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39baff850c2f4fe1fee3b7a3918ba62a526e4f08
eigen/test/array.cpp
Eugene Brevdo 39baff850c Add TernaryFunctors and the betainc SpecialFunction. 
TernaryFunctors and their executors allow operations on 3-tuples of inputs.
API fully implemented for Arrays and Tensors based on binary functors.

Ported the cephes betainc function (regularized incomplete beta
integral) to Eigen, with support for CPU and GPU, floats, doubles, and
half types.

Added unit tests in array.cpp and cxx11_tensor_cuda.cu


Collapsed revision
* Merged helper methods for betainc across floats and doubles.
* Added TensorGlobalFunctions with betainc().  Removed betainc() from TensorBase.
* Clean up CwiseTernaryOp checks, change igamma_helper to cephes_helper.
* betainc: merge incbcf and incbd into incbeta_cfe.  and more cleanup.
* Update TernaryOp and SpecialFunctions (betainc) based on review comments.
2016-06-02 17:04:19 -07:00

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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// 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/.
#include "main.h"
template<typename ArrayType> void array(const ArrayType& m)
{
typedef typename ArrayType::Index Index;
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();
ArrayType m1 = ArrayType::Random(rows, cols),
m2 = ArrayType::Random(rows, cols),
m3(rows, cols);
ArrayType m4 = m1; // copy constructor
VERIFY_IS_APPROX(m1, m4);
ColVectorType cv1 = ColVectorType::Random(rows);
RowVectorType rv1 = RowVectorType::Random(cols);
Scalar s1 = internal::random<Scalar>(),
s2 = internal::random<Scalar>();
// scalar addition
VERIFY_IS_APPROX(m1 + s1, s1 + m1);
VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1);
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) );
m3 = m1;
m3 += s2;
VERIFY_IS_APPROX(m3, m1 + s2);
m3 = m1;
m3 -= s1;
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);
m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) += ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 + m2);
m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) *= ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 * m2);
m3 = m1;
m2 = ArrayType::Random(rows,cols);
m2 = (m2==0).select(1,m2);
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>()));
// 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);
// 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);
// Check possible conflicts with 1D ctor
typedef Array<Scalar, Dynamic, 1> OneDArrayType;
OneDArrayType o1(rows);
VERIFY(o1.size()==rows);
OneDArrayType o4((int)rows);
VERIFY(o4.size()==rows);
}
template<typename ArrayType> void comparisons(const ArrayType& m)
{
using std::abs;
typedef typename ArrayType::Index Index;
typedef typename ArrayType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
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 = ArrayType::Random(rows, cols),
m3(rows, cols),
m4 = m1;
m4 = (m4.abs()==Scalar(0)).select(1,m4);
VERIFY(((m1 + Scalar(1)) > m1).all());
VERIFY(((m1 - Scalar(1)) < m1).all());
if (rows*cols>1)
{
m3 = m1;
m3(r,c) += 1;
VERIFY(! (m1 < m3).all() );
VERIFY(! (m1 > m3).all() );
}
VERIFY(!(m1 > m2 && m1 < m2).any());
VERIFY((m1 <= m2 || m1 >= m2).all());
// comparisons array to scalar
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
VERIFY_IS_APPROX( (m1<m2).select(m1,m2), m1.cwiseMin(m2) );
VERIFY_IS_APPROX( (m1>m2).select(m1,m2), m1.cwiseMax(m2) );
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:
VERIFY_IS_APPROX( (m1.abs()<mid).select(0,m1), m3);
// count
VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols);
// 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<typename ArrayType::Index, Dynamic, 1> ArrayOfIndices;
// 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::Index Index;
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),
m2 = ArrayType::Random(rows, cols),
m3(rows, cols),
m4 = m1;
m4 = (m4.abs()==Scalar(0)).select(1,m4);
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_C99_MATH
VERIFY_IS_APPROX(m1.lgamma(), lgamma(m1));
VERIFY_IS_APPROX(m1.digamma(), digamma(m1));
VERIFY_IS_APPROX(m1.erf(), erf(m1));
VERIFY_IS_APPROX(m1.erfc(), erfc(m1));
#endif // EIGEN_HAS_C99_MATH
VERIFY_IS_APPROX(m1.arg(), arg(m1));
VERIFY_IS_APPROX(m1.round(), round(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));
// 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(m3.log(), log(m3));
VERIFY_IS_APPROX(m3.log1p(), log1p(m3));
VERIFY_IS_APPROX(m3.log10(), log10(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))));
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((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.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(real(m1)) + numext::abs2(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));
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());
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(pow(m1(0,0), exponents), ArrayType::Constant(rows,cols,m1(0,0)*m1(0,0)));
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));
// 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());
#if EIGEN_HAS_C99_MATH
// check special functions (comparing against numpy implementation)
if (!NumTraits<Scalar>::IsComplex)
{
{
// Test various propreties of igamma & igammac. These are normalized
// gamma integrals where
// igammac(a, x) = Gamma(a, x) / Gamma(a)
// igamma(a, x) = gamma(a, x) / Gamma(a)
// where Gamma and gamma are considered the standard unnormalized
// upper and lower incomplete gamma functions, respectively.
ArrayType a = m1.abs() + 2;
ArrayType x = m2.abs() + 2;
ArrayType zero = ArrayType::Zero(rows, cols);
ArrayType one = ArrayType::Constant(rows, cols, Scalar(1.0));
ArrayType a_m1 = a - one;
ArrayType Gamma_a_x = Eigen::igammac(a, x) * a.lgamma().exp();
ArrayType Gamma_a_m1_x = Eigen::igammac(a_m1, x) * a_m1.lgamma().exp();
ArrayType gamma_a_x = Eigen::igamma(a, x) * a.lgamma().exp();
ArrayType gamma_a_m1_x = Eigen::igamma(a_m1, x) * a_m1.lgamma().exp();
// Gamma(a, 0) == Gamma(a)
VERIFY_IS_APPROX(Eigen::igammac(a, zero), one);
// Gamma(a, x) + gamma(a, x) == Gamma(a)
VERIFY_IS_APPROX(Gamma_a_x + gamma_a_x, a.lgamma().exp());
// Gamma(a, x) == (a - 1) * Gamma(a-1, x) + x^(a-1) * exp(-x)
VERIFY_IS_APPROX(Gamma_a_x, (a - 1) * Gamma_a_m1_x + x.pow(a-1) * (-x).exp());
// gamma(a, x) == (a - 1) * gamma(a-1, x) - x^(a-1) * exp(-x)
VERIFY_IS_APPROX(gamma_a_x, (a - 1) * gamma_a_m1_x - x.pow(a-1) * (-x).exp());
}
// Check exact values of igamma and igammac against a third party calculation.
Scalar a_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
Scalar x_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
// location i*6+j corresponds to a_s[i], x_s[j].
Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
Scalar igamma_s[][6] = {{0.0, nan, nan, nan, nan, nan},
{0.0, 0.6321205588285578, 0.7768698398515702,
0.9816843611112658, 9.999500016666262e-05, 1.0},
{0.0, 0.4275932955291202, 0.608374823728911,
0.9539882943107686, 7.522076445089201e-07, 1.0},
{0.0, 0.01898815687615381, 0.06564245437845008,
0.5665298796332909, 4.166333347221828e-18, 1.0},
{0.0, 0.9999780593618628, 0.9999899967080838,
0.9999996219837988, 0.9991370418689945, 1.0},
{0.0, 0.0, 0.0, 0.0, 0.0, 0.5042041932513908}};
Scalar igammac_s[][6] = {{nan, nan, nan, nan, nan, nan},
{1.0, 0.36787944117144233, 0.22313016014842982,
0.018315638888734182, 0.9999000049998333, 0.0},
{1.0, 0.5724067044708798, 0.3916251762710878,
0.04601170568923136, 0.9999992477923555, 0.0},
{1.0, 0.9810118431238462, 0.9343575456215499,
0.4334701203667089, 1.0, 0.0},
{1.0, 2.1940638138146658e-05, 1.0003291916285e-05,
3.7801620118431334e-07, 0.0008629581310054535,
0.0},
{1.0, 1.0, 1.0, 1.0, 1.0, 0.49579580674813944}};
for (int i = 0; i < 6; ++i) {
for (int j = 0; j < 6; ++j) {
if ((std::isnan)(igamma_s[i][j])) {
VERIFY((std::isnan)(numext::igamma(a_s[i], x_s[j])));
} else {
VERIFY_IS_APPROX(numext::igamma(a_s[i], x_s[j]), igamma_s[i][j]);
}
if ((std::isnan)(igammac_s[i][j])) {
VERIFY((std::isnan)(numext::igammac(a_s[i], x_s[j])));
} else {
VERIFY_IS_APPROX(numext::igammac(a_s[i], x_s[j]), igammac_s[i][j]);
}
}
}
}
#endif // EIGEN_HAS_C99_MATH
// 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::Index Index;
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),
m2(rows, cols),
m4 = m1;
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));
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));
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(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))));
for (Index i = 0; i < m.rows(); ++i)
for (Index j = 0; j < m.cols(); ++j)
m3(i,j) = std::atan2(imag(m1(i,j)), real(m1(i,j)));
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(real(m1))+square(imag(m1))));
VERIFY_IS_APPROX(abs(m1), sqrt(abs2(m1)));
VERIFY_IS_APPROX(log10(m1), log(m1)/log(10));
VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
VERIFY_IS_APPROX( m1.sign() * m1.abs(), m1);
// scalar by array division
Scalar s1 = internal::random<Scalar>();
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);
}
template<typename ArrayType> void min_max(const ArrayType& m)
{
typedef typename ArrayType::Index Index;
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));
}
template<typename X, typename Y>
void verify_component_wise(const X& x, const Y& y)
{
for(Index i=0; i<x.size(); ++i)
{
if((numext::isfinite)(y(i)))
VERIFY_IS_APPROX( x(i), y(i) );
else if((numext::isnan)(y(i)))
VERIFY((numext::isnan)(x(i)));
else
VERIFY_IS_EQUAL( x(i), y(i) );
}
}
// check special functions (comparing against numpy implementation)
template<typename ArrayType> void array_special_functions()
{
using std::abs;
using std::sqrt;
typedef typename ArrayType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
Scalar plusinf = std::numeric_limits<Scalar>::infinity();
Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
// Check the zeta function against scipy.special.zeta
{
ArrayType x(7), q(7), res(7), ref(7);
x << 1.5, 4, 10.5, 10000.5, 3, 1, 0.9;
q << 2, 1.5, 3, 1.0001, -2.5, 1.2345, 1.2345;
ref << 1.61237534869, 0.234848505667, 1.03086757337e-5, 0.367879440865, 0.054102025820864097, plusinf, nan;
CALL_SUBTEST( verify_component_wise(ref, ref); );
CALL_SUBTEST( res = x.zeta(q); verify_component_wise(res, ref); );
CALL_SUBTEST( res = zeta(x,q); verify_component_wise(res, ref); );
}
// digamma
{
ArrayType x(7), res(7), ref(7);
x << 1, 1.5, 4, -10.5, 10000.5, 0, -1;
ref << -0.5772156649015329, 0.03648997397857645, 1.2561176684318, 2.398239129535781, 9.210340372392849, plusinf, plusinf;
CALL_SUBTEST( verify_component_wise(ref, ref); );
CALL_SUBTEST( res = x.digamma(); verify_component_wise(res, ref); );
CALL_SUBTEST( res = digamma(x); verify_component_wise(res, ref); );
}
#if EIGEN_HAS_C99_MATH
{
ArrayType n(11), x(11), res(11), ref(11);
n << 1, 1, 1, 1.5, 17, 31, 28, 8, 42, 147, 170;
x << 2, 3, 25.5, 1.5, 4.7, 11.8, 17.7, 30.2, 15.8, 54.1, 64;
ref << 0.644934066848, 0.394934066848, 0.0399946696496, nan, 293.334565435, 0.445487887616, -2.47810300902e-07, -8.29668781082e-09, -0.434562276666, 0.567742190178, -0.0108615497927;
CALL_SUBTEST( verify_component_wise(ref, ref); );
if(sizeof(RealScalar)>=8) { // double
// Reason for commented line: http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
// CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res, ref); );
CALL_SUBTEST( res = polygamma(n,x); verify_component_wise(res, ref); );
}
else {
// CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res.head(8), ref.head(8)); );
CALL_SUBTEST( res = polygamma(n,x); verify_component_wise(res.head(8), ref.head(8)); );
}
}
#endif
#if EIGEN_HAS_C99_MATH
{
// Inputs and ground truth generated with scipy via:
// a = np.logspace(-3, 3, 5) - 1e-3
// b = np.logspace(-3, 3, 5) - 1e-3
// x = np.linspace(-0.1, 1.1, 5)
// (full_a, full_b, full_x) = np.vectorize(lambda a, b, x: (a, b, x))(*np.ix_(a, b, x))
// full_a = full_a.flatten().tolist() # same for full_b, full_x
// v = scipy.special.betainc(full_a, full_b, full_x).flatten().tolist()
//
// Note in Eigen, we call betainc with arguments in the order (x, a, b).
ArrayType a(125);
ArrayType b(125);
ArrayType x(125);
ArrayType v(125);
ArrayType res(125);
a << 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
999.999, 999.999, 999.999;
b << 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999,
999.999, 999.999, 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.999, 0.999, 0.999, 0.999,
0.999, 31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
31.62177660168379, 31.62177660168379, 31.62177660168379,
31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
999.999, 999.999;
x << -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1,
-0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8,
1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
0.8, 1.1;
v << nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
nan, nan, nan, 0.47972119876364683, 0.5, 0.5202788012363533, nan, nan,
0.9518683957740043, 0.9789663010413743, 0.9931729188073435, nan, nan,
0.999995949033062, 0.9999999999993698, 0.9999999999999999, nan, nan,
0.9999999999999999, 0.9999999999999999, 0.9999999999999999, nan, nan,
nan, nan, nan, nan, nan, 0.006827081192655869, 0.0210336989586256,
0.04813160422599567, nan, nan, 0.20014344256217678, 0.5000000000000001,
0.7998565574378232, nan, nan, 0.9991401428435834, 0.999999999698403,
0.9999999999999999, nan, nan, 0.9999999999999999, 0.9999999999999999,
0.9999999999999999, nan, nan, nan, nan, nan, nan, nan,
1.0646600232370887e-25, 6.301722877826246e-13, 4.050966937974938e-06,
nan, nan, 7.864342668429763e-23, 3.015969667594166e-10,
0.0008598571564165444, nan, nan, 6.031987710123844e-08,
0.5000000000000007, 0.9999999396801229, nan, nan, 0.9999999999999999,
0.9999999999999999, 0.9999999999999999, nan, nan, nan, nan, nan, nan,
nan, 0.0, 7.029920380986636e-306, 2.2450728208591345e-101, nan, nan,
0.0, 9.275871147869727e-302, 1.2232913026152827e-97, nan, nan, 0.0,
3.0891393081932924e-252, 2.9303043666183996e-60, nan, nan,
2.248913486879199e-196, 0.5000000000004947, 0.9999999999999999, nan;
CALL_SUBTEST(res = betainc(a, b, x);
verify_component_wise(res, v););
}
#endif
}
void test_array()
{
#ifndef EIGEN_HAS_C99_MATH
std::cerr << "WARNING: testing of special math functions disabled" << std::endl;
#endif
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( array(Array<float, 1, 1>()) );
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))) );
}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( comparisons(Array<float, 1, 1>()) );
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))) );
}
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))) );
}
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( array_real(Array<float, 1, 1>()) );
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))) );
}
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))) );
}
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_multiple_op<double>, ArrayXd > Xpr;
VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Xpr>::type,
ArrayBase<Xpr>
>::value));
CALL_SUBTEST_7(array_special_functions<ArrayXf>());
CALL_SUBTEST_7(array_special_functions<ArrayXd>());
}
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