mirror of https://github.com/Relintai/pmlpp.git
301 lines
9.1 KiB
C++
301 lines
9.1 KiB
C++
#ifndef MLPP_VECTOR_H
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#define MLPP_VECTOR_H
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/*************************************************************************/
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/* mlpp_vector.h */
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/*************************************************************************/
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/* This file is part of: */
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/* PMLPP Machine Learning Library */
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/* https://github.com/Relintai/pmlpp */
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/*************************************************************************/
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/* Copyright (c) 2023-present Péter Magyar. */
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/* Copyright (c) 2022-2023 Marc Melikyan */
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/* */
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/* Permission is hereby granted, free of charge, to any person obtaining */
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/* a copy of this software and associated documentation files (the */
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/* "Software"), to deal in the Software without restriction, including */
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/* without limitation the rights to use, copy, modify, merge, publish, */
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/* distribute, sublicense, and/or sell copies of the Software, and to */
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/* permit persons to whom the Software is furnished to do so, subject to */
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/* the following conditions: */
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/* */
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/* The above copyright notice and this permission notice shall be */
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/* included in all copies or substantial portions of the Software. */
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/* */
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/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */
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/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */
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/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*/
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/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */
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/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */
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/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */
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/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */
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/*************************************************************************/
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#ifdef USING_SFW
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#include "sfw.h"
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#else
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#include "core/math/math_defs.h"
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#include "core/math/math_funcs.h"
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#include "core/containers/pool_vector.h"
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#include "core/containers/sort_array.h"
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#include "core/containers/vector.h"
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#include "core/error/error_macros.h"
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#include "core/os/memory.h"
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#include "core/object/resource.h"
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#endif
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//REMOVE
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#include <vector>
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class MLPPMatrix;
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class MLPPVector : public Resource {
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GDCLASS(MLPPVector, Resource);
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public:
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PoolRealArray get_data();
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void set_data(const PoolRealArray &p_from);
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_FORCE_INLINE_ real_t *ptrw() {
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return _data;
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}
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_FORCE_INLINE_ const real_t *ptr() const {
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return _data;
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}
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void push_back(real_t p_elem);
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void append_mlpp_vector(const Ref<MLPPVector> &p_other);
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void remove(int p_index);
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// Removes the item copying the last value into the position of the one to
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// remove. It's generally faster than `remove`.
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void remove_unordered(int p_index);
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void erase(const real_t &p_val);
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int erase_multiple_unordered(const real_t &p_val);
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void invert();
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_FORCE_INLINE_ void clear() { resize(0); }
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_FORCE_INLINE_ void reset() {
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if (_data) {
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memfree(_data);
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_data = NULL;
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_size = 0;
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}
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}
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_FORCE_INLINE_ bool empty() const { return _size == 0; }
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_FORCE_INLINE_ int size() const { return _size; }
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void resize(int p_size);
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_FORCE_INLINE_ const real_t &operator[](int p_index) const {
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CRASH_BAD_INDEX(p_index, _size);
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return _data[p_index];
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}
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_FORCE_INLINE_ real_t &operator[](int p_index) {
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CRASH_BAD_INDEX(p_index, _size);
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return _data[p_index];
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}
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_FORCE_INLINE_ real_t element_get(int p_index) const {
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ERR_FAIL_INDEX_V(p_index, _size, 0);
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return _data[p_index];
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}
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_FORCE_INLINE_ void element_set(int p_index, real_t p_val) {
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ERR_FAIL_INDEX(p_index, _size);
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_data[p_index] = p_val;
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}
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_FORCE_INLINE_ const real_t &element_get_ref(int p_index) const {
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CRASH_BAD_INDEX(p_index, _size);
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return _data[p_index];
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}
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_FORCE_INLINE_ real_t &element_get_ref(int p_index) {
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CRASH_BAD_INDEX(p_index, _size);
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return _data[p_index];
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}
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void fill(real_t p_val);
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void insert(int p_pos, real_t p_val);
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int find(const real_t &p_val, int p_from = 0) const;
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template <class C>
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void sort_custom() {
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int len = _size;
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if (len == 0) {
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return;
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}
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SortArray<real_t, C> sorter;
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sorter.sort(_data, len);
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}
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void sort() {
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sort_custom<_DefaultComparator<real_t>>();
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}
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void ordered_insert(real_t p_val);
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Vector<real_t> to_vector() const;
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PoolRealArray to_pool_vector() const;
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Vector<uint8_t> to_byte_array() const;
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Ref<MLPPVector> duplicate_fast() const;
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void set_from_mlpp_vectorr(const MLPPVector &p_from);
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void set_from_mlpp_vector(const Ref<MLPPVector> &p_from);
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void set_from_vector(const Vector<real_t> &p_from);
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void set_from_pool_vector(const PoolRealArray &p_from);
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bool is_equal_approx(const Ref<MLPPVector> &p_with, real_t tolerance = static_cast<real_t>(CMP_EPSILON)) const;
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void flatten_vectors(const Vector<Ref<MLPPVector>> &A);
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Ref<MLPPVector> flatten_vectorsn(const Vector<Ref<MLPPVector>> &A) const;
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void hadamard_product(const Ref<MLPPVector> &b);
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Ref<MLPPVector> hadamard_productn(const Ref<MLPPVector> &b) const;
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void hadamard_productb(const Ref<MLPPVector> &a, const Ref<MLPPVector> &b);
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void division_element_wise(const Ref<MLPPVector> &b);
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Ref<MLPPVector> division_element_wisen(const Ref<MLPPVector> &b) const;
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void division_element_wiseb(const Ref<MLPPVector> &a, const Ref<MLPPVector> &b);
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void scalar_multiply(real_t scalar);
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Ref<MLPPVector> scalar_multiplyn(real_t scalar) const;
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void scalar_multiplyb(real_t scalar, const Ref<MLPPVector> &a);
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void scalar_add(real_t scalar);
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Ref<MLPPVector> scalar_addn(real_t scalar) const;
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void scalar_addb(real_t scalar, const Ref<MLPPVector> &a);
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void add(const Ref<MLPPVector> &b);
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Ref<MLPPVector> addn(const Ref<MLPPVector> &b) const;
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void addb(const Ref<MLPPVector> &a, const Ref<MLPPVector> &b);
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void sub(const Ref<MLPPVector> &b);
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Ref<MLPPVector> subn(const Ref<MLPPVector> &b) const;
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void subb(const Ref<MLPPVector> &a, const Ref<MLPPVector> &b);
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void log();
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Ref<MLPPVector> logn() const;
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void logb(const Ref<MLPPVector> &a);
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void log10();
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Ref<MLPPVector> log10n() const;
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void log10b(const Ref<MLPPVector> &a);
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void exp();
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Ref<MLPPVector> expn() const;
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void expb(const Ref<MLPPVector> &a);
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void erf();
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Ref<MLPPVector> erfn() const;
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void erfb(const Ref<MLPPVector> &a);
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void exponentiate(real_t p);
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Ref<MLPPVector> exponentiaten(real_t p) const;
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void exponentiateb(const Ref<MLPPVector> &a, real_t p);
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void sqrt();
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Ref<MLPPVector> sqrtn() const;
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void sqrtb(const Ref<MLPPVector> &a);
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void cbrt();
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Ref<MLPPVector> cbrtn() const;
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void cbrtb(const Ref<MLPPVector> &a);
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real_t dot(const Ref<MLPPVector> &b) const;
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Ref<MLPPVector> cross(const Ref<MLPPVector> &b);
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void abs();
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Ref<MLPPVector> absn() const;
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void absb(const Ref<MLPPVector> &a);
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Ref<MLPPVector> vecn_zero(int n) const;
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Ref<MLPPVector> vecn_one(int n) const;
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Ref<MLPPVector> vecn_full(int n, int k) const;
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static Ref<MLPPVector> create_vec_zero(int n);
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static Ref<MLPPVector> create_vec_one(int n);
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static Ref<MLPPVector> create_vec_full(int n, int k);
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void sin();
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Ref<MLPPVector> sinn() const;
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void sinb(const Ref<MLPPVector> &a);
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void cos();
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Ref<MLPPVector> cosn() const;
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void cosb(const Ref<MLPPVector> &a);
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void max(const Ref<MLPPVector> &b);
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Ref<MLPPVector> maxn(const Ref<MLPPVector> &b) const;
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void maxb(const Ref<MLPPVector> &a, const Ref<MLPPVector> &b);
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void min(const Ref<MLPPVector> &b);
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Ref<MLPPVector> minn(const Ref<MLPPVector> &b) const;
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void minb(const Ref<MLPPVector> &a, const Ref<MLPPVector> &b);
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real_t max_element() const;
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int max_element_index() const;
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real_t min_element() const;
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int min_element_index() const;
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//std::vector<real_t> round(std::vector<real_t> a);
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real_t euclidean_distance(const Ref<MLPPVector> &b) const;
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real_t euclidean_distance_squared(const Ref<MLPPVector> &b) const;
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real_t norm_2() const;
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real_t norm_sq() const;
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real_t sum_elements() const;
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//real_t cosineSimilarity(std::vector<real_t> a, std::vector<real_t> b);
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void subtract_matrix_rows(const Ref<MLPPMatrix> &B);
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Ref<MLPPVector> subtract_matrix_rowsn(const Ref<MLPPMatrix> &B) const;
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void subtract_matrix_rowsb(const Ref<MLPPVector> &a, const Ref<MLPPMatrix> &B);
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// This multiplies a, bT
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Ref<MLPPMatrix> outer_product(const Ref<MLPPVector> &b) const;
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// as_diagonal_matrix / to_diagonal_matrix
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Ref<MLPPMatrix> diagnm() const;
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String to_string();
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MLPPVector();
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MLPPVector(const MLPPVector &p_from);
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MLPPVector(const Vector<real_t> &p_from);
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MLPPVector(const PoolRealArray &p_from);
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MLPPVector(const real_t *p_from, const int p_size);
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~MLPPVector();
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// TODO: These are temporary
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std::vector<real_t> to_std_vector() const;
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void set_from_std_vector(const std::vector<real_t> &p_from);
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MLPPVector(const std::vector<real_t> &p_from);
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protected:
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static void _bind_methods();
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protected:
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int _size;
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real_t *_data;
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};
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#endif
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