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cvlr-cluster.c
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cvlr-cluster.c
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/* cvlr-cluster.c -- cluster reads based on methylation patterns */
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
#define MAXLINE 1000
#include "clustering.c"
int main(int argc, char* argv[]){
clock_t begin = clock();
char* splash = malloc(MAXLINE);
sprintf(splash, "cvlr-cluster source code timestamp: %s\n", __TIMESTAMP__);
fprintf(stderr, "%s", splash);
if (argc < 5){
fprintf(stderr,
"usage:%s <matrix-file> ('-' for stdin) <k> <seed> <maxit>\n",
argv[0]);
fprintf(stderr, "<seed> can be -1 for random initialization\n");
exit(EXIT_FAILURE);
}
int k = atoi(argv[2]);
int seed = atoi(argv[3]);
int maxit = atoi(argv[4]);
srand((unsigned int) seed);
FILE* infile = stdin;
if (strcmp(argv[1], "-")){
infile = fopen(argv[1], "r");
if (NULL == infile ){
fprintf(stderr, "could not open %s\n", argv[1]);
exit(EXIT_FAILURE);
}
fprintf(stderr, "reading from %s\n", argv[1]);
} else {
fprintf(stderr, "reading from stdin\n");
}
fprintf(stderr, "K:%d\n", k);
fprintf(stderr, "seed:%d\n", seed);
size_t i,j, n,d;
read_n_d_from_file(infile, &n, &d);
fprintf(stderr, "n:%lu d:%lu\n", n, d);
/* matrix to be clustered */
int32_t* m = malloc(n * d * sizeof(int32_t));
for(i = 0; i < n * d; i++) m[i] = -1;
/* store names of rows and columns */
char** rnames = malloc(n * sizeof(char*));
for(i = 0; i < n; i++) rnames[i] = NULL;
uint32_t* gpos = malloc(d * sizeof(uint32_t));
for(i = 0; i < d; i++) gpos[i] = 0;
read_matrix_from_file(infile, n,d, rnames, gpos, m);
fclose(infile);
// number of parameters
fprintf(stdout, "#@N:%lu\n#@D:%lu\n#@K:%d\n", n, d, k);
uint32_t df = k * d + k - 1;
fprintf(stdout, "#@DF:%d\n", df);
double* mu = calloc(k * d , sizeof(double));
double* gamma = malloc(n * k * sizeof(double));
double* pi = calloc(k , sizeof(double));
double* pop = malloc(k * sizeof(double));
/* counts after final cluster assignment */
uint* clusterpop = calloc(k, sizeof(uint));
size_t* cluster = malloc(n * sizeof(size_t));
for (i = 0; i < n; i++){
cluster[i] = random_cluster(k);
}
size_t* n0 = calloc(k*d, sizeof(size_t));
size_t* n1 = calloc(k*d, sizeof(size_t));
fill_n0_n1(m, cluster, n, d, k, n0, n1);
init_pi(cluster, n, k, pi);
init_mu(n0, n1, k, d, mu);
fprintf(stdout, "#@INITPI:");
for(i = 0; i < (k-1); i++) fprintf(stdout, "%.3lf\t", pi[i]);
fprintf(stdout, "%.3lf\n", pi[k-1]);
fprintf(stdout, "#@GPOS:");
for(i=0; i<d-1; i++){
fprintf(stdout, "%u\t", gpos[i]);
}
fprintf(stdout, "%u\n", gpos[d-1]);
for(i=0; i<k; i++){
fprintf(stdout, "#@INITMU%ld:",i);
for(j=0; j < (d - 1); j++){
fprintf(stdout, "%.3lf\t",mu[i * d + j]);
}
fprintf(stdout, "%.3lf\n",mu[i * d + d - 1]);
}
uint32_t it = 0;
double ll;
/* EM loop */
while (it < maxit){
bernoulli_gamma(pi, m, mu, n, d, k, gamma);
update_mu(m, gamma, n, d, k, mu, pop);
for(i=0;i < k; i++) pi[i] = pop[i] / n;
ll = llbern(m , mu, pi, n, d, k);
it++;
fprintf(stdout,"#@IT:%u\tLL:%.3g\n", it, ll);
}
double bic = ll - ( df / 2 ) * log(n);
double aic = ll - df;
fprintf(stdout,"#@LL:%.3g\tBIC:%.3g\tAIC:%.3g\n", ll, bic, aic);
/* ***************************** */
fprintf(stdout, "#@PI:");
for(i=0; i< (k-1); i++) fprintf(stdout, "%.3lf\t", pi[i]);
fprintf(stdout, "%.3lf\n", pi[k-1]);
for(i=0; i < k; i++){
fprintf(stdout, "#@MU%ld:",i);
for(j=0; j < (d-1); j++){
fprintf(stdout, "%.3lf\t",mu[i*d+j]);
}
fprintf(stdout, "%.3lf\n",mu[i*d+d-1]);
}
for(i=0; i<n; i++){
fprintf(stdout, "%s\t", rnames[i]);
double maxg = -1.0;
for(j=0; j<k;j++){
if (gamma[i*k+j] > maxg) {
maxg = gamma[i*k+j];
cluster[i] = j;
clusterpop[j]+=1;
}
}
fprintf(stdout,"%ld\t", cluster[i]);
for(j=0; j<k-1;j++){
fprintf(stdout, "%.3g\t", gamma[i*k+j]);
}
fprintf(stdout, "%.3g\n", gamma[i*k+k-1]);
}
for(j=0; j < k;j++){
fprintf(stdout,"#@POP%ld=%u\n", j, clusterpop[j]);
}
free(m);
free(mu);
free(pi);
free(rnames);
free(gpos);
free(pop);
free(clusterpop);
clock_t end = clock();
fprintf(stderr, "cvlr-cluster done in %.3gs\n", (double)(end-begin)/CLOCKS_PER_SEC);
exit(EXIT_SUCCESS);
}