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#include <CommonTools/Statistics/interface/RandomMultiGauss.h>
Public Member Functions | |
| AlgebraicVector | fire () |
| Generation of a vector of random numbers. | |
| RandomMultiGauss (const AlgebraicSymMatrix &aMatrix) | |
| constructor with covariance matrix only (all means = 0) | |
| RandomMultiGauss (const AlgebraicVector &aVector, const AlgebraicSymMatrix &aMatrix) | |
| constructor with explicit vector of mean values | |
| ~RandomMultiGauss () | |
Private Member Functions | |
| void | initialise (const AlgebraicSymMatrix &) |
| generation of the cholesky decomposition | |
Private Attributes | |
| AlgebraicVector | theMeans |
| int | theSize |
| AlgebraicMatrix | theTriangle |
Generates vectors of random numbers given a vector of mean values (optional) and a covariance matrix. Will accept empty rows/columns in the input matrix. Uses RandGauss with default engine for generation.
Definition at line 14 of file RandomMultiGauss.h.
| RandomMultiGauss::RandomMultiGauss | ( | const AlgebraicVector & | aVector, | |
| const AlgebraicSymMatrix & | aMatrix | |||
| ) |
constructor with explicit vector of mean values
Definition at line 9 of file RandomMultiGauss.cc.
References initialise(), theMeans, and theSize.
00009 : 00010 theSize(aMatrix.num_row()), 00011 theMeans(aVector), 00012 theTriangle(theSize,theSize,0) { 00013 // 00014 // Check consistency 00015 // 00016 if ( theMeans.num_row() == theSize ) { 00017 initialise(aMatrix); 00018 } 00019 else { 00020 // throw DetLogicError("RandomMultiGauss: size of vector and matrix do not match"); 00021 theMeans = AlgebraicVector(theSize,0); 00022 } 00023 } //
| RandomMultiGauss::RandomMultiGauss | ( | const AlgebraicSymMatrix & | aMatrix | ) |
constructor with covariance matrix only (all means = 0)
Definition at line 27 of file RandomMultiGauss.cc.
References initialise().
00027 : 00028 theSize(aMatrix.num_row()), 00029 theMeans(theSize,0), 00030 theTriangle(theSize,theSize,0) { 00031 // 00032 initialise(aMatrix); 00033 } //
| RandomMultiGauss::~RandomMultiGauss | ( | ) | [inline] |
| AlgebraicVector RandomMultiGauss::fire | ( | ) |
Generation of a vector of random numbers.
Definition at line 74 of file RandomMultiGauss.cc.
References i, theMeans, theSize, and theTriangle.
00074 { 00075 AlgebraicVector vRandom(theSize,0); 00076 for ( int i=0; i<theSize; i++ ) { 00077 if ( theTriangle[i][i]!=0 ) 00078 vRandom[i] = RandGauss::shoot(); 00079 } 00080 return theTriangle*vRandom+theMeans; 00081 }
| void RandomMultiGauss::initialise | ( | const AlgebraicSymMatrix & | aMatrix | ) | [private] |
generation of the cholesky decomposition
Definition at line 37 of file RandomMultiGauss.cc.
References i1, i2, i3, funct::sqrt(), sum(), theSize, and theTriangle.
Referenced by RandomMultiGauss().
00037 { 00038 // 00039 // Cholesky decomposition with protection against empty rows/columns 00040 // 00041 for ( int i1=0; i1<theSize; i1++ ) { 00042 if ( fabs(aMatrix[i1][i1])<FLT_MIN ) continue; 00043 00044 for ( int i2=i1; i2<theSize; i2++ ) { 00045 if ( fabs(aMatrix[i2][i2])<FLT_MIN ) continue; 00046 00047 double sum = aMatrix[i2][i1]; 00048 for ( int i3=i1-1; i3>=0; i3-- ) { 00049 if ( fabs(aMatrix[i3][i3])<FLT_MIN ) continue; 00050 sum -= theTriangle[i1][i3]*theTriangle[i2][i3]; 00051 } 00052 00053 if ( i1==i2 ) { 00054 // 00055 // check for positive definite input matrix, but allow for effects 00056 // due to finite precision 00057 // 00058 if ( sum<=0 ) { 00059 // if ( sum<-FLT_MIN ) throw DetLogicError("RandomMultiGauss: input matrix is not positive definite"); 00060 sum = FLT_MIN; 00061 } 00062 theTriangle[i1][i1] = sqrt(sum); 00063 } 00064 else { 00065 theTriangle[i1][i2] = 0.; 00066 theTriangle[i2][i1] = sum / theTriangle[i1][i1]; 00067 } 00068 } 00069 } 00070 }
AlgebraicVector RandomMultiGauss::theMeans [private] |
int RandomMultiGauss::theSize [private] |
Definition at line 34 of file RandomMultiGauss.h.
Referenced by fire(), initialise(), and RandomMultiGauss().
AlgebraicMatrix RandomMultiGauss::theTriangle [private] |
1.5.4