eigen/test/array_cwise.cpp

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
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//
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// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
// 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/.
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#include "main.h"
template<typename ArrayType> void array(const ArrayType& m)
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{
typedef typename ArrayType::Scalar Scalar;
typedef typename ArrayType::RealScalar RealScalar;
typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType;
typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType;
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Index rows = m.rows();
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Index cols = m.cols();
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ArrayType m1 = ArrayType::Random(rows, cols),
m2 = ArrayType::Random(rows, cols),
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m3(rows, cols);
ArrayType m4 = m1; // copy constructor
VERIFY_IS_APPROX(m1, m4);
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ColVectorType cv1 = ColVectorType::Random(rows);
RowVectorType rv1 = RowVectorType::Random(cols);
Scalar s1 = internal::random<Scalar>(),
s2 = internal::random<Scalar>();
// scalar addition
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VERIFY_IS_APPROX(m1 + s1, s1 + m1);
VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1);
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VERIFY_IS_APPROX(s1 - m1, (-m1)+s1 );
VERIFY_IS_APPROX(m1 - s1, m1 - ArrayType::Constant(rows,cols,s1));
VERIFY_IS_APPROX(s1 - m1, ArrayType::Constant(rows,cols,s1) - m1);
VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - ArrayType::Constant(rows,cols,s2) );
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m3 = m1;
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m3 += s2;
VERIFY_IS_APPROX(m3, m1 + s2);
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m3 = m1;
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m3 -= s1;
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VERIFY_IS_APPROX(m3, m1 - s1);
// scalar operators via Maps
m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) -= ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 - m2);
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m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) += ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 + m2);
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m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) *= ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 * m2);
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m3 = m1;
m2 = ArrayType::Random(rows,cols);
m2 = (m2==0).select(1,m2);
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ArrayType::Map(m1.data(), m1.rows(), m1.cols()) /= ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 / m2);
// reductions
VERIFY_IS_APPROX(m1.abs().colwise().sum().sum(), m1.abs().sum());
VERIFY_IS_APPROX(m1.abs().rowwise().sum().sum(), m1.abs().sum());
using std::abs;
VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.colwise().sum().sum() - m1.sum()), m1.abs().sum());
VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.rowwise().sum().sum() - m1.sum()), m1.abs().sum());
if (!internal::isMuchSmallerThan(abs(m1.sum() - (m1+m2).sum()), m1.abs().sum(), test_precision<Scalar>()))
VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
// vector-wise ops
m3 = m1;
VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1);
m3 = m1;
VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1);
m3 = m1;
VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1);
m3 = m1;
VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1);
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// Conversion from scalar
VERIFY_IS_APPROX((m3 = s1), ArrayType::Constant(rows,cols,s1));
VERIFY_IS_APPROX((m3 = 1), ArrayType::Constant(rows,cols,1));
VERIFY_IS_APPROX((m3.topLeftCorner(rows,cols) = 1), ArrayType::Constant(rows,cols,1));
typedef Array<Scalar,
ArrayType::RowsAtCompileTime==Dynamic?2:ArrayType::RowsAtCompileTime,
ArrayType::ColsAtCompileTime==Dynamic?2:ArrayType::ColsAtCompileTime,
ArrayType::Options> FixedArrayType;
{
FixedArrayType f1(s1);
VERIFY_IS_APPROX(f1, FixedArrayType::Constant(s1));
FixedArrayType f2(numext::real(s1));
VERIFY_IS_APPROX(f2, FixedArrayType::Constant(numext::real(s1)));
FixedArrayType f3((int)100*numext::real(s1));
VERIFY_IS_APPROX(f3, FixedArrayType::Constant((int)100*numext::real(s1)));
f1.setRandom();
FixedArrayType f4(f1.data());
VERIFY_IS_APPROX(f4, f1);
}
#if EIGEN_HAS_CXX11
{
FixedArrayType f1{s1};
VERIFY_IS_APPROX(f1, FixedArrayType::Constant(s1));
FixedArrayType f2{numext::real(s1)};
VERIFY_IS_APPROX(f2, FixedArrayType::Constant(numext::real(s1)));
FixedArrayType f3{(int)100*numext::real(s1)};
VERIFY_IS_APPROX(f3, FixedArrayType::Constant((int)100*numext::real(s1)));
f1.setRandom();
FixedArrayType f4{f1.data()};
VERIFY_IS_APPROX(f4, f1);
}
#endif
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// pow
VERIFY_IS_APPROX(m1.pow(2), m1.square());
VERIFY_IS_APPROX(pow(m1,2), m1.square());
VERIFY_IS_APPROX(m1.pow(3), m1.cube());
VERIFY_IS_APPROX(pow(m1,3), m1.cube());
VERIFY_IS_APPROX((-m1).pow(3), -m1.cube());
VERIFY_IS_APPROX(pow(2*m1,3), 8*m1.cube());
ArrayType exponents = ArrayType::Constant(rows, cols, RealScalar(2));
VERIFY_IS_APPROX(Eigen::pow(m1,exponents), m1.square());
VERIFY_IS_APPROX(m1.pow(exponents), m1.square());
VERIFY_IS_APPROX(Eigen::pow(2*m1,exponents), 4*m1.square());
VERIFY_IS_APPROX((2*m1).pow(exponents), 4*m1.square());
VERIFY_IS_APPROX(Eigen::pow(m1,2*exponents), m1.square().square());
VERIFY_IS_APPROX(m1.pow(2*exponents), m1.square().square());
VERIFY_IS_APPROX(Eigen::pow(m1(0,0), exponents), ArrayType::Constant(rows,cols,m1(0,0)*m1(0,0)));
// Check possible conflicts with 1D ctor
typedef Array<Scalar, Dynamic, 1> OneDArrayType;
{
OneDArrayType o1(rows);
VERIFY(o1.size()==rows);
OneDArrayType o2(static_cast<int>(rows));
VERIFY(o2.size()==rows);
}
#if EIGEN_HAS_CXX11
{
OneDArrayType o1{rows};
VERIFY(o1.size()==rows);
OneDArrayType o4{int(rows)};
VERIFY(o4.size()==rows);
}
#endif
// Check possible conflicts with 2D ctor
typedef Array<Scalar, Dynamic, Dynamic> TwoDArrayType;
typedef Array<Scalar, 2, 1> ArrayType2;
{
TwoDArrayType o1(rows,cols);
VERIFY(o1.rows()==rows);
VERIFY(o1.cols()==cols);
TwoDArrayType o2(static_cast<int>(rows),static_cast<int>(cols));
VERIFY(o2.rows()==rows);
VERIFY(o2.cols()==cols);
ArrayType2 o3(rows,cols);
VERIFY(o3(0)==Scalar(rows) && o3(1)==Scalar(cols));
ArrayType2 o4(static_cast<int>(rows),static_cast<int>(cols));
VERIFY(o4(0)==Scalar(rows) && o4(1)==Scalar(cols));
}
#if EIGEN_HAS_CXX11
{
TwoDArrayType o1{rows,cols};
VERIFY(o1.rows()==rows);
VERIFY(o1.cols()==cols);
TwoDArrayType o2{int(rows),int(cols)};
VERIFY(o2.rows()==rows);
VERIFY(o2.cols()==cols);
ArrayType2 o3{rows,cols};
VERIFY(o3(0)==Scalar(rows) && o3(1)==Scalar(cols));
ArrayType2 o4{int(rows),int(cols)};
VERIFY(o4(0)==Scalar(rows) && o4(1)==Scalar(cols));
}
#endif
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}
template<typename ArrayType> void comparisons(const ArrayType& m)
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{
using std::abs;
typedef typename ArrayType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
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Index rows = m.rows();
Index cols = m.cols();
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Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);
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ArrayType m1 = ArrayType::Random(rows, cols),
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m2 = ArrayType::Random(rows, cols),
m3(rows, cols),
m4 = m1;
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m4 = (m4.abs()==Scalar(0)).select(1,m4);
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VERIFY(((m1 + Scalar(1)) > m1).all());
VERIFY(((m1 - Scalar(1)) < m1).all());
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if (rows*cols>1)
{
m3 = m1;
m3(r,c) += 1;
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VERIFY(! (m1 < m3).all() );
VERIFY(! (m1 > m3).all() );
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}
VERIFY(!(m1 > m2 && m1 < m2).any());
VERIFY((m1 <= m2 || m1 >= m2).all());
// comparisons array to scalar
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VERIFY( (m1 != (m1(r,c)+1) ).any() );
VERIFY( (m1 > (m1(r,c)-1) ).any() );
VERIFY( (m1 < (m1(r,c)+1) ).any() );
VERIFY( (m1 == m1(r,c) ).any() );
// comparisons scalar to array
VERIFY( ( (m1(r,c)+1) != m1).any() );
VERIFY( ( (m1(r,c)-1) < m1).any() );
VERIFY( ( (m1(r,c)+1) > m1).any() );
VERIFY( ( m1(r,c) == m1).any() );
// test Select
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VERIFY_IS_APPROX( (m1<m2).select(m1,m2), m1.cwiseMin(m2) );
VERIFY_IS_APPROX( (m1>m2).select(m1,m2), m1.cwiseMax(m2) );
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Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2);
for (int j=0; j<cols; ++j)
for (int i=0; i<rows; ++i)
m3(i,j) = abs(m1(i,j))<mid ? 0 : m1(i,j);
VERIFY_IS_APPROX( (m1.abs()<ArrayType::Constant(rows,cols,mid))
.select(ArrayType::Zero(rows,cols),m1), m3);
// shorter versions:
VERIFY_IS_APPROX( (m1.abs()<ArrayType::Constant(rows,cols,mid))
.select(0,m1), m3);
VERIFY_IS_APPROX( (m1.abs()>=ArrayType::Constant(rows,cols,mid))
.select(m1,0), m3);
// even shorter version:
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VERIFY_IS_APPROX( (m1.abs()<mid).select(0,m1), m3);
// count
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VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols);
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// and/or
VERIFY( (m1<RealScalar(0) && m1>RealScalar(0)).count() == 0);
VERIFY( (m1<RealScalar(0) || m1>=RealScalar(0)).count() == rows*cols);
RealScalar a = m1.abs().mean();
VERIFY( (m1<-a || m1>a).count() == (m1.abs()>a).count());
typedef Array<Index, Dynamic, 1> ArrayOfIndices;
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// TODO allows colwise/rowwise for array
VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayOfIndices::Constant(cols,rows).transpose());
VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayOfIndices::Constant(rows, cols));
}
template<typename ArrayType> void array_real(const ArrayType& m)
{
using std::abs;
using std::sqrt;
typedef typename ArrayType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
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Index rows = m.rows();
Index cols = m.cols();
ArrayType m1 = ArrayType::Random(rows, cols),
m2 = ArrayType::Random(rows, cols),
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m3(rows, cols),
m4 = m1;
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m4 = (m4.abs()==Scalar(0)).select(1,m4);
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Scalar s1 = internal::random<Scalar>();
// these tests are mostly to check possible compilation issues with free-functions.
VERIFY_IS_APPROX(m1.sin(), sin(m1));
VERIFY_IS_APPROX(m1.cos(), cos(m1));
VERIFY_IS_APPROX(m1.tan(), tan(m1));
VERIFY_IS_APPROX(m1.asin(), asin(m1));
VERIFY_IS_APPROX(m1.acos(), acos(m1));
VERIFY_IS_APPROX(m1.atan(), atan(m1));
VERIFY_IS_APPROX(m1.sinh(), sinh(m1));
VERIFY_IS_APPROX(m1.cosh(), cosh(m1));
VERIFY_IS_APPROX(m1.tanh(), tanh(m1));
#if EIGEN_HAS_CXX11_MATH
VERIFY_IS_APPROX(m1.tanh().atanh(), atanh(tanh(m1)));
VERIFY_IS_APPROX(m1.sinh().asinh(), asinh(sinh(m1)));
VERIFY_IS_APPROX(m1.cosh().acosh(), acosh(cosh(m1)));
#endif
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VERIFY_IS_APPROX(m1.logistic(), logistic(m1));
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VERIFY_IS_APPROX(m1.arg(), arg(m1));
VERIFY_IS_APPROX(m1.round(), round(m1));
VERIFY_IS_APPROX(m1.rint(), rint(m1));
VERIFY_IS_APPROX(m1.floor(), floor(m1));
VERIFY_IS_APPROX(m1.ceil(), ceil(m1));
VERIFY((m1.isNaN() == (Eigen::isnan)(m1)).all());
VERIFY((m1.isInf() == (Eigen::isinf)(m1)).all());
VERIFY((m1.isFinite() == (Eigen::isfinite)(m1)).all());
VERIFY_IS_APPROX(m1.inverse(), inverse(m1));
VERIFY_IS_APPROX(m1.abs(), abs(m1));
VERIFY_IS_APPROX(m1.abs2(), abs2(m1));
VERIFY_IS_APPROX(m1.square(), square(m1));
VERIFY_IS_APPROX(m1.cube(), cube(m1));
VERIFY_IS_APPROX(cos(m1+RealScalar(3)*m2), cos((m1+RealScalar(3)*m2).eval()));
VERIFY_IS_APPROX(m1.sign(), sign(m1));
VERIFY((m1.sqrt().sign().isNaN() == (Eigen::isnan)(sign(sqrt(m1)))).all());
// avoid NaNs with abs() so verification doesn't fail
m3 = m1.abs();
VERIFY_IS_APPROX(m3.sqrt(), sqrt(abs(m1)));
VERIFY_IS_APPROX(m3.rsqrt(), Scalar(1)/sqrt(abs(m1)));
VERIFY_IS_APPROX(rsqrt(m3), Scalar(1)/sqrt(abs(m1)));
VERIFY_IS_APPROX(m3.log(), log(m3));
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VERIFY_IS_APPROX(m3.log1p(), log1p(m3));
VERIFY_IS_APPROX(m3.log10(), log10(m3));
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VERIFY_IS_APPROX(m3.log2(), log2(m3));
VERIFY((!(m1>m2) == (m1<=m2)).all());
VERIFY_IS_APPROX(sin(m1.asin()), m1);
VERIFY_IS_APPROX(cos(m1.acos()), m1);
VERIFY_IS_APPROX(tan(m1.atan()), m1);
VERIFY_IS_APPROX(sinh(m1), 0.5*(exp(m1)-exp(-m1)));
VERIFY_IS_APPROX(cosh(m1), 0.5*(exp(m1)+exp(-m1)));
VERIFY_IS_APPROX(tanh(m1), (0.5*(exp(m1)-exp(-m1)))/(0.5*(exp(m1)+exp(-m1))));
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VERIFY_IS_APPROX(logistic(m1), (1.0/(1.0+exp(-m1))));
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VERIFY_IS_APPROX(arg(m1), ((m1<0).template cast<Scalar>())*std::acos(-1.0));
VERIFY((round(m1) <= ceil(m1) && round(m1) >= floor(m1)).all());
VERIFY((rint(m1) <= ceil(m1) && rint(m1) >= floor(m1)).all());
VERIFY(((ceil(m1) - round(m1)) <= Scalar(0.5) || (round(m1) - floor(m1)) <= Scalar(0.5)).all());
VERIFY(((ceil(m1) - round(m1)) <= Scalar(1.0) && (round(m1) - floor(m1)) <= Scalar(1.0)).all());
VERIFY(((ceil(m1) - rint(m1)) <= Scalar(0.5) || (rint(m1) - floor(m1)) <= Scalar(0.5)).all());
VERIFY(((ceil(m1) - rint(m1)) <= Scalar(1.0) && (rint(m1) - floor(m1)) <= Scalar(1.0)).all());
VERIFY((Eigen::isnan)((m1*0.0)/0.0).all());
VERIFY((Eigen::isinf)(m4/0.0).all());
VERIFY(((Eigen::isfinite)(m1) && (!(Eigen::isfinite)(m1*0.0/0.0)) && (!(Eigen::isfinite)(m4/0.0))).all());
VERIFY_IS_APPROX(inverse(inverse(m1)),m1);
VERIFY((abs(m1) == m1 || abs(m1) == -m1).all());
VERIFY_IS_APPROX(m3, sqrt(abs2(m1)));
VERIFY_IS_APPROX(m1.absolute_difference(m2), (m1 > m2).select(m1 - m2, m2 - m1));
VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
VERIFY_IS_APPROX( m1*m1.sign(),m1.abs());
VERIFY_IS_APPROX(m1.sign() * m1.abs(), m1);
VERIFY_IS_APPROX(numext::abs2(numext::real(m1)) + numext::abs2(numext::imag(m1)), numext::abs2(m1));
VERIFY_IS_APPROX(numext::abs2(Eigen::real(m1)) + numext::abs2(Eigen::imag(m1)), numext::abs2(m1));
if(!NumTraits<Scalar>::IsComplex)
VERIFY_IS_APPROX(numext::real(m1), m1);
// shift argument of logarithm so that it is not zero
Scalar smallNumber = NumTraits<Scalar>::dummy_precision();
VERIFY_IS_APPROX((m3 + smallNumber).log() , log(abs(m1) + smallNumber));
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VERIFY_IS_APPROX((m3 + smallNumber + 1).log() , log1p(abs(m1) + smallNumber));
VERIFY_IS_APPROX(m1.exp() * m2.exp(), exp(m1+m2));
VERIFY_IS_APPROX(m1.exp(), exp(m1));
VERIFY_IS_APPROX(m1.exp() / m2.exp(),(m1-m2).exp());
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VERIFY_IS_APPROX(m1.expm1(), expm1(m1));
VERIFY_IS_APPROX((m3 + smallNumber).exp() - 1, expm1(abs(m3) + smallNumber));
VERIFY_IS_APPROX(m3.pow(RealScalar(0.5)), m3.sqrt());
VERIFY_IS_APPROX(pow(m3,RealScalar(0.5)), m3.sqrt());
VERIFY_IS_APPROX(m3.pow(RealScalar(-0.5)), m3.rsqrt());
VERIFY_IS_APPROX(pow(m3,RealScalar(-0.5)), m3.rsqrt());
VERIFY_IS_APPROX(log10(m3), log(m3)/log(10));
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VERIFY_IS_APPROX(log2(m3), log(m3)/log(2));
// scalar by array division
const RealScalar tiny = sqrt(std::numeric_limits<RealScalar>::epsilon());
s1 += Scalar(tiny);
m1 += ArrayType::Constant(rows,cols,Scalar(tiny));
VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse());
// check inplace transpose
m3 = m1;
m3.transposeInPlace();
VERIFY_IS_APPROX(m3, m1.transpose());
m3.transposeInPlace();
VERIFY_IS_APPROX(m3, m1);
}
template<typename ArrayType> void array_complex(const ArrayType& m)
{
typedef typename ArrayType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
Index rows = m.rows();
Index cols = m.cols();
ArrayType m1 = ArrayType::Random(rows, cols),
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m2(rows, cols),
m4 = m1;
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m4.real() = (m4.real().abs()==RealScalar(0)).select(RealScalar(1),m4.real());
m4.imag() = (m4.imag().abs()==RealScalar(0)).select(RealScalar(1),m4.imag());
Array<RealScalar, -1, -1> m3(rows, cols);
for (Index i = 0; i < m.rows(); ++i)
for (Index j = 0; j < m.cols(); ++j)
m2(i,j) = sqrt(m1(i,j));
// these tests are mostly to check possible compilation issues with free-functions.
VERIFY_IS_APPROX(m1.sin(), sin(m1));
VERIFY_IS_APPROX(m1.cos(), cos(m1));
VERIFY_IS_APPROX(m1.tan(), tan(m1));
VERIFY_IS_APPROX(m1.sinh(), sinh(m1));
VERIFY_IS_APPROX(m1.cosh(), cosh(m1));
VERIFY_IS_APPROX(m1.tanh(), tanh(m1));
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VERIFY_IS_APPROX(m1.logistic(), logistic(m1));
VERIFY_IS_APPROX(m1.arg(), arg(m1));
VERIFY((m1.isNaN() == (Eigen::isnan)(m1)).all());
VERIFY((m1.isInf() == (Eigen::isinf)(m1)).all());
VERIFY((m1.isFinite() == (Eigen::isfinite)(m1)).all());
VERIFY_IS_APPROX(m1.inverse(), inverse(m1));
VERIFY_IS_APPROX(m1.log(), log(m1));
VERIFY_IS_APPROX(m1.log10(), log10(m1));
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VERIFY_IS_APPROX(m1.log2(), log2(m1));
VERIFY_IS_APPROX(m1.abs(), abs(m1));
VERIFY_IS_APPROX(m1.abs2(), abs2(m1));
VERIFY_IS_APPROX(m1.sqrt(), sqrt(m1));
VERIFY_IS_APPROX(m1.square(), square(m1));
VERIFY_IS_APPROX(m1.cube(), cube(m1));
VERIFY_IS_APPROX(cos(m1+RealScalar(3)*m2), cos((m1+RealScalar(3)*m2).eval()));
VERIFY_IS_APPROX(m1.sign(), sign(m1));
VERIFY_IS_APPROX(m1.exp() * m2.exp(), exp(m1+m2));
VERIFY_IS_APPROX(m1.exp(), exp(m1));
VERIFY_IS_APPROX(m1.exp() / m2.exp(),(m1-m2).exp());
VERIFY_IS_APPROX(m1.expm1(), expm1(m1));
VERIFY_IS_APPROX(expm1(m1), exp(m1) - 1.);
// Check for larger magnitude complex numbers that expm1 matches exp - 1.
VERIFY_IS_APPROX(expm1(10. * m1), exp(10. * m1) - 1.);
VERIFY_IS_APPROX(sinh(m1), 0.5*(exp(m1)-exp(-m1)));
VERIFY_IS_APPROX(cosh(m1), 0.5*(exp(m1)+exp(-m1)));
VERIFY_IS_APPROX(tanh(m1), (0.5*(exp(m1)-exp(-m1)))/(0.5*(exp(m1)+exp(-m1))));
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VERIFY_IS_APPROX(logistic(m1), (1.0/(1.0 + exp(-m1))));
for (Index i = 0; i < m.rows(); ++i)
for (Index j = 0; j < m.cols(); ++j)
m3(i,j) = std::atan2(m1(i,j).imag(), m1(i,j).real());
VERIFY_IS_APPROX(arg(m1), m3);
std::complex<RealScalar> zero(0.0,0.0);
VERIFY((Eigen::isnan)(m1*zero/zero).all());
#if EIGEN_COMP_MSVC
// msvc complex division is not robust
VERIFY((Eigen::isinf)(m4/RealScalar(0)).all());
#else
#if EIGEN_COMP_CLANG
// clang's complex division is notoriously broken too
if((numext::isinf)(m4(0,0)/RealScalar(0))) {
#endif
VERIFY((Eigen::isinf)(m4/zero).all());
#if EIGEN_COMP_CLANG
}
else
{
VERIFY((Eigen::isinf)(m4.real()/zero.real()).all());
}
#endif
#endif // MSVC
VERIFY(((Eigen::isfinite)(m1) && (!(Eigen::isfinite)(m1*zero/zero)) && (!(Eigen::isfinite)(m1/zero))).all());
VERIFY_IS_APPROX(inverse(inverse(m1)),m1);
VERIFY_IS_APPROX(conj(m1.conjugate()), m1);
VERIFY_IS_APPROX(abs(m1), sqrt(square(m1.real())+square(m1.imag())));
VERIFY_IS_APPROX(abs(m1), sqrt(abs2(m1)));
VERIFY_IS_APPROX(log10(m1), log(m1)/log(10));
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VERIFY_IS_APPROX(log2(m1), log(m1)/log(2));
VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
VERIFY_IS_APPROX( m1.sign() * m1.abs(), m1);
// scalar by array division
Scalar s1 = internal::random<Scalar>();
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const RealScalar tiny = std::sqrt(std::numeric_limits<RealScalar>::epsilon());
s1 += Scalar(tiny);
m1 += ArrayType::Constant(rows,cols,Scalar(tiny));
VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse());
// check inplace transpose
m2 = m1;
m2.transposeInPlace();
VERIFY_IS_APPROX(m2, m1.transpose());
m2.transposeInPlace();
VERIFY_IS_APPROX(m2, m1);
Block transposeInPlace() when the matrix is real and square. This yields a large speedup because we transpose in registers (or L1 if we spill), instead of one packet at a time, which in the worst case makes the code write to the same cache line PacketSize times instead of once. rmlarsen@rmlarsen4:.../eigen_bench/google3$ benchy --benchmarks=.*TransposeInPlace.*float.* --reference=srcfs experimental/users/rmlarsen/bench:matmul_bench 10 / 10 [====================================================================================================================================================================================================================] 100.00% 2m50s (Generated by http://go/benchy. Settings: --runs 5 --benchtime 1s --reference "srcfs" --benchmarks ".*TransposeInPlace.*float.*" experimental/users/rmlarsen/bench:matmul_bench) name old time/op new time/op delta BM_TransposeInPlace<float>/4 9.84ns ± 0% 6.51ns ± 0% -33.80% (p=0.008 n=5+5) BM_TransposeInPlace<float>/8 23.6ns ± 1% 17.6ns ± 0% -25.26% (p=0.016 n=5+4) BM_TransposeInPlace<float>/16 78.8ns ± 0% 60.3ns ± 0% -23.50% (p=0.029 n=4+4) BM_TransposeInPlace<float>/32 302ns ± 0% 229ns ± 0% -24.40% (p=0.008 n=5+5) BM_TransposeInPlace<float>/59 1.03µs ± 0% 0.84µs ± 1% -17.87% (p=0.016 n=5+4) BM_TransposeInPlace<float>/64 1.20µs ± 0% 0.89µs ± 1% -25.81% (p=0.008 n=5+5) BM_TransposeInPlace<float>/128 8.96µs ± 0% 3.82µs ± 2% -57.33% (p=0.008 n=5+5) BM_TransposeInPlace<float>/256 152µs ± 3% 17µs ± 2% -89.06% (p=0.008 n=5+5) BM_TransposeInPlace<float>/512 837µs ± 1% 208µs ± 0% -75.15% (p=0.008 n=5+5) BM_TransposeInPlace<float>/1k 4.28ms ± 2% 1.08ms ± 2% -74.72% (p=0.008 n=5+5)
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// Check vectorized inplace transpose.
ArrayType m5 = ArrayType::Random(131, 131);
Block transposeInPlace() when the matrix is real and square. This yields a large speedup because we transpose in registers (or L1 if we spill), instead of one packet at a time, which in the worst case makes the code write to the same cache line PacketSize times instead of once. rmlarsen@rmlarsen4:.../eigen_bench/google3$ benchy --benchmarks=.*TransposeInPlace.*float.* --reference=srcfs experimental/users/rmlarsen/bench:matmul_bench 10 / 10 [====================================================================================================================================================================================================================] 100.00% 2m50s (Generated by http://go/benchy. Settings: --runs 5 --benchtime 1s --reference "srcfs" --benchmarks ".*TransposeInPlace.*float.*" experimental/users/rmlarsen/bench:matmul_bench) name old time/op new time/op delta BM_TransposeInPlace<float>/4 9.84ns ± 0% 6.51ns ± 0% -33.80% (p=0.008 n=5+5) BM_TransposeInPlace<float>/8 23.6ns ± 1% 17.6ns ± 0% -25.26% (p=0.016 n=5+4) BM_TransposeInPlace<float>/16 78.8ns ± 0% 60.3ns ± 0% -23.50% (p=0.029 n=4+4) BM_TransposeInPlace<float>/32 302ns ± 0% 229ns ± 0% -24.40% (p=0.008 n=5+5) BM_TransposeInPlace<float>/59 1.03µs ± 0% 0.84µs ± 1% -17.87% (p=0.016 n=5+4) BM_TransposeInPlace<float>/64 1.20µs ± 0% 0.89µs ± 1% -25.81% (p=0.008 n=5+5) BM_TransposeInPlace<float>/128 8.96µs ± 0% 3.82µs ± 2% -57.33% (p=0.008 n=5+5) BM_TransposeInPlace<float>/256 152µs ± 3% 17µs ± 2% -89.06% (p=0.008 n=5+5) BM_TransposeInPlace<float>/512 837µs ± 1% 208µs ± 0% -75.15% (p=0.008 n=5+5) BM_TransposeInPlace<float>/1k 4.28ms ± 2% 1.08ms ± 2% -74.72% (p=0.008 n=5+5)
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ArrayType m6 = m5;
m6.transposeInPlace();
VERIFY_IS_APPROX(m6, m5.transpose());
}
template<typename ArrayType> void min_max(const ArrayType& m)
{
typedef typename ArrayType::Scalar Scalar;
Index rows = m.rows();
Index cols = m.cols();
ArrayType m1 = ArrayType::Random(rows, cols);
// min/max with array
Scalar maxM1 = m1.maxCoeff();
Scalar minM1 = m1.minCoeff();
VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, minM1), (m1.min)(ArrayType::Constant(rows,cols, minM1)));
VERIFY_IS_APPROX(m1, (m1.min)(ArrayType::Constant(rows,cols, maxM1)));
VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, maxM1), (m1.max)(ArrayType::Constant(rows,cols, maxM1)));
VERIFY_IS_APPROX(m1, (m1.max)(ArrayType::Constant(rows,cols, minM1)));
// min/max with scalar input
VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, minM1), (m1.min)( minM1));
VERIFY_IS_APPROX(m1, (m1.min)( maxM1));
VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, maxM1), (m1.max)( maxM1));
VERIFY_IS_APPROX(m1, (m1.max)( minM1));
}
EIGEN_DECLARE_TEST(array_cwise)
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{
for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( array(Array<float, 1, 1>()) );
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CALL_SUBTEST_2( array(Array22f()) );
CALL_SUBTEST_3( array(Array44d()) );
CALL_SUBTEST_4( array(ArrayXXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_5( array(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_6( array(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_6( array(Array<Index,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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}
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for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( comparisons(Array<float, 1, 1>()) );
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CALL_SUBTEST_2( comparisons(Array22f()) );
CALL_SUBTEST_3( comparisons(Array44d()) );
CALL_SUBTEST_5( comparisons(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_6( comparisons(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( min_max(Array<float, 1, 1>()) );
CALL_SUBTEST_2( min_max(Array22f()) );
CALL_SUBTEST_3( min_max(Array44d()) );
CALL_SUBTEST_5( min_max(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_6( min_max(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
}
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for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( array_real(Array<float, 1, 1>()) );
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CALL_SUBTEST_2( array_real(Array22f()) );
CALL_SUBTEST_3( array_real(Array44d()) );
CALL_SUBTEST_5( array_real(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
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}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_4( array_complex(ArrayXXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
}
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VERIFY((internal::is_same< internal::global_math_functions_filtering_base<int>::type, int >::value));
VERIFY((internal::is_same< internal::global_math_functions_filtering_base<float>::type, float >::value));
VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Array2i>::type, ArrayBase<Array2i> >::value));
typedef CwiseUnaryOp<internal::scalar_abs_op<double>, ArrayXd > Xpr;
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VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Xpr>::type,
ArrayBase<Xpr>
>::value));
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}