dumpingFeaturesForClustering_25ms.py

import pandas as pd
import numpy as np
import scipy.io.wavfile as wav
import matplotlib.pyplot as plt
import os
import math
import scipy
from scipy.stats import f
from scipy import stats

np.set_printoptions(threshold=np.inf)

def print_features(localFile, dumpFile):
    mfcc = np.nan_to_num(np.array(pd.read_csv(localFile + '_mfcc.csv', header=None), dtype='float64'))
    energy = np.nan_to_num(np.array(pd.read_csv(localFile + '_energyOfFrames.csv', header=None), dtype='float64'))[0][:-1]
    labels = np.array(pd.read_csv(localFile + '_labels.csv', header=None))[:, 1]

    if mfcc.shape[0] != len(labels):
        print("The number of data frames in the MFCC CSV, and the number of labels for frames, are not equal. MFCC Shape:", mfcc.shape, "Number of labels:", len(labels))
        return
        
    avgOfMfcc = np.mean(mfcc, axis = 0)
    
    j = 0
    for tempMfcc in mfcc:
        for i in range(len(tempMfcc)):
            tempMfcc[i] = (tempMfcc[i] - avgOfMfcc[i])
        print(labels[j], tempMfcc[0], tempMfcc[1], tempMfcc[2], tempMfcc[3], tempMfcc[4], tempMfcc[5], tempMfcc[6], tempMfcc[7], tempMfcc[8], tempMfcc[9], file=dumpFile)
        j += 1

    return

def main():

    printToFileNameMen = "Docs/men_angry_neutral_mfcc.csv"
    printToFileNameWomen = "Docs/women_angry_neutral_mfcc.csv"
    
    if os.path.isfile(printToFileNameMen):
        os.remove(printToFileNameMen)
    if os.path.isfile(printToFileNameWomen):
        os.remove(printToFileNameWomen)

    menFiles = np.ravel(np.array(pd.read_csv('Docs/filenames/men_filenames.csv', header=None)))
    womenFiles = np.ravel(np.array(pd.read_csv('Docs/filenames/women_filenames.csv', header=None)))
    for filename in menFiles:
        if filename[0] == "#":
            continue
        else:
            printToFile = open(printToFileNameMen, "a+")
            print(filename)
            print_features(filename, printToFile)
    for filename in womenFiles:
        if filename[0] == "#":
            continue
        else:
            printToFile = open(printToFileNameWomen, "a+")
            print(filename)
            print_features(filename, printToFile)

if __name__ == '__main__':
    main()