114 lines
4.3 KiB
C++
114 lines
4.3 KiB
C++
/********************************************************
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* ██████╗ ██████╗████████╗██╗
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* ██╔════╝ ██╔════╝╚══██╔══╝██║
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* ██║ ███╗██║ ██║ ██║
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* ██║ ██║██║ ██║ ██║
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* ╚██████╔╝╚██████╗ ██║ ███████╗
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* ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝
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* Geophysical Computational Tools & Library (GCTL)
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*
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* Copyright (c) 2023 Yi Zhang (yizhang-geo@zju.edu.cn)
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*
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* GCTL is distributed under a dual licensing scheme. You can redistribute
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* it and/or modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation, either version 2
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* of the License, or (at your option) any later version. You should have
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* received a copy of the GNU Lesser General Public License along with this
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* program. If not, see <http://www.gnu.org/licenses/>.
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*
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* If the terms and conditions of the LGPL v.2. would prevent you from using
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* the GCTL, please consider the option to obtain a commercial license for a
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* fee. These licenses are offered by the GCTL's original author. As a rule,
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* licenses are provided "as-is", unlimited in time for a one time fee. Please
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* send corresponding requests to: yizhang-geo@zju.edu.cn. Please do not forget
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* to include some description of your company and the realm of its activities.
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* Also add information on how to contact you by electronic and paper mail.
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******************************************************/
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#ifndef _GCTL_COMMON_GRADIENT_H
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#define _GCTL_COMMON_GRADIENT_H
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#include "lcg.h"
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namespace gctl
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{
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class common_gradient : public lcg_solver
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{
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public:
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common_gradient(); ///< 构造函数
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/**
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* @brief Construct a new common_gradient object
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*
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* @param Ln Number of loss functions
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* @param Mn Number of model parameters
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*/
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common_gradient(size_t Ln, size_t Mn);
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virtual ~common_gradient(); ///< 析构函数
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virtual void LCG_Ax(const array<double> &x, array<double> &ax); ///< 计算Ax
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/**
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* @brief Configure the solver's setups
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*
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* @param para LCG solver parameters
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*/
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void set_solver(const lcg_para ¶);
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/**
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* @brief Set the weights for the loss functions.
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*
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* The number of weights equal to the number of the loss functions.
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* The bigger weights is the calculated gradient is more dependent
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* on the corresponding gradients.
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*/
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void set_weights(const _1d_array &w);
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/**
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* @brief Initialize the common_gradient object
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*
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* @param Ln Number of loss functions
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* @param Mn Number of model parameters
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*/
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void init(size_t Ln, size_t Mn);
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/**
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* @brief Fill the model gradient
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*
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* @param id Loss function index
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* @param fx Objective value
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* @param g Model gradient
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*/
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void fill_model_gradient(size_t id, double fx, const _1d_array &g);
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/**
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* @brief Get the conflict free gradient
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*
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* @param normalized Normalize the output gradient
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* @param fixed_w Fixed weights
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* @return Calculated model gradient
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*/
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const _1d_array &get_common_gradient(bool normalized = true, bool fixed_w = true);
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/**
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* @brief Save the recorded weights.
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*
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* @param file Output file name
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*/
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void save_records(std::string file);
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private:
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bool zero_iter_;
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size_t Ln_, Mn_; // Ln_: loss_func number，Mn_: model number
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_2d_matrix G_; // kernel martix
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_1d_array B_, g_, t_, x_; // variables of the linear system
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_1d_array gm_, w_; // gradient module and functions' weight
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_1d_array fx_, fx0_; // functions' value, initial functions' value
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array<bool> filled_; // new gradient filled for the current round of evaluation
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std::vector<array<double> > rcd_wgts_; // weights records
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std::vector<array<double> > rcd_fxs_; // fx records
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};
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};
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#endif // _GCTL_COMMON_GRADIENT_H
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