portelli/LatAnalyze
1
0
Fork 0
mirror of https://github.com/aportelli/LatAnalyze.git synced 2025-06-22 00:42:02 +01:00
Code Releases Activity

significant optimisation of covariance routines + checks

Browse Source
This commit is contained in:
Antonin Portelli
2021-12-20 01:25:13 +01:00
parent c796187d1e
commit 57c6004797
4 changed files with 288 additions and 33 deletions
Download Patch File Download Diff File Expand all files Collapse all files

119
lib/Statistics/StatArray.hpp
View File

@ -51,14 +51,17 @@ public:
const T & operator[](const Index s) const;
// statistics
void bin(Index binSize);
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 covariance(const StatArray<T, os> &array, const Index pos = 0,
const Index n = -1) const;
T covarianceMatrix(const StatArray<T, os> &array, const Index pos = 0,
T covarianceOld(const StatArray<T, os> &array) const;
T covariance(const StatArray<T, os> &array) const;
T covarianceMatrixOld(const StatArray<T, os> &array, const Index pos = 0,
const Index n = -1) const;
T variance(const Index pos = 0, const Index n = -1) const;
T varianceMatrix(const Index pos = 0, const Index n = -1) const;
T correlationMatrix(const Index pos = 0, const Index n = -1) const;
T varianceOld(void) const;
T variance(void) const;
T varianceMatrixOld(const Index pos = 0, const Index n = -1) const;
T correlationMatrixOld(const Index pos = 0, const Index n = -1) const;
// IO type
virtual IoType getType(void) const;
public:
@ -66,7 +69,7 @@ public:
};
// reduction operations
namespace ReducOp
namespace StatOp
{
// general templates
template <typename T>
@ -149,42 +152,82 @@ void StatArray<T, os>::bin(Index binSize)
}
template <typename T, Index os>
T StatArray<T, os>::mean(const Index pos, const Index n) const
T StatArray<T, os>::meanOld(const Index pos, const Index n) const
{
T result = T();
const Index m = (n >= 0) ? n : size();
if (m)
{
result = this->segment(pos+os, m).redux(&ReducOp::sum<T>);
result = this->segment(pos+os, m).redux(&StatOp::sum<T>);
}
return result/static_cast<double>(m);
}
template <typename T, Index os>
T StatArray<T, os>::covariance(const StatArray<T, os> &array, const Index pos,
const Index n) const
T StatArray<T, os>::sum(const Index pos, const Index n) const
{
T result;
const Index m = (n >= 0) ? n : size();
result = (*this)[pos];
for (Index i = pos + 1; i < pos + m; ++i)
{
result += (*this)[i];
}
return result;
}
template <typename T, Index os>
T StatArray<T, os>::mean(const Index pos, const Index n) const
{
const Index m = (n >= 0) ? n : size();
return sum(pos, n)/static_cast<double>(m);
}
template <typename T, Index os>
T StatArray<T, os>::covarianceOld(const StatArray<T, os> &array) const
{
T s1, s2, prs, res = T();
const Index m = (n >= 0) ? n : size();
const Index m = size();
if (m)
{
auto arraySeg = array.segment(pos+os, m);
auto thisSeg = this->segment(pos+os, m);
auto arraySeg = array.segment(os, m);
auto thisSeg = this->segment(os, m);
s1 = thisSeg.redux(&ReducOp::sum<T>);
s2 = arraySeg.redux(&ReducOp::sum<T>);
prs = thisSeg.binaryExpr(arraySeg, &ReducOp::prod<T>)
.redux(&ReducOp::sum<T>);
res = prs - ReducOp::prod(s1, s2)/static_cast<double>(m);
s1 = thisSeg.redux(&StatOp::sum<T>);
s2 = arraySeg.redux(&StatOp::sum<T>);
prs = thisSeg.binaryExpr(arraySeg, &StatOp::prod<T>)
.redux(&StatOp::sum<T>);
res = prs - StatOp::prod(s1, s2)/static_cast<double>(m);
}
return res/static_cast<double>(m - 1);
}
template <typename T, Index os>
T StatArray<T, os>::covarianceMatrix(const StatArray<T, os> &array,
T StatArray<T, os>::covariance(const StatArray<T, os> &array) const
{
T s1, s2, res;
s1 = array.sum();
s2 = this->sum();
res = StatOp::prod<T>(array[0], (*this)[0]);
for (Index i = 1; i < size(); ++i)
{
res += StatOp::prod<T>(array[i], (*this)[i]);
}
res -= StatOp::prod<T>(s1, s2)/static_cast<double>(size());
res /= static_cast<double>(size() - 1);
return res;
}
template <typename T, Index os>
T StatArray<T, os>::covarianceMatrixOld(const StatArray<T, os> &array,
const Index pos, const Index n) const
{
T s1, s2, prs, res = T();
@ -195,32 +238,38 @@ T StatArray<T, os>::covarianceMatrix(const StatArray<T, os> &array,
auto arraySeg = array.segment(pos+os, m);
auto thisSeg = this->segment(pos+os, m);
s1 = thisSeg.redux(&ReducOp::sum<T>);
s2 = arraySeg.redux(&ReducOp::sum<T>);
prs = thisSeg.binaryExpr(arraySeg, &ReducOp::tensProd<T>)
.redux(&ReducOp::sum<T>);
res = prs - ReducOp::tensProd(s1, s2)/static_cast<double>(m);
s1 = thisSeg.redux(&StatOp::sum<T>);
s2 = arraySeg.redux(&StatOp::sum<T>);
prs = thisSeg.binaryExpr(arraySeg, &StatOp::tensProd<T>)
.redux(&StatOp::sum<T>);
res = prs - StatOp::tensProd(s1, s2)/static_cast<double>(m);
}
return res/static_cast<double>(m - 1);
}
template <typename T, Index os>
T StatArray<T, os>::variance(const Index pos, const Index n) const
T StatArray<T, os>::variance(void) const
{
return covariance(*this, pos, n);
return covariance(*this);
}
template <typename T, Index os>
T StatArray<T, os>::varianceMatrix(const Index pos, const Index n) const
T StatArray<T, os>::varianceOld(void) const
{
return covarianceMatrix(*this, pos, n);
return covarianceOld(*this);
}
template <typename T, Index os>
T StatArray<T, os>::correlationMatrix(const Index pos, const Index n) const
T StatArray<T, os>::varianceMatrixOld(const Index pos, const Index n) const
{
T res = varianceMatrix(pos, n);
return covarianceMatrixOld(*this, pos, n);
}
template <typename T, Index os>
T StatArray<T, os>::correlationMatrixOld(const Index pos, const Index n) const
{
T res = varianceMatrixOld(pos, n);
T invDiag(res.rows(), 1);
invDiag = res.diagonal();
@ -231,8 +280,14 @@ T StatArray<T, os>::correlationMatrix(const Index pos, const Index n) const
}
// reduction operations ////////////////////////////////////////////////////////
namespace ReducOp
namespace StatOp
{
template <typename T>
inline void zero(T &a)
{
a = 0.;
}
template <typename T>
inline T sum(const T &a, const T &b)
{