LocalLinearMap

class pyopenms.LocalLinearMap

Bases: object

Cython implementation of _LocalLinearMap

Original C++ documentation is available here

Trained Local Linear Map (LLM) model for peak intensity prediction

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__(self) → None

Methods

__init__(self)
getCodebooks(self)	Returns position of the codebook vectors (18-dim)
getLLMParam(self)	Returns parameters of the LocalLinearMap model
getMatrixA(self)	Returns linear mappings of the codebooks
getVectorWout(self)	Returns linear bias
normalizeVector(self, aaIndexVariables)	Calculates and returns the normalized amino acid index variables from string representation of peptide

getCodebooks(self) → MatrixDouble

Returns position of the codebook vectors (18-dim)

getLLMParam(self) → LLMParam

Returns parameters of the LocalLinearMap model

getMatrixA(self) → MatrixDouble

Returns linear mappings of the codebooks

getVectorWout(self) → List[float]

Returns linear bias

normalizeVector(self, aaIndexVariables: List[float]) → None

Calculates and returns the normalized amino acid index variables from string representation of peptide