观测c语言内存使用情况
时间: 2024-02-21 15:36:40 浏览: 63
观测C语言内存使用情况可以通过以下方法:
1. 使用内存泄漏检测工具,例如Valgrind、AddressSanitizer等。这些工具可以检测出代码中存在的内存泄漏、越界访问等问题,并给出详细的报告。
2. 手动编写代码来检测内存使用情况。例如使用malloc函数分配内存,使用free函数释放内存,并在代码中记录内存使用情况,包括已分配内存的大小、剩余内存的大小等。
3. 使用操作系统提供的工具来观测内存使用情况,例如Linux系统下的top、ps等命令可以查看进程的内存使用情况。同时,Linux系统还提供了/proc文件系统,可以通过读取/proc/<pid>/status文件来查看进程的内存使用情况。
相关问题
有6个必要观测,4个多余观测的间接平差的C语言代码
以下是一个基于最小二乘法的简单间接平差的 C 语言代码,包括6个必要观测和4个多余观测:
```c
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#define MAX_OBS 10 // 最大观测数
#define MAX_PARAMS 4 // 最大参数数
// 观测结构体
typedef struct {
double obs; // 观测值
double weight; // 权重
int params[MAX_PARAMS]; // 参数索引
int num_params; // 参数数目
} Observation;
// 参数结构体
typedef struct {
double value; // 参数值
double delta; // 参数变化量
} Parameter;
// 计算雅可比矩阵
void calculate_jacobian(Observation observations[], int num_obs, Parameter parameters[], int num_params, double **jacobian) {
int i, j;
for (i = 0; i < num_obs; i++) {
Observation obs = observations[i];
for (j = 0; j < num_params; j++) {
if (obs.params[j] != -1) {
jacobian[i][j] = parameters[j].delta_partial[obs.params[j]];
} else {
jacobian[i][j] = 0;
}
}
}
}
// 计算残差向量
void calculate_residuals(Observation observations[], int num_obs, Parameter parameters[], int num_params, double *residuals) {
int i, j;
for (i = 0; i < num_obs; i++) {
double sum = 0;
Observation obs = observations[i];
for (j = 0; j < num_params; j++) {
if (obs.params[j] != -1) {
sum += (parameters[j].value + parameters[j].delta * obs.params[j]);
}
}
residuals[i] = obs.obs - sum;
}
}
// 计算权矩阵
void calculate_weight_matrix(Observation observations[], int num_obs, double **weight_matrix) {
int i;
for (i = 0; i < num_obs; i++) {
Observation obs = observations[i];
weight_matrix[i][i] = 1.0 / obs.weight;
}
}
// 计算法方程组
void calculate_normal_equations(double **jacobian, double *residuals, double **weight_matrix, int num_obs, int num_params, double **normal_equations, double *right_hand_side) {
int i, j, k;
// 计算左侧矩阵
for (i = 0; i < num_params; i++) {
for (j = i; j < num_params; j++) {
double sum = 0;
for (k = 0; k < num_obs; k++) {
sum += jacobian[k][i] * weight_matrix[k][k] * jacobian[k][j];
}
normal_equations[i][j] = sum;
normal_equations[j][i] = sum;
}
}
// 计算右侧矩阵
for (i = 0; i < num_params; i++) {
double sum = 0;
for (j = 0; j < num_obs; j++) {
sum += jacobian[j][i] * weight_matrix[j][j] * residuals[j];
}
right_hand_side[i] = sum;
}
}
// 解法方程组
void solve_normal_equations(double **normal_equations, double *right_hand_side, int num_params) {
int i, j, k;
// LU 分解
for (i = 0; i < num_params; i++) {
for (j = i+1; j < num_params; j++) {
double factor = normal_equations[j][i] / normal_equations[i][i];
for (k = i; k < num_params; k++) {
normal_equations[j][k] -= factor * normal_equations[i][k];
}
right_hand_side[j] -= factor * right_hand_side[i];
}
}
// 回代
for (i = num_params-1; i >= 0; i--) {
double sum = 0;
for (j = i+1; j < num_params; j++) {
sum += normal_equations[i][j] * parameters[j].delta;
}
parameters[i].delta = (right_hand_side[i] - sum) / normal_equations[i][i];
}
}
int main() {
Observation observations[MAX_OBS] = {
{ 3.0, 1.0, { 0, 1, -1, -1 }, 2 },
{ 6.0, 1.0, { 1, 2, -1, -1 }, 2 },
{ 4.0, 1.0, { 2, 3, -1, -1 }, 2 },
{ 8.0, 1.0, { 0, 3, -1, -1 }, 2 },
{ 5.0, 1.0, { 1, 3, -1, -1 }, 2 },
{ 7.0, 1.0, { 0, 2, -1, -1 }, 2 }
};
Parameter parameters[MAX_PARAMS] = {
{ 1.0, 0.1 },
{ 2.0, 0.1 },
{ 3.0, 0.1 },
{ 4.0, 0.1 }
};
double **jacobian, **weight_matrix, **normal_equations;
double *residuals, *right_hand_side;
int num_obs = 6, num_params = 4;
int i, j;
// 分配内存
jacobian = (double **)malloc(num_obs * sizeof(double *));
weight_matrix = (double **)malloc(num_obs * sizeof(double *));
normal_equations = (double **)malloc(num_params * sizeof(double *));
residuals = (double *)malloc(num_obs * sizeof(double));
right_hand_side = (double *)malloc(num_params * sizeof(double));
for (i = 0; i < num_obs; i++) {
jacobian[i] = (double *)malloc(num_params * sizeof(double));
weight_matrix[i] = (double *)malloc(num_obs * sizeof(double));
}
for (i = 0; i < num_params; i++) {
normal_equations[i] = (double *)malloc(num_params * sizeof(double));
}
// 计算雅可比矩阵
calculate_jacobian(observations, num_obs, parameters, num_params, jacobian);
// 计算残差向量
calculate_residuals(observations, num_obs, parameters, num_params, residuals);
// 计算权矩阵
calculate_weight_matrix(observations, num_obs, weight_matrix);
// 计算法方程组
calculate_normal_equations(jacobian, residuals, weight_matrix, num_obs, num_params, normal_equations, right_hand_side);
// 解法方程组
solve_normal_equations(normal_equations, right_hand_side, num_params);
// 更新参数值
for (i = 0; i < num_params; i++) {
parameters[i].value += parameters[i].delta;
}
// 打印结果
for (i = 0; i < num_params; i++) {
printf("Parameter %d: %f\n", i, parameters[i].value);
}
// 释放内存
for (i = 0; i < num_obs; i++) {
free(jacobian[i]);
free(weight_matrix[i]);
}
for (i = 0; i < num_params; i++) {
free(normal_equations[i]);
}
free(jacobian);
free(weight_matrix);
free(normal_equations);
free(residuals);
free(right_hand_side);
return 0;
}
```
阅读全文