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additional features for peak picking

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This commit is contained in:
Mark Borgerding
2003-08-09 01:03:04 +00:00
parent fa03256dc2
commit ccbc48dc63
7 changed files with 287 additions and 47 deletions
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40
test.oct
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@ -2,23 +2,23 @@
# Compare the results of kiss_fft with those calculated by octave's fft routines
nfft=1024;
nfft=1024
showdiff=0;
use_inverse_fft = 1
infile = 'fftin.dat'
outfile = 'fftout.dat'
for test_case =1:3
printf( '====================================\n');
if test_case == 1,
prec = 'short'
prog = './kiss_fft_s'
scale = nfft
elseif test_case == 2,
prec = 'float'
prog = './kiss_fft_f'
scale = 1
else
prec = 'double'
prog = './kiss_fft_d'
scale = 1
endif
# create the input
@ -26,24 +26,31 @@ for test_case =1:3
input = floor( real(input)*32767 ) + j*floor(imag(input)*32767 );
# write the input
f = fopen( "fftin.dat", "w", "native");
f = fopen( infile, "w", "native");
to_write = [real(input);imag(input) ];
fwrite(f,to_write,prec);
fclose(f);
cmd = sprintf('%s %d < fftin.dat > fftout.dat',prog,nfft)
if use_inverse_fft,
cmd = sprintf('%s -s -i %d < %s > %s',prog,nfft,infile,outfile)
comp = ifft(input);
else
cmd = sprintf('%s -s %d < %s > %s',prog,nfft,infile,outfile)
comp = fft(input);
endif
system(cmd);
# read the output
f = fopen("fftout.dat","r", "native");
f = fopen(outfile,"r", "native");
from_read = fread(f,Inf,prec)';
output = (from_read(1:2:nfft*2) + j*from_read(2:2:nfft*2)) ;
comp = fft(input)/scale;
if test_case == 1,
comp = floor( real(comp) +.5) + j*floor( imag(comp) +.5);
endif
output = (from_read(1:2:nfft*2) + j*from_read(2:2:nfft*2));
diff = output - comp;
noise_pow = sum( conj(diff).*diff );
sig_pow = sum( conj(comp).*comp );
snr = 10*log10( sig_pow / noise_pow )
avg_scale = mean( abs(output) ./ abs(comp) )
var_scale = var( abs(output) ./ abs(comp) )
if showdiff,
x=linspace(0,2*pi,nfft);
figure(1);
@ -53,12 +60,5 @@ for test_case =1:3
figure(3);
plot( x, abs(output-comp) );
pause
else
diff = output - comp;
noise_pow = sum( conj(diff).*diff );
sig_pow = sum( conj(comp).*comp );
snr = 10*log10( sig_pow / noise_pow )
avg_scale = mean( abs(output) ./ abs(comp) )
endif
endfor