From 9ac9c6f724c16a172ecb923a0360bc9a9ffc3806 Mon Sep 17 00:00:00 2001 From: wukong Date: Tue, 25 Dec 2018 14:44:46 -0800 Subject: began merging windowing scripts; swapped std_dev and std_err in mean and mean_avg; --- fib.awk | 4 +++- gaussian.awk | 19 ++++++++++++++----- hamming.awk | 48 +++++++++++++++++++++++++++++++++--------------- lpf.awk | 5 +++-- mean.awk | 4 ++-- mean_avg.awk | 6 +++--- 6 files changed, 58 insertions(+), 28 deletions(-) diff --git a/fib.awk b/fib.awk index 654921c..0d46479 100644 --- a/fib.awk +++ b/fib.awk @@ -6,6 +6,8 @@ BEGIN { ARGV[1] ? n = ARGV[1] : n = 0 ARGV[2] ? OFMT = "%." ARGV[2] "g" : OFMT = "%g" - print (1/sqrt(5))*(0.5*(1 + sqrt(5)))^n - (1/sqrt(5))*(0.5*(1 - sqrt(5)))^n + C1 = 1.0/sqrt(5) + C2 = -1.0/sqrt(5) + print C1*(0.5*(1 + sqrt(5)))^n + C2*(0.5*(1 - sqrt(5)))^n } diff --git a/gaussian.awk b/gaussian.awk index 48c3f9a..dfb5fb4 100644 --- a/gaussian.awk +++ b/gaussian.awk @@ -4,19 +4,28 @@ # generate a Gaussian window # https://en.wikipedia.org/wiki/Window_function + +### Gaussian +function gaussian(n) { + # sigma <= 0.5 + sigma = 0.4 + en[n] = (n - M)/(sigma*M) + return exp(-0.5*e[n]*e[n]) +} + + BEGIN { ARGV[1] ? N = ARGV[1] : N = 0 ARGV[2] ? OFMT = "%." ARGV[2] "g" : OFMT = "%g" - M = 0.5*(N - 1) - # sigma <= 0.5 - sigma = 0.4 + # window interval goes from -M to M + M = 0.5*(N - 1) + pi = 4*atan2(1,1) for (n=0; n 1 && M > 0) { - e[n] = (n - M)/(sigma*M) - w[n] = exp(-0.5*e[n]*e[n]) + w[n] = gaussian(n) print n, w[n]/M } else { diff --git a/hamming.awk b/hamming.awk index f7ff9f7..acfde97 100644 --- a/hamming.awk +++ b/hamming.awk @@ -2,35 +2,52 @@ ### hamming.awk # generate a Hamming window +# R.W. Hamming, 'Digital Filters': H = '0.23 0.54 0.23' # https://en.wikipedia.org/wiki/Window_function provides a few values for the # 'a0' and 'a1' parameters of the raised cosine. -BEGIN { - ARGV[1] ? N = ARGV[1] : N = 0 - ARGV[2] ? OFMT = "%." ARGV[2] "g" : OFMT = "%g" +### Gaussian +function gaussian(n) { + # sigma <= 0.5 + sigma = 0.4 + e[n] = (n)/(sigma*M) + return exp(-0.5*e[n]*e[n]) +} - # window interval goes from -M to M - M = 0.5*(N - 1) - pi = 4*atan2(1,1) - ### R.W. Hamming, "Digital Filters" - # H = "0.23 0.54 0.23" +### Hamming, raised cosine +function hamming(n) { + ### optimal values for equal-ripple + #a0 = 0.53836 + #a1 = 0.46164 a0 = (25.0/46.0) a1 = (21.0/46.0) + return a0 + a1*cos((pi*n)/M) +} - ### optimal values for equal-ripple - #a0 = 0.53836 - #a1 = 0.46164 - ### VonHann - #a0 = 0.5 - #a1 = 0.5 +### vonHann, raised cosine +function vonhann(n) { + a0 = 0.5 + a1 = 0.5 + return a0 + a1*cos((pi*n)/M) +} + + +BEGIN { + + ARGV[1] ? N = ARGV[1] : N = 0 + ARGV[2] ? OFMT = "%." ARGV[2] "g" : OFMT = "%g" + + # window interval goes from -M to M + M = 0.5*(N - 1) + pi = 4*atan2(1,1) for (n=-M; n<=M; n++) { if (N > 1 && M > 0) { - w[n] = a0 + a1*cos((pi*n)/M) + w[n] = hamming(n) print n + M, w[n]/M } else { @@ -39,3 +56,4 @@ BEGIN { } } + diff --git a/lpf.awk b/lpf.awk index 814020f..aba92e1 100644 --- a/lpf.awk +++ b/lpf.awk @@ -5,6 +5,7 @@ BEGIN { OFS = FS + ARGV[1] ? OFMT = "%." ARGV[1] "g" : OFMT = "%g" sign = "[+-]?" decimal = "[0-9]+[.]?[0-9]*" fraction = "[.][0-9]*" @@ -28,7 +29,7 @@ NF > 0 { if (NF > nf_max) nf_max = NF - input_size = window_size + input_size = window_size output_size = (input_size + window_size - 1) ### columns @@ -72,7 +73,7 @@ NF > 0 { printf(OFS) else printf(ORS) - + } diff --git a/mean.awk b/mean.awk index b509473..816208c 100644 --- a/mean.awk +++ b/mean.awk @@ -30,7 +30,7 @@ NF > 0 { } END { - print "mean", "std_dev", "std_err", "count" - print mean, sqrt(var), sqrt(var/count), count + print "mean", "std_err", "std_dev", "count" + print mean, sqrt(var/count), sqrt(var), count } diff --git a/mean_avg.awk b/mean_avg.awk index 8a5a3c5..ed6f81a 100644 --- a/mean_avg.awk +++ b/mean_avg.awk @@ -34,12 +34,12 @@ NF > 0 { } END { - print "col", "mean", "std_dev", "std_err", "count" + print "col", "mean", "std_err", "std_dev", "count" for (n=1; n<=max_nf; n++) { if (header[n]) - print header[n], mean[n], sqrt(var[n]), sqrt(var[n]/count[n]), count[n] + print header[n], mean[n], sqrt(var[n]/count[n]), sqrt(var[n]), count[n] else - print "col" n, mean[n], sqrt(var[n]), sqrt(var[n]/count[n]), count[n] + print "col" n, mean[n], sqrt(var[n]/count[n]), sqrt(var[n]), count[n] } } -- cgit v1.2.3