565 lines
27 KiB
Matlab
565 lines
27 KiB
Matlab
classdef z_dsp < handle
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properties
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%input
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fs_L;
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fs_H;
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TargetFrequency;
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G;
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simulink_time;
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intp_mode;
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dac_mode_sel;
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route_num;
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env_num;
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%output
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Ideal2Low;
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Ideal2Target;
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wave_pre;
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wave_preL;
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amp_real;
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amp_imag;
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time_real;
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time_imag;
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name;
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wave_revised;
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wave_revisedL;
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DownsamplingBy12GDataAlign;
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HardwareMeanIntpDataAlign;
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Delay;
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Delay_mode;
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pause_time;
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filename;
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rpt_num;
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FallingEdge;
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Amp;
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itv_time; %信号具有周期性时的间隔
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end
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methods
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function obj = z_dsp(fs_L,fs_H,TargetFrequency,G,simulink_time,intp_mode,dac_mode_sel)
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obj.fs_L = fs_L;
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obj.fs_H = fs_H;
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obj.TargetFrequency = TargetFrequency;
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obj.G = G;
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obj.simulink_time = simulink_time;
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obj.intp_mode = intp_mode;
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obj.dac_mode_sel = dac_mode_sel;
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obj.Ideal2Low = fs_H/(fs_L/2);
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obj.Ideal2Target = fs_H/TargetFrequency;
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obj.name = [
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"第一组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿",...
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"第一组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿",...
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"第一组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿",...
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"第一组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿",...
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"第一组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿",...
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"第一组S21参数_acz_持续时间30ns_下降沿",...
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"第一组S21参数_acz_持续时间50ns_下降沿";
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"第二组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿",...
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"第二组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿",...
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"第二组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿",...
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"第二组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿",...
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"第二组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿",...
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"第二组S21参数_acz_持续时间30ns_下降沿",...
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"第二组S21参数_acz_持续时间50ns_下降沿";
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"第三组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿",...
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"第三组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿",...
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"第三组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿",...
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"第三组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿",...
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"第三组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿",...
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"第三组S21参数_acz_持续时间30ns_下降沿",...
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"第三组S21参数_acz_持续时间50ns_下降沿";
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"第四组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿",...
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"第四组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿",...
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"第四组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿",...
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"第四组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿",...
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"第四组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿",...
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"第四组S21参数_acz_持续时间30ns_下降沿",...
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"第四组S21参数_acz_持续时间50ns_下降沿";
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"第五组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿",...
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"第五组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿",...
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"第五组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿",...
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"第五组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿",...
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"第五组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿",...
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"第五组S21参数_acz_持续时间30ns_下降沿",...
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"第五组S21参数_acz_持续时间50ns_下降沿";
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"第一组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿后",...
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"第一组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿后",...
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"第一组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿后",...
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"第一组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿后",...
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"第一组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿后",...
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"第一组S21参数_acz_持续时间30ns_下降沿后",...
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"第一组S21参数_acz_持续时间50ns_下降沿后";
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"第二组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿后",...
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"第二组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿后",...
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"第二组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿后",...
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"第二组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿后",...
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"第二组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿后",...
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"第二组S21参数_acz_持续时间30ns_下降沿后",...
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"第二组S21参数_acz_持续时间50ns_下降沿后";
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"第三组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿后",...
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"第三组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿后",...
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"第三组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿后",...
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"第三组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿后",...
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"第三组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿后",...
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"第三组S21参数_acz_持续时间30ns_下降沿后",...
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"第三组S21参数_acz_持续时间50ns_下降沿后";
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"第四组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿后",...
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"第四组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿后",...
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"第四组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿后",...
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"第四组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿后",...
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"第四组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿后",...
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"第四组S21参数_acz_持续时间30ns_下降沿后",...
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"第四组S21参数_acz_持续时间50ns_下降沿后";
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"第五组S21参数_flattop_上升沿2ns_持续时间30ns_下降沿后",...
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"第五组S21参数_flattop_上升沿4ns_持续时间30ns_下降沿后",...
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"第五组S21参数_flattop_上升沿4ns_持续时间50ns_下降沿后",...
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"第五组S21参数_flattop_上升沿4ns_持续时间1000ns_下降沿后",...
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"第五组S21参数_flattop_上升沿100ns_持续时间10000ns_下降沿后",...
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"第五组S21参数_acz_持续时间30ns_下降沿后",...
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"第五组S21参数_acz_持续时间50ns_下降沿后";
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];
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obj.pause_time = 0.5;
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obj.Amp = 1.5e4;
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end
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function env(obj)
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cd("D:\Work\EnvData\acz");
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obj1 = py.importlib.import_module('acz');
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py.importlib.reload(obj1);
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%按点数产生理想方波
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% amp_rect = 1.5e4;
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% %单位是ns front是到达时间，flat是持续时间，lagging是后边还有多少个0，会影响脚本的修正时间
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% [front(1), flat(1), lagging(1)] = deal(50,100,7400);% 50,100,7400;100ns方波
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% [front(2), flat(2), lagging(2)] = deal(50,4000,11500);% 50,4000,11500；4us方波
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%
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% for i = 1:2
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% front_H(i) = front(i)*fs_H/1e9; flat_H(i) = flat(i)*fs_H/1e9; lagging_H(i) = lagging(i)*fs_H/1e9;
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% wave_pre{i} = amp_rect*cat(2,zeros(1,front_H(i)),ones(1,flat_H(i)),zeros(1,lagging_H(i)));%脚本的单位是点数
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% end
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%flattop波
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A = 1.5e4;
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[edge(1), length_flattop(1)] = deal(2,30);%ns，在fsn_L取1时是参数里的length
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[edge(2), length_flattop(2)] = deal(4,30);
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[edge(3), length_flattop(3)] = deal(4,50);
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[edge(4), length_flattop(4)] = deal(4,1000);
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[edge(5), length_flattop(5)] = deal(100,10000);
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for i = 1:length(length_flattop)
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[edge_H(i), length_H(i)] = deal(edge(i)*obj.fs_H/1e9,length_flattop(i)*obj.fs_H/1e9);
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obj.wave_pre{i} = flattop(A, edge_H(i), length_H(i), 1);
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end
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%acz波
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amplitude = 1.5e4;
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carrierFreq = 0.000000;
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carrierPhase = 0.000000;
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dragAlpha = 0.000000;
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thf = 0.864;
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thi = 0.05;
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lam2 = -0.18;
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lam3 = 0.04;
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length_acz(1) = 30;
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length_acz(2) = 50;
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for i = 1:length(length_acz)
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length_acz_H(i) = int32(length_acz(i)*obj.fs_H/1e9);
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obj.wave_pre{i+length(length_flattop)} = real(double(py.acz.aczwave(amplitude, length_acz_H(i), carrierFreq,carrierPhase, dragAlpha,thf, thi, lam2, lam3)));
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end
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obj.env_num = length(length_flattop) + length(length_acz);
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for i = 1:obj.env_num
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obj.wave_pre{i} = cat(2,repmat(cat(2,obj.wave_pre{i},zeros(1,round(30e-9*obj.fs_H))),1,obj.rpt_num),zeros(1,floor(obj.simulink_time*obj.fs_H))); %校正前的高频信号
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obj.wave_preL{i} = obj.wave_pre{i}(1:obj.Ideal2Low:end); %校正前的低频信号
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end
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assignin("base",'wave_preL',obj.wave_preL);
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obj.FallingEdge = [30e-9,30e-9,50e-9,1000e-9,10000e-9,30e-9,50e-9];
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end
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function route(obj)
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obj.amp_real{1}= [0.025 0.015 0.0002 0.2 0 0];
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obj.amp_imag{1}= [0 0 0 0 0 0];
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obj.time_real{1} = [-1/250, -1/650, -1/1600 -1/20 0 0];
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obj.time_imag{1} = [0 0 0 0 0 0];
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obj.amp_real{2}= [0.025 0.015 0.0002 0.2 0 0];
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obj.amp_imag{2}= [0 0 0 0 0 0];
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obj.time_real{2} = [-1/250, -1/650, -1/1600 -1/20 0 0];
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obj.time_imag{2} = [0 -1/300 -1/500 0 0 0];
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obj.amp_real{3}= [0.025 0.009 0.0002 0.2 0 0];
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obj.amp_imag{3}= [0 0.012 0 0 0 0];
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obj.time_real{3} = [-1/250, -1/650, -1/1600 -1/20 0 0];
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obj.time_imag{3} = [0 -1/300 -1/500 0 0 0];
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obj.amp_real{4}= [0.025 0.015 0.0002 0.2 0 0];
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obj.amp_imag{4}= [0 0 0 0 0 0];
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obj.time_real{4} = [-1/250, -1/2000, -1/1600 -1/20 0 0];
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obj.time_imag{4} = [0 -1/15 -1/50 0 0 0];
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obj.amp_real{5}= [0.025 0.009 0.0002 0.2 0 0];
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obj.amp_imag{5}= [0 0.012 0 0 0 0];
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obj.time_real{5} = [-1/250, -1/2000, -1/1600 -1/20 0 0];
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obj.time_imag{5} = [0 -1/15 -1/50 0 0 0];
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[m,n] = size(obj.amp_real);
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obj.route_num = n;
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end
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function py_cal(obj)
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cd("D:\Work\TailCorr_20241008_NoGit");
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obj2 = py.importlib.import_module('wave_calculation');
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py.importlib.reload(obj2);
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cd("D:\Work\TailCorr");
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convolve_bound = int8(3);
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calibration_time = int32(20e3);
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cal_method = int8(1);
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sampling_rateL = int64(obj.fs_L/2);
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sampling_rate = int64(obj.fs_H);
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%校正后的高频信号
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for m = 1:obj.route_num
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for n = 1:obj.env_num
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wave_cal = cell(py.wave_calculation.wave_cal(obj.wave_pre{1,n}, obj.amp_real{1,m}, obj.amp_imag{1,m}, obj.time_real{1,m}, obj.time_imag{1,m}, convolve_bound, calibration_time, cal_method, sampling_rate));
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obj.wave_revised{m,n} = double(wave_cal{1,1});
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wave_calL = cell(py.wave_calculation.wave_cal(obj.wave_preL{1,n}, obj.amp_real{1,m}, obj.amp_imag{1,m}, obj.time_real{1,m}, obj.time_imag{1,m}, convolve_bound, calibration_time, cal_method, sampling_rateL));
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obj.wave_revisedL{m,n} = double(wave_calL{1,1});
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end
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alpha{m} = double(wave_calL{1,2});
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beta{m} = double(wave_calL{1,3});
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end
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alpha_wideth=32;
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beta_width=32;
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%定点化系数
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for i = 1:obj.route_num
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alphaFixRe{i} = ceil((2^(alpha_wideth-1))*real(alpha{i}));
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alphaFixIm{i} = ceil((2^(alpha_wideth-1))*imag(alpha{i}));
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betaFixRe{i} = ceil((2^(beta_width-1))*real(beta{i}));
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betaFixIm{i} = ceil((2^(beta_width-1))*imag(beta{i}));
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end
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assignin('base', 'alphaFixRe', alphaFixRe);
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assignin('base', 'alphaFixIm', alphaFixIm);
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assignin('base', 'betaFixRe' , betaFixRe);
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assignin('base', 'betaFixIm' , betaFixIm);
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end
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function FIL(obj)
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for m = 1:obj.route_num
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assignin('base', 'm', m);
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for n = 1:obj.env_num
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assignin('base', 'n', n);
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optnons=simset('SrcWorkspace','current');
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sim('z_dsp_FIL',[0,obj.simulink_time]);
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sim2m = @(x)reshape(logsout.get(x).Values.Data,[],1);
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dout0{m,n} = sim2m("dout0");
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dout1{m,n} = sim2m("dout1");
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dout2{m,n} = sim2m("dout2");
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dout3{m,n} = sim2m("dout3");
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N = length(dout0{m,n});
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cs_wave{m,n} = zeros(4*N,1);
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cs_wave{m,n}(1:4:4*N) = dout0{m,n};
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cs_wave{m,n}(2:4:4*N) = dout1{m,n};
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cs_wave{m,n}(3:4:4*N) = dout2{m,n};
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cs_wave{m,n}(4:4:4*N) = dout3{m,n};
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HardwareMeanIntpData{m,n} = cs_wave{m,n};%硬件校正后内插
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DownsamplingBy12GData{m,n} = obj.wave_revised{m,n}(1:obj.Ideal2Target:end);
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[obj.DownsamplingBy12GDataAlign{m,n},obj.HardwareMeanIntpDataAlign{m,n},obj.Delay(m,n)] = ...
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alignsignals(DownsamplingBy12GData{m,n}(1:round(obj.TargetFrequency*20e-6)),HardwareMeanIntpData{m,n}(1:round(obj.TargetFrequency*20e-6)),"Method","xcorr");
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end
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end
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obj.Delay_mode = mode(obj.Delay,'all');
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fprintf('Delay_mode = %d\n',obj.Delay_mode);
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end
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function DataShow(obj,save)
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close all;
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fileID = fopen(obj.filename, 'w');
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if fileID == -1
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disp('文件打开失败');
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else
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disp('文件打开成功');
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end
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start_time = abs(obj.Delay_mode)/(obj.TargetFrequency/1e9)*1e-9;%由于相位修正后会有偏移的点数，所以需要考虑上这个偏移的时间，采样率为3GHz，3个点对应1ns
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if(obj.rpt_num == 1)
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for m = 1:obj.route_num
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for n = 1:obj.env_num
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edge_Align(n) = obj.FallingEdge(n) + start_time;
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tmp(n) = edge_Align(n) + 10e-9;
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a{n} = [start_time-5e-9 tmp(n)];%[1/obj.fs_H 50e-9];[50e-9 1.5e-6],[500e-9+10e-9 tmp-20e-9]
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b{n} = [tmp(n) 20e-6];
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figure('Units','normalized','Position',[0.0004 0.5174 0.4992 0.4229]);
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obj.diff_plot_py(obj.TargetFrequency,obj.HardwareMeanIntpDataAlign{m,n}', obj.DownsamplingBy12GDataAlign{m,n}(1:floor(obj.TargetFrequency*20e-6)),obj.name(m,n),'硬件与脚本的差值',a{n},obj.Amp,edge_Align(n),fileID);
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if(save == "save")
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savefig(obj.name(m,n));
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end
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figure('Units','normalized','Position',[0.0004 0.0340 0.4992 0.4229]);
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obj.diff_plot_py(obj.TargetFrequency,obj.HardwareMeanIntpDataAlign{m,n}', obj.DownsamplingBy12GDataAlign{m,n}(1:floor(obj.TargetFrequency*20e-6)),obj.name(m+5,n),'硬件与脚本的差值',b{n},obj.Amp,edge_Align(n),fileID);
|
||
if(save == "save")
|
||
savefig(obj.name(m+5,n));
|
||
end
|
||
end
|
||
end
|
||
else
|
||
for m = 1:obj.route_num
|
||
for n = 1:obj.env_num
|
||
figure('Units','normalized','Position',[0 0.0333 1.0000 0.9125]);
|
||
title(obj.name(m,n),Interpreter="none");
|
||
tiledlayout('vertical','TileSpacing','tight')
|
||
obj.diff_plot_py(obj.TargetFrequency,obj.HardwareMeanIntpDataAlign{m,n}', obj.DownsamplingBy12GDataAlign{m,n}(1:floor(obj.TargetFrequency*20e-6)),obj.name(m,n),'硬件与脚本的差值',obj.FallingEdge(n)+obj.itv_time,obj.Amp,start_time,fileID);
|
||
if(save == "save")
|
||
savefig(obj.name(m,n));
|
||
end
|
||
end
|
||
end
|
||
end
|
||
|
||
fclose(fileID);
|
||
|
||
end
|
||
|
||
function RouteShow(obj,save)
|
||
|
||
t = 0:1/(1e2):10000;
|
||
for i = 1:5
|
||
amp_routing{i} = obj.amp_real{1,i} + 1j*obj.amp_imag{1,i};
|
||
time_routing{i} = obj.time_real{1,i} + 1j*obj.time_imag{1,i};
|
||
tau{i} = -1./time_routing{i};
|
||
end
|
||
|
||
figure()
|
||
set(gcf,"Position",[1 49 2560 1314])
|
||
tiledlayout('flow','TileSpacing','tight');
|
||
title_name = ["第一组S_{21}参数","第二组S_{21}参数","第三组S_{21}参数","第四组S_{21}参数","第五组S_{21}参数"];
|
||
for m = 1:obj.route_num
|
||
for n = 1:1:length(amp_routing{1,m})
|
||
S21_time{m}(:,n) = amp_routing{1,m}(n)*exp(time_routing{1,m}(n)*t);
|
||
end
|
||
nexttile
|
||
plot(t*1e-9,real(sum(S21_time{m},2)));
|
||
grid on
|
||
title(title_name(m));
|
||
end
|
||
|
||
if(save == "save")
|
||
savefig("S21线路参数");
|
||
end
|
||
|
||
end
|
||
|
||
function FigDisplay(obj)
|
||
if(obj.rpt_num == 1)
|
||
for m = 1:obj.route_num*obj.env_num
|
||
figure(2*m-1)
|
||
figure(2*m)
|
||
pause(obj.pause_time);
|
||
end
|
||
|
||
else
|
||
for m = 1:obj.route_num*obj.env_num
|
||
figure(m)
|
||
pause(obj.pause_time);
|
||
end
|
||
end
|
||
end
|
||
|
||
function LoadFigAndDisplay(obj)
|
||
for n = 1:obj.route_num
|
||
for m = 1:obj.env_num
|
||
open(strcat(obj.name(n,m),'.fig'));
|
||
open(strcat(obj.name(n+5,m),'.fig'));
|
||
pause(obj.pause_time);
|
||
end
|
||
end
|
||
end
|
||
|
||
function ErrAny(obj,save)
|
||
fid = fopen(obj.filename,'r');
|
||
if(obj.rpt_num == 1)
|
||
data = textscan(fid,'Falling edge of 20ns~40ns mean :%s std :%s Falling edge of 1us~1.1us mean :%s std :%s The mean and std stably less than 1e-4 is :%s s');
|
||
fclose(fid);
|
||
data{1} = cellfun(@str2num,data{1});
|
||
data{2} = cellfun(@str2num,data{2});
|
||
data{3} = cellfun(@str2num,data{3});
|
||
data{4} = cellfun(@str2num,data{4});
|
||
data{5} = cellfun(@str2num,data{5});
|
||
title_name = ["下降沿后20ns~40ns误差的平均值","下降沿后20ns~40ns误差的标准差","下降沿后1us~1.1us误差的平均值","下降沿后1us~1.1us误差的标准差","加窗参数"];
|
||
err_threshold = [1e-3 1e-3 1e-4 3e-4 5e-6];
|
||
else
|
||
data = textscan(fid,'每个周期拖尾误差均值的标准差 = %s s');
|
||
fclose(fid);
|
||
data{1} = cellfun(@str2num,data{1});
|
||
title_name = ["多周期误差平均值的标准差"];
|
||
err_threshold = [0.5e-3];
|
||
end
|
||
[h,v] = size(data);
|
||
figure()
|
||
tiledlayout('flow','TileSpacing','tight')
|
||
colors = lines(obj.route_num);
|
||
set(gcf,'Position', [1 49 2560 1314]);
|
||
for m = 1:v
|
||
nexttile
|
||
hold on
|
||
for i = 1:(obj.route_num)
|
||
idx = (i-1)*(length(data{m})/obj.route_num) + 1 : i*(length(data{m})/obj.route_num);
|
||
plot(idx,abs(data{m}(idx)),'-o','Color', colors(i, :));
|
||
end
|
||
yline(err_threshold(m),'--r');
|
||
title(title_name(m));
|
||
set(gca,'YScale','log');
|
||
legend("第一组线路","第二组线路","第三组线路","第四组线路","第五组线路",'Location','northwest');
|
||
end
|
||
if(obj.rpt_num == 1)
|
||
if(save == "save")
|
||
savefig("单周期误差分析")
|
||
end
|
||
else
|
||
if(save == "save")
|
||
savefig("多周期误差分析")
|
||
end
|
||
end
|
||
|
||
end
|
||
|
||
%compare FIL with python script
|
||
function diff_plot_py(obj,fs,iir_out, Script_out,title1,title2,a,amp,edge,fileID)
|
||
|
||
%输入数据长度不等时取其公共部分
|
||
N = min(length(iir_out),length(Script_out));
|
||
iir_out = iir_out(1:N);
|
||
Script_out = Script_out(1:N);
|
||
|
||
diff = (iir_out - Script_out)/amp;%求差，并归一化
|
||
|
||
n = (0:1:N-1)/fs;
|
||
%找出关心的数据点
|
||
if(obj.rpt_num == 1)
|
||
n_edge = find(n>=edge-1e-12);%edge代表下降沿
|
||
n50 = find(n>=edge+20e-9-1e-12);%下降沿后20ns
|
||
n20_40 = find((n>=edge+20e-9-1e-12) & (n<=edge+40e-9+1e-12));%下降沿后20ns到40ns
|
||
n1000 = find(n>=edge+1000e-9-1e-12);%下降沿后1us
|
||
n1000_1100 = find((n>=edge+1000e-9-1e-12) & (n<=edge+1100e-9+1e-12));%下降沿后1us到1.1us
|
||
|
||
ne = find((abs(diff)>=1e-4) & (abs(diff)<1));%误差小于万分之一的点
|
||
ne(1) = 1;
|
||
|
||
window_length = 100e-9*fs;
|
||
diff_mean_window = movmean(diff,window_length);
|
||
diff_std_window = movstd(diff,window_length);
|
||
n_mean_window = find((abs(diff_mean_window)>=1e-4) );%100ns窗，误差均值小于万分之一点
|
||
n_std_window = find((abs(diff_std_window)>=1e-4) ); %100ns窗，误差方差小于万分之一点
|
||
n_common = max(n_mean_window(end),n_std_window(end));
|
||
%原始数据作图
|
||
tiledlayout(2,1)
|
||
ax1 = nexttile;
|
||
plot(n,iir_out,n,Script_out)
|
||
legend('硬件','软件');
|
||
xlabel('t/s')
|
||
xlim(a);
|
||
title(title1,Interpreter="none");
|
||
grid on
|
||
hold on
|
||
|
||
%差值做图
|
||
ax2 = nexttile;
|
||
plot(n,diff)
|
||
xlabel('t/s')
|
||
title('diff')
|
||
grid on
|
||
hold on
|
||
xlim(a)
|
||
title('硬件与脚本的差值',Interpreter="none");
|
||
linkaxes([ax1,ax2],'x');
|
||
|
||
plot_p = @(x)[
|
||
plot(n(x),diff(x),'r*');
|
||
text(n(x), diff(x)+diff(x)*0.1, ['(',num2str(n(x)),',',num2str(diff(x)),')'],'color','k');
|
||
];
|
||
|
||
ne(1) = 1;
|
||
|
||
% [diff_max,R_mpos] = max(abs(diff));%误差最大值
|
||
% plot_p(R_mpos);
|
||
|
||
if a(2) <= 5e-6
|
||
plot_p(n_edge(1));%下降沿
|
||
% plot_p(R_mpos);
|
||
elseif a(2) == 20e-6
|
||
plot_p(n50(1)); %下降沿20ns
|
||
plot_p(n1000(1)); %下降沿1us
|
||
plot_p(ne(end)); %误差小于万分之一
|
||
fprintf(fileID,"Falling edge of 20ns~40ns mean :%.4e\t std :%.4e\t",mean(diff(n20_40)),std(diff(n20_40)));
|
||
fprintf(fileID,"Falling edge of 1us~1.1us mean :%.4e\t std :%.4e\t",mean(diff(n1000_1100)),std(diff(n1000_1100)));
|
||
% fprintf("The error after falling edge of 1us is:%.4e\t",diff(n1000(1)));
|
||
% fprintf("The time of erroe less than 1e-4 is :%.4e us\n",(n(ne(end))-n(n_edge(1))));
|
||
fprintf(fileID,"The mean and std stably less than 1e-4 is :%.4e s\n",(n(n_common)-n(n_edge(1))));
|
||
end
|
||
else
|
||
n_start = find(n>=edge-1e-12);%edge代表下降沿
|
||
|
||
% 确定周期长度对应的采样点数量
|
||
T = a; %在这种情况下，a这个参数用不到了，使用其传递周期，也就是说a这个参数有两种不同的涵义
|
||
samples_per_period = round(T * fs); % 每个周期采样点数
|
||
num_periods = obj.rpt_num; % 总周期数
|
||
period_means = zeros(1, num_periods); % 存储每周期均值
|
||
|
||
for i = 1:num_periods
|
||
% 提取当前周期的起止索引
|
||
start_idx(i) = n_start(1) + (i - 1) * samples_per_period;
|
||
end_idx(i) = n_start(1) + i * samples_per_period;
|
||
|
||
% 提取当前周期的数据
|
||
period_data = diff(start_idx(i):end_idx(i));
|
||
|
||
% 计算当前周期的均值
|
||
period_means(i) = mean(period_data);
|
||
end
|
||
fprintf(fileID,"每个周期拖尾误差均值的标准差 = %.4e s\n",std(period_means));
|
||
ax1 = nexttile;
|
||
plot(n,iir_out,n,Script_out);
|
||
hold on
|
||
plot(n(start_idx), Script_out(start_idx), 'r*'); % 标记每个周期的起始点
|
||
plot(n(end_idx), Script_out(end_idx), 'g*'); % 标记每个周期的起始点
|
||
legend('硬件','软件');
|
||
xlabel('t/s');
|
||
title(title1,Interpreter="none");
|
||
ax2 = nexttile;
|
||
hold on
|
||
plot(n, diff); hold on; % 原始信号
|
||
plot(n(end_idx), diff(end_idx), 'g*'); % 标记每个周期的起始点
|
||
xlabel('t/s');
|
||
ylabel('归一化误差');
|
||
linkaxes([ax1,ax2],'x');
|
||
xlim([0,n(end_idx(end)) + 5e-7]);
|
||
title(title2,Interpreter="none");
|
||
|
||
end
|
||
end
|
||
|
||
|
||
|
||
end
|
||
|
||
end
|
||
|