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Sparse matrix column/row removal

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Charles Schlosser 2023-05-24 17:04:45 +00:00 committed by Rasmus Munk Larsen
parent de1c884687
commit 67a1e881d9
2 changed files with 129 additions and 2 deletions
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62
Eigen/src/SparseCore/SparseMatrix.h
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@ -368,7 +368,7 @@ class SparseMatrix
m_innerNonZeros[j] = innerNNZ;
}
if(m_outerSize>0)
m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + reserveSizes[m_outerSize-1];
m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + internal::convert_index<StorageIndex>(reserveSizes[m_outerSize-1]);
m_data.resize(m_outerIndex[m_outerSize]);
}
@ -472,7 +472,65 @@ class SparseMatrix
}
}
//---
// remove outer vectors j, j+1 ... j+num-1 and resize the matrix
void removeOuterVectors(Index j, Index num = 1) {
eigen_assert(num >= 0 && j >= 0 && j + num <= m_outerSize && "Invalid parameters");
const Index newRows = IsRowMajor ? m_outerSize - num : rows();
const Index newCols = IsRowMajor ? cols() : m_outerSize - num;
const Index begin = j + num;
const Index end = m_outerSize;
const Index target = j;
// if the removed vectors are not empty, uncompress the matrix
if (m_outerIndex[j + num] > m_outerIndex[j]) uncompress();
// shift m_outerIndex and m_innerNonZeros [num] to the left
internal::smart_memmove(m_outerIndex + begin, m_outerIndex + end + 1, m_outerIndex + target);
if (!isCompressed())
internal::smart_memmove(m_innerNonZeros + begin, m_innerNonZeros + end, m_innerNonZeros + target);
// if m_outerIndex[0] > 0, shift the data within the first vector while it is easy to do so
if (m_outerIndex[0] > StorageIndex(0)) {
uncompress();
const Index from = internal::convert_index<Index>(m_outerIndex[0]);
const Index to = Index(0);
const Index chunkSize = internal::convert_index<Index>(m_innerNonZeros[0]);
m_data.moveChunk(from, to, chunkSize);
m_outerIndex[0] = StorageIndex(0);
}
// truncate the matrix to the smaller size
conservativeResize(newRows, newCols);
}
// insert empty outer vectors at indices j, j+1 ... j+num-1 and resize the matrix
void insertEmptyOuterVectors(Index j, Index num = 1) {
EIGEN_USING_STD(fill_n);
eigen_assert(num >= 0 && j >= 0 && j < m_outerSize && "Invalid parameters");
const Index newRows = IsRowMajor ? m_outerSize + num : rows();
const Index newCols = IsRowMajor ? cols() : m_outerSize + num;
const Index begin = j;
const Index end = m_outerSize;
const Index target = j + num;
// expand the matrix to the larger size
conservativeResize(newRows, newCols);
// shift m_outerIndex and m_innerNonZeros [num] to the right
internal::smart_memmove(m_outerIndex + begin, m_outerIndex + end + 1, m_outerIndex + target);
// m_outerIndex[begin] == m_outerIndex[target], set all indices in this range to same value
fill_n(m_outerIndex + begin, num, m_outerIndex[begin]);
if (!isCompressed()) {
internal::smart_memmove(m_innerNonZeros + begin, m_innerNonZeros + end, m_innerNonZeros + target);
// set the nonzeros of the newly inserted vectors to 0
fill_n(m_innerNonZeros + begin, num, StorageIndex(0));
}
}
template<typename InputIterators>
void setFromTriplets(const InputIterators& begin, const InputIterators& end);

69
test/sparse_basic.cpp
View File

@ -38,6 +38,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
double density = (std::max)(8./(rows*cols), 0.01);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef Matrix<Scalar, Dynamic, Dynamic, SparseMatrixType::IsRowMajor ? RowMajor : ColMajor> CompatibleDenseMatrix;
Scalar eps = 1e-6;
Scalar s1 = internal::random<Scalar>();
@ -162,6 +163,74 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
VERIFY_IS_APPROX(m2,m1);
}
// test removeOuterVectors / insertEmptyOuterVectors
{
for (int mode = 0; mode < 4; mode++) {
CompatibleDenseMatrix m1(rows, cols);
m1.setZero();
SparseMatrixType m2(rows, cols);
Vector<Index, Dynamic> reserveSizes(outer);
for (Index j = 0; j < outer; j++) reserveSizes(j) = internal::random<Index>(1, inner - 1);
m2.reserve(reserveSizes);
for (Index j = 0; j < outer; j++) {
Index i = internal::random<Index>(0, inner - 1);
Scalar val = internal::random<Scalar>();
m1.coeffRefByOuterInner(j, i) = val;
m2.insertByOuterInner(j, i) = val;
}
if (mode % 2 == 0) m2.makeCompressed();
if (mode < 2) {
Index num = internal::random<Index>(0, outer - 1);
Index start = internal::random<Index>(0, outer - num);
Index newRows = SparseMatrixType::IsRowMajor ? rows - num : rows;
Index newCols = SparseMatrixType::IsRowMajor ? cols : cols - num;
CompatibleDenseMatrix m3(newRows, newCols);
m3.setConstant(Scalar(NumTraits<RealScalar>::quiet_NaN()));
if (SparseMatrixType::IsRowMajor) {
m3.topRows(start) = m1.topRows(start);
m3.bottomRows(newRows - start) = m1.bottomRows(newRows - start);
} else {
m3.leftCols(start) = m1.leftCols(start);
m3.rightCols(newCols - start) = m1.rightCols(newCols - start);
}
SparseMatrixType m4 = m2;
m4.removeOuterVectors(start, num);
VERIFY_IS_CWISE_EQUAL(m3, m4.toDense());
} else {
Index num = internal::random<Index>(0, outer - 1);
Index start = internal::random<Index>(0, outer - 1);
Index newRows = SparseMatrixType::IsRowMajor ? rows + num : rows;
Index newCols = SparseMatrixType::IsRowMajor ? cols : cols + num;
CompatibleDenseMatrix m3(newRows, newCols);
m3.setConstant(Scalar(NumTraits<RealScalar>::quiet_NaN()));
if (SparseMatrixType::IsRowMajor) {
m3.topRows(start) = m1.topRows(start);
m3.middleRows(start, num).setZero();
m3.bottomRows(rows - start) = m1.bottomRows(rows - start);
} else {
m3.leftCols(start) = m1.leftCols(start);
m3.middleCols(start, num).setZero();
m3.rightCols(cols - start) = m1.rightCols(cols - start);
}
SparseMatrixType m4 = m2;
m4.insertEmptyOuterVectors(start, num);
VERIFY_IS_CWISE_EQUAL(m3, m4.toDense());
}
}
}
// test sort
if (inner > 1) {
bool StorageOrdersMatch = int(DenseMatrix::IsRowMajor) == int(SparseMatrixType::IsRowMajor);