.m增加了寻找误差和均方误差均小于万分之一的功能

修改了z_dsp.m的路径

rtl/z_dsp/IIR_Filter.v

@@ -172,7 +172,7 @@ inst_c4         (
 assign	y_re       =   v1_re + y2_re;
 assign	y_im       =   v1_im + y2_im;
 
-reg signed	[data_in_width+frac_data_out_width+1:0] dout_round;
+wire signed	[data_in_width+frac_data_out_width+1:0] dout_round;
 
 FixRound #(data_in_width+frac_data_out_width+2,frac_data_out_width) u_round1 (clk, rstn, en, y_re, dout_round);
 

rtl/z_dsp/mult_C.v

@@ -98,8 +98,8 @@ wire         signed  [A_width+D_width:0]     Im_tmp;
 assign    Re_tmp  =  ac - bd;
 assign    Im_tmp  =  ad + bc;
 
-reg         signed  [A_width+C_width:0]     Re_round;
+wire         signed  [A_width+C_width:0]     Re_round;
-reg         signed  [A_width+D_width:0]     Im_round;
+wire         signed  [A_width+D_width:0]     Im_round;
 
 FixRound #(A_width+C_width+1,frac_coef_width) u_round1 (clk, rstn, en, Re_tmp, Re_round);
 FixRound #(A_width+C_width+1,frac_coef_width) u_round2 (clk, rstn, en, Im_tmp, Im_round);

script_m/diff_plot_py.m

@@ -18,12 +18,12 @@ n1000_1100 = find((n>=edge+1000e-9-1e-12) & (n<=edge+1100e-9+1e-12));%下降沿
 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;
+window_length = 100e-9*fs;
-% diff_mean_window = movmean(diff,window_length);
+diff_mean_window = movmean(diff,window_length);
-% diff_std_window = movstd(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_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_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));
+n_common = max(n_mean_window(end),n_std_window(end));
 %原始数据作图
 tiledlayout(2,1)
 ax1 = nexttile;
@@ -68,10 +68,10 @@ elseif a(2) > 5e-6
     plot_p(n1000(1)); %下降沿1us
     plot_p(ne(end));  %误差小于万分之一
     fprintf("Falling edge of 20ns~40ns mean :%.4e\t std :%.4e\t",mean(diff(n20_40)),std(diff(n20_40)));
-    fprintf("Falling edge of 1us~1.1us mean :%.4e\t std :%.4e\n",mean(diff(n1000_1100)),std(diff(n1000_1100)));
+    fprintf("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("The mean and std stably less than 1e-4 is :%.4e s\n",(n(n_common)-n(n_edge(1))));
+    fprintf("The mean and std stably less than 1e-4 is :%.4e s\n",(n(n_common)-n(n_edge(1))));
 
 end
 

script_m/z_dsp.m

@@ -2,17 +2,17 @@ clc;clear;close all
 
 % hdlsetuptoolpath('ToolName','Xilinx Vivado','ToolPath','D:\SoftWare\Xilinx\Vivado\2019.2\bin\vivado.bat');	
 
-addpath(genpath('D:\Work\EnvData'));	
+% addpath(genpath('D:\Work\EnvData'));	
-addpath(genpath('D:\Work\EnvData\data-v2'));	
+% addpath(genpath('D:\Work\EnvData\data-v2'));	
 % addpath(genpath('D:\Work\TailCorr_20241008_NoGit'));	
-
+% addpath('D:\Work\TailCorr\script_m');
 cd("D:\Work\EnvData\acz");
 obj1 = py.importlib.import_module('acz');
 py.importlib.reload(obj1);
 cd("D:\Work\TailCorr_20241008_NoGit");
 obj2 = py.importlib.import_module('wave_calculation');
 py.importlib.reload(obj2);
-cd("D:\Work\TailCorr\script_m");
+cd("D:\Work\TailCorr");
 
 fs_L = 0.75e9;    %硬件频率
 fs_H = 12e9;      %以高频近似理想信号
@@ -77,20 +77,10 @@ end
 
 %%%python脚本校正结果
 %S21参数
-amp_real = [0.025 0.015 0.0002 0 0 0];
+amp_real = [0.025 0.015 0.0002 0.2 0 0];
 amp_imag = [0 0 0 0 0 0];
-time_real = [-1/250, -1/650, -1/1600 0 0 0];
+time_real = [-1/250, -1/650, -1/1600 -1/20 0 0];
-time_imag = [0 0 0 0 0 0];
+time_imag = [0 -1/300 -1/500 0 0 0];
-
-% amp_real = [0.0539981,-0.0319766,0.084015161,0.0048,0,0];
-% amp_imag = [0,-0.041014189,-0.052936266,0,0,0];
-% time_real = [-0.0024820146,-0.0080529118,-0.006728925,-0.0001,0,0];
-% time_imag = [0,-0.008137675,-0.0033212836,0,0,0];
-% 
-% amp_real = [0.025 0.015 0.0002 0.2 0 0];
-% amp_imag = [0 0 0 0 0 0];
-% time_real = [-1/250, -1/650, -1/1600 -1/20 0 0];
-% time_imag = [0 0 0 0 0 0];
 
 amp_routing = amp_real + 1j*amp_imag;
 time_routing = time_real + 1j*time_imag;
@@ -174,11 +164,11 @@ for i = 1:8
     fig1 = figure('Units','normalized','Position',[0.000390625,0.517361111111111,0.49921875,0.422916666666667]);
     diff_plot_py(TargetFrequency,HardwareMeanIntpDataAlign{i}', DownsamplingBy12GDataAlign{i}(1:floor(TargetFrequency*20e-6)),'HardwareRevised','ScriptRevised',a{i},Amp,edge_Align(i));
     title(name(i,1),Interpreter="none");
-    savefig(name(i,1));
+    % savefig(name(i,1));
     fig2 = figure('Units','normalized','Position',[0.000390625,0.034027777777778,0.49921875,0.422916666666667]);
     diff_plot_py(TargetFrequency,HardwareMeanIntpDataAlign{i}', DownsamplingBy12GDataAlign{i}(1:floor(TargetFrequency*20e-6)),'HardwareRevised','ScriptRevised',b{i},Amp,edge_Align(i));
     title(name(i,2),Interpreter="none");
-    savefig(name(i,2));
+    % savefig(name(i,2));
 end
 
 %% 可视化S21参数