/*
* 组合数学中的选与不选例子
*/
int subsum(int n,int a[],int cur,int m,int idx)
{
int i;
#ifdef DEBUG
printf("m:%d,cur:%d,idx:%d,n:%d\n",m,cur,idx,n);
#endif
if(m < 0 || idx > n) // || (m != 0 && cur > m))
return 0;
else if(0 == m) {
for(i = 0;i < idx;i++)
printf("%d ",a[i]);
printf("\n");
return 0;
}
for(i = cur;i < n;i++)
if(i <= m)
break;
if(i != n) {
a[idx] = i;
subsum(n,a,i+1,m-i,idx+1);
}
if(cur <= m)
subsum(n,a,cur+1,m,idx);
return 0;
}
int main(int argc,char *argv[])
{
int a[10],n,m;
n = 10;
m = 11;
printf("n:%d,m:%d\n",n,m);
subsum(n,a,1,m,0);
return 0;
}
int main(){
int sum = 9;
std::vector<int> num_set;
num_set.push_back(3);
num_set.push_back(34);
num_set.push_back(4);
num_set.push_back(12);
num_set.push_back(5);
num_set.push_back(2);
SumArray sum_array(sum+1,0);
SumMap sum_map(num_set.size()+1,sum_array);
TakenMap taken_map(sum_map);
int result = subsum(num_set,sum_map,taken_map,num_set.size(),sum);
std::cout<<"result:"<<result<<std::endl;
system("PAUSE");
}
void adajoint_chr(char **R_file_prefix, int *R_method,
int *R_nperm, int *R_seed,
int *R_nthread, int *R_nsnp, int *R_ngene,
double *R_vU, double *R_score0, double *R_vV,
int *R_vgene_idx, int *R_gene_start, int *R_gene_end,
int *R_vgene_cutpoint,
int *R_gene_cutpoint_start, int *R_gene_cutpoint_end,
double *R_gene_pval, int *R_arr_rank,
int *R_sel_id, int *R_marg_id){
int len_file_prefix = strlen(*R_file_prefix);
char *file_prefix = new char[len_file_prefix + 1];
file_prefix[0] = '\0';
strcat(file_prefix, *R_file_prefix);
int method = *R_method;
assert(method == 1 || method == 2);
int nperm = *R_nperm;
int seed = *R_seed;
int nthread = *R_nthread;
int nsnp = *R_nsnp;
int ngene = *R_ngene;
fvec score0;
fmat V;
fmat U;
load_score0(R_score0, score0, nsnp);
load_cov(R_vV, V, nsnp);
load_U(R_vU, U, nsnp);
imat gene_idx; // index of SNPs in a gene
load_gene_idx(R_vgene_idx, R_gene_start, R_gene_end,
gene_idx, ngene);
imat cutpoint;
load_gene_cutpoint(R_vgene_cutpoint, R_gene_cutpoint_start, R_gene_cutpoint_end,
cutpoint, ngene);
string fprefix (file_prefix);
svec gene_out (ngene, fprefix);
for(int g = 0; g < ngene; ++g){
ostringstream gid;
gid << g;
gene_out[g] = gene_out[g] + string("GID.") + gid.str() + string(".bin");
}
// write obs statistics for all genes
imat sel_id(ngene);
ivec marg_id(ngene);
for(int g = 0; g < ngene; ++g){
fstream gout(gene_out[g].c_str(), ios::out | ios::binary);
if(!gout){
error("Fail to write observed statistics to file");
}
fvec S;
fmat Sigma;
extract_score(S, score0, gene_idx[g]);
extract_cov(Sigma, V, gene_idx[g]);
fvec s;
int ncp = cutpoint[g].size();
int mc = cutpoint[g][ncp - 1];
if(method == 1){
search1(s, sel_id[g], marg_id[g], S, Sigma, mc);
}else{//assert(method == 2)
search2(s, sel_id[g], marg_id[g], S, Sigma, mc);
}
for(int k = 0; k < ncp; ++k){
float u = s[cutpoint[g][k]];
gout.write((char*)(&u), sizeof(u));
}
gout.close();
}
int i_sel_id = -1;
for(int g = 0; g < ngene; ++g){
R_marg_id[g] = gene_idx[g][marg_id[g]] + 1;
for(int k = 0; k < sel_id[g].size(); ++k){
++i_sel_id;
R_sel_id[i_sel_id] = gene_idx[g][sel_id[g][k]] + 1;
}
int nn = gene_idx[g].size() - sel_id[g].size();
while(nn){
++i_sel_id;
R_sel_id[i_sel_id] = -1;
--nn;
}
}
int ngap = min(10000, nperm);
int nblock = nperm / ngap;
for(int b = 0; b < nblock; ++b){
fmat null(ngap, fvec (nsnp, .0f));
drand48_data buf;
// compute null score
#pragma omp parallel num_threads(nthread) private(buf)
{
srand48_r(seed + b * nthread + omp_get_thread_num(), &buf);
#pragma omp for
for(int i = 0; i < ngap; ++i){
fvec rn;
rnorm(buf, nsnp, rn);
for(int j = 0; j < nsnp; ++j){
null[i][j] = .0f;
for(int k = 0; k < nsnp; ++k){
null[i][j] += rn[k] * U[k][j];
}
}
}
}
// write null statistics to local files (per gene)
#pragma omp parallel num_threads(min(nthread, ngene))
{
#pragma omp for
for(int g = 0; g < ngene; ++g){
ofstream gout;
gout.open(gene_out[g].c_str(), ios::out | ios::binary | ios::app);
if(!gout){
error("Fail to write null statistics to file");
}
fmat Sigma;
extract_cov(Sigma, V, gene_idx[g]);
int ns = gene_idx[g].size();
int ncp = cutpoint[g].size();
int mc = cutpoint[g][ncp - 1];
for(int i = 0; i < ngap; ++i){
fvec S;
extract_score(S, null[i], gene_idx[g]);
fvec s;
ivec sel_id;
int marg_id;
if(method == 1){
search1(s, sel_id, marg_id, S, Sigma, mc);
}else{
search2(s, sel_id, marg_id, S, Sigma, mc);
}
for(int k = 0; k < ncp; ++k){
float u = s[cutpoint[g][k]];
gout.write((char*)(&u), sizeof(u));
}
}
gout.close();
}
}
//fmat().swap(null);
}
// read null statistics (per gene)
int irk = -1;
for(int g = 0; g < ngene; ++g){
int ncp = cutpoint[g].size();
vector<VecStat> stat(ncp, VecStat (nperm + 1, STAT0));
fstream gin(gene_out[g].c_str(), ios::in | ios::binary);
for(int i = 0; i < nperm + 1; ++i){
for(int j = 0; j < ncp; ++j){
float s = .0f;
gin.read((char*)(&s), sizeof(s));
stat[j][i].stat = s;
stat[j][i].id = i;
}
}
gin.close();
if(remove(gene_out[g].c_str())){
error("Cannot delete gene output file");
}
imat arr_rank(ncp, ivec (nperm + 1, 0));
#pragma omp parallel num_threads(min(ncp, nthread))
{
#pragma omp for
for(int j = 0; j < ncp; ++j){
sort(stat[j].begin(), stat[j].end(), descending);
for(int i = 0; i < nperm + 1; ++i){
int id = stat[j][i].id;
arr_rank[j][id] = i;
}
}
}
vector<VecStat>().swap(stat);
ivec gene_min_p (nperm + 1, -1);
ivec subsum(nthread, 0);
ivec subtie(nthread, 0);
int m = nperm + 1;
for(int j = 0; j < ncp; ++j){
++irk;
R_arr_rank[irk] = arr_rank[j][0];
if(arr_rank[j][0] < m){
m = arr_rank[j][0];
}
}
gene_min_p[0] = m;
#pragma omp parallel num_threads(nthread)
{
#pragma omp for
for(int i = 1; i < nperm + 1; ++i){
int tid = omp_get_thread_num();
int m = nperm + 1;
for(int j = 0; j < ncp; ++j){
if(arr_rank[j][i] < m){
m = arr_rank[j][i];
}
}
gene_min_p[i] = m;
if(gene_min_p[i] < gene_min_p[0]){
subsum[tid] += 1;
}else if(gene_min_p[i] == gene_min_p[0]){
subtie[tid] += 1;
}else{
;
}
}
}
R_gene_pval[g] = 1.0;
int rep = 0;
for(int t = 0; t < nthread; ++t){
R_gene_pval[g] += subsum[t];
rep += subtie[t];
}
R_gene_pval[g] += rep / 2.0;
R_gene_pval[g] /= nperm + 1;
fstream gout(gene_out[g].c_str(), ios::out | ios::binary);
if(!gout){
error("Fail to write gene statistics to file");
}
for(int i = 0; i < nperm + 1; ++i){
gout.write((char*)(&(gene_min_p[i])), sizeof(gene_min_p[i]));
}
gout.close();
}
delete[] file_prefix;
}
void artp3(char **R_file_prefix, int *R_nperm, int *R_nthread,
int *R_ngene, int *R_group_id, int *R_gene_id,
int *R_pathway_cutpoint, int *R_ncp,
double *R_pathway_pval, int *R_arr_rank, double *R_gene_pval){
int len_file_prefix = strlen(*R_file_prefix);
char *file_prefix = new char[len_file_prefix + 1];
file_prefix[0] = '\0';
strcat(file_prefix, *R_file_prefix);
int nperm = *R_nperm;
int nthread = *R_nthread;
int ngene = *R_ngene;
int ncp = *R_ncp;
assert(nthread == 1);
ivec group_id;
load_group_id(R_group_id, group_id, ngene);
ivec gene_id;
load_gene_id(R_gene_id, gene_id, ngene);
ivec pathway_cutpoint;
load_pathway_cutpoint(R_pathway_cutpoint, pathway_cutpoint, ncp);
int max_cutpoint = pathway_cutpoint[ncp - 1];
string fprefix (file_prefix);
svec gene_out (ngene, fprefix);
for(int g = 0; g < ngene; ++g){
ostringstream cid;
cid << group_id[g];
ostringstream gid;
gid << gene_id[g];
gene_out[g] = gene_out[g] + string(".CID.") + cid.str() + string(".GID.") + gid.str() + string(".bin");
}
vector<VecMinp> gene_stat (ngene, VecMinp(nperm + 1, MINP0));
imat gene_p_stat (ngene, ivec(nperm + 1, -1));
for(int g = 0; g < ngene; ++g){
fstream gin(gene_out[g].c_str(), ios::in | ios::binary);
//ivec zero_loc;
for(int i = 0; i < nperm + 1; ++i){
gin.read((char*)(&(gene_stat[g][i].stat)), sizeof(gene_stat[g][i].stat));
gene_stat[g][i].id = i;
}
gin.close();
if(remove(gene_out[g].c_str())){
error("Cannot delete gene output file");
}
sort(gene_stat[g].begin(), gene_stat[g].end());
for(int i = 0; i < nperm + 1; ++i){
int id = gene_stat[g][i].id;
gene_p_stat[g][id] = i;
}
VecMinp().swap(gene_stat[g]);
}
vector<VecMinp>().swap(gene_stat);
for(int g = 0; g < ngene; ++g){
R_gene_pval[g] = (gene_p_stat[g][0] + 1.0) / (nperm + 1);
}
vector<VecStat> stat(ncp, VecStat (nperm + 1, STAT0));
for(int i = 0; i < nperm + 1; ++i){
fvec s(ngene, .0f);
for(int g = 0; g < ngene; ++g){
s[g] = (float) log((gene_p_stat[g][i] + 1.0) / (nperm + 1));
}
if(ngene > 1){
sort(s.begin(), s.end());
for(int g = 1; g <= max_cutpoint; ++g){
s[g] += s[g - 1];
}
}
for(int k = 0; k < ncp; ++k){
float u = -s[pathway_cutpoint[k]];
stat[k][i].stat = u;
stat[k][i].id = i;
}
}
imat().swap(gene_p_stat);
imat arr_rank(ncp, ivec (nperm + 1, 0));
for(int k = 0; k < ncp; ++k){
sort(stat[k].begin(), stat[k].end(), descending);
for(int i = 0; i < nperm + 1; ++i){
int id = stat[k][i].id;
arr_rank[k][id] = i;
}
VecStat().swap(stat[k]);
}
vector<VecStat>().swap(stat);
ivec pathway_min_p(nperm + 1, -1);
ivec subsum(nthread, 0);
ivec subtie(nthread, 0);
int m = nperm + 1;
for(int k = 0; k < ncp; ++k){
R_arr_rank[k] = arr_rank[k][0];
if(arr_rank[k][0] < m){
m = arr_rank[k][0];
}
}
pathway_min_p[0] = m;
for(int i = 1; i < nperm + 1; ++i){
int tid = 0;
int m = nperm + 1;
for(int k = 0; k < ncp; ++k){
if(arr_rank[k][i] < m){
m = arr_rank[k][i];
}
}
pathway_min_p[i] = m;
if(pathway_min_p[i] < pathway_min_p[0]){
subsum[tid] += 1;
}else if(pathway_min_p[i] == pathway_min_p[0]){
subtie[tid] += 1;
}else{
;
}
}
*R_pathway_pval = 1.0;
int rep = 0;
for(int t = 0; t < nthread; ++t){
*R_pathway_pval += subsum[t];
rep += subtie[t];
}
*R_pathway_pval += rep / 2.0;
*R_pathway_pval /= nperm + 1;
delete[] file_prefix;
}
void artp3_chr(char **R_file_prefix, int *R_method,
int *R_nperm, int *R_seed,
int *R_nthread, int *R_nsnp, int *R_ngene,
double *R_vU, double *R_score0, double *R_vV,
int *R_vgene_idx, int *R_gene_start, int *R_gene_end,
int *R_vgene_cutpoint,
int *R_gene_cutpoint_start, int *R_gene_cutpoint_end,
double *R_gene_pval, int *R_arr_rank,
int *R_sel_id, int *R_marg_id){
int len_file_prefix = strlen(*R_file_prefix);
char *file_prefix = new char[len_file_prefix + 1];
file_prefix[0] = '\0';
strcat(file_prefix, *R_file_prefix);
int method = *R_method;
assert(method == 3);
if(method == 3){
;
}
int nperm = *R_nperm;
int seed = *R_seed;
int nthread = *R_nthread;
int nsnp = *R_nsnp;
int ngene = *R_ngene;
assert(nthread == 1);
fvec score0;
fvec sigma2;
fmat U;
fmat V;
load_score0(R_score0, score0, nsnp);
load_cov(R_vV, V, nsnp);
load_sigma2(V, sigma2);
load_U(R_vU, U, nsnp);
imat gene_idx; // index of SNPs in a gene
load_gene_idx(R_vgene_idx, R_gene_start, R_gene_end,
gene_idx, ngene);
imat cutpoint;
load_gene_cutpoint(R_vgene_cutpoint, R_gene_cutpoint_start, R_gene_cutpoint_end,
cutpoint, ngene);
string fprefix (file_prefix);
svec gene_out (ngene, fprefix);
for(int g = 0; g < ngene; ++g){
ostringstream gid;
gid << g;
gene_out[g] = gene_out[g] + string("GID.") + gid.str() + string(".bin");
}
// write obs statistics for all genes
imat sel_id(ngene);
ivec marg_id(ngene);
for(int g = 0; g < ngene; ++g){
fstream gout(gene_out[g].c_str(), ios::out | ios::binary);
if(!gout){
error("Fail to write observed statistics to file");
}
int ns = gene_idx[g].size();
int ncp = cutpoint[g].size();
int max_cutpoint = cutpoint[g][ncp - 1];
fvec s (ns, .0f);
VecStat vs (ns, STAT0);
for(int j = 0; j < ns; ++j){
s[j] = score0[gene_idx[g][j]];
s[j] = pchisq(s[j] * s[j] / sigma2[gene_idx[g][j]], 1, false, true);
vs[j].stat = -s[j];
vs[j].id = j;
}
sort(vs.begin(), vs.end(), descending);
marg_id[g] = vs[0].id;
for(int j = 0; j < ns; ++j){
sel_id[g].push_back(vs[j].id);
}
sort(s.begin(), s.end());
for(int j = 1; j <= max_cutpoint; ++j){
s[j] += s[j - 1];
}
for(int k = 0; k < ncp; ++k){
float u = -s[cutpoint[g][k]];
gout.write((char*)(&u), sizeof(u));
}
gout.close();
}
int i_sel_id = -1;
for(int g = 0; g < ngene; ++g){
R_marg_id[g] = gene_idx[g][marg_id[g]] + 1;
for(int k = 0; k < sel_id[g].size(); ++k){
++i_sel_id;
R_sel_id[i_sel_id] = gene_idx[g][sel_id[g][k]] + 1;
}
int nn = gene_idx[g].size() - sel_id[g].size();
while(nn){
++i_sel_id;
R_sel_id[i_sel_id] = -1;
--nn;
}
}
int ngap = min(10000, nperm);
int nblock = nperm / ngap;
srand(seed);
for(int b = 0; b < nblock; ++b){
fmat null(ngap, fvec (nsnp, .0f));
// compute null statistics
for(int i = 0; i < ngap; ++i){
fvec rn;
rnorm(nsnp, rn);
for(int j = 0; j < nsnp; ++j){
null[i][j] = .0f;
for(int k = 0; k < nsnp; ++k){
null[i][j] += rn[k] * U[k][j];
}
null[i][j] = null[i][j] * null[i][j] / sigma2[j];
null[i][j] = pchisq(null[i][j], 1, false, true);
}
}
// write null statistics to local files (per gene)
for(int g = 0; g < ngene; ++g){
ofstream gout;
gout.open(gene_out[g].c_str(), ios::out | ios::binary | ios::app);
if(!gout){
error("Fail to write null statistics to file");
}
int ns = gene_idx[g].size();
int ncp = cutpoint[g].size();
int max_cutpoint = cutpoint[g][ncp - 1];
for(int i = 0; i < ngap; ++i){
fvec s(ns, .0f);
for(int j = 0; j < ns; ++j){
s[j] = null[i][gene_idx[g][j]];
}
sort(s.begin(), s.end());
for(int j = 1; j <= max_cutpoint; ++j){
s[j] += s[j - 1];
}
for(int k = 0; k < ncp; ++k){
float u = -s[cutpoint[g][k]];
gout.write((char*)(&u), sizeof(u));
}
}
gout.close();
}
//fmat().swap(null);
}
// read null statistics (per gene)
int irk = -1;
for(int g = 0; g < ngene; ++g){
int ncp = cutpoint[g].size();
vector<VecStat> stat(ncp, VecStat (nperm + 1, STAT0));
fstream gin(gene_out[g].c_str(), ios::in | ios::binary);
for(int i = 0; i < nperm + 1; ++i){
for(int j = 0; j < ncp; ++j){
float s = .0f;
gin.read((char*)(&s), sizeof(s));
stat[j][i].stat = s;
stat[j][i].id = i;
}
}
gin.close();
if(remove(gene_out[g].c_str())){
error("Cannot delete gene output file");
}
imat arr_rank(ncp, ivec (nperm + 1, 0));
for(int j = 0; j < ncp; ++j){
sort(stat[j].begin(), stat[j].end(), descending);
for(int i = 0; i < nperm + 1; ++i){
int id = stat[j][i].id;
arr_rank[j][id] = i;
}
}
vector<VecStat>().swap(stat);
ivec gene_min_p (nperm + 1, -1);
ivec subsum(nthread, 0);
ivec subtie(nthread, 0);
int m = nperm + 1;
for(int j = 0; j < ncp; ++j){
++irk;
R_arr_rank[irk] = arr_rank[j][0];
if(arr_rank[j][0] < m){
m = arr_rank[j][0];
}
}
gene_min_p[0] = m;
for(int i = 1; i < nperm + 1; ++i){
int tid = 0;
int m = nperm + 1;
for(int j = 0; j < ncp; ++j){
if(arr_rank[j][i] < m){
m = arr_rank[j][i];
}
}
gene_min_p[i] = m;
if(gene_min_p[i] < gene_min_p[0]){
subsum[tid] += 1;
}else if(gene_min_p[i] == gene_min_p[0]){
subtie[tid] += 1;
}else{
;
}
}
R_gene_pval[g] = 1.0;
int rep = 0;
for(int t = 0; t < nthread; ++t){
R_gene_pval[g] += subsum[t];
rep += subtie[t];
}
R_gene_pval[g] += rep / 2.0;
R_gene_pval[g] /= nperm + 1;
fstream gout(gene_out[g].c_str(), ios::out | ios::binary);
if(!gout){
error("Fail to write gene statistics to file");
}
for(int i = 0; i < nperm + 1; ++i){
gout.write((char*)(&(gene_min_p[i])), sizeof(gene_min_p[i]));
}
gout.close();
}
delete[] file_prefix;
}
