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cba14e4782
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9e7c18930f
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@ -27,11 +27,10 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
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# remove high_pitched/low-pitched frequencies
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# remove high_pitched/low-pitched frequencies
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minfreq = 110
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minfreq = 110
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maxfreq = 440*6
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maxfreq = 440*8
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# cutting the song to only keep the one we're interested in
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# cutting the song to only keep the one we're interested in
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subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen), "-i", song_name, "crop.wav"], shell=False)
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subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen+offset), "-i", song_name, "crop.wav"], shell=False)
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subprocess.run(["clear"])
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# extracting data from cropped song
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# extracting data from cropped song
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sample_rate, raw_song_data = wavfile.read("crop.wav")
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sample_rate, raw_song_data = wavfile.read("crop.wav")
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@ -51,9 +50,6 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
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else:
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else:
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song_data = raw_song_data
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song_data = raw_song_data
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print("\nSampleRate : ", sample_rate)
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print("SegSize : ", blit)
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# remove the copy of the song
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# remove the copy of the song
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subprocess.run(["rm", "crop.wav"], shell=False)
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subprocess.run(["rm", "crop.wav"], shell=False)
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@ -81,7 +77,6 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
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# calculate the fft, append it to fft_list
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# calculate the fft, append it to fft_list
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pff = scp.fft.rfft(song_data[int(current_time*sample_rate):int(sample_rate*(current_time+segsize))])
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pff = scp.fft.rfft(song_data[int(current_time*sample_rate):int(sample_rate*(current_time+segsize))])
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fft_list.append(pff)
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fft_list.append(pff)
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#print("(k =", k, ") :", left_id, "to", right_id)
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# just to avoid what causes 0.1 + 0.1 == 0.2 to be False
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# just to avoid what causes 0.1 + 0.1 == 0.2 to be False
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k += 1
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k += 1
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@ -103,7 +98,7 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
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current_fmax = 0
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current_fmax = 0
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for j in range(len(fft_list[i])):
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for j in range(len(fft_list[i])):
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if(j < len(pfreq) and pfreq[j] < maxfreq and pfreq[j] >= minfreq and np.abs(fft_list[i][j]) > current_max):
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if(pfreq[j] < maxfreq and pfreq[j] >= minfreq and np.abs(fft_list[i][j]) > current_max):
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current_max = np.abs(fft_list[i][j])
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current_max = np.abs(fft_list[i][j])
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current_fmax = pfreq[j]
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current_fmax = pfreq[j]
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@ -116,10 +111,17 @@ def retrieve_dominant_freqs(song_name, offset, songlen, segsize):
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def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampthr, output_name):
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def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampthr, output_name):
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# removes unnecessary frequencies/amps from a song
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# removes unnecessary frequencies/amps from a song
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# ampthr is in [0, 1]
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#ampthr is in [0, 1]
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# remove high_pitched/low-pitched frequencies
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minfreq = 110
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maxfreq = 440*8
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# cutting the song to only keep the one we're interested in
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subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen+offset), "-i", song_name, "crop.wav"], shell=False)
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# extracting data from cropped song
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# extracting data from cropped song
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sample_rate, raw_song_data = wavfile.read(song_name)
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sample_rate, raw_song_data = wavfile.read("crop.wav")
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blit = int(sample_rate*segsize) # Te
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blit = int(sample_rate*segsize) # Te
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song_data = [0 for i in range(len(raw_song_data))]
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song_data = [0 for i in range(len(raw_song_data))]
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@ -206,15 +208,13 @@ def void_freq_clean(song_name, offset, songlen, segsize, minfreq, maxfreq, ampth
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res = np.array(res)
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res = np.array(res)
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wavfile.write(output_name, sample_rate, res)
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wavfile.write(output_name, sample_rate, res)
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def retrieve_dominant_amps(song_name, offset, songlen, segsize, percent, divlen):
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def retrieve_dominant_amps(song_name, offset, songlen, segsize, percent):
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# returns a list with the percent% peak amplitudes alongside the sample rate
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# returns a list with the percent% peak amplitudes alongside the sample rate
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# /!\ song_name is specified to be a list, NOT a list of couples (aka song is mono)
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# /!\ song_name is specified to be a list, NOT a list of couples (aka song is mono)
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# segsize is in seconds
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# segsize is in seconds
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# divlen is in seconds
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# cutting the song to only keep the one we're interested in
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# cutting the song to only keep the one we're interested in
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subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen), "-i", song_name, "crop.wav"], shell=False)
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subprocess.run(["ffmpeg", "-ss", str(offset), "-t", str(songlen+offset), "-i", song_name, "crop.wav"], shell=False)
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subprocess.run(["clear"])
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# extracting data from cropped song
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# extracting data from cropped song
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sample_rate, raw_song_data = wavfile.read("crop.wav")
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sample_rate, raw_song_data = wavfile.read("crop.wav")
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@ -239,24 +239,12 @@ def retrieve_dominant_amps(song_name, offset, songlen, segsize, percent, divlen)
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is_locked = [False for i in range(len(song_data))]
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is_locked = [False for i in range(len(song_data))]
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x = int((len(song_data)*percent)//100)
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x = int((len(song_data)*percent)//100)
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# length of segments
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seglen = int(divlen*sample_rate)
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# current offset
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curptr = 0
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print("Retreiving the", int(x), "/", len(song_data), "highest values")
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print("Retreiving the", int(x), "/", len(song_data), "highest values")
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while(curptr < len(song_data)):
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elements = heapq.nlargest(int(x), enumerate(song_data), key=lambda x: x[1])
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left = curptr
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#returns a list of couples [id, value]
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right = min(len(song_data), curptr+seglen)
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#returns a list of couples [id, value]
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for idx in range(len(elements)):
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elements = heapq.nlargest(int(x), enumerate(song_data[left:right]), key=lambda x: x[1])
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is_locked[elements[idx][0]] = True
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for idx in range(len(elements)):
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is_locked[elements[idx][0]+left] = True
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curptr += seglen
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for r in range(len(song_data)):
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for r in range(len(song_data)):
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if(is_locked[r] == False):
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if(is_locked[r] == False):
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@ -303,7 +291,7 @@ def convert_to_wav(song_name:str, output_file="audio.wav") -> str:
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return output_file
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return output_file
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return song_name
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return song_name
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def retrieve_all_from_song(filename, t0, t1, bpm, dta=0.001, dtf=0.01, threshold=0.06, show=True):
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def retrieve_all_from_song(filename, t0, t1, dt=0.001, threshold=0.1):
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# dt = sample interval
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# dt = sample interval
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# threshold is in percent
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# threshold is in percent
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@ -314,37 +302,37 @@ def retrieve_all_from_song(filename, t0, t1, bpm, dta=0.001, dtf=0.01, threshold
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# converts format to .wav
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# converts format to .wav
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new_fn = convert_to_wav(filename)
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new_fn = convert_to_wav(filename)
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# crop the song to the part that will be mapped
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subprocess.run(["ffmpeg", "-ss", str(t0), "-t", str(t1), "-i", new_fn, "crop0.wav"], shell=False)
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subprocess.run(["clear"])
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sample_rate, _ = wavfile.read("crop0.wav")
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print("Filtering song...")
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print("Filtering song...")
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#void_freq_clean(new_fn, t0, t1-t0, dt, 200, 2500, 0.05, "crop1.wav")
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void_freq_clean(new_fn, t0, t1-t0, dt, 200, 2500, 0.05, "crop1.wav")
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print("Now retrieving the frequencies")
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print("Now retrieving the frequencies")
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(maxlist, maxamps) = retrieve_dominant_freqs(new_fn, t0, t1, dtf)
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(maxlist, maxamps) = retrieve_dominant_freqs(new_fn, t0, t1-t0, dt)
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print("Now retrieving the amplitudes")
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print("Now retrieving the amplitudes")
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amps = retrieve_dominant_amps(new_fn, t0, t1, dta, threshold, 4/(bpm/60))
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amps = retrieve_dominant_amps(new_fn, t0, t1-t0, dt, threshold)
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print("Len of freqs : ", len(maxlist), "|", len(maxamps))
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print("Len of freqs : ", len(maxlist), "|", len(maxamps))
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print("Len of amps : ", len(maxlist), "|", len(amps))
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print("Len of amps : ", len(maxlist), "|", len(amps))
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maxa = amps[0]
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timesF = [t0 + dt*k for k in range(len(maxlist))]
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for jj in amps:
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timesA = [t0 + dt*k for k in range(len(amps))]
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if(jj > maxa):
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maxa = jj
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for i in range(len(amps)):
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plt.plot(timesF, maxlist)
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amps[i] = (amps[i] * 2000) / maxa
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plt.show()
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if(show):
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plt.plot(timesA, amps)
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timesF = [t0 + dtf*k for k in range(len(maxlist))]
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plt.show()
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timesA = [t0 + dta*k for k in range(len(amps))]
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plt.plot(timesA, amps)
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plt.plot(timesF, maxlist)
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plt.show()
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# free()
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# free()
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subprocess.run(["rm", "crop0.wav"], shell=False)
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retrieve_all_from_song("ctype.mp3", 0, 5, 149.3, dtf=1/(149.3/60)/8)
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retrieve_all_from_song("tetris_4.wav", 0, 5)
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print("yipee")
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print("yipee")
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BIN
tetris_2.wav
BIN
tetris_2.wav
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