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#include <random> | ||
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template <typename T, typename MAJ> | ||
std::shared_ptr<SparseArray2d<T, MAJ>> SparseArray2d<T, MAJ>::RANDOM(size_t rows, size_t cols, T density, T seed) { | ||
if(density < 0 || density > 1) | ||
throw std::runtime_error("Invalid sparse density, must be between 0 and 1"); | ||
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size_t size = std::floor(rows * cols * density); | ||
auto arr = SSparseArray2d<T, MAJ>::new_ptr(rows, cols, size); | ||
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std::mt19937_64 generator; | ||
if(seed > 0) generator = std::mt19937_64(seed); | ||
else{ | ||
std::random_device r; | ||
std::seed_seq seed_seq{r(), r(), r(), r(), r(), r(), r(), r()}; | ||
generator = std::mt19937_64(seed_seq); | ||
} | ||
std::uniform_real_distribution<T> dist; | ||
auto data = arr->data(); | ||
for (size_t i = 0; i < size; i++) data[i] = dist(generator); | ||
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size_t nnz = size; | ||
std::vector<size_t> nnz_row(rows, 0); | ||
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size_t index = 0; | ||
while (nnz > 0) { | ||
std::uniform_int_distribution<size_t> dist_int(1, 100);//to do 50 50 | ||
if (dist_int(generator) > 50) { | ||
nnz_row[index]++; | ||
nnz--; | ||
} | ||
index++; | ||
if (index >= rows) index = 0; | ||
} | ||
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index = 0; | ||
auto indices = arr->indices(); | ||
for (size_t i : nnz_row) { | ||
std::vector<size_t> indice_comb; | ||
for (size_t j = 0; j < cols; j++) indice_comb.emplace_back(j); | ||
std::shuffle(indice_comb.begin(), indice_comb.end(), generator); | ||
for (size_t j = 0; j < i; j++) { | ||
indices[index++] = indice_comb[j]; | ||
} | ||
} | ||
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// if (index != arr->indices().size() - 1) | ||
// std::runtime_error("Uh something is wrong"); | ||
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auto row_indices = arr->row_indices(); | ||
row_indices[0] = 0; | ||
for (size_t i = 1; i < rows + 1; i++) row_indices[i] = row_indices[i - 1] + nnz_row[i - 1]; | ||
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return arr; | ||
} |
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