We process a higher amount of data
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bfd3004106
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2 changed files with 13 additions and 12 deletions
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@ -5,7 +5,7 @@
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%pkg install -forge parallel
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%pkg install -forge parallel
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pkg load parallel
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pkg load parallel
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system('cat /dev/urandom | csdr pack_bits_8to1_u8_u8 | csdr psk_modulator_u8_c 2 | csdr gain_ff 0.25 | csdr psk31_interpolate_sine_cc 256 | csdr add_n_zero_samples_at_beginning_f 170 | dd bs=32M count=1 of=/tmp/psk31-raw-data');
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system('cat /dev/urandom | csdr pack_bits_8to1_u8_u8 | csdr psk_modulator_u8_c 2 | csdr gain_ff 0.25 | csdr psk31_interpolate_sine_cc 256 | csdr add_n_zero_samples_at_beginning_f 170 | dd iflag=fullblock bs=4M count=1 of=/tmp/psk31-raw-data');
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function output=shrun(cmd, type, minsize)
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function output=shrun(cmd, type, minsize)
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SIGTERM=15;
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SIGTERM=15;
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@ -15,11 +15,11 @@ function output=shrun(cmd, type, minsize)
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%fclose(pin);
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%fclose(pin);
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do
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do
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sleep(0.3)
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sleep(0.3)
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disp('size(output)');
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fwrite(stdout,'.');
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%size(output)
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%size(output)
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%output
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%output
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current_output=fread(pout, Inf, type)
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current_output=fread(pout, Inf, type);
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frewind(pout)
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frewind(pout);
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output=[output; current_output];
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output=[output; current_output];
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until(size(output)(1)>=minsize)
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until(size(output)(1)>=minsize)
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waitpid(pid);
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waitpid(pid);
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@ -30,22 +30,22 @@ end
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function variance=run_var(snr, which_ted)
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function variance=run_var(snr, which_ted)
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disp('ran a command')
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disp('ran a command')
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out_vect=shrun(sprintf('cat /tmp/psk31-raw-data | csdr awgn_cc %d | csdr timing_recovery_cc %s 256 --add_q --output_indexes | CSDR_FIXED_BUFSIZE=65536 csdr normalized_timing_variance_u32_f 256 85', snr, which_ted), 'float32', 1);
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out_vect=shrun(sprintf('cat /tmp/psk31-raw-data | csdr awgn_cc %d --snrshow-no| csdr timing_recovery_cc %s 256 --add_q --output_indexes | CSDR_FIXED_BUFSIZE=131072 csdr normalized_timing_variance_u32_f 256 85', snr, which_ted), 'float32', 1);
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disp('run_var output:');
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disp('run_var output:');
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out_vect'
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out_vect'
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variance=out_vect(1);
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variance=out_vect(1);
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end
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end
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function variances=mkvarplot(which_ted, snrs)
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function variances=mkvarplot(which_ted, snrs)
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%{
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fun = @(x) run_var(x, which_ted);
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fun = @(x) run_var(x, which_ted);
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variances=pararrayfun(nproc, fun, snrs);
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variances=pararrayfun(nproc, fun, snrs);
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%}
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%{
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variances=[]
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variances=[]
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for snr=snrs
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for snr=snrs
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snr
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snr
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variances=[variances run_var(snr, which_ted)];
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variances=[variances run_var(snr, which_ted)];
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end
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end
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%}
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end
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end
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function fmtplot(h)
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function fmtplot(h)
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@ -54,11 +54,12 @@ function fmtplot(h)
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set(FN,'FontName','times');
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set(FN,'FontName','times');
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FS = findall(h,'-property','FontSize');
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FS = findall(h,'-property','FontSize');
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set(FS,'FontSize',18);
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set(FS,'FontSize',18);
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xlabel('Phase offset in number of samples');
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xlabel('SNR [dB]');
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ylabel('Error value (TED output)');
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ylabel('Phase error variance [rad^2]');
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end
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end
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snrs_gardner=-30:5:40
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snrs_gardner=-70:5:40
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%snrs_gardner=[10]
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error_values_gardner=mkvarplot('GARDNER',snrs_gardner);
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error_values_gardner=mkvarplot('GARDNER',snrs_gardner);
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%{
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%{
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snrs_earlylate=0:256
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snrs_earlylate=0:256
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@ -69,7 +70,7 @@ error_values_earlylate=mkvarplot('EARLYLATE',snrs_earlylate);
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h=figure(1);
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h=figure(1);
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semilogy(snrs_gardner, error_values_gardner, 'linewidth', 2);
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semilogy(snrs_gardner, error_values_gardner, 'linewidth', 2);
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title('S-curve for Gardner TED');
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title('Variance curve');
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fmtplot(h)
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fmtplot(h)
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pause
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pause
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@ -2187,7 +2187,7 @@ float normalized_timing_variance_u32_f(unsigned* input, float* temp, int input_s
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ndiff_rad_mean = ndiff_rad_mean*(((float)i)/(i+1))+(ndiff_rad[i]/(i+1));
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ndiff_rad_mean = ndiff_rad_mean*(((float)i)/(i+1))+(ndiff_rad[i]/(i+1));
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//fprintf(stderr, "input[%d] = %u, sinearest = %u, socorrect = %u, sodiff = %u, ndiff = %f, ndiff_rad[i] = %f, ndiff_rad_mean = %f\n", i, input[i], sinearest, socorrect, sodiff, ndiff, ndiff_rad[i], ndiff_rad_mean);
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//fprintf(stderr, "input[%d] = %u, sinearest = %u, socorrect = %u, sodiff = %u, ndiff = %f, ndiff_rad[i] = %f, ndiff_rad_mean = %f\n", i, input[i], sinearest, socorrect, sodiff, ndiff, ndiff_rad[i], ndiff_rad_mean);
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}
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}
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//fprintf(stderr, "ndiff_rad_mean = %f\n", ndiff_rad_mean);
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fprintf(stderr, "ndiff_rad_mean = %f\n", ndiff_rad_mean);
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float result = 0;
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float result = 0;
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for(int i=0;i<input_size;i++) result+=(powf(ndiff_rad[i]-ndiff_rad_mean,2))/(input_size-1);
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for(int i=0;i<input_size;i++) result+=(powf(ndiff_rad[i]-ndiff_rad_mean,2))/(input_size-1);
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