double MaxFlowSegmentation::get_histoprob(int index0)
{
int pix = 0;
if(threeD==true) pix = image_data[3*index0+0];
else pix = image_data[index0];
double probA = compute_prob(mean_histogram_bg, stdv_histogram_bg, normal_mean_histogram_bg, normal_stdv_histogram_bg, pix);
double probB = compute_prob(mean_histogram_fg, stdv_histogram_fg, normal_mean_histogram_fg, normal_stdv_histogram_fg, pix);
if(probB==0.0) probB = 0.000000001;
//double log_like = -2*(log(w_weight*probA)/log(probB));
double log_like = (w_weight*probA)/probB;
return log_like;
}
double Joint_like(int num_times, double T[pop_dim], double pop_size[num_times], double p[2])
{
int num_haps = p[0];
//int num_times = p[1];
double lambda[num_times];
int marker = 0;
int i=0;
for(i=0; i<num_times; i++)
{
//printf("pop_size[%d] = %f\n",i, pop_size[i]);
if (pop_size[i] < 100) //&& pop_size[i] < 100000000){}
// else{ }//break; }
{
marker = 1;
// printf("MARKER = %f\n", 1.0);
return(10000000000000);
}
lambda[i] = (1 / pop_size[i]);
}
precompute_L_ind_quantities( num_haps, num_times, T, pop_size );
double joint = 0;
// int l=0;
// for(l=0; l<num_bins; l++)
// {
// int m;
// for(m = 0; m < num_times; m++)
// {
// exp_part_L[m] = exp( T[m] * mu * bin_center[l] );
// }
int l=0;
for(l=0; l< num_loci; l++)
{
if(bin_center[l] > 1)
{
// printf("asdasdfbin_center = %f", bin_center[l]);
int m;
for(m = 0; m < num_times; m++)
{
exp_part_L[m] = exp( T[m] * mu * bin_center[l] );
}
}
}
double temp = 0;
double tile = 0;
double total = 0;
for(i=0; i< num_quantiles; i++)
{
temp =compute_prob(num_haps, num_times, quant_values[i], T, pop_size, lambda);
tile = quant_list[i];
total = total + pow( (1 - temp) - tile, 2);
//if (i % 100 == 0) { printf("computed_quant_values(%d) = %f \t tile = %f\n", i, 1- temp, tile); }
}
total = sqrt(total / num_quantiles);
//double temp1 = compute_prob(num_haps, num_times, 236.0, T, pop_size, lambda);
//double temp2 = compute_prob(num_haps, num_times, 658.0, T, pop_size, lambda);
// double temp3 = compute_prob(num_haps, num_times, 1640.0, T, pop_size, lambda);
// //printf("temp2 = %f\n", temp2);
//
//total = pow(fabs(temp3- .25),2);
//double temp4 = compute_prob(num_haps, num_times, bin_center[l], T, pop_size, lambda);
printf("total = %f\n", total);
if (total >-100 && total < 100){}
else{abort();}
return ( total );
}
float* compute_weight(char* matrix, float* weight, char** miss, char** hit)
{
float* n = new float[featurecount];
init(n);
auto dis = new float*[msize];
for (int i = 0; i < msize; i++)
{
dis[i] = new float[msize];
init(dis[i]);
}
distance(matrix, weight,dis);
for (int i = 0; i < samplecount; ++i)
{
float* m_n = new float[featurecount];
float* h_n = new float[featurecount];
init(m_n);
init(h_n);
for (int j = 0; j < samplecount; ++j)
{
if (i == j)
{
continue;
}
if (miss[i][j] == 1)
{
float a = compute_prob(dis, j, i, miss[i]);
char* x1 = new char[featurecount];
getLine(matrix,x1,i);
char* x2 = new char[featurecount];
getLine(matrix, x2, j);
char* b = new char[featurecount];
sub(x1,x2,b);
for (int k = 0; k < featurecount; k++)
{
m_n[k] += a*b[k];
}
delete[] b;
delete[] x1;
delete[] x2;
}
else if(hit[i][j]==1)
{
float a = compute_prob(dis, j, i, hit[i]);
char* x1 = new char[featurecount];
getLine(matrix, x1, i);
char* x2 = new char[featurecount];
getLine(matrix, x2, j);
char* b = new char[featurecount];
sub(x1, x2, b);
for (int k = 0; k < featurecount; k++)
{
h_n[k] += a*b[k];
}
delete[] b;
delete[] x1;
delete[] x2;
}
}
float gn = compute_gn(matrix, dis, i, miss[i]);
for (int j = 0; j < featurecount; ++j)
{
n[j] += gn*(m_n[j] - h_n[j]);
}
delete[] m_n;
delete[] h_n;
}
for (int i = 0; i < msize; i++)
{
delete[] dis[i];
}
delete[] dis;
for (int i = 0; i < featurecount; ++i)
{
if (n[i] < 0)
{
n[i] = 0;
}
else
{
n[i] /= 1000;
}
}
float n_norm = norm_2(n);
for (int i = 0; i < featurecount; ++i)
{
n[i] /= n_norm;
}
return n;
}
