pmlpp/mlpp/lin_alg/mlpp_matrix.h

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#ifndef MLPP_MATRIX_H
#define MLPP_MATRIX_H
#include "core/containers/pool_vector.h"
#include "core/containers/sort_array.h"
#include "core/containers/vector.h"
#include "core/error/error_macros.h"
#include "core/math/vector2i.h"
#include "core/os/memory.h"
#include "core/object/reference.h"
#include "mlpp_vector.h"
// Matrices are stored as rows first
// [x][y]
class MLPPMatrix : public Reference {
GDCLASS(MLPPMatrix, Reference);
public:
double *ptr() {
return _data;
}
const double *ptr() const {
return _data;
}
_FORCE_INLINE_ void add_row(const Vector<double> &p_row) {
if (_size.x == 0) {
_size.x = p_row.size();
}
ERR_FAIL_COND(_size.x != p_row.size());
int ci = data_size();
++_size.y;
_data = (double *)memrealloc(_data, data_size() * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
const double *row_arr = p_row.ptr();
for (int i = 0; i < p_row.size(); ++i) {
_data[ci + i] = row_arr[i];
}
}
_FORCE_INLINE_ void add_row_pool_vector(const PoolRealArray &p_row) {
if (_size.x == 0) {
_size.x = p_row.size();
}
ERR_FAIL_COND(_size.x != p_row.size());
int ci = data_size();
++_size.y;
_data = (double *)memrealloc(_data, data_size() * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
PoolRealArray::Read rread = p_row.read();
const real_t *row_arr = rread.ptr();
for (int i = 0; i < p_row.size(); ++i) {
_data[ci + i] = row_arr[i];
}
}
void remove_row(double p_index) {
ERR_FAIL_INDEX(p_index, _size.y);
--_size.y;
int ds = data_size();
if (ds == 0) {
memfree(_data);
_data = NULL;
return;
}
for (int i = p_index * _size.x; i < ds; ++i) {
_data[i] = _data[i + _size.x];
}
_data = (double *)memrealloc(_data, data_size() * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
}
// Removes the item copying the last value into the position of the one to
// remove. It's generally faster than `remove`.
void remove_unordered(int p_index) {
ERR_FAIL_INDEX(p_index, _size.y);
--_size.y;
int ds = data_size();
if (ds == 0) {
memfree(_data);
_data = NULL;
return;
}
int start_ind = p_index * _size.x;
int end_ind = (p_index + 1) * _size.x;
for (int i = start_ind; i < end_ind; ++i) {
_data[i] = _data[ds + i];
}
_data = (double *)memrealloc(_data, data_size() * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
}
void swap_row(int p_index_1, int p_index_2) {
ERR_FAIL_INDEX(p_index_1, _size.y);
ERR_FAIL_INDEX(p_index_2, _size.y);
int ind1_start = p_index_1 * _size.x;
int ind2_start = p_index_2 * _size.x;
for (int i = 0; i < _size.x; ++i) {
SWAP(_data[ind1_start + i], _data[ind2_start + i]);
}
}
_FORCE_INLINE_ void clear() { resize(Size2i()); }
_FORCE_INLINE_ void reset() {
clear();
if (_data) {
memfree(_data);
_data = NULL;
_size = Vector2i();
}
}
_FORCE_INLINE_ bool empty() const { return data_size() == 0; }
_FORCE_INLINE_ int data_size() const { return _size.x * _size.y; }
_FORCE_INLINE_ Size2i size() const { return _size; }
void resize(const Size2i &p_size) {
_size = p_size;
int ds = data_size();
if (ds == 0) {
memfree(_data);
_data = NULL;
return;
}
_data = (double *)memrealloc(_data, ds * sizeof(double));
CRASH_COND_MSG(!_data, "Out of memory");
}
_FORCE_INLINE_ const double &operator[](int p_index) const {
CRASH_BAD_INDEX(p_index, data_size());
return _data[p_index];
}
_FORCE_INLINE_ double &operator[](int p_index) {
CRASH_BAD_INDEX(p_index, data_size());
return _data[p_index];
}
_FORCE_INLINE_ double get_element(int p_index_x, int p_index_y) const {
ERR_FAIL_INDEX_V(p_index_x, _size.x, 0);
ERR_FAIL_INDEX_V(p_index_y, _size.y, 0);
return _data[p_index_x * p_index_y];
}
_FORCE_INLINE_ double get_element(int p_index_x, int p_index_y) {
ERR_FAIL_INDEX_V(p_index_x, _size.x, 0);
ERR_FAIL_INDEX_V(p_index_y, _size.y, 0);
return _data[p_index_x * p_index_y];
}
_FORCE_INLINE_ real_t get_element_bind(int p_index_x, int p_index_y) const {
ERR_FAIL_INDEX_V(p_index_x, _size.x, 0);
ERR_FAIL_INDEX_V(p_index_y, _size.y, 0);
return static_cast<real_t>(_data[p_index_x * p_index_y]);
}
_FORCE_INLINE_ void set_element(int p_index_x, int p_index_y, double p_val) {
ERR_FAIL_INDEX(p_index_x, _size.x);
ERR_FAIL_INDEX(p_index_y, _size.y);
_data[p_index_x * p_index_y] = p_val;
}
_FORCE_INLINE_ void set_element_bind(int p_index_x, int p_index_y, real_t p_val) {
ERR_FAIL_INDEX(p_index_x, _size.x);
ERR_FAIL_INDEX(p_index_y, _size.y);
_data[p_index_x * p_index_y] = p_val;
}
_FORCE_INLINE_ void set_row_vector(int p_index_y, const Vector<double> &p_row) {
ERR_FAIL_COND(p_row.size() != _size.x);
ERR_FAIL_INDEX(p_index_y, _size.y);
int ind_start = p_index_y * _size.x;
const double *row_ptr = p_row.ptr();
for (int i = 0; i < _size.x; ++i) {
_data[ind_start + i] = row_ptr[i];
}
}
_FORCE_INLINE_ void set_row_pool_vector(int p_index_y, const PoolRealArray &p_row) {
ERR_FAIL_COND(p_row.size() != _size.x);
ERR_FAIL_INDEX(p_index_y, _size.y);
int ind_start = p_index_y * _size.x;
PoolRealArray::Read r = p_row.read();
const real_t *row_ptr = r.ptr();
for (int i = 0; i < _size.x; ++i) {
_data[ind_start + i] = row_ptr[i];
}
}
void fill(double p_val) {
int ds = data_size();
for (int i = 0; i < ds; i++) {
_data[i] = p_val;
}
}
Vector<double> to_flat_vector() const {
Vector<double> ret;
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ret.resize(data_size());
double *w = ret.ptrw();
memcpy(w, _data, sizeof(double) * data_size());
return ret;
}
PoolRealArray to_flat_pool_vector() const {
PoolRealArray pl;
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if (data_size()) {
pl.resize(data_size());
typename PoolRealArray::Write w = pl.write();
real_t *dest = w.ptr();
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for (int i = 0; i < data_size(); ++i) {
dest[i] = static_cast<real_t>(_data[i]);
}
}
return pl;
}
Vector<uint8_t> to_flat_byte_array() const {
Vector<uint8_t> ret;
ret.resize(data_size() * sizeof(double));
uint8_t *w = ret.ptrw();
memcpy(w, _data, sizeof(double) * data_size());
return ret;
}
Ref<MLPPMatrix> duplicate() const {
Ref<MLPPMatrix> ret;
ret.instance();
ret->set_from_mlpp_matrixr(*this);
return ret;
}
_FORCE_INLINE_ void set_from_mlpp_matrixr(const MLPPMatrix &p_from) {
resize(p_from.size());
for (int i = 0; i < p_from.data_size(); i++) {
_data[i] = p_from._data[i];
}
}
_FORCE_INLINE_ void set_from_mlpp_vectors(const Vector<Ref<MLPPVector>> &p_from) {
if (p_from.size() == 0) {
reset();
return;
}
if (!p_from[0].is_valid()) {
reset();
return;
}
resize(Size2i(p_from[0]->size(), p_from.size()));
if (data_size() == 0) {
reset();
return;
}
for (int i = 0; i < p_from.size(); ++i) {
const Ref<MLPPVector> &r = p_from[i];
ERR_CONTINUE(!r.is_valid());
ERR_CONTINUE(r->size() != _size.x);
int start_index = i * _size.x;
const double *from_ptr = r->ptr();
for (int j = 0; j < _size.x; j++) {
_data[start_index + j] = from_ptr[j];
}
}
}
_FORCE_INLINE_ void set_from_mlpp_vectors_array(const Array &p_from) {
if (p_from.size() == 0) {
reset();
return;
}
Ref<MLPPVector> v0 = p_from[0];
if (!v0.is_valid()) {
reset();
return;
}
resize(Size2i(v0->size(), p_from.size()));
if (data_size() == 0) {
reset();
return;
}
for (int i = 0; i < p_from.size(); ++i) {
Ref<MLPPVector> r = p_from[i];
ERR_CONTINUE(!r.is_valid());
ERR_CONTINUE(r->size() != _size.x);
int start_index = i * _size.x;
const double *from_ptr = r->ptr();
for (int j = 0; j < _size.x; j++) {
_data[start_index + j] = from_ptr[j];
}
}
}
_FORCE_INLINE_ void set_from_vectors(const Vector<Vector<double>> &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 (int i = 0; i < p_from.size(); ++i) {
const Vector<double> &r = p_from[i];
ERR_CONTINUE(r.size() != _size.x);
int start_index = i * _size.x;
const double *from_ptr = r.ptr();
for (int j = 0; j < _size.x; j++) {
_data[start_index + j] = from_ptr[j];
}
}
}
_FORCE_INLINE_ void set_from_arrays(const Array &p_from) {
if (p_from.size() == 0) {
reset();
return;
}
PoolRealArray p0arr = p_from[0];
resize(Size2i(p0arr.size(), p_from.size()));
if (data_size() == 0) {
reset();
return;
}
for (int i = 0; i < p_from.size(); ++i) {
PoolRealArray r = p_from[i];
ERR_CONTINUE(r.size() != _size.x);
int start_index = i * _size.x;
PoolRealArray::Read read = r.read();
const real_t *from_ptr = read.ptr();
for (int j = 0; j < _size.x; j++) {
_data[start_index + j] = from_ptr[j];
}
}
}
String to_string();
_FORCE_INLINE_ MLPPMatrix() {
_data = NULL;
}
_FORCE_INLINE_ MLPPMatrix(const MLPPMatrix &p_from) {
_data = NULL;
resize(p_from.size());
for (int i = 0; i < p_from.data_size(); ++i) {
_data[i] = p_from._data[i];
}
}
MLPPMatrix(const Vector<Vector<double>> &p_from) {
_data = NULL;
set_from_vectors(p_from);
}
MLPPMatrix(const Array &p_from) {
_data = NULL;
set_from_arrays(p_from);
}
_FORCE_INLINE_ ~MLPPMatrix() {
if (_data) {
reset();
}
}
// TODO: These are temporary
std::vector<double> to_flat_std_vector() const {
std::vector<double> ret;
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ret.resize(data_size());
double *w = &ret[0];
memcpy(w, _data, sizeof(double) * data_size());
return ret;
}
_FORCE_INLINE_ void set_from_std_vectors(const std::vector<std::vector<double>> &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<double> &r = p_from[i];
ERR_CONTINUE(r.size() != static_cast<uint32_t>(_size.x));
int start_index = i * _size.x;
const double *from_ptr = &r[0];
for (int j = 0; j < _size.x; j++) {
_data[start_index + j] = from_ptr[j];
}
}
}
_FORCE_INLINE_ void set_row_std_vector(int p_index_y, const std::vector<double> &p_row) {
ERR_FAIL_COND(p_row.size() != static_cast<uint32_t>(_size.x));
ERR_FAIL_INDEX(p_index_y, _size.y);
int ind_start = p_index_y * _size.x;
const double *row_ptr = &p_row[0];
for (int i = 0; i < _size.x; ++i) {
_data[ind_start + i] = row_ptr[i];
}
}
MLPPMatrix(const std::vector<std::vector<double>> &p_from) {
_data = NULL;
set_from_std_vectors(p_from);
}
protected:
static void _bind_methods();
protected:
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Size2i _size;
double *_data;
};
#endif