Позвоните Юлии СВД из переполнения стека

Я пытаюсь использовать язык Julia из Qt C ++ для получения результата функции SVD:

jl_value_t *array_type = jl_apply_array_type(jl_float64_type, 2);
jl_array_t *x  = jl_alloc_array_2d(array_type, matrixForSvd.rows(), matrixForSvd.cols());

jl_value_t * bol = jl_box_bool(true);

double *p = (double*)jl_array_data(x);

int ndims = jl_array_ndims(x);

size_t size0 = jl_array_dim(x,0);
size_t size1 = jl_array_dim(x,1);

// Fill array with data
for(size_t i=0; i<size1; i++)
for(size_t j=0; j<size0; j++)
p[j + size0*i] = matrixForSvd(j,i);

jl_function_t *func  = jl_get_function(jl_base_module, "svd");
jl_tupletype_t *y = (jl_tupletype_t*)jl_call1(func, (jl_value_t*)x);

Но когда я пытаюсь разобрать y Я получаю много мусора (это нормально) и только U а также V но нет S:

double *res = (double*)jl_array_data(y);

for(int t = 0; t < 50; t++){
cout<<res[t]<<endl;
}

Выход:

6.94448e-310
1.97626e-323
2.7725e-318
9.88131e-324
9.88131e-324
0
-0.404554 //U
-0.914514
-0.914514
0.404554
0
6.94448e-310
6.94448e-310
1.97626e-323
2.7725e-318
9.88131e-324
9.88131e-324
0
-0.576048 //V
0.817416
-0.817416
-0.576048
0
6.94448e-310
6.94448e-310
1.97626e-323
2.7725e-318

Итак, как я могу правильно получить кортеж из функции Джулии, как SVD?

2

Решение

svd.cpp:

#include <julia.h>

#include <iostream>
#include <vector>void print_vector(jl_array_t *vec) {
double *data = (double *) jl_array_data(vec);
size_t n = jl_array_dim(vec, 0);

for(int i = 0; i < n; ++i)
std::cout << data[i] << " ";
std::cout << std::endl;
}

// from column major vector
void print_2d_matrix(jl_array_t *mat) {
double *data = (double *) jl_array_data(mat);
size_t m = jl_array_dim(mat, 0);
size_t n = jl_array_dim(mat, 1);for(int i = 0; i < m; ++i) {
for(int j = 0; j < n; ++j)
std::cout << data[i+j*m] << " ";
std::cout << std::endl;
}
}

int main() {

// matrix represented as a vector in column-major order
std::vector<double> mat = {
1, 0, 0, 0,  0, 0, 0, 2,  0, 3, 0, 0,  0, 0, 0, 0,  2, 0, 0, 0
};

// initialize Julia
jl_init(NULL);

jl_value_t* dims = (jl_value_t *) jl_eval_string("(4, 5)");

// make sure dims isn't cleaned up by the Julia gc till we're done with it.
JL_GC_PUSH(&dims);
// get the svd function
jl_function_t *svd = jl_get_function(jl_base_module, "svd");

// build a wrapper around the std::vector data to pass our matrix
// to the svd function
jl_value_t* array_type = jl_apply_array_type(jl_float64_type, 2);
jl_array_t *jl_mat = jl_ptr_to_array(array_type, mat.data(), dims, 0);
JL_GC_POP();

// call svd
jl_value_t *ret = jl_call1(svd, (jl_value_t*)jl_mat);

// make sure we don't lose our return data
JL_GC_PUSH1(&ret);
jl_array_t *jl_U = (jl_array_t*)(jl_fieldref(ret, 0));
jl_array_t *jl_S = (jl_array_t*)(jl_fieldref(ret, 1));
jl_array_t *jl_V = (jl_array_t*)(jl_fieldref(ret, 2));

std::cout << "M: " << std::endl;
print_2d_matrix(jl_mat);

std::cout << "U: " << std::endl;
print_2d_matrix(jl_U);

std::cout << "S: " << std::endl;
print_vector(jl_S);

std::cout << "V: " << std::endl;
print_2d_matrix(jl_V);

JL_GC_POP();

jl_atexit_hook(0);

return 0;
}

компилировать с:

g++ -std=c++14 -fPIC -I$HOME/local/include/julia svd.cpp -L$HOME/local/lib/julia -ljulia

бежать:

LD_LIBRARY_PATH=$HOME/local/lib/julia JULIA_HOME=$HOME/local/bin ./a.out

выход:

M:
1 0 0 0 2
0 0 3 0 0
0 0 0 0 0
0 2 0 0 0
U:
0 1 0 0
1 0 0 0
0 0 0 -1
0 0 1 0
S:
3 2.23607 2 0
V:
-0 0.447214 -0 0
0 0 1 0
1 0 0 0
-0 0 -0 1
0 0.894427 0 0

Юлия выходной:

               _
_       _ _(_)_     |  A fresh approach to technical computing
(_)     | (_) (_)    |  Documentation: http://docs.julialang.org
_ _   _| |_  __ _   |  Type "?help" for help.
| | | | | | |/ _` |  |
| | |_| | | | (_| |  |  Version 0.4.6 (2016-06-19 17:16 UTC)
_/ |\__'_|_|_|\__'_|  |
|__/                   |  x86_64-redhat-linux

julia> mat = [1 0 0 0 2; 0 0 3 0 0; 0 0 0 0 0; 0 2 0 0 0]
4x5 Array{Int64,2}:
1  0  0  0  2
0  0  3  0  0
0  0  0  0  0
0  2  0  0  0

julia> svd(mat)
(
4x4 Array{Float64,2}:
0.0  1.0  0.0   0.0
1.0  0.0  0.0   0.0
0.0  0.0  0.0  -1.0
0.0  0.0  1.0   0.0,

[3.0,2.23606797749979,2.0,0.0],
5x4 Array{Float64,2}:
-0.0  0.447214  -0.0  0.0
0.0  0.0        1.0  0.0
1.0  0.0        0.0  0.0
-0.0  0.0       -0.0  1.0
0.0  0.894427   0.0  0.0)

julia>
3

Другие решения

https://discourse.julialang.org/t/calling-functions-defined-a-custom-module-when-embeded-in-c/8918/3

Как построить массив измерений массива без jl_eval_string:

jl_value_t *types[] = {(jl_value_t*)jl_long_type, (jl_value_t*)jl_long_type};
jl_tupletype_t *tt = jl_apply_tuple_type_v(types, 2);
typedef struct {
ssize_t a;
ssize_t b;
} ntuple2int;
ntuple2int *tuple = (ntuple2int*)jl_new_struct_uninit(tt);
JL_GC_PUSH1(&tuple);
tuple->a = 3;
tuple->b = 2;
jl_array_t *ary = jl_ptr_to_array(atype, data, (jl_value_t*)tuple, own_buffer);
JL_GC_POP();
0

По вопросам рекламы [email protected]