def computeR(doc, s, query): """compute different diversity features""" r1 = ldaIt(doc, s, query) docb, sb = bagwords(doc, s) r2 = CosineSimilarity().buildMat(docb, sb) doccn, scn = cn_field(doc, s) r3 = cnDistance(doccn, scn) return [r1, r2, r3]
def computeR(doc, s, query): """compute different diversity features""" r1 = ldaIt(doc, s, query) docb, sb = bagwords(doc, s) r2 = CosineSimilarity().buildMat(docb, sb) doccsd, scsd = feat_field(doc, s, "csd") r3 = l1Distance(doccsd, scsd) dochog, shog = feat_field(doc, s, "hog") r4 = batachariaDistance(dochog, shog) if 1: doccn, scn = feat_field(doc, s, "cn") r5 = eucDistance(doccn, scn) doccm, scm = feat_field(doc, s, "cm") r6 = canberraDistance(doccm, scm) doclbp, slbp = feat_field(doc, s, "lbp") r7 = chisquareDistance(doclbp, slbp) docglr, sglr = feat_field(doc, s, "glr") r8 = l1Distance(docglr, sglr) # or batachariaDistance else: doccn, scn = feat_field(doc, s, "cn3") r5 = eucDistance(doccn, scn) doccm, scm = feat_field(doc, s, "cm3") r6 = canberraDistance(doccm, scm) doclbp, slbp = feat_field(doc, s, "lbp3") r7 = chisquareDistance(doclbp, slbp) docglr, sglr = feat_field(doc, s, "glr3") r8 = l1Distance(docglr, sglr) # # or batachariaDistance return [r1, r2, r3, r4, r5, r6, r7, r8]