int
main(int argc, char **argv)
{
ESL_RANDOMNESS *r; /* source of random numbers */
ESL_HISTOGRAM *h; /* histogram to store the data */
ESL_HYPEREXP *hxp; /* hyperexponential to sample from */
ESL_HYPEREXP *ehxp; /* estimated hyperexponential */
double x; /* sampled data point */
int n = 100000; /* number of samples */
double *data;
int ndata;
int i;
hxp = esl_hyperexp_Create(3);
hxp->mu = -2.0;
hxp->q[0] = 0.6; hxp->q[1] = 0.3; hxp->q[2] = 0.1;
hxp->lambda[0] = 1.0; hxp->lambda[1] = 0.3; hxp->lambda[2] = 0.1;
r = esl_randomness_Create(0);
h = esl_histogram_CreateFull(hxp->mu, 100, 1.0);
for (i = 0; i < n; i++)
{
x = esl_hxp_Sample(r, hxp);
esl_histogram_Add(h, x);
}
esl_histogram_GetData(h, &data, &ndata);
/* Plot the empirical (sampled) and expected survivals */
esl_histogram_PlotSurvival(stdout, h);
esl_hxp_Plot(stdout, hxp, &esl_hxp_surv, h->xmin, h->xmax, 0.1);
/* ML fit to complete data, and plot fitted survival curve */
ehxp = esl_hyperexp_Create(3);
esl_hxp_FitGuess(data, ndata, ehxp);
esl_hxp_FitComplete(data, ndata, ehxp);
esl_hxp_Plot(stdout, ehxp, &esl_hxp_surv, h->xmin, h->xmax, 0.1);
/* ML fit to binned data, plot fitted survival curve */
esl_hxp_FitGuessBinned(h, ehxp);
esl_hxp_FitCompleteBinned(h, ehxp);
esl_hxp_Plot(stdout, ehxp, &esl_hxp_surv, h->xmin, h->xmax, 0.1);
esl_randomness_Destroy(r);
esl_histogram_Destroy(h);
esl_hyperexp_Destroy(hxp);
esl_hyperexp_Destroy(ehxp);
return 0;
}
int
main(int argc, char **argv)
{
double mu = -50.0;
double lambda = 2.5;
double tau = 0.7;
ESL_HISTOGRAM *h = esl_histogram_CreateFull(mu, 100., 0.1);
ESL_RANDOMNESS *r = esl_randomness_Create(0);
int n = 10000;
double *data;
int ndata;
double emu, elam, etau;
int i;
double x;
for (i = 0; i < n; i++)
{
x = esl_sxp_Sample(r, mu, lambda, tau);
esl_histogram_Add(h, x);
}
esl_histogram_GetData(h, &data, &ndata);
/* Plot the empirical (sampled) and expected survivals */
esl_histogram_PlotSurvival(stdout, h);
esl_sxp_Plot(stdout, mu, lambda, tau,
&esl_sxp_surv, h->xmin, h->xmax, 0.1);
/* ML fit to complete data, and plot fitted survival curve */
esl_sxp_FitComplete(data, ndata, &emu, &elam, &etau);
esl_sxp_Plot(stdout, emu, elam, etau,
&esl_sxp_surv, h->xmin, h->xmax, 0.1);
/* ML fit to binned data, plot fitted survival curve */
esl_sxp_FitCompleteBinned(h, &emu, &elam, &etau);
esl_sxp_Plot(stdout, emu, elam, etau,
&esl_sxp_surv, h->xmin, h->xmax, 0.1);
esl_randomness_Destroy(r);
esl_histogram_Destroy(h);
return 0;
}
int
main(int argc, char **argv)
{
ESL_HISTOGRAM *h;
ESL_RANDOMNESS *r;
ESL_HYPEREXP *hxp;
ESL_HYPEREXP *ehxp;
int n = 20000;
double binwidth = 0.1;
int i;
double x;
double *data;
int ndata;
int k, ek, mink;
double mindiff, diff;
int opti;
int be_verbose = FALSE;
char *paramfile = NULL;
char *plotfile = NULL;
FILE *pfp = stdout;
int plot_pdf = FALSE;
int plot_logpdf = FALSE;
int plot_cdf = FALSE;
int plot_logcdf = FALSE;
int plot_surv = FALSE;
int plot_logsurv = FALSE;
int xmin_set = FALSE;
double xmin;
int xmax_set = FALSE;
double xmax;
int xstep_set = FALSE;
double xstep;
int do_fixmix = FALSE;
int status;
for (opti = 1; opti < argc && *(argv[opti]) == '-'; opti++)
{
if (strcmp(argv[opti], "-f") == 0) do_fixmix = TRUE;
else if (strcmp(argv[opti], "-i") == 0) paramfile = argv[++opti];
else if (strcmp(argv[opti], "-n") == 0) n = atoi(argv[++opti]);
else if (strcmp(argv[opti], "-o") == 0) plotfile = argv[++opti];
else if (strcmp(argv[opti], "-v") == 0) be_verbose = TRUE;
else if (strcmp(argv[opti], "-w") == 0) binwidth = atof(argv[++opti]);
else if (strcmp(argv[opti], "-C") == 0) plot_cdf = TRUE;
else if (strcmp(argv[opti], "-LC") == 0) plot_logcdf = TRUE;
else if (strcmp(argv[opti], "-P") == 0) plot_pdf = TRUE;
else if (strcmp(argv[opti], "-LP") == 0) plot_logpdf = TRUE;
else if (strcmp(argv[opti], "-S") == 0) plot_surv = TRUE;
else if (strcmp(argv[opti], "-LS") == 0) plot_logsurv = TRUE;
else if (strcmp(argv[opti], "-XL") == 0) { xmin_set = TRUE; xmin = atof(argv[++opti]); }
else if (strcmp(argv[opti], "-XH") == 0) { xmax_set = TRUE; xmax = atof(argv[++opti]); }
else if (strcmp(argv[opti], "-XS") == 0) { xstep_set = TRUE; xstep = atof(argv[++opti]); }
else esl_fatal("bad option");
}
if (paramfile != NULL)
{
status = esl_hyperexp_ReadFile(paramfile, &hxp);
if (status == eslENOTFOUND) esl_fatal("Param file %s not found", paramfile);
else if (status == eslEFORMAT) esl_fatal("Parse failed: param file %s invalid format", paramfile);
else if (status != eslOK) esl_fatal("Unusual failure opening param file %s", paramfile);
}
else
{
hxp = esl_hyperexp_Create(3);
hxp->mu = -2.0;
hxp->q[0] = 0.5; hxp->q[1] = 0.3; hxp->q[2] = 0.2;
hxp->lambda[0] = 1.0; hxp->lambda[1] = 0.3; hxp->lambda[2] = 0.1;
}
if (do_fixmix) esl_hyperexp_FixedUniformMixture(hxp); /* overrides q's above */
if (be_verbose) esl_hyperexp_Dump(stdout, hxp);
r = esl_randomness_Create(42);
h = esl_histogram_CreateFull(hxp->mu, 100., binwidth);
if (plotfile != NULL) {
if ((pfp = fopen(plotfile, "w")) == NULL)
esl_fatal("Failed to open plotfile");
}
if (! xmin_set) xmin = hxp->mu;
if (! xmax_set) xmax = hxp->mu+ 20*(1. / esl_vec_DMin(hxp->lambda, hxp->K));
if (! xstep_set) xstep = 0.1;
for (i = 0; i < n; i++)
{
x = esl_hxp_Sample(r, hxp);
esl_histogram_Add(h, x);
}
esl_histogram_GetData(h, &data, &ndata); /* get sorted data vector */
ehxp = esl_hyperexp_Create(hxp->K);
if (do_fixmix) esl_hyperexp_FixedUniformMixture(ehxp);
esl_hxp_FitGuess(data, ndata, ehxp);
if ( esl_hxp_FitComplete(data, ndata, ehxp) != eslOK) esl_fatal("Failed to fit hyperexponential");
if (be_verbose) esl_hyperexp_Dump(stdout, ehxp);
if (fabs( (ehxp->mu-hxp->mu)/hxp->mu ) > 0.01)
esl_fatal("Error in (complete) fitted mu > 1%\n");
for (ek = 0; ek < ehxp->K; ek++)
{ /* try to match each estimated lambda up to a parametric lambda */
mindiff = 1.0;
mink = -1;
for (k = 0; k < hxp->K; k++)
{
diff = fabs( (ehxp->lambda[ek] - hxp->lambda[k]) / hxp->lambda[k]);
if (diff < mindiff) {
mindiff = diff;
mink = k;
}
}
if (mindiff > 0.50)
esl_fatal("Error in (complete) fitted lambda > 50%\n");
if (fabs( (ehxp->q[ek] - hxp->q[mink]) / hxp->q[mink]) > 1.0)
esl_fatal("Error in (complete) fitted q > 2-fold%\n");
}
esl_hxp_FitGuessBinned(h, ehxp);
if ( esl_hxp_FitCompleteBinned(h, ehxp) != eslOK) esl_fatal("Failed to fit binned hyperexponential");
if (be_verbose) esl_hyperexp_Dump(stdout, ehxp);
if (fabs( (ehxp->mu-hxp->mu)/hxp->mu ) > 0.01)
esl_fatal("Error in (binned) fitted mu > 1%\n");
for (ek = 0; ek < ehxp->K; ek++)
{ /* try to match each estimated lambda up to a parametric lambda */
mindiff = 1.0;
mink = -1;
for (k = 0; k < hxp->K; k++)
{
diff = fabs( (ehxp->lambda[ek] - hxp->lambda[k]) / hxp->lambda[k]);
if (diff < mindiff) {
mindiff = diff;
mink = k;
}
}
if (mindiff > 0.50)
esl_fatal("Error in (binned) fitted lambda > 50%\n");
if (fabs( (ehxp->q[ek] - hxp->q[mink]) / hxp->q[mink]) > 1.0)
esl_fatal("Error in (binned) fitted q > 2-fold\n");
}
if (plot_pdf) esl_hxp_Plot(pfp, hxp, &esl_hxp_pdf, xmin, xmax, xstep);
if (plot_logpdf) esl_hxp_Plot(pfp, hxp, &esl_hxp_logpdf, xmin, xmax, xstep);
if (plot_cdf) esl_hxp_Plot(pfp, hxp, &esl_hxp_cdf, xmin, xmax, xstep);
if (plot_logcdf) esl_hxp_Plot(pfp, hxp, &esl_hxp_logcdf, xmin, xmax, xstep);
if (plot_surv) esl_hxp_Plot(pfp, hxp, &esl_hxp_surv, xmin, xmax, xstep);
if (plot_logsurv) esl_hxp_Plot(pfp, hxp, &esl_hxp_logsurv, xmin, xmax, xstep);
if (plotfile != NULL) fclose(pfp);
esl_histogram_Destroy(h);
esl_hyperexp_Destroy(hxp);
esl_hyperexp_Destroy(ehxp);
esl_randomness_Destroy(r);
return 0;
}
int
main(int argc, char **argv)
{
ESL_HISTOGRAM *h;
ESL_RANDOMNESS *r;
double mu = -5.0;
double lambda = 2.0;
double tau = 0.7;
int n = 10000;
double binwidth = 0.1;
double elambda, etau;
int i;
double x;
double *data;
int ndata;
int opti;
int be_verbose = FALSE;
char *plotfile = NULL;
FILE *pfp = stdout;
int plot_pdf = FALSE;
int plot_logpdf = FALSE;
int plot_cdf = FALSE;
int plot_logcdf = FALSE;
int plot_surv = FALSE;
int plot_logsurv = FALSE;
int xmin_set = FALSE;
double xmin;
int xmax_set = FALSE;
double xmax;
int xstep_set = FALSE;
double xstep;
for (opti = 1; opti < argc && *(argv[opti]) == '-'; opti++)
{
if (strcmp(argv[opti], "-m") == 0) mu = atof(argv[++opti]);
else if (strcmp(argv[opti], "-l") == 0) lambda = atof(argv[++opti]);
else if (strcmp(argv[opti], "-n") == 0) n = atoi(argv[++opti]);
else if (strcmp(argv[opti], "-o") == 0) plotfile = argv[++opti];
else if (strcmp(argv[opti], "-t") == 0) tau = atof(argv[++opti]);
else if (strcmp(argv[opti], "-v") == 0) be_verbose = TRUE;
else if (strcmp(argv[opti], "-w") == 0) binwidth = atof(argv[++opti]);
else if (strcmp(argv[opti], "-C") == 0) plot_cdf = TRUE;
else if (strcmp(argv[opti], "-LC") == 0) plot_logcdf = TRUE;
else if (strcmp(argv[opti], "-P") == 0) plot_pdf = TRUE;
else if (strcmp(argv[opti], "-LP") == 0) plot_logpdf = TRUE;
else if (strcmp(argv[opti], "-S") == 0) plot_surv = TRUE;
else if (strcmp(argv[opti], "-LS") == 0) plot_logsurv = TRUE;
else if (strcmp(argv[opti], "-XL") == 0) { xmin_set = TRUE; xmin = atof(argv[++opti]); }
else if (strcmp(argv[opti], "-XH") == 0) { xmax_set = TRUE; xmax = atof(argv[++opti]); }
else if (strcmp(argv[opti], "-XS") == 0) { xstep_set = TRUE; xstep = atof(argv[++opti]); }
else ESL_EXCEPTION(eslEINVAL, "bad option");
}
if (be_verbose)
printf("Parametric: mu = %f lambda = %f tau = %f\n", mu, lambda, tau);
r = esl_randomness_Create(0);
h = esl_histogram_CreateFull(mu, 100., binwidth);
if (plotfile != NULL) {
if ((pfp = fopen(plotfile, "w")) == NULL)
ESL_EXCEPTION(eslFAIL, "Failed to open plotfile");
}
if (! xmin_set) xmin = mu;
if (! xmax_set) xmax = mu+40*(1./lambda);
if (! xstep_set) xstep = 0.1;
for (i = 0; i < n; i++)
{
x = esl_gam_Sample(r, mu, lambda, tau);
esl_histogram_Add(h, x);
}
esl_histogram_GetData(h, &data, &ndata);
esl_gam_FitComplete(data, ndata, mu, &elambda, &etau);
if (be_verbose)
printf("Complete data fit: mu = %f lambda = %f tau = %f\n",
mu, elambda, etau);
if (fabs( (elambda-lambda)/lambda ) > 0.10)
ESL_EXCEPTION(eslFAIL, "Error in (complete) fitted lambda > 10%\n");
if (fabs( (etau-tau)/tau ) > 0.10)
ESL_EXCEPTION(eslFAIL, "Error in (complete) fitted tau > 10%\n");
if (plot_pdf) esl_gam_Plot(pfp, mu, lambda, tau, &esl_gam_pdf, xmin, xmax, xstep);
if (plot_logpdf) esl_gam_Plot(pfp, mu, lambda, tau, &esl_gam_logpdf, xmin, xmax, xstep);
if (plot_cdf) esl_gam_Plot(pfp, mu, lambda, tau, &esl_gam_cdf, xmin, xmax, xstep);
if (plot_logcdf) esl_gam_Plot(pfp, mu, lambda, tau, &esl_gam_logcdf, xmin, xmax, xstep);
if (plot_surv) esl_gam_Plot(pfp, mu, lambda, tau, &esl_gam_surv, xmin, xmax, xstep);
if (plot_logsurv) esl_gam_Plot(pfp, mu, lambda, tau, &esl_gam_logsurv, xmin, xmax, xstep);
if (plotfile != NULL) fclose(pfp);
esl_randomness_Destroy(r);
esl_histogram_Destroy(h);
return 0;
}
int
main(int argc, char **argv)
{
ESL_GETOPTS *go = esl_getopts_CreateDefaultApp(options, 0, argc, argv, banner, usage);
double mu = esl_opt_GetReal(go, "-m");
double lambda = esl_opt_GetReal(go, "-l");
double tau = esl_opt_GetReal(go, "-t");
ESL_RANDOMNESS *r = esl_randomness_Create(esl_opt_GetInteger(go, "-s"));
ESL_HISTOGRAM *h = esl_histogram_CreateFull(mu, 100., esl_opt_GetReal(go, "-w"));;
int n = esl_opt_GetInteger(go, "-n");
int be_verbose = esl_opt_GetBoolean(go, "-v");
char *plotfile = esl_opt_GetString(go, "-o");
FILE *pfp = stdout;
int plot_pdf = esl_opt_GetBoolean(go, "--P");
int plot_logpdf = esl_opt_GetBoolean(go, "--LP");
int plot_cdf = esl_opt_GetBoolean(go, "--C");
int plot_logcdf = esl_opt_GetBoolean(go, "--LC");
int plot_surv = esl_opt_GetBoolean(go, "--S");
int plot_logsurv = esl_opt_GetBoolean(go, "--LS");
double xmin = esl_opt_IsOn(go, "--XL") ? esl_opt_GetReal(go, "--XL") : mu;
double xmax = esl_opt_IsOn(go, "--XH") ? esl_opt_GetReal(go, "--XH") : mu+40*(1./lambda);
double xstep = esl_opt_IsOn(go, "--XS") ? esl_opt_GetReal(go, "--XS") : 0.1;
double emu, elambda, etau;
int i;
double x;
double *data;
int ndata;
if (be_verbose)
printf("Parametric: mu = %f lambda = %f tau = %f\n", mu, lambda, tau);
if (plotfile != NULL) {
if ((pfp = fopen(plotfile, "w")) == NULL)
esl_fatal("Failed to open plotfile");
}
for (i = 0; i < n; i++)
{
x = esl_sxp_Sample(r, mu, lambda, tau);
esl_histogram_Add(h, x);
}
esl_histogram_GetData(h, &data, &ndata);
esl_sxp_FitComplete(data, ndata, &emu, &elambda, &etau);
if (be_verbose)
printf("Complete data fit: mu = %f lambda = %f tau = %f\n",
emu, elambda, etau);
if (fabs( (emu-mu)/mu ) > 0.01) esl_fatal("Error in (complete) fitted mu > 1%\n");
if (fabs( (elambda-lambda)/lambda ) > 0.10) esl_fatal("Error in (complete) fitted lambda > 10%\n");
if (fabs( (etau-tau)/tau ) > 0.10) esl_fatal("Error in (complete) fitted tau > 10%\n");
esl_sxp_FitCompleteBinned(h, &emu, &elambda, &etau);
if (be_verbose)
printf("Binned data fit: mu = %f lambda = %f tau = %f\n",
emu, elambda, etau);
if (fabs( (emu-mu)/mu ) > 0.01) esl_fatal("Error in (binned) fitted mu > 1%\n");
if (fabs( (elambda-lambda)/lambda ) > 0.10) esl_fatal("Error in (binned) fitted lambda > 10%\n");
if (fabs( (etau-tau)/tau ) > 0.10) esl_fatal("Error in (binned) fitted tau > 10%\n");
if (plot_pdf) esl_sxp_Plot(pfp, mu, lambda, tau, &esl_sxp_pdf, xmin, xmax, xstep);
if (plot_logpdf) esl_sxp_Plot(pfp, mu, lambda, tau, &esl_sxp_logpdf, xmin, xmax, xstep);
if (plot_cdf) esl_sxp_Plot(pfp, mu, lambda, tau, &esl_sxp_cdf, xmin, xmax, xstep);
if (plot_logcdf) esl_sxp_Plot(pfp, mu, lambda, tau, &esl_sxp_logcdf, xmin, xmax, xstep);
if (plot_surv) esl_sxp_Plot(pfp, mu, lambda, tau, &esl_sxp_surv, xmin, xmax, xstep);
if (plot_logsurv) esl_sxp_Plot(pfp, mu, lambda, tau, &esl_sxp_logsurv, xmin, xmax, xstep);
if (plotfile != NULL) fclose(pfp);
esl_histogram_Destroy(h);
esl_randomness_Destroy(r);
esl_getopts_Destroy(go);
return 0;
}
int
main(int argc, char **argv)
{
ESL_GETOPTS *go = esl_getopts_CreateDefaultApp(options, 0, argc, argv, banner, usage);
ESL_RANDOMNESS *rng = esl_randomness_Create(esl_opt_GetInteger(go, "-s"));
double mu = esl_opt_GetReal (go, "-m");
double lambda = esl_opt_GetReal (go, "-l");
double tau = esl_opt_GetReal (go, "-t");
int n = esl_opt_GetInteger(go, "-n");
double binwidth = esl_opt_GetReal (go, "-w");
int plot_cdf = esl_opt_GetBoolean(go, "--cdf");
int plot_logcdf = esl_opt_GetBoolean(go, "--logcdf");
int plot_pdf = esl_opt_GetBoolean(go, "--pdf");
int plot_logpdf = esl_opt_GetBoolean(go, "--logpdf");
int plot_surv = esl_opt_GetBoolean(go, "--surv");
int plot_logsurv = esl_opt_GetBoolean(go, "--logsurv");
int be_verbose = esl_opt_GetBoolean(go, "-v");
char *plotfile = esl_opt_GetString (go, "-o");
ESL_HISTOGRAM *h = NULL;
int xmin_set = esl_opt_IsOn(go, "--xL");
double xmin = xmin_set ? esl_opt_GetReal(go, "--xL") : mu;
int xmax_set = esl_opt_IsOn(go, "--xH");
double xmax = xmax_set ? esl_opt_GetReal(go, "--xH") : mu+40*(1./lambda);
int xstep_set = esl_opt_IsOn(go, "--xH");
double xstep = xstep_set ? esl_opt_GetReal(go, "--xS") : 0.1;
FILE *pfp = stdout;
double emu, elambda, etau;
int i;
double x;
double *data;
int ndata;
fprintf(stderr, "## %s\n", argv[0]);
fprintf(stderr, "# rng seed = %" PRIu32 "\n", esl_randomness_GetSeed(rng));
if (be_verbose) printf("Parametric: mu = %f lambda = %f tau = %f\n", mu, lambda, tau);
h = esl_histogram_CreateFull(mu, 100., binwidth);
if (plotfile && (pfp = fopen(plotfile, "w")) == NULL) ESL_EXCEPTION(eslFAIL, "Failed to open plotfile");
for (i = 0; i < n; i++)
{
x = esl_wei_Sample(rng, mu, lambda, tau);
esl_histogram_Add(h, x);
}
esl_histogram_GetData(h, &data, &ndata);
esl_wei_FitComplete(data, ndata, &emu, &elambda, &etau);
if (be_verbose) printf("Complete data fit: mu = %f lambda = %f tau = %f\n", emu, elambda, etau);
if (fabs( (emu-mu)/mu ) > 0.01) ESL_EXCEPTION(eslFAIL, "Error in (complete) fitted mu > 1%\n");
if (fabs( (elambda-lambda)/lambda ) > 0.10) ESL_EXCEPTION(eslFAIL, "Error in (complete) fitted lambda > 10%\n");
if (fabs( (etau-tau)/tau ) > 0.10) ESL_EXCEPTION(eslFAIL, "Error in (complete) fitted tau > 10%\n");
esl_wei_FitCompleteBinned(h, &emu, &elambda, &etau);
if (be_verbose) printf("Binned data fit: mu = %f lambda = %f tau = %f\n", emu, elambda, etau);
if (fabs( (emu-mu)/mu ) > 0.01) ESL_EXCEPTION(eslFAIL, "Error in (binned) fitted mu > 1%\n");
if (fabs( (elambda-lambda)/lambda ) > 0.10) ESL_EXCEPTION(eslFAIL, "Error in (binned) fitted lambda > 10%\n");
if (fabs( (etau-tau)/tau ) > 0.10) ESL_EXCEPTION(eslFAIL, "Error in (binned) fitted lambda > 10%\n");
if (plot_pdf) esl_wei_Plot(pfp, mu, lambda, tau, &esl_wei_pdf, xmin, xmax, xstep);
if (plot_logpdf) esl_wei_Plot(pfp, mu, lambda, tau, &esl_wei_logpdf, xmin, xmax, xstep);
if (plot_cdf) esl_wei_Plot(pfp, mu, lambda, tau, &esl_wei_cdf, xmin, xmax, xstep);
if (plot_logcdf) esl_wei_Plot(pfp, mu, lambda, tau, &esl_wei_logcdf, xmin, xmax, xstep);
if (plot_surv) esl_wei_Plot(pfp, mu, lambda, tau, &esl_wei_surv, xmin, xmax, xstep);
if (plot_logsurv) esl_wei_Plot(pfp, mu, lambda, tau, &esl_wei_logsurv, xmin, xmax, xstep);
if (plotfile) fclose(pfp);
esl_histogram_Destroy(h);
esl_randomness_Destroy(rng);
esl_getopts_Destroy(go);
fprintf(stderr, "# status = ok\n");
return 0;
}
