如何在 MATLAB 中旋转绘图?
How can I rotate a plot in MATLAB?
例如,我想将绘图 scatterplot(rxSig)
(如下所示)旋转 8 度。
(照片中的红点组)
它看起来不像一个常规的情节,我没有找到相关的信息。
预期结果:(旋转)
不旋转绘图:
R = 1000.0;
freq = 28*1e9;
T = 20.0;
lwd = 0.5;
F = fogpl(R,freq,T,lwd);
P = 101300.0;
W = 7.5;
G = gaspl(R,freq,T,P,W);
RR=[0.75,1.75,2.5,3];
for irr=1:length(RR)
R = rainpl(10000,freq,RR(irr));
L=R+F+G;
end
M = 64; % Modulation order
k = log2(M); % Bits per symbol
EbNoVec = (0:25)'; % Eb/No values (dB)
numSymPerFrame = 1000;
for n = 1:length(EbNoVec)
% Convert Eb/No to SNR
snrdB = EbNoVec(n) + 10*log10(k)-L(1);
% Reset the error and bit counters
numErrs = 0;
numBits = 0;
while numErrs < 200 && numBits < 1e8
% Generate binary data and convert to symbols
dataIn = randi([0 1],numSymPerFrame,k);
dataSym = bi2de(dataIn);
% QAM modulate using 'Gray' symbol mapping
txSig = qammod(dataSym,M);
% Pass through AWGN channel
rxSig = awgn(txSig,snrdB,'measured');
% Demodulate the noisy signal
rxSym = qamdemod(rxSig,M);
% Convert received symbols to bits
dataOut = de2bi(rxSym,k);
% Calculate the number of bit errors
nErrors = biterr(dataIn,dataOut);
% Increment the error and bit counters
numErrs = numErrs + nErrors;
numBits = numBits + numSymPerFrame*k;
end
% Estimate the BER
berEst(n) = numErrs/numBits;
end
berTheory = berawgn(EbNoVec,'qam',M);
semilogy(EbNoVec,berEst,'*')
hold on
semilogy(EbNoVec,berTheory)
grid
legend('Estimated BER with our attenuation function','Theoretical Matlab BER')
xlabel('Eb/No (dB)')
ylabel('Bit Error Rate')
scatterplot(rxSig)
我结合了我的两个建议来创建以下代码。
% Extract data points from current figure
h = findobj(gca,'Type','line');
x_org=get(h,'Xdata');
y_org=get(h,'Ydata');
points = [x_org; y_org]';
% to rotate 8 degree counterclockwise
theta = 8;
% Rotation matrix
R = [cosd(theta) -sind(theta); sind(theta) cosd(theta)];
% Rotate points
points_rot = R*points';
figure(3)
plot(points_rot(1,:), points_rot(2,:), '.');
将此添加到代码末尾会产生下图:
例如,我想将绘图 scatterplot(rxSig)
(如下所示)旋转 8 度。
(照片中的红点组)
它看起来不像一个常规的情节,我没有找到相关的信息。
预期结果:(旋转)
不旋转绘图:
R = 1000.0;
freq = 28*1e9;
T = 20.0;
lwd = 0.5;
F = fogpl(R,freq,T,lwd);
P = 101300.0;
W = 7.5;
G = gaspl(R,freq,T,P,W);
RR=[0.75,1.75,2.5,3];
for irr=1:length(RR)
R = rainpl(10000,freq,RR(irr));
L=R+F+G;
end
M = 64; % Modulation order
k = log2(M); % Bits per symbol
EbNoVec = (0:25)'; % Eb/No values (dB)
numSymPerFrame = 1000;
for n = 1:length(EbNoVec)
% Convert Eb/No to SNR
snrdB = EbNoVec(n) + 10*log10(k)-L(1);
% Reset the error and bit counters
numErrs = 0;
numBits = 0;
while numErrs < 200 && numBits < 1e8
% Generate binary data and convert to symbols
dataIn = randi([0 1],numSymPerFrame,k);
dataSym = bi2de(dataIn);
% QAM modulate using 'Gray' symbol mapping
txSig = qammod(dataSym,M);
% Pass through AWGN channel
rxSig = awgn(txSig,snrdB,'measured');
% Demodulate the noisy signal
rxSym = qamdemod(rxSig,M);
% Convert received symbols to bits
dataOut = de2bi(rxSym,k);
% Calculate the number of bit errors
nErrors = biterr(dataIn,dataOut);
% Increment the error and bit counters
numErrs = numErrs + nErrors;
numBits = numBits + numSymPerFrame*k;
end
% Estimate the BER
berEst(n) = numErrs/numBits;
end
berTheory = berawgn(EbNoVec,'qam',M);
semilogy(EbNoVec,berEst,'*')
hold on
semilogy(EbNoVec,berTheory)
grid
legend('Estimated BER with our attenuation function','Theoretical Matlab BER')
xlabel('Eb/No (dB)')
ylabel('Bit Error Rate')
scatterplot(rxSig)
我结合了我的两个建议来创建以下代码。
% Extract data points from current figure
h = findobj(gca,'Type','line');
x_org=get(h,'Xdata');
y_org=get(h,'Ydata');
points = [x_org; y_org]';
% to rotate 8 degree counterclockwise
theta = 8;
% Rotation matrix
R = [cosd(theta) -sind(theta); sind(theta) cosd(theta)];
% Rotate points
points_rot = R*points';
figure(3)
plot(points_rot(1,:), points_rot(2,:), '.');
将此添加到代码末尾会产生下图: