Load all mat files to Workspace and plot

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Mike Buba
Mike Buba 2021-11-3
评论： Mathieu NOE 2022-5-16
Hi,
I am recording signals from DSP in External mode and I can record a certain number of data (depends on sample time, number of signals, heap size, etc.) before a new mat file is created (increment file after one-shot). So I end up with e.g., Data_0.mat, Data_1.mat, Data_2.mat, etc.
I can load each mat file into Workspace and plot. e.g.:
load('Data_8.mat')
figure
subplot(2,1,1)
plot(ScopeData1.time,ScopeData1.signals.values)
grid on
subplot(2,1,2)
plot(ScopeData2.time,ScopeData2.signals.values).
For the next recoded section I have to load another mat file (e.g., Data_9.mat), run the plot script, etc.
How to load all mat files into Workspace and plot them all in one single graph?
Note that the signal name is the same in each mat file (ScopeData1.signals.values and ScopeData2.signals.values) and time is not continuous, i.e., there is a break in time for MATLAB to save this recoding and start another.

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采纳的回答

Mathieu NOE
Mathieu NOE 2021-11-3
hello
this is one example how to load all mat files and sort them in natural order (what matlab does not do by default)
you need : https://fr.mathworks.com/matlabcentral/fileexchange/47434-natural-order-filename-sort
the results is that all data are being concatenated but there is this time gap between the recordings , I don't know how you deal with that
fileDir = pwd;
fileNames = dir(fullfile(fileDir,'Data*.mat')); % get list of data files in directory
fileNames_sorted = natsortfiles({fileNames.name}); % sort file names into natural order
% (download FEX : https://fr.mathworks.com/matlabcentral/fileexchange/47434-natural-order-filename-sort)
M= length (fileNames_sorted);
out_data = [];
time1 = [];
signal1 = [];
time2 = [];
signal2 = [];
for f = 1:M
S = load(fullfile(fileDir, fileNames_sorted{f}))
% contatenation of all individual files data
time1 = [time1; S.ScopeData1.time];
signal1 = [signal1; S.ScopeData1.signals.values];
time2 = [time2; S.ScopeData2.time];
signal2 = [signal2; S.ScopeData2.signals.values];
end
figure
subplot(2,1,1)
plot(time1,signal1,'*-')
grid on
subplot(2,1,2)
plot(time2,signal2,'*-');

更多回答（1 个）

venkat reddy
venkat reddy 2022-5-14
plz help me to plot the file
close all;clear all;clc;
Nt0 = [8;8];
Nt = Nt0(1)*Nt0(2);
Nr0 = [8;8];
Nr = Nt0(1)*Nt0(2);
Ny = 32;
Nx = 32;
N_RF = 4;
L = 3;
d = 0.5;
H = zeros(Nr, Nt);
X = 1/sqrt(Nt)*exp(-1i*2*pi*rand(Nt, Nx));
mu_X = max(max(abs(X*X'-Nx/Nt*eye(Nt))));
W = 1/sqrt(Nr)*exp(-1i*2*pi*rand(Ny, Nr));
mu_W = max(max(abs(W'*W-Ny/Nr*eye(Nr))));
for i = 1:1000000
X0 = 1/sqrt(Nt)*exp(-1i*2*pi*rand(Nt, Nx));
mu_X0 = max(max(abs(X0*X0'-Nx/Nt*eye(Nt))));
if (mu_X0 < mu_X)
X = X0;
mu_X = mu_X0;
end
W0 = 1/sqrt(Nr)*exp(-1i*2*pi*rand(Ny, Nr));
mu_W0 = max(max(abs(W0'*W0-Ny/Nr*eye(Nr))));
if (mu_W0 < mu_W)
W = W0;
mu_W = mu_W0;
end
end
SNR_list = -5:2.5:20;
sample_num = 3;
nmse_result = zeros(numel(SNR_list),sample_num);
alpha_true = zeros(numel(SNR_list),sample_num,L);
phi_t_true = zeros(numel(SNR_list),sample_num,L,2);
phi_r_true = zeros(numel(SNR_list),sample_num,L,2);
L_result = zeros(numel(SNR_list),sample_num);
theta_result = zeros(numel(SNR_list),sample_num,4,10);
z_result = zeros(numel(SNR_list),sample_num,10);
for sample_ii = 1:sample_num
H = zeros(Nr, Nt);
alpha = zeros(L,1);
alpha(1:L) = (normrnd(0, 1, L, 1) + 1i*normrnd(0, 1, L, 1)) / sqrt(2);
while (find(abs(alpha)<0.01))
alpha(1:L) = (normrnd(0, 1, L, 1) + 1i*normrnd(0, 1, L, 1)) / sqrt(2);
end
alpha = sort(alpha, 'descend');
phi_t = 2*rand(L,2)-1;%virtual AoD
phi_r = 2*rand(L,2)-1;%virtual AoA
for l = 1:L
at = kron(exp(-1i*2*pi*[0:Nt0(1)-1]'*d*phi_t(l,1)), exp(-1i*2*pi*[0:Nt0(2)-1]'*d*phi_t(l,2)));
ar = kron(exp(-1i*2*pi*[0:Nr0(1)-1]'*d*phi_r(l,1)), exp(-1i*2*pi*[0:Nr0(2)-1]'*d*phi_r(l,2)));
H = H + alpha(l)*ar*at';
end
for snr_ii = 1:numel(SNR_list)
snr = SNR_list(snr_ii);
noise = sqrt(10^(-snr/10)/2);
H = zeros(Nr, Nt);
alpha = zeros(L,1);
alpha(1:L) = (normrnd(0, 1, L, 1) + 1i*normrnd(0, 1, L, 1)) / sqrt(2);
while (find(abs(alpha)<0.01))
alpha(1:L) = (normrnd(0, 1, L, 1) + 1i*normrnd(0, 1, L, 1)) / sqrt(2);
end
alpha = sort(alpha, 'descend');
phi_t = 2*rand(L,2)-1;%virtual AoD
phi_r = 2*rand(L,2)-1;%virtual AoA
for l = 1:L
at = kron(exp(-1i*2*pi*[0:Nt0(1)-1]'*d*phi_t(l,1)), exp(-1i*2*pi*[0:Nt0(2)-1]'*d*phi_t(l,2)));
ar = kron(exp(-1i*2*pi*[0:Nr0(1)-1]'*d*phi_r(l,1)), exp(-1i*2*pi*[0:Nr0(2)-1]'*d*phi_r(l,2)));
H = H + alpha(l)*ar*at';
end
Y = W*(H*X + noise*(normrnd(0, 1, Nr, Nx) + 1i*normrnd(0, 1, Nr, Nx)));
Rth = noise*sqrt(Ny*Nx);
[theta_es,z_es,err]=IR_SURE_CE_UPA(Y,X,W,Nx,Nt0,Nr0,Ny,Rth);
H_es = zeros(Nr, Nt);
at = zeros(Nt,1);
ar = zeros(Nr,1);
for l = 1:numel(z_es)
at = kron(exp(-1i*2*pi*[0:Nt0(1)-1]'*theta_es(1,l)), exp(-1i*2*pi*[0:Nt0(2)-1]'*theta_es(2,l)));
ar = kron(exp(-1i*2*pi*[0:Nt0(1)-1]'*theta_es(3,l)), exp(-1i*2*pi*[0:Nt0(2)-1]'*theta_es(4,l)));
H_es = H_es + z_es(l)*ar*at';
end
nmse_sample = sum(sum(abs(H-H_es).^2))/sum(sum(abs(H).^2));
disp(['sample_ii=' num2str(sample_ii) ' snr=' num2str(SNR_list(snr_ii)) ' nmse=' num2str(nmse_sample) ' err=' num2str(err)]);
%% spectral efficiency
[U_perfectCSI,S,V_perfectCSI] = svd(H);
P_perfectCSI = V_perfectCSI(:,1:N_RF);
Q_perfectCSI = U_perfectCSI(:,1:N_RF);
R_perfectCSI = 0.5*noise*noise*(Q_perfectCSI'*Q_perfectCSI);
SE_perfectCSI = log2(det(eye(N_RF)+(1/N_RF)*inv(R_perfectCSI)*((Q_perfectCSI'*H*P_perfectCSI)*(Q_perfectCSI'*H*P_perfectCSI)')));
[U_estCSI_SURE,S,V_estCSI_SURE] = svd(H_es);
P_estCSI_SURE = V_estCSI_SURE(:,1:N_RF);
Q_estCSI_SURE = U_estCSI_SURE(:,1:N_RF);
R_estCSI_SURE = 0.5*noise*noise*(Q_estCSI_SURE'*Q_estCSI_SURE);
SE_estCSI_SURE = log2(det(eye(N_RF)+(1/N_RF)*inv(R_estCSI_SURE)*((Q_perfectCSI'*H*P_estCSI_SURE)*(Q_perfectCSI'*H*P_estCSI_SURE)')));
alpha_true(snr_ii, sample_ii,:) = alpha;
phi_t_true(snr_ii, sample_ii,:,:) = phi_t;
phi_r_true(snr_ii, sample_ii,:,:) = phi_r;
nmse_result(snr_ii, sample_ii) = nmse_sample;
L_sample = numel(z_es);
L_result(snr_ii, sample_ii) = L_sample;
theta_result(snr_ii, sample_ii, :, 1:L_sample) = theta_es(:,:);
z_result(snr_ii, sample_ii, 1:L_sample) = z_es(:);
end
save result.mat
load result.mat
figure;
hold on; box on;
plot(snr,result,'rd-','LineWidth',1);
% plot(nmse_result,SE_estCSI_SURE,'ko:','LineWidth',1);
% plot(nmse_result,V_estCSI_SURE,'k*--','LineWidth',1);
% plot(nmse_result,V_perfectCSI,'bs-','LineWidth',1);
%
xlabel('SNR (dB)');
ylabel('NMSE');
legend('ULA','UPA','OMP','AUXILARY BEAM PAIR','Location','NorthWest');
set(gca,'XScale','log');
title('NMSE performance comparison of different channel estimation schemes under NLoS channel');
end
  2 个评论
Mathieu NOE
Mathieu NOE 2022-5-16
hello
what is the issue ? I tried to run your code but got this error :
Unrecognized function or variable 'rndcheck'.
Error in normrnd (line 27)
[errorcode rows columns] =
rndcheck(4,2,mu,sigma,m,n);
Error in venkat (line 45)
alpha(1:L) = (normrnd(0, 1, L, 1) + 1i*normrnd(0,
1, L, 1)) / sqrt(2);
Mathieu NOE
Mathieu NOE 2022-5-16
maybe I fixed the previous error - could find the rndcheck function on internet
but now Ihave another issue as this function is not provided in your code :
Unrecognized function or variable 'IR_SURE_CE_UPA'.
Error in venkat (line 80)
[theta_es,z_es,err]=IR_SURE_CE_UPA(Y,X,W,Nx,Nt0,Nr0,Ny,Rth);

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