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eigen/test/array_cwise.cpp

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forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
// This file is part of Eigen, a lightweight C++ template library
remove sentence "Eigen itself is part of the KDE project." it never made very precise sense. but now does it still make any?
2009-05-23 02:25:33 +08:00
// for linear algebra.
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
//
email change
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// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
forgot to add the unit test array.cpp
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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/.
Remove erroneously committed debugging stuff.
2013-02-25 08:17:44 +08:00
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
#include "main.h"
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
// Test the corner cases of pow(x, y) for real types.
template<typename Scalar>
void pow_test() {
const Scalar zero = Scalar(0);
Augment NumTraits with min/max_exponent() again. Replace usage of `std::numeric_limits<...>::min/max_exponent` in codebase where possible. Also replaced some other `numeric_limits` usages in affected tests with the `NumTraits` equivalent. The previous MR !443 failed for c++03 due to lack of `constexpr`. Because of this, we need to keep around the `std::numeric_limits` version in enum expressions until the switch to c++11. Fixes #2148
2021-03-17 11:12:46 +08:00
const Scalar eps = Eigen::NumTraits<Scalar>::epsilon();
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
const Scalar one = Scalar(1);
Add more tests for pow and fix a corner case for huge exponent where the result is always zero or infinite unless x is one.
2021-02-06 08:58:49 +08:00
const Scalar two = Scalar(2);
const Scalar three = Scalar(3);
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
const Scalar sqrt_half = Scalar(std::sqrt(0.5));
const Scalar sqrt2 = Scalar(std::sqrt(2));
Augment NumTraits with min/max_exponent() again. Replace usage of `std::numeric_limits<...>::min/max_exponent` in codebase where possible. Also replaced some other `numeric_limits` usages in affected tests with the `NumTraits` equivalent. The previous MR !443 failed for c++03 due to lack of `constexpr`. Because of this, we need to keep around the `std::numeric_limits` version in enum expressions until the switch to c++11. Fixes #2148
2021-03-17 11:12:46 +08:00
const Scalar inf = Eigen::NumTraits<Scalar>::infinity();
const Scalar nan = Eigen::NumTraits<Scalar>::quiet_NaN();
New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
2021-02-17 10:50:32 +08:00
const Scalar denorm_min = std::numeric_limits<Scalar>::denorm_min();
Add more tests for pow and fix a corner case for huge exponent where the result is always zero or infinite unless x is one.
2021-02-06 08:58:49 +08:00
const Scalar min = (std::numeric_limits<Scalar>::min)();
const Scalar max = (std::numeric_limits<Scalar>::max)();
Augment NumTraits with min/max_exponent() again. Replace usage of `std::numeric_limits<...>::min/max_exponent` in codebase where possible. Also replaced some other `numeric_limits` usages in affected tests with the `NumTraits` equivalent. The previous MR !443 failed for c++03 due to lack of `constexpr`. Because of this, we need to keep around the `std::numeric_limits` version in enum expressions until the switch to c++11. Fixes #2148
2021-03-17 11:12:46 +08:00
const Scalar max_exp = (static_cast<Scalar>(int(Eigen::NumTraits<Scalar>::max_exponent())) * Scalar(EIGEN_LN2)) / eps;
New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
2021-02-17 10:50:32 +08:00
Add more tests for pow and fix a corner case for huge exponent where the result is always zero or infinite unless x is one.
2021-02-06 08:58:49 +08:00
const static Scalar abs_vals[] = {zero,
New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
2021-02-17 10:50:32 +08:00
denorm_min,
min,
eps,
Add more tests for pow and fix a corner case for huge exponent where the result is always zero or infinite unless x is one.
2021-02-06 08:58:49 +08:00
sqrt_half,
one,
sqrt2,
two,
three,
New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
2021-02-17 10:50:32 +08:00
max_exp,
Add more tests for pow and fix a corner case for huge exponent where the result is always zero or infinite unless x is one.
2021-02-06 08:58:49 +08:00
max,
inf,
nan};
New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
2021-02-17 10:50:32 +08:00
const int abs_cases = 13;
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
const int num_cases = 2*abs_cases * 2*abs_cases;
// Repeat the same value to make sure we hit the vectorized path.
const int num_repeats = 32;
Array<Scalar, Dynamic, Dynamic> x(num_repeats, num_cases);
Array<Scalar, Dynamic, Dynamic> y(num_repeats, num_cases);
int count = 0;
for (int i = 0; i < abs_cases; ++i) {
const Scalar abs_x = abs_vals[i];
for (int sign_x = 0; sign_x < 2; ++sign_x) {
Scalar x_case = sign_x == 0 ? -abs_x : abs_x;
for (int j = 0; j < abs_cases; ++j) {
const Scalar abs_y = abs_vals[j];
for (int sign_y = 0; sign_y < 2; ++sign_y) {
Scalar y_case = sign_y == 0 ? -abs_y : abs_y;
for (int repeat = 0; repeat < num_repeats; ++repeat) {
x(repeat, count) = x_case;
y(repeat, count) = y_case;
}
++count;
}
}
}
}
Array<Scalar, Dynamic, Dynamic> actual = x.pow(y);
const Scalar tol = test_precision<Scalar>();
bool all_pass = true;
for (int i = 0; i < 1; ++i) {
for (int j = 0; j < num_cases; ++j) {
New accurate algorithm for pow(x,y). This version is accurate to 1.4 ulps for float, while still being 10x faster than std::pow for AVX512. A future change will introduce a specialization for double.
2021-02-17 10:50:32 +08:00
Scalar e = static_cast<Scalar>(std::pow(x(i,j), y(i,j)));
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
Scalar a = actual(i, j);
Replace std::isnan with numext::isnan for c++03
2021-01-24 03:02:35 +08:00
bool fail = !(a==e) && !internal::isApprox(a, e, tol) && !((numext::isnan)(a) && (numext::isnan)(e));
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
all_pass &= !fail;
if (fail) {
std::cout << "pow(" << x(i,j) << "," << y(i,j) << ") = " << a << " != " << e << std::endl;
}
}
}
VERIFY(all_pass);
}
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
template<typename ArrayType> void array(const ArrayType& m)
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
{
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
typedef typename ArrayType::Scalar Scalar;
bug #1247: fix regression in compilation of pow(integer,integer), and add respective unit tests.
2016-06-25 16:12:06 +08:00
typedef typename ArrayType::RealScalar RealScalar;
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType;
typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType;
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
Utilize Index in all unit tests.
2010-06-20 23:37:56 +08:00
Index rows = m.rows();
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
Index cols = m.cols();
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
ArrayType m1 = ArrayType::Random(rows, cols),
m2 = ArrayType::Random(rows, cols),
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
m3(rows, cols);
Constructing a Matrix/Array with implicit transpose could lead to memory leaks. Also reduced code duplication for Matrix/Array constructors
2015-04-16 19:25:20 +08:00
ArrayType m4 = m1; // copy constructor
VERIFY_IS_APPROX(m1, m4);
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
* rename PartialRedux to VectorwiseOp * add VectorwiseOp's +, -, +=, -= operators
2009-06-10 17:20:30 +08:00
ColVectorType cv1 = ColVectorType::Random(rows);
RowVectorType rv1 = RowVectorType::Random(cols);
bug #86 : use internal:: namespace instead of ei_ prefix
2010-10-25 22:15:22 +08:00
Scalar s1 = internal::random<Scalar>(),
Added support for scalar / array division.
2012-03-02 23:27:27 +08:00
s2 = internal::random<Scalar>();
Add a Select expression in the Array module which mimics a coeff-wise ?: operator. Example: mat = (mat.cwise().abs().cwise() < Ones()).select(0,mat); replaces all small values by 0. (the scalar version is "s = abs(s)<1 ? 0 : s")
2008-09-04 01:16:28 +08:00
// scalar addition
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY_IS_APPROX(m1 + s1, s1 + m1);
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1);
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY_IS_APPROX(s1 - m1, (-m1)+s1 );
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
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) );
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
m3 = m1;
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
m3 += s2;
VERIFY_IS_APPROX(m3, m1 + s2);
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
m3 = m1;
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
m3 -= s1;
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
VERIFY_IS_APPROX(m3, m1 - s1);
Fixed compound subtraction in ArrayBase where the assignment needs to be carried out on the derived type. Added unit tests for map based component wise arithmetic.
2010-12-17 00:34:13 +08:00
// 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);
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
Fixed compound subtraction in ArrayBase where the assignment needs to be carried out on the derived type. Added unit tests for map based component wise arithmetic.
2010-12-17 00:34:13 +08:00
m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) += ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 + m2);
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
Fixed compound subtraction in ArrayBase where the assignment needs to be carried out on the derived type. Added unit tests for map based component wise arithmetic.
2010-12-17 00:34:13 +08:00
m3 = m1;
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) *= ArrayType::Map(m2.data(), m2.rows(), m2.cols());
VERIFY_IS_APPROX(m1, m3 * m2);
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
Fixed compound subtraction in ArrayBase where the assignment needs to be carried out on the derived type. Added unit tests for map based component wise arithmetic.
2010-12-17 00:34:13 +08:00
m3 = m1;
m2 = ArrayType::Random(rows,cols);
m2 = (m2==0).select(1,m2);
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
ArrayType::Map(m1.data(), m1.rows(), m1.cols()) /= ArrayType::Map(m2.data(), m2.rows(), m2.cols());
Fixed compound subtraction in ArrayBase where the assignment needs to be carried out on the derived type. Added unit tests for map based component wise arithmetic.
2010-12-17 00:34:13 +08:00
VERIFY_IS_APPROX(m1, m3 / m2);
Added MatrixBase::Unit*() static function to easily create unit/basis vectors. Removed EulerAngles, addes typdefs for Quaternion and AngleAxis, and added automatic conversions from Quaternion/AngleAxis to Matrix3 such that: Matrix3f m = AngleAxisf(0.2,Vector3f::UnitX) * AngleAxisf(0.2,Vector3f::UnitY); just works.
2008-07-19 21:03:23 +08:00
Add a Select expression in the Array module which mimics a coeff-wise ?: operator. Example: mat = (mat.cwise().abs().cwise() < Ones()).select(0,mat); replaces all small values by 0. (the scalar version is "s = abs(s)<1 ? 0 : s")
2008-09-04 01:16:28 +08:00
// reductions
Fix array unit test: isApprox(log(0),log(0)) is false, and summing up signed float value might result in very small values and thus large numerical errors
2013-02-24 05:58:14 +08:00
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());
Fix another issue related to summing up many signed values.
2013-02-24 06:06:45 +08:00
if (!internal::isMuchSmallerThan(abs(m1.sum() - (m1+m2).sum()), m1.abs().sum(), test_precision<Scalar>()))
Improved the array unit test - internal::isApprox needs to use the same precision as VERIFY_IS_NOT_APPROX. Removed debug code from test_isApprox.
2010-12-17 01:53:02 +08:00
VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
Relax mixing-type constraints for binary coefficient-wise operators: - Replace internal::scalar_product_traits<A,B> by Eigen::ScalarBinaryOpTraits<A,B,OP> - Remove the "functor_is_product_like" helper (was pretty ugly) - Currently, OP is not used, but it is available to the user for fine grained tuning - Currently, only the following operators have been generalized: *,/,+,-,=,*=,/=,+=,-= - TODO: generalize all other binray operators (comparisons,pow,etc.) - TODO: handle "scalar op array" operators (currently only * is handled) - TODO: move the handling of the "void" scalar type to ScalarBinaryOpTraits
2016-06-06 21:11:41 +08:00
VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
* rename PartialRedux to VectorwiseOp * add VectorwiseOp's +, -, +=, -= operators
2009-06-10 17:20:30 +08:00
// 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);
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
bug #100: add support for explicit scalar to Array conversion (as enable implicit conversion is much more tricky)
2014-09-19 19:25:28 +08:00
// 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;
Add more extensive tests of Array ctors, including {} variants
2019-01-22 22:30:50 +08:00
{
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
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
bug #1247: fix regression in compilation of pow(integer,integer), and add respective unit tests.
2016-06-25 16:12:06 +08:00
// 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());
Fix compilation of some unit tests with msvc
2016-07-04 17:49:03 +08:00
VERIFY_IS_APPROX(Eigen::pow(m1(0,0), exponents), ArrayType::Constant(rows,cols,m1(0,0)*m1(0,0)));
bug #1247: fix regression in compilation of pow(integer,integer), and add respective unit tests.
2016-06-25 16:12:06 +08:00
bug #100: add support for explicit scalar to Array conversion (as enable implicit conversion is much more tricky)
2014-09-19 19:25:28 +08:00
// Check possible conflicts with 1D ctor
typedef Array<Scalar, Dynamic, 1> OneDArrayType;
Add more extensive tests of Array ctors, including {} variants
2019-01-22 22:30:50 +08:00
{
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
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
}
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
template<typename ArrayType> void comparisons(const ArrayType& m)
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
{
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
using std::abs;
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
typedef typename ArrayType::Scalar Scalar;
fix msvc warnings (useful ones again) reported by gael on CDash
2009-01-27 01:56:04 +08:00
typedef typename NumTraits<Scalar>::Real RealScalar;
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
Utilize Index in all unit tests.
2010-06-20 23:37:56 +08:00
Index rows = m.rows();
Index cols = m.cols();
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
bug #86 : use internal:: namespace instead of ei_ prefix
2010-10-25 22:15:22 +08:00
Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
ArrayType m1 = ArrayType::Random(rows, cols),
Fix isinf unit tests
2015-06-22 22:48:27 +08:00
m2 = ArrayType::Random(rows, cols),
m3(rows, cols),
m4 = m1;
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
Fix isinf unit tests
2015-06-22 22:48:27 +08:00
m4 = (m4.abs()==Scalar(0)).select(1,m4);
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY(((m1 + Scalar(1)) > m1).all());
VERIFY(((m1 - Scalar(1)) < m1).all());
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
if (rows*cols>1)
{
m3 = m1;
m3(r,c) += 1;
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY(! (m1 < m3).all() );
VERIFY(! (m1 > m3).all() );
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
}
bug #872: Avoid deprecated binder1st/binder2nd usage by providing custom functors for comparison operators
2015-05-07 23:28:40 +08:00
VERIFY(!(m1 > m2 && m1 < m2).any());
VERIFY((m1 <= m2 || m1 >= m2).all());
* rename PartialRedux to VectorwiseOp * add VectorwiseOp's +, -, +=, -= operators
2009-06-10 17:20:30 +08:00
Added comparisons scalar to array (previously only the array to scalar was possible) (Fixes bug #147) Extended the unit test for that
2013-10-17 21:37:29 +08:00
// comparisons array to scalar
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY( (m1 != (m1(r,c)+1) ).any() );
Added comparisons scalar to array (previously only the array to scalar was possible) (Fixes bug #147) Extended the unit test for that
2013-10-17 21:37:29 +08:00
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() );
* rename PartialRedux to VectorwiseOp * add VectorwiseOp's +, -, +=, -= operators
2009-06-10 17:20:30 +08:00
Add a Select expression in the Array module which mimics a coeff-wise ?: operator. Example: mat = (mat.cwise().abs().cwise() < Ones()).select(0,mat); replaces all small values by 0. (the scalar version is "s = abs(s)<1 ? 0 : s")
2008-09-04 01:16:28 +08:00
// test Select
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY_IS_APPROX( (m1<m2).select(m1,m2), m1.cwiseMin(m2) );
VERIFY_IS_APPROX( (m1>m2).select(m1,m2), m1.cwiseMax(m2) );
a lot of cleaning and fixes
2009-12-17 02:18:40 +08:00
Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2);
Add a Select expression in the Array module which mimics a coeff-wise ?: operator. Example: mat = (mat.cwise().abs().cwise() < Ones()).select(0,mat); replaces all small values by 0. (the scalar version is "s = abs(s)<1 ? 0 : s")
2008-09-04 01:16:28 +08:00
for (int j=0; j<cols; ++j)
for (int i=0; i<rows; ++i)
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
m3(i,j) = abs(m1(i,j))<mid ? 0 : m1(i,j);
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
VERIFY_IS_APPROX( (m1.abs()<ArrayType::Constant(rows,cols,mid))
.select(ArrayType::Zero(rows,cols),m1), m3);
Add coeff-wise comparisons to scalar operators. You can now write: mat.cwise() < 2 instead of: mat.cwise() < MatrixType::Constant(mat.rows(), mat.cols(), 2)
2008-09-04 01:56:06 +08:00
// shorter versions:
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
VERIFY_IS_APPROX( (m1.abs()<ArrayType::Constant(rows,cols,mid))
Add a Select expression in the Array module which mimics a coeff-wise ?: operator. Example: mat = (mat.cwise().abs().cwise() < Ones()).select(0,mat); replaces all small values by 0. (the scalar version is "s = abs(s)<1 ? 0 : s")
2008-09-04 01:16:28 +08:00
.select(0,m1), m3);
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
VERIFY_IS_APPROX( (m1.abs()>=ArrayType::Constant(rows,cols,mid))
Add a Select expression in the Array module which mimics a coeff-wise ?: operator. Example: mat = (mat.cwise().abs().cwise() < Ones()).select(0,mat); replaces all small values by 0. (the scalar version is "s = abs(s)<1 ? 0 : s")
2008-09-04 01:16:28 +08:00
.select(m1,0), m3);
Add coeff-wise comparisons to scalar operators. You can now write: mat.cwise() < 2 instead of: mat.cwise() < MatrixType::Constant(mat.rows(), mat.cols(), 2)
2008-09-04 01:56:06 +08:00
// even shorter version:
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY_IS_APPROX( (m1.abs()<mid).select(0,m1), m3);
* rename PartialRedux to VectorwiseOp * add VectorwiseOp's +, -, +=, -= operators
2009-06-10 17:20:30 +08:00
add partial count redux (adapted patch from Ricard Marxer)
2009-01-24 23:22:44 +08:00
// count
add unit tests for true array objects
2010-01-19 05:54:20 +08:00
VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols);
the Index types change. As discussed on the list (too long to explain here).
2010-05-31 04:00:58 +08:00
add boolean || and && operators
2011-06-01 04:17:34 +08:00
// 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());
Remove local Index typedef from unit-tests
2018-07-12 23:16:40 +08:00
typedef Array<Index, Dynamic, 1> ArrayOfIndices;
implicit conversion to scalar for inner product
2010-06-02 15:45:57 +08:00
a lot of cleaning and fixes
2009-12-17 02:18:40 +08:00
// TODO allows colwise/rowwise for array
the Index types change. As discussed on the list (too long to explain here).
2010-05-31 04:00:58 +08:00
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));
add lpNorm<p>() method to MatrixBase, implemented in Array module, with specializations for cases p=1,2,Eigen::Infinity.
2008-11-04 06:47:00 +08:00
}
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
template<typename ArrayType> void array_real(const ArrayType& m)
add support for global math function for array
2010-01-28 06:23:59 +08:00
{
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
using std::abs;
Fix a couple of warnings in unit tests.
2013-07-05 19:35:34 +08:00
using std::sqrt;
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
typedef typename ArrayType::Scalar Scalar;
add support for global math function for array
2010-01-28 06:23:59 +08:00
typedef typename NumTraits<Scalar>::Real RealScalar;
Utilize Index in all unit tests.
2010-06-20 23:37:56 +08:00
Index rows = m.rows();
Index cols = m.cols();
add support for global math function for array
2010-01-28 06:23:59 +08:00
Complete rework of global math functions and NumTraits. * Now completely generic so all standard integer types (like char...) are supported. ** add unit test for that (integer_types). * NumTraits does no longer inherit numeric_limits * All math functions are now templated * Better guard (static asserts) against using certain math functions on integer types.
2010-04-29 06:51:38 +08:00
ArrayType m1 = ArrayType::Random(rows, cols),
fix compilation of ArrayBase::transposeInPlace
2013-06-24 19:33:44 +08:00
m2 = ArrayType::Random(rows, cols),
Fix isinf unit tests
2015-06-22 22:48:27 +08:00
m3(rows, cols),
m4 = m1;
Only test the lgamma, erf and erfc function when using a C99 compliant compiler
2015-12-11 05:13:45 +08:00
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
m4 = (m4.abs()==Scalar(0)).select(Scalar(1),m4);
add support for global math function for array
2010-01-28 06:23:59 +08:00
rm cC++11 features
2012-03-09 19:08:06 +08:00
Scalar s1 = internal::random<Scalar>();
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
// these tests are mostly to check possible compilation issues with free-functions.
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
VERIFY_IS_APPROX(m1.sin(), sin(m1));
VERIFY_IS_APPROX(m1.cos(), cos(m1));
Add hyperbolic trigonometric functions from std array support
2015-03-11 11:13:30 +08:00
VERIFY_IS_APPROX(m1.tan(), tan(m1));
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
VERIFY_IS_APPROX(m1.asin(), asin(m1));
VERIFY_IS_APPROX(m1.acos(), acos(m1));
Add documentation and very simple test for array atan(), part 2 (files I forget in the previous commit).
2014-06-19 22:12:33 +08:00
VERIFY_IS_APPROX(m1.atan(), atan(m1));
Add hyperbolic trigonometric functions from std array support
2015-03-11 11:13:30 +08:00
VERIFY_IS_APPROX(m1.sinh(), sinh(m1));
VERIFY_IS_APPROX(m1.cosh(), cosh(m1));
VERIFY_IS_APPROX(m1.tanh(), tanh(m1));
Add support for inverse hyperbolic functions. Fix cost of division.
2019-01-12 09:45:37 +08:00
#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
sigmoid -> logistic
2018-08-14 02:14:50 +08:00
VERIFY_IS_APPROX(m1.logistic(), logistic(m1));
bug #1232: refactor special functions as a new SpecialFunctions module, currently in unsupported/.
2016-07-08 17:13:55 +08:00
Add log10 array support
2015-03-11 06:56:42 +08:00
VERIFY_IS_APPROX(m1.arg(), arg(m1));
Additional unary coeff-wise functors (isnan, round, arg, e.g.)
2015-03-11 04:39:23 +08:00
VERIFY_IS_APPROX(m1.round(), round(m1));
Bug #1785: Introduce numext::rint. This provides a new op that matches std::rint and previous behavior of pround. Also adds corresponding unsupported/../Tensor op. Performance is the same as e. g. floor (tested SSE/AVX).
2019-12-17 05:00:35 +08:00
VERIFY_IS_APPROX(m1.rint(), rint(m1));
Additional unary coeff-wise functors (isnan, round, arg, e.g.)
2015-03-11 04:39:23 +08:00
VERIFY_IS_APPROX(m1.floor(), floor(m1));
VERIFY_IS_APPROX(m1.ceil(), ceil(m1));
Protect all calls to isnan, isinf and isfinite with parentheses.
2015-08-14 23:32:34 +08:00
VERIFY((m1.isNaN() == (Eigen::isnan)(m1)).all());
VERIFY((m1.isInf() == (Eigen::isinf)(m1)).all());
VERIFY((m1.isFinite() == (Eigen::isfinite)(m1)).all());
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX(m4.inverse(), inverse(m4));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
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));
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
VERIFY_IS_APPROX(cos(m1+RealScalar(3)*m2), cos((m1+RealScalar(3)*m2).eval()));
ArrayBase::sign: add unit test and fix doc
2015-11-27 23:27:53 +08:00
VERIFY_IS_APPROX(m1.sign(), sign(m1));
Change the sign operator in Eigen to return NaN for NaN arguments, not zero.
2020-07-07 09:54:04 +08:00
VERIFY((m1.sqrt().sign().isNaN() == (Eigen::isnan)(sign(sqrt(m1)))).all());
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
// avoid inf and NaNs so verification doesn't fail
m3 = m4.abs();
VERIFY_IS_APPROX(m3.sqrt(), sqrt(abs(m3)));
VERIFY_IS_APPROX(m3.rsqrt(), Scalar(1)/sqrt(abs(m3)));
VERIFY_IS_APPROX(rsqrt(m3), Scalar(1)/sqrt(abs(m3)));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(m3.log(), log(m3));
Expose log1p to Array.
2016-06-01 23:00:08 +08:00
VERIFY_IS_APPROX(m3.log1p(), log1p(m3));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(m3.log10(), log10(m3));
Add log2() to Eigen.
2020-12-05 05:45:09 +08:00
VERIFY_IS_APPROX(m3.log2(), log2(m3));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
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);
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX(sinh(m1), Scalar(0.5)*(exp(m1)-exp(-m1)));
VERIFY_IS_APPROX(cosh(m1), Scalar(0.5)*(exp(m1)+exp(-m1)));
VERIFY_IS_APPROX(tanh(m1), (Scalar(0.5)*(exp(m1)-exp(-m1)))/(Scalar(0.5)*(exp(m1)+exp(-m1))));
VERIFY_IS_APPROX(logistic(m1), (Scalar(1)/(Scalar(1)+exp(-m1))));
VERIFY_IS_APPROX(arg(m1), ((m1<Scalar(0)).template cast<Scalar>())*Scalar(std::acos(Scalar(-1))));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY((round(m1) <= ceil(m1) && round(m1) >= floor(m1)).all());
Bug #1785: Introduce numext::rint. This provides a new op that matches std::rint and previous behavior of pround. Also adds corresponding unsupported/../Tensor op. Performance is the same as e. g. floor (tested SSE/AVX).
2019-12-17 05:00:35 +08:00
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());
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY((Eigen::isnan)((m1*Scalar(0))/Scalar(0)).all());
VERIFY((Eigen::isinf)(m4/Scalar(0)).all());
VERIFY(((Eigen::isfinite)(m1) && (!(Eigen::isfinite)(m1*Scalar(0)/Scalar(0))) && (!(Eigen::isfinite)(m4/Scalar(0)))).all());
VERIFY_IS_APPROX(inverse(inverse(m4)),m4);
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY((abs(m1) == m1 || abs(m1) == -m1).all());
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX(m3, sqrt(abs2(m3)));
Add absolute_difference coefficient-wise binary Array function
2020-03-20 01:45:20 +08:00
VERIFY_IS_APPROX(m1.absolute_difference(m2), (m1 > m2).select(m1 - m2, m2 - m1));
ArrayBase::sign: add unit test and fix doc
2015-11-27 23:27:53 +08:00
VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
VERIFY_IS_APPROX( m1*m1.sign(),m1.abs());
VERIFY_IS_APPROX(m1.sign() * m1.abs(), m1);
* kill the retval typedefs, instead introduce ei_xxx_retval which does the job automatically in 99% cases and can be specialized * add real/imag/abs2 global functions for Array * document ei_global_math_functions_filtering_base * improve unit tests
2010-04-29 10:42:34 +08:00
Fix bug #314: move remaining math functions from internal to numext namespace
2013-06-11 05:40:56 +08:00
VERIFY_IS_APPROX(numext::abs2(numext::real(m1)) + numext::abs2(numext::imag(m1)), numext::abs2(m1));
PR 719: fix real/imag namespace conflict
2019-10-08 15:15:17 +08:00
VERIFY_IS_APPROX(numext::abs2(Eigen::real(m1)) + numext::abs2(Eigen::imag(m1)), numext::abs2(m1));
* kill the retval typedefs, instead introduce ei_xxx_retval which does the job automatically in 99% cases and can be specialized * add real/imag/abs2 global functions for Array * document ei_global_math_functions_filtering_base * improve unit tests
2010-04-29 10:42:34 +08:00
if(!NumTraits<Scalar>::IsComplex)
Fix bug #314: move remaining math functions from internal to numext namespace
2013-06-11 05:40:56 +08:00
VERIFY_IS_APPROX(numext::real(m1), m1);
implicit conversion to scalar for inner product
2010-06-02 15:45:57 +08:00
Fix bug #748 - array_5 test fails for seed 1392781168.
2014-02-24 22:10:17 +08:00
// shift argument of logarithm so that it is not zero
Scalar smallNumber = NumTraits<Scalar>::dummy_precision();
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX((m3 + smallNumber).log() , log(abs(m3) + smallNumber));
VERIFY_IS_APPROX((m3 + smallNumber + Scalar(1)).log() , log1p(abs(m3) + smallNumber));
implicit conversion to scalar for inner product
2010-06-02 15:45:57 +08:00
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
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());
add missing support for std::pow(array,scalar)
2010-06-20 05:17:07 +08:00
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
VERIFY_IS_APPROX(m1.expm1(), expm1(m1));
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX((m3 + smallNumber).exp() - Scalar(1), expm1(abs(m3) + smallNumber));
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
add missing support for std::pow(array,scalar)
2010-06-20 05:17:07 +08:00
VERIFY_IS_APPROX(m3.pow(RealScalar(0.5)), m3.sqrt());
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
VERIFY_IS_APPROX(pow(m3,RealScalar(0.5)), m3.sqrt());
Added rsqrt() method to the Array class: this method computes the coefficient-wise inverse square root much more efficiently than calling sqrt().inverse().
2015-12-04 10:16:35 +08:00
VERIFY_IS_APPROX(m3.pow(RealScalar(-0.5)), m3.rsqrt());
VERIFY_IS_APPROX(pow(m3,RealScalar(-0.5)), m3.rsqrt());
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
// Avoid inf and NaN.
m3 = (m1.square()<NumTraits<Scalar>::epsilon()).select(Scalar(1),m3);
VERIFY_IS_APPROX(m3.pow(RealScalar(-2)), m3.square().inverse());
Vectorize `pow(x, y)`. This closes https://gitlab.com/libeigen/eigen/-/issues/2085, which also contains a description of the algorithm. I ran some testing (comparing to `std::pow(double(x), double(y)))` for `x` in the set of all (positive) floats in the interval `[std::sqrt(std::numeric_limits<float>::min()), std::sqrt(std::numeric_limits<float>::max())]`, and `y` in `{2, sqrt(2), -sqrt(2)}` I get the following error statistics: ``` max_rel_error = 8.34405e-07 rms_rel_error = 2.76654e-07 ``` If I widen the range to all normal float I see lower accuracy for arguments where the result is subnormal, e.g. for `y = sqrt(2)`: ``` max_rel_error = 0.666667 rms = 6.8727e-05 count = 1335165689 argmax = 2.56049e-32, 2.10195e-45 != 1.4013e-45 ``` which seems reasonable, since these results are subnormals with only couple of significant bits left.
2021-01-18 21:25:16 +08:00
pow_test<Scalar>();
Added rsqrt() method to the Array class: this method computes the coefficient-wise inverse square root much more efficiently than calling sqrt().inverse().
2015-12-04 10:16:35 +08:00
Eliminate implicit conversion warning in test/array_cwise.cpp
2021-01-24 03:54:00 +08:00
VERIFY_IS_APPROX(log10(m3), log(m3)/numext::log(Scalar(10)));
VERIFY_IS_APPROX(log2(m3), log(m3)/numext::log(Scalar(2)));
Added support for component-wise pow (equivalent to Matlab's operator .^).
2012-03-07 15:58:42 +08:00
// scalar by array division
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
const RealScalar tiny = sqrt(std::numeric_limits<RealScalar>::epsilon());
Fixed division by zero corner case in array unit test.
2012-03-09 21:04:13 +08:00
s1 += Scalar(tiny);
m1 += ArrayType::Constant(rows,cols,Scalar(tiny));
Added support for component-wise pow (equivalent to Matlab's operator .^).
2012-03-07 15:58:42 +08:00
VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse());
Add digamma for CPU + CUDA. Includes tests.
2015-12-25 13:15:38 +08:00
fix compilation of ArrayBase::transposeInPlace
2013-06-24 19:33:44 +08:00
// check inplace transpose
m3 = m1;
m3.transposeInPlace();
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(m3, m1.transpose());
fix compilation of ArrayBase::transposeInPlace
2013-06-24 19:33:44 +08:00
m3.transposeInPlace();
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(m3, m1);
add support for global math function for array
2010-01-28 06:23:59 +08:00
}
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
template<typename ArrayType> void array_complex(const ArrayType& m)
{
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
typedef typename ArrayType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
Index rows = m.rows();
Index cols = m.cols();
ArrayType m1 = ArrayType::Random(rows, cols),
Fix isinf unit tests
2015-06-22 22:48:27 +08:00
m2(rows, cols),
m4 = m1;
Added support for expm1 in Eigen.
2016-12-03 06:13:01 +08:00
Fix isinf unit tests
2015-06-22 22:48:27 +08:00
m4.real() = (m4.real().abs()==RealScalar(0)).select(RealScalar(1),m4.real());
m4.imag() = (m4.imag().abs()==RealScalar(0)).select(RealScalar(1),m4.imag());
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
Array<RealScalar, -1, -1> m3(rows, cols);
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
for (Index i = 0; i < m.rows(); ++i)
for (Index j = 0; j < m.cols(); ++j)
Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
2012-11-06 22:25:50 +08:00
m2(i,j) = sqrt(m1(i,j));
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
// these tests are mostly to check possible compilation issues with free-functions.
Add hyperbolic trigonometric functions from std array support
2015-03-11 11:13:30 +08:00
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));
sigmoid -> logistic
2018-08-14 02:14:50 +08:00
VERIFY_IS_APPROX(m1.logistic(), logistic(m1));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(m1.arg(), arg(m1));
Protect all calls to isnan, isinf and isfinite with parentheses.
2015-08-14 23:32:34 +08:00
VERIFY((m1.isNaN() == (Eigen::isnan)(m1)).all());
VERIFY((m1.isInf() == (Eigen::isinf)(m1)).all());
VERIFY((m1.isFinite() == (Eigen::isfinite)(m1)).all());
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX(m4.inverse(), inverse(m4));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(m1.log(), log(m1));
VERIFY_IS_APPROX(m1.log10(), log10(m1));
Add log2() to Eigen.
2020-12-05 05:45:09 +08:00
VERIFY_IS_APPROX(m1.log2(), log2(m1));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
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()));
ArrayBase::sign: add unit test and fix doc
2015-11-27 23:27:53 +08:00
VERIFY_IS_APPROX(m1.sign(), sign(m1));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
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());
Fix implementation of complex expm1. Add tests that fail with previous implementation, but pass with the current one.
2019-12-12 09:56:54 +08:00
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.);
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
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))));
sigmoid -> logistic
2018-08-14 02:14:50 +08:00
VERIFY_IS_APPROX(logistic(m1), (1.0/(1.0 + exp(-m1))));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
for (Index i = 0; i < m.rows(); ++i)
for (Index j = 0; j < m.cols(); ++j)
PR 719: fix real/imag namespace conflict
2019-10-08 15:15:17 +08:00
m3(i,j) = std::atan2(m1(i,j).imag(), m1(i,j).real());
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(arg(m1), m3);
std::complex<RealScalar> zero(0.0,0.0);
Protect all calls to isnan, isinf and isfinite with parentheses.
2015-08-14 23:32:34 +08:00
VERIFY((Eigen::isnan)(m1*zero/zero).all());
Workaround msvc broken complex/complex division in unit test
2015-11-20 21:52:08 +08:00
#if EIGEN_COMP_MSVC
// msvc complex division is not robust
VERIFY((Eigen::isinf)(m4/RealScalar(0)).all());
#else
workaround clang's broken complex division
2015-06-17 21:33:09 +08:00
#if EIGEN_COMP_CLANG
Workaround msvc broken complex/complex division in unit test
2015-11-20 21:52:08 +08:00
// clang's complex division is notoriously broken too
Protect all calls to isnan, isinf and isfinite with parentheses.
2015-08-14 23:32:34 +08:00
if((numext::isinf)(m4(0,0)/RealScalar(0))) {
workaround clang's broken complex division
2015-06-17 21:33:09 +08:00
#endif
Workaround msvc broken complex/complex division in unit test
2015-11-20 21:52:08 +08:00
VERIFY((Eigen::isinf)(m4/zero).all());
workaround clang's broken complex division
2015-06-17 21:33:09 +08:00
#if EIGEN_COMP_CLANG
}
else
{
Protect all calls to isnan, isinf and isfinite with parentheses.
2015-08-14 23:32:34 +08:00
VERIFY((Eigen::isinf)(m4.real()/zero.real()).all());
workaround clang's broken complex division
2015-06-17 21:33:09 +08:00
}
#endif
Workaround msvc broken complex/complex division in unit test
2015-11-20 21:52:08 +08:00
#endif // MSVC
Protect all calls to isnan, isinf and isfinite with parentheses.
2015-08-14 23:32:34 +08:00
VERIFY(((Eigen::isfinite)(m1) && (!(Eigen::isfinite)(m1*zero/zero)) && (!(Eigen::isfinite)(m1/zero))).all());
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
VERIFY_IS_APPROX(inverse(inverse(m4)),m4);
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(conj(m1.conjugate()), m1);
PR 719: fix real/imag namespace conflict
2019-10-08 15:15:17 +08:00
VERIFY_IS_APPROX(abs(m1), sqrt(square(m1.real())+square(m1.imag())));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
VERIFY_IS_APPROX(abs(m1), sqrt(abs2(m1)));
VERIFY_IS_APPROX(log10(m1), log(m1)/log(10));
Add log2() to Eigen.
2020-12-05 05:45:09 +08:00
VERIFY_IS_APPROX(log2(m1), log(m1)/log(2));
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
ArrayBase::sign: add unit test and fix doc
2015-11-27 23:27:53 +08:00
VERIFY_IS_APPROX( m1.sign(), -(-m1).sign() );
VERIFY_IS_APPROX( m1.sign() * m1.abs(), m1);
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
// scalar by array division
Add digamma for CPU + CUDA. Includes tests.
2015-12-25 13:15:38 +08:00
Scalar s1 = internal::random<Scalar>();
Avoid float to double conversion
2016-05-17 22:20:11 +08:00
const RealScalar tiny = std::sqrt(std::numeric_limits<RealScalar>::epsilon());
More extensive unit tests for recent array-wise functors
2015-03-18 01:11:03 +08:00
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)
2020-04-28 09:55:15 +08:00
// Check vectorized inplace transpose.
Make size odd for transposeInPlace test to make sure we hit the scalar path.
2020-05-08 01:29:56 +08:00
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)
2020-04-28 09:55:15 +08:00
ArrayType m6 = m5;
m6.transposeInPlace();
VERIFY_IS_APPROX(m6, m5.transpose());
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
}
added functions to allow for cwise min/max operations with scalar argument (bug #400). added function for array.min(), array.max(), matrix.cwiseMin(), matrix.cwiseMax(). The matrix.cwiseMin/Max functions required the definition of the ConstantReturnType typedef. However, it wasn't defined until after MatrixCwiseBinaryOps was included in Eigen/src/SparseCore/SparseMatrixBase.h, so I moved those includes after the definition of the typedefs. tests for both the regular and scalar min/max functions were added as well
2012-01-12 00:00:30 +08:00
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));
Make it possible to specify NaN propagation strategy for maxCoeff/minCoeff reductions.
2021-02-25 09:49:20 +08:00
// min/max with various NaN propagation options.
if (m1.size() > 1 && !NumTraits<Scalar>::IsInteger) {
Augment NumTraits with min/max_exponent() again. Replace usage of `std::numeric_limits<...>::min/max_exponent` in codebase where possible. Also replaced some other `numeric_limits` usages in affected tests with the `NumTraits` equivalent. The previous MR !443 failed for c++03 due to lack of `constexpr`. Because of this, we need to keep around the `std::numeric_limits` version in enum expressions until the switch to c++11. Fixes #2148
2021-03-17 11:12:46 +08:00
m1(0,0) = NumTraits<Scalar>::quiet_NaN();
Make it possible to specify NaN propagation strategy for maxCoeff/minCoeff reductions.
2021-02-25 09:49:20 +08:00
maxM1 = m1.template maxCoeff<PropagateNaN>();
minM1 = m1.template minCoeff<PropagateNaN>();
VERIFY((numext::isnan)(maxM1));
VERIFY((numext::isnan)(minM1));
maxM1 = m1.template maxCoeff<PropagateNumbers>();
minM1 = m1.template minCoeff<PropagateNumbers>();
VERIFY(!(numext::isnan)(maxM1));
VERIFY(!(numext::isnan)(minM1));
}
added functions to allow for cwise min/max operations with scalar argument (bug #400). added function for array.min(), array.max(), matrix.cwiseMin(), matrix.cwiseMax(). The matrix.cwiseMin/Max functions required the definition of the ConstantReturnType typedef. However, it wasn't defined until after MatrixCwiseBinaryOps was included in Eigen/src/SparseCore/SparseMatrixBase.h, so I moved those includes after the definition of the typedefs. tests for both the regular and scalar min/max functions were added as well
2012-01-12 00:00:30 +08:00
}
Renamed shift_left/shift_right to shiftLeft/shiftRight. For naming consistency. Also moved to ArrayCwiseUnaryOps, and added test.
2021-08-18 11:04:48 +08:00
template<int N>
struct shift_left {
template<typename Scalar>
Scalar operator()(const Scalar& v) const {
return v << N;
}
};
template<int N>
struct arithmetic_shift_right {
template<typename Scalar>
Scalar operator()(const Scalar& v) const {
return v >> N;
}
};
template<typename ArrayType> void array_integer(const ArrayType& m)
{
Index rows = m.rows();
Index cols = m.cols();
ArrayType m1 = ArrayType::Random(rows, cols),
m2(rows, cols);
m2 = m1.template shiftLeft<2>();
VERIFY( (m2 == m1.unaryExpr(shift_left<2>())).all() );
m2 = m1.template shiftLeft<9>();
VERIFY( (m2 == m1.unaryExpr(shift_left<9>())).all() );
m2 = m1.template shiftRight<2>();
VERIFY( (m2 == m1.unaryExpr(arithmetic_shift_right<2>())).all() );
m2 = m1.template shiftRight<9>();
VERIFY( (m2 == m1.unaryExpr(arithmetic_shift_right<9>())).all() );
}
Rename test/array.cpp to test/array_cwise.cpp to avoid conflicts with the array header.
2018-09-21 00:07:32 +08:00
EIGEN_DECLARE_TEST(array_cwise)
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
{
for(int i = 0; i < g_repeat; i++) {
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
CALL_SUBTEST_1( array(Array<float, 1, 1>()) );
Re-enabled the missing tests, again...
2010-12-17 02:07:23 +08:00
CALL_SUBTEST_2( array(Array22f()) );
CALL_SUBTEST_3( array(Array44d()) );
add the possibility to configure the maximal matrix size in the unit tests
2011-07-12 20:41:00 +08:00
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))) );
Add more extensive tests of Array ctors, including {} variants
2019-01-22 22:30:50 +08:00
CALL_SUBTEST_6( array(Array<Index,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
Renamed shift_left/shift_right to shiftLeft/shiftRight. For naming consistency. Also moved to ArrayCwiseUnaryOps, and added test.
2021-08-18 11:04:48 +08:00
CALL_SUBTEST_6( array_integer(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
CALL_SUBTEST_6( array_integer(Array<Index,Dynamic,Dynamic>(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
}
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( comparisons(Array<float, 1, 1>()) );
Re-enabled the missing tests, again...
2010-12-17 02:07:23 +08:00
CALL_SUBTEST_2( comparisons(Array22f()) );
CALL_SUBTEST_3( comparisons(Array44d()) );
add the possibility to configure the maximal matrix size in the unit tests
2011-07-12 20:41:00 +08:00
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))) );
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
}
added functions to allow for cwise min/max operations with scalar argument (bug #400). added function for array.min(), array.max(), matrix.cwiseMin(), matrix.cwiseMax(). The matrix.cwiseMin/Max functions required the definition of the ConstantReturnType typedef. However, it wasn't defined until after MatrixCwiseBinaryOps was included in Eigen/src/SparseCore/SparseMatrixBase.h, so I moved those includes after the definition of the typedefs. tests for both the regular and scalar min/max functions were added as well
2012-01-12 00:00:30 +08:00
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))) );
}
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
for(int i = 0; i < g_repeat; i++) {
CALL_SUBTEST_1( array_real(Array<float, 1, 1>()) );
Re-enabled the missing tests, again...
2010-12-17 02:07:23 +08:00
CALL_SUBTEST_2( array_real(Array22f()) );
CALL_SUBTEST_3( array_real(Array44d()) );
add the possibility to configure the maximal matrix size in the unit tests
2011-07-12 20:41:00 +08:00
CALL_SUBTEST_5( array_real(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
Fix pow and other cwise ops for half/bfloat16. The new `generic_pow` implementation was failing for half/bfloat16 since their construction from int/float is not `constexpr`. Modified in `GenericPacketMathFunctions` to remove `constexpr`. While adding tests for half/bfloat16, found other issues related to implicit conversions. Also needed to implement `numext::arg` for non-integer, non-complex, non-float/double/long double types. These seem to be implicitly converted to `std::complex<T>`, which then fails for half/bfloat16.
2021-01-23 03:10:54 +08:00
CALL_SUBTEST_7( array_real(Array<Eigen::half, 32, 32>()) );
CALL_SUBTEST_8( array_real(Array<Eigen::bfloat16, 32, 32>()) );
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
}
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
for(int i = 0; i < g_repeat; i++) {
add the possibility to configure the maximal matrix size in the unit tests
2011-07-12 20:41:00 +08:00
CALL_SUBTEST_4( array_complex(ArrayXXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
Add test for sqrt() on complex Arrays. From Gael's dashboard output of matrix_square_root test, I suspect the test committed here may fail on old gcc.
2011-05-09 17:17:41 +08:00
}
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
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));
Implement scalar multiples and division by a scalar as a binary-expression with a constant expression. This slightly complexifies the type of the expressions and implies that we now have to distinguish between scalar*expr and expr*scalar to catch scalar-multiple expression (e.g., see BlasUtil.h), but this brings several advantages: - it makes it clear on each side the scalar is applied, - it clearly reflects that we are dealing with a binary-expression, - the complexity of the type is hidden through macros defined at the end of Macros.h, - distinguishing between "scalar op expr" and "expr op scalar" is important to support non commutative fields (like quaternions) - "scalar op expr" is now fully equivalent to "ConstantExpr(scalar) op expr" - scalar_multiple_op, scalar_quotient1_op and scalar_quotient2_op are not used anymore in officially supported modules (still used in Tensor)
2016-06-14 17:26:57 +08:00
typedef CwiseUnaryOp<internal::scalar_abs_op<double>, ArrayXd > Xpr;
Uups - re-enabled subtests 1 to 5.
2010-12-17 00:36:10 +08:00
VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Xpr>::type,
ArrayBase<Xpr>
>::value));
forgot to add the unit test array.cpp
2008-06-22 01:28:07 +08:00
}
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