How to calculate SNR before and after filtering in Matlab?

Hi. I have this noisy signal and I want to calculate its SNR before and after filtering process. Please help me!!

f1=50;
f2=100;
fsampling=1000;
fn1_normfreq=0.4;
fn2_normfreq=0.5;
x1 = cos(2*pi*f1*[0:1/fsampling:1.23]);
x2 = cos(2*pi*f2*[0:1/fsampling:1.23]);
x = x1 + x2;
x(end) = [];
[b,a] = butter(2,[fn1_normfreq fn2_normfreq],'bandpass');
filtered_noise = filter(b,a,randn(1, length(x)*2));
noise = 0.5*filtered_noise(500:500+length(x)-1);
y = (x + noise)/length(x)*2; %noisy signal

%Lowpass FIR filter using rectangular window
fp=300;
fs=400;
rp=0.005;
rs=0.1;

% Normalizing the frequencies
wp=2*fp/fsampling;
ws=2*fs/fsampling;
num=-20*log10(sqrt(rp*rs))-13;
dem=14.6*(fs-fp)/fsampling;

n=ceil(num/dem);
n1=n+1;
if (rem(n,2)~=0)
    n1=n;
    n=n-1;
end

w=rectwin(n1);
b=fir1(n,wp,'high',w);%Filter coefficients

%filtering
Y_filtered=filtfilt(b,1,y); %filtered signal

Answer 1

[Walter Roberson]

A signal in isolation must always be considered to be a perfect signal, noiseless. You can only calculate SNR if you have at least two signals (one of which might be the constant signal, all 0, if you know that the other signal consists entirely of noise.)