使用 eigen::Matrix 修改 zip 迭代器会给出错误的结果
Modifying zip iterator with eigen::Matrix gives errenous results
我有三组点 X、Y、Z。我打算使用 Eigen::Matrix4f 应用转换。我使用一个 zip 迭代器和一个转换运算符来完成它。该程序可以编译，但结果只是部分正确。这个 post 的灵感来自
转型
A = [0 1 2;3 4 5;6 7 8; 1 1 1] 和 M=[1 2 3 4;5 6 7 8;9 10 11 12;13 14 15 16] 使用 M*A 应该导致：R=[28 34 40; 68 86 104； 108 138 168]
然而它给出：R=[28 34 40; 208 251 294； 2410 2905 3400]。
正在正确修改 X 值。但是 Y 和 Z 值是错误的。
我的代码和cmakelists如下：
#include <thrust/iterator/zip_iterator.h>
#include <thrust/execution_policy.h>
#include <thrust/copy.h>
#include <thrust/device_vector.h>
#include <Eigen/Dense>
#include <iostream>
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, FloatIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
typedef thrust::tuple<float,float,float> Float3;
struct modify_tuple
{
Eigen::Matrix4f _Mat4f;
modify_tuple(Eigen::Matrix4f Mat4f) : _Mat4f(Mat4f) { }
__host__ __device__ Float3 operator()(Float3 a) const
{
Eigen::Vector4f V(thrust::get<0>(a), thrust::get<1>(a), thrust::get<2>(a), 1.0);
V=_Mat4f*V;
Float3 res=thrust::make_tuple( V(0,0), V(1,0), V(2,0) );
return res;
}
};
int main(void)
{
thrust::device_vector<float> X(3);
thrust::device_vector<float> Y(3);
thrust::device_vector<float> Z(3);
X[0]=0, X[1]=1, X[2]=2;
Y[0]=4, Y[1]=5, Y[2]=6;
Z[0]=7, Z[1]=8, Z[2]=9;
std::cout << "X,Y,Z before transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
Float3Iterator P_first = thrust::make_zip_iterator(make_tuple(X.begin(), Y.begin(), Z.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(make_tuple(X.end(), Y.end(), Z.end()));
Eigen::Matrix4f M;
M(0,0)= 1; M(0,1)= 2; M(0,2)= 3; M(0,3)= 4;
M(1,0)= 5; M(1,1)= 6; M(1,2)= 7; M(1,3)= 8;
M(2,0)= 9; M(2,1)= 10; M(2,2)= 11; M(2,3)= 12;
M(3,0)= 13; M(3,1)= 14; M(3,2)= 15; M(3,3)= 16;
thrust::transform(thrust::device, P_first,P_last, P_first, modify_tuple(M));
std::cout << "X, Y, Z after transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
return 0;
}
CMakeLists.txt
CMAKE_MINIMUM_REQUIRED(VERSION 2.8)
FIND_PACKAGE(CUDA REQUIRED)
INCLUDE_DIRECTORIES(${CUDA_INCLUDE_DIRS})
INCLUDE_DIRECTORIES (/usr/include/eigen3)
set(
CUDA_NVCC_FLAGS
${CUDA_NVCC_FLAGS};
-O3 -gencode arch=compute_52,code=sm_52;
)
CUDA_ADD_EXECUTABLE(modify_zip_iterator_Whosebug_ver2 modify_zip_iterator_Whosebug_ver2.cu)
TARGET_LINK_LIBRARIES(modify_zip_iterator_Whosebug_ver2 ${CUDA_LIBRARIES})
可能你只需要获取最新的 Eigen。
我在 Fedora27 上使用了 CUDA 9.2，并从 here.
中获取了最新的特征。
然后我编译运行你的代码如下：
$ cat t21.cu
#include <thrust/iterator/zip_iterator.h>
#include <thrust/execution_policy.h>
#include <thrust/copy.h>
#include <thrust/device_vector.h>
#include <Eigen/Dense>
#include <iostream>
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, FloatIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
typedef thrust::tuple<float,float,float> Float3;
struct modify_tuple
{
Eigen::Matrix4f _Mat4f;
modify_tuple(Eigen::Matrix4f Mat4f) : _Mat4f(Mat4f) { }
__host__ __device__ Float3 operator()(Float3 a) const
{
Eigen::Vector4f V(thrust::get<0>(a), thrust::get<1>(a), thrust::get<2>(a), 1.0);
V=_Mat4f*V;
Float3 res=thrust::make_tuple( V(0,0), V(1,0), V(2,0) );
return res;
}
};
int main(void)
{
thrust::device_vector<float> X(3);
thrust::device_vector<float> Y(3);
thrust::device_vector<float> Z(3);
X[0]=0, X[1]=1, X[2]=2;
Y[0]=4, Y[1]=5, Y[2]=6;
Z[0]=7, Z[1]=8, Z[2]=9;
std::cout << "X,Y,Z before transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
Float3Iterator P_first = thrust::make_zip_iterator(make_tuple(X.begin(), Y.begin(), Z.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(make_tuple(X.end(), Y.end(), Z.end()));
Eigen::Matrix4f M;
M(0,0)= 1; M(0,1)= 2; M(0,2)= 3; M(0,3)= 4;
M(1,0)= 5; M(1,1)= 6; M(1,2)= 7; M(1,3)= 8;
M(2,0)= 9; M(2,1)= 10; M(2,2)= 11; M(2,3)= 12;
M(3,0)= 13; M(3,1)= 14; M(3,2)= 15; M(3,3)= 16;
thrust::transform(thrust::device, P_first,P_last, P_first, modify_tuple(M));
std::cout << "X, Y, Z after transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
return 0;
}
$ nvcc -std=c++11 -I/path/to/eigen/eigen-eigen-71546f1a9f0c t21.cu -o t21 --expt-relaxed-constexpr
$ ./t21
X,Y,Z before transformation=
0,1,2,
4,5,6,
7,8,9,
X, Y, Z after transformation=
33,39,45,
81,99,117,
129,159,189,
$
输出与您在问题中的预期不符，但您的预期也不正确。
由于取消引用 zip 迭代器而提供给仿函数的第一个元组将是 (X[0],Y[0],Z[0])，即 (0,4,7)。然后，您的仿函数将其转换为 (0,4,7,1) 并与 M 矩阵进行矩阵向量乘法。第一行内积由0*1+4*2+7*3+1*4给出，总和为33。第二行内积由0*5+4*6+7*7+1*8给出，总和为81。第三行内积由[=18=给出]]，其和为129。可以看到这个序列33,81,129正好是上面输出的第一列。
由于取消引用 zip 迭代器而提供给仿函数的第二个元组将是 (X[1],Y[1],Z[1])，即 (1,5,8)。然后，您的仿函数将其转换为 (1,5,8,1) 并与 M 矩阵进行矩阵向量乘法。第一行内积由 1*1+5*2+8*3+1*4 给出，总和为 39。第二行内积由 1*5+5*6+8*7+1*8 给出，总和为 99。第三行内积由 1*9+5*10+8*11+1*12 给出，其中sum 是 159。你可以看到这个序列 39,99,159 正好是上面输出的第二列。
输出的第3列我没有做相应的运算，但我觉得没有错
这是对您的代码的修改，证明了结果的正确性，在 Eigen 主机代码中进行算术运算：
$ cat t21.cu
#include <thrust/iterator/zip_iterator.h>
#include <thrust/execution_policy.h>
#include <thrust/copy.h>
#include <thrust/device_vector.h>
#include <Eigen/Dense>
#include <iostream>
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, FloatIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
typedef thrust::tuple<float,float,float> Float3;
struct modify_tuple
{
Eigen::Matrix4f _Mat4f;
modify_tuple(Eigen::Matrix4f Mat4f) : _Mat4f(Mat4f) { }
__host__ __device__ Float3 operator()(Float3 a) const
{
Eigen::Vector4f V(thrust::get<0>(a), thrust::get<1>(a), thrust::get<2>(a), 1.0);
V=_Mat4f*V;
Float3 res=thrust::make_tuple( V(0,0), V(1,0), V(2,0) );
return res;
}
};
int main(void)
{
thrust::device_vector<float> X(3);
thrust::device_vector<float> Y(3);
thrust::device_vector<float> Z(3);
X[0]=0, X[1]=1, X[2]=2;
Y[0]=4, Y[1]=5, Y[2]=6;
Z[0]=7, Z[1]=8, Z[2]=9;
std::cout << "X,Y,Z before transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::host_vector<float> hX = X;
thrust::host_vector<float> hY = Y;
thrust::host_vector<float> hZ = Z;
Float3Iterator P_first = thrust::make_zip_iterator(make_tuple(X.begin(), Y.begin(), Z.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(make_tuple(X.end(), Y.end(), Z.end()));
Eigen::Matrix4f M;
M(0,0)= 1; M(0,1)= 2; M(0,2)= 3; M(0,3)= 4;
M(1,0)= 5; M(1,1)= 6; M(1,2)= 7; M(1,3)= 8;
M(2,0)= 9; M(2,1)= 10; M(2,2)= 11; M(2,3)= 12;
M(3,0)= 13; M(3,1)= 14; M(3,2)= 15; M(3,3)= 16;
thrust::transform(thrust::device, P_first,P_last, P_first, modify_tuple(M));
std::cout << "X, Y, Z after transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
Eigen::Vector4f hV;
hV(0) = hX[0];
hV(1) = hY[0];
hV(2) = hZ[0];
hV(3) = 1;
hV = M*hV;
std::cout << "column 0:" << std::endl;
std::cout << hV;
std::cout << std::endl;
hV(0) = hX[1];
hV(1) = hY[1];
hV(2) = hZ[1];
hV(3) = 1;
hV = M*hV;
std::cout << "column 1:" << std::endl;
std::cout << hV;
std::cout << std::endl;
hV(0) = hX[2];
hV(1) = hY[2];
hV(2) = hZ[2];
hV(3) = 1;
hV = M*hV;
std::cout << "column 2:" << std::endl;
std::cout << hV;
std::cout << std::endl;
return 0;
}
$ nvcc -std=c++11 -I/home/bob/eigen/eigen-eigen-71546f1a9f0c t21.cu -o t21 --expt-relaxed-constexpr
$ ./t21
X,Y,Z before transformation=
0,1,2,
4,5,6,
7,8,9,
X, Y, Z after transformation=
33,39,45,
81,99,117,
129,159,189,
column 0:
33
81
129
177
column 1:
39
99
159
219
column 2:
45
117
189
261
$
我有三组点 X、Y、Z。我打算使用 Eigen::Matrix4f 应用转换。我使用一个 zip 迭代器和一个转换运算符来完成它。该程序可以编译，但结果只是部分正确。这个 post 的灵感来自
转型 A = [0 1 2;3 4 5;6 7 8; 1 1 1] 和 M=[1 2 3 4;5 6 7 8;9 10 11 12;13 14 15 16] 使用 M*A 应该导致：R=[28 34 40; 68 86 104； 108 138 168] 然而它给出：R=[28 34 40; 208 251 294； 2410 2905 3400]。
正在正确修改 X 值。但是 Y 和 Z 值是错误的。
我的代码和cmakelists如下：
#include <thrust/iterator/zip_iterator.h>
#include <thrust/execution_policy.h>
#include <thrust/copy.h>
#include <thrust/device_vector.h>
#include <Eigen/Dense>
#include <iostream>
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, FloatIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
typedef thrust::tuple<float,float,float> Float3;
struct modify_tuple
{
Eigen::Matrix4f _Mat4f;
modify_tuple(Eigen::Matrix4f Mat4f) : _Mat4f(Mat4f) { }
__host__ __device__ Float3 operator()(Float3 a) const
{
Eigen::Vector4f V(thrust::get<0>(a), thrust::get<1>(a), thrust::get<2>(a), 1.0);
V=_Mat4f*V;
Float3 res=thrust::make_tuple( V(0,0), V(1,0), V(2,0) );
return res;
}
};
int main(void)
{
thrust::device_vector<float> X(3);
thrust::device_vector<float> Y(3);
thrust::device_vector<float> Z(3);
X[0]=0, X[1]=1, X[2]=2;
Y[0]=4, Y[1]=5, Y[2]=6;
Z[0]=7, Z[1]=8, Z[2]=9;
std::cout << "X,Y,Z before transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
Float3Iterator P_first = thrust::make_zip_iterator(make_tuple(X.begin(), Y.begin(), Z.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(make_tuple(X.end(), Y.end(), Z.end()));
Eigen::Matrix4f M;
M(0,0)= 1; M(0,1)= 2; M(0,2)= 3; M(0,3)= 4;
M(1,0)= 5; M(1,1)= 6; M(1,2)= 7; M(1,3)= 8;
M(2,0)= 9; M(2,1)= 10; M(2,2)= 11; M(2,3)= 12;
M(3,0)= 13; M(3,1)= 14; M(3,2)= 15; M(3,3)= 16;
thrust::transform(thrust::device, P_first,P_last, P_first, modify_tuple(M));
std::cout << "X, Y, Z after transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
return 0;
}
CMakeLists.txt
CMAKE_MINIMUM_REQUIRED(VERSION 2.8)
FIND_PACKAGE(CUDA REQUIRED)
INCLUDE_DIRECTORIES(${CUDA_INCLUDE_DIRS})
INCLUDE_DIRECTORIES (/usr/include/eigen3)
set(
CUDA_NVCC_FLAGS
${CUDA_NVCC_FLAGS};
-O3 -gencode arch=compute_52,code=sm_52;
)
CUDA_ADD_EXECUTABLE(modify_zip_iterator_Whosebug_ver2 modify_zip_iterator_Whosebug_ver2.cu)
TARGET_LINK_LIBRARIES(modify_zip_iterator_Whosebug_ver2 ${CUDA_LIBRARIES})
可能你只需要获取最新的 Eigen。
我在 Fedora27 上使用了 CUDA 9.2，并从 here.
中获取了最新的特征。然后我编译运行你的代码如下：
$ cat t21.cu
#include <thrust/iterator/zip_iterator.h>
#include <thrust/execution_policy.h>
#include <thrust/copy.h>
#include <thrust/device_vector.h>
#include <Eigen/Dense>
#include <iostream>
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, FloatIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
typedef thrust::tuple<float,float,float> Float3;
struct modify_tuple
{
Eigen::Matrix4f _Mat4f;
modify_tuple(Eigen::Matrix4f Mat4f) : _Mat4f(Mat4f) { }
__host__ __device__ Float3 operator()(Float3 a) const
{
Eigen::Vector4f V(thrust::get<0>(a), thrust::get<1>(a), thrust::get<2>(a), 1.0);
V=_Mat4f*V;
Float3 res=thrust::make_tuple( V(0,0), V(1,0), V(2,0) );
return res;
}
};
int main(void)
{
thrust::device_vector<float> X(3);
thrust::device_vector<float> Y(3);
thrust::device_vector<float> Z(3);
X[0]=0, X[1]=1, X[2]=2;
Y[0]=4, Y[1]=5, Y[2]=6;
Z[0]=7, Z[1]=8, Z[2]=9;
std::cout << "X,Y,Z before transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
Float3Iterator P_first = thrust::make_zip_iterator(make_tuple(X.begin(), Y.begin(), Z.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(make_tuple(X.end(), Y.end(), Z.end()));
Eigen::Matrix4f M;
M(0,0)= 1; M(0,1)= 2; M(0,2)= 3; M(0,3)= 4;
M(1,0)= 5; M(1,1)= 6; M(1,2)= 7; M(1,3)= 8;
M(2,0)= 9; M(2,1)= 10; M(2,2)= 11; M(2,3)= 12;
M(3,0)= 13; M(3,1)= 14; M(3,2)= 15; M(3,3)= 16;
thrust::transform(thrust::device, P_first,P_last, P_first, modify_tuple(M));
std::cout << "X, Y, Z after transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
return 0;
}
$ nvcc -std=c++11 -I/path/to/eigen/eigen-eigen-71546f1a9f0c t21.cu -o t21 --expt-relaxed-constexpr
$ ./t21
X,Y,Z before transformation=
0,1,2,
4,5,6,
7,8,9,
X, Y, Z after transformation=
33,39,45,
81,99,117,
129,159,189,
$
输出与您在问题中的预期不符，但您的预期也不正确。
由于取消引用 zip 迭代器而提供给仿函数的第一个元组将是 (X[0],Y[0],Z[0])，即 (0,4,7)。然后，您的仿函数将其转换为 (0,4,7,1) 并与 M 矩阵进行矩阵向量乘法。第一行内积由0*1+4*2+7*3+1*4给出，总和为33。第二行内积由0*5+4*6+7*7+1*8给出，总和为81。第三行内积由[=18=给出]]，其和为129。可以看到这个序列33,81,129正好是上面输出的第一列。
由于取消引用 zip 迭代器而提供给仿函数的第二个元组将是 (X[1],Y[1],Z[1])，即 (1,5,8)。然后，您的仿函数将其转换为 (1,5,8,1) 并与 M 矩阵进行矩阵向量乘法。第一行内积由 1*1+5*2+8*3+1*4 给出，总和为 39。第二行内积由 1*5+5*6+8*7+1*8 给出，总和为 99。第三行内积由 1*9+5*10+8*11+1*12 给出，其中sum 是 159。你可以看到这个序列 39,99,159 正好是上面输出的第二列。
输出的第3列我没有做相应的运算，但我觉得没有错
这是对您的代码的修改，证明了结果的正确性，在 Eigen 主机代码中进行算术运算：
$ cat t21.cu
#include <thrust/iterator/zip_iterator.h>
#include <thrust/execution_policy.h>
#include <thrust/copy.h>
#include <thrust/device_vector.h>
#include <Eigen/Dense>
#include <iostream>
typedef thrust::device_vector<float>::iterator FloatIterator;
typedef thrust::tuple<FloatIterator, FloatIterator, FloatIterator> FloatIteratorTuple;
typedef thrust::zip_iterator<FloatIteratorTuple> Float3Iterator;
typedef thrust::tuple<float,float,float> Float3;
struct modify_tuple
{
Eigen::Matrix4f _Mat4f;
modify_tuple(Eigen::Matrix4f Mat4f) : _Mat4f(Mat4f) { }
__host__ __device__ Float3 operator()(Float3 a) const
{
Eigen::Vector4f V(thrust::get<0>(a), thrust::get<1>(a), thrust::get<2>(a), 1.0);
V=_Mat4f*V;
Float3 res=thrust::make_tuple( V(0,0), V(1,0), V(2,0) );
return res;
}
};
int main(void)
{
thrust::device_vector<float> X(3);
thrust::device_vector<float> Y(3);
thrust::device_vector<float> Z(3);
X[0]=0, X[1]=1, X[2]=2;
Y[0]=4, Y[1]=5, Y[2]=6;
Z[0]=7, Z[1]=8, Z[2]=9;
std::cout << "X,Y,Z before transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::host_vector<float> hX = X;
thrust::host_vector<float> hY = Y;
thrust::host_vector<float> hZ = Z;
Float3Iterator P_first = thrust::make_zip_iterator(make_tuple(X.begin(), Y.begin(), Z.begin()));
Float3Iterator P_last = thrust::make_zip_iterator(make_tuple(X.end(), Y.end(), Z.end()));
Eigen::Matrix4f M;
M(0,0)= 1; M(0,1)= 2; M(0,2)= 3; M(0,3)= 4;
M(1,0)= 5; M(1,1)= 6; M(1,2)= 7; M(1,3)= 8;
M(2,0)= 9; M(2,1)= 10; M(2,2)= 11; M(2,3)= 12;
M(3,0)= 13; M(3,1)= 14; M(3,2)= 15; M(3,3)= 16;
thrust::transform(thrust::device, P_first,P_last, P_first, modify_tuple(M));
std::cout << "X, Y, Z after transformation="<< std::endl;
thrust::copy_n(X.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Y.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
thrust::copy_n(Z.begin(), 3, std::ostream_iterator<float>(std::cout, ","));
std::cout << std::endl;
Eigen::Vector4f hV;
hV(0) = hX[0];
hV(1) = hY[0];
hV(2) = hZ[0];
hV(3) = 1;
hV = M*hV;
std::cout << "column 0:" << std::endl;
std::cout << hV;
std::cout << std::endl;
hV(0) = hX[1];
hV(1) = hY[1];
hV(2) = hZ[1];
hV(3) = 1;
hV = M*hV;
std::cout << "column 1:" << std::endl;
std::cout << hV;
std::cout << std::endl;
hV(0) = hX[2];
hV(1) = hY[2];
hV(2) = hZ[2];
hV(3) = 1;
hV = M*hV;
std::cout << "column 2:" << std::endl;
std::cout << hV;
std::cout << std::endl;
return 0;
}
$ nvcc -std=c++11 -I/home/bob/eigen/eigen-eigen-71546f1a9f0c t21.cu -o t21 --expt-relaxed-constexpr
$ ./t21
X,Y,Z before transformation=
0,1,2,
4,5,6,
7,8,9,
X, Y, Z after transformation=
33,39,45,
81,99,117,
129,159,189,
column 0:
33
81
129
177
column 1:
39
99
159
219
column 2:
45
117
189
261
$