setQscore : quality score for PeakGroup. This class is being updated. For now, simply it calculate the setQscore using a fixed weight vector. The weight vector has been determined by logistic regression. But afterwards, the training part for the setQscore should be added in here. Or other technique such as deep learning would be used. This class also contains tsv output function. The tsv file contains features of PeakGroups which are used for training.
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#include <OpenMS/ANALYSIS/TOPDOWN/Qscore.h>
setQscore : quality score for PeakGroup. This class is being updated. For now, simply it calculate the setQscore using a fixed weight vector. The weight vector has been determined by logistic regression. But afterwards, the training part for the setQscore should be added in here. Or other technique such as deep learning would be used. This class also contains tsv output function. The tsv file contains features of PeakGroups which are used for training.
◆ LogMzPeak
◆ getQscore()
| static double getQscore |
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const PeakGroup * |
pg, |
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bool |
is_profile = false, |
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double |
cv = -1 |
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) |
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static |
get QScore for a peak group of specific abs_charge
◆ toFeatureVector_()
| static std::vector<double> toFeatureVector_ |
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const PeakGroup * |
pg | ) |
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staticprivate |
convert a peak group to a feature vector for setQscore calculation
◆ writeAttCsvFromDummy()
| static void writeAttCsvFromDummy |
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const DeconvolvedSpectrum & |
deconvolved_spectrum, |
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std::fstream & |
f |
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) |
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static |
◆ writeAttCsvFromDummyHeader()
| static void writeAttCsvFromDummyHeader |
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std::fstream & |
f | ) |
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static |
◆ weight_centroid_
| std::vector<double> weight_centroid_ |
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staticprivate |
◆ weight_CV_
| std::vector<double> weight_CV_ |
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staticprivate |
◆ weight_profile_
| std::vector<double> weight_profile_ |
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staticprivate |