python_prosodizer/pdfFromClusters.py at master · dipack95/python_prosodizer · GitHub

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import numpy as np

import pandas as pd

import os

def main():

data = np.array(pd.read_csv("Docs/labelsAndPredictedLabels.csv", header=None, sep=' '))

printToFile = "Docs/trainingPDF.csv"

if os.path.isfile(printToFile):

os.remove(printToFile)

printToFileObj = open(printToFile, "a+")

# In Milliseconds

frameLength = 25

blockLength = 1000

jump = 250

numOfFrames = blockLength // frameLength

startIndex = 0

endIndex = numOfFrames

jumpIndex = jump // frameLength

numOfBlocks = np.ceil(data.shape[0] / jumpIndex - (numOfFrames // jumpIndex))

#numOfBlocks = np.ceil(data.shape[0] / numOfFrames)

weightOfEmotions = {}

clustersForEmotions = {}

for _ in range(np.int(numOfBlocks)):

'''

# NOTE: If the frames are not divisible by the numOfFrames,

# When it reaches the last block, since it is not of the exact size, it just takes how many ever values it can find,

# creating a block of less than the size that we want

'''

#print (startIndex, endIndex)

dataBlock = data[startIndex : endIndex, :]

dataBlockLabels = dataBlock[:, 0]

dataBlockClusters = dataBlock[:, 1]

emotions, emotionsCount = np.lib.arraysetops.unique(dataBlockLabels, return_counts=True)

clusters, clustersCount = np.lib.arraysetops.unique(dataBlockClusters, return_counts=True)

percentagesOfEmotions = {}

for i in range(len(emotionsCount)):

percentagesOfEmotions[emotions[i]] = (emotionsCount[i] / numOfFrames) * 100

if emotions[i] not in list(weightOfEmotions.keys()):

weightOfEmotions[emotions[i]] = percentagesOfEmotions[emotions[i]]

else:

weightOfEmotions[emotions[i]] += percentagesOfEmotions[emotions[i]]

percentagesOfClusters = {}

for i in range(len(clustersCount)):

percentagesOfClusters[clusters[i]] = (clustersCount[i] / numOfFrames) * 100

for i in range(len(emotions)):

for j in range(len(clusters)):

val = (percentagesOfEmotions[emotions[i]]) * percentagesOfClusters[clusters[j]]

tempKey = emotions[i] + '_' + str(clusters[j])

if tempKey not in list(clustersForEmotions.keys()):

clustersForEmotions[tempKey] = val

else:

clustersForEmotions[emotions[i] + '_' + str(clusters[j])] += val

# print(emotions[i], clusters[j], val)

# print(percentagesOfEmotions, percentagesOfClusters)

# print("------------NEXT BLOCK---------")

#startIndex += numOfFrames

#endIndex += numOfFrames

startIndex += jumpIndex

endIndex = startIndex + numOfFrames

# print(weightOfEmotions, clustersForEmotions)

for tempEmote in list(weightOfEmotions.keys()):

for tempEmotionCluster in list(clustersForEmotions.keys()):

if tempEmote in tempEmotionCluster:

stdWeight = clustersForEmotions[tempEmotionCluster] / weightOfEmotions[tempEmote]

print(tempEmotionCluster, stdWeight, file=printToFileObj)

printToFileObj.close()

if __name__ == '__main__':

main()

python_prosodizer/pdfFromClusters.py at master · dipack95/python_prosodizer · GitHub

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