OpenMS
2.4.0
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Trained Local Linear Map (LLM) model for peak intensity prediction. More...
#include <OpenMS/ANALYSIS/PIP/LocalLinearMap.h>
Classes | |
struct | LLMParam |
Define parameters needed by the Local Linear Map (LLM) model. More... | |
Public Member Functions | |
LocalLinearMap () | |
default constructor More... | |
virtual | ~LocalLinearMap () |
destructor More... | |
const LLMParam & | getLLMParam () const |
return parameters of the LocalLinearMap model More... | |
const Matrix< double > & | getCodebooks () const |
return position of the codebook vectors (18-dim) More... | |
const Matrix< double > & | getMatrixA () const |
return linear mappings of the codebooks More... | |
const std::vector< double > & | getVectorWout () const |
return linear bias More... | |
const Matrix< UInt > & | getCord () const |
return coordinates of codebook vectors on the 2-d grid More... | |
void | normalizeVector (std::vector< double > &aaIndexVariables) |
calculate and return normalized amino acid index variables from string representation of peptide More... | |
std::vector< double > | neigh (const Matrix< UInt > &cord, Size win, double radius) |
calculate neighborhood function based on distance of prototypes to winner prototype on two-dimensional grid structure and neighborhood width. More... | |
Private Member Functions | |
Matrix< UInt > | genCord_ (Size xdim, Size ydim) |
needed to store prototype coordinates More... | |
double | dist_ (const Matrix< UInt > &u, const Matrix< UInt > &v, Size a, Size b) |
calculate distance between two prototypes More... | |
LocalLinearMap (LocalLinearMap &rhs) | |
Copy constructor not implemented => private. More... | |
LocalLinearMap & | operator= (const LocalLinearMap &llm) |
Assignment operator not implemented => private. More... | |
Private Attributes | |
LLMParam | param_ |
parameters of the model More... | |
Matrix< double > | code_ |
codebook vectors More... | |
Matrix< double > | A_ |
linear mappings More... | |
std::vector< double > | wout_ |
linear bias More... | |
Matrix< UInt > | cord_ |
coordinates of codebooks on grid More... | |
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.
LocalLinearMap | ( | ) |
default constructor
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virtual |
destructor
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private |
Copy constructor not implemented => private.
calculate distance between two prototypes
const LLMParam& getLLMParam | ( | ) | const |
return parameters of the LocalLinearMap model
const std::vector<double>& getVectorWout | ( | ) | const |
return linear bias
calculate neighborhood function based on distance of prototypes to winner prototype on two-dimensional grid structure and neighborhood width.
void normalizeVector | ( | std::vector< double > & | aaIndexVariables | ) |
calculate and return normalized amino acid index variables from string representation of peptide
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private |
Assignment operator not implemented => private.
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private |
parameters of the model
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private |
linear bias