def _f_cover(self, bInd): vector_o = self.multiDocs.meanVector vector_os = self.multiDocs.getMeanVectorOfSolution(bInd) cover = helper.cosin(vector_o, vector_os) t = 0 for i in xrange(self.multiDocs.numOfSentences): if bInd[i] == 1: t += helper.cosin(vector_o, self.multiDocs.getSentenceVector(i)) return cover * t
def _f_diver(self, bInd): f_diver = 0.0 for i in xrange(self.multiDocs.numOfSentences-1): vector_i = self.multiDocs.getSentenceVector(i) for j in xrange(i+1, self.multiDocs.numOfSentences): if bInd[i] == 1 and bInd[j] == 1: vector_j = self.multiDocs.getSentenceVector(j) f_diver += helper.cosin(vector_i, vector_j) return f_diver
def _calCosinMatrix(self): ''' calculate cosin similarity matrix between sentences ''' self.cosinMatrix = [[0]*self.numOfSentences for _ in xrange(self.numOfSentences)] for i in xrange(self.numOfSentences-1): vector_i = self.tfisfVectors[i] for j in xrange(i+1, self.numOfSentences): vector_j = self.tfisfVectors[j] # calculate cosin self.cosinMatrix[i][j] = self.cosinMatrix[j][i] = helper.cosin(vector_i, vector_j)
def _calCosinMatrix(self): ''' calculate cosin similarity matrix between sentences ''' self.cosinMatrix = [[0] * self.numOfSentences for _ in xrange(self.numOfSentences)] for i in xrange(self.numOfSentences - 1): vector_i = self.tfisfVectors[i] for j in xrange(i + 1, self.numOfSentences): vector_j = self.tfisfVectors[j] # calculate cosin self.cosinMatrix[i][j] = self.cosinMatrix[j][i] = helper.cosin( vector_i, vector_j)