LocalLinearMap

class pyopenms.LocalLinearMap

Bases: object

Cython implementation of _LocalLinearMap

Documentation is available at http://www.openms.de/current_doxygen/html/classOpenMS_1_1LocalLinearMap.html

This class offers a model for predictions of peptide peak heights (referred to as intensities) by a Local Linear Map (LLM) model and is the basis of PeakIntensityPredictor —– A general introduction to the Peak Intensity Predictor (PIP) can be found in the PIP Tutorial —– The model trained needs two files for storing the position of the codebook vectors and the linear mappings (codebooks.data, linearMapping.data) This is the default model used by PeakIntensityPredictor

__init__()

Cython signature: void LocalLinearMap()

Methods

__init__	Cython signature: void LocalLinearMap()
getCodebooks	Cython signature: MatrixDouble getCodebooks() Returns position of the codebook vectors (18-dim)
getLLMParam	Cython signature: LLMParam getLLMParam() Returns parameters of the LocalLinearMap model
getMatrixA	Cython signature: MatrixDouble getMatrixA() Returns linear mappings of the codebooks
getVectorWout	Cython signature: libcpp_vector[double] getVectorWout() Returns linear bias
normalizeVector	Cython signature: void normalizeVector(libcpp_vector[double] & aaIndexVariables) Calculates and returns the normalized amino acid index variables from string representation of peptide

getCodebooks()

Cython signature: MatrixDouble getCodebooks() Returns position of the codebook vectors (18-dim)

getLLMParam()

Cython signature: LLMParam getLLMParam() Returns parameters of the LocalLinearMap model

getMatrixA()

Cython signature: MatrixDouble getMatrixA() Returns linear mappings of the codebooks

getVectorWout()

Cython signature: libcpp_vector[double] getVectorWout() Returns linear bias

normalizeVector()

Cython signature: void normalizeVector(libcpp_vector[double] & aaIndexVariables) Calculates and returns the normalized amino acid index variables from string representation of peptide