#include "mlpp_matrix.h" String MLPPMatrix::to_string() { String str; str += "[MLPPMatrix: \n"; for (int y = 0; y < _size.y; ++y) { str += " [ "; for (int x = 0; x < _size.x; ++x) { str += String::num(_data[_size.x * y + x]); str += " "; } str += "]\n"; } str += "]"; return str; } std::vector MLPPMatrix::to_flat_std_vector() const { std::vector ret; ret.resize(data_size()); real_t *w = &ret[0]; memcpy(w, _data, sizeof(real_t) * data_size()); return ret; } void MLPPMatrix::set_from_std_vectors(const std::vector> &p_from) { if (p_from.size() == 0) { reset(); return; } resize(Size2i(p_from[0].size(), p_from.size())); if (data_size() == 0) { reset(); return; } for (uint32_t i = 0; i < p_from.size(); ++i) { const std::vector &r = p_from[i]; ERR_CONTINUE(r.size() != static_cast(_size.x)); int start_index = i * _size.x; const real_t *from_ptr = &r[0]; for (int j = 0; j < _size.x; j++) { _data[start_index + j] = from_ptr[j]; } } } std::vector> MLPPMatrix::to_std_vector() { std::vector> ret; ret.resize(_size.y); for (int i = 0; i < _size.y; ++i) { std::vector row; for (int j = 0; j < _size.x; ++j) { row.push_back(_data[calculate_index(i, j)]); } ret[i] = row; } return ret; } void MLPPMatrix::set_row_std_vector(int p_index_y, const std::vector &p_row) { ERR_FAIL_COND(p_row.size() != static_cast(_size.x)); ERR_FAIL_INDEX(p_index_y, _size.y); int ind_start = p_index_y * _size.x; const real_t *row_ptr = &p_row[0]; for (int i = 0; i < _size.x; ++i) { _data[ind_start + i] = row_ptr[i]; } } MLPPMatrix::MLPPMatrix(const std::vector> &p_from) { _data = NULL; set_from_std_vectors(p_from); } void MLPPMatrix::_bind_methods() { ClassDB::bind_method(D_METHOD("add_row", "row"), &MLPPMatrix::add_row_pool_vector); ClassDB::bind_method(D_METHOD("add_row_mlpp_vector", "row"), &MLPPMatrix::add_row_mlpp_vector); ClassDB::bind_method(D_METHOD("add_rows_mlpp_matrix", "other"), &MLPPMatrix::add_rows_mlpp_matrix); ClassDB::bind_method(D_METHOD("remove_row", "index"), &MLPPMatrix::remove_row); ClassDB::bind_method(D_METHOD("remove_row_unordered", "index"), &MLPPMatrix::remove_row_unordered); ClassDB::bind_method(D_METHOD("swap_row", "index_1", "index_2"), &MLPPMatrix::swap_row); ClassDB::bind_method(D_METHOD("clear"), &MLPPMatrix::clear); ClassDB::bind_method(D_METHOD("reset"), &MLPPMatrix::reset); ClassDB::bind_method(D_METHOD("empty"), &MLPPMatrix::empty); ClassDB::bind_method(D_METHOD("data_size"), &MLPPMatrix::data_size); ClassDB::bind_method(D_METHOD("size"), &MLPPMatrix::size); ClassDB::bind_method(D_METHOD("resize", "size"), &MLPPMatrix::resize); ClassDB::bind_method(D_METHOD("get_element", "index_x", "index_y"), &MLPPMatrix::get_element_bind); ClassDB::bind_method(D_METHOD("set_element", "index_x", "index_y", "val"), &MLPPMatrix::set_element_bind); ClassDB::bind_method(D_METHOD("get_row_pool_vector", "index_y"), &MLPPMatrix::get_row_pool_vector); ClassDB::bind_method(D_METHOD("get_row_mlpp_vector", "index_y"), &MLPPMatrix::get_row_mlpp_vector); ClassDB::bind_method(D_METHOD("get_row_into_mlpp_vector", "index_y", "target"), &MLPPMatrix::get_row_into_mlpp_vector); ClassDB::bind_method(D_METHOD("set_row_pool_vector", "index_y", "row"), &MLPPMatrix::set_row_pool_vector); ClassDB::bind_method(D_METHOD("set_row_mlpp_vector", "index_y", "row"), &MLPPMatrix::set_row_mlpp_vector); ClassDB::bind_method(D_METHOD("fill", "val"), &MLPPMatrix::fill); ClassDB::bind_method(D_METHOD("to_flat_pool_vector"), &MLPPMatrix::to_flat_pool_vector); ClassDB::bind_method(D_METHOD("to_flat_byte_array"), &MLPPMatrix::to_flat_byte_array); ClassDB::bind_method(D_METHOD("duplicate"), &MLPPMatrix::duplicate); ClassDB::bind_method(D_METHOD("set_from_mlpp_vectors_array", "from"), &MLPPMatrix::set_from_mlpp_vectors_array); ClassDB::bind_method(D_METHOD("set_from_arrays", "from"), &MLPPMatrix::set_from_arrays); ClassDB::bind_method(D_METHOD("set_from_mlpp_matrix", "from"), &MLPPMatrix::set_from_mlpp_matrix); ClassDB::bind_method(D_METHOD("is_equal_approx", "with", "tolerance"), &MLPPMatrix::is_equal_approx, CMP_EPSILON); }