1 files changed, 117 insertions, 0 deletions
diff --git a/test/permutationmatrices.cpp b/test/permutationmatrices.cpp
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+++ b/test/permutationmatrices.cpp
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+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+
+using namespace std;
+template<typename MatrixType> void permutationmatrices(const MatrixType& m)
+{
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime,
+         Options = MatrixType::Options };
+  typedef PermutationMatrix<Rows> LeftPermutationType;
+  typedef Matrix<int, Rows, 1> LeftPermutationVectorType;
+  typedef Map<LeftPermutationType> MapLeftPerm;
+  typedef PermutationMatrix<Cols> RightPermutationType;
+  typedef Matrix<int, Cols, 1> RightPermutationVectorType;
+  typedef Map<RightPermutationType> MapRightPerm;
+
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  MatrixType m_original = MatrixType::Random(rows,cols);
+  LeftPermutationVectorType lv;
+  randomPermutationVector(lv, rows);
+  LeftPermutationType lp(lv);
+  RightPermutationVectorType rv;
+  randomPermutationVector(rv, cols);
+  RightPermutationType rp(rv);
+  MatrixType m_permuted = lp * m_original * rp;
+
+  for (int i=0; i<rows; i++)
+    for (int j=0; j<cols; j++)
+        VERIFY_IS_APPROX(m_permuted(lv(i),j), m_original(i,rv(j)));
+
+  Matrix<Scalar,Rows,Rows> lm(lp);
+  Matrix<Scalar,Cols,Cols> rm(rp);
+
+  VERIFY_IS_APPROX(m_permuted, lm*m_original*rm);
+
+  VERIFY_IS_APPROX(lp.inverse()*m_permuted*rp.inverse(), m_original);
+  VERIFY_IS_APPROX(lv.asPermutation().inverse()*m_permuted*rv.asPermutation().inverse(), m_original);
+  VERIFY_IS_APPROX(MapLeftPerm(lv.data(),lv.size()).inverse()*m_permuted*MapRightPerm(rv.data(),rv.size()).inverse(), m_original);
+  
+  VERIFY((lp*lp.inverse()).toDenseMatrix().isIdentity());
+  VERIFY((lv.asPermutation()*lv.asPermutation().inverse()).toDenseMatrix().isIdentity());
+  VERIFY((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv.data(),lv.size()).inverse()).toDenseMatrix().isIdentity());
+
+  LeftPermutationVectorType lv2;
+  randomPermutationVector(lv2, rows);
+  LeftPermutationType lp2(lv2);
+  Matrix<Scalar,Rows,Rows> lm2(lp2);
+  VERIFY_IS_APPROX((lp*lp2).toDenseMatrix().template cast<Scalar>(), lm*lm2);
+  VERIFY_IS_APPROX((lv.asPermutation()*lv2.asPermutation()).toDenseMatrix().template cast<Scalar>(), lm*lm2);
+  VERIFY_IS_APPROX((MapLeftPerm(lv.data(),lv.size())*MapLeftPerm(lv2.data(),lv2.size())).toDenseMatrix().template cast<Scalar>(), lm*lm2);
+
+  LeftPermutationType identityp;
+  identityp.setIdentity(rows);
+  VERIFY_IS_APPROX(m_original, identityp*m_original);
+
+  // check inplace permutations
+  m_permuted = m_original;
+  m_permuted = lp.inverse() * m_permuted;
+  VERIFY_IS_APPROX(m_permuted, lp.inverse()*m_original);
+
+  m_permuted = m_original;
+  m_permuted = m_permuted * rp.inverse();
+  VERIFY_IS_APPROX(m_permuted, m_original*rp.inverse());
+
+  m_permuted = m_original;
+  m_permuted = lp * m_permuted;
+  VERIFY_IS_APPROX(m_permuted, lp*m_original);
+
+  m_permuted = m_original;
+  m_permuted = m_permuted * rp;
+  VERIFY_IS_APPROX(m_permuted, m_original*rp);
+
+  if(rows>1 && cols>1)
+  {
+    lp2 = lp;
+    Index i = internal::random<Index>(0, rows-1);
+    Index j;
+    do j = internal::random<Index>(0, rows-1); while(j==i);
+    lp2.applyTranspositionOnTheLeft(i, j);
+    lm = lp;
+    lm.row(i).swap(lm.row(j));
+    VERIFY_IS_APPROX(lm, lp2.toDenseMatrix().template cast<Scalar>());
+
+    RightPermutationType rp2 = rp;
+    i = internal::random<Index>(0, cols-1);
+    do j = internal::random<Index>(0, cols-1); while(j==i);
+    rp2.applyTranspositionOnTheRight(i, j);
+    rm = rp;
+    rm.col(i).swap(rm.col(j));
+    VERIFY_IS_APPROX(rm, rp2.toDenseMatrix().template cast<Scalar>());
+  }  
+}
+
+void test_permutationmatrices()
+{
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( permutationmatrices(Matrix<float, 1, 1>()) );
+    CALL_SUBTEST_2( permutationmatrices(Matrix3f()) );
+    CALL_SUBTEST_3( permutationmatrices(Matrix<double,3,3,RowMajor>()) );
+    CALL_SUBTEST_4( permutationmatrices(Matrix4d()) );
+    CALL_SUBTEST_5( permutationmatrices(Matrix<double,40,60>()) );
+    CALL_SUBTEST_6( permutationmatrices(Matrix<double,Dynamic,Dynamic,RowMajor>(20, 30)) );
+    CALL_SUBTEST_7( permutationmatrices(MatrixXcf(15, 10)) );
+  }
+}