void single_flow_optimizer::FitKrateOneFlow(int fnum, float *evect, BeadParams *p, error_track *err_t, float *signal_corrected, float *signal_predicted, int NucID, float *lnucRise, int l_i_start,
int flow_block_start, TimeCompression &time_c, EmphasisClass &emphasis_data,RegionTracker &my_regions)
{
oneFlowFitKrate->SetWeightVector (evect);
oneFlowFitKrate->SetLambdaStart (1E-20);
oneFlowFitKrate->calc_trace.SetWellRegionParams (p,&my_regions.rp,fnum,
NucID, flow_block_start + fnum,
l_i_start,lnucRise);
if (my_regions.rp.use_log_taub)
oneFlowFitKrate->calc_trace.GuessLogTaub(signal_corrected,p,fnum,&my_regions.rp); // replaces tauB in setWellRegionParams()
oneFlowFitKrate->SetFvalCacheEnable (use_fval_cache);
p->kmult[fnum] = local_min_param[KMULT];
oneFlowFitKrate->InitParams();
// float start_guess = p->Ampl[fnum];
oneFlowFitKrate->calc_trace.ResetEval();
int max_fit_iter = gauss_newton_fit ? NUMSINGLEFLOWITER_GAUSSNEWTON : NUMSINGLEFLOWITER_LEVMAR;
oneFlowFitKrate->Fit (gauss_newton_fit, max_fit_iter, signal_corrected);
// cur_hits = oneFlowFitKrate->calc_trace.GetEvalCount();
p->Ampl[fnum] = oneFlowFitKrate->ReturnNthParam (AMPLITUDE);
p->kmult[fnum] = oneFlowFitKrate->ReturnNthParam (KMULT);
oneFlowFitKrate->ReturnPredicted(signal_predicted, use_fval_cache);
//float posf=0.0f, negf=0.0f;
const float kmult_at_bottom = 0.01f;
const float fit_error_too_high = 20.0f; //@TODO: this does not scale with signal!!!!
const float final_minimum_kmult = 0.3f;
const float extend_emphasis_amount = 2.0f;
if(fabs( p->kmult[fnum]-local_min_param[KMULT])<kmult_at_bottom){
float errx=sqrt (oneFlowFitKrate->GetMeanSquaredError (signal_corrected,use_fval_cache));
if (errx>fit_error_too_high){ //if the fit error is high it could be a slow incorporation
//fprintf(stdout,"/n>mapx=%f,%f,%f\n",errx, p->kmult[fnum],p->Ampl[fnum]);
//oneFlowFitKrate->InitParams();
oneFlowFitKrate->calc_trace.ResetEval();
local_max_param[KMULT] =local_min_param[KMULT];
p->kmult[fnum] = final_minimum_kmult;
local_min_param[KMULT]=final_minimum_kmult;
oneFlowFitKrate->SetParamMin (&local_min_param[0]);
oneFlowFitKrate->SetParamMax (&local_max_param[0]);
emphasis_data.CustomEmphasis (evect, p->Ampl[fnum]+extend_emphasis_amount);
oneFlowFitKrate->Fit (gauss_newton_fit, max_fit_iter, signal_corrected);
}
}
cur_hits = oneFlowFitKrate->calc_trace.GetEvalCount();
p->Ampl[fnum] = oneFlowFitKrate->ReturnNthParam (AMPLITUDE);
p->kmult[fnum] = oneFlowFitKrate->ReturnNthParam (KMULT);
p->tauB[fnum] = oneFlowFitKrate->calc_trace.tauB; // save tauB for output to trace.h5
// store output for later
oneFlowFitKrate->SetWeightVector (emphasis_data.EmphasisVectorByHomopolymer[emphasis_data.numEv-1]);
err_t->mean_residual_error[fnum] = sqrt (oneFlowFitKrate->GetMeanSquaredError (signal_corrected,use_fval_cache)); // backwards compatibility
oneFlowFitKrate->ReturnPredicted(signal_predicted, use_fval_cache);
}
int single_flow_optimizer::FitStandardPath (int fnum, float *evect, BeadParams *p, error_track *err_t, float *signal_corrected, float *signal_predicted, int NucID, float *lnucRise, int l_i_start,
int flow_block_start, TimeCompression &time_c, EmphasisClass &emphasis_data,RegionTracker &my_regions)
{
float A_start = p->Ampl[fnum];
bool done = false;
int retry_count = 0;
int fitType = 0;
SetLowerLimitAmplFit (pmin_param[0],pmin_param[1]);
SetUpperLimitAmplFit (pmax_param[0],pmax_param[1]);
while (!done && (retry_count <=retry_limit))
{
emphasis_data.CustomEmphasis (evect, p->Ampl[fnum]+AdjustEmphasisForKmult(p->kmult[fnum],retry_count));
bool krate_fit = ( ( (p->Copies*p->Ampl[fnum]) > decision_threshold)); // this may not be the best way of deciding this
krate_fit = krate_fit || var_kmult_only;
fitType = krate_fit ? 1:0;
//printf("single_flow_optimizer::FitStandardPath... krate_fit=%d\n",krate_fit);
if (krate_fit)
{
FitKrateOneFlow (fnum,evect,p,err_t, signal_corrected,signal_predicted, NucID, lnucRise, l_i_start,flow_block_start,time_c,emphasis_data,my_regions);
}
else
{
// if (use_projection_search_ampl_fit)
// FitProjection (fnum,evect,p, err_t, signal_corrected,NucID, lnucRise, l_i_start,my_flow,time_c,emphasis_data,my_regions);
// else
FitThisOneFlow (fnum,evect,p, err_t, signal_corrected,signal_predicted, NucID, lnucRise, l_i_start,flow_block_start,time_c,emphasis_data,my_regions);
}
float amplitude_delta = A_start - p->Ampl[fnum];
float kmult_above_bottom = (p->kmult[fnum]-local_min_param[KMULT]);
const float amplitude_step_minimum = 0.1f;
const float kmult_near_bottom = 0.1f;
if ((fabs(amplitude_delta) > amplitude_step_minimum)||((fabs(kmult_above_bottom)<kmult_near_bottom)&&krate_fit))
A_start = p->Ampl[fnum];
else
done = true;
retry_count++;
}
return (fitType);
}