PosteriorErrorProbabilityModel

class pyopenms.PosteriorErrorProbabilityModel

Bases: object

Cython implementation of _PosteriorErrorProbabilityModel

Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS::Math_1_1PosteriorErrorProbabilityModel.html

– Inherits from [‘DefaultParamHandler’]

__init__()

Cython signature: void PosteriorErrorProbabilityModel()

Methods

__init__	Cython signature: void PosteriorErrorProbabilityModel()
computeLogLikelihood	Cython signature: double computeLogLikelihood(libcpp_vector[double] & incorrect_density, libcpp_vector[double] & correct_density) Computes the Maximum Likelihood with a log-likelihood function
computeProbability	Cython signature: double computeProbability(double score) Returns the computed posterior error probability for a given score
fillDensities	Cython signature: void fillDensities(libcpp_vector[double] & x_scores, libcpp_vector[double] & incorrect_density, libcpp_vector[double] & correct_density) Writes the distributions densities into the two vectors for a set of scores.
fillLogDensities	Cython signature: void fillLogDensities(libcpp_vector[double] & x_scores, libcpp_vector[double] & incorrect_density, libcpp_vector[double] & correct_density) Writes the log distributions densities into the two vectors for a set of scores.
fit	Cython signature: bool fit(libcpp_vector[double] & search_engine_scores, String outlier_handling)
getBothGnuplotFormula	Cython signature: String getBothGnuplotFormula(GaussFitResult & incorrect, GaussFitResult & correct) Returns the gnuplot formula of the fitted mixture distribution
getCorrectlyAssignedFitResult	Cython signature: GaussFitResult getCorrectlyAssignedFitResult() Returns estimated parameters for correctly assigned sequences.
getDefaults	Cython signature: Param getDefaults() Returns the default parameters
getGaussGnuplotFormula	Cython signature: String getGaussGnuplotFormula(GaussFitResult & params) Returns the gnuplot formula of the fitted gauss distribution
getGumbelGnuplotFormula	Cython signature: String getGumbelGnuplotFormula(GaussFitResult & params) Returns the gnuplot formula of the fitted gumbel distribution
getIncorrectlyAssignedFitResult	Cython signature: GaussFitResult getIncorrectlyAssignedFitResult() Returns estimated parameters for correctly assigned sequences.
getName	Cython signature: String getName() Returns the name
getNegativePrior	Cython signature: double getNegativePrior() Returns the estimated negative prior probability
getParameters	Cython signature: Param getParameters() Returns the parameters
getSmallestScore	Cython signature: double getSmallestScore() Returns the smallest score used in the last fit
getSubsections	Cython signature: libcpp_vector[String] getSubsections()
initPlots	Cython signature: TextFile initPlots(libcpp_vector[double] & x_scores) Initializes the plots
plotTargetDecoyEstimation	Cython signature: void plotTargetDecoyEstimation(libcpp_vector[double] & target, libcpp_vector[double] & decoy) Plots the estimated distribution against target and decoy hits
pos_neg_mean_weighted_posteriors	Cython signature: libcpp_pair[double,double] pos_neg_mean_weighted_posteriors(libcpp_vector[double] & x_scores, libcpp_vector[double] & incorrect_posteriors)
setName	Cython signature: void setName(const String &) Sets the name
setParameters	Cython signature: void setParameters(Param & param) Sets the parameters
tryGnuplot	Cython signature: void tryGnuplot(const String & gp_file)

computeLogLikelihood()

Cython signature: double computeLogLikelihood(libcpp_vector[double] & incorrect_density, libcpp_vector[double] & correct_density) Computes the Maximum Likelihood with a log-likelihood function

computeProbability()

Cython signature: double computeProbability(double score) Returns the computed posterior error probability for a given score

fillDensities()

Cython signature: void fillDensities(libcpp_vector[double] & x_scores, libcpp_vector[double] & incorrect_density, libcpp_vector[double] & correct_density) Writes the distributions densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences

fillLogDensities()

Cython signature: void fillLogDensities(libcpp_vector[double] & x_scores, libcpp_vector[double] & incorrect_density, libcpp_vector[double] & correct_density) Writes the log distributions densities into the two vectors for a set of scores. Incorrect_densities represent the incorrectly assigned sequences

fit()

• Cython signature: bool fit(libcpp_vector[double] & search_engine_scores, String outlier_handling)

Fits the distributions to the data points(search_engine_scores). Estimated parameters for the distributions are saved in member variables computeProbability can be used afterwards Uses two Gaussians to fit. And Gauss+Gauss or Gumbel+Gauss to plot and calculate final probabilities —– :param search_engine_scores: A vector which holds the data points :returns: true if algorithm has run through. Else false will be returned. In that case no plot and no probabilities are calculated

• Cython signature: bool fit(libcpp_vector[double] & search_engine_scores, libcpp_vector[double] & probabilities, String outlier_handling)

Fits the distributions to the data points(search_engine_scores). Estimated parameters for the distributions are saved in member variables computeProbability can be used afterwards Uses two Gaussians to fit. And Gauss+Gauss or Gumbel+Gauss to plot and calculate final probabilities —– :param search_engine_scores: A vector which holds the data points :param probabilities a vector which holds the probability for each data point after running this function. If it has some content it will be overwritten :returns: true if algorithm has run through. Else false will be returned. In that case no plot and no probabilities are calculated

getBothGnuplotFormula()

Cython signature: String getBothGnuplotFormula(GaussFitResult & incorrect, GaussFitResult & correct) Returns the gnuplot formula of the fitted mixture distribution

getCorrectlyAssignedFitResult()

Cython signature: GaussFitResult getCorrectlyAssignedFitResult() Returns estimated parameters for correctly assigned sequences. Fit should be used before

getDefaults()

Cython signature: Param getDefaults() Returns the default parameters

getGaussGnuplotFormula()

Cython signature: String getGaussGnuplotFormula(GaussFitResult & params) Returns the gnuplot formula of the fitted gauss distribution

getGumbelGnuplotFormula()

Cython signature: String getGumbelGnuplotFormula(GaussFitResult & params) Returns the gnuplot formula of the fitted gumbel distribution

getIncorrectlyAssignedFitResult()

Cython signature: GaussFitResult getIncorrectlyAssignedFitResult() Returns estimated parameters for correctly assigned sequences. Fit should be used before

getName()

Cython signature: String getName() Returns the name

getNegativePrior()

Cython signature: double getNegativePrior() Returns the estimated negative prior probability

getParameters()

Cython signature: Param getParameters() Returns the parameters

getSmallestScore()

Cython signature: double getSmallestScore() Returns the smallest score used in the last fit

getSubsections()

Cython signature: libcpp_vector[String] getSubsections()

initPlots()

Cython signature: TextFile initPlots(libcpp_vector[double] & x_scores) Initializes the plots

plotTargetDecoyEstimation()

Cython signature: void plotTargetDecoyEstimation(libcpp_vector[double] & target, libcpp_vector[double] & decoy) Plots the estimated distribution against target and decoy hits

pos_neg_mean_weighted_posteriors()

Cython signature: libcpp_pair[double,double] pos_neg_mean_weighted_posteriors(libcpp_vector[double] & x_scores, libcpp_vector[double] & incorrect_posteriors)

setName()

Cython signature: void setName(const String &) Sets the name

setParameters()

Cython signature: void setParameters(Param & param) Sets the parameters

tryGnuplot()

Cython signature: void tryGnuplot(const String & gp_file)