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moving covariance matrix to StatArray

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This commit is contained in:
Antonin Portelli 2024-01-19 22:39:16 -03:00
parent fde57d79f3
commit 83e09b82fc
2 changed files with 37 additions and 39 deletions
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36
lib/Statistics/MatSample.hpp
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@ -103,8 +103,6 @@ public:
const Index nCol); const Index nCol);
// resize all matrices // resize all matrices
void resizeMat(const Index nRow, const Index nCol); void resizeMat(const Index nRow, const Index nCol);
// covariance matrix
Mat<T> covarianceMatrix(const MatSample<T> &sample) const;
}; };
// non-member operators // non-member operators
@ -381,40 +379,6 @@ void MatSample<T>::resizeMat(const Index nRow, const Index nCol)
} }
} }
// covariance matrix ///////////////////////////////////////////////////////////
template <typename T>
Mat<T> MatSample<T>::covarianceMatrix(const MatSample<T> &sample) const
{
if (((*this)[central].cols() != 1) or (sample[central].cols() != 1))
{
LATAN_ERROR(Size, "samples have more than one column");
}
Index n1 = (*this)[central].rows(), n2 = sample[central].rows();
Index nSample = this->size();
Mat<T> tmp1(n1, nSample), tmp2(n2, nSample), res(n1, n2);
Mat<T> s1(n1, 1), s2(n2, 1), one(nSample, 1);
one.fill(1.);
s1.fill(0.);
s2.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);
for (unsigned int s = 0; s < nSample; ++s)
{
s2 += sample[s];
tmp2.col(s) = sample[s];
}
tmp2 -= s2*one.transpose()/static_cast<double>(nSample);
res = tmp1*tmp2.transpose()/static_cast<double>(nSample - 1);
return res;
}
END_LATAN_NAMESPACE END_LATAN_NAMESPACE
#endif // Latan_MatSample_hpp_ #endif // Latan_MatSample_hpp_

36
lib/Statistics/StatArray.hpp
View File

@ -52,10 +52,10 @@ public:
// statistics // statistics
void bin(Index binSize); void bin(Index binSize);
T sum(const Index pos = 0, const Index n = -1) const; T sum(const Index pos = 0, const Index n = -1) const;
T meanOld(const Index pos = 0, const Index n = -1) const;
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 covarianceMatrix(const StatArray<T, os> &data) const;
T varianceMatrix(void) const; T varianceMatrix(void) const;
T correlationMatrix(void) const; T correlationMatrix(void) const;
@ -195,6 +195,40 @@ T StatArray<T, os>::variance(void) const
return covariance(*this); return covariance(*this);
} }
template <typename MatType, Index os>
MatType StatArray<MatType, os>::covarianceMatrix(
const StatArray<MatType, os> &data) const
{
if (((*this)[central].cols() != 1) or (data[central].cols() != 1))
{
LATAN_ERROR(Size, "samples have more than one column");
}
Index n1 = (*this)[central].rows(), n2 = data[central].rows();
Index nSample = this->size();
MatType tmp1(n1, nSample), tmp2(n2, nSample), res(n1, n2);
MatType s1(n1, 1), s2(n2, 1), one(nSample, 1);
one.fill(1.);
s1.fill(0.);
s2.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);
for (unsigned int s = 0; s < nSample; ++s)
{
s2 += data[s];
tmp2.col(s) = data[s];
}
tmp2 -= s2*one.transpose()/static_cast<double>(nSample);
res = tmp1*tmp2.transpose()/static_cast<double>(nSample - 1);
return res;
}
template <typename MatType, Index os> template <typename MatType, Index os>
MatType StatArray<MatType, os>::varianceMatrix(void) const MatType StatArray<MatType, os>::varianceMatrix(void) const
{ {