Maria@1: # -*- coding: utf-8 -*-
Maria@1: """
Maria@1: Created on Thu Feb 11 19:51:24 2016
Maria@1: 
Maria@1: @author: mariapanteli
Maria@1: """
Maria@1: """ Extract scale transform and pitch bihistogram descriptors"""
Maria@1: 
Maria@1: import os
Maria@1: import numpy
Maria@1: import pandas
Maria@1: import sys
Maria@1: sys.path.append('util')
Maria@1: import pitch_bihist as pbh
Maria@1: import scale_transform as stf
Maria@1: 
Maria@1: 
Maria@1: def extract_pitch_bihist(filenames):
Maria@1:     """ compute pitch bihistogram feature for each audio file in filenames
Maria@1:     """
Maria@1:     melf = []
Maria@1:     for filename in filenames:
Maria@1:         print filename
Maria@1:         pb = pbh.PitchBihist()
Maria@1:         pbihist = pb.get_pitchbihist(filename=filename)
Maria@1:         average_frame = numpy.nanmean(pbihist.T, axis=0, keepdims=True)
Maria@1:         melf.append(average_frame)
Maria@1:     melf = numpy.concatenate(melf)
Maria@1:     return melf
Maria@1: 
Maria@1: 
Maria@1: def extract_scale_transform(filenames):
Maria@1:     """ compute scale transform feature for each audio file in filenames
Maria@1:     """
Maria@1:     rhyf = []
Maria@7:     for filename in filenames:
Maria@1:         print filename
Maria@1:         st = stf.ScaleTransform()
Maria@1:         stransf = st.get_scale_transform(filename=filename)
Maria@1:         average_frame = numpy.nanmean(stransf.T, axis=0, keepdims=True)
Maria@1:         rhyf.append(average_frame)
Maria@1:     rhyf = numpy.concatenate(rhyf)
Maria@1:     return rhyf
Maria@1: 
Maria@1: 
Maria@1: if __name__ == '__main__':
Maria@1:     # Load metadata to get audio filenames
Maria@1:     df = pandas.read_csv(os.path.join('data','Metadata.csv'))
Maria@1:     filenames = df["filename"].get_values()
Maria@1:     
Maria@1:     # Specify audio directory and append to audio filenames
Maria@1:     filenames_mel = [os.path.join('audio','melodies', ff) for ff in filenames]
Maria@1:     filenames_rhy = [os.path.join('audio','rhythms', ff) for ff in filenames]
Maria@1:     
Maria@1:     pitch_bihist = extract_pitch_bihist(filenames_mel)
Maria@1:     scale_transform = extract_scale_transform(filenames_rhy)
Maria@1:     
Maria@1:     # Save .csv where rows = n_files, columns = n_features
Maria@1:     write_file = False
Maria@1:     if write_file:
Maria@1:         numpy.savetxt(os.path.join('data', 'PB.csv'), pitch_bihist, delimiter=',', fmt='%10.12f')
Maria@1:         numpy.savetxt(os.path.join('data', 'ST.csv'), scale_transform, delimiter=',', fmt='%10.12f')