Takes an input directory containing wave files and splices them together into a morphagene reel

morphagene_directory.py

#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
USAGE: 
morphagene_directory.py -d <inputdirectory> -o <outputfile>'

Script will go through <inputdirectory> and splice all wave-files 
together in alphabetic order and place a marker in between.

Requires all wave-files in directory to have the same number of channels and bitrate!
    
Does not require input file to be 48000Hz, but .WAV-files must be stereo.
     
See the Morphagene manual for naming conventions of output files:    
    http://www.makenoisemusic.com/content/manuals/morphagene-manual.pdf
    
# see http://stackoverflow.com/questions/15576798/create-32bit-float-wav-file-in-python
# see... http://blog.theroyweb.com/extracting-wav-file-header-information-using-a-python-script
# marker code from Joseph Basquin [https://gist.github.com/josephernest/3f22c5ed5dabf1815f16efa8fa53d476]
"""

import sys, getopt
import struct
import numpy as np
from scipy import interpolate
import gzip
import os

def float32_wav_file(file_name, sample_array, sample_rate, 
                     markers=None, verbose=False):
    (M,N)=sample_array.shape
    #print "len sample_array=(%d,%d)" % (M,N)
    byte_count = M * N * 4 # (len(sample_array)) * 4  # 32-bit floats
    wav_file = ""
    # write the header
    wav_file += struct.pack('<ccccIccccccccIHHIIHH',
        'R', 'I', 'F', 'F',
        byte_count + 0x2c - 8,  # header size
        'W', 'A', 'V', 'E', 'f', 'm', 't', ' ',
        0x10,  # size of 'fmt ' header
        3,  # format 3 = floating-point PCM
        M,  # channels
        sample_rate,  # samples / second
        sample_rate * 4,  # bytes / second
        4,  # block alignment
        32)  # bits / sample
    wav_file += struct.pack('<ccccI',
        'd', 'a', 't', 'a', byte_count)
    if verbose:
        print("packing...")
    # flatten data in an alternating fashion 
    # see: http://soundfile.sapp.org/doc/WaveFormat/
    reordered_wav = [sample_array[k,j] for j in range(N) for k in range(M)]
    wav_file += struct.pack('<%df' % len(reordered_wav), *reordered_wav)
    if verbose:
        print("saving audio...")
    fid=open(file_name,'wb')
    for value in wav_file:
        fid.write(value)
    if markers:    # != None and != []
        if verbose:
            print("saving cue markers...")
        if isinstance(markers[0], dict):# then we have [{'position': 100, 'label': 'marker1'}, ...]
            labels = [m['label'] for m in markers]
            markers = [m['position'] for m in markers]
        else:
            labels = ['' for m in markers]
        fid.write(b'cue ')
        size = 4 + len(markers) * 24
        fid.write(struct.pack('<ii', size, len(markers)))
        for i, c in enumerate(markers):
            s = struct.pack('<iiiiii', i + 1, c, 1635017060, 0, 0, c)# 1635017060 is struct.unpack('<i',b'data')
            fid.write(s)
        lbls = ''
        for i, lbl in enumerate(labels):
            lbls += b'labl'
            label = lbl + ('\x00' if len(lbl) % 2 == 1 else '\x00\x00')
            size = len(lbl) + 1 + 4          # because \x00
            lbls += struct.pack('<ii', size, i + 1)
            lbls += label
        fid.write(b'LIST')
        size = len(lbls) + 4
        fid.write(struct.pack('<i', size))                         
        fid.write(b'adtl')# https://web.archive.org/web/20141226210234/http://www.sonicspot.com/guide/wavefiles.html#list
        fid.write(lbls) 
    fid.close()
 
def wav_file_read(filename,verbose=False):
    
    # read file and close
    fi=open(filename,'rb')
    data=fi.read()
    fi.close()
    # take raw data and read subsections for important format data
    A,B,C,D=struct.unpack('4c', data[0:4])      # 'RIFF'
    ChunkSize=struct.unpack('<l', data[4:8])[0]   #4+(8+SubChunk1Size)+8+SubChunk2Size)
    A,B,C,D=struct.unpack('4c', data[8:12])     # 'WAVE'
    A,B,C,D=struct.unpack('4c', data[12:16])    # 'fmt '
    
    Subchunk1Size=struct.unpack('<l', data[16:20])[0] # LITTLE ENDIAN, long, 16
    AudioFormat=struct.unpack('<h', data[20:22])[0] # LITTLE ENDIAN, short, 1
    NumChannels=struct.unpack('<h', data[22:24])[0] # LITTLE ENDIAN, short, Mono = 1, Stereo = 2
    SampleRate =struct.unpack('<l', data[24:28])[0] # LITTLE ENDIAN, long,  sample rate in samples per second
    ByteRate=struct.unpack('<l', data[28:32])[0] # self.SampleRate * self.NumChannels * self.BitsPerSample/8)) # (ByteRate) LITTLE ENDIAN, long
    BlockAlign=struct.unpack('<h', data[32:34])[0] # self.NumChannels * self.BitsPerSample/8))  # (BlockAlign) LITTLE ENDIAN, short
    BitsPerSample=struct.unpack('<h', data[34:36])[0] # LITTLE ENDIAN, short
    A,B,C,D=struct.unpack('4c', data[36:40])    # BIG ENDIAN, char*4
    SubChunk2Size=struct.unpack('<l', data[40:44])[0] # LITTLE ENDIAN, long
    waveData=data[44:]
    
    if verbose:
        print("ChunkSize     =%d\nSubchunk1Size =%d\nAudioFormat   =%d\nNumChannels   =%d\nSampleRate    =%d\nByteRate      =%d\nBlockAlign    =%d\nBitsPerSample =%d\nA:%c,  B:%c,  C:%c,  D:%c\nSubChunk2Size =%d" %
            (ChunkSize     , 
            Subchunk1Size, 
            AudioFormat   ,
            NumChannels   ,
            SampleRate    ,
            ByteRate      ,
            BlockAlign    ,
            BitsPerSample ,
            A,  B,  C,  D ,
            SubChunk2Size ))    
    # convert audio data to float based on bitdepth
    if BitsPerSample==8:
        if verbose:
            print("Unpacking 8 bits on len(waveData)=%d" % len(waveData))
        d=np.fromstring(waveData,np.uint8)
        floatdata=d.astype(np.float64)/np.float(127)    
    elif BitsPerSample==16:
        if verbose:
            print("Unpacking 16 bits on len(waveData)=%d" % len(waveData))
        d=np.zeros(SubChunk2Size/2, dtype=np.int16)
        j=0
        for k in range(0, SubChunk2Size, 2):
            d[j]=struct.unpack('<h',waveData[k:k+2])[0]
            j=j+1
        floatdata=d.astype(np.float64)/np.float(32767)    
    elif BitsPerSample==24:
        if verbose:
            print("Unpacking 24 bits on len(waveData)=%d" % len(waveData))
        d=np.zeros(SubChunk2Size/3,  dtype=np.int32)
        j=0
        for k in range(0, SubChunk2Size, 3):
            d[j]=struct.unpack('<l',struct.pack('c',waveData[k])+waveData[k:k+3])[0]
            j=j+1
        floatdata=d.astype(np.float64)/np.float(2147483647)    
    else: # anything else will be considered 32 bits
        if verbose:
            print("Unpacking 32 bits on len(waveData)=%d" % len(waveData))
        d=np.fromstring(waveData,np.int32)
        floatdata=d.astype(np.float64)/np.float(2147483647)  
    v=floatdata[0::NumChannels]
    for i in range(1,NumChannels):
        v=np.vstack((v,floatdata[i::NumChannels]))
    #return (np.vstack((floatdata[0::2],floatdata[1::2])), SampleRate, NumChannels, BitsPerSample)
    return (v, SampleRate, NumChannels, BitsPerSample)

def change_samplerate_interp(old_audio,old_rate,new_rate):
    '''
    Change sample rate to new sample rate by simple interpolation.
    If old_rate > new_rate, there may be aliasing / data loss.
    Input should be in column format, as the interpolation will be completed
        on each channel this way.
    Modified from:
    https://stackoverflow.com/questions/33682490/how-to-read-a-wav-file-using-scipy-at-a-different-sampling-rate
    '''    
    if old_rate != new_rate:
        # duration of audio
        duration = old_audio.shape[0] / old_rate
        
        # length of old and new audio
        time_old  = np.linspace(0, duration, old_audio.shape[0])
        time_new  = np.linspace(0, duration, int(old_audio.shape[0] * new_rate / old_rate))
        
        # fit old_audio into new_audio length by interpolation
        interpolator = interpolate.interp1d(time_old, old_audio.T)
        new_audio = interpolator(time_new).T
        return new_audio
    else:
        print('Conversion not needed, old and new rates match')
        return old_audio # conversion not needed

def main(argv):
    inputdirectory = ''
    outputfile = ''
    try:
        opts, args = getopt.getopt(argv,"hd:o:",["inputdirectory=","outputfile="])
    except getopt.GetoptError:
        print('Error in usage, correct format:\n'+\
            'morphagene_directory.py -d <inputdirectory> -o <outputfile>')
        sys.exit(2)
    for opt, arg in opts:
        if opt == '-h':
            print('morphagene_directory.py -d <inputdirectory> -o <outputfile>')
            sys.exit()
        elif opt in ("-d", "--inputdirectory"):
            inputdirectory = arg
        elif opt in ("-o", "--outputfile"):
            outputfile = arg
    print('Input directory: %s'%inputdirectory)
    print('Output Morphagene reel: %s'%outputfile)
    
    ###########################################################################
    '''
    Write single file, to Morphagene 32bit
        WAV file at 48000hz sample rate.
    '''
    ###########################################################################
    morph_srate = 48000 # required samplerate for Morphagene

    # find .wav-files in inputdirectory

    wavfiles = []

    entries = sorted(os.listdir(inputdirectory))
    for entry in entries:
        if entry.endswith('.wav'):
            wavfiles.append("{0}/{1}".format(inputdirectory,entry))

    first_num_channels = None
    first_bits_per_sample = None

    allwaves = None
    markers = []

    for wavfile in wavfiles:
        # read pertinent info from audio file, exit if input wave file is broken
        try:
            (array,sample_rate,num_channels,bits_per_sample)=wav_file_read(wavfile, verbose=False)
            if first_num_channels == None:
                first_num_channels = num_channels
                first_bits_per_sample = bits_per_sample
            else:
                if num_channels != first_num_channels or bits_per_sample != first_bits_per_sample:
                    print('All wave files must have the same number of channels and bitrate')
                    sys.exit()
        except: 
            print('Input .wav file %s is poorly formatted, exiting'%wavfile)
            sys.exit()

        # check if input wav has a different rate than desired Morphagene rate,
        #   and correct by interpolation
        if sample_rate != morph_srate:
            print("Correcting input sample rate %iHz to Morphagene rate %iHz"%(sample_rate,morph_srate))
            # perform interpolation on each channel, then transpose back
            array = change_samplerate_interp(array.T,float(sample_rate),float(morph_srate)).T

        if allwaves == None:
            allwaves = np.array(array)
            markers.append(len(array[0]))
        else:
            #for a in array:
            allwaves = np.concatenate((allwaves,array), axis=1)
            markers.append(len(array[0]) + markers[-1])
    
    markers.pop() # remove last marker
    
    # write wav file with additional cue markers from labels
    float32_wav_file(outputfile,allwaves,morph_srate,markers=markers)
    print('Saved Morphagene reel with %i splices: %s'%(len(markers)+1,outputfile))

if __name__ == "__main__":
   main(sys.argv[1:])

Good stuff! I feel like you should convert this from gist to repo elsewhere. I have some ideas to propose when I get some time later.

Great idea @nicksort, I was actually considering that too!