add unit tests for true array objects
diff --git a/test/CMakeLists.txt b/test/CMakeLists.txt
index 31f8a9b..88c6f20 100644
--- a/test/CMakeLists.txt
+++ b/test/CMakeLists.txt
@@ -110,6 +110,7 @@
ei_add_test(smallvectors)
ei_add_test(map)
ei_add_test(array)
+ei_add_test(array_for_matrix)
ei_add_test(array_replicate)
ei_add_test(array_reverse)
ei_add_test(triangular)
diff --git a/test/array.cpp b/test/array.cpp
index 0d54cf9..05b3789 100644
--- a/test/array.cpp
+++ b/test/array.cpp
@@ -27,14 +27,10 @@
template<typename MatrixType> void array(const MatrixType& m)
{
- /* this test covers the following files:
- Array.cpp
- */
-
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
- typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType;
- typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
+ typedef Array<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType;
+ typedef Array<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
int rows = m.rows();
int cols = m.cols();
@@ -50,15 +46,18 @@
s2 = ei_random<Scalar>();
// scalar addition
- VERIFY_IS_APPROX(m1.array() + s1, s1 + m1.array());
- VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1);
- VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,s2) );
+ VERIFY_IS_APPROX(m1 + s1, s1 + m1);
+ VERIFY_IS_APPROX(m1 + s1, MatrixType::Constant(rows,cols,s1) + m1);
+ VERIFY_IS_APPROX(s1 - m1, (-m1)+s1 );
+ VERIFY_IS_APPROX(m1 - s1, m1 - MatrixType::Constant(rows,cols,s1));
+ VERIFY_IS_APPROX(s1 - m1, MatrixType::Constant(rows,cols,s1) - m1);
+ VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
m3 = m1;
- m3.array() += s2;
- VERIFY_IS_APPROX(m3, (m1.array() + s2).matrix());
+ m3 += s2;
+ VERIFY_IS_APPROX(m3, m1 + s2);
m3 = m1;
- m3.array() -= s1;
- VERIFY_IS_APPROX(m3, (m1.array() - s1).matrix());
+ m3 -= s1;
+ VERIFY_IS_APPROX(m3, m1 - s1);
// reductions
VERIFY_IS_APPROX(m1.colwise().sum().sum(), m1.sum());
@@ -82,7 +81,7 @@
{
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
- typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+ typedef Array<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
int rows = m.rows();
int cols = m.cols();
@@ -94,79 +93,61 @@
m2 = MatrixType::Random(rows, cols),
m3(rows, cols);
- VERIFY(((m1.array() + Scalar(1)) > m1.array()).all());
- VERIFY(((m1.array() - Scalar(1)) < m1.array()).all());
+ VERIFY(((m1 + Scalar(1)) > m1).all());
+ VERIFY(((m1 - Scalar(1)) < m1).all());
if (rows*cols>1)
{
m3 = m1;
m3(r,c) += 1;
- VERIFY(! (m1.array() < m3.array()).all() );
- VERIFY(! (m1.array() > m3.array()).all() );
+ VERIFY(! (m1 < m3).all() );
+ VERIFY(! (m1 > m3).all() );
}
// comparisons to scalar
- VERIFY( (m1.array() != (m1(r,c)+1) ).any() );
- VERIFY( (m1.array() > (m1(r,c)-1) ).any() );
- VERIFY( (m1.array() < (m1(r,c)+1) ).any() );
- VERIFY( (m1.array() == m1(r,c) ).any() );
+ 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() );
// test Select
- VERIFY_IS_APPROX( (m1.array()<m2.array()).select(m1,m2), m1.cwiseMin(m2) );
- VERIFY_IS_APPROX( (m1.array()>m2.array()).select(m1,m2), m1.cwiseMax(m2) );
+ 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) = ei_abs(m1(i,j))<mid ? 0 : m1(i,j);
- VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
+ VERIFY_IS_APPROX( (m1.abs()<MatrixType::Constant(rows,cols,mid))
.select(MatrixType::Zero(rows,cols),m1), m3);
// shorter versions:
- VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
+ VERIFY_IS_APPROX( (m1.abs()<MatrixType::Constant(rows,cols,mid))
.select(0,m1), m3);
- VERIFY_IS_APPROX( (m1.array().abs()>=MatrixType::Constant(rows,cols,mid).array())
+ VERIFY_IS_APPROX( (m1.abs()>=MatrixType::Constant(rows,cols,mid))
.select(m1,0), m3);
// even shorter version:
- VERIFY_IS_APPROX( (m1.array().abs()<mid).select(0,m1), m3);
+ VERIFY_IS_APPROX( (m1.abs()<mid).select(0,m1), m3);
// count
- VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols);
+ VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols);
// TODO allows colwise/rowwise for array
- VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), RowVectorXi::Constant(cols,rows));
- VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorXi::Constant(rows, cols));
-}
-
-template<typename VectorType> void lpNorm(const VectorType& v)
-{
- VectorType u = VectorType::Random(v.size());
-
- VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff());
- VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwiseAbs().sum());
- VERIFY_IS_APPROX(u.template lpNorm<2>(), ei_sqrt(u.array().abs().square().sum()));
- VERIFY_IS_APPROX(ei_pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum());
+ VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayXi::Constant(cols,rows).transpose());
+ VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayXi::Constant(rows, cols));
}
void test_array()
{
for(int i = 0; i < g_repeat; i++) {
- CALL_SUBTEST_1( array(Matrix<float, 1, 1>()) );
- CALL_SUBTEST_2( array(Matrix2f()) );
- CALL_SUBTEST_3( array(Matrix4d()) );
- CALL_SUBTEST_4( array(MatrixXcf(3, 3)) );
- CALL_SUBTEST_5( array(MatrixXf(8, 12)) );
- CALL_SUBTEST_6( array(MatrixXi(8, 12)) );
+ CALL_SUBTEST_1( array(Array<float, 1, 1>()) );
+ CALL_SUBTEST_2( array(Array22f()) );
+ CALL_SUBTEST_3( array(Array44d()) );
+ CALL_SUBTEST_4( array(ArrayXXcf(3, 3)) );
+ CALL_SUBTEST_5( array(ArrayXXf(8, 12)) );
+ CALL_SUBTEST_6( array(ArrayXXi(8, 12)) );
}
for(int i = 0; i < g_repeat; i++) {
- CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) );
- CALL_SUBTEST_2( comparisons(Matrix2f()) );
- CALL_SUBTEST_3( comparisons(Matrix4d()) );
- CALL_SUBTEST_5( comparisons(MatrixXf(8, 12)) );
- CALL_SUBTEST_6( comparisons(MatrixXi(8, 12)) );
- }
- for(int i = 0; i < g_repeat; i++) {
- CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) );
- CALL_SUBTEST_2( lpNorm(Vector2f()) );
- CALL_SUBTEST_7( lpNorm(Vector3d()) );
- CALL_SUBTEST_8( lpNorm(Vector4f()) );
- CALL_SUBTEST_5( lpNorm(VectorXf(16)) );
- CALL_SUBTEST_4( lpNorm(VectorXcf(10)) );
+ CALL_SUBTEST_1( comparisons(Array<float, 1, 1>()) );
+ CALL_SUBTEST_2( comparisons(Array22f()) );
+ CALL_SUBTEST_3( comparisons(Array44d()) );
+ CALL_SUBTEST_5( comparisons(ArrayXXf(8, 12)) );
+ CALL_SUBTEST_6( comparisons(ArrayXXi(8, 12)) );
}
}
diff --git a/test/array_for_matrix.cpp b/test/array_for_matrix.cpp
new file mode 100644
index 0000000..deb7388
--- /dev/null
+++ b/test/array_for_matrix.cpp
@@ -0,0 +1,168 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
+//
+// Eigen is free software; you can redistribute it and/or
+// modify it under the terms of the GNU Lesser General Public
+// License as published by the Free Software Foundation; either
+// version 3 of the License, or (at your option) any later version.
+//
+// Alternatively, you can redistribute it and/or
+// modify it under the terms of the GNU General Public License as
+// published by the Free Software Foundation; either version 2 of
+// the License, or (at your option) any later version.
+//
+// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
+// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
+// GNU General Public License for more details.
+//
+// You should have received a copy of the GNU Lesser General Public
+// License and a copy of the GNU General Public License along with
+// Eigen. If not, see <http://www.gnu.org/licenses/>.
+
+#include "main.h"
+#include <Eigen/Array>
+
+template<typename MatrixType> void array_for_matrix(const MatrixType& m)
+{
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType;
+ typedef Matrix<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType;
+
+ int rows = m.rows();
+ int cols = m.cols();
+
+ MatrixType m1 = MatrixType::Random(rows, cols),
+ m2 = MatrixType::Random(rows, cols),
+ m3(rows, cols);
+
+ ColVectorType cv1 = ColVectorType::Random(rows);
+ RowVectorType rv1 = RowVectorType::Random(cols);
+
+ Scalar s1 = ei_random<Scalar>(),
+ s2 = ei_random<Scalar>();
+
+ // scalar addition
+ VERIFY_IS_APPROX(m1.array() + s1, s1 + m1.array());
+ VERIFY_IS_APPROX((m1.array() + s1).matrix(), MatrixType::Constant(rows,cols,s1) + m1);
+ VERIFY_IS_APPROX(((m1*Scalar(2)).array() - s2).matrix(), (m1+m1) - MatrixType::Constant(rows,cols,s2) );
+ m3 = m1;
+ m3.array() += s2;
+ VERIFY_IS_APPROX(m3, (m1.array() + s2).matrix());
+ m3 = m1;
+ m3.array() -= s1;
+ VERIFY_IS_APPROX(m3, (m1.array() - s1).matrix());
+
+ // reductions
+ VERIFY_IS_APPROX(m1.colwise().sum().sum(), m1.sum());
+ VERIFY_IS_APPROX(m1.rowwise().sum().sum(), m1.sum());
+ if (!ei_isApprox(m1.sum(), (m1+m2).sum()))
+ VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
+ VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(ei_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);
+}
+
+template<typename MatrixType> void comparisons(const MatrixType& m)
+{
+ typedef typename MatrixType::Scalar Scalar;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+ typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
+
+ int rows = m.rows();
+ int cols = m.cols();
+
+ int r = ei_random<int>(0, rows-1),
+ c = ei_random<int>(0, cols-1);
+
+ MatrixType m1 = MatrixType::Random(rows, cols),
+ m2 = MatrixType::Random(rows, cols),
+ m3(rows, cols);
+
+ VERIFY(((m1.array() + Scalar(1)) > m1.array()).all());
+ VERIFY(((m1.array() - Scalar(1)) < m1.array()).all());
+ if (rows*cols>1)
+ {
+ m3 = m1;
+ m3(r,c) += 1;
+ VERIFY(! (m1.array() < m3.array()).all() );
+ VERIFY(! (m1.array() > m3.array()).all() );
+ }
+
+ // comparisons to scalar
+ VERIFY( (m1.array() != (m1(r,c)+1) ).any() );
+ VERIFY( (m1.array() > (m1(r,c)-1) ).any() );
+ VERIFY( (m1.array() < (m1(r,c)+1) ).any() );
+ VERIFY( (m1.array() == m1(r,c) ).any() );
+
+ // test Select
+ VERIFY_IS_APPROX( (m1.array()<m2.array()).select(m1,m2), m1.cwiseMin(m2) );
+ VERIFY_IS_APPROX( (m1.array()>m2.array()).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) = ei_abs(m1(i,j))<mid ? 0 : m1(i,j);
+ VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
+ .select(MatrixType::Zero(rows,cols),m1), m3);
+ // shorter versions:
+ VERIFY_IS_APPROX( (m1.array().abs()<MatrixType::Constant(rows,cols,mid).array())
+ .select(0,m1), m3);
+ VERIFY_IS_APPROX( (m1.array().abs()>=MatrixType::Constant(rows,cols,mid).array())
+ .select(m1,0), m3);
+ // even shorter version:
+ VERIFY_IS_APPROX( (m1.array().abs()<mid).select(0,m1), m3);
+
+ // count
+ VERIFY(((m1.array().abs()+1)>RealScalar(0.1)).count() == rows*cols);
+ // TODO allows colwise/rowwise for array
+ VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), RowVectorXi::Constant(cols,rows));
+ VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().rowwise().count(), VectorXi::Constant(rows, cols));
+}
+
+template<typename VectorType> void lpNorm(const VectorType& v)
+{
+ VectorType u = VectorType::Random(v.size());
+
+ VERIFY_IS_APPROX(u.template lpNorm<Infinity>(), u.cwiseAbs().maxCoeff());
+ VERIFY_IS_APPROX(u.template lpNorm<1>(), u.cwiseAbs().sum());
+ VERIFY_IS_APPROX(u.template lpNorm<2>(), ei_sqrt(u.array().abs().square().sum()));
+ VERIFY_IS_APPROX(ei_pow(u.template lpNorm<5>(), typename VectorType::RealScalar(5)), u.array().abs().pow(5).sum());
+}
+
+void test_array_for_matrix()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( array_for_matrix(Matrix<float, 1, 1>()) );
+ CALL_SUBTEST_2( array_for_matrix(Matrix2f()) );
+ CALL_SUBTEST_3( array_for_matrix(Matrix4d()) );
+ CALL_SUBTEST_4( array_for_matrix(MatrixXcf(3, 3)) );
+ CALL_SUBTEST_5( array_for_matrix(MatrixXf(8, 12)) );
+ CALL_SUBTEST_6( array_for_matrix(MatrixXi(8, 12)) );
+ }
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( comparisons(Matrix<float, 1, 1>()) );
+ CALL_SUBTEST_2( comparisons(Matrix2f()) );
+ CALL_SUBTEST_3( comparisons(Matrix4d()) );
+ CALL_SUBTEST_5( comparisons(MatrixXf(8, 12)) );
+ CALL_SUBTEST_6( comparisons(MatrixXi(8, 12)) );
+ }
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( lpNorm(Matrix<float, 1, 1>()) );
+ CALL_SUBTEST_2( lpNorm(Vector2f()) );
+ CALL_SUBTEST_7( lpNorm(Vector3d()) );
+ CALL_SUBTEST_8( lpNorm(Vector4f()) );
+ CALL_SUBTEST_5( lpNorm(VectorXf(16)) );
+ CALL_SUBTEST_4( lpNorm(VectorXcf(10)) );
+ }
+}
