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#pragma once
#include "data_math.hpp"
namespace saw {
template<uint64_t D>
class iterator final {
private:
template<uint64_t i, typename Func>
static void iterate_over_i(
Func& func,
const data<schema::FixedArray<schema::UInt64,D>>& start,
const data<schema::FixedArray<schema::UInt64,D>>& end,
data<schema::FixedArray<schema::UInt64,D>>& iter
){
static_assert(i <= D, "Iterator sanity check");
if constexpr ( i == D ){
func(iter);
}else // Has to be i < D due to last static_assert and constexpr if
{
for(iter.at({i}) = start.at({i}); iter.at({i}) < end.at({i}); ++iter.at({i})){
iterate_over_i<i+1u,Func>(func,start,end,iter);
}
}
}
public:
template<typename Func>
static void apply(
Func&& func,
const data<schema::FixedArray<schema::UInt64,D>>& start,
const data<schema::FixedArray<schema::UInt64,D>>& end
){
data<schema::FixedArray<schema::UInt64,D>> iter;
iterate_over_i<0u,Func>(func,start,end,iter);
}
};
namespace math {
/**
* Builds a scalar from its native value. Shorthand for the two step
* data<T>{value} -> data<Scalar<T>>{...} conversion, which the language won't
* do implicitly.
*/
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
constexpr data<schema::Scalar<T>, Encoding> make_scalar(typename native_data_type<T>::type value){
return data<schema::Scalar<T>, Encoding>{data<T,Encoding>{value}};
}
/**
* Builds a vector from its native component values. The dimension is deduced
* from the argument count.
*/
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING, typename... Args>
constexpr data<schema::Vector<T,sizeof...(Args)>, Encoding> make_vector(Args... args){
return data<schema::Vector<T,sizeof...(Args)>, Encoding>{
data<schema::FixedArray<T,sizeof...(Args)>, Encoding>{
std::array<data<T,Encoding>, sizeof...(Args)>{
data<T,Encoding>{static_cast<typename native_data_type<T>::type>(args)}...
}
}
};
}
template<typename T, uint64_t D, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>, Encoding> dot(const data<schema::Vector<T,D>, Encoding>& left, const data<schema::Vector<T,D>, Encoding>& right){
data<schema::Scalar<T>,Encoding> val;
auto& inner = val({});
for(uint64_t i = 0u; i < D; ++i){
inner = inner + left({{i}}) * right({{i}});
}
return val;
}
template<typename T,typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>,Encoding> sqrt(const data<schema::Scalar<T>,Encoding>& inp){
data<schema::Scalar<T>,Encoding> out;
out.at({}).set(std::sqrt(inp.at({}).get()));
return out;
}
/**
* Euclidean length of a vector.
*/
template<typename T, uint64_t D, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>, Encoding> norm(const data<schema::Vector<T,D>, Encoding>& input){
return sqrt<T,Encoding>(dot<T,D,Encoding>(input,input));
}
template<typename T, uint64_t D, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,D>, Encoding> normalize(const data<schema::Vector<T,D>>& input ) {
auto inp_dot = dot<T,D,Encoding>(input,input);
if(inp_dot.at({}).get() <= 0){
return input;
}
auto sqrt_inp_dot = sqrt<T>(inp_dot);
saw::data<schema::Vector<T,D>, Encoding> out;
for(uint64_t i = 0u; i < D; ++i){
out.at({{i}}) = (input.at({{i}}) / sqrt_inp_dot.at({}));
}
return out;
}
template<typename T, uint64_t D, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,D>, Encoding> vectorize_data(const data<schema::FixedArray<T,D>>& dat){
data<schema::Vector<T,D>,Encoding> vec_data;
for(uint64_t i{0u}; i < D; ++i){
vec_data.at({{i}}) = dat.at({{i}});
}
return vec_data;
}
template<typename T, uint64_t M, uint64_t N, uint64_t K, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Matrix<T,M,N>, Encoding> multiply(const data<schema::Matrix<T,M,K>, Encoding>& left, const data<schema::Matrix<T,K,N>, Encoding>& right){
data<schema::Matrix<T,M,N>, Encoding> lr;
for(uint64_t i = 0u; i < M; ++i){
for(uint64_t j = 0u; j < N; ++j){
for(uint64_t k = 0u; k < K; ++k){
lr.at({{i,j}}) = lr.at({{i,j}}) + left.at({{i,k}}) * right.at({{k,j}});
}
}
}
return lr;
}
template<typename T, uint64_t M, uint64_t N, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,M>, Encoding> multiply(const data<schema::Matrix<T,M,N>, Encoding>& left, const data<schema::Vector<T,N>, Encoding>& right){
data<schema::Vector<T,M>, Encoding> lr;
for(uint64_t i = 0u; i < M; ++i){
for(uint64_t j = 0u; j < N; ++j){
lr.at({{i}}) = lr.at({{i}}) + left.at({{i,j}}) * right.at({{j}});
}
}
return lr;
}
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,3u>, Encoding> cross(
const data<schema::Vector<T,3u>, Encoding> lh,
const data<schema::Vector<T,3u>, Encoding> rh
){
data<schema::Vector<T,3u>, Encoding> cross_prod;
cross_prod.at({{0u}}) = lh.at({{1u}}) * rh.at({{2u}}) - lh.at({{2u}}) * rh.at({{1u}});
cross_prod.at({{1u}}) = lh.at({{2u}}) * rh.at({{0u}}) - lh.at({{0u}}) * rh.at({{2u}});
cross_prod.at({{2u}}) = lh.at({{0u}}) * rh.at({{1u}}) - lh.at({{1u}}) * rh.at({{0u}});
return cross_prod;
}
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>,Encoding> cross(
const data<schema::Vector<T,2u>, Encoding> lh,
const data<schema::Vector<T,2u>, Encoding> rh
){
data<schema::Scalar<T>, Encoding> cross_prod;
cross_prod.at({}) = lh.at({{0u}}) * rh.at({{1u}}) - lh.at({{1u}}) * rh.at({{0u}});
return cross_prod;
}
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,2u>,Encoding> cross(
const data<schema::Scalar<T>, Encoding> lh,
const data<schema::Vector<T,2u>, Encoding> rh
){
data<schema::Vector<T,2u>, Encoding> cross_prod;
cross_prod.at({{0u}}) = lh.at({}) * rh.at({{1u}}) * -1;
cross_prod.at({{1u}}) = lh.at({}) * rh.at({{0u}});
return cross_prod;
}
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>,Encoding> cos(
const data<schema::Scalar<T>,Encoding>& val
){
data<schema::Scalar<T>,Encoding> ret;
ret.at({}).set(std::cos(val.at({}).get()));
return ret;
}
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>,Encoding> sin(
const data<schema::Scalar<T>,Encoding>& val
){
data<schema::Scalar<T>,Encoding> ret;
ret.at({}).set(std::sin(val.at({}).get()));
return ret;
}
/**
* Angle of a 2d vector measured counter clockwise from the positive x axis.
* Inverse of unit_vector().
*/
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Scalar<T>,Encoding> angle(
const data<schema::Vector<T,2u>, Encoding>& vec
){
data<schema::Scalar<T>,Encoding> ret;
ret.at({}).set(std::atan2(vec.at({{1u}}).get(), vec.at({{0u}}).get()));
return ret;
}
/**
* Unit length 2d vector pointing along the given angle. Inverse of angle().
*/
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,2u>,Encoding> unit_vector(
const data<schema::Scalar<T>, Encoding>& rot
){
data<schema::Vector<T,2u>,Encoding> ret;
ret.at({{0u}}) = cos<T,Encoding>(rot).at({});
ret.at({{1u}}) = sin<T,Encoding>(rot).at({});
return ret;
}
template<typename T, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,2u>,Encoding> rotate(
const data<schema::Vector<T,2u>, Encoding> vec,
const data<schema::Scalar<T>, Encoding> rot
){
data<schema::Vector<T,2u>, Encoding> rot_vec;
rot_vec.at({{0u}}) = vec.at({{0u}}) * cos(rot).at({});
rot_vec.at({{1u}}) = vec.at({{1u}}) * sin(rot).at({});
return rot_vec;
}
template<typename T, uint64_t D, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
data<schema::Vector<T,D>,Encoding> scale(
const data<schema::Vector<T,D>, Encoding> vec,
const data<schema::Scalar<T>, Encoding> scale
){
data<schema::Vector<T,D>, Encoding> sc_vec;
for(uint64_t i = 0u; i< D; ++i){
sc_vec.at({{i}}) = vec.at({{i}}) * scale.at({});
}
return sc_vec;
}
template<typename T, uint64_t... Ds, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
void fill(
data<schema::Tensor<T,Ds...>, Encoding>& tbf,
const data<T,Encoding>& filler
){
iterator<sizeof...(Ds)>::apply([&](const auto& index){
tbf.at(index) = filler;
}, {}, {{Ds...}});
}
template<typename T, uint64_t... Ds, typename Encoding = FORSTIO_DEFAULT_DATA_ENCODING>
saw::data<schema::Scalar<T>, Encoding> sum(const data<schema::Tensor<T,Ds...>,Encoding>& tens){
saw::data<schema::Scalar<T>, Encoding> s;
iterator<sizeof...(Ds)>::apply([&](const auto& index){
s.at({}) = s.at({}) + tens.at(index);
}, {}, {{Ds...}});
return s;
}
}
}
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