From 4a04f7206914a49f5f95adc5eb786237f1a9f547 Mon Sep 17 00:00:00 2001
From: Campbell Barton <ideasman42@gmail.com>
Date: Sun, 23 Oct 2011 17:52:20 +0000
Subject: remove $Id: tags after discussion on the mailign list:
 http://markmail.org/message/fp7ozcywxum3ar7n

---
 .../src/Core/products/SelfadjointMatrixMatrix.h    | 427 +++++++++++++++++++++
 1 file changed, 427 insertions(+)
 create mode 100644 extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h

(limited to 'extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h')

diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
new file mode 100644
index 00000000000..ccd757cfaf8
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
@@ -0,0 +1,427 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.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/>.
+
+#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_H
+#define EIGEN_SELFADJOINT_MATRIX_MATRIX_H
+
+namespace internal {
+
+// pack a selfadjoint block diagonal for use with the gebp_kernel
+template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder>
+struct symm_pack_lhs
+{
+  template<int BlockRows> inline
+  void pack(Scalar* blockA, const const_blas_data_mapper<Scalar,Index,StorageOrder>& lhs, Index cols, Index i, Index& count)
+  {
+    // normal copy
+    for(Index k=0; k<i; k++)
+      for(Index w=0; w<BlockRows; w++)
+        blockA[count++] = lhs(i+w,k);           // normal
+    // symmetric copy
+    Index h = 0;
+    for(Index k=i; k<i+BlockRows; k++)
+    {
+      for(Index w=0; w<h; w++)
+        blockA[count++] = conj(lhs(k, i+w)); // transposed
+
+      blockA[count++] = real(lhs(k,k));   // real (diagonal)
+
+      for(Index w=h+1; w<BlockRows; w++)
+        blockA[count++] = lhs(i+w, k);          // normal
+      ++h;
+    }
+    // transposed copy
+    for(Index k=i+BlockRows; k<cols; k++)
+      for(Index w=0; w<BlockRows; w++)
+        blockA[count++] = conj(lhs(k, i+w)); // transposed
+  }
+  void operator()(Scalar* blockA, const Scalar* _lhs, Index lhsStride, Index cols, Index rows)
+  {
+    const_blas_data_mapper<Scalar,Index,StorageOrder> lhs(_lhs,lhsStride);
+    Index count = 0;
+    Index peeled_mc = (rows/Pack1)*Pack1;
+    for(Index i=0; i<peeled_mc; i+=Pack1)
+    {
+      pack<Pack1>(blockA, lhs, cols, i, count);
+    }
+
+    if(rows-peeled_mc>=Pack2)
+    {
+      pack<Pack2>(blockA, lhs, cols, peeled_mc, count);
+      peeled_mc += Pack2;
+    }
+
+    // do the same with mr==1
+    for(Index i=peeled_mc; i<rows; i++)
+    {
+      for(Index k=0; k<i; k++)
+        blockA[count++] = lhs(i, k);              // normal
+
+      blockA[count++] = real(lhs(i, i));       // real (diagonal)
+
+      for(Index k=i+1; k<cols; k++)
+        blockA[count++] = conj(lhs(k, i));     // transposed
+    }
+  }
+};
+
+template<typename Scalar, typename Index, int nr, int StorageOrder>
+struct symm_pack_rhs
+{
+  enum { PacketSize = packet_traits<Scalar>::size };
+  void operator()(Scalar* blockB, const Scalar* _rhs, Index rhsStride, Index rows, Index cols, Index k2)
+  {
+    Index end_k = k2 + rows;
+    Index count = 0;
+    const_blas_data_mapper<Scalar,Index,StorageOrder> rhs(_rhs,rhsStride);
+    Index packet_cols = (cols/nr)*nr;
+
+    // first part: normal case
+    for(Index j2=0; j2<k2; j2+=nr)
+    {
+      for(Index k=k2; k<end_k; k++)
+      {
+        blockB[count+0] = rhs(k,j2+0);
+        blockB[count+1] = rhs(k,j2+1);
+        if (nr==4)
+        {
+          blockB[count+2] = rhs(k,j2+2);
+          blockB[count+3] = rhs(k,j2+3);
+        }
+        count += nr;
+      }
+    }
+
+    // second part: diagonal block
+    for(Index j2=k2; j2<(std::min)(k2+rows,packet_cols); j2+=nr)
+    {
+      // again we can split vertically in three different parts (transpose, symmetric, normal)
+      // transpose
+      for(Index k=k2; k<j2; k++)
+      {
+        blockB[count+0] = conj(rhs(j2+0,k));
+        blockB[count+1] = conj(rhs(j2+1,k));
+        if (nr==4)
+        {
+          blockB[count+2] = conj(rhs(j2+2,k));
+          blockB[count+3] = conj(rhs(j2+3,k));
+        }
+        count += nr;
+      }
+      // symmetric
+      Index h = 0;
+      for(Index k=j2; k<j2+nr; k++)
+      {
+        // normal
+        for (Index w=0 ; w<h; ++w)
+          blockB[count+w] = rhs(k,j2+w);
+
+        blockB[count+h] = real(rhs(k,k));
+
+        // transpose
+        for (Index w=h+1 ; w<nr; ++w)
+          blockB[count+w] = conj(rhs(j2+w,k));
+        count += nr;
+        ++h;
+      }
+      // normal
+      for(Index k=j2+nr; k<end_k; k++)
+      {
+        blockB[count+0] = rhs(k,j2+0);
+        blockB[count+1] = rhs(k,j2+1);
+        if (nr==4)
+        {
+          blockB[count+2] = rhs(k,j2+2);
+          blockB[count+3] = rhs(k,j2+3);
+        }
+        count += nr;
+      }
+    }
+
+    // third part: transposed
+    for(Index j2=k2+rows; j2<packet_cols; j2+=nr)
+    {
+      for(Index k=k2; k<end_k; k++)
+      {
+        blockB[count+0] = conj(rhs(j2+0,k));
+        blockB[count+1] = conj(rhs(j2+1,k));
+        if (nr==4)
+        {
+          blockB[count+2] = conj(rhs(j2+2,k));
+          blockB[count+3] = conj(rhs(j2+3,k));
+        }
+        count += nr;
+      }
+    }
+
+    // copy the remaining columns one at a time (=> the same with nr==1)
+    for(Index j2=packet_cols; j2<cols; ++j2)
+    {
+      // transpose
+      Index half = (std::min)(end_k,j2);
+      for(Index k=k2; k<half; k++)
+      {
+        blockB[count] = conj(rhs(j2,k));
+        count += 1;
+      }
+
+      if(half==j2 && half<k2+rows)
+      {
+        blockB[count] = real(rhs(j2,j2));
+        count += 1;
+      }
+      else
+        half--;
+
+      // normal
+      for(Index k=half+1; k<k2+rows; k++)
+      {
+        blockB[count] = rhs(k,j2);
+        count += 1;
+      }
+    }
+  }
+};
+
+/* Optimized selfadjoint matrix * matrix (_SYMM) product built on top of
+ * the general matrix matrix product.
+ */
+template <typename Scalar, typename Index,
+          int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
+          int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs,
+          int ResStorageOrder>
+struct product_selfadjoint_matrix;
+
+template <typename Scalar, typename Index,
+          int LhsStorageOrder, bool LhsSelfAdjoint, bool ConjugateLhs,
+          int RhsStorageOrder, bool RhsSelfAdjoint, bool ConjugateRhs>
+struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,LhsSelfAdjoint,ConjugateLhs, RhsStorageOrder,RhsSelfAdjoint,ConjugateRhs,RowMajor>
+{
+
+  static EIGEN_STRONG_INLINE void run(
+    Index rows, Index cols,
+    const Scalar* lhs, Index lhsStride,
+    const Scalar* rhs, Index rhsStride,
+    Scalar* res,       Index resStride,
+    Scalar alpha)
+  {
+    product_selfadjoint_matrix<Scalar, Index,
+      EIGEN_LOGICAL_XOR(RhsSelfAdjoint,RhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
+      RhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsSelfAdjoint,ConjugateRhs),
+      EIGEN_LOGICAL_XOR(LhsSelfAdjoint,LhsStorageOrder==RowMajor) ? ColMajor : RowMajor,
+      LhsSelfAdjoint, NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsSelfAdjoint,ConjugateLhs),
+      ColMajor>
+      ::run(cols, rows,  rhs, rhsStride,  lhs, lhsStride,  res, resStride,  alpha);
+  }
+};
+
+template <typename Scalar, typename Index,
+          int LhsStorageOrder, bool ConjugateLhs,
+          int RhsStorageOrder, bool ConjugateRhs>
+struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,true,ConjugateLhs, RhsStorageOrder,false,ConjugateRhs,ColMajor>
+{
+
+  static EIGEN_DONT_INLINE void run(
+    Index rows, Index cols,
+    const Scalar* _lhs, Index lhsStride,
+    const Scalar* _rhs, Index rhsStride,
+    Scalar* res,        Index resStride,
+    Scalar alpha)
+  {
+    Index size = rows;
+
+    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
+    const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
+
+    typedef gebp_traits<Scalar,Scalar> Traits;
+
+    Index kc = size;  // cache block size along the K direction
+    Index mc = rows;  // cache block size along the M direction
+    Index nc = cols;  // cache block size along the N direction
+    computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
+    // kc must smaller than mc
+    kc = (std::min)(kc,mc);
+
+    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
+    std::size_t sizeB = sizeW + kc*cols;
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
+    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
+    Scalar* blockB = allocatedBlockB + sizeW;
+
+    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+    symm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+    gemm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
+    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder==RowMajor?ColMajor:RowMajor, true> pack_lhs_transposed;
+
+    for(Index k2=0; k2<size; k2+=kc)
+    {
+      const Index actual_kc = (std::min)(k2+kc,size)-k2;
+
+      // we have selected one row panel of rhs and one column panel of lhs
+      // pack rhs's panel into a sequential chunk of memory
+      // and expand each coeff to a constant packet for further reuse
+      pack_rhs(blockB, &rhs(k2,0), rhsStride, actual_kc, cols);
+
+      // the select lhs's panel has to be split in three different parts:
+      //  1 - the transposed panel above the diagonal block => transposed packed copy
+      //  2 - the diagonal block => special packed copy
+      //  3 - the panel below the diagonal block => generic packed copy
+      for(Index i2=0; i2<k2; i2+=mc)
+      {
+        const Index actual_mc = (std::min)(i2+mc,k2)-i2;
+        // transposed packed copy
+        pack_lhs_transposed(blockA, &lhs(k2, i2), lhsStride, actual_kc, actual_mc);
+
+        gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+      }
+      // the block diagonal
+      {
+        const Index actual_mc = (std::min)(k2+kc,size)-k2;
+        // symmetric packed copy
+        pack_lhs(blockA, &lhs(k2,k2), lhsStride, actual_kc, actual_mc);
+
+        gebp_kernel(res+k2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+      }
+
+      for(Index i2=k2+kc; i2<size; i2+=mc)
+      {
+        const Index actual_mc = (std::min)(i2+mc,size)-i2;
+        gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder,false>()
+          (blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
+
+        gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+      }
+    }
+  }
+};
+
+// matrix * selfadjoint product
+template <typename Scalar, typename Index,
+          int LhsStorageOrder, bool ConjugateLhs,
+          int RhsStorageOrder, bool ConjugateRhs>
+struct product_selfadjoint_matrix<Scalar,Index,LhsStorageOrder,false,ConjugateLhs, RhsStorageOrder,true,ConjugateRhs,ColMajor>
+{
+
+  static EIGEN_DONT_INLINE void run(
+    Index rows, Index cols,
+    const Scalar* _lhs, Index lhsStride,
+    const Scalar* _rhs, Index rhsStride,
+    Scalar* res,        Index resStride,
+    Scalar alpha)
+  {
+    Index size = cols;
+
+    const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
+
+    typedef gebp_traits<Scalar,Scalar> Traits;
+
+    Index kc = size; // cache block size along the K direction
+    Index mc = rows;  // cache block size along the M direction
+    Index nc = cols;  // cache block size along the N direction
+    computeProductBlockingSizes<Scalar,Scalar>(kc, mc, nc);
+    std::size_t sizeW = kc*Traits::WorkSpaceFactor;
+    std::size_t sizeB = sizeW + kc*cols;
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
+    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
+    Scalar* blockB = allocatedBlockB + sizeW;
+
+    gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp_kernel;
+    gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
+    symm_pack_rhs<Scalar, Index, Traits::nr,RhsStorageOrder> pack_rhs;
+
+    for(Index k2=0; k2<size; k2+=kc)
+    {
+      const Index actual_kc = (std::min)(k2+kc,size)-k2;
+
+      pack_rhs(blockB, _rhs, rhsStride, actual_kc, cols, k2);
+
+      // => GEPP
+      for(Index i2=0; i2<rows; i2+=mc)
+      {
+        const Index actual_mc = (std::min)(i2+mc,rows)-i2;
+        pack_lhs(blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
+
+        gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+      }
+    }
+  }
+};
+
+} // end namespace internal
+
+/***************************************************************************
+* Wrapper to product_selfadjoint_matrix
+***************************************************************************/
+
+namespace internal {
+template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
+struct traits<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false> >
+  : traits<ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>, Lhs, Rhs> >
+{};
+}
+
+template<typename Lhs, int LhsMode, typename Rhs, int RhsMode>
+struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>
+  : public ProductBase<SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>, Lhs, Rhs >
+{
+  EIGEN_PRODUCT_PUBLIC_INTERFACE(SelfadjointProductMatrix)
+
+  SelfadjointProductMatrix(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) {}
+
+  enum {
+    LhsIsUpper = (LhsMode&(Upper|Lower))==Upper,
+    LhsIsSelfAdjoint = (LhsMode&SelfAdjoint)==SelfAdjoint,
+    RhsIsUpper = (RhsMode&(Upper|Lower))==Upper,
+    RhsIsSelfAdjoint = (RhsMode&SelfAdjoint)==SelfAdjoint
+  };
+
+  template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
+  {
+    eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
+
+    const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
+    const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
+
+    Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
+                               * RhsBlasTraits::extractScalarFactor(m_rhs);
+
+    internal::product_selfadjoint_matrix<Scalar, Index,
+      EIGEN_LOGICAL_XOR(LhsIsUpper,
+                        internal::traits<Lhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, LhsIsSelfAdjoint,
+      NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(LhsIsUpper,bool(LhsBlasTraits::NeedToConjugate)),
+      EIGEN_LOGICAL_XOR(RhsIsUpper,
+                        internal::traits<Rhs>::Flags &RowMajorBit) ? RowMajor : ColMajor, RhsIsSelfAdjoint,
+      NumTraits<Scalar>::IsComplex && EIGEN_LOGICAL_XOR(RhsIsUpper,bool(RhsBlasTraits::NeedToConjugate)),
+      internal::traits<Dest>::Flags&RowMajorBit  ? RowMajor : ColMajor>
+      ::run(
+        lhs.rows(), rhs.cols(),                 // sizes
+        &lhs.coeffRef(0,0),    lhs.outerStride(),  // lhs info
+        &rhs.coeffRef(0,0),    rhs.outerStride(),  // rhs info
+        &dst.coeffRef(0,0), dst.outerStride(),  // result info
+        actualAlpha                             // alpha
+      );
+  }
+};
+
+#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H
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