1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This file is part of Eigen, a lightweight C++ template library
2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// for linear algebra.
3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath//
7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// This Source Code Form is subject to the terms of the Mozilla
8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// Public License v. 2.0. If a copy of the MPL was not distributed
9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include "main.h"
12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath// using namespace Eigen;
14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace Eigen {
16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathnamespace internal {
17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename T> T negate(const T& x) { return -x; }
18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> bool isApproxAbs(const Scalar& a, const Scalar& b, const typename NumTraits<Scalar>::Real& refvalue)
22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return internal::isMuchSmallerThan(a-b, refvalue);
24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> bool areApproxAbs(const Scalar* a, const Scalar* b, int size, const typename NumTraits<Scalar>::Real& refvalue)
27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    if (!isApproxAbs(a[i],b[i],refvalue))
31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      std::cout << "[" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != " << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "\n";
33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return false;
34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return true;
37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> bool areApprox(const Scalar* a, const Scalar* b, int size)
40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
437faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    if (a[i]!=b[i] && !internal::isApprox(a[i],b[i]))
44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      std::cout << "[" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != " << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "\n";
46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      return false;
47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  return true;
50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define CHECK_CWISE2(REFOP, POP) { \
54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i) \
55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = REFOP(data1[i], data1[i+PacketSize]); \
56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(data2, POP(internal::pload<Packet>(data1), internal::pload<Packet>(data1+PacketSize))); \
57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define CHECK_CWISE1(REFOP, POP) { \
61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i) \
62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = REFOP(data1[i]); \
63c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(data2, POP(internal::pload<Packet>(data1))); \
64c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
65c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
66c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
67c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<bool Cond,typename Packet>
68c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct packet_helper
69c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
70c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename T>
71c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline Packet load(const T* from) const { return internal::pload<Packet>(from); }
72c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
73c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename T>
74c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline void store(T* to, const Packet& x) const { internal::pstore(to,x); }
75c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
76c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
77c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Packet>
78c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathstruct packet_helper<false,Packet>
79c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
80c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename T>
81c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline T load(const T* from) const { return *from; }
82c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
83c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  template<typename T>
84c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  inline void store(T* to, const T& x) const { *to = x; }
85c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath};
86c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
87c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define CHECK_CWISE1_IF(COND, REFOP, POP) if(COND) { \
88c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  packet_helper<COND,Packet> h; \
89c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i) \
90c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = REFOP(data1[i]); \
91c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  h.store(data2, POP(h.load(data1))); \
92c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && #POP); \
93c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
94c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
95c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_ADD(a,b) ((a)+(b))
96c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_SUB(a,b) ((a)-(b))
97c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_MUL(a,b) ((a)*(b))
98c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#define REF_DIV(a,b) ((a)/(b))
99c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
100c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> void packetmath()
101c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
1027faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::abs;
103c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::packet_traits<Scalar>::type Packet;
104c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int PacketSize = internal::packet_traits<Scalar>::size;
105c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename NumTraits<Scalar>::Real RealScalar;
106c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
107c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int size = PacketSize*4;
108c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar data1[internal::packet_traits<Scalar>::size*4];
109c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar data2[internal::packet_traits<Scalar>::size*4];
110c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Packet packets[PacketSize*2];
111c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar ref[internal::packet_traits<Scalar>::size*4];
112c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  RealScalar refvalue = 0;
113c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
114c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
115c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data1[i] = internal::random<Scalar>()/RealScalar(PacketSize);
116c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data2[i] = internal::random<Scalar>()/RealScalar(PacketSize);
1177faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    refvalue = (std::max)(refvalue,abs(data1[i]));
118c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
119c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
120c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(data2, internal::pload<Packet>(data1));
121c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(data1, data2, PacketSize) && "aligned load/store");
122c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
123c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int offset=0; offset<PacketSize; ++offset)
124c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
125c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::pstore(data2, internal::ploadu<Packet>(data1+offset));
126c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(data1+offset, data2, PacketSize) && "internal::ploadu");
127c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
128c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
129c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int offset=0; offset<PacketSize; ++offset)
130c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
131c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::pstoreu(data2+offset, internal::pload<Packet>(data1));
132c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(data1, data2+offset, PacketSize) && "internal::pstoreu");
133c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
134c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
135c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int offset=0; offset<PacketSize; ++offset)
136c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
137c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    packets[0] = internal::pload<Packet>(data1);
138c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    packets[1] = internal::pload<Packet>(data1+PacketSize);
139c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath         if (offset==0) internal::palign<0>(packets[0], packets[1]);
140c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if (offset==1) internal::palign<1>(packets[0], packets[1]);
141c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if (offset==2) internal::palign<2>(packets[0], packets[1]);
142c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    else if (offset==3) internal::palign<3>(packets[0], packets[1]);
143c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::pstore(data2, packets[0]);
144c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
145c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<PacketSize; ++i)
146c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ref[i] = data1[i+offset];
147c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
148c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(ref, data2, PacketSize) && "internal::palign");
149c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
150c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
151c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE2(REF_ADD,  internal::padd);
152c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE2(REF_SUB,  internal::psub);
153c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE2(REF_MUL,  internal::pmul);
154c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  #ifndef EIGEN_VECTORIZE_ALTIVEC
155c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if (!internal::is_same<Scalar,int>::value)
156c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CHECK_CWISE2(REF_DIV,  internal::pdiv);
157c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  #endif
158c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE1(internal::negate, internal::pnegate);
1597faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1(numext::conj, internal::pconj);
160c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
161c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int offset=0;offset<3;++offset)
162c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
163c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<PacketSize; ++i)
164c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ref[i] = data1[offset];
165c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::pstore(data2, internal::pset1<Packet>(data1[offset]));
166c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(ref, data2, PacketSize) && "internal::pset1");
167c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
168c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
169c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(internal::isApprox(data1[0], internal::pfirst(internal::pload<Packet>(data1))) && "internal::pfirst");
170c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
171c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  if(PacketSize>1)
172c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
173c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int offset=0;offset<4;++offset)
174c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    {
175c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      for(int i=0;i<PacketSize/2;++i)
176c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath        ref[2*i+0] = ref[2*i+1] = data1[offset+i];
177c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      internal::pstore(data2,internal::ploaddup<Packet>(data1+offset));
178c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      VERIFY(areApprox(ref, data2, PacketSize) && "ploaddup");
179c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    }
180c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
181c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
182c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ref[0] = 0;
183c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
184c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[0] += data1[i];
185c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(isApproxAbs(ref[0], internal::predux(internal::pload<Packet>(data1)), refvalue) && "internal::predux");
186c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
187c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ref[0] = 1;
188c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
189c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[0] *= data1[i];
190c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(internal::isApprox(ref[0], internal::predux_mul(internal::pload<Packet>(data1))) && "internal::predux_mul");
191c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
192c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int j=0; j<PacketSize; ++j)
193c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
194c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[j] = 0;
195c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for (int i=0; i<PacketSize; ++i)
196c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ref[j] += data1[i+j*PacketSize];
197c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    packets[j] = internal::pload<Packet>(data1+j*PacketSize);
198c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
199c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(data2, internal::preduxp(packets));
200c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApproxAbs(ref, data2, PacketSize, refvalue) && "internal::preduxp");
201c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
202c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
203c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = data1[PacketSize-i-1];
204c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(data2, internal::preverse(internal::pload<Packet>(data1)));
205c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && "internal::preverse");
206c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
207c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
208c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> void packetmath_real()
209c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
2107faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::abs;
211c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::packet_traits<Scalar>::type Packet;
212c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int PacketSize = internal::packet_traits<Scalar>::size;
213c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
214c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int size = PacketSize*4;
215c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar data1[internal::packet_traits<Scalar>::size*4];
216c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar data2[internal::packet_traits<Scalar>::size*4];
217c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar ref[internal::packet_traits<Scalar>::size*4];
218c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
219c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
220c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
2217faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    data1[i] = internal::random<Scalar>(-1,1) * std::pow(Scalar(10), internal::random<Scalar>(-3,3));
2227faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    data2[i] = internal::random<Scalar>(-1,1) * std::pow(Scalar(10), internal::random<Scalar>(-3,3));
223c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
2247faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasSin, std::sin, internal::psin);
2257faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasCos, std::cos, internal::pcos);
2267faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasTan, std::tan, internal::ptan);
227c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
228c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
229c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
230c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data1[i] = internal::random<Scalar>(-1,1);
231c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data2[i] = internal::random<Scalar>(-1,1);
232c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
2337faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasASin, std::asin, internal::pasin);
2347faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasACos, std::acos, internal::pacos);
235c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
236c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
237c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
238c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data1[i] = internal::random<Scalar>(-87,88);
239c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data2[i] = internal::random<Scalar>(-87,88);
240c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
2417faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasExp, std::exp, internal::pexp);
242c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
243c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
244c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
2457faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    data1[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
2467faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    data2[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
247c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
2487faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  if(internal::random<float>(0,1)<0.1)
2497faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    data1[internal::random<int>(0, PacketSize)] = 0;
2507faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasLog, std::log, internal::plog);
2517faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1_IF(internal::packet_traits<Scalar>::HasSqrt, std::sqrt, internal::psqrt);
2527faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez}
2537faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
2547faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandeztemplate<typename Scalar> void packetmath_notcomplex()
2557faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez{
2567faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  using std::abs;
2577faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  typedef typename internal::packet_traits<Scalar>::type Packet;
2587faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  const int PacketSize = internal::packet_traits<Scalar>::size;
2597faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
2607faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  EIGEN_ALIGN16 Scalar data1[internal::packet_traits<Scalar>::size*4];
2617faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  EIGEN_ALIGN16 Scalar data2[internal::packet_traits<Scalar>::size*4];
2627faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  EIGEN_ALIGN16 Scalar ref[internal::packet_traits<Scalar>::size*4];
2637faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
2647faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  Array<Scalar,Dynamic,1>::Map(data1, internal::packet_traits<Scalar>::size*4).setRandom();
265c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
266c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ref[0] = data1[0];
267c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
268c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[0] = (std::min)(ref[0],data1[i]);
269c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(internal::isApprox(ref[0], internal::predux_min(internal::pload<Packet>(data1))) && "internal::predux_min");
270c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
271c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE2((std::min), internal::pmin);
272c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  CHECK_CWISE2((std::max), internal::pmax);
2737faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez  CHECK_CWISE1(abs, internal::pabs);
274c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
275c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  ref[0] = data1[0];
276c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
277c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[0] = (std::max)(ref[0],data1[i]);
278c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(internal::isApprox(ref[0], internal::predux_max(internal::pload<Packet>(data1))) && "internal::predux_max");
279c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
280c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<PacketSize; ++i)
281c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = data1[0]+Scalar(i);
282c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(data2, internal::plset(data1[0]));
283c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, data2, PacketSize) && "internal::plset");
284c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
285c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
286c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar,bool ConjLhs,bool ConjRhs> void test_conj_helper(Scalar* data1, Scalar* data2, Scalar* ref, Scalar* pval)
287c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
288c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::packet_traits<Scalar>::type Packet;
289c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int PacketSize = internal::packet_traits<Scalar>::size;
290c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
291c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::conj_if<ConjLhs> cj0;
292c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::conj_if<ConjRhs> cj1;
293c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::conj_helper<Scalar,Scalar,ConjLhs,ConjRhs> cj;
294c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::conj_helper<Packet,Packet,ConjLhs,ConjRhs> pcj;
295c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
296c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i=0;i<PacketSize;++i)
297c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
298c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] = cj0(data1[i]) * cj1(data2[i]);
299c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(internal::isApprox(ref[i], cj.pmul(data1[i],data2[i])) && "conj_helper pmul");
300c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
301c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(pval,pcj.pmul(internal::pload<Packet>(data1),internal::pload<Packet>(data2)));
302c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, pval, PacketSize) && "conj_helper pmul");
303c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
304c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i=0;i<PacketSize;++i)
305c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
306c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    Scalar tmp = ref[i];
307c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    ref[i] += cj0(data1[i]) * cj1(data2[i]);
308c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(internal::isApprox(ref[i], cj.pmadd(data1[i],data2[i],tmp)) && "conj_helper pmadd");
309c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
310c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  internal::pstore(pval,pcj.pmadd(internal::pload<Packet>(data1),internal::pload<Packet>(data2),internal::pload<Packet>(pval)));
311c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  VERIFY(areApprox(ref, pval, PacketSize) && "conj_helper pmadd");
312c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
313c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
314c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathtemplate<typename Scalar> void packetmath_complex()
315c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
316c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  typedef typename internal::packet_traits<Scalar>::type Packet;
317c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int PacketSize = internal::packet_traits<Scalar>::size;
318c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
319c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  const int size = PacketSize*4;
320c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar data1[PacketSize*4];
321c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar data2[PacketSize*4];
322c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar ref[PacketSize*4];
323c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  EIGEN_ALIGN16 Scalar pval[PacketSize*4];
324c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
325c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for (int i=0; i<size; ++i)
326c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
327c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data1[i] = internal::random<Scalar>() * Scalar(1e2);
328c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    data2[i] = internal::random<Scalar>() * Scalar(1e2);
329c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
330c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
331c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  test_conj_helper<Scalar,false,false> (data1,data2,ref,pval);
332c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  test_conj_helper<Scalar,false,true>  (data1,data2,ref,pval);
333c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  test_conj_helper<Scalar,true,false>  (data1,data2,ref,pval);
334c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  test_conj_helper<Scalar,true,true>   (data1,data2,ref,pval);
335c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
336c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  {
337c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    for(int i=0;i<PacketSize;++i)
338c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath      ref[i] = Scalar(std::imag(data1[i]),std::real(data1[i]));
339c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    internal::pstore(pval,internal::pcplxflip(internal::pload<Packet>(data1)));
340c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    VERIFY(areApprox(ref, pval, PacketSize) && "pcplxflip");
341c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
342c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
343c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
344c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
345c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
346c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathvoid test_packetmath()
347c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{
348c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  for(int i = 0; i < g_repeat; i++) {
349c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( packetmath<float>() );
350c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( packetmath<double>() );
351c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_3( packetmath<int>() );
352c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( packetmath<std::complex<float> >() );
353c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( packetmath<std::complex<double> >() );
354c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
3557faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    CALL_SUBTEST_1( packetmath_notcomplex<float>() );
3567faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    CALL_SUBTEST_2( packetmath_notcomplex<double>() );
3577faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez    CALL_SUBTEST_3( packetmath_notcomplex<int>() );
3587faaa9f3f0df9d23790277834d426c3d992ac3baCarlos Hernandez
359c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( packetmath_real<float>() );
360c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( packetmath_real<double>() );
361c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath
362c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_1( packetmath_complex<std::complex<float> >() );
363c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath    CALL_SUBTEST_2( packetmath_complex<std::complex<double> >() );
364c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath  }
365c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath}
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