def getTranscribedPatterns(ptr = ['TA', 'TA', 'KI', 'TA']):
    """
    Gets the transcribed sequences for the pattern (ptr) provided bsed on the onset information in the transcribed data.
    """
    result = []
    l = len(ptr)
    # Getting the masterdata
    config = ut.loadConfig('/home/swapnil/SMC/MasterThesis/gitPercPatterns/code/rlcs/config')
    transFolder = config['transFolder']
    #transFolder = '/home/swapnil/Desktop/temp'
    lblDir = config['lblDir']
    onsDir = config['onsDir']
    masterData = ut.getAllSylbData(tPath = transFolder, lblDir = lblDir, onsDir = onsDir)
    
    # Find the start and the end point of patters in
    for comp in masterData:
        compName = comp[2]
        print 'Working for composition:' + compName
        transScore = comp[0][0]
        transOnset = comp[0][1]
        origScore = comp[1][0]
        origOnset = comp[1][1]

        # Get the starting indices for the pattern in the composition comp
        ptrStartIndices = ut.getSubstringPos(origScore, ptr)

        # Get the dictionaries of set for the indices of patterns in the ground truth
        dictPtrIndices = populateDictPtrIndices(ptrStartIndices, l)

        # Get the closest set onsets for the pattern in the transcription
        ptrIndicesInTrans = getIndicesInTrans(origOnset, transOnset, dictPtrIndices)
        ptrnsInTrans = getPatternsInTrans(transScore, ptrIndicesInTrans)
        result.append((compName, ptrnsInTrans))

    return result
    baseline = True



#similarityListFile = os.path.join(sylbSimFolder,'simMatList.txt')
#similarityList = [line.strip().split('.')[0] for line in open(similarityListFile)]
# For correctness check
#similarityList = ['TablaDB_3_kmeans_mahal'] # looks promising ....
#similarityList = ['KLMonteCarlo-5','KLMonteCarlo-6', 'KLMonteCarlo-7'] # looks promising ....
#similarityList = ['KLGaussApprox-3', 'KLGaussApprox-4', 'KLGaussApprox-5', 'KLGaussApprox-6', 'KLGaussApprox-7'] # looks promising ....
similarityList = ['binaryDistance'] # results without similarity
ignrSimList = ['TablaDB_10_GMM_euclidean']

simObject = None

masterData = ut.getAllSylbData(tPath = transFolder, lblDir = lblDir, onsDir = onsDir)

#simDict = ut.getSimilarityDict('/home/swapnil/SMC/MasterThesis/sylbSimilarity/TablaDBstrokes','/home/swapnil/SMC/MasterThesis/sylbSimilarity/results_mat/TablaDB_6_kmeans_euclidean.mat')

def getAccuracies(payload, tres = 70.0, fp = None):

    #fo.write('run.getAccuracies::')

    totalRelvRetrieved = 0
    totalRetrieved = 0
    totalRelevant = 0
    totalRelvRetrievedInGt = 0
    ptrInTransLen = [] # List for the length of all the patterns that are the candidate patterns 

    for inst in payload:
        retrieved = inst[0]