portelli/LatAnalyze
1
0
Fork 0
mirror of https://github.com/aportelli/LatAnalyze.git synced 2025-04-11 03:20:46 +01:00
Code Releases Activity

moving variance matrix to StatArray

Browse Source
This commit is contained in:
Antonin Portelli 2024-01-19 22:36:29 -03:00
parent 145155f733
commit fde57d79f3
2 changed files with 42 additions and 41 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

41
lib/Statistics/MatSample.hpp
View File

@ -105,8 +105,6 @@ public:
void resizeMat(const Index nRow, const Index nCol); void resizeMat(const Index nRow, const Index nCol);
// covariance matrix // covariance matrix
Mat<T> covarianceMatrix(const MatSample<T> &sample) const; Mat<T> covarianceMatrix(const MatSample<T> &sample) const;
Mat<T> varianceMatrix(void) const;
Mat<T> correlationMatrix(void) const;
}; };
// non-member operators // non-member operators
@ -417,45 +415,6 @@ Mat<T> MatSample<T>::covarianceMatrix(const MatSample<T> &sample) const
return res; return res;
} }
template <typename T>
Mat<T> MatSample<T>::varianceMatrix(void) const
{
if ((*this)[central].cols() != 1)
{
LATAN_ERROR(Size, "samples have more than one column");
}
Index n1 = (*this)[central].rows();
Index nSample = this->size();
Mat<T> tmp1(n1, nSample), res(n1, n1);
Mat<T> s1(n1, 1), one(nSample, 1);
one.fill(1.);
s1.fill(0.);
for (unsigned int s = 0; s < nSample; ++s)
{
s1 += (*this)[s];
tmp1.col(s) = (*this)[s];
}
tmp1 -= s1*one.transpose()/static_cast<double>(nSample);
res = tmp1*tmp1.transpose()/static_cast<double>(nSample - 1);
return res;
}
template <typename T>
Mat<T> MatSample<T>::correlationMatrix(void) const
{
Mat<T> res = varianceMatrix();
Mat<T> invDiag(res.rows(), 1);
invDiag = res.diagonal();
invDiag = invDiag.cwiseInverse().cwiseSqrt();
res = (invDiag*invDiag.transpose()).cwiseProduct(res);
return res;
}
END_LATAN_NAMESPACE END_LATAN_NAMESPACE
#endif // Latan_MatSample_hpp_ #endif // Latan_MatSample_hpp_

42
lib/Statistics/StatArray.hpp
View File

@ -56,6 +56,9 @@ public:
T mean(const Index pos = 0, const Index n = -1) const; T mean(const Index pos = 0, const Index n = -1) const;
T covariance(const StatArray<T, os> &array) const; T covariance(const StatArray<T, os> &array) const;
T variance(void) const; T variance(void) const;
T varianceMatrix(void) const;
T correlationMatrix(void) const;
// IO type // IO type
virtual IoType getType(void) const; virtual IoType getType(void) const;
public: public:
@ -192,6 +195,45 @@ T StatArray<T, os>::variance(void) const
return covariance(*this); return covariance(*this);
} }
template <typename MatType, Index os>
MatType StatArray<MatType, os>::varianceMatrix(void) const
{
if ((*this)[0].cols() != 1)
{
LATAN_ERROR(Size, "samples have more than one column");
}
Index n1 = (*this)[0].rows();
Index nSample = this->size();
MatType tmp1(n1, nSample), res(n1, n1);
MatType s1(n1, 1), one(nSample, 1);
one.fill(1.);
s1.fill(0.);
for (unsigned int s = 0; s < nSample; ++s)
{
s1 += (*this)[s];
tmp1.col(s) = (*this)[s];
}
tmp1 -= s1*one.transpose()/static_cast<double>(nSample);
res = tmp1*tmp1.transpose()/static_cast<double>(nSample - 1);
return res;
}
template <typename MatType, Index os>
MatType StatArray<MatType, os>::correlationMatrix(void) const
{
MatType res = varianceMatrix();
MatType invDiag(res.rows(), 1);
invDiag = res.diagonal();
invDiag = invDiag.cwiseInverse().cwiseSqrt();
res = (invDiag*invDiag.transpose()).cwiseProduct(res);
return res;
}
// reduction operations //////////////////////////////////////////////////////// // reduction operations ////////////////////////////////////////////////////////
namespace StatOp namespace StatOp
{ {