/**
* @brief Run the analysis.
*/
void CNFamilialAnalysisMethodGenotypeConcordance::run()
{
Verbose::out(1, "CNFamilialAnalysisMethodGenotypeConcordance::run(...) start");
CNCychp& cychpIndex = getCychpIndex();
CNCychp& cychpMother = getCychpMother();
CNCychp& cychpFather = getCychpFather();
getIndexSegments().deleteAll();
getMotherSegments().deleteAll();
getFatherSegments().deleteAll();
int iProbeSetCount = cychpIndex.getCychpProbeSetsCopyNumbers().getCount();
if (cychpMother.getFamilialCall() == 1)
{
Verbose::progressBegin(1, "CNFamilialAnalysisMethodGenotypeConcordance::run(...) Mother's segments ", iProbeSetCount, 100000, (iProbeSetCount / 100000));
for (int i = 0; (i < iProbeSetCount); i++)
{
Verbose::progressStep(1);
CNCychpProbeSetsCopyNumber* pIndex = cychpIndex.getCychpProbeSetsCopyNumbers().getAt(i);
CNCychpProbeSetsCopyNumber* pMother = cychpMother.getCychpProbeSetsCopyNumbers().getAt(i);
if ((pMother->getGenotypeCall() == -1) || (pIndex->getGenotypeCall() == -1))
{
pMother->setSegmentInput(-1);
}
else
{
pMother->setSegmentInput(1);
if (isGenotypeConcordance(pIndex, pMother)) {pMother->setSegmentInput(0);}
}
}
anneal(cychpMother);
newSegments(cychpIndex, cychpMother, 1, getMotherSegments(), getSegmentType(), 1, m_iMarkerCountCutoff, m_iCallCutoff, m_iMinGenomicSpan);
Verbose::progressEnd(1, "Done");
}
if (cychpFather.getFamilialCall() == 1)
{
Verbose::progressBegin(1, "CNFamilialAnalysisMethodGenotypeConcordance::run(...) Father's segments ", iProbeSetCount, 100000, (iProbeSetCount / 100000));
for (int i = 0; (i < iProbeSetCount); i++)
{
Verbose::progressStep(1);
CNCychpProbeSetsCopyNumber* pIndex = cychpIndex.getCychpProbeSetsCopyNumbers().getAt(i);
CNCychpProbeSetsCopyNumber* pFather = cychpFather.getCychpProbeSetsCopyNumbers().getAt(i);
if ((pFather->getGenotypeCall() == -1) || (pIndex->getGenotypeCall() == -1))
{
pFather->setSegmentInput(-1);
}
else
{
pFather->setSegmentInput(1);
if (isGenotypeConcordance(pIndex, pFather)) {pFather->setSegmentInput(0);}
}
}
anneal(cychpFather);
newSegments(cychpIndex, cychpFather, 2, getFatherSegments(), getSegmentType(), 1, m_iMarkerCountCutoff, m_iCallCutoff, m_iMinGenomicSpan);
Verbose::progressEnd(1, "Done");
}
Verbose::out(1, "CNFamilialAnalysisMethodGenotypeConcordance::run(...) end");
}
int main() {
circ = load_circuit();
//print_circuit(circ);
//print_tree(circ_tree, 600, 0);
//print_tree(circ_tree, 600, 1);
fprintf(stderr, "Cost: %lld\n", register_circuit(circ));
anneal();
//print_tree(c_tree, 650,0);
print_circuit(circ);
}
/*
* Improves k to the maximum extent possible.
*/
Keyboard improver(Keyboard k)
{
printPercentages(&k);
Keyboard tk, bestk;
copy(&tk, &k);
copy(&bestk, &k);
int64_t bestEval = k.fitness;
int64_t curEval = anneal(&tk, NULL, 0);
if (curEval < bestEval) {
copy(&bestk, &tk);
bestEval = curEval;
printPercentages(&tk);
}
return bestk;
}
/**
* @brief Run the analysis.
* Denovo is when the Index CN != the CN of either parent.
*/
void CNFamilialAnalysisMethodDenovoCopyNumber::run()
{
Verbose::out(1, "CNFamilialAnalysisMethodDenovoCopyNumber::run(...) start");
CNCychp& cychpIndex = getCychpIndex();
CNCychp& cychpMother = getCychpMother();
CNCychp& cychpFather = getCychpFather();
getIndexSegments().deleteAll();
getMotherSegments().deleteAll();
getFatherSegments().deleteAll();
if ((cychpMother.getFamilialCall() == 0) && (cychpFather.getFamilialCall() == 0)) {return;}
int iProbeSetCount = cychpIndex.getCychpProbeSetsCopyNumbers().getCount();
if ((cychpMother.getFamilialCall() == 1) && (cychpFather.getFamilialCall() == 1))
{
Verbose::progressBegin(1, "CNFamilialAnalysisMethodDenovoCopyNumber::run(...) Index's segments ", iProbeSetCount, 100000, (iProbeSetCount / 100000));
for (int i = 0; (i < iProbeSetCount); i++)
{
Verbose::progressStep(1);
CNCychpProbeSetsCopyNumber* pIndex = cychpIndex.getCychpProbeSetsCopyNumbers().getAt(i);
CNCychpProbeSetsCopyNumber* pMother = cychpMother.getCychpProbeSetsCopyNumbers().getAt(i);
CNCychpProbeSetsCopyNumber* pFather = cychpFather.getCychpProbeSetsCopyNumbers().getAt(i);
pIndex->setSegmentInput(1);
if ((pIndex->getCnCall() != pMother->getCnCall()) && (pIndex->getCnCall() != pFather->getCnCall()))
{
pIndex->setSegmentInput(0);
}
}
anneal(cychpIndex);
newSegments(cychpIndex, cychpIndex, 0, getIndexSegments(), getSegmentType(), 1, m_iMarkerCountCutoff, m_iCallCutoff, m_iMinGenomicSpan);
Verbose::progressEnd(1, "Done");
}
Verbose::out(1, "CNFamilialAnalysisMethodDenovoCopyNumber::run(...) end");
}
int main(int argc, char * argv[])
{
//============================================
// Set input parameters
if (argc < 4|| argc > 4){
printf("Wrong number of inputs. You entered %d. You should enter 4\n.", argc);
myusage();
}
int XLENGTH = atoi(argv[1]);
int YLENGTH = atoi(argv[2]);
int NCLUST = atoi(argv[3]);
int HLENGTH;
double px[XLENGTH];
double py[YLENGTH];
double beta = .00001;
double F;
double infocurve[4] = {1,1,1,1};
//int modus = 0;
// modus = 0 : use p(y|c) cluster centers as initialization
// modus = 1 : use p(c|x) assignment ruls as initialization
double annealingrate = 1.1;
bool plotme = true; //some debug printing
bool debug = false;//verbose debug printing
FILE * histFile;
FILE * probFile;
histogram_t *histo;
histogram_t *pxy;
histogram_t *pygc;
histogram_t *pcgx;
histogram_t *pc;
if(plotme)
{
printf("XLENGTH= %d\n", XLENGTH);
printf("YLENGTH= %d\n", YLENGTH);
printf("NCLUST = %d\n", NCLUST);
}
histFile = fopen(histoName, "r");
if(histFile == NULL)
{
printf("Error: can't access %s\n", histoName);
exit(1);
}
float v;
int j,i = 0;
int y;
int x;
char s [YLENGTH*20];
char * tok;
// //allocate memory for large cluster probability arrays
// double** pygc;
// //allocate pointer memory for first dimension
// pygc = (double**)malloc(YLENGTH*sizeof(double));
// if(NULL == pygc){free(pygc); printf("Memory allocation failed while allocating for pygc[].\n"); exit(-1);}
//
// /*allocate memory for second dimension */
// for(i = 0; i < YLENGTH;i++)
// {
// pygc[i] = (double *) malloc( NCLUST * sizeof(double) );
// if(NULL == pygc[i]){free(pygc[i]); printf("Memory allocation failed while allocating for matrix[x][].\n"); exit(-1);}
// }
//
// double** pcgx;
// //allocate pointer memory for first dimension
// pcgx = (double**)malloc(NCLUST*sizeof(double));
// if(NULL == pcgx){free(pcgx); printf("Memory allocation failed while allocating for pcgx[].\n"); exit(-1);}
//
// /*allocate memory for second dimension */
// for(i = 0; i < NCLUST;i++)
// {
// pcgx[i] = (double *) malloc( XLENGTH * sizeof(double) );
// if(NULL == pcgx[i]){free(pcgx[i]); printf("Memory allocation failed while allocating for matrix[x][].\n"); exit(-1);}
// }
//count how many entries are actually in the histogram file -- these are only the non-zero p(y|x)
while(fscanf(histFile, "%f", &v)!= EOF)
{
i++;
}
rewind(histFile);
if(debug){printf("Counted %d entries in histogram file\n", i);}
//make histogram size 1/2 number entries counted because 1/2 are the indices (y values)
HLENGTH = i/2;
histo = histogram_create(HLENGTH);
x = 0;
//make p(y|x) histogram
//YLENGTH*20 is assuming most words are less than 20 chars long
while(fgets(s, (YLENGTH*20), histFile)!= NULL)
{
tok = strtok(s,"\t");
while(tok != NULL)
{
if(debug){printf("Found word: %d\n", atoi(tok));}
y = atoi(tok);
tok = strtok(NULL, "\t");
if(tok != NULL) //hits null in the word
{
if(debug){printf("Found value: %f\n", atof(tok));}
v = atof(tok);
tok = strtok(NULL, "\t");
histogram_set(histo,x,y,v);
}
}
x++;
}
if(debug)
{
printf("Checking histogram\n");
for(x = 0; x < XLENGTH; x++)
{
for(y = 0; y < YLENGTH; y++)
{
if((v = histogram_get(histo, x, y)))
{
printf("Found doc %d - word %d in histo: %f\n",x,y,v);
}
}
}
}
fclose(histFile);
// now read in the other initial probs
probFile = fopen(probName, "r");
if(probFile == NULL)
{
printf("Error: can't access %s\n", histoName);
exit(1);
}
//*********** p(x) is first line *******************
printf("read in p(x)\n");
fgets(s, (XLENGTH*20), probFile);
//printf("s = %s\n",s);
// printf("length of s = %d\n", strlen(s));
tok = strtok(s,"\t");
x = 0;
while(tok != NULL)
{
//printf("tok = %s\n", tok);
if(strcmp(tok,"\n") != 0)
{
px[x] = atof(tok);
//printf("px(%d) = %f\n", x, px[x]);
x++;
}
tok = strtok(NULL,"\t");
}
//second line is blank
fgets(s, (YLENGTH*20), probFile);
//************** p(y) is third line ************************
fgets(s, (YLENGTH*20), probFile);
printf("read in p(y)\n");
// printf("s = %s\n",s);
// printf("length of s = %d\n", strlen(s));
tok = strtok(s,"\t");
x = 0;
while(tok != NULL)
{
if(strcmp(tok,"\n") != 0)
{
py[x] = atof(tok);
// printf("py(%d) = %f\n", x, py[x]);
x++;
}
tok = strtok(NULL,"\t");
}
//fourth line is blank
fgets(s,(YLENGTH*20), probFile);
//******************** fifth line on is p(xy)
printf("Making p(x;y)\n");
pxy = histogram_create(HLENGTH);
x = 0;
while(fgets(s, (YLENGTH*20), probFile)!= NULL)
{
//get line for doc
//printf("Found %s\n", s);
//split y and p
tok = strtok(s,"\t");
while(tok != NULL)
{
//printf("Found word: %d\n", atoi(tok));
y = atoi(tok);
tok = strtok(NULL, "\t");
if(tok != NULL) //hits null in the word
{
//printf("Found value: %f\n", atof(tok));
v = atof(tok);
tok = strtok(NULL, "\t");
histogram_set(pxy,x,y,v);
}
}
x++;
}
fclose(probFile);
if(debug){
printf("Checking pxy\n");
for(x = 0; x < XLENGTH; x++)
{
for(y = 0; y < YLENGTH; y++)
{
if((v = histogram_get(pxy, x, y)))
{
printf("Found doc %d - word %d in histo: %f\n",x,y,v);
}
}
}
}
//****************** initialize cluster probs *****************************
printf("Making p(c|x)\n");
ini_pcgx(NCLUST, XLENGTH, pcgx);
printf("Now going to anneal\n");
//******************* NOW GO TO ANNEAL **************************
F = anneal(XLENGTH, YLENGTH, NCLUST, beta, pxy, histo, pcgx, pygc, pc,
infocurve, annealingrate, plotme);
printf("Returned from anneal\n");
//cleanup
histogram_destroy(pxy);
histogram_destroy(histo);
histogram_destroy(pygc);
histogram_destroy(pcgx);
histogram_destroy(pc);
// for(i = 0; i < YLENGTH; i++)
// free(pygc[i]);
// free(pygc);
// for(i = 0; i < NCLUST; i++)
// free(pcgx[i]);
// free(pcgx);
exit(1);
}
