IsotopeFitter1D::QualityType IsotopeFitter1D::fit1d(const RawDataArrayType& set, InterpolationModel*& model)
{
// Calculate bounding box
min_ = max_ = set[0].getPos();
for (UInt pos = 1; pos < set.size(); ++pos)
{
CoordinateType tmp = set[pos].getPos();
if (min_ > tmp)
min_ = tmp;
if (max_ < tmp)
max_ = tmp;
}
// Enlarge the bounding box by a few multiples of the standard deviation
{
stdev1_ = sqrt(statistics_.variance()) * tolerance_stdev_box_;
min_ -= stdev1_;
max_ += stdev1_;
}
// build model
if (charge_ == 0)
{
model = static_cast<InterpolationModel*>(Factory<BaseModel<1> >::create("GaussModel"));
model->setInterpolationStep(interpolation_step_);
Param tmp;
tmp.setValue("bounding_box:min", min_);
tmp.setValue("bounding_box:max", max_);
tmp.setValue("statistics:variance", statistics_.variance());
tmp.setValue("statistics:mean", statistics_.mean());
model->setParameters(tmp);
}
else
{
model = static_cast<InterpolationModel*>(Factory<BaseModel<1> >::create("IsotopeModel"));
Param iso_param = this->param_.copy("isotope_model:", true);
iso_param.removeAll("stdev");
model->setParameters(iso_param);
model->setInterpolationStep(interpolation_step_);
Param tmp;
tmp.setValue("statistics:mean", statistics_.mean());
tmp.setValue("charge", static_cast<Int>(charge_));
tmp.setValue("isotope:mode:GaussianSD", isotope_stdev_);
tmp.setValue("isotope:maximum", max_isotope_);
model->setParameters(tmp);
(static_cast<IsotopeModel*>(model))->setSamples((static_cast<IsotopeModel*>(model))->getFormula());
}
// fit offset
QualityType quality;
quality = fitOffset_(model, set, stdev1_, stdev1_, interpolation_step_);
if (boost::math::isnan(quality))
quality = -1.0;
return quality;
}
BiGaussFitter1D::QualityType BiGaussFitter1D::fit1d(const RawDataArrayType& set, InterpolationModel*& model)
{
// Calculate bounding box
CoordinateType min_bb = set[0].getPos(), max_bb = set[0].getPos();
for (UInt pos = 1; pos < set.size(); ++pos)
{
CoordinateType tmp = set[pos].getPos();
if (min_bb > tmp)
min_bb = tmp;
if (max_bb < tmp)
max_bb = tmp;
}
// Enlarge the bounding box by a few multiples of the standard deviation
const CoordinateType stdev1 = sqrt(statistics1_.variance()) * tolerance_stdev_box_;
const CoordinateType stdev2 = sqrt(statistics2_.variance()) * tolerance_stdev_box_;
min_bb -= stdev1;
max_bb += stdev2;
// build model
model = static_cast<InterpolationModel*>(Factory<BaseModel<1> >::create("BiGaussModel"));
model->setInterpolationStep(interpolation_step_);
Param tmp;
tmp.setValue("bounding_box:min", min_bb);
tmp.setValue("bounding_box:max", max_bb);
tmp.setValue("statistics:mean", statistics1_.mean());
tmp.setValue("statistics:variance1", statistics1_.variance());
tmp.setValue("statistics:variance2", statistics2_.variance());
model->setParameters(tmp);
// fit offset
QualityType quality;
quality = fitOffset_(model, set, stdev1, stdev2, interpolation_step_);
if (boost::math::isnan(quality))
quality = -1.0;
return quality;
}
ExtendedIsotopeFitter1D::QualityType ExtendedIsotopeFitter1D::fit1d(const RawDataArrayType & set, InterpolationModel * & model)
{
// build model
if (charge_ == 0)
{
// Calculate bounding box
min_ = max_ = set[0].getPos();
for (UInt pos = 1; pos < set.size(); ++pos)
{
CoordinateType tmp = set[pos].getPos();
if (min_ > tmp)
min_ = tmp;
if (max_ < tmp)
max_ = tmp;
}
// Enlarge the bounding box by a few multiples of the standard deviation
{
stdev1_ = sqrt(statistics_.variance()) * tolerance_stdev_box_;
min_ -= stdev1_;
max_ += stdev1_;
}
model = static_cast<InterpolationModel *>(Factory<BaseModel<1> >::create("GaussModel"));
model->setInterpolationStep(interpolation_step_);
Param tmp;
tmp.setValue("bounding_box:min", min_);
tmp.setValue("bounding_box:max", max_);
tmp.setValue("statistics:variance", statistics_.variance());
tmp.setValue("statistics:mean", statistics_.mean());
model->setParameters(tmp);
}
else
{
model = static_cast<InterpolationModel *>(Factory<BaseModel<1> >::create("ExtendedIsotopeModel"));
Param iso_param = this->param_.copy("isotope_model:", true);
iso_param.removeAll("stdev");
model->setParameters(iso_param);
model->setInterpolationStep(interpolation_step_);
Param tmp;
tmp.setValue("isotope:monoisotopic_mz", monoisotopic_mz_);
tmp.setValue("charge", static_cast<Int>(charge_));
tmp.setValue("isotope:stdev", isotope_stdev_);
tmp.setValue("isotope:maximum", max_isotope_);
model->setParameters(tmp);
}
// calculate pearson correlation
std::vector<Real> real_data;
real_data.reserve(set.size());
std::vector<Real> model_data;
model_data.reserve(set.size());
for (Size i = 0; i < set.size(); ++i)
{
real_data.push_back(set[i].getIntensity());
model_data.push_back(model->getIntensity(DPosition<1>(set[i].getPosition())));
}
QualityType correlation = Math::pearsonCorrelationCoefficient(real_data.begin(), real_data.end(), model_data.begin(), model_data.end());
if (boost::math::isnan(correlation))
correlation = -1.0;
return correlation;
}
