def useHier(topX, regX, R, hierIters, hierInner, regIters, regInner,
tensorInfo):
topY1, top1stats, top1mstats = CP_APR.cp_apr(topX,
R,
maxiters=hierIters,
maxinner=hierInner)
# reduce them to probability and then just sort them
topY1.normalize_sort(1)
topY1 = pmdTools.zeroSmallFactors(topY1, 1e-4)
### Use the factors to populate the factors
Udiag = np.zeros((len(tensorInfo['diag']), R))
Umed = np.zeros((len(tensorInfo['med']), R))
### Patient factors stays the same
for idx, diag in enumerate(tensorInfo['diag']):
topDiagIdx = tensorInfo['diagHier'][diag]
diagCount = tensorInfo['diagHierCount'][topDiagIdx]
Udiag[idx, :] = topY1.U[1][topDiagIdx, :] / diagCount
for idx, med in enumerate(tensorInfo['med']):
topMedIdx = tensorInfo['medHier'][med]
medCount = tensorInfo['medHierCount'][topMedIdx]
Umed[idx, :] = topY1.U[2][topMedIdx, :] / medCount
Mtop = ktensor.ktensor(np.ones(R), [topY1.U[0].copy(), Udiag, Umed])
Y1, ystats, mstats = CP_APR.cp_apr(X1,
R,
Minit=Mtop,
maxiters=regIters,
maxinner=regInner)
return Y1, topY1, top1stats, top1mstats, ystats, mstats
def useHier(topX, regX, R, hierIters, hierInner, regIters, regInner, tensorInfo):
topY1, top1stats, top1mstats = CP_APR.cp_apr(topX, R, maxiters=hierIters, maxinner=hierInner)
# reduce them to probability and then just sort them
topY1.normalize_sort(1)
topY1 = pmdTools.zeroSmallFactors(topY1, 1e-4)
### Use the factors to populate the factors
Udiag = np.zeros((len(tensorInfo['diag']), R))
Umed = np.zeros((len(tensorInfo['med']), R))
### Patient factors stays the same
for idx, diag in enumerate(tensorInfo['diag']):
topDiagIdx = tensorInfo['diagHier'][diag]
diagCount = tensorInfo['diagHierCount'][topDiagIdx]
Udiag[idx,:] = topY1.U[1][topDiagIdx,:] / diagCount
for idx, med in enumerate(tensorInfo['med']):
topMedIdx = tensorInfo['medHier'][med]
medCount = tensorInfo['medHierCount'][topMedIdx]
Umed[idx,:] = topY1.U[2][topMedIdx,:] / medCount
Mtop = ktensor.ktensor(np.ones(R), [topY1.U[0].copy(), Udiag, Umed])
Y1, ystats, mstats = CP_APR.cp_apr(X1, R, Minit=Mtop, maxiters=regIters, maxinner=regInner)
return Y1, topY1, top1stats, top1mstats, ystats, mstats
outfile = 'results/unique-hier-db-{0}-{1}.csv'
rawTopFile = 'results/unique-hier-top-raw-{0}-{1}.dat'
rawRegFile = 'results/unique-hier-reg-raw-{0}-{1}.dat'
yaxis = [np.array(tensorInfo['pat']), np.array(tensorInfo['diag']), np.array(tensorInfo['med'])]
modelOut = file("results/uniq-hier-{0}.sql".format(exptID), "w")
for i in range(totalIter):
# set the seed for repeatability
np.random.seed(seedArray[i])
yreg, ytop, ytopstats, ytopMstats, yregstats, yregMstats = useHier(topX1, X1, R, hierIters, innerIters, regIters, innerIters, tensorInfo)
yreg.writeRawFile(rawRegFile.format(exptID, i))
ytop.writeRawFile(rawTopFile.format(exptID, i))
yreg.normalize_sort(1)
yreg = pmdTools.zeroSmallFactors(yreg, 1e-4)
yfile = outfile.format(exptID, i)
__writeDBFile(yreg, yfile, yaxis, exptID, i)
mstats = yregMstats
modelOut.write("insert into joyceho.tensor_uniq_models values({0},{1},{2},\'{3}\',{4},{5},{6},{7},{8});\n".format(exptID, i, labelID, expt_desc, hierIters+regIters, innerIters, mstats['LS'], mstats['LL'], mstats['KKT']))
modelOut.write("load client from /home/joyceho/workspace/tensor/{0} of del modified by coldel| insert into joyceho.tensor_uniq_results;\n".format(yfile))
yTopFactor.append(ytop)
yRegFactor.append(yreg)
yTopStats.append(ytopstats)
yRegStats.append(yregstats)
mTopStats.append(ytopMstats)
mRegStats.append(yregMstats)
## Calculate all the scores
np.array(tensorInfo['pat']),
np.array(tensorInfo['diag']),
np.array(tensorInfo['med'])
]
modelOut = file("results/uniq-hier-{0}.sql".format(exptID), "w")
for i in range(totalIter):
# set the seed for repeatability
np.random.seed(seedArray[i])
yreg, ytop, ytopstats, ytopMstats, yregstats, yregMstats = useHier(
topX1, X1, R, hierIters, innerIters, regIters, innerIters, tensorInfo)
yreg.writeRawFile(rawRegFile.format(exptID, i))
ytop.writeRawFile(rawTopFile.format(exptID, i))
yreg.normalize_sort(1)
yreg = pmdTools.zeroSmallFactors(yreg, 1e-4)
yfile = outfile.format(exptID, i)
__writeDBFile(yreg, yfile, yaxis, exptID, i)
mstats = yregMstats
modelOut.write(
"insert into joyceho.tensor_uniq_models values({0},{1},{2},\'{3}\',{4},{5},{6},{7},{8});\n"
.format(exptID, i, labelID, expt_desc, hierIters + regIters,
innerIters, mstats['LS'], mstats['LL'], mstats['KKT']))
modelOut.write(
"load client from /home/joyceho/workspace/tensor/{0} of del modified by coldel| insert into joyceho.tensor_uniq_results;\n"
.format(yfile))
yTopFactor.append(ytop)
yRegFactor.append(yreg)
yTopStats.append(ytopstats)