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sparse module:

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* add row(i), col(i) functions
* add prune() function to remove small coefficients
This commit is contained in:
Gael Guennebaud 2009-01-21 18:46:04 +00:00
parent 25f1658fce
commit 52cf07d266
8 changed files with 138 additions and 17 deletions
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1
Eigen/src/Core/util/StaticAssert.h
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@ -72,6 +72,7 @@
INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION,
YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY,
THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES,
THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES,
INVALID_MATRIX_TEMPLATE_PARAMETERS
};
};

17
Eigen/src/Sparse/CompressedStorage.h
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@ -31,6 +31,7 @@
template<typename Scalar>
class CompressedStorage
{
typedef typename NumTraits<Scalar>::Real RealScalar;
public:
CompressedStorage()
: m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
@ -183,6 +184,22 @@ class CompressedStorage
}
return m_values[id];
}
void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
{
int k = 0;
int n = size();
for (int i=0; i<n; ++i)
{
if (!ei_isMuchSmallerThan(value(i), reference, epsilon))
{
value(k) = value(i);
index(k) = index(i);
++k;
}
}
resize(k,0);
}
protected:

10
Eigen/src/Sparse/DynamicSparseMatrix.h
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@ -74,7 +74,7 @@ class DynamicSparseMatrix
std::vector<CompressedStorage<Scalar> > m_data;
public:
inline int rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
inline int cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
inline int innerSize() const { return m_innerSize; }
@ -102,8 +102,6 @@ class DynamicSparseMatrix
return m_data[outer].atWithInsertion(inner);
}
public:
class InnerIterator;
inline void setZero()
@ -176,6 +174,12 @@ class DynamicSparseMatrix
/** Does nothing. Provided for compatibility with SparseMatrix. */
inline void endFill() {}
void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
{
for (int j=0; j<outerSize(); ++j)
m_data[j].prune(reference,epsilon);
}
/** Resize the matrix without preserving the data (the matrix is set to zero)
*/

34
Eigen/src/Sparse/SparseBlock.h
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@ -78,6 +78,40 @@ public:
}
};
/** \returns the i-th row of the matrix \c *this. For row-major matrix only. */
template<typename Derived>
SparseInnerVector<Derived> SparseMatrixBase<Derived>::row(int i)
{
EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
return innerVector(i);
}
/** \returns the i-th row of the matrix \c *this. For row-major matrix only.
* (read-only version) */
template<typename Derived>
const SparseInnerVector<Derived> SparseMatrixBase<Derived>::row(int i) const
{
EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
return innerVector(i);
}
/** \returns the i-th column of the matrix \c *this. For column-major matrix only. */
template<typename Derived>
SparseInnerVector<Derived> SparseMatrixBase<Derived>::col(int i)
{
EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
return innerVector(i);
}
/** \returns the i-th column of the matrix \c *this. For column-major matrix only.
* (read-only version) */
template<typename Derived>
const SparseInnerVector<Derived> SparseMatrixBase<Derived>::col(int i) const
{
EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
return innerVector(i);
}
/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
* is col-major (resp. row-major).
*/

24
Eigen/src/Sparse/SparseMatrix.h
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@ -69,11 +69,11 @@ class SparseMatrix
int* m_outerIndex;
CompressedStorage<Scalar> m_data;
public:
inline int rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
inline int cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
inline int innerSize() const { return m_innerSize; }
inline int outerSize() const { return m_outerSize; }
inline int innerNonZeros(int j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
@ -230,6 +230,28 @@ class SparseMatrix
++i;
}
}
void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
{
int k = 0;
for (int j=0; j<m_outerSize; ++j)
{
int previousStart = m_outerIndex[j];
m_outerIndex[j] = k;
int end = m_outerIndex[j+1];
for (int i=previousStart; i<end; ++i)
{
if (!ei_isMuchSmallerThan(m_data.value(i), reference, epsilon))
{
m_data.value(k) = m_data.value(i);
m_data.index(k) = m_data.index(i);
++k;
}
}
}
m_outerIndex[m_outerSize] = k;
m_data.resize(k,0);
}
void resize(int rows, int cols)
{

4
Eigen/src/Sparse/SparseMatrixBase.h
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@ -327,6 +327,10 @@ template<typename Derived> class SparseMatrixBase
// void transposeInPlace();
const AdjointReturnType adjoint() const { return conjugate()/*.nestByValue()*/; }
SparseInnerVector<Derived> row(int i);
const SparseInnerVector<Derived> row(int i) const;
SparseInnerVector<Derived> col(int j);
const SparseInnerVector<Derived> col(int j) const;
SparseInnerVector<Derived> innerVector(int outer);
const SparseInnerVector<Derived> innerVector(int outer) const;

24
Eigen/src/Sparse/SparseVector.h
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@ -67,20 +67,19 @@ class SparseVector
CompressedStorage<Scalar> m_data;
int m_size;
public:
inline int rows() const { return IsColVector ? m_size : 1; }
inline int cols() const { return IsColVector ? 1 : m_size; }
inline int innerSize() const { return m_size; }
inline int outerSize() const { return 1; }
inline int innerNonZeros(int j) const { ei_assert(j==0); return m_size; }
EIGEN_STRONG_INLINE int rows() const { return IsColVector ? m_size : 1; }
EIGEN_STRONG_INLINE int cols() const { return IsColVector ? 1 : m_size; }
EIGEN_STRONG_INLINE int innerSize() const { return m_size; }
EIGEN_STRONG_INLINE int outerSize() const { return 1; }
EIGEN_STRONG_INLINE int innerNonZeros(int j) const { ei_assert(j==0); return m_size; }
inline const Scalar* _valuePtr() const { return &m_data.value(0); }
inline Scalar* _valuePtr() { return &m_data.value(0); }
EIGEN_STRONG_INLINE const Scalar* _valuePtr() const { return &m_data.value(0); }
EIGEN_STRONG_INLINE Scalar* _valuePtr() { return &m_data.value(0); }
inline const int* _innerIndexPtr() const { return &m_data.index(0); }
inline int* _innerIndexPtr() { return &m_data.index(0); }
EIGEN_STRONG_INLINE const int* _innerIndexPtr() const { return &m_data.index(0); }
EIGEN_STRONG_INLINE int* _innerIndexPtr() { return &m_data.index(0); }
inline Scalar coeff(int row, int col) const
{
@ -145,6 +144,11 @@ class SparseVector
m_data.value(id+1) = 0;
return m_data.value(id+1);
}
void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
{
m_data.prune(reference,epsilon);
}
void resize(int newSize)
{

41
test/sparse_basic.cpp
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@ -323,14 +323,49 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
VERIFY_IS_APPROX(x=mLo.template marked<LowerTriangular|SelfAdjoint>()*b, refX=refS*b);
VERIFY_IS_APPROX(x=mS.template marked<SelfAdjoint>()*b, refX=refS*b);
}
// test prune
{
SparseMatrixType m2(rows, rows);
DenseMatrix refM2(rows, rows);
refM2.setZero();
int countFalseNonZero = 0;
int countTrueNonZero = 0;
m2.startFill();
for (int j=0; j<m2.outerSize(); ++j)
for (int i=0; i<m2.innerSize(); ++i)
{
float x = ei_random<float>(0,1);
if (x<0.1)
{
// do nothing
}
else if (x<0.5)
{
countFalseNonZero++;
m2.fill(i,j) = Scalar(0);
}
else
{
countTrueNonZero++;
m2.fill(i,j) = refM2(i,j) = Scalar(1);
}
}
m2.endFill();
VERIFY(countFalseNonZero+countTrueNonZero == m2.nonZeros());
VERIFY_IS_APPROX(m2, refM2);
m2.prune(1);
VERIFY(countTrueNonZero==m2.nonZeros());
VERIFY_IS_APPROX(m2, refM2);
}
}
void test_sparse_basic()
{
for(int i = 0; i < g_repeat; i++) {
// CALL_SUBTEST( sparse_basic(SparseMatrix<double>(8, 8)) );
// CALL_SUBTEST( sparse_basic(SparseMatrix<std::complex<double> >(16, 16)) );
// CALL_SUBTEST( sparse_basic(SparseMatrix<double>(33, 33)) );
CALL_SUBTEST( sparse_basic(SparseMatrix<double>(8, 8)) );
CALL_SUBTEST( sparse_basic(SparseMatrix<std::complex<double> >(16, 16)) );
CALL_SUBTEST( sparse_basic(SparseMatrix<double>(33, 33)) );
CALL_SUBTEST( sparse_basic(DynamicSparseMatrix<double>(8, 8)) );
}