allData = []
for l in range(len(assigned)):
tmpClust = analysis.projectList(assigned[l], u)
projections.classify(tmpClust, l + startClassify)
allData += tmpClust
return allData
if __name__ == "__main__":
tmpd = dataio.loadData(dataDirectory)
assigned = make_assigned(tmpd.projList)
u = lsa_reduce(assigned)
data = apply_projection(assigned, u)
nd = classify_data(assigned, data, tmpd.centers)
#tmpd2 = dataio.loadData(dataDirectory2)
#assigned2 = make_assigned(tmpd2.projList[:40])
#data2 = apply_projection(assigned2, u, 2)
#nd2 = classify_data(assigned2, data2, tmpd.centers)
#for l in range(len(nd)):
# nd[l] += nd2[l]
t = visualizer.plotPoints(nd)
lsaVector.append(lsaData.pwz[:, 3])
lsaVector.append(lsaData.pwz[:, 4])
#Stip down to the optimal number }
#for i in range (0, numVectors):
# lsaVector.append(lsaData.pwz[:, index[i]])
#lsaVector.append(lsaData.pwz[:, i])
projections = []
for v in lsaVector:
projections.append([])
for d in dVector:
projections[-1].append(analysis.lsaProjection(d, v))
pr = []
for s in range(len(projections[0])):
tmp = []
for r in range(len(projections)):
tmp.append(projections[r][s])
pr.append(tmp)
pointsPlot = [[] for i in range(2)]
numtosplit = 20
dim = 2
for s in range(len(times)):
spot = int(s / numtosplit)
pointsPlot[spot].append((pr[s][0:dim], str(times[s])))
visualizer.plotPoints(pointsPlot)
lsaVector.append(lsaData.pwz[:, 3])
lsaVector.append(lsaData.pwz[:, 4])
#Stip down to the optimal number }
#for i in range (0, numVectors):
# lsaVector.append(lsaData.pwz[:, index[i]])
#lsaVector.append(lsaData.pwz[:, i])
projections = []
for v in lsaVector:
projections.append([])
for d in dVector:
projections[-1].append(analysis.lsaProjection(d, v))
pr = []
for s in range(len(projections[0])):
tmp = []
for r in range(len(projections)):
tmp.append(projections[r][s])
pr.append(tmp)
pointsPlot = [[] for i in range(2)]
numtosplit = 20
dim = 2
for s in range(len(times)):
spot = int(s / numtosplit)
pointsPlot[spot].append((pr[s][0:dim], str(times[s])))
visualizer.plotPoints(pointsPlot)
