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Top Forums UNIX for Beginners Questions & Answers Match patterns between two files and extract certain range of strings Post 303041964 by vgersh99 on Monday 9th of December 2019 11:44:45 AM
Old 12-09-2019
a bit verbose, but a possible starter.
awk -f bunny.awk inputfile2.txt inputfile1.fa where bunny.awk is:
Code:
function printRec() {
   #print a[f], s[f], e[f]
   for ( i in s) {
      split(i,t, OFS)
      if (f == ">" t[1])
        print ">" i ORS substr(a[f],s[i],e[i]-s[i]+1)
   }
   f=""
   split("",a)
}
FNR==NR {
   idx=$1 OFS $2 OFS $3
   s[idx]=$2
   e[idx]=$3
   next
}
/>/ && f {
   printRec()
}
f { a[f]=(f in a)?a[f] $1:$1 }
/^>/ { f=$1 }
END { printRec() }

results in:
Code:
>l-WR24-1:1 1 71
GCCGGCGTCGCGGTTGCTCGCGCTCTGGGCGCTGGCGGCTGTGGCTCTACCCGGCTCCGGGGCGGAGGGCG
>l-ZF385A-2:1 33 105
TGAGCTTCGGGTCACCGCCCCTCCAGAGGCTGAGTACTCAGGACTCGTCAGACACCCAGGGGTGAGATGAGAC
>l-YJC-1:1 1 161
GTCCCGCCCTCGCATGCGCCTGGTGGTCACCGCGGACGACTTTGGTTACTGCCCGCGACGCGATGAGGGTATCGTGGAGGCCTTTCTGGCCGGGGCTGTGACCAGCGTGTCCCTGCTGGTCAACGGTGCGGCCACGGAGAGCGCGGCGGAGCTGGCCCGCA
>l-YJC-1:1 1 165
GTCCCGCCCTCGCATGCGCCTGGTGGTCACCGCGGACGACTTTGGTTACTGCCCGCGACGCGATGAGGGTATCGTGGAGGCCTTTCTGGCCGGGGCTGTGACCAGCGTGTCCCTGCTGGTCAACGGTGCGGCCACGGAGAGCGCGGCGGAGCTGGCCCGCAGGCA


Last edited by vgersh99; 12-09-2019 at 12:51 PM..
This User Gave Thanks to vgersh99 For This Post:
 

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spectral-analysis(7)						  Numm Tutorials					      spectral-analysis(7)

NAME
spectral analysis - perform realtime spectral analysis SYNOPSIS
numm-run FILE DESCRIPTION
Frequency makes for a meaningful description of many audio signals. We can use numpy's fourier analysis to compute spectra from the micro- phone and display the results visually. We will break down the process into smaller parts: baby steps... First, create and save a skeletal file that moves a line across the screen: idx = 0 def video_out(a): global idx a[:,idx] = 255 idx = (idx + 1) % a.shape[1] def audio_in(a): pass Save this snippet and run it with numm-run. We will use the numpy.fft module for our analysis. First we define a function to get a particular frequency from the fourier transform: import numpy as np def get_freq(fourier, frequency): freqs = np.fft.fftfreq(len(fourier), 1/44100.0) nearest = (abs(freqs - frequency)).argmin() return abs(fourier[nearest]) Next, we hook up this function to audio input from the microphone. A frequency bin is chosen on a log scale for each row on the screen to display a spectogram. In total: import numpy as np idx = 0 recent_audio = np.zeros(4096, np.int16) recent_video = np.zeros((240,320,3), np.uint8) freq_bins = np.exp2(np.linspace(np.log2(27000),np.log2(27),240)) def get_freq(fourier, frequency): freqs = np.fft.fftfreq(len(fourier), 1/44100.0) nearest = (abs(freqs - frequency)).argmin() return abs(fourier[nearest]) def video_out(a): global idx fourier=np.fft.fft(recent_audio) values =np.array([get_freq(fourier,X) for X in freq_bins]) recent_video[:,idx,1] = (values/10000).clip(0,255) idx = (idx + 1) % a.shape[1] a[:] = np.roll(recent_video, -idx, axis=1) def audio_in(a): recent_audio[:] = np.roll(recent_audio, len(a)) recent_audio[:len(a)] = a.mean(axis=1) SEE ALSO
numm-run(1), numm.getting-started(7), numm.one-bit-instrument(7) numm February 2012 spectral-analysis(7)
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