constrained_majorization_ipsep.c

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/**********************************************************
 * Based on constrained_majorization.c
 *
 * Perform stress majorization subject
 * to separation constraints, for background see the paper:
 * "IPSep-CoLa: An Incremental Procedure for Separation Constraint Layout of Graphs"
 * by Tim Dwyer, Yehuda Koren and Kim Marriott
 *
 * Available separation constraints so far are:
 *  o Directed edge constraints
 *  o Node non-overlap constraints
 *  o Cluster containment constraints
 *  o Cluster/node non-overlap constraints
 *
 * Tim Dwyer, 2006
 **********************************************************/
 
#include "config.h"
 
#include <assert.h>
#include <limits.h>
#include <neatogen/digcola.h>
#include <stdbool.h>
#include <util/alloc.h>
#ifdef IPSEPCOLA
#include <math.h>
#include <stdlib.h>
#include <time.h>
#include <stdio.h>
#include <float.h>
#include <neatogen/stress.h>
#include <neatogen/dijkstra.h>
#include <neatogen/bfs.h>
#include <neatogen/matrix_ops.h>
#include <neatogen/kkutils.h>
#include <neatogen/conjgrad.h>
#include <vpsc/csolve_VPSC.h>
#include <neatogen/quad_prog_vpsc.h>
#include <neatogen/quad_prog_solver.h>
#include <neatogen/matrix_ops.h>
 
#define localConstrMajorIterations 1000
 
int stress_majorization_cola(vtx_data * graph,  /* Input graph in sparse representation  */
                             int n,     /* Number of nodes */
                             double **d_coords, /* Coordinates of nodes (output layout)  */
                             node_t ** nodes,   /* Original nodes */
                             int dim,   /* Dimensionality of layout */
                             int model, /* difference model */
                             int maxi,  /* max iterations */
                             ipsep_options * opt)
{
    int iterations = 0;         /* Output: number of iteration of the process */
 
        /*************************************************
        ** Computation of full, dense, unrestricted k-D ** 
        ** stress minimization by majorization          ** 
        ** This function imposes HIERARCHY CONSTRAINTS  **
        *************************************************/
 
    int k;
    float *lap1 = NULL;
    float *dist_accumulator = NULL;
    float *tmp_coords = NULL;
    float **b = NULL;
    double *degrees = NULL;
    float *lap2 = NULL;
    int lap_length;
    float *f_storage = NULL;
    float **coords = NULL;
    int orig_n = n;
 
    CMajEnvVPSC *cMajEnvHor = NULL;
    CMajEnvVPSC *cMajEnvVrt = NULL;
    double y_0;
    int length;
    DistType diameter;
    float *Dij = NULL;
    float constant_term;
    int count;
    double degree;
    int step;
    float val;
    double old_stress, new_stress = 0;
    bool converged;
    int len;
    double nsizeScale = 0;
    float maxEdgeLen = 0;
    double max = 1;
 
    initLayout(n, dim, d_coords, nodes);
    if (n == 1)
        return 0;
 
    for (int i = 0; i < n; i++) {
        for (size_t j = 1; j < graph[i].nedges; j++) {
            maxEdgeLen = MAX(graph[i].ewgts[j], maxEdgeLen);
        }
    }
 
        /****************************************************
        ** Compute the all-pairs-shortest-distances matrix **
        ****************************************************/
 
    if (maxi == 0)
        return iterations;
 
    if (Verbose)
        start_timer();
 
    if (model == MODEL_SUBSET) {
        /* weight graph to separate high-degree nodes */
        /* and perform slower Dijkstra-based computation */
        if (Verbose)
            fprintf(stderr, "Calculating subset model");
        Dij = compute_apsp_artificial_weights_packed(graph, n);
    } else if (model == MODEL_CIRCUIT) {
        Dij = circuitModel(graph, n);
        if (!Dij) {
            agwarningf(
                  "graph is disconnected. Hence, the circuit model\n");
            agerr(AGPREV,
                  "is undefined. Reverting to the shortest path model.\n");
        }
    } else if (model == MODEL_MDS) {
        if (Verbose)
            fprintf(stderr, "Calculating MDS model");
        Dij = mdsModel(graph, n);
    }
    if (!Dij) {
        if (Verbose)
            fprintf(stderr, "Calculating shortest paths");
        Dij = compute_apsp_packed(graph, n);
    }
    if (Verbose) {
        fprintf(stderr, ": %.2f sec\n", elapsed_sec());
        fprintf(stderr, "Setting initial positions");
        start_timer();
    }
 
    diameter = -1;
    length = n + n * (n - 1) / 2;
    for (int i = 0; i < length; i++) {
        if (Dij[i] > diameter) {
            diameter = (int) Dij[i];
        }
    }
 
    /* for numerical stability, scale down layout                */
    /* No Jiggling, might conflict with constraints                      */
    for (int i = 0; i < dim; i++) {
        for (int j = 0; j < n; j++) {
            max = fmax(max, fabs(d_coords[i][j]));
        }
    }
    for (int i = 0; i < dim; i++) {
        for (int j = 0; j < n; j++) {
            d_coords[i][j] *= 10 / max;
        }
    }
 
        /**************************
        ** Layout initialization **
        **************************/
 
    for (int i = 0; i < dim; i++) {
        orthog1(n, d_coords[i]);
    }
 
    /* for the y-coords, don't center them, but translate them so y[0]=0 */
    y_0 = d_coords[1][0];
    for (int i = 0; i < n; i++) {
        d_coords[1][i] -= y_0;
    }
    if (Verbose)
        fprintf(stderr, ": %.2f sec", elapsed_sec());
 
        /**************************
        ** Laplacian computation **
        **************************/
 
    lap2 = Dij;
    lap_length = n + n * (n - 1) / 2;
    square_vec(lap_length, lap2);
    /* compute off-diagonal entries */
    invert_vec(lap_length, lap2);
 
    if (opt->clusters.nclusters > 0) {
        const size_t nn = n + opt->clusters.nclusters * 2;
        const size_t clap_length = nn + nn * (nn - 1) / 2;
        float *clap = gv_calloc(clap_length, sizeof(float));
        int c0, c1;
        float v;
        c0 = c1 = 0;
        for (size_t i = 0; i < nn; i++) {
            for (int j = 0; j < nn - i; j++) {
                if (i < n && j < n - i) {
                    v = lap2[c0++];
                } else {
                    /* v=j==1?i%2:0; */
                    if (j == 1 && i % 2 == 1) {
                        v = maxEdgeLen;
                        v *= v;
                        if (v > 0.01f) {
                            v = 1.0f / v;
                        }
                    } else
                        v = 0;
                }
                clap[c1++] = v;
            }
        }
        free(lap2);
        lap2 = clap;
        assert(nn <= INT_MAX);
        n = (int)nn;
        assert(clap_length <= INT_MAX);
        lap_length = (int)clap_length;
    }
    /* compute diagonal entries */
    count = 0;
    degrees = gv_calloc(n, sizeof(double));
    set_vector_val(n, 0, degrees);
    for (int i = 0; i < n - 1; i++) {
        degree = 0;
        count++;                /* skip main diag entry */
        for (int j = 1; j < n - i; j++, count++) {
            val = lap2[count];
            degree += val;
            degrees[i + j] -= val;
        }
        degrees[i] -= degree;
    }
    int i;
    for (step = n, count = 0, i = 0; i < n; i++, count += step, step--) {
        lap2[count] = (float) degrees[i];
    }
 
    coords = gv_calloc(dim, sizeof(float *));
    f_storage = gv_calloc(dim * n, sizeof(float));
    for (i = 0; i < dim; i++) {
        coords[i] = f_storage + i * n;
        for (int j = 0; j < n; j++) {
            coords[i][j] = j < orig_n ? (float)d_coords[i][j] : 0;
        }
    }
 
    /* compute constant term in stress sum
     * which is \sum_{i<j} w_{ij}d_{ij}^2
     */
    constant_term = (float) (n * (n - 1) / 2);
 
        /*************************
        ** Layout optimization  **
        *************************/
 
    b = gv_calloc(dim, sizeof(float *));
    b[0] = gv_calloc(dim * n, sizeof(float));
    for (k = 1; k < dim; k++) {
        b[k] = b[0] + k * n;
    }
 
    tmp_coords = gv_calloc(n, sizeof(float));
    dist_accumulator = gv_calloc(n, sizeof(float));
 
    old_stress = DBL_MAX;       /* at least one iteration */
 
    if ((cMajEnvHor = initCMajVPSC(n, lap2, graph, opt, 0)) == NULL) {
        iterations = -1;
        goto finish;
    }
    if ((cMajEnvVrt = initCMajVPSC(n, lap2, graph, opt, opt->diredges)) == NULL) {
        iterations = -1;
        goto finish;
    }
 
    lap1 = gv_calloc(lap_length, sizeof(float));
 
    for (converged = false, iterations = 0;
         iterations < maxi && !converged; iterations++) {
 
        /* First, construct Laplacian of 1/(d_ij*|p_i-p_j|)  */
        set_vector_val(n, 0, degrees);
        sqrt_vecf(lap_length, lap2, lap1);
        for (count = 0, i = 0; i < n - 1; i++) {
            len = n - i - 1;
            /* init 'dist_accumulator' with zeros */
            set_vector_valf(n, 0, dist_accumulator);
 
            /* put into 'dist_accumulator' all squared distances 
             * between 'i' and 'i'+1,...,'n'-1
             */
            for (k = 0; k < dim; k++) {
                set_vector_valf(len, coords[k][i], tmp_coords);
                vectors_mult_additionf(len, tmp_coords, -1, coords[k] + i + 1);
                square_vec(len, tmp_coords);
                vectors_additionf(len, tmp_coords, dist_accumulator, dist_accumulator);
            }
 
            /* convert to 1/d_{ij} */
            invert_sqrt_vec(len, dist_accumulator);
            /* detect overflows */
            for (int j = 0; j < len; j++) {
                if (dist_accumulator[j] >= FLT_MAX || dist_accumulator[j] < 0) {
                    dist_accumulator[j] = 0;
                }
            }
 
            count++;            /* save place for the main diagonal entry */
            degree = 0;
            for (int j = 0; j < len; j++, count++) {
                val = lap1[count] *= dist_accumulator[j];
                degree += val;
                degrees[i + j + 1] -= val;
            }
            degrees[i] -= degree;
        }
        for (step = n, count = 0, i = 0; i < n; i++, count += step, step--) {
            lap1[count] = (float) degrees[i];
        }
 
        /* Now compute b[] (L^(X(t))*X(t)) */
        for (k = 0; k < dim; k++) {
            /* b[k] := lap1*coords[k] */
            right_mult_with_vector_ff(lap1, n, coords[k], b[k]);
        }
 
        /* compute new stress
         * remember that the Laplacians are negated, so we subtract 
         * instead of add and vice versa
         */
        new_stress = 0;
        for (k = 0; k < dim; k++) {
            new_stress += vectors_inner_productf(n, coords[k], b[k]);
        }
        new_stress *= 2;
        new_stress += constant_term;    /* only after mult by 2 */
        for (k = 0; k < dim; k++) {
            right_mult_with_vector_ff(lap2, n, coords[k], tmp_coords);
            new_stress -= vectors_inner_productf(n, coords[k], tmp_coords);
        }
 
        /* check for convergence */
        if (Verbose && (iterations % 1 == 0)) {
            fprintf(stderr, "%.3f ", new_stress);
            if (iterations % 10 == 0)
                fprintf(stderr, "\n");
        }
        converged = new_stress < old_stress
            && fabs(new_stress - old_stress) / fabs(old_stress + 1e-10) <
            Epsilon;
        /*converged = converged || (iterations>1 && new_stress>old_stress); */
        /* in first iteration we allowed stress increase, which 
         * might result ny imposing constraints
         */
        old_stress = new_stress;
 
        /* in determining non-overlap constraints we gradually scale up the
         * size of nodes to avoid local minima
         */
        if ((iterations >= maxi - 1 || converged) && opt->noverlap == 1
            && nsizeScale < 0.999) {
            nsizeScale += 0.1;
            if (Verbose)
                fprintf(stderr, "nsizescale=%f,iterations=%d\n",
                        nsizeScale, iterations);
            iterations = 0;
            converged = false;
        }
 
 
        /* now we find the optimizer of trace(X'LX)+X'B by solving 'dim' 
         * system of equations, thereby obtaining the new coordinates.
         * If we use the constraints (given by the var's: 'ordering', 
         * 'levels' and 'num_levels'), we cannot optimize 
         * trace(X'LX)+X'B by simply solving equations, but we have
         * to use a quadratic programming solver
         * note: 'lap2' is a packed symmetric matrix, that is its 
         * upper-triangular part is arranged in a vector row-wise
         * also note: 'lap2' is really the negated laplacian (the 
         * laplacian is -'lap2')
         */
 
        if (opt->noverlap == 1 && nsizeScale > 0.001) {
            generateNonoverlapConstraints(cMajEnvHor, nsizeScale, coords,
                                          0,
                                          nsizeScale >= 0.5,
                                          opt);
        }
        if (cMajEnvHor->m > 0) {
                constrained_majorization_vpsc(cMajEnvHor, b[0], coords[0],
                                              localConstrMajorIterations);
        } else {
            /* if there are no constraints then use conjugate gradient
             * optimisation which should be considerably faster
             */
            if (conjugate_gradient_mkernel(lap2, coords[0], b[0], n,
                                       tolerance_cg, n) < 0) {
                iterations = -1;
                goto finish;
            }
        }
        if (opt->noverlap == 1 && nsizeScale > 0.001) {
            generateNonoverlapConstraints(cMajEnvVrt, nsizeScale, coords,
                                          1, false, opt);
        }
        if (cMajEnvVrt->m > 0) {
                if (constrained_majorization_vpsc(cMajEnvVrt, b[1], coords[1],
                                              localConstrMajorIterations) < 0) {
                iterations = -1;
                goto finish;
            }
        } else {
            conjugate_gradient_mkernel(lap2, coords[1], b[1], n,
                                       tolerance_cg, n);
        }
    }
    if (Verbose) {
        fprintf(stderr, "\nfinal e = %f %d iterations %.2f sec\n",
                new_stress, iterations, elapsed_sec());
    }
    deleteCMajEnvVPSC(cMajEnvHor);
    deleteCMajEnvVPSC(cMajEnvVrt);
 
    if (opt->noverlap == 2) {
        /* fprintf(stderr, "Removing overlaps as post-process...\n"); */
        removeoverlaps(orig_n, coords, opt);
    }
 
finish:
    if (coords != NULL) {
        for (i = 0; i < dim; i++) {
            for (int j = 0; j < orig_n; j++) {
                d_coords[i][j] = coords[i][j];
            }
        }
        free(coords[0]);
        free(coords);
    }
 
    if (b) {
        free(b[0]);
        free(b);
    }
    free(tmp_coords);
    free(dist_accumulator);
    free(degrees);
    free(lap2);
    free(lap1);
 
    return iterations;
}
#endif                          /* IPSEPCOLA */