1102 lines
31 KiB
C
1102 lines
31 KiB
C
#include <stdio.h>
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#include <stdlib.h>
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#include "bsp.h"
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#include "Algorithm.h"
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#include "Debug.h"
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#include <stdint.h>
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#include <stdbool.h>
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#include <stdlib.h> // 用于 abs() 函数
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/**
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* @brief 比较两个数组对应位置的绝对值差值，统计满足条件的个数
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*
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* 判断条件：|arr1[i] - zero1| + offset > |arr2[i] - zero2|
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*
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* @param arr1 数组1指针
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* @param arr2 数组2指针
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* @param length 要比较的数组长度（截取值）
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* @param zero1 数组1的零点值
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* @param zero2 数组2的零点值
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* @param offset 补偿值
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* @return int 满足条件的个数
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*
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* @note 如果 length 为0，返回0
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* @note 如果 arr1 或 arr2 为 NULL，返回0
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*/
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int CompareAndCountAbs(const int32_t *arr1, const int32_t *arr2, uint16_t length,
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int32_t zero1, int32_t zero2, int32_t offset)
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{
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// 参数校验
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if (arr1 == NULL || arr2 == NULL || length == 0) {
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return 0;
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}
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int count = 0;
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for (uint16_t i = 0; i < length; i++) {
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// 计算绝对值
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int32_t abs1 = abs(arr1[i] - zero1);
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int32_t abs2 = abs(arr2[i] - zero2);
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// 判断：|arr1[i] - zero1| + offset > |arr2[i] - zero2|
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if (abs1 + offset > abs2) {
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count++;
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}
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}
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return count;
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}
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/**
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* 加强特定区域的平滑处理（使用更小的权重衰减，更平滑的效果）
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*
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* @param arr 待处理的int32_t数组
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* @param size 数组的大小
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* @param windowSize 滑动窗口大小
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* @param enhanceStart 加强区域的起始索引（包含）
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* @param enhanceEnd 加强区域的结束索引（包含）
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* @param enhanceFactor 加强因子（>1表示更强的平滑，建议2-5）
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* @param verbose 是否打印详细调试信息
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* @return 返回修正的次数
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*/
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int weightedMovingAverageWithEnhance(int32_t arr[], int size, int windowSize,
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int enhanceStart, int enhanceEnd,
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double enhanceFactor, int verbose) {
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if (size <= 1 || windowSize < 2) return 0;
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int32_t *temp = (int32_t*)malloc(size * sizeof(int32_t));
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if (temp == NULL) {
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DBG_LOG("内存分配失败！\n");
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return 0;
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}
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int halfWindow = windowSize / 2;
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int fixCount = 0;
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if (verbose) {
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DBG_LOG("加权移动平均平滑 (窗口大小: %d)\n", windowSize);
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DBG_LOG("加强平滑区域: [%d - %d], 加强因子: %.1f\n", enhanceStart, enhanceEnd, enhanceFactor);
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DBG_LOG("========================================\n");
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}
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for (int i = 0; i < size; i++) {
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// 判断是否在加强区域内
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int isEnhanced = (i >= enhanceStart && i <= enhanceEnd);
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// 计算窗口边界
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int start = (i - halfWindow) < 0 ? 0 : (i - halfWindow);
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int end = (i + halfWindow) >= size ? (size - 1) : (i + halfWindow);
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// 计算加权平均值
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double weightedSum = 0;
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double weightSum = 0;
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for (int j = start; j <= end; j++) {
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// 权重：距离越近权重越大
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int distance = abs(j - i);
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double weight = 1.0 / (distance + 1);
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// 如果在加强区域内，且当前点不是中心点，可以调整权重
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if (isEnhanced && j != i) {
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// 加强区域内的参考点权重提高，使平滑效果更强
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weight *= enhanceFactor;
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}
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weightedSum += arr[j] * weight;
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weightSum += weight;
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}
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int newValue = (int)(weightedSum / weightSum + 0.5);
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if (newValue != arr[i]) {
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if (verbose && fixCount < 50) {
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DBG_LOG("位置 [%d]: %d -> %d %s\n", i, arr[i], newValue,
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isEnhanced ? "[加强区域]" : "");
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}
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temp[i] = newValue;
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fixCount++;
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} else {
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temp[i] = arr[i];
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}
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}
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// 写回原数组
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memcpy(arr, temp, size * sizeof(int32_t));
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free(temp);
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if (verbose) {
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DBG_LOG("========================================\n");
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DBG_LOG("共修正 %d 个点（加强区域修正了更多点）\n", fixCount);
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}
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return fixCount;
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}
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int finalCheck(int arr[], int size, int threshold, int verbose) {
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int problemCount = 0;
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if (verbose) {
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DBG_LOG("\n========== 最终检查 ==========\n");
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}
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for (int i = 1; i < size - 1; i++) {
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int diffPrev = abs(arr[i] - arr[i-1]);
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int diffNext = abs(arr[i+1] - arr[i]);
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if (diffPrev > threshold && diffNext > threshold) {
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problemCount++;
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if (verbose) {
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DBG_LOG("警告: 位置 [%d] 仍有突变问题 (前差%d, 后差%d)\n", i, diffPrev, diffNext);
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}
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}
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}
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// 检查首尾
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if (size >= 2) {
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if (abs(arr[0] - arr[1]) > threshold * 2) {
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problemCount++;
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if (verbose) {
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DBG_LOG("警告: 位置 [0] 仍有突变问题 (与第二元素差%d)\n", abs(arr[0] - arr[1]));
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}
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}
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if (abs(arr[size-1] - arr[size-2]) > threshold * 2) {
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problemCount++;
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if (verbose) {
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DBG_LOG("警告: 位置 [%d] 仍有突变问题 (与前元素差%d)\n", size-1, abs(arr[size-1] - arr[size-2]));
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}
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}
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}
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if (verbose) {
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if (problemCount == 0) {
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DBG_LOG("检查通过！没有发现突变点\n");
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} else {
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DBG_LOG("发现 %d 个问题点\n", problemCount);
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}
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DBG_LOG("========================================\n");
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}
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return problemCount;
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}
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/**
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* 使用滑动窗口修正突变值，并打印修改信息
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*
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* @param arr 待处理的int类型数组
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* @param size 数组的大小
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* @param windowSize 滑动窗口大小（建议奇数）
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* @param threshold 突变阈值
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* @return 返回修正的次数
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*/
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int fixWithMedianIterative(int arr[], int size, int windowSize, int threshold, int maxIterations, int verbose) {
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if (arr == NULL || size <= 2 || windowSize < 3) {
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return 0;
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}
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int totalFixCount = 0;
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int iteration = 0;
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int changed = 1;
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int halfWindow = windowSize / 2;
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int *temp = (int*)malloc(size * sizeof(int));
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if (temp == NULL) {
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DBG_LOG("内存分配失败！\n");
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return 0;
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}
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if (verbose) {
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DBG_LOG("========== 开始迭代修正 (中位数窗口) ==========\n");
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DBG_LOG("数组大小: %d, 窗口大小: %d, 阈值: %d, 最大迭代: %d\n",
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size, windowSize, threshold, maxIterations);
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DBG_LOG("========================================\n");
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}
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while (changed && iteration < maxIterations) {
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changed = 0;
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int iterFixCount = 0;
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memcpy(temp, arr, size * sizeof(int));
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if (verbose) {
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DBG_LOG("\n第 %d 次迭代:\n", iteration + 1);
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DBG_LOG("----------------------------------------\n");
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}
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// 处理所有点
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for (int i = 0; i < size; i++) {
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int isAbnormal = 0;
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// 判断是否为异常点
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if (i > 0 && i < size - 1) {
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// 中间点：检查前后突变
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int diffPrev = abs(arr[i] - arr[i-1]);
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int diffNext = abs(arr[i+1] - arr[i]);
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if (diffPrev > threshold && diffNext > threshold) {
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isAbnormal = 1;
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}
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} else if (i == 0 && size >= 2) {
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// 首元素：检查与第二个元素的差异
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if (abs(arr[0] - arr[1]) > threshold * 2) {
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isAbnormal = 1;
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}
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} else if (i == size - 1 && size >= 2) {
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// 尾元素：检查与倒数第二个元素的差异
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if (abs(arr[size-1] - arr[size-2]) > threshold * 2) {
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isAbnormal = 1;
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}
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}
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if (isAbnormal) {
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// 计算窗口边界
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int start = (i - halfWindow) < 0 ? 0 : (i - halfWindow);
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int end = (i + halfWindow) >= size ? (size - 1) : (i + halfWindow);
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// 收集窗口内的值（排除自身）
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int windowActualSize = end - start + 1;
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int *window = (int*)malloc(windowActualSize * sizeof(int));
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if (window == NULL) continue;
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int idx = 0;
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for (int j = start; j <= end; j++) {
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if (j != i) {
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window[idx++] = arr[j];
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}
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}
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int correctedValue;
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if (idx > 0) {
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// 排序找中位数
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for (int m = 0; m < idx - 1; m++) {
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for (int n = 0; n < idx - m - 1; n++) {
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if (window[n] > window[n+1]) {
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int tmp = window[n];
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window[n] = window[n+1];
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window[n+1] = tmp;
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}
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}
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}
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correctedValue = window[idx / 2];
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} else {
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// 没有参考值，使用相邻点平均
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if (i > 0 && i < size - 1) {
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correctedValue = (arr[i-1] + arr[i+1]) / 2;
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} else if (i == 0) {
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correctedValue = arr[1];
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} else {
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correctedValue = arr[size-2];
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}
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}
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if (correctedValue != arr[i]) {
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if (verbose) {
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DBG_LOG("位置 [%d]: %d -> %d (窗口[%d-%d], 中位数:%d)\n",
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i, arr[i], correctedValue, start, end, correctedValue);
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}
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temp[i] = correctedValue;
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iterFixCount++;
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changed = 1;
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}
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free(window);
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}
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}
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if (changed) {
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memcpy(arr, temp, size * sizeof(int));
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totalFixCount += iterFixCount;
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if (verbose) {
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DBG_LOG("本次修正了 %d 个点\n", iterFixCount);
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}
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}
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iteration++;
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}
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free(temp);
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if (verbose) {
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DBG_LOG("========================================\n");
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DBG_LOG("迭代完成！共进行了 %d 次迭代，总修正 %d 个点\n", iteration, totalFixCount);
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DBG_LOG("========================================\n");
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}
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return totalFixCount;
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}
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/*****************************************************************************************
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* 函数名称: check_peaks_valleys_ratio
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* 功能描述: 检查数据的峰值是否大于0，谷值是否小于0（忽略0值）
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* 参 数: data, 数据
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length, 数据长度
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* 返 回 值: 结果返回峰值谷值检查结果结构体
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*****************************************************************************************/
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PeakValleyCheck check_peaks_valleys(int data[], int length) {
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PeakValleyCheck result = {true, true, 0, 0};
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// 如果数据长度小于3，无法形成有效的峰值/谷值
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if (length < 3) {
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return result;
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}
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int i = 0;
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// 跳过开头的0值
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while (i < length && data[i] == 0) {
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i++;
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}
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// 遍历数据点
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while (i < length) {
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// 1. 寻找下一个非零点作为起点
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int start = i;
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while (i < length && data[i] == 0) {
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i++;
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}
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if (i >= length) break;
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// 2. 寻找当前非零段的结束点
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int end = i;
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while (end < length && data[end] != 0) {
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end++;
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}
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end--; // 指向最后一个非零点
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// 3. 在当前非零段中检测峰值和谷值
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for (int j = i; j <= end; j++) {
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// 跳过边界点
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if (j == i || j == end) continue;
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// 检查是否为峰值（大于左右相邻的非零点）
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if (data[j] > data[j-1] && data[j] > data[j+1]) {
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result.peak_count++;
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if (data[j] <= 0) {
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result.peaks_positive = false;
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}
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}
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// 检查是否为谷值（小于左右相邻的非零点）
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if (data[j] < data[j-1] && data[j] < data[j+1]) {
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result.valley_count++;
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if (data[j] >= 0) {
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result.valleys_negative = false;
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}
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}
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}
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// 移动到下一段
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i = end + 1;
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}
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return result;
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}
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/*****************************************************************************************
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* 函数名称: analyze_trend
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* 功能描述: 趋势分析函数
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* 参 数: data, 数据
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length, 数据长度
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* 返 回 值: 结果返回趋势分析结构体
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*****************************************************************************************/
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TrendResult analyze_trend(int data[], int length) {
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TrendResult result = {0};
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#if 1
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// 0. 检查有效数据长度
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if (length < 2) {
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DBG_LOG("Data deficient\r\n");
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return result;
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}
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// 1. 计算线性回归斜率
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double sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0;
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for (int i = 0; i < length; i++) {
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double x = i; // 时间序列 (0,1,2,...)
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double y = data[i];
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sum_x += x;
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sum_y += y;
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sum_xy += x * y;
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sum_x2 += x * x;
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}
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double numerator = length * sum_xy - sum_x * sum_y;
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double denominator = length * sum_x2 - sum_x * sum_x;
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// 处理分母为零的情况
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if (fabs(denominator) > 1e-10) {
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result.slope = numerator / denominator;
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}
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#endif
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#if 0
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// 2. 计算振荡特征（差分符号变化次数）
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int sign_changes = 0;
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int prev_sign = 0; // 0=未初始化, 1=正, -1=负
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for (int i = 1; i < length; i++) {
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int diff = data[i] - data[i-1];
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int curr_sign = (diff > 0) ? 1 : (diff < 0) ? -1 : 0;
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if (curr_sign != 0) {
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if (prev_sign != 0 && curr_sign != prev_sign) {
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sign_changes++;
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}
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prev_sign = curr_sign;
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}
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}
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result.sign_changes = sign_changes;
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#endif
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#if 0
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// 3. 动态计算阈值（基于数据长度）
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int oscillation_threshold = (int)(0.4 * (length - 1)); // 40%的变化率
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double slope_threshold = 0.05 * (length / 20.0); // 长度标准化
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#endif
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#if 0
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// 4. 趋势判断
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if (sign_changes >= oscillation_threshold) {
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//DBG_LOG("Oscillating trend\r\n");//振荡趋势
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result.trend_type = 0;
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} else if (fabs(result.slope) < slope_threshold) {
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//DBG_LOG("Smooth trend\r\n");//平稳趋势
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result.trend_type = 1;
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} else if (result.slope > 0) {
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//DBG_LOG("Up trend\r\n");//上升趋势
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result.trend_type = 2;
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} else {
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//DBG_LOG("Down trend\r\n");//下降趋势
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result.trend_type = 3;
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}
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#endif
|
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#if 0
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// 5. 陡峭判断
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double abs_slope = fabs(result.slope);
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||
if (abs_slope > 0.8) {
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//DBG_LOG("Steeply");//陡峭
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result.sign_changes = 0;
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} else if (abs_slope > 0.3) {
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//DBG_LOG("Obvious");//明显
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result.sign_changes = 1;
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||
} else if (abs_slope > 0.1) {
|
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//DBG_LOG("Mild");//温和
|
||
result.sign_changes = 2;
|
||
} else {
|
||
//DBG_LOG("gentle");//平缓
|
||
result.sign_changes = 3;
|
||
}
|
||
#endif
|
||
return result;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: calculateAverage
|
||
* 功能描述: 计算平均值
|
||
* 参 数: arr, 数据
|
||
size, 数据长度
|
||
* 返 回 值: 结果返回 long long 防溢出
|
||
*****************************************************************************************/
|
||
float calculateAverage(int *arr, int size)
|
||
{
|
||
int sum = 0;
|
||
for (int i = 0; i < size; i++) {
|
||
sum += arr[i]; // 累加数组中的每个元素
|
||
}
|
||
return (float)sum / size; // 返回平均值
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: slope
|
||
* 功能描述: 计算斜率
|
||
* 参 数: x_data, x轴数据
|
||
y_data, y轴数据
|
||
* 返 回 值: 结果返回 long long 防溢出
|
||
*****************************************************************************************/
|
||
double slope(int32_t *x_data, int32_t *y_data, int n)
|
||
{
|
||
double sum_x = 0, sum_y = 0, sum_xx = 0, sum_xy = 0;
|
||
for (int i = 0; i < n; i++) {
|
||
sum_x += x_data[i];
|
||
sum_y += y_data[i];
|
||
sum_xx += pow(x_data[i] - calculateAverage(x_data, n), 2);
|
||
sum_xy += (x_data[i] - calculateAverage(x_data, n)) * (y_data[i] - calculateAverage(y_data, n));
|
||
}
|
||
|
||
return sum_xy / sum_xx;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: power
|
||
* 功能描述: 快速幂算法
|
||
* 参 数: base, 滤波数据
|
||
exponent, 滤波数据长度
|
||
* 返 回 值: 结果返回 long long 防溢出
|
||
*****************************************************************************************/
|
||
long long power(int base, unsigned int exponent) {
|
||
long long result = 1;
|
||
while (exponent > 0) {
|
||
if (exponent % 2 == 1) {
|
||
result *= base; // 指数为奇数时累乘
|
||
}
|
||
base *= base; // 底数平方
|
||
exponent /= 2; // 指数折半
|
||
}
|
||
return result;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: IntFilter_16t
|
||
* 功能描述: 16位数据中值滤波函数
|
||
* 参 数: Data, 滤波数据
|
||
Cnt, 滤波数据长度
|
||
FilterCnt, 滤除的数据长度，必须为2的倍数
|
||
* 返 回 值: 滤波后的16位数据
|
||
*****************************************************************************************/
|
||
int IntFilter_16t(int16_t *Data, uint8_t Cnt, uint8_t FilterCnt)
|
||
{
|
||
int32_t sum = 0;
|
||
int32_t temp;
|
||
|
||
if(Cnt < 2)
|
||
return *Data;
|
||
|
||
for(int j=0; j<Cnt-1; j++) {
|
||
for(int i=0; i<Cnt-j-1; i++) {
|
||
if(Data[i] > Data[i+1]) {
|
||
temp = Data[i];
|
||
Data[i] = Data[i+1];
|
||
Data[i+1] = temp;
|
||
}
|
||
}
|
||
}
|
||
|
||
for(int count = FilterCnt / 2; count < Cnt - FilterCnt / 2; count++)
|
||
sum += Data[count];
|
||
return (sum / (Cnt - FilterCnt));
|
||
}
|
||
|
||
/*****************************************************************************************
|
||
* 函数名称: IntFilter_32t
|
||
* 功能描述: 32位数据中值滤波函数
|
||
* 参 数: Data, 滤波数据
|
||
Cnt, 滤波数据长度
|
||
FilterCnt, 滤除的数据长度，必须为2的倍数
|
||
* 返 回 值: 滤波后的32位数据
|
||
*****************************************************************************************/
|
||
int IntFilter_32t(int32_t *Data, uint8_t Cnt, uint8_t FilterCnt)
|
||
{
|
||
int32_t sum = 0;
|
||
int32_t temp;
|
||
|
||
if(Cnt < 2)
|
||
return *Data;
|
||
|
||
for(int j=0; j<Cnt-1; j++) {
|
||
for(int i=0; i<Cnt-j-1; i++) {
|
||
if(Data[i] > Data[i+1]) {
|
||
temp = Data[i];
|
||
Data[i] = Data[i+1];
|
||
Data[i+1] = temp;
|
||
}
|
||
}
|
||
}
|
||
|
||
for(int count = FilterCnt / 2; count < Cnt - FilterCnt / 2; count++)
|
||
sum += Data[count];
|
||
return (sum / (Cnt - FilterCnt));
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: IntFilter_u32t
|
||
* 功能描述: 32位无符号位数据中值滤波函数
|
||
* 参 数: Data, 滤波数据
|
||
Cnt, 滤波数据长度
|
||
FilterCnt, 滤除的数据长度，必须为2的倍数
|
||
* 返 回 值: 滤波后的32位数据
|
||
*****************************************************************************************/
|
||
uint32_t IntFilter_u32t(uint32_t *Data, uint8_t Cnt, uint8_t FilterCnt)
|
||
{
|
||
uint32_t sum = 0;
|
||
uint32_t temp;
|
||
|
||
if(Cnt < 2)
|
||
return *Data;
|
||
|
||
for(int j=0; j<Cnt-1; j++) {
|
||
for(int i=0; i<Cnt-j-1; i++) {
|
||
if(Data[i] > Data[i+1]) {
|
||
temp = Data[i];
|
||
Data[i] = Data[i+1];
|
||
Data[i+1] = temp;
|
||
}
|
||
}
|
||
}
|
||
|
||
for(int count = FilterCnt / 2; count < Cnt - FilterCnt / 2; count++)
|
||
sum += Data[count];
|
||
return (sum / (Cnt - FilterCnt));
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: IntFilter_Float
|
||
* 功能描述: 32位浮点数数据中值滤波函数
|
||
* 参 数: Data, 滤波数据
|
||
Cnt, 滤波数据长度
|
||
FilterCnt, 滤除的数据长度，必须为2的倍数
|
||
* 返 回 值: 滤波后的32位数据
|
||
*****************************************************************************************/
|
||
float IntFilter_Float(float *Data, uint8_t Cnt, uint8_t FilterCnt)
|
||
{
|
||
float sum = 0;
|
||
float temp;
|
||
|
||
if(Cnt < 2)
|
||
return *Data;
|
||
|
||
for(int j=0; j<Cnt-1; j++) {
|
||
for(int i=0; i<Cnt-j-1; i++) {
|
||
if(Data[i] > Data[i+1]) {
|
||
temp = Data[i];
|
||
Data[i] = Data[i+1];
|
||
Data[i+1] = temp;
|
||
}
|
||
}
|
||
}
|
||
|
||
for(int count = FilterCnt / 2; count < Cnt - FilterCnt / 2; count++)
|
||
sum += Data[count];
|
||
return (sum / (Cnt - FilterCnt));
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: AverageFilter_u32t
|
||
* 功能描述: 32位数据均值滤波函数,去除了最大值和最小值
|
||
* 参 数: Data, 滤波数据
|
||
Cnt, 滤波数据长度
|
||
* 返 回 值: 滤波后的32位数据
|
||
*****************************************************************************************/
|
||
uint32_t AverageFilter_u32t(uint32_t *Data, uint8_t Cnt)
|
||
{
|
||
uint32_t sum = 0;
|
||
uint32_t temp;
|
||
uint32_t max = Data[0];
|
||
uint32_t min = Data[0];
|
||
|
||
if(Cnt == 0)
|
||
return 0;
|
||
|
||
if(Cnt == 1)
|
||
return Data[0];
|
||
|
||
if(Cnt == 2)
|
||
{
|
||
sum = Data[0] + Data[1];
|
||
return sum / 2;
|
||
}
|
||
|
||
for (uint8_t i = 0; i < Cnt; i++)//找出最大值
|
||
{
|
||
if (Data[i] > max)
|
||
{
|
||
max = Data[i];
|
||
}
|
||
}
|
||
|
||
for (uint8_t i = 0; i < Cnt; i++)//找出最小值
|
||
{
|
||
if (Data[i] < min)
|
||
{
|
||
min = Data[i];
|
||
}
|
||
}
|
||
|
||
for(int i = 0; i < Cnt; i++){//求和
|
||
sum += Data[i];
|
||
}
|
||
|
||
return (sum - max - min) / (Cnt - 2);
|
||
}
|
||
|
||
/*****************************************************************************************
|
||
* 函数名称: AverageFilter_32t
|
||
* 功能描述: 32位数据均值滤波函数,去除了最大值和最小值
|
||
* 参 数: Data, 滤波数据
|
||
Cnt, 滤波数据长度
|
||
* 返 回 值: 滤波后的32位数据
|
||
*****************************************************************************************/
|
||
int AverageFilter_32t(int32_t *Data, uint8_t Cnt)
|
||
{
|
||
int32_t sum = 0;
|
||
int32_t max = Data[0];
|
||
int32_t min = Data[0];
|
||
|
||
if(Cnt == 0)
|
||
return 0;
|
||
|
||
if(Cnt == 1)
|
||
return Data[0];
|
||
|
||
if(Cnt == 2)
|
||
{
|
||
sum = Data[0] + Data[1];
|
||
return sum / 2;
|
||
}
|
||
|
||
for (uint8_t i = 0; i < Cnt; i++)//找出最大值
|
||
{
|
||
if (Data[i] > max)
|
||
{
|
||
max = Data[i];
|
||
}
|
||
}
|
||
|
||
for (uint8_t i = 0; i < Cnt; i++)//找出最小值
|
||
{
|
||
if (Data[i] < min)
|
||
{
|
||
min = Data[i];
|
||
}
|
||
}
|
||
|
||
for(int i = 0; i < Cnt; i++){//求和
|
||
sum += Data[i];
|
||
}
|
||
|
||
return (sum - max - min) / (Cnt - 2);
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: Fitting_Polynomial
|
||
* 功能描述: 根据数组AD[], Actual[]列出的一组数据，用最小二乘法求它的拟合曲线,默认3阶
|
||
近似解析表达式为y = a3*x^3 + a2*x^2 + a1*x + a0;
|
||
* 参 数: AD, AD芯片采样值
|
||
Actual, 实际标校值
|
||
Cnt, 拟合数据个数
|
||
* 返 回 值: 无
|
||
*****************************************************************************************/
|
||
void Fitting_Polynomial(double *AD, double *Actual, uint8_t Cnt)
|
||
{
|
||
static const uint8_t rank_ = 3;//拟合阶数3
|
||
double atemp[2 * (rank_ + 1)], b[rank_ + 1], a[rank_ + 1][rank_ + 1];
|
||
int i, j, k;
|
||
|
||
for(i = 0; i < Cnt; i++){
|
||
atemp[1] += AD[i];
|
||
atemp[2] += pow(AD[i], 2);
|
||
atemp[3] += pow(AD[i], 3);
|
||
atemp[4] += pow(AD[i], 4);
|
||
atemp[5] += pow(AD[i], 5);
|
||
atemp[6] += pow(AD[i], 6);
|
||
b[0] += Actual[i];
|
||
b[1] += AD[i] * Actual[i];
|
||
b[2] += pow(AD[i], 2) * Actual[i];
|
||
b[3] += pow(AD[i], 3) * Actual[i];
|
||
}
|
||
|
||
atemp[0] = Cnt;
|
||
|
||
for(i = 0; i < rank_ + 1; i++){ //构建线性方程组系数矩阵，b[]不变
|
||
k = i;
|
||
for(j = 0; j < rank_ + 1; j++) a[i][j] = atemp[k++];
|
||
}
|
||
|
||
//以下为高斯列主元消去法解线性方程组
|
||
for(k = 0; k < rank_ + 1 - 1; k++){ //n - 1列
|
||
int column = k;
|
||
double mainelement = a[k][k];
|
||
|
||
for(i = k; i < rank_ + 1; i++) //找主元素
|
||
if(fabs(a[i][k]) > mainelement){
|
||
mainelement = fabs(a[i][k]);
|
||
column = i;
|
||
}
|
||
for(j = k; j < rank_ + 1; j++){ //交换两行
|
||
double atemp = a[k][j];
|
||
a[k][j] = a[column][j];
|
||
a[column][j] = atemp;
|
||
}
|
||
double btemp = b[k];
|
||
b[k] = b[column];
|
||
b[column] = btemp;
|
||
|
||
for(i = k + 1; i < rank_ + 1; i++){ //消元过程
|
||
double Mik = a[i][k] / a[k][k];
|
||
for(j = k; j < rank_ + 1; j++) a[i][j] -= Mik * a[k][j];
|
||
b[i] -= Mik * b[k];
|
||
}
|
||
}
|
||
|
||
b[rank_ + 1 - 1] /= a[rank_ + 1 - 1][rank_ + 1 - 1]; //回代过程
|
||
for(i = rank_ + 1 - 2; i >= 0; i--){
|
||
double sum = 0;
|
||
for(j = i + 1; j < rank_ + 1; j++) sum += a[i][j] * b[j];
|
||
b[i] = (b[i] - sum) / a[i][i];
|
||
}//高斯列主元消去法结束
|
||
|
||
DBG_LOG("P(x) = %.16fx^3%+.16fx^2%+.16fx%+.16f\r\n", b[3], b[2], b[1], b[0]);
|
||
|
||
// App.Para.Cali.FitCoef[0] = b[0];
|
||
// App.Para.Cali.FitCoef[1] = b[1];
|
||
// App.Para.Cali.FitCoef[2] = b[2];
|
||
// App.Para.Cali.FitCoef[3] = b[3];
|
||
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: get_K
|
||
* 功能描述: 斜率计算
|
||
* 参 数: count，数据个数 数组行(列)的个数 数组的行列数目相等
|
||
dataCol_X[count]，数据的列数据
|
||
dataRow_Y[count]，数据的行数据
|
||
* 返 回 值: k 斜率
|
||
*****************************************************************************************/
|
||
float get_K(uint8_t count , int32_t *dataCol_X, int32_t *dataRow_Y)
|
||
{
|
||
float k = 0;//斜率
|
||
float aveCol_X = 0;//列的平均值x
|
||
float aveRow_Y = 0;//行的平均值y
|
||
int32_t sum_XY = 0;//行列的总和xy
|
||
int32_t sumRow_Y = 0;//行的总和y
|
||
int32_t sumCol_X = 0;//列的总和x
|
||
int32_t sumCol_X2 = 0;//列的总和x^2
|
||
|
||
for(uint16_t i = 0 ; i < count ; i++)
|
||
{
|
||
sumCol_X += dataCol_X[i];//求列x的总和
|
||
sumRow_Y += dataRow_Y[i];//求行y的总和
|
||
sumCol_X2 += dataCol_X[i] * dataCol_X[i];//求x^2的总和
|
||
sum_XY += (dataCol_X[i] * dataRow_Y[i]);//求xy的总和
|
||
}
|
||
|
||
aveCol_X = 1.0 * sumCol_X / count;//求平均值
|
||
aveRow_Y = 1.0 * sumRow_Y / count;
|
||
|
||
k = (sum_XY - aveCol_X * aveRow_Y * count) / //根据公式求斜率
|
||
(sumCol_X2 - aveCol_X * aveCol_X * count);
|
||
|
||
return k;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: TrendAnalyse
|
||
* 功能描述: 判断数组中的值的总体趋势
|
||
* 参 数: Data,
|
||
Cnt,
|
||
VPT,
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
int8_t TrendAnalyse(int32_t *Data, uint8_t Cnt, int32_t VPT)
|
||
{
|
||
int8_t zero = 0,plus = 0, minus = 0, Trend = 0xEE;
|
||
|
||
if(Cnt < 2)
|
||
return Trend;
|
||
|
||
for(uint8_t i = 1; i < Cnt; i++)
|
||
{
|
||
if((Data[i] - Data[i - 1]) <= VPT && ((Data[i] - Data[i - 1]) >= (-VPT)))
|
||
{
|
||
zero++;
|
||
}
|
||
else if((Data[i] - Data[i - 1]) > VPT)
|
||
{
|
||
plus++;
|
||
}
|
||
else if((Data[i] - Data[i - 1]) < VPT)
|
||
{
|
||
minus++;
|
||
}
|
||
}
|
||
if(zero > (Cnt-(Cnt / 5)))
|
||
Trend = 0;//振荡趋势
|
||
else if(plus > (Cnt-(Cnt/ 5)))
|
||
Trend = 1;//上升趋势
|
||
else if(minus > (Cnt-(Cnt/ 5)))
|
||
Trend = -1;//下降趋势
|
||
|
||
return Trend;//总趋势
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: Waveform_Up
|
||
* 功能描述: 找出一段波形的波峰值
|
||
dCnt, 波形数据长度
|
||
pCnt, 要查找波峰数
|
||
vlue, 返回的波峰值
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
void Waveform_Up(int32_t *Data, uint8_t dCnt, uint8_t pCnt, int32_t *vlue)
|
||
{
|
||
uint8_t peak[pCnt];
|
||
for(uint8_t i = 0, j = 0; i < dCnt; i++)//找出峰值地址
|
||
{
|
||
if(Data[i] < Data[i + 1] && Data[i + 1] > Data[i + 2])
|
||
{
|
||
peak[j++] = i;
|
||
}
|
||
if(j == pCnt)
|
||
break;
|
||
}
|
||
for(uint8_t i = 0; i < pCnt; i++)
|
||
{
|
||
vlue[i] = Data[peak[i]];
|
||
}
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: Waveform_Down
|
||
* 功能描述: 找出一段波形的波谷值
|
||
dCnt, 波形数据长度
|
||
pCnt, 要查找波谷数
|
||
vlue, 返回的波谷值
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
void Waveform_Down(int32_t *Data, uint8_t dCnt, uint8_t pCnt, int32_t *vlue)
|
||
{
|
||
uint8_t peak[pCnt];
|
||
for(uint8_t i = 0, j = 0; i < dCnt; i++)//找出峰值地址
|
||
{
|
||
if(Data[i] > Data[i + 1] && Data[i + 1] < Data[i + 2])
|
||
{
|
||
peak[j++] = i;
|
||
}
|
||
if(j == pCnt)
|
||
break;
|
||
}
|
||
for(uint8_t i = 0; i < pCnt; i++)
|
||
{
|
||
vlue[i] = Data[peak[i]];
|
||
}
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: count_most_greater
|
||
* 功能描述: 判断数组中的值是否大部分大于 target
|
||
* 参 数: arr,
|
||
size,
|
||
target,
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
bool count_most_greater(int32_t *arr, uint8_t size, int32_t target)
|
||
{
|
||
uint8_t cnt = 0;
|
||
for (int i = 0; i < size; i++) {
|
||
if (arr[i] < target)
|
||
cnt++;
|
||
if(cnt > (size - (size / 5)))
|
||
return false;
|
||
}
|
||
return true;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: count_greater
|
||
* 功能描述: 判断数组中的值是否全部大于 target
|
||
* 参 数: arr,
|
||
size,
|
||
target,
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
bool count_greater(int32_t *arr, uint8_t size, int32_t target)
|
||
{
|
||
for (int i = 0; i < size; i++) {
|
||
if (arr[i] < target)
|
||
return false;
|
||
}
|
||
return true;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: count_smaller
|
||
* 功能描述: 判断数组中的值是否全部小于 target
|
||
* 参 数: arr,
|
||
size,
|
||
target,
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
bool count_smaller(int32_t *arr, uint8_t size, int32_t target)
|
||
{
|
||
for (int i = 0; i < size; i++) {
|
||
if (arr[i] > target)
|
||
return false;
|
||
}
|
||
return true;
|
||
}
|
||
|
||
/*****************************************************************************************
|
||
* 函数名称: CRC_Modbus
|
||
* 功能描述: CRC16计算函数
|
||
* 参 数: wBase, 多项式
|
||
Para，校验数据入口
|
||
Data, 校验数据长度入口
|
||
* 返 回 值: crc16校验值
|
||
*****************************************************************************************/
|
||
uint16_t CRC_Modbus(uint16_t wBase, uint8_t *para, uint16_t length)
|
||
{
|
||
uint16_t crc = 0xffff;
|
||
|
||
uint16_t index,i;
|
||
|
||
for(index = 0 ; index < length;index++) {
|
||
crc ^= para[index];
|
||
for(i = 0; i < 8; i++) {
|
||
if(crc & 1) {
|
||
crc >>= 1;
|
||
crc ^= wBase;
|
||
}
|
||
else
|
||
crc >>= 1;
|
||
}
|
||
}
|
||
return crc;
|
||
}
|
||
|
||
/*****************************************************************************************
|
||
* 函数名称: CRC_Sum
|
||
* 功能描述: 从第二个字节开始，求和取反
|
||
* 参 数: _pbuff，校验数据入口
|
||
_cmdLen，校验数据长度入口
|
||
* 返 回 值: cmd_sum，校验值(一个字节)
|
||
*****************************************************************************************/
|
||
uint8_t CRC_Sum(uint8_t *_pbuff, uint16_t _cmdLen)
|
||
{
|
||
uint8_t cmd_sum=0;
|
||
uint16_t i;
|
||
|
||
for(i=1;i<_cmdLen;i++)//从1开始，跳过第一个字节
|
||
{
|
||
cmd_sum += _pbuff[i];
|
||
}
|
||
cmd_sum = (~cmd_sum);
|
||
|
||
return cmd_sum;
|
||
}
|
||
/*****************************************************************************************
|
||
* 函数名称: isAllZero
|
||
* 功能描述: 判断一个数组的值是否全部为0
|
||
* 参 数: arr，数组
|
||
size，长度
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
bool isAllZero(uint8_t *arr, int size)
|
||
{
|
||
for (int i = 0; i < size; i++) {
|
||
if (arr[i] != 0) {
|
||
return false; // 如果数组中有一个元素不为0，则返回false
|
||
}
|
||
}
|
||
return true; // 遍历完数组后，若所有元素都为0，则返回true
|
||
}
|
||
|
||
/*****************************************************************************************
|
||
* 函数名称: HexToAscii
|
||
* 功能描述: 16进制转ASCII码
|
||
* 参 数: HexData，16进制数组
|
||
ASCData，ASCII码
|
||
sLen，数据长度
|
||
* 返 回 值: true或false
|
||
*****************************************************************************************/
|
||
void HexToAscii(uint8_t *HexData, char *ASCData, uint8_t sLen)
|
||
{
|
||
uint8_t temp;
|
||
|
||
for(int i = 0; i < sLen; i++) {
|
||
temp = (HexData[i] >> 4) & 0x0f;
|
||
if(temp < 10)
|
||
temp += '0';
|
||
else
|
||
temp = (temp - 10) + 'A';
|
||
|
||
ASCData[i * 2] = temp;
|
||
|
||
temp = HexData[i] & 0x0f;
|
||
if(temp < 10)
|
||
temp += '0';
|
||
else
|
||
temp = (temp - 10) + 'A';
|
||
|
||
ASCData[i * 2 + 1] = temp;
|
||
}
|
||
ASCData[sLen * 2] = '\r';
|
||
ASCData[sLen * 2 + 1] = '\n';
|
||
ASCData[sLen * 2 + 2] = 0;
|
||
}
|
||
|
||
|