)});time("    normalize.undo",function(){normalize.undo(g)});time("    fixupEdgeLabelCoords",function(){fixupEdgeLabelCoords(g)});time("    undoCoordinateSystem",function(){coordinateSystem.undo(g)});time("    translateGraph",function(){translateGraph(g)});time("    assignNodeIntersects",function(){assignNodeIntersects(g)});time("    reversePoints",function(){reversePointsForReversedEdges(g)});time("    acyclic.undo",function(){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){_.forEach(inputGraph.nodes(),function(v){var inputLabel=inputGraph.node(v);var layoutLabel=layoutGraph.node(v);if(inputLabel){inputLabel.x=layoutLabel.x;inputLabel.y=layoutLabel.y;if(layoutGraph.children(v).length){inputLabel.width=layoutLabel.width;inputLabel.height=layoutLabel.height}}});_.forEach(inputGraph.edges(),function(e){var inputLabel=inputGraph.edge(e);var layoutLabel=layoutGraph.edge(e);inputLabel.points=layoutLabel.points;if(_.has(layoutLabel,"x")){inputLabel.x=layoutLabel.x;inputLabel.y=layoutLabel.y}});inputGraph.graph().width=layoutGraph.graph().width;inputGraph.graph().height=layoutGraph.graph().height}var graphNumAttrs=["nodesep","edgesep","ranksep","marginx","marginy"];var graphDefaults={ranksep:50,edgesep:20,nodesep:50,rankdir:"tb"};var graphAttrs=["acyclicer","ranker","rankdir","align"];var nodeNumAttrs=["width","height"];var nodeDefaults={width:0,height:0};var edgeNumAttrs=["minlen","weight","width","height","labeloffset"];var edgeDefaults={minlen:1,weight:1,width:0,height:0,labeloffset:10,labelpos:"r"};var 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){var g=new Graph({multigraph:true,compound:true});var graph=canonicalize(inputGraph.graph());g.setGraph(_.merge({},graphDefaults,selectNumberAttrs(graph,graphNumAttrs),_.pick(graph,graphAttrs)));_.forEach(inputGraph.nodes(),function(v){var node=canonicalize(inputGraph.node(v));g.setNode(v,_.defaults(selectNumberAttrs(node,nodeNumAttrs),nodeDefaults));g.setParent(v,inputGraph.parent(v))});_.forEach(inputGraph.edges(),function(e){var edge=canonicalize(inputGraph.edge(e));g.setEdge(e,_.merge({},edgeDefaults,selectNumberAttrs(edge,edgeNumAttrs),_.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){var graph=g.graph();graph.ranksep/=2;_.forEach(g.edges(),function(e){var 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){_.forEach(g.edges(),function(e){var edge=g.edge(e);if(edge.width&&edge.height){var v=g.node(e.v);var w=g.node(e.w);var label={rank:(w.rank-v.rank)/2+v.rank,e:e};util.addDummyNode(g,"edge-proxy",label,"_ep")}})}function assignRankMinMax(g){var maxRank=0;_.forEach(g.nodes(),function(v){var node=g.node(v);if(node.borderTop){node.minRank=g.node(node.borderTop).rank;node.maxRank=g.node(node.borderBottom).rank;maxRank=_.max(maxRank,node.maxRank)}});g.graph().maxRank=maxRank}function removeEdgeLabelProxies(g){_.forEach(g.nodes(),function(v){var node=g.node(v);if(node.dummy==="edge-proxy"){g.edge(node.e).labelRank=node.rank;g.removeNode(v)}})}function translateGraph(g){var minX=Number.POSITIVE_INFINITY;var maxX=0;var minY=Number.POSITIVE_INFINITY;var maxY=0;var graphLabel=g.graph();var marginX=graphLabel.marginx||0;var marginY=graphLabel.marginy||0;function getExtremes(attrs){var x=attrs.x;var y=attrs.y;var w=attrs.width;var 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)}_.forEach(g.nodes(),function(v){getExtremes(g.node(v))});_.forEach(g.edges(),function(e){var edge=g.edge(e);if(_.has(edge,"x")){getExtremes(edge)}});minX-=marginX;minY-=marginY;_.forEach(g.nodes(),function(v){var node=g.node(v);node.x-=minX;node.y-=minY});_.forEach(g.edges(),function(e){var edge=g.edge(e);_.forEach(edge.points,function(p){p.x-=minX;p.y-=minY});if(_.has(edge,"x")){edge.x-=minX}if(_.has(edge,"y")){edge.y-=minY}});graphLabel.width=maxX-minX+marginX;graphLabel.height=maxY-minY+marginY}function assignNodeIntersects(g){_.forEach(g.edges(),function(e){var edge=g.edge(e);var nodeV=g.node(e.v);var nodeW=g.node(e.w);var 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){_.forEach(g.edges(),function(e){var edge=g.edge(e);if(_.has(edge,"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){_.forEach(g.edges(),function(e){var edge=g.edge(e);if(edge.reversed){edge.points.reverse()}})}function removeBorderNodes(g){_.forEach(g.nodes(),function(v){if(g.children(v).length){var node=g.node(v);var t=g.node(node.borderTop);var b=g.node(node.borderBottom);var l=g.node(_.last(node.borderLeft));var r=g.node(_.last(node.borderRight));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}});_.forEach(g.nodes(),function(v){if(g.node(v).dummy==="border"){g.removeNode(v)}})}function removeSelfEdges(g){_.forEach(g.edges(),function(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);_.forEach(layers,function(layer){var orderShift=0;_.forEach(layer,function(v,i){var node=g.node(v);node.order=i+orderShift;_.forEach(node.selfEdges,function(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){_.forEach(g.nodes(),function(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 _.mapValues(_.pick(obj,attrs),Number)}function canonicalize(attrs){var newAttrs={};_.forEach(attrs,function(v,k){newAttrs[k.toLowerCase()]=v});return newAttrs}},{"./acyclic":2,"./add-border-segments":3,"./coordinate-system":4,"./graphlib":7,"./lodash":10,"./nesting-graph":11,"./normalize":12,"./order":17,"./parent-dummy-chains":22,"./position":24,"./rank":26,"./util":29}],10:[function(require,module,exports){
/* global window */
var lodash;if(typeof require==="function"){try{lodash={cloneDeep:require("lodash/cloneDeep"),constant:require("lodash/constant"),defaults:require("lodash/defaults"),each:require("lodash/each"),filter:require("lodash/filter"),find:require("lodash/find"),flatten:require("lodash/flatten"),forEach:require("lodash/forEach"),forIn:require("lodash/forIn"),has:require("lodash/has"),isUndefined:require("lodash/isUndefined"),last:require("lodash/last"),map:require("lodash/map"),mapValues:require("lodash/mapValues"),max:require("lodash/max"),merge:require("lodash/merge"),min:require("lodash/min"),minBy:require("lodash/minBy"),now:require("lodash/now"),pick:require("lodash/pick"),range:require("lodash/range"),reduce:require("lodash/reduce"),sortBy:require("lodash/sortBy"),uniqueId:require("lodash/uniqueId"),values:require("lodash/values"),zipObject:require("lodash/zipObject")}}catch(e){
// continue regardless of error
}}if(!lodash){lodash=window._}module.exports=lodash},{"lodash/cloneDeep":undefined,"lodash/constant":undefined,"lodash/defaults":undefined,"lodash/each":undefined,"lodash/filter":undefined,"lodash/find":undefined,"lodash/flatten":undefined,"lodash/forEach":undefined,"lodash/forIn":undefined,"lodash/has":undefined,"lodash/isUndefined":undefined,"lodash/last":undefined,"lodash/map":undefined,"lodash/mapValues":undefined,"lodash/max":undefined,"lodash/merge":undefined,"lodash/min":undefined,"lodash/minBy":undefined,"lodash/now":undefined,"lodash/pick":undefined,"lodash/range":undefined,"lodash/reduce":undefined,"lodash/sortBy":undefined,"lodash/uniqueId":undefined,"lodash/values":undefined,"lodash/zipObject":undefined}],11:[function(require,module,exports){var _=require("./lodash");var 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 boundries, 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){var root=util.addDummyNode(g,"root",{},"_root");var depths=treeDepths(g);var height=_.max(_.values(depths))-1;// Note: depths is an Object not an array
var nodeSep=2*height+1;g.graph().nestingRoot=root;
// Multiply minlen by nodeSep to align nodes on non-border ranks.
_.forEach(g.edges(),function(e){g.edge(e).minlen*=nodeSep});
// Calculate a weight that is sufficient to keep subgraphs vertically compact
var weight=sumWeights(g)+1;
// Create border nodes and link them up
_.forEach(g.children(),function(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){var children=g.children(v);if(!children.length){if(v!==root){g.setEdge(root,v,{weight:0,minlen:nodeSep})}return}var top=util.addBorderNode(g,"_bt");var bottom=util.addBorderNode(g,"_bb");var label=g.node(v);g.setParent(top,v);label.borderTop=top;g.setParent(bottom,v);label.borderBottom=bottom;_.forEach(children,function(child){dfs(g,root,nodeSep,weight,height,depths,child);var childNode=g.node(child);var childTop=childNode.borderTop?childNode.borderTop:child;var childBottom=childNode.borderBottom?childNode.borderBottom:child;var thisWeight=childNode.borderTop?weight:2*weight;var 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){_.forEach(children,function(child){dfs(child,depth+1)})}depths[v]=depth}_.forEach(g.children(),function(v){dfs(v,1)});return depths}function sumWeights(g){return _.reduce(g.edges(),function(acc,e){return acc+g.edge(e).weight},0)}function cleanup(g){var graphLabel=g.graph();g.removeNode(graphLabel.nestingRoot);delete graphLabel.nestingRoot;_.forEach(g.edges(),function(e){var edge=g.edge(e);if(edge.nestingEdge){g.removeEdge(e)}})}},{"./lodash":10,"./util":29}],12:[function(require,module,exports){"use strict";var _=require("./lodash");var 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=[];_.forEach(g.edges(),function(edge){normalizeEdge(g,edge)})}function normalizeEdge(g,e){var v=e.v;var vRank=g.node(v).rank;var w=e.w;var wRank=g.node(w).rank;var name=e.name;var edgeLabel=g.edge(e);var labelRank=edgeLabel.labelRank;if(wRank===vRank+1)return;g.removeEdge(e);var dummy,attrs,i;for(i=0,++vRank;vRank<wRank;++i,++vRank){edgeLabel.points=[];attrs={width:0,height:0,edgeLabel:edgeLabel,edgeObj:e,rank:vRank};dummy=util.addDummyNode(g,"edge",attrs,"_d");if(vRank===labelRank){attrs.width=edgeLabel.width;attrs.height=edgeLabel.height;attrs.dummy="edge-label";attrs.labelpos=edgeLabel.labelpos}g.setEdge(v,dummy,{weight:edgeLabel.weight},name);if(i===0){g.graph().dummyChains.push(dummy)}v=dummy}g.setEdge(v,w,{weight:edgeLabel.weight},name)}function undo(g){_.forEach(g.graph().dummyChains,function(v){var node=g.node(v);var origLabel=node.edgeLabel;var 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)}})}},{"./lodash":10,"./util":29}],13:[function(require,module,exports){var _=require("../lodash");module.exports=addSubgraphConstraints;function addSubgraphConstraints(g,cg,vs){var prev={},rootPrev;_.forEach(vs,function(v){var 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 = [];
      _.each(children, function(child) {
        var childMin = dfs(child);
        if (g.children(child).length) {
          subgraphs.push({ v: child, order: childMin });
        }
        min = Math.min(min, childMin);
      });
      _.reduce(_.sortBy(subgraphs, "order"), function(prev, curr) {
        cg.setEdge(prev.v, curr.v);
        return curr;
      });
      return min;
    }
    return g.node(v).order;
  }
  dfs(undefined);
  */}},{"../lodash":10}],14:[function(require,module,exports){var _=require("../lodash");module.exports=barycenter;function barycenter(g,movable){return _.map(movable,function(v){var inV=g.inEdges(v);if(!inV.length){return{v:v}}else{var result=_.reduce(inV,function(acc,e){var 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}}})}},{"../lodash":10}],15:[function(require,module,exports){var _=require("../lodash");var Graph=require("../graphlib").Graph;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){var root=createRootNode(g),result=new Graph({compound:true}).setGraph({root:root}).setDefaultNodeLabel(function(v){return g.node(v)});_.forEach(g.nodes(),function(v){var 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!
_.forEach(g[relationship](v),function(e){var u=e.v===v?e.w:e.v,edge=result.edge(u,v),weight=!_.isUndefined(edge)?edge.weight:0;result.setEdge(u,v,{weight:g.edge(e).weight+weight})});if(_.has(node,"minRank")){result.setNode(v,{borderLeft:node.borderLeft[rank],borderRight:node.borderRight[rank]})}}});return result}function createRootNode(g){var v;while(g.hasNode(v=_.uniqueId("_root")));return v}},{"../graphlib":7,"../lodash":10}],16:[function(require,module,exports){"use strict";var _=require("../lodash");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){var cc=0;for(var i=1;i<layering.length;++i){cc+=twoLayerCrossCount(g,layering[i-1],layering[i])}return cc}function twoLayerCrossCount(g,northLayer,southLayer){
// Sort all of the edges between the north and south layers by their position
// in the north layer and then the south. Map these edges to the position of
// their head in the south layer.
var southPos=_.zipObject(southLayer,_.map(southLayer,function(v,i){return i}));var southEntries=_.flatten(_.map(northLayer,function(v){return _.sortBy(_.map(g.outEdges(v),function(e){return{pos:southPos[e.w],weight:g.edge(e).weight}}),"pos")}),true);
// Build the accumulator tree
var firstIndex=1;while(firstIndex<southLayer.length)firstIndex<<=1;var treeSize=2*firstIndex-1;firstIndex-=1;var tree=_.map(new Array(treeSize),function(){return 0});
// Calculate the weighted crossings
var cc=0;_.forEach(southEntries.forEach(function(entry){var index=entry.pos+firstIndex;tree[index]+=entry.weight;var 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}},{"../lodash":10}],17:[function(require,module,exports){"use strict";var _=require("../lodash");var initOrder=require("./init-order");var crossCount=require("./cross-count");var sortSubgraph=require("./sort-subgraph");var buildLayerGraph=require("./build-layer-graph");var addSubgraphConstraints=require("./add-subgraph-constraints");var Graph=require("../graphlib").Graph;var 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){var maxRank=util.maxRank(g),downLayerGraphs=buildLayerGraphs(g,_.range(1,maxRank+1),"inEdges"),upLayerGraphs=buildLayerGraphs(g,_.range(maxRank-1,-1,-1),"outEdges");var layering=initOrder(g);assignOrder(g,layering);var bestCC=Number.POSITIVE_INFINITY,best;for(var i=0,lastBest=0;lastBest<4;++i,++lastBest){sweepLayerGraphs(i%2?downLayerGraphs:upLayerGraphs,i%4>=2);layering=util.buildLayerMatrix(g);var cc=crossCount(g,layering);if(cc<bestCC){lastBest=0;best=_.cloneDeep(layering);bestCC=cc}}assignOrder(g,best)}function buildLayerGraphs(g,ranks,relationship){return _.map(ranks,function(rank){return buildLayerGraph(g,rank,relationship)})}function sweepLayerGraphs(layerGraphs,biasRight){var cg=new Graph;_.forEach(layerGraphs,function(lg){var root=lg.graph().root;var sorted=sortSubgraph(lg,root,cg,biasRight);_.forEach(sorted.vs,function(v,i){lg.node(v).order=i});addSubgraphConstraints(lg,cg,sorted.vs)})}function assignOrder(g,layering){_.forEach(layering,function(layer){_.forEach(layer,function(v,i){g.node(v).order=i})})}},{"../graphlib":7,"../lodash":10,"../util":29,"./add-subgraph-constraints":13,"./build-layer-graph":15,"./cross-count":16,"./init-order":18,"./sort-subgraph":20}],18:[function(require,module,exports){"use strict";var _=require("../lodash");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){var visited={};var simpleNodes=_.filter(g.nodes(),function(v){return!g.children(v).length});var maxRank=_.max(_.map(simpleNodes,function(v){return g.node(v).rank}));var layers=_.map(_.range(maxRank+1),function(){return[]});function dfs(v){if(_.has(visited,v))return;visited[v]=true;var node=g.node(v);layers[node.rank].push(v);_.forEach(g.successors(v),dfs)}var orderedVs=_.sortBy(simpleNodes,function(v){return g.node(v).rank});_.forEach(orderedVs,dfs);return layers}},{"../lodash":10}],19:[function(require,module,exports){"use strict";var _=require("../lodash");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){var mappedEntries={};_.forEach(entries,function(entry,i){var tmp=mappedEntries[entry.v]={indegree:0,in:[],out:[],vs:[entry.v],i:i};if(!_.isUndefined(entry.barycenter)){tmp.barycenter=entry.barycenter;tmp.weight=entry.weight}});_.forEach(cg.edges(),function(e){var entryV=mappedEntries[e.v];var entryW=mappedEntries[e.w];if(!_.isUndefined(entryV)&&!_.isUndefined(entryW)){entryW.indegree++;entryV.out.push(mappedEntries[e.w])}});var sourceSet=_.filter(mappedEntries,function(entry){return!entry.indegree});return doResolveConflicts(sourceSet)}function doResolveConflicts(sourceSet){var entries=[];function handleIn(vEntry){return function(uEntry){if(uEntry.merged){return}if(_.isUndefined(uEntry.barycenter)||_.isUndefined(vEntry.barycenter)||uEntry.barycenter>=vEntry.barycenter){mergeEntries(vEntry,uEntry)}}}function handleOut(vEntry){return function(wEntry){wEntry["in"].push(vEntry);if(--wEntry.indegree===0){sourceSet.push(wEntry)}}}while(sourceSet.length){var entry=sourceSet.pop();entries.push(entry);_.forEach(entry["in"].reverse(),handleIn(entry));_.forEach(entry.out,handleOut(entry))}return _.map(_.filter(entries,function(entry){return!entry.merged}),function(entry){return _.pick(entry,["vs","i","barycenter","weight"])})}function mergeEntries(target,source){var sum=0;var 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}},{"../lodash":10}],20:[function(require,module,exports){var _=require("../lodash");var barycenter=require("./barycenter");var resolveConflicts=require("./resolve-conflicts");var sort=require("./sort");module.exports=sortSubgraph;function sortSubgraph(g,v,cg,biasRight){var movable=g.children(v);var node=g.node(v);var bl=node?node.borderLeft:undefined;var br=node?node.borderRight:undefined;var subgraphs={};if(bl){movable=_.filter(movable,function(w){return w!==bl&&w!==br})}var barycenters=barycenter(g,movable);_.forEach(barycenters,function(entry){if(g.children(entry.v).length){var subgraphResult=sortSubgraph(g,entry.v,cg,biasRight);subgraphs[entry.v]=subgraphResult;if(_.has(subgraphResult,"barycenter")){mergeBarycenters(entry,subgraphResult)}}});var entries=resolveConflicts(barycenters,cg);expandSubgraphs(entries,subgraphs);var result=sort(entries,biasRight);if(bl){result.vs=_.flatten([bl,result.vs,br],true);if(g.predecessors(bl).length){var blPred=g.node(g.predecessors(bl)[0]),brPred=g.node(g.predecessors(br)[0]);if(!_.has(result,"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){_.forEach(entries,function(entry){entry.vs=_.flatten(entry.vs.map(function(v){if(subgraphs[v]){return subgraphs[v].vs}return v}),true)})}function mergeBarycenters(target,other){if(!_.isUndefined(target.barycenter)){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}}},{"../lodash":10,"./barycenter":14,"./resolve-conflicts":19,"./sort":21}],21:[function(require,module,exports){var _=require("../lodash");var util=require("../util");module.exports=sort;function sort(entries,biasRight){var parts=util.partition(entries,function(entry){return _.has(entry,"barycenter")});var sortable=parts.lhs,unsortable=_.sortBy(parts.rhs,function(entry){return-entry.i}),vs=[],sum=0,weight=0,vsIndex=0;sortable.sort(compareWithBias(!!biasRight));vsIndex=consumeUnsortable(vs,unsortable,vsIndex);_.forEach(sortable,function(entry){vsIndex+=entry.vs.length;vs.push(entry.vs);sum+=entry.barycenter*entry.weight;weight+=entry.weight;vsIndex=consumeUnsortable(vs,unsortable,vsIndex)});var result={vs:_.flatten(vs,true)};if(weight){result.barycenter=sum/weight;result.weight=weight}return result}function consumeUnsortable(vs,unsortable,index){var last;while(unsortable.length&&(last=_.last(unsortable)).i<=index){unsortable.pop();vs.push(last.vs);index++}return index}function compareWithBias(bias){return function(entryV,entryW){if(entryV.barycenter<entryW.barycenter){return-1}else if(entryV.barycenter>entryW.barycenter){return 1}return!bias?entryV.i-entryW.i:entryW.i-entryV.i}}},{"../lodash":10,"../util":29}],22:[function(require,module,exports){var _=require("./lodash");module.exports=parentDummyChains;function parentDummyChains(g){var postorderNums=postorder(g);_.forEach(g.graph().dummyChains,function(v){var node=g.node(v);var edgeObj=node.edgeObj;var pathData=findPath(g,postorderNums,edgeObj.v,edgeObj.w);var path=pathData.path;var lca=pathData.lca;var pathIdx=0;var pathV=path[pathIdx];var ascending=true;while(v!==edgeObj.w){node=g.node(v);if(ascending){while((pathV=path[pathIdx])!==lca&&g.node(pathV).maxRank<node.rank){pathIdx++}if(pathV===lca){ascending=false}}if(!ascending){while(pathIdx<path.length-1&&g.node(pathV=path[pathIdx+1]).minRank<=node.rank){pathIdx++}pathV=path[pathIdx]}g.setParent(v,pathV);v=g.successors(v)[0]}})}
// Find a path from v to w through the lowest common ancestor (LCA). Return the
// full path and the LCA.
function findPath(g,postorderNums,v,w){var vPath=[];var wPath=[];var low=Math.min(postorderNums[v].low,postorderNums[w].low);var lim=Math.max(postorderNums[v].lim,postorderNums[w].lim);var parent;var lca;
// Traverse up from v to find the LCA
parent=v;do{parent=g.parent(parent);vPath.push(parent)}while(parent&&(postorderNums[parent].low>low||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){var result={};var lim=0;function dfs(v){var low=lim;_.forEach(g.children(v),dfs);result[v]={low:low,lim:lim++}}_.forEach(g.children(),dfs);return result}},{"./lodash":10}],23:[function(require,module,exports){"use strict";var _=require("../lodash");var Graph=require("../graphlib").Graph;var 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){var conflicts={};function visitLayer(prevLayer,layer){var
// 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=_.last(layer);_.forEach(layer,function(v,i){var w=findOtherInnerSegmentNode(g,v),k1=w?g.node(w).order:prevLayerLength;if(w||v===lastNode){_.forEach(layer.slice(scanPos,i+1),function(scanNode){_.forEach(g.predecessors(scanNode),function(u){var uLabel=g.node(u),uPos=uLabel.order;if((uPos<k0||k1<uPos)&&!(uLabel.dummy&&g.node(scanNode).dummy)){addConflict(conflicts,u,scanNode)}})});scanPos=i+1;k0=k1}});return layer}_.reduce(layering,visitLayer);return conflicts}function findType2Conflicts(g,layering){var conflicts={};function scan(south,southPos,southEnd,prevNorthBorder,nextNorthBorder){var v;_.forEach(_.range(southPos,southEnd),function(i){v=south[i];if(g.node(v).dummy){_.forEach(g.predecessors(v),function(u){var uNode=g.node(u);if(uNode.dummy&&(uNode.order<prevNorthBorder||uNode.order>nextNorthBorder)){addConflict(conflicts,u,v)}})}})}function visitLayer(north,south){var prevNorthPos=-1,nextNorthPos,southPos=0;_.forEach(south,function(v,southLookahead){if(g.node(v).dummy==="border"){var 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}_.reduce(layering,visitLayer);return conflicts}function findOtherInnerSegmentNode(g,v){if(g.node(v).dummy){return _.find(g.predecessors(v),function(u){return g.node(u).dummy})}}function addConflict(conflicts,v,w){if(v>w){var tmp=v;v=w;w=tmp}var conflictsV=conflicts[v];if(!conflictsV){conflicts[v]=conflictsV={}}conflictsV[w]=true}function hasConflict(conflicts,v,w){if(v>w){var tmp=v;v=w;w=tmp}return _.has(conflicts[v],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){var 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.
_.forEach(layering,function(layer){_.forEach(layer,function(v,order){root[v]=v;align[v]=v;pos[v]=order})});_.forEach(layering,function(layer){var prevIdx=-1;_.forEach(layer,function(v){var ws=neighborFn(v);if(ws.length){ws=_.sortBy(ws,function(w){return pos[w]});var mp=(ws.length-1)/2;for(var i=Math.floor(mp),il=Math.ceil(mp);i<=il;++i){var w=ws[i];if(align[v]===v&&prevIdx<pos[w]&&!hasConflict(conflicts,v,w)){align[w]=v;align[v]=root[v]=root[w];prevIdx=pos[w]}}}})});return{root:root,align:align}}function horizontalCompaction(g,layering,root,align,reverseSep){
// This portion of the algorithm differs from BK due to a number of problems.
// Instead of their algorithm we construct a new block graph and do two
// sweeps. The first sweep places blocks with the smallest possible
// coordinates. The second sweep removes unused space by moving blocks to the
// greatest coordinates without violating separation.
var xs={},blockG=buildBlockGraph(g,layering,root,reverseSep),borderType=reverseSep?"borderLeft":"borderRight";function iterate(setXsFunc,nextNodesFunc){var stack=blockG.nodes();var elem=stack.pop();var visited={};while(elem){if(visited[elem]){setXsFunc(elem)}else{visited[elem]=true;stack.push(elem);stack=stack.concat(nextNodesFunc(elem))}elem=stack.pop()}}
// First pass, assign smallest coordinates
function pass1(elem){xs[elem]=blockG.inEdges(elem).reduce(function(acc,e){return Math.max(acc,xs[e.v]+blockG.edge(e))},0)}
// Second pass, assign greatest coordinates
function pass2(elem){var min=blockG.outEdges(elem).reduce(function(acc,e){return Math.min(acc,xs[e.w]-blockG.edge(e))},Number.POSITIVE_INFINITY);var 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
_.forEach(align,function(v){xs[v]=xs[root[v]]});return xs}function buildBlockGraph(g,layering,root,reverseSep){var blockGraph=new Graph,graphLabel=g.graph(),sepFn=sep(graphLabel.nodesep,graphLabel.edgesep,reverseSep);_.forEach(layering,function(layer){var u;_.forEach(layer,function(v){var 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 _.minBy(_.values(xss),function(xs){var max=Number.NEGATIVE_INFINITY;var min=Number.POSITIVE_INFINITY;_.forIn(xs,function(x,v){var halfWidth=width(g,v)/2;max=Math.max(x+halfWidth,max);min=Math.min(x-halfWidth,min)});return max-min})}
/*
 * Align the coordinates of each of the layout alignments such that
 * left-biased alignments have their minimum coordinate at the same point as
 * the minimum coordinate of the smallest width alignment and right-biased
 * alignments have their maximum coordinate at the same point as the maximum
 * coordinate of the smallest width alignment.
 */function alignCoordinates(xss,alignTo){var alignToVals=_.values(alignTo),alignToMin=_.min(alignToVals),alignToMax=_.max(alignToVals);_.forEach(["u","d"],function(vert){_.forEach(["l","r"],function(horiz){var alignment=vert+horiz,xs=xss[alignment],delta;if(xs===alignTo)return;var xsVals=_.values(xs);delta=horiz==="l"?alignToMin-_.min(xsVals):alignToMax-_.max(xsVals);if(delta){xss[alignment]=_.mapValues(xs,function(x){return x+delta})}})})}function balance(xss,align){return _.mapValues(xss.ul,function(ignore,v){if(align){return xss[align.toLowerCase()][v]}else{var xs=_.sortBy(_.map(xss,v));return(xs[1]+xs[2])/2}})}function positionX(g){var layering=util.buildLayerMatrix(g);var conflicts=_.merge(findType1Conflicts(g,layering),findType2Conflicts(g,layering));var xss={};var adjustedLayering;_.forEach(["u","d"],function(vert){adjustedLayering=vert==="u"?layering:_.values(layering).reverse();_.forEach(["l","r"],function(horiz){if(horiz==="r"){adjustedLayering=_.map(adjustedLayering,function(inner){return _.values(inner).reverse()})}var neighborFn=(vert==="u"?g.predecessors:g.successors).bind(g);var align=verticalAlignment(g,adjustedLayering,conflicts,neighborFn);var xs=horizontalCompaction(g,adjustedLayering,align.root,align.align,horiz==="r");if(horiz==="r"){xs=_.mapValues(xs,function(x){return-x})}xss[vert+horiz]=xs})});var smallestWidth=findSmallestWidthAlignment(g,xss);alignCoordinates(xss,smallestWidth);return balance(xss,g.graph().align)}function sep(nodeSep,edgeSep,reverseSep){return function(g,v,w){var vLabel=g.node(v);var wLabel=g.node(w);var sum=0;var delta;sum+=vLabel.width/2;if(_.has(vLabel,"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(_.has(wLabel,"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}},{"../graphlib":7,"../lodash":10,"../util":29}],24:[function(require,module,exports){"use strict";var _=require("../lodash");var util=require("../util");var positionX=require("./bk").positionX;module.exports=position;function position(g){g=util.asNonCompoundGraph(g);positionY(g);_.forEach(positionX(g),function(x,v){g.node(v).x=x})}function positionY(g){var layering=util.buildLayerMatrix(g);var rankSep=g.graph().ranksep;var prevY=0;_.forEach(layering,function(layer){var maxHeight=_.max(_.map(layer,function(v){return g.node(v).height}));_.forEach(layer,function(v){g.node(v).y=prevY+maxHeight/2});prevY+=maxHeight+rankSep})}},{"../lodash":10,"../util":29,"./bk":23}],25:[function(require,module,exports){"use strict";var _=require("../lodash");var Graph=require("../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)<size){edge=findMinSlackEdge(t,g);delta=t.hasNode(edge.v)?slack(g,edge):-slack(g,edge);shiftRanks(t,g,delta)}return t}
/*
 * Finds a maximal tree of tight edges and returns the number of nodes in the
 * tree.
 */function tightTree(t,g){function dfs(v){_.forEach(g.nodeEdges(v),function(e){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)}})}_.forEach(t.nodes(),dfs);return t.nodeCount()}
/*
 * Finds the edge with the smallest slack that is incident on tree and returns
 * it.
 */function findMinSlackEdge(t,g){return _.minBy(g.edges(),function(e){if(t.hasNode(e.v)!==t.hasNode(e.w)){return slack(g,e)}})}function shiftRanks(t,g,delta){_.forEach(t.nodes(),function(v){g.node(v).rank+=delta})}},{"../graphlib":7,"../lodash":10,"./util":28}],26:[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":25,"./network-simplex":27,"./util":28}],27:[function(require,module,exports){"use strict";var _=require("../lodash");var feasibleTree=require("./feasible-tree");var slack=require("./util").slack;var initRank=require("./util").longestPath;var preorder=require("../graphlib").alg.preorder;var postorder=require("../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);_.forEach(vs,function(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;_.forEach(g.nodeEdges(child),function(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;_.forEach(tree.neighbors(v),function(w){if(!_.has(visited,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 _.find(tree.edges(),function(e){return 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=_.filter(g.edges(),function(edge){return flip===isDescendant(t,t.node(edge.v),tailLabel)&&flip!==isDescendant(t,t.node(edge.w),tailLabel)});return _.minBy(candidates,function(edge){return slack(g,edge)})}function exchangeEdges(t,g,e,f){var v=e.v;var w=e.w;t.removeEdge(v,w);t.setEdge(f.v,f.w,{});initLowLimValues(t);initCutValues(t,g);updateRanks(t,g)}function updateRanks(t,g){var root=_.find(t.nodes(),function(v){return!g.node(v).parent});var vs=preorder(t,root);vs=vs.slice(1);_.forEach(vs,function(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}},{"../graphlib":7,"../lodash":10,"../util":29,"./feasible-tree":25,"./util":28}],28:[function(require,module,exports){"use strict";var _=require("../lodash");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(_.has(visited,v)){return label.rank}visited[v]=true;var rank=_.min(_.map(g.outEdges(v),function(e){return dfs(e.w)-g.edge(e).minlen}));if(rank===Number.POSITIVE_INFINITY||// return value of _.map([]) for Lodash 3
rank===undefined||// return value of _.map([]) for Lodash 4
rank===null){// return value of _.map([null])
rank=0}return label.rank=rank}_.forEach(g.sources(),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}},{"../lodash":10}],29:[function(require,module,exports){
/* eslint "no-console": off */
"use strict";var _=require("./lodash");var Graph=require("./graphlib").Graph;module.exports={addDummyNode:addDummyNode,simplify:simplify,asNonCompoundGraph:asNonCompoundGraph,successorWeights:successorWeights,predecessorWeights:predecessorWeights,intersectRect:intersectRect,buildLayerMatrix:buildLayerMatrix,normalizeRanks:normalizeRanks,removeEmptyRanks:removeEmptyRanks,addBorderNode:addBorderNode,maxRank:maxRank,partition:partition,time:time,notime:notime};
/*
 * Adds a dummy node to the graph and return v.
 */function addDummyNode(g,type,attrs,name){var 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){var simplified=(new Graph).setGraph(g.graph());_.forEach(g.nodes(),function(v){simplified.setNode(v,g.node(v))});_.forEach(g.edges(),function(e){var simpleLabel=simplified.edge(e.v,e.w)||{weight:0,minlen:1};var 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){var simplified=new Graph({multigraph:g.isMultigraph()}).setGraph(g.graph());_.forEach(g.nodes(),function(v){if(!g.children(v).length){simplified.setNode(v,g.node(v))}});_.forEach(g.edges(),function(e){simplified.setEdge(e,g.edge(e))});return simplified}function successorWeights(g){var weightMap=_.map(g.nodes(),function(v){var sucs={};_.forEach(g.outEdges(v),function(e){sucs[e.w]=(sucs[e.w]||0)+g.edge(e).weight});return sucs});return _.zipObject(g.nodes(),weightMap)}function predecessorWeights(g){var weightMap=_.map(g.nodes(),function(v){var preds={};_.forEach(g.inEdges(v),function(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){var x=rect.x;var y=rect.y;
// Rectangle intersection algorithm from:
// http://math.stackexchange.com/questions/108113/find-edge-between-two-boxes
var dx=point.x-x;var dy=point.y-y;var w=rect.width/2;var h=rect.height/2;if(!dx&&!dy){throw new Error("Not possible to find intersection inside of the rectangle")}var 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){var layering=_.map(_.range(maxRank(g)+1),function(){return[]});_.forEach(g.nodes(),function(v){var node=g.node(v);var rank=node.rank;if(!_.isUndefined(rank)){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){var min=_.min(_.map(g.nodes(),function(v){return g.node(v).rank}));_.forEach(g.nodes(),function(v){var node=g.node(v);if(_.has(node,"rank")){node.rank-=min}})}function removeEmptyRanks(g){
// Ranks may not start at 0, so we need to offset them
var offset=_.min(_.map(g.nodes(),function(v){return g.node(v).rank}));var layers=[];_.forEach(g.nodes(),function(v){var rank=g.node(v).rank-offset;if(!layers[rank]){layers[rank]=[]}layers[rank].push(v)});var delta=0;var nodeRankFactor=g.graph().nodeRankFactor;_.forEach(layers,function(vs,i){if(_.isUndefined(vs)&&i%nodeRankFactor!==0){--delta}else if(delta){_.forEach(vs,function(v){g.node(v).rank+=delta})}})}function addBorderNode(g,prefix,rank,order){var 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 _.max(_.map(g.nodes(),function(v){var rank=g.node(v).rank;if(!_.isUndefined(rank)){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){var result={lhs:[],rhs:[]};_.forEach(collection,function(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){var start=_.now();try{return fn()}finally{console.log(name+" time: "+(_.now()-start)+"ms")}}function notime(name,fn){return fn()}},{"./graphlib":7,"./lodash":10}],30:[function(require,module,exports){module.exports="0.8.5"},{}]},{},[1])(1)});
