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 | |
| virtual | ~LocalLinearMap () |
| destructor | |
| const LLMParam & | getLLMParam () const |
| return parameters of the LocalLinearMap model | |
| const Matrix< DoubleReal > & | getCodebooks () const |
| return position of the codebook vectors (18-dim) | |
| const Matrix< DoubleReal > & | getMatrixA () const |
| return linear mappings of the codebooks | |
| const std::vector< DoubleReal > & | getVectorWout () const |
| return linear bias | |
| const Matrix< UInt > & | getCord () const |
| return coordinates of codebook vectors on the 2-d grid | |
| void | normalizeVector (std::vector< DoubleReal > &aaIndexVariables) |
| calculate and return normalized amino acid index variables from string representation of peptide | |
| std::vector< DoubleReal > | neigh (const Matrix< UInt > &cord, Size win, DoubleReal radius) |
| calculate neighborhood function based on distance of prototypes to winner prototype on two-dimensional grid structure and neighborhood width. | |
Private Member Functions | |
| Matrix< UInt > | genCord_ (Size xdim, Size ydim) |
| needed to store prototype coordinates | |
| DoubleReal | dist_ (const Matrix< UInt > &u, const Matrix< UInt > &v, Size a, Size b) |
| calculate distance between two prototypes | |
| LocalLinearMap (LocalLinearMap &rhs) | |
| Copy constructor not implemented => private. | |
| LocalLinearMap & | operator= (const LocalLinearMap &llm) |
| Assignment operator not implemented => private. | |
Private Attributes | |
| LLMParam | param_ |
| parameters of the model | |
| Matrix< DoubleReal > | code_ |
| codebook vectors | |
| Matrix< DoubleReal > | A_ |
| linear mappings | |
| std::vector< DoubleReal > | wout_ |
| linear bias | |
| Matrix< UInt > | cord_ |
| coordinates of codebooks on grid | |
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
| virtual ~LocalLinearMap | ( | ) | [virtual] |
destructor
| LocalLinearMap | ( | LocalLinearMap & | rhs | ) | [private] |
Copy constructor not implemented => private.
calculate distance between two prototypes
| const Matrix<DoubleReal>& getCodebooks | ( | ) | const |
return position of the codebook vectors (18-dim)
| const LLMParam& getLLMParam | ( | ) | const |
return parameters of the LocalLinearMap model
| const Matrix<DoubleReal>& getMatrixA | ( | ) | const |
return linear mappings of the codebooks
| const std::vector<DoubleReal>& getVectorWout | ( | ) | const |
return linear bias
| std::vector<DoubleReal> neigh | ( | const Matrix< UInt > & | cord, | |
| Size | win, | |||
| DoubleReal | radius | |||
| ) |
calculate neighborhood function based on distance of prototypes to winner prototype on two-dimensional grid structure and neighborhood width.
| void normalizeVector | ( | std::vector< DoubleReal > & | aaIndexVariables | ) |
calculate and return normalized amino acid index variables from string representation of peptide
| LocalLinearMap& operator= | ( | const LocalLinearMap & | llm | ) | [private] |
Assignment operator not implemented => private.
Matrix<DoubleReal> A_ [private] |
linear mappings
Matrix<DoubleReal> code_ [private] |
codebook vectors
std::vector<DoubleReal> wout_ [private] |
linear bias
| OpenMS / TOPP release 1.10.0 | Documentation generated on Thu Mar 7 2013 09:42:50 using doxygen 1.7.1 |