From 12b21e1d27f43deaa748419919b40b80cedd0ddd Mon Sep 17 00:00:00 2001
From: Tim Dwyer <tgdwyer@gmail.com>
Date: Wed, 12 Jul 2006 00:55:58 +0000
Subject: Previously graph layout was done using the Kamada-Kawai layout
 algorithm implemented in Boost.  I am replacing this with a custom
 implementation of a constrained stress-majorization algorithm.

The stress-majorization algorithm is more robust and has better convergence
characteristics than Kamada-Kawai, and also simple constraints can be placed
on node position (for example, to enforce downward-pointing edges, non-overlap constraints, or cluster constraints).

Another big advantage is that we no longer need Boost.

I've tested the basic functionality, but I have yet to properly handle
disconnected graphs or to properly scale the resulting layout.

This commit also includes significant refactoring... the quadratic program solver - libvpsc (Variable Placement with Separation Constraints) has been moved to src/libvpsc and the actual graph layout algorithm is in libcola.

(bzr r1394)
---
 src/libcola/cola.cpp | 299 +++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 299 insertions(+)
 create mode 100644 src/libcola/cola.cpp

(limited to 'src/libcola/cola.cpp')

diff --git a/src/libcola/cola.cpp b/src/libcola/cola.cpp
new file mode 100644
index 000000000..74663f501
--- /dev/null
+++ b/src/libcola/cola.cpp
@@ -0,0 +1,299 @@
+#include "cola.h"
+#include "conjugate_gradient.h"
+#include "straightener.h"
+
+namespace cola {
+
+/**
+ * Find the euclidean distance between a pair of dummy variables
+ */
+inline double dummy_var_euclidean_dist(GradientProjection* gpx, GradientProjection* gpy, unsigned i) {
+    double dx = gpx->dummy_vars[i]->place_r - gpx->dummy_vars[i]->place_l,
+        dy = gpy->dummy_vars[i]->place_r - gpy->dummy_vars[i]->place_l;
+    return sqrt(dx*dx + dy*dy);
+}
+
+void 
+ConstrainedMajorizationLayout
+::setupDummyVars() {
+    if(clusters==NULL) return;
+    double* coords[2]={X,Y};
+    GradientProjection* gp[2]={gpX,gpY};
+    for(unsigned k=0;k<2;k++) {
+        gp[k]->clearDummyVars();
+        if(clusters) {
+            for(Clusters::iterator cit=clusters->begin();
+                    cit!=clusters->end(); ++cit) {
+                Cluster *c = *cit;
+                DummyVarPair* p = new DummyVarPair(edge_length);
+                gp[k]->dummy_vars.push_back(p);
+                double minPos=DBL_MAX, maxPos=-DBL_MAX;
+                for(Cluster::iterator vit=c->begin();
+                        vit!=c->end(); ++vit) {
+                    double pos = coords[k][*vit];
+                    minPos=min(pos,minPos);
+                    maxPos=max(pos,maxPos);
+                    p->leftof.push_back(make_pair(*vit,0)); 
+                    p->rightof.push_back(make_pair(*vit,0)); 
+                }
+                p->place_l = minPos;
+                p->place_r = maxPos;
+            }
+        }
+    }
+    for(unsigned k=0;k<2;k++) {
+        unsigned n_d = gp[k]->dummy_vars.size();
+        if(n_d > 0) {
+            for(unsigned i=0; i<n_d; i++) {
+                gp[k]->dummy_vars[i]->computeLinearTerm(dummy_var_euclidean_dist(gpX, gpY, i));
+            }
+        }
+    }
+}
+void ConstrainedMajorizationLayout::majlayout(
+        double** Dij, GradientProjection* gp, double* coords) 
+{
+    double b[n];
+    fill(b,b+n,0);
+    majlayout(Dij,gp,coords,b);
+}
+void ConstrainedMajorizationLayout::majlayout(
+        double** Dij, GradientProjection* gp, double* coords, double* b) 
+{
+    double L_ij,dist_ij,degree;
+    /* compute the vector b */
+    /* multiply on-the-fly with distance-based laplacian */
+    for (unsigned i = 0; i < n; i++) {
+        degree = 0;
+        if(i<lapSize) {
+            for (unsigned j = 0; j < lapSize; j++) {
+                if (j == i) continue;
+                dist_ij = euclidean_distance(i, j);
+                if (dist_ij > 1e-30 && Dij[i][j] > 1e-30) {	/* skip zero distances */
+                    /* calculate L_ij := w_{ij}*d_{ij}/dist_{ij} */
+                    L_ij = 1.0 / (dist_ij * Dij[i][j]);
+                    degree -= L_ij;
+                    b[i] += L_ij * coords[j];
+                }
+            }
+            b[i] += degree * coords[i];
+        }
+        assert(!isnan(b[i]));
+    }
+    if(constrainedLayout) {
+        setupDummyVars();
+        gp->solve(b);
+    } else {
+        conjugate_gradient(lap2, coords, b, n, tol, n);
+    }
+    moveBoundingBoxes();
+}
+inline double ConstrainedMajorizationLayout
+::compute_stress(double **Dij) {
+    double sum = 0, d, diff;
+    for (unsigned i = 1; i < lapSize; i++) {
+        for (unsigned j = 0; j < i; j++) {
+            d = Dij[i][j];
+            diff = d - euclidean_distance(i,j);
+            sum += diff*diff / (d*d);
+        }
+    }
+    if(clusters!=NULL) {
+        for(unsigned i=0; i<gpX->dummy_vars.size(); i++) {
+            sum += gpX->dummy_vars[i]->stress(dummy_var_euclidean_dist(gpX, gpY, i));
+        }
+    }
+    return sum;
+}
+/*
+void ConstrainedMajorizationLayout
+::addLinearConstraints(LinearConstraints* linearConstraints) {
+    n=lapSize+linearConstraints->size();
+    Q=new double*[n];
+    X=new double[n];
+    Y=new double[n];
+    for(unsigned i = 0; i<n; i++) {
+        X[i]=rs[i]->getCentreX();
+        Y[i]=rs[i]->getCentreY();
+        Q[i]=new double[n];
+        for(unsigned j=0; j<n; j++) {
+            if(i<lapSize&&j<lapSize) {
+                Q[i][j]=lap2[i][j];
+            } else {
+                Q[i][j]=0;
+            }
+        }
+    }
+    for(LinearConstraints::iterator i=linearConstraints->begin();
+           i!= linearConstraints->end();i++) {
+        LinearConstraint* c=*i;
+        Q[c->u][c->u]+=c->w*c->duu;
+        Q[c->u][c->v]+=c->w*c->duv;
+        Q[c->u][c->b]+=c->w*c->dub;
+        Q[c->v][c->u]+=c->w*c->duv;
+        Q[c->v][c->v]+=c->w*c->dvv;
+        Q[c->v][c->b]+=c->w*c->dvb;
+        Q[c->b][c->b]+=c->w*c->dbb;
+        Q[c->b][c->u]+=c->w*c->dub;
+        Q[c->b][c->v]+=c->w*c->dvb;
+    }
+}
+*/
+
+bool ConstrainedMajorizationLayout::run() {
+    /*
+    for(unsigned i=0;i<n;i++) {
+        for(unsigned j=0;j<n;j++) {
+            cout << lap2[i][j] << " ";
+        }
+        cout << endl;
+    }
+    */
+    do {
+        /* Axis-by-axis optimization: */
+        if(straightenEdges) {
+            straighten(*straightenEdges,HORIZONTAL);
+            straighten(*straightenEdges,VERTICAL);
+        } else {
+            majlayout(Dij,gpX,X);
+            majlayout(Dij,gpY,Y);
+        }
+    } while(!done(compute_stress(Dij),X,Y));
+    return true;
+}
+static bool straightenToProjection=true;
+void ConstrainedMajorizationLayout::straighten(vector<straightener::Edge*>& sedges, Dim dim) {
+	vector<straightener::Node*> snodes;
+	for (unsigned i=0;i<lapSize;i++) {
+		snodes.push_back(new straightener::Node(i,boundingBoxes[i]));
+	}
+    SimpleConstraints cs;
+    straightener::generateConstraints(snodes,sedges,cs,dim);
+    n=snodes.size();
+    Q=new double*[n];
+    delete [] X;
+    delete [] Y;
+    X=new double[n];
+    Y=new double[n];
+    for(unsigned i = 0; i<n; i++) {
+        X[i]=snodes[i]->x;
+        Y[i]=snodes[i]->y;
+        Q[i]=new double[n];
+        for(unsigned j=0; j<n; j++) {
+            if(i<lapSize&&j<lapSize) {
+                Q[i][j]=lap2[i][j];
+            } else {
+                Q[i][j]=0;
+            }
+        }
+    }
+    LinearConstraints linearConstraints;
+    for(unsigned i=0;i<sedges.size();i++) {
+        sedges[i]->nodePath(snodes);
+        vector<unsigned>& path=sedges[i]->path;
+        // take u and v as the ends of the line
+        //unsigned u=path[0];
+        //unsigned v=path[path.size()-1];
+        double total_length=0;
+        for(unsigned j=1;j<path.size();j++) {
+            unsigned u=path[j-1], v=path[j];
+            total_length+=euclidean_distance(u,v);
+        }
+        for(unsigned j=1;j<path.size()-1;j++) {
+            // find new u and v for each line segment
+            unsigned u=path[j-1];
+            unsigned b=path[j];
+            unsigned v=path[j+1];
+            double weight=-0.01;
+            double wub=euclidean_distance(u,b)/total_length;
+            double wbv=euclidean_distance(b,v)/total_length;
+            linearConstraints.push_back(new cola::LinearConstraint(u,v,b,weight,wub,wbv,X,Y));
+        }
+    }
+    //cout << "Generated "<<linearConstraints.size()<< " linear constraints"<<endl;
+    assert(snodes.size()==lapSize+linearConstraints.size());
+    double b[n],*coords=dim==HORIZONTAL?X:Y,dist_ub,dist_bv;
+    fill(b,b+n,0);
+    for(LinearConstraints::iterator i=linearConstraints.begin();
+           i!= linearConstraints.end();i++) {
+        LinearConstraint* c=*i;
+        if(straightenToProjection) {
+            Q[c->u][c->u]+=c->w*c->duu;
+            Q[c->u][c->v]+=c->w*c->duv;
+            Q[c->u][c->b]+=c->w*c->dub;
+            Q[c->v][c->u]+=c->w*c->duv;
+            Q[c->v][c->v]+=c->w*c->dvv;
+            Q[c->v][c->b]+=c->w*c->dvb;
+            Q[c->b][c->b]+=c->w*c->dbb;
+            Q[c->b][c->u]+=c->w*c->dub;
+            Q[c->b][c->v]+=c->w*c->dvb;
+        } else {
+            double wub=edge_length*c->frac_ub;
+            double wbv=edge_length*c->frac_bv;
+            dist_ub=euclidean_distance(c->u,c->b)*wub;
+            dist_bv=euclidean_distance(c->b,c->v)*wbv;
+            wub=max(wub,0.00001);
+            wbv=max(wbv,0.00001);
+            dist_ub=max(dist_ub,0.00001);
+            dist_bv=max(dist_bv,0.00001);
+            wub=1/(wub*wub);
+            wbv=1/(wbv*wbv);
+            Q[c->u][c->u]-=wub;
+            Q[c->u][c->b]+=wub;
+            Q[c->v][c->v]-=wbv;
+            Q[c->v][c->b]+=wbv;
+            Q[c->b][c->b]-=wbv+wub;
+            Q[c->b][c->u]+=wub;
+            Q[c->b][c->v]+=wbv;
+
+            b[c->u]+=(coords[c->b]-coords[c->u]) / dist_ub;
+            b[c->v]+=(coords[c->b]-coords[c->v]) / dist_bv;
+            b[c->b]+=coords[c->u] / dist_ub + coords[c->v] / dist_bv
+                   - coords[c->b] / dist_ub - coords[c->b] / dist_bv;
+        }
+    }
+	GradientProjection gp(dim,n,Q,coords,tol,100,
+            (AlignmentConstraints*)NULL,false,(Rectangle**)NULL,(PageBoundaryConstraints*)NULL,&cs);
+    constrainedLayout = true;
+    majlayout(Dij,&gp,coords,b);
+    for(unsigned i=0;i<sedges.size();i++) {
+        sedges[i]->createRouteFromPath(X,Y);
+        sedges[i]->dummyNodes.clear();
+        sedges[i]->path.clear();
+    }
+    for(unsigned i=0;i<cs.size();i++) {
+        delete cs[i];
+    }
+    for(unsigned i=0;i<linearConstraints.size();i++) {
+        delete linearConstraints[i];
+    }
+    for(unsigned i=0;i<snodes.size();i++) {
+        delete snodes[i];
+    }
+    for(unsigned i = 0; i<n; i++) {
+        delete [] Q[i];
+    }
+    delete [] Q;
+    snodes.resize(lapSize);
+}
+
+void ConstrainedMajorizationLayout::setupConstraints(
+        AlignmentConstraints* acsx, AlignmentConstraints* acsy,
+        bool avoidOverlaps, 
+        PageBoundaryConstraints* pbcx, PageBoundaryConstraints* pbcy,
+        SimpleConstraints* scx, SimpleConstraints* scy,
+        Clusters* cs,
+        vector<straightener::Edge*>* straightenEdges) {
+    constrainedLayout = true;
+    this->avoidOverlaps = avoidOverlaps;
+    if(cs) {
+        clusters=cs;
+    }
+	gpX=new GradientProjection(
+            HORIZONTAL,n,Q,X,tol,100,acsx,avoidOverlaps,boundingBoxes,pbcx,scx);
+	gpY=new GradientProjection(
+            VERTICAL,n,Q,Y,tol,100,acsy,avoidOverlaps,boundingBoxes,pbcy,scy);
+    this->straightenEdges = straightenEdges;
+}
+} // namespace cola
+// vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=4:softtabstop=4
-- 
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