GNU Scientific Library – Reference Manual: Nonlinear Least-Squares Large Example

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#### 39.12.4 Large Nonlinear Least Squares Example

The following program illustrates the large nonlinear least squares solvers on a system with significant sparse structure in the Jacobian. The cost function is given by

    \Phi(x) &= 1/2 \sum_{i=1}^{p+1} f_i^2
    f_i &= \sqrt{\alpha} (x_i - 1), 1 \le i \le p
    f_{p+1} &= ||x||^2 - 1/4

with \alpha = 10^{-5}. The residual f_{p+1} imposes a constraint on the p parameters x, to ensure that ||x||^2 \approx {1 \over 4}. The (p+1)-by-p Jacobian for this system is given by

    J(x) = [ \sqrt{alpha} I_p; 2 x^T ]

and the normal equations matrix is given by

    J^T J = [ \alpha I_p + 4 x x^T ]

Finally, the second directional derivative of f for the geodesic acceleration method is given by

    fvv = [ 0; 2 ||v||^2 ]

Since the upper p-by-p block of J is diagonal, this sparse structure should be exploited in the nonlinear solver. For comparison, the following program solves the system for p = 2000 using the dense direct Cholesky solver based on the normal equations matrix J^T J, as well as the iterative Steihaug-Toint solver, based on sparse matrix-vector products J u and J^T u. The program output is shown below.

    Method                    NITER NFEV NJUEV NJTJEV NAEV Init Cost  Final cost cond(J) Final |x|^2 Time (s)
    levenberg-marquardt       25    31   26    26     0    7.1218e+18 1.9555e-02 447.50  2.5044e-01  46.28
    levenberg-marquardt+accel 22    23   45    23     22   7.1218e+18 1.9555e-02 447.64  2.5044e-01  33.92
    dogleg                    37    87   36    36     0    7.1218e+18 1.9555e-02 447.59  2.5044e-01  56.05
    double-dogleg             35    88   34    34     0    7.1218e+18 1.9555e-02 447.62  2.5044e-01  52.65
    2D-subspace               37    88   36    36     0    7.1218e+18 1.9555e-02 447.71  2.5044e-01  59.75
    steihaug-toint            35    88   345   0      0    7.1218e+18 1.9555e-02 inf     2.5044e-01  0.09

The first five rows use methods based on factoring the dense J^T J matrix while the last row uses the iterative Steihaug-Toint method. While the number of Jacobian matrix-vector products (NJUEV) is less for the dense methods, the added time to construct and factor the J^T J matrix (NJTJEV) results in a much larger runtime than the iterative method (see last column).

The program is given below.

    #include <stdlib.h>
    #include <stdio.h>
    #include <sys/time.h>
    #include <gsl/gsl_vector.h>
    #include <gsl/gsl_matrix.h>
    #include <gsl/gsl_blas.h>
    #include <gsl/gsl_multilarge_nlinear.h>
    #include <gsl/gsl_spblas.h>
    #include <gsl/gsl_spmatrix.h>

    /* parameters for functions */
    struct model_params
    {
      double alpha;
      gsl_spmatrix *J;
    };

    /* penalty function */
    int
    penalty_f (const gsl_vector * x, void *params, gsl_vector * f)
    {
      struct model_params *par = (struct model_params *) params;
      const double sqrt_alpha = sqrt(par->alpha);
      const size_t p = x->size;
      size_t i;
      double sum = 0.0;

      for (i = 0; i < p; ++i)
        {
          double xi = gsl_vector_get(x, i);

          gsl_vector_set(f, i, sqrt_alpha*(xi - 1.0));

          sum += xi * xi;
        }

      gsl_vector_set(f, p, sum - 0.25);

      return GSL_SUCCESS;
    }

    int
    penalty_df (CBLAS_TRANSPOSE_t TransJ, const gsl_vector * x,
                const gsl_vector * u, void * params, gsl_vector * v,
                gsl_matrix * JTJ)
    {
      struct model_params *par = (struct model_params *) params;
      const size_t p = x->size;
      size_t j;

      /* store 2*x in last row of J */
      for (j = 0; j < p; ++j)
        {
          double xj = gsl_vector_get(x, j);
          gsl_spmatrix_set(par->J, p, j, 2.0 * xj);
        }

      /* compute v = op(J) u */
      if (v)
        gsl_spblas_dgemv(TransJ, 1.0, par->J, u, 0.0, v);

      if (JTJ)
        {
          gsl_vector_view diag = gsl_matrix_diagonal(JTJ);

          /* compute J^T J = [ alpha*I_p + 4 x x^T ] */
          gsl_matrix_set_zero(JTJ);

          /* store 4 x x^T in lower half of JTJ */
          gsl_blas_dsyr(CblasLower, 4.0, x, JTJ);

          /* add alpha to diag(JTJ) */
          gsl_vector_add_constant(&diag.vector, par->alpha);
        }

      return GSL_SUCCESS;
    }

    int
    penalty_fvv (const gsl_vector * x, const gsl_vector * v,
                 void *params, gsl_vector * fvv)
    {
      const size_t p = x->size;
      double normv = gsl_blas_dnrm2(v);

      gsl_vector_set_zero(fvv);
      gsl_vector_set(fvv, p, 2.0 * normv * normv);

      (void)params; /* avoid unused parameter warning */

      return GSL_SUCCESS;
    }

    void
    solve_system(const gsl_vector *x0, gsl_multilarge_nlinear_fdf *fdf,
                 gsl_multilarge_nlinear_parameters *params)
    {
      const gsl_multilarge_nlinear_type *T = gsl_multilarge_nlinear_trust;
      const size_t max_iter = 200;
      const double xtol = 1.0e-8;
      const double gtol = 1.0e-8;
      const double ftol = 1.0e-8;
      const size_t n = fdf->n;
      const size_t p = fdf->p;
      gsl_multilarge_nlinear_workspace *work =
        gsl_multilarge_nlinear_alloc(T, params, n, p);
      gsl_vector * f = gsl_multilarge_nlinear_residual(work);
      gsl_vector * x = gsl_multilarge_nlinear_position(work);
      int info;
      double chisq0, chisq, rcond, xsq;
      struct timeval tv0, tv1;

      gettimeofday(&tv0, NULL);

      /* initialize solver */
      gsl_multilarge_nlinear_init(x0, fdf, work);

      /* store initial cost */
      gsl_blas_ddot(f, f, &chisq0);

      /* iterate until convergence */
      gsl_multilarge_nlinear_driver(max_iter, xtol, gtol, ftol,
                                    NULL, NULL, &info, work);

      gettimeofday(&tv1, NULL);

      /* store final cost */
      gsl_blas_ddot(f, f, &chisq);

      /* compute final ||x||^2 */
      gsl_blas_ddot(x, x, &xsq);

      /* store cond(J(x)) */
      gsl_multilarge_nlinear_rcond(&rcond, work);

      /* print summary */
      fprintf(stderr, "%-25s %-5zu %-4zu %-5zu %-6zu %-4zu %-10.4e %-10.4e %-7.2f %-11.4e %.2f\n",
              gsl_multilarge_nlinear_trs_name(work),
              gsl_multilarge_nlinear_niter(work),
              fdf->nevalf,
              fdf->nevaldfu,
              fdf->nevaldf2,
              fdf->nevalfvv,
              chisq0,
              chisq,
              1.0 / rcond,
              xsq,
              (tv1.tv_sec - tv0.tv_sec) + 1.0e-6 * (tv1.tv_usec - tv0.tv_usec));

      gsl_multilarge_nlinear_free(work);
    }

    int
    main (void)
    {
      const size_t p = 2000;
      const size_t n = p + 1;
      gsl_vector *f = gsl_vector_alloc(n);
      gsl_vector *x = gsl_vector_alloc(p);

      /* allocate sparse Jacobian matrix with 2*p non-zero elements in triplet format */
      gsl_spmatrix *J = gsl_spmatrix_alloc_nzmax(n, p, 2 * p, GSL_SPMATRIX_TRIPLET);

      gsl_multilarge_nlinear_fdf fdf;
      gsl_multilarge_nlinear_parameters fdf_params =
        gsl_multilarge_nlinear_default_parameters();
      struct model_params params;
      size_t i;

      params.alpha = 1.0e-5;
      params.J = J;

      /* define function to be minimized */
      fdf.f = penalty_f;
      fdf.df = penalty_df;
      fdf.fvv = penalty_fvv;
      fdf.n = n;
      fdf.p = p;
      fdf.params = &params;

      for (i = 0; i < p; ++i)
        {
          /* starting point */
          gsl_vector_set(x, i, i + 1.0);

          /* store sqrt(alpha)*I_p in upper p-by-p block of J */
          gsl_spmatrix_set(J, i, i, sqrt(params.alpha));
        }

      fprintf(stderr, "%-25s %-4s %-4s %-5s %-6s %-4s %-10s %-10s %-7s %-11s %-10s\n",
              "Method", "NITER", "NFEV", "NJUEV", "NJTJEV", "NAEV", "Init Cost",
              "Final cost", "cond(J)", "Final |x|^2", "Time (s)");

      fdf_params.scale = gsl_multilarge_nlinear_scale_levenberg;

      fdf_params.trs = gsl_multilarge_nlinear_trs_lm;
      solve_system(x, &fdf, &fdf_params);

      fdf_params.trs = gsl_multilarge_nlinear_trs_lmaccel;
      solve_system(x, &fdf, &fdf_params);

      fdf_params.trs = gsl_multilarge_nlinear_trs_dogleg;
      solve_system(x, &fdf, &fdf_params);

      fdf_params.trs = gsl_multilarge_nlinear_trs_ddogleg;
      solve_system(x, &fdf, &fdf_params);

      fdf_params.trs = gsl_multilarge_nlinear_trs_subspace2D;
      solve_system(x, &fdf, &fdf_params);

      fdf_params.trs = gsl_multilarge_nlinear_trs_cgst;
      solve_system(x, &fdf, &fdf_params);

      gsl_vector_free(f);
      gsl_vector_free(x);
      gsl_spmatrix_free(J);

      return 0;
    }

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