vector_math.hpp
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* Author: Anatoly Baskeheev, Itseez Ltd, (myname.mysurname@mycompany.com)
*/
#ifndef PCL_GPU_UTILS_DEVICE_VECTOR_MATH_HPP_
#define PCL_GPU_UTILS_DEVICE_VECTOR_MATH_HPP_
namespace pcl
{
namespace device
{
////////////////////////////////
// one element vectors
////////////////////////////////
// two element vectors
////////////////////////////////
// three element vectors
#define PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP(type, scalar, op) \
__device__ __host__ __forceinline__ type & operator op (type & v1, const type & v2) { v1.x op v2.x; v1.y op v2.y; v1.z op v2.z; return v1; } \
__device__ __host__ __forceinline__ type & operator op (type & v, scalar val) { v.x op val; v.y op val; v.z op val; return v; }
PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP(float3, float, -=)
PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP(float3, float, +=)
PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP(float3, float, *=)
PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP(short3, short, -=)
PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP(int3, int, +=)
#undef PCL_GPU_IMPLEMENT_COMPOUND_VEC3_OP
__device__ __host__ __forceinline__ float dot(const float3& v1, const float3& v2)
{
return v1.x * v2.x + v1.y * v2.y + v1.z * v2.z;
}
__device__ __host__ __forceinline__ float3 cross(const float3& v1, const float3& v2)
{
return make_float3(v1.y * v2.z - v1.z * v2.y, v1.z * v2.x - v1.x * v2.z, v1.x * v2.y - v1.y * v2.x);
}
////////////////////////////////
// four element vectors
__device__ __host__ __forceinline__ float dot(const float4& v1, const float4& v2)
{
return v1.x * v2.x + v1.y * v2.y + v1.z * v2.z + v1.w * v2.w;
}
////////////////////////////////
// alltype binary operarators
#define PCL_GPU_IMPLEMENT_VEC_BINOP(type, scalar, op, cop) \
__device__ __host__ __forceinline__ type operator op (const type & v1, const type & v2) { type r = v1; r cop v2; return r; } \
__device__ __host__ __forceinline__ type operator op (const type & v1, scalar c) { type r = v1; r cop c; return r; }
PCL_GPU_IMPLEMENT_VEC_BINOP(float3, float, -, -=)
PCL_GPU_IMPLEMENT_VEC_BINOP(float3, float, +, +=)
PCL_GPU_IMPLEMENT_VEC_BINOP(float3, float, *, *=)
PCL_GPU_IMPLEMENT_VEC_BINOP(short3, short, -, -=)
PCL_GPU_IMPLEMENT_VEC_BINOP(int3, int, +, +=)
#undef PCL_GPU_IMPLEMENT_VEC_BINOP
////////////////////////////////
// tempalted operations vectors
template<typename T> __device__ __host__ __forceinline__ float norm(const T& val)
{
return sqrtf(dot(val, val));
}
template<typename T> __host__ __device__ __forceinline__ float inverse_norm(const T& v)
{
return rsqrtf(dot(v, v));
}
template<typename T> __host__ __device__ __forceinline__ T normalized(const T& v)
{
return v * inverse_norm(v);
}
template<typename T> __host__ __device__ __forceinline__ T normalized_safe(const T& v)
{
return (dot(v, v) > 0) ? (v * rsqrtf(dot(v, v))) : v;
}
}
}
#endif /* PCL_GPU_UTILS_DEVICE_VECTOR_MATH_HPP_ */
pcl
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:45
pcl::device::normalized
__device__ __forceinline__ float3 normalized(const float3 &v)
Definition: utils.hpp:99
pcl::device::cross
__device__ __host__ __forceinline__ float3 cross(const float3 &v1, const float3 &v2)
Definition: utils.hpp:105
pcl::device::dot
__device__ __forceinline__ float dot(const float3 &v1, const float3 &v2)
Definition: utils.hpp:57
pcl::device::inverse_norm
__host__ __device__ __forceinline__ float inverse_norm(const T &v)
Definition: vector_math.hpp:113
pcl::device::norm
__device__ __host__ __forceinline__ float norm(const float3 &v1, const float3 &v2)
Definition: vector_operations.hpp:60
pcl::device::normalized_safe
__host__ __device__ __forceinline__ T normalized_safe(const T &v)
Definition: vector_math.hpp:123