr=stack.pop();if(!visited.hasOwnProperty(curr)){visited[curr]=true;acc.push(curr);forEachRight(navigation(curr),w=>stack.push(w))}}}function forEachRight(array,iteratee){var length=array.length;while(length--){iteratee(array[length],length,array)}return array}},{}],32:[function(require,module,exports){var dijkstra=require("./dijkstra");module.exports=dijkstraAll;function dijkstraAll(g,weightFunc,edgeFunc){return g.nodes().reduce(function(acc,v){acc[v]=dijkstra(g,v,weightFunc,edgeFunc);return acc},{})}},{"./dijkstra":33}],33:[function(require,module,exports){var PriorityQueue=require("../data/priority-queue");module.exports=dijkstra;var DEFAULT_WEIGHT_FUNC=()=>1;function dijkstra(g,source,weightFn,edgeFn){return runDijkstra(g,String(source),weightFn||DEFAULT_WEIGHT_FUNC,edgeFn||function(v){return g.outEdges(v)})}function runDijkstra(g,source,weightFn,edgeFn){var results={};var pq=new PriorityQueue;var v,vEntry;var updateNeighbors=function(edge){var w=edge.v!==v?edge.v:edge.w;var wEntry=results[w];var weight=weightFn(edge);var distance=vEntry.distance+weight;if(weight<0){throw new Error("dijkstra does not allow negative edge weights. "+"Bad edge: "+edge+" Weight: "+weight)}if(distance0){v=pq.removeMin();vEntry=results[v];if(vEntry.distance===Number.POSITIVE_INFINITY){break}edgeFn(v).forEach(updateNeighbors)}return results}},{"../data/priority-queue":43}],34:[function(require,module,exports){var tarjan=require("./tarjan");module.exports=findCycles;function findCycles(g){return tarjan(g).filter(function(cmpt){return cmpt.length>1||cmpt.length===1&&g.hasEdge(cmpt[0],cmpt[0])})}},{"./tarjan":41}],35:[function(require,module,exports){module.exports=floydWarshall;var DEFAULT_WEIGHT_FUNC=()=>1;function floydWarshall(g,weightFn,edgeFn){return runFloydWarshall(g,weightFn||DEFAULT_WEIGHT_FUNC,edgeFn||function(v){return g.outEdges(v)})}function runFloydWarshall(g,weightFn,edgeFn){var results={};var nodes=g.nodes();nodes.forEach(function(v){results[v]={};results[v][v]={distance:0};nodes.forEach(function(w){if(v!==w){results[v][w]={distance:Number.POSITIVE_INFINITY}}});edgeFn(v).forEach(function(edge){var w=edge.v===v?edge.w:edge.v;var d=weightFn(edge);results[v][w]={distance:d,predecessor:v}})});nodes.forEach(function(k){var rowK=results[k];nodes.forEach(function(i){var rowI=results[i];nodes.forEach(function(j){var ik=rowI[k];var kj=rowK[j];var ij=rowI[j];var altDistance=ik.distance+kj.distance;if(altDistance0){v=pq.removeMin();if(parents.hasOwnProperty(v)){result.setEdge(v,parents[v])}else if(init){throw new Error("Input graph is not connected: "+g)}else{init=true}g.nodeEdges(v).forEach(updateNeighbors)}return result}},{"../data/priority-queue":43,"../graph":44}],41:[function(require,module,exports){module.exports=tarjan;function tarjan(g){var index=0;var stack=[];var visited={};// node id -> { onStack, lowlink, index } var results=[];function dfs(v){var entry=visited[v]={onStack:true,lowlink:index,index:index++};stack.push(v);g.successors(v).forEach(function(w){if(!visited.hasOwnProperty(w)){dfs(w);entry.lowlink=Math.min(entry.lowlink,visited[w].lowlink)}else if(visited[w].onStack){entry.lowlink=Math.min(entry.lowlink,visited[w].index)}});if(entry.lowlink===entry.index){var cmpt=[];var w;do{w=stack.pop();visited[w].onStack=false;cmpt.push(w)}while(v!==w);results.push(cmpt)}}g.nodes().forEach(function(v){if(!visited.hasOwnProperty(v)){dfs(v)}});return results}},{}],42:[function(require,module,exports){function topsort(g){var visited={};var stack={};var results=[];function visit(node){if(stack.hasOwnProperty(node)){throw new CycleException}if(!visited.hasOwnProperty(node)){stack[node]=true;visited[node]=true;g.predecessors(node).forEach(visit);delete stack[node];results.push(node)}}g.sinks().forEach(visit);if(Object.keys(visited).length!==g.nodeCount()){throw new CycleException}return results}class CycleException extends Error{constructor(){super(...arguments)}}module.exports=topsort;topsort.CycleException=CycleException},{}],43:[function(require,module,exports){ /** * A min-priority queue data structure. This algorithm is derived from Cormen, * et al., "Introduction to Algorithms". The basic idea of a min-priority * queue is that you can efficiently (in O(1) time) get the smallest key in * the queue. Adding and removing elements takes O(log n) time. A key can * have its priority decreased in O(log n) time. */ class PriorityQueue{_arr=[];_keyIndices={}; /** * Returns the number of elements in the queue. Takes `O(1)` time. */size(){return this._arr.length} /** * Returns the keys that are in the queue. Takes `O(n)` time. */keys(){return this._arr.map(function(x){return x.key})} /** * Returns `true` if **key** is in the queue and `false` if not. */has(key){return this._keyIndices.hasOwnProperty(key)} /** * Returns the priority for **key**. If **key** is not present in the queue * then this function returns `undefined`. Takes `O(1)` time. * * @param {Object} key */priority(key){var index=this._keyIndices[key];if(index!==undefined){return this._arr[index].priority}} /** * Returns the key for the minimum element in this queue. If the queue is * empty this function throws an Error. Takes `O(1)` time. */min(){if(this.size()===0){throw new Error("Queue underflow")}return this._arr[0].key} /** * Inserts a new key into the priority queue. If the key already exists in * the queue this function returns `false`; otherwise it will return `true`. * Takes `O(n)` time. * * @param {Object} key the key to add * @param {Number} priority the initial priority for the key */add(key,priority){var keyIndices=this._keyIndices;key=String(key);if(!keyIndices.hasOwnProperty(key)){var arr=this._arr;var index=arr.length;keyIndices[key]=index;arr.push({key:key,priority:priority});this._decrease(index);return true}return false} /** * Removes and returns the smallest key in the queue. Takes `O(log n)` time. */removeMin(){this._swap(0,this._arr.length-1);var min=this._arr.pop();delete this._keyIndices[min.key];this._heapify(0);return min.key} /** * Decreases the priority for **key** to **priority**. If the new priority is * greater than the previous priority, this function will throw an Error. * * @param {Object} key the key for which to raise priority * @param {Number} priority the new priority for the key */decrease(key,priority){var index=this._keyIndices[key];if(priority>this._arr[index].priority){throw new Error("New priority is greater than current priority. "+"Key: "+key+" Old: "+this._arr[index].priority+" New: "+priority)}this._arr[index].priority=priority;this._decrease(index)}_heapify(i){var arr=this._arr;var l=2*i;var r=l+1;var largest=i;if(l>1;if(arr[parent].priorityundefined; // Defaults to be set when creating a new edge _defaultEdgeLabelFn=()=>undefined; // v -> label _nodes={}; // v -> edgeObj _in={}; // u -> v -> Number _preds={}; // v -> edgeObj _out={}; // v -> w -> Number _sucs={}; // e -> edgeObj _edgeObjs={}; // e -> label _edgeLabels={}; /* Number of nodes in the graph. Should only be changed by the implementation. */_nodeCount=0; /* Number of edges in the graph. Should only be changed by the implementation. */_edgeCount=0;_parent;_children;constructor(opts){if(opts){this._isDirected=opts.hasOwnProperty("directed")?opts.directed:true;this._isMultigraph=opts.hasOwnProperty("multigraph")?opts.multigraph:false;this._isCompound=opts.hasOwnProperty("compound")?opts.compound:false}if(this._isCompound){ // v -> parent this._parent={}; // v -> children this._children={};this._children[GRAPH_NODE]={}}} /* === Graph functions ========= */ /** * Whether graph was created with 'directed' flag set to true or not. */isDirected(){return this._isDirected} /** * Whether graph was created with 'multigraph' flag set to true or not. */isMultigraph(){return this._isMultigraph} /** * Whether graph was created with 'compound' flag set to true or not. */isCompound(){return this._isCompound} /** * Sets the label of the graph. */setGraph(label){this._label=label;return this} /** * Gets the graph label. */graph(){return this._label} /* === Node functions ========== */ /** * Sets the default node label. If newDefault is a function, it will be * invoked ach time when setting a label for a node. Otherwise, this label * will be assigned as default label in case if no label was specified while * setting a node. * Complexity: O(1). */setDefaultNodeLabel(newDefault){this._defaultNodeLabelFn=newDefault;if(typeof newDefault!=="function"){this._defaultNodeLabelFn=()=>newDefault}return this} /** * Gets the number of nodes in the graph. * Complexity: O(1). */nodeCount(){return this._nodeCount} /** * Gets all nodes of the graph. Note, the in case of compound graph subnodes are * not included in list. * Complexity: O(1). */nodes(){return Object.keys(this._nodes)} /** * Gets list of nodes without in-edges. * Complexity: O(|V|). */sources(){var self=this;return this.nodes().filter(v=>Object.keys(self._in[v]).length===0)} /** * Gets list of nodes without out-edges. * Complexity: O(|V|). */sinks(){var self=this;return this.nodes().filter(v=>Object.keys(self._out[v]).length===0)} /** * Invokes setNode method for each node in names list. * Complexity: O(|names|). */setNodes(vs,value){var args=arguments;var self=this;vs.forEach(function(v){if(args.length>1){self.setNode(v,value)}else{self.setNode(v)}});return this} /** * Creates or updates the value for the node v in the graph. If label is supplied * it is set as the value for the node. If label is not supplied and the node was * created by this call then the default node label will be assigned. * Complexity: O(1). */setNode(v,value){if(this._nodes.hasOwnProperty(v)){if(arguments.length>1){this._nodes[v]=value}return this}this._nodes[v]=arguments.length>1?value:this._defaultNodeLabelFn(v);if(this._isCompound){this._parent[v]=GRAPH_NODE;this._children[v]={};this._children[GRAPH_NODE][v]=true}this._in[v]={};this._preds[v]={};this._out[v]={};this._sucs[v]={};++this._nodeCount;return this} /** * Gets the label of node with specified name. * Complexity: O(|V|). */node(v){return this._nodes[v]} /** * Detects whether graph has a node with specified name or not. */hasNode(v){return this._nodes.hasOwnProperty(v)} /** * Remove the node with the name from the graph or do nothing if the node is not in * the graph. If the node was removed this function also removes any incident * edges. * Complexity: O(1). */removeNode(v){var self=this;if(this._nodes.hasOwnProperty(v)){var removeEdge=e=>self.removeEdge(self._edgeObjs[e]);delete this._nodes[v];if(this._isCompound){this._removeFromParentsChildList(v);delete this._parent[v];this.children(v).forEach(function(child){self.setParent(child)});delete this._children[v]}Object.keys(this._in[v]).forEach(removeEdge);delete this._in[v];delete this._preds[v];Object.keys(this._out[v]).forEach(removeEdge);delete this._out[v];delete this._sucs[v];--this._nodeCount}return this} /** * Sets node p as a parent for node v if it is defined, or removes the * parent for v if p is undefined. Method throws an exception in case of * invoking it in context of noncompound graph. * Average-case complexity: O(1). */setParent(v,parent){if(!this._isCompound){throw new Error("Cannot set parent in a non-compound graph")}if(parent===undefined){parent=GRAPH_NODE}else{ // Coerce parent to string parent+="";for(var ancestor=parent;ancestor!==undefined;ancestor=this.parent(ancestor)){if(ancestor===v){throw new Error("Setting "+parent+" as parent of "+v+" would create a cycle")}}this.setNode(parent)}this.setNode(v);this._removeFromParentsChildList(v);this._parent[v]=parent;this._children[parent][v]=true;return this}_removeFromParentsChildList(v){delete this._children[this._parent[v]][v]} /** * Gets parent node for node v. * Complexity: O(1). */parent(v){if(this._isCompound){var parent=this._parent[v];if(parent!==GRAPH_NODE){return parent}}} /** * Gets list of direct children of node v. * Complexity: O(1). */children(v=GRAPH_NODE){if(this._isCompound){var children=this._children[v];if(children){return Object.keys(children)}}else if(v===GRAPH_NODE){return this.nodes()}else if(this.hasNode(v)){return[]}} /** * Return all nodes that are predecessors of the specified node or undefined if node v is not in * the graph. Behavior is undefined for undirected graphs - use neighbors instead. * Complexity: O(|V|). */predecessors(v){var predsV=this._preds[v];if(predsV){return Object.keys(predsV)}} /** * Return all nodes that are successors of the specified node or undefined if node v is not in * the graph. Behavior is undefined for undirected graphs - use neighbors instead. * Complexity: O(|V|). */successors(v){var sucsV=this._sucs[v];if(sucsV){return Object.keys(sucsV)}} /** * Return all nodes that are predecessors or successors of the specified node or undefined if * node v is not in the graph. * Complexity: O(|V|). */neighbors(v){var preds=this.predecessors(v);if(preds){const union=new Set(preds);for(var succ of this.successors(v)){union.add(succ)}return Array.from(union.values())}}isLeaf(v){var neighbors;if(this.isDirected()){neighbors=this.successors(v)}else{neighbors=this.neighbors(v)}return neighbors.length===0} /** * Creates new graph with nodes filtered via filter. Edges incident to rejected node * are also removed. In case of compound graph, if parent is rejected by filter, * than all its children are rejected too. * Average-case complexity: O(|E|+|V|). */filterNodes(filter){var copy=new this.constructor({directed:this._isDirected,multigraph:this._isMultigraph,compound:this._isCompound});copy.setGraph(this.graph());var self=this;Object.entries(this._nodes).forEach(function([v,value]){if(filter(v)){copy.setNode(v,value)}});Object.values(this._edgeObjs).forEach(function(e){if(copy.hasNode(e.v)&©.hasNode(e.w)){copy.setEdge(e,self.edge(e))}});var parents={};function findParent(v){var parent=self.parent(v);if(parent===undefined||copy.hasNode(parent)){parents[v]=parent;return parent}else if(parent in parents){return parents[parent]}else{return findParent(parent)}}if(this._isCompound){copy.nodes().forEach(v=>copy.setParent(v,findParent(v)))}return copy} /* === Edge functions ========== */ /** * Sets the default edge label or factory function. This label will be * assigned as default label in case if no label was specified while setting * an edge or this function will be invoked each time when setting an edge * with no label specified and returned value * will be used as a label for edge. * Complexity: O(1). */setDefaultEdgeLabel(newDefault){this._defaultEdgeLabelFn=newDefault;if(typeof newDefault!=="function"){this._defaultEdgeLabelFn=()=>newDefault}return this} /** * Gets the number of edges in the graph. * Complexity: O(1). */edgeCount(){return this._edgeCount} /** * Gets edges of the graph. In case of compound graph subgraphs are not considered. * Complexity: O(|E|). */edges(){return Object.values(this._edgeObjs)} /** * Establish an edges path over the nodes in nodes list. If some edge is already * exists, it will update its label, otherwise it will create an edge between pair * of nodes with label provided or default label if no label provided. * Complexity: O(|nodes|). */setPath(vs,value){var self=this;var args=arguments;vs.reduce(function(v,w){if(args.length>1){self.setEdge(v,w,value)}else{self.setEdge(v,w)}return w});return this} /** * Creates or updates the label for the edge (v, w) with the optionally supplied * name. If label is supplied it is set as the value for the edge. If label is not * supplied and the edge was created by this call then the default edge label will * be assigned. The name parameter is only useful with multigraphs. */setEdge(){var v,w,name,value;var valueSpecified=false;var arg0=arguments[0];if(typeof arg0==="object"&&arg0!==null&&"v"in arg0){v=arg0.v;w=arg0.w;name=arg0.name;if(arguments.length===2){value=arguments[1];valueSpecified=true}}else{v=arg0;w=arguments[1];name=arguments[3];if(arguments.length>2){value=arguments[2];valueSpecified=true}}v=""+v;w=""+w;if(name!==undefined){name=""+name}var e=edgeArgsToId(this._isDirected,v,w,name);if(this._edgeLabels.hasOwnProperty(e)){if(valueSpecified){this._edgeLabels[e]=value}return this}if(name!==undefined&&!this._isMultigraph){throw new Error("Cannot set a named edge when isMultigraph = false")} // It didn't exist, so we need to create it. // First ensure the nodes exist. this.setNode(v);this.setNode(w);this._edgeLabels[e]=valueSpecified?value:this._defaultEdgeLabelFn(v,w,name);var edgeObj=edgeArgsToObj(this._isDirected,v,w,name); // Ensure we add undirected edges in a consistent way. v=edgeObj.v;w=edgeObj.w;Object.freeze(edgeObj);this._edgeObjs[e]=edgeObj;incrementOrInitEntry(this._preds[w],v);incrementOrInitEntry(this._sucs[v],w);this._in[w][e]=edgeObj;this._out[v][e]=edgeObj;this._edgeCount++;return this} /** * Gets the label for the specified edge. * Complexity: O(1). */edge(v,w,name){var e=arguments.length===1?edgeObjToId(this._isDirected,arguments[0]):edgeArgsToId(this._isDirected,v,w,name);return this._edgeLabels[e]} /** * Gets the label for the specified edge and converts it to an object. * Complexity: O(1) */edgeAsObj(){const edge=this.edge(...arguments);if(typeof edge!=="object"){return{label:edge}}return edge} /** * Detects whether the graph contains specified edge or not. No subgraphs are considered. * Complexity: O(1). */hasEdge(v,w,name){var e=arguments.length===1?edgeObjToId(this._isDirected,arguments[0]):edgeArgsToId(this._isDirected,v,w,name);return this._edgeLabels.hasOwnProperty(e)} /** * Removes the specified edge from the graph. No subgraphs are considered. * Complexity: O(1). */removeEdge(v,w,name){var e=arguments.length===1?edgeObjToId(this._isDirected,arguments[0]):edgeArgsToId(this._isDirected,v,w,name);var edge=this._edgeObjs[e];if(edge){v=edge.v;w=edge.w;delete this._edgeLabels[e];delete this._edgeObjs[e];decrementOrRemoveEntry(this._preds[w],v);decrementOrRemoveEntry(this._sucs[v],w);delete this._in[w][e];delete this._out[v][e];this._edgeCount--}return this} /** * Return all edges that point to the node v. Optionally filters those edges down to just those * coming from node u. Behavior is undefined for undirected graphs - use nodeEdges instead. * Complexity: O(|E|). */inEdges(v,u){var inV=this._in[v];if(inV){var edges=Object.values(inV);if(!u){return edges}return edges.filter(edge=>edge.v===u)}} /** * Return all edges that are pointed at by node v. Optionally filters those edges down to just * those point to w. Behavior is undefined for undirected graphs - use nodeEdges instead. * Complexity: O(|E|). */outEdges(v,w){var outV=this._out[v];if(outV){var edges=Object.values(outV);if(!w){return edges}return edges.filter(edge=>edge.w===w)}} /** * Returns all edges to or from node v regardless of direction. Optionally filters those edges * down to just those between nodes v and w regardless of direction. * Complexity: O(|E|). */nodeEdges(v,w){var inEdges=this.inEdges(v,w);if(inEdges){return inEdges.concat(this.outEdges(v,w))}}}function incrementOrInitEntry(map,k){if(map[k]){map[k]++}else{map[k]=1}}function decrementOrRemoveEntry(map,k){if(!--map[k]){delete map[k]}}function edgeArgsToId(isDirected,v_,w_,name){var v=""+v_;var w=""+w_;if(!isDirected&&v>w){var tmp=v;v=w;w=tmp}return v+EDGE_KEY_DELIM+w+EDGE_KEY_DELIM+(name===undefined?DEFAULT_EDGE_NAME:name)}function edgeArgsToObj(isDirected,v_,w_,name){var v=""+v_;var w=""+w_;if(!isDirected&&v>w){var tmp=v;v=w;w=tmp}var edgeObj={v:v,w:w};if(name){edgeObj.name=name}return edgeObj}function edgeObjToId(isDirected,edgeObj){return edgeArgsToId(isDirected,edgeObj.v,edgeObj.w,edgeObj.name)}module.exports=Graph},{}],45:[function(require,module,exports){ // Includes only the "core" of graphlib module.exports={Graph:require("./graph"),version:require("./version")}},{"./graph":44,"./version":47}],46:[function(require,module,exports){var Graph=require("./graph");module.exports={write:write,read:read}; /** * Creates a JSON representation of the graph that can be serialized to a string with * JSON.stringify. The graph can later be restored using json.read. */function write(g){var json={options:{directed:g.isDirected(),multigraph:g.isMultigraph(),compound:g.isCompound()},nodes:writeNodes(g),edges:writeEdges(g)};if(g.graph()!==undefined){json.value=structuredClone(g.graph())}return json}function writeNodes(g){return g.nodes().map(function(v){var nodeValue=g.node(v);var parent=g.parent(v);var node={v:v};if(nodeValue!==undefined){node.value=nodeValue}if(parent!==undefined){node.parent=parent}return node})}function writeEdges(g){return g.edges().map(function(e){var edgeValue=g.edge(e);var edge={v:e.v,w:e.w};if(e.name!==undefined){edge.name=e.name}if(edgeValue!==undefined){edge.value=edgeValue}return edge})} /** * Takes JSON as input and returns the graph representation. * * @example * var g2 = graphlib.json.read(JSON.parse(str)); * g2.nodes(); * // ['a', 'b'] * g2.edges() * // [ { v: 'a', w: 'b' } ] */function read(json){var g=new Graph(json.options).setGraph(json.value);json.nodes.forEach(function(entry){g.setNode(entry.v,entry.value);if(entry.parent){g.setParent(entry.v,entry.parent)}});json.edges.forEach(function(entry){g.setEdge({v:entry.v,w:entry.w,name:entry.name},entry.value)});return g}},{"./graph":44}],47:[function(require,module,exports){module.exports="2.2.2"},{}]},{},[1])(1)});