2024-09-10 15:45:07 +08:00
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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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* ╚═════╝ ╚═════╝ ╚═╝ ╚══════╝
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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_ALGORITHM_FUNC_H
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#define _GCTL_ALGORITHM_FUNC_H
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#include "../core/array.h"
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#include "../core/matrix.h"
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2024-09-13 10:08:41 +08:00
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#include "../maths/mathfunc.h"
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2024-09-10 15:45:07 +08:00
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namespace gctl
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{
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/**
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* @brief 按距离反比加权计算均值
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*
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* @param dis_vec 距离向量
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* @param val_vec 数值向量
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* @param[in] order 距离加权的阶次 默认为1
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*
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* @return 加权平均值
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*/
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double dist_inverse_weight(std::vector<double> *dis_vec, std::vector<double> *val_vec, int order = 1);
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/**
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* @brief 查找一个数在已排序的数组中的位置,即找到包含该数的最小区间
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*
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* @param[in] in_array 输入数组
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* @param[in] array_size 数组大小
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* @param[in] in_val 查找值
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* @param index 返回的索引值
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*
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* @return 成功0失败-1
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*/
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int find_index(const double *in_array, int array_size, double in_val, int &index);
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/**
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* @brief 查找一个数在已排序的数组中的位置,即找到包含该数的最小区间
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*
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* @param in_array 输入数组
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* @param[in] in_val 查找值
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* @param index 返回的索引值
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*
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* @return 成功0失败-1
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*/
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int find_index(array<double> *in_array, double in_val, int &index);
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/**
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* @brief 计算一维分形模型
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*
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* @param out_arr 输出数组
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* @param[in] l_val 分形计算的左端点值
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* @param[in] r_val 分形计算的右端点值
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* @param[in] maxi_range 最大变化值
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* @param[in] smoothness 变化光滑度
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*/
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void fractal_model_1d(array<double> &out_arr, int out_size, double l_val,
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double r_val, double maxi_range, double smoothness);
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/**
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* @brief 计算二维分形模型
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*
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* @param out_arr 输出数组
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* @param[in] dl_val 分形计算的左下角端点值
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* @param[in] dr_val 分形计算的右下角端点值
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* @param[in] ul_val 分形计算的左上角端点值
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* @param[in] ur_val 分形计算的右上角端点值
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* @param[in] maxi_range 最大变化值
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* @param[in] smoothness 变化光滑度
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*/
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void fractal_model_2d(_2d_matrix &out_arr, int r_size, int c_size, double dl_val,
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double dr_val, double ul_val, double ur_val, double maxi_range, double smoothness, unsigned int seed = 0);
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/**
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* @brief 一维数组差分(使用二阶差分公式)
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*
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* 计算一个一维数组中相邻元素间的差分结果(求导)。
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*
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* @param[in] in 输入数组
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* @param diff 输出的差分结果
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* @param[in] spacing 相邻元素的距离
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* @param[in] order 求导的次数。最小为1(默认),最大为4。两边的数据将分别使用对应的向前或向后差分公式
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*/
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void difference_1d(const array<double> &in, array<double> &diff, double spacing, int order = 1);
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/**
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* @brief 二维数组差分(使用二阶差分公式)
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*
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* 计算一个二维数组中相邻元素间的差分结果(求导)。
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*
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* @param[in] in 输入数组
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* @param diff 输出的差分结果
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* @param[in] spacing 相邻元素对应方向的距离
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* @param[in] d_type 求导的类型
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* @param[in] order 求导的次数。最小为1(默认),最大为4。边缘的数据将分别使用对应的向前或向后差分公式
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*/
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void difference_2d(const _2d_matrix &in, _2d_matrix &diff, double spacing, gradient_type_e d_type, int order = 1);
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/**
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* @brief 二维数组差分(使用二阶差分公式)
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*
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* 计算一个二维数组中相邻元素间的差分结果(求导)。数组以列优先的方式储存为一个一维数组
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*
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* @param[in] in 输入数组
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* @param diff 输出的差分结果
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* @param[in] row_size 数组二维排列的行数
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* @param[in] col_size 数组二维排列的列数
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* @param[in] spacing 相邻元素对应方向的距离
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* @param[in] d_type 求导的类型
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* @param[in] order 求导的次数。最小为1(默认),最大为4。边缘的数据将分别使用对应的向前或向后差分公式
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*/
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void difference_2d(const array<double> &in, array<double> &diff, int row_size, int col_size,
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double spacing, gradient_type_e d_type, int order = 1);
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}
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#endif // _GCTL_ALGORITHM_FUNC_H
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