def softMax(PoIs, Words, ArqOut, numeroPalavras, label): ArqOut = open(ArqOut,"wb") ArqOut.write(label + " ") # distances - Matriz n * V (número de pontos * número de palavras) que calculará apenas uma vez as distâncias distances = sp.cdist(PoIs, Words, 'euclidean') # first points, after codewords. Return a len(PoIs) x len(Words) matrix of distances distances = [ gaussiankernel(45.0, dist) for dist in numpy.reshape(distances, (1,distances.size))[0] ] # apply the gaussian kernel distances = numpy.reshape(distances, (len(PoIs), len(Words))) # put again in the format len(PoIs) x len(Words) # distToAll - Vetor que armazenará para cada ponto o somatório das distâncias para todas as palavras distToAll = [] for point in distances: distToAll.append(sum(point)) distToAll = numpy.asarray(distToAll) features = [] distances = numpy.transpose(distances) # transpose. Format len(Words) x len(PoIs) division = numpy.divide(distances, distToAll) # Equivalent to divide the distance of codeword i to PoI j by the summation of the distances of PoI j to all codewords features = [ max(dist) for dist in division ] # get the maximum activation for each codeword features = common_functions.l1norm(features) for f in features: ArqOut.write(str(f) + " ") ArqOut.close()
def softMax(PoIs, Words, ArqOut, numeroPalavras, label): ArqOut = open(ArqOut,"wb") ArqOut.write(label + " ") # distances - Matriz n * V (número de pontos * número de palavras) que calculará apenas uma vez as distâncias distances = sp.cdist(PoIs, Words, 'euclidean') # first points, after codewords. Return a len(PoIs) x len(Words) matrix of distances distances = [ gaussiankernel(45.0, dist) for dist in numpy.reshape(distances, (1,distances.size))[0] ] # apply the gaussian kernel distances = numpy.reshape(distances, (len(PoIs), len(Words))) # put again in the format len(PoIs) x len(Words) # distToAll - Vetor que armazenará para cada ponto o somatório das distâncias para todas as palavras distToAll = [] for point in distances: distToAll.append(sum(point)) distToAll = numpy.asarray(distToAll) features = [] distances = numpy.transpose(distances) # transpose. Format len(Words) x len(PoIs) division = numpy.divide(distances, distToAll) # Equivalent to divide the distance of codeword i to PoI j by the summation of the distances of PoI j to all codewords features = [ max(dist) for dist in division ] # get the maximum activation for each codeword features = common_functions.l1norm(features) for f in features: ArqOut.write(str(f) + " ") ArqOut.close()
def semiSoft(PoIs, Words, ArqOut, numeroPalavras, label): ArqOut = open(ArqOut,"wb") ArqOut.write(label + " ") distances = numpy.zeros(numeroPalavras) distances = sp.cdist(Words, PoIs, 'euclidean') # first codewords, after PoIs. Return a len(Words) x len(PoIs) matrix of distances distances = [ 1/min(d) for d in distances ] distances = common_functions.l1norm(distances) for d in distances: ArqOut.write(str(d) + " ") ArqOut.close()
def semiSoft(PoIs, Words, ArqOut, numeroPalavras, label):
ArqOut = open(ArqOut, "wb")
ArqOut.write(label + " ")
distances = numpy.zeros(numeroPalavras)
distances = sp.cdist(
Words, PoIs, 'euclidean'
) # first codewords, after PoIs. Return a len(Words) x len(PoIs) matrix of distances
distances = [1 / min(d) for d in distances]
distances = common_functions.l1norm(distances)
for d in distances:
ArqOut.write(str(d) + " ")
ArqOut.close()
def hardSum(PoIs, Words, ArqOut, numeroPalavras, label): ArqOut = open(ArqOut,"wb") ArqOut.write(label + " ") histograma = [0 for i in range(numeroPalavras)] distMatrix = sp.cdist(PoIs, Words, 'euclidean') # first points, after codewords. Return a len(PoIs) x len(Words) matrix of distances for i in range(len(PoIs)): minimum = min(distMatrix[i]) ind = numpy.where(distMatrix[i]==minimum)[0][0] histograma[ind] += 1 histograma = common_functions.l1norm(histograma) for h in histograma: ArqOut.write(str(h) + " ") ArqOut.close()
def hardSum(PoIs, Words, ArqOut, numeroPalavras, label): ArqOut = open(ArqOut,"wb") ArqOut.write(label + " ") histograma = [0 for i in range(numeroPalavras)] distMatrix = sp.cdist(PoIs, Words, 'euclidean') # first points, after codewords. Return a len(PoIs) x len(Words) matrix of distances for i in range(len(PoIs)): minimum = min(distMatrix[i]) ind = numpy.where(distMatrix[i]==minimum)[0][0] histograma[ind] += 1 histograma = common_functions.l1norm(histograma) for h in histograma: ArqOut.write(str(h) + " ") ArqOut.close()
