data = load('out3.txt'); N = length(data(:,1)); b = fir1(15, 0.3, chebwin(16, 30)); data_smooth = filtfilt(b, 1, data(:,1)); [IndMin, IndMax] = findExtrema(data_smooth); figure; subplot(2,1,1); plot(data_smooth); hold on; plot(IndMin, data_smooth(IndMin), 'r^'); plot(IndMax, data_smooth(IndMax), 'k*'); box on; legend('曲线','波谷点','波峰点'); title('计算离散节点的波峰波谷信息', 'FontWeight', 'Bold'); subplot(2,1,2); plot(data(:,1), 'k'); hold on; plot(data_smooth, 'r'); box on; legend('原始数据','平滑数据'); title('原始数据和平滑数据', 'FontWeight', 'Bold'); % 计算波峰点和波谷点对应的y值 y_min = data_smooth(IndMin); y_max = data_smooth(IndMax); y1=mean(y_min); y2=mean(y_max); F= mean(data); %计算WFD值 WFD=(y2-y1)/F; fprintf('WFD值为:%f\n', WFD); function [IndMin, IndMax] = findExtrema(data_smooth) %获得局部最小值的位置 IndMin = find(diff(sign(diff(data_smooth))) > 0) + 1; %获得局部最大值的位置 IndMax = find(diff(sign(diff(data_smooth))) < 0) + 1; end 优化这段代码
时间: 2024-03-08 14:47:36 浏览: 17
这段代码的优化方向有以下几点:
1. 函数参数传递方式:可以将 data_smooth 作为全局变量,这样在函数中就不需要传递参数了,可以提高代码的执行效率。
2. 函数内部的计算:可以将 y_min、y_max、y1、y2 的计算合并为一行,以减少计算量。
3. 变量命名:可以将变量名更改为更有意义的名称,以提高代码的可读性。
4. 绘图操作:可以将绘图操作放在函数外部完成,以进一步提高代码的执行效率。
改进后的代码如下:
```matlab
data = load('out3.txt');
N = length(data(:,1));
b = fir1(15, 0.3, chebwin(16, 30));
data_smooth = filtfilt(b, 1, data(:,1));
[IndMin, IndMax] = find_extrema(data_smooth);
y_min = data_smooth(IndMin);
y_max = data_smooth(IndMax);
F = mean(data(:,1));
WFD = (mean(y_max) - mean(y_min)) / F;
fprintf('WFD值为:%f\n', WFD);
function [IndMin, IndMax] = find_extrema(data_smooth)
global data_smooth;
IndMin = find(diff(sign(diff(data_smooth))) > 0) + 1;
IndMax = find(diff(sign(diff(data_smooth))) < 0) + 1;
end
figure;
subplot(2,1,1);
plot(data_smooth);
hold on;
plot(IndMin, y_min, 'r^');
plot(IndMax, y_max, 'k*');
box on;
legend('曲线','波谷点','波峰点');
title('计算离散节点的波峰波谷信息', 'FontWeight', 'Bold');
subplot(2,1,2);
plot(data(:,1), 'k');
hold on;
plot(data_smooth, 'r');
box on;
legend('原始数据','平滑数据');
title('原始数据和平滑数据', 'FontWeight', 'Bold');
```