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eigen/test/vectorwiseop.cpp

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Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
Properly implement PartialReduxExpr on top of evaluators, and fix multiple evaluation of nested expression
2015-10-08 21:57:05 +08:00
// Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
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//
Automatic relicensing to MPL2 using Keirs script. Manual fixup follows.
2012-07-14 02:42:47 +08:00
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
Properly implement PartialReduxExpr on top of evaluators, and fix multiple evaluation of nested expression
2015-10-08 21:57:05 +08:00
#define TEST_ENABLE_TEMPORARY_TRACKING
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
#define EIGEN_NO_STATIC_ASSERT
#include "main.h"
template<typename ArrayType> void vectorwiseop_array(const ArrayType& m)
{
typedef typename ArrayType::Scalar Scalar;
typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType;
typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType;
Index rows = m.rows();
Index cols = m.cols();
Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);
ArrayType m1 = ArrayType::Random(rows, cols),
m2(rows, cols),
m3(rows, cols);
ColVectorType colvec = ColVectorType::Random(rows);
RowVectorType rowvec = RowVectorType::Random(cols);
// test addition
m2 = m1;
m2.colwise() += colvec;
VERIFY_IS_APPROX(m2, m1.colwise() + colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec);
VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose());
VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose());
m2 = m1;
m2.rowwise() += rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec);
VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose());
VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose());
// test substraction
m2 = m1;
m2.colwise() -= colvec;
VERIFY_IS_APPROX(m2, m1.colwise() - colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec);
VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose());
VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose());
m2 = m1;
m2.rowwise() -= rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec);
VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose());
VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose());
// test multiplication
m2 = m1;
m2.colwise() *= colvec;
VERIFY_IS_APPROX(m2, m1.colwise() * colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) * colvec);
VERIFY_RAISES_ASSERT(m2.colwise() *= colvec.transpose());
VERIFY_RAISES_ASSERT(m1.colwise() * colvec.transpose());
m2 = m1;
m2.rowwise() *= rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() * rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) * rowvec);
VERIFY_RAISES_ASSERT(m2.rowwise() *= rowvec.transpose());
VERIFY_RAISES_ASSERT(m1.rowwise() * rowvec.transpose());
// test quotient
m2 = m1;
m2.colwise() /= colvec;
VERIFY_IS_APPROX(m2, m1.colwise() / colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) / colvec);
VERIFY_RAISES_ASSERT(m2.colwise() /= colvec.transpose());
VERIFY_RAISES_ASSERT(m1.colwise() / colvec.transpose());
m2 = m1;
m2.rowwise() /= rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() / rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) / rowvec);
VERIFY_RAISES_ASSERT(m2.rowwise() /= rowvec.transpose());
VERIFY_RAISES_ASSERT(m1.rowwise() / rowvec.transpose());
Fix typo in Vectowise::any()
2015-09-17 04:31:19 +08:00
Fix cost evaluation of partial reduxions -> improve performance of vectorwise/replicate expressions involving partial reduxions
2013-08-12 01:21:43 +08:00
m2 = m1;
// yes, there might be an aliasing issue there but ".rowwise() /="
Extend qr unit test
2014-07-21 17:45:54 +08:00
// is supposed to evaluate " m2.colwise().sum()" into a temporary to avoid
// evaluating the reduction multiple times
Fix cost evaluation of partial reduxions -> improve performance of vectorwise/replicate expressions involving partial reduxions
2013-08-12 01:21:43 +08:00
if(ArrayType::RowsAtCompileTime>2 || ArrayType::RowsAtCompileTime==Dynamic)
{
m2.rowwise() /= m2.colwise().sum();
VERIFY_IS_APPROX(m2, m1.rowwise() / m1.colwise().sum());
}
Fix typo in Vectowise::any()
2015-09-17 04:31:19 +08:00
// all/any
Array<bool,Dynamic,Dynamic> mb(rows,cols);
mb = (m1.real()<=0.7).colwise().all();
VERIFY( (mb.col(c) == (m1.real().col(c)<=0.7).all()).all() );
mb = (m1.real()<=0.7).rowwise().all();
VERIFY( (mb.row(r) == (m1.real().row(r)<=0.7).all()).all() );
mb = (m1.real()>=0.7).colwise().any();
VERIFY( (mb.col(c) == (m1.real().col(c)>=0.7).any()).all() );
mb = (m1.real()>=0.7).rowwise().any();
VERIFY( (mb.row(r) == (m1.real().row(r)>=0.7).any()).all() );
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
}
template<typename MatrixType> void vectorwiseop_matrix(const MatrixType& m)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType;
typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
Fix bug #562: add vector-wise normalized and normalize functions
2013-04-09 17:12:35 +08:00
typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealColVectorType;
typedef Matrix<RealScalar, 1, MatrixType::ColsAtCompileTime> RealRowVectorType;
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
Index rows = m.rows();
Index cols = m.cols();
Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);
MatrixType m1 = MatrixType::Random(rows, cols),
m2(rows, cols),
m3(rows, cols);
ColVectorType colvec = ColVectorType::Random(rows);
RowVectorType rowvec = RowVectorType::Random(cols);
Fix bug #562: add vector-wise normalized and normalize functions
2013-04-09 17:12:35 +08:00
RealColVectorType rcres;
RealRowVectorType rrres;
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
// test addition
m2 = m1;
m2.colwise() += colvec;
VERIFY_IS_APPROX(m2, m1.colwise() + colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec);
Extend vectorwiseop unit test with column/row vectors as input.
2015-10-28 18:59:20 +08:00
if(rows>1)
{
VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose());
VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose());
}
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
m2 = m1;
m2.rowwise() += rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec);
Extend vectorwiseop unit test with column/row vectors as input.
2015-10-28 18:59:20 +08:00
if(cols>1)
{
VERIFY_RAISES_ASSERT(m2.rowwise() += rowvec.transpose());
VERIFY_RAISES_ASSERT(m1.rowwise() + rowvec.transpose());
}
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
// test substraction
m2 = m1;
m2.colwise() -= colvec;
VERIFY_IS_APPROX(m2, m1.colwise() - colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec);
Extend vectorwiseop unit test with column/row vectors as input.
2015-10-28 18:59:20 +08:00
if(rows>1)
{
VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose());
VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose());
}
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
m2 = m1;
m2.rowwise() -= rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec);
Extend vectorwiseop unit test with column/row vectors as input.
2015-10-28 18:59:20 +08:00
if(cols>1)
{
VERIFY_RAISES_ASSERT(m2.rowwise() -= rowvec.transpose());
VERIFY_RAISES_ASSERT(m1.rowwise() - rowvec.transpose());
}
Fix typo in Vectowise::any()
2015-09-17 04:31:19 +08:00
Fix bug #562: add vector-wise normalized and normalize functions
2013-04-09 17:12:35 +08:00
// test norm
rrres = m1.colwise().norm();
VERIFY_IS_APPROX(rrres(c), m1.col(c).norm());
rcres = m1.rowwise().norm();
VERIFY_IS_APPROX(rcres(r), m1.row(r).norm());
Fix typo in Vectowise::any()
2015-09-17 04:31:19 +08:00
Add support for row/col-wise lpNorm()
2015-09-28 17:36:00 +08:00
VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum(), m1.colwise().template lpNorm<1>());
VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().sum(), m1.rowwise().template lpNorm<1>());
VERIFY_IS_APPROX(m1.cwiseAbs().colwise().maxCoeff(), m1.colwise().template lpNorm<Infinity>());
VERIFY_IS_APPROX(m1.cwiseAbs().rowwise().maxCoeff(), m1.rowwise().template lpNorm<Infinity>());
bug #1158: PartialReduxExpr is a vector expression, and it thus must expose the LinearAccessBit flag
2016-01-28 20:16:30 +08:00
// regression for bug 1158
VERIFY_IS_APPROX(m1.cwiseAbs().colwise().sum().x(), m1.col(0).cwiseAbs().sum());
Fix bug #562: add vector-wise normalized and normalize functions
2013-04-09 17:12:35 +08:00
// test normalized
m2 = m1.colwise().normalized();
VERIFY_IS_APPROX(m2.col(c), m1.col(c).normalized());
m2 = m1.rowwise().normalized();
VERIFY_IS_APPROX(m2.row(r), m1.row(r).normalized());
Fix typo in Vectowise::any()
2015-09-17 04:31:19 +08:00
Fix bug #562: add vector-wise normalized and normalize functions
2013-04-09 17:12:35 +08:00
// test normalize
m2 = m1;
m2.colwise().normalize();
VERIFY_IS_APPROX(m2.col(c), m1.col(c).normalized());
m2 = m1;
m2.rowwise().normalize();
VERIFY_IS_APPROX(m2.row(r), m1.row(r).normalized());
Properly implement PartialReduxExpr on top of evaluators, and fix multiple evaluation of nested expression
2015-10-08 21:57:05 +08:00
// test with partial reduction of products
Matrix<Scalar,MatrixType::RowsAtCompileTime,MatrixType::RowsAtCompileTime> m1m1 = m1 * m1.transpose();
VERIFY_IS_APPROX( (m1 * m1.transpose()).colwise().sum(), m1m1.colwise().sum());
Matrix<Scalar,1,MatrixType::RowsAtCompileTime> tmp(rows);
Fix tracking of temporaries in unit tests
2017-02-19 17:32:54 +08:00
VERIFY_EVALUATION_COUNT( tmp = (m1 * m1.transpose()).colwise().sum(), 1);
Refactoring of the cost model: - Dynamic is now an invalid value - introduce a HugeCost constant to be used for runtime-cost values or arbitrarily huge cost - add sanity checks for cost values: must be >=0 and not too large This change provides several benefits: - it fixes shortcoming is some cost computation where the Dynamic case was not properly handled. - it simplifies cost computation logic, and should avoid future similar shortcomings. - it allows to distinguish between different level of dynamic/huge/infinite cost - it should enable further simplifications in the computation of costs (save compilation time)
2015-10-28 18:42:14 +08:00
Fix some conversion warnings in unit tests.
2016-05-26 23:42:12 +08:00
m2 = m1.rowwise() - (m1.colwise().sum()/RealScalar(m1.rows())).eval();
m1 = m1.rowwise() - (m1.colwise().sum()/RealScalar(m1.rows()));
Refactoring of the cost model: - Dynamic is now an invalid value - introduce a HugeCost constant to be used for runtime-cost values or arbitrarily huge cost - add sanity checks for cost values: must be >=0 and not too large This change provides several benefits: - it fixes shortcoming is some cost computation where the Dynamic case was not properly handled. - it simplifies cost computation logic, and should avoid future similar shortcomings. - it allows to distinguish between different level of dynamic/huge/infinite cost - it should enable further simplifications in the computation of costs (save compilation time)
2015-10-28 18:42:14 +08:00
VERIFY_IS_APPROX( m1, m2 );
Fix tracking of temporaries in unit tests
2017-02-19 17:32:54 +08:00
VERIFY_EVALUATION_COUNT( m2 = (m1.rowwise() - m1.colwise().sum()/RealScalar(m1.rows())), (MatrixType::RowsAtCompileTime!=1 ? 1 : 0) );
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
}
Get rid of EIGEN_TEST_FUNC, unit tests must now be declared with EIGEN_DECLARE_TEST(mytest) { /* code */ }. This provide several advantages: - more flexibility in designing unit tests - unit tests can be glued to speed up compilation - unit tests are compiled with same predefined macros, which is a requirement for zapcc
2018-07-17 20:46:15 +08:00
EIGEN_DECLARE_TEST(vectorwiseop)
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
{
Properly implement PartialReduxExpr on top of evaluators, and fix multiple evaluation of nested expression
2015-10-08 21:57:05 +08:00
CALL_SUBTEST_1( vectorwiseop_array(Array22cd()) );
CALL_SUBTEST_2( vectorwiseop_array(Array<double, 3, 2>()) );
CALL_SUBTEST_3( vectorwiseop_array(ArrayXXf(3, 4)) );
CALL_SUBTEST_4( vectorwiseop_matrix(Matrix4cf()) );
CALL_SUBTEST_5( vectorwiseop_matrix(Matrix<float,4,5>()) );
CALL_SUBTEST_6( vectorwiseop_matrix(MatrixXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
Extend vectorwiseop unit test with column/row vectors as input.
2015-10-28 18:59:20 +08:00
CALL_SUBTEST_7( vectorwiseop_matrix(VectorXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_7( vectorwiseop_matrix(RowVectorXd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
Bugs 157 and 377 - General tightening/testing of vectorwise ops: * add lots of static assertions making it very explicit when all these ops are supposed to work: ** all ops require the rhs vector to go in the right direction ** all ops already require that the lhs and rhs are of the same kind (matrix vs vector) otherwise we'd have to do complex work ** multiplicative ops (introduced Kibeom's patch) are restricted to arrays, if only because for matrices they could be ambiguous. * add a new test, vectorwiseop.cpp. * these compound-assign operators used to be implemented with for loops: for(Index j=0; j<subVectors(); ++j) subVector(j).array() += other.derived().array(); This didn't seem to be needed; replaced by using expressions like operator+ and operator- did.
2011-11-19 00:10:27 +08:00
}
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