本文整理汇总了C++中PeakSpectrum::back方法的典型用法代码示例。如果您正苦于以下问题：C++ PeakSpectrum::back方法的具体用法？C++ PeakSpectrum::back怎么用？C++ PeakSpectrum::back使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类PeakSpectrum的用法示例。
在下文中一共展示了PeakSpectrum::back方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: window_upper_bound
std::vector<PeakSpectrum> AScore::peakPickingPerWindowsInSpectrum_(PeakSpectrum &real_spectrum) const
{
vector<PeakSpectrum> windows_top10;
double spect_lower_bound = floor(real_spectrum.front().getMZ() / 100) * 100;
double spect_upper_bound = ceil(real_spectrum.back().getMZ() / 100) * 100;
Size number_of_windows = static_cast<Size>(ceil((spect_upper_bound - spect_lower_bound) / 100));
windows_top10.resize(number_of_windows);
PeakSpectrum::Iterator it_current_peak = real_spectrum.begin();
Size window_upper_bound(spect_lower_bound + 100);
for (Size current_window = 0; current_window < number_of_windows; ++current_window)
{
PeakSpectrum real_window;
while (((*it_current_peak).getMZ() <= window_upper_bound) && (it_current_peak < real_spectrum.end()))
{
real_window.push_back(*it_current_peak);
++it_current_peak;
}
real_window.sortByIntensity(true);
for (Size i = 0; (i < 10) & (i < real_window.size()); ++i)
{
windows_top10[current_window].push_back(real_window[i]);
}
window_upper_bound += 100;
}
return windows_top10;
}示例2: logOccupancyProb
double XQuestScores::logOccupancyProb(const PeakSpectrum& theoretical_spec, const Size matched_size, double fragment_mass_tolerance, bool fragment_mass_tolerance_unit_ppm)
{
using boost::math::binomial;
Size theo_size = theoretical_spec.size();
if (matched_size < 1 || theo_size < 1)
{
return 0;
}
double range;
double used_tolerance;
if (fragment_mass_tolerance_unit_ppm)
{
range = std::log(theoretical_spec.back().getMZ()) - std::log(theoretical_spec[0].getMZ());
used_tolerance = fragment_mass_tolerance / 1e6;
}
else
{
range = theoretical_spec.back().getMZ() - theoretical_spec[0].getMZ();
used_tolerance = fragment_mass_tolerance;
}
// A priori probability of a random match given info about the theoretical spectrum
double a_priori_p = 0;
a_priori_p = 1 - pow(1 - 2 * used_tolerance / range, static_cast<double>(theo_size));
double log_occu_prob = 0;
binomial flip(theo_size, a_priori_p);
// min double number to avoid 0 values, causing scores with the value "inf"
log_occu_prob = -log(1 - cdf(flip, matched_size) + std::numeric_limits<double>::min());
// score lower than 0 does not make sense, but can happen, if cfd = 0, then -log( 1 + <double>::min() ) < 0
if (log_occu_prob >= 0.0)
{
return log_occu_prob;
}
else // underflow warning?
{
return 0;
}
}