inputFile = args.inputFile.format("data")
yaxis = decompTools.loadAxisInfo(args.inputFile.format("info"))
print "Starting Tensor Factorization with ID:{0}".format(exptID)
np.random.seed(seed)
Y, ystats, mstats = decompTools.decomposeCountTensor(inputFile,
R,
outerIters=iter,
innerIters=innerIter,
convergeTol=tol,
zeroTol=zeroThr)
Y.writeRawFile("results/apr-raw-{0}.dat".format(exptID))
Youtfile = "results/apr-db-{0}-{1}.csv".format(exptID, iter)
Ysqlfile = "results/apr-sql-{0}.sql".format(exptID)
# save the decomposition into the format
Yout = decompTools.getDBOutput(Y, yaxis)
Yout = np.column_stack((np.repeat(exptID, Yout.shape[0]), Yout))
np.savetxt(Youtfile, Yout, fmt="%s", delimiter="|")
sqlOut = file(Ysqlfile, "w")
sqlOut.write(
"load data local infile '/home/joyce/workspace//Health/analysis/tensor/{0}' into table tensor_factors fields terminated by '|' ;\n"
.format(Youtfile))
sqlOut.write(
"insert into tensor_models(expt_ID, label_ID, description, rank, iterations, inner_iterations, seed, least_squares, log_likelihood, kkt_violation) values({0}, {1}, \'{2}\', {3}, {4}, {5}, {6}, {7}, {8}, {9});\n"
.format(exptID, labelID, exptDesc, R, iter, innerIter, seed, mstats['LS'],
mstats['LL'], mstats['KKT']))
sqlOut.close()
print "Completed Tensor Factorization with ID:{0}".format(exptID)
print "Import sql file " + Ysqlfile
idx = np.flatnonzero(pf[:, 0])
dbOut = np.column_stack((axis[idx], np.repeat(0, len(idx)), pf[idx, 0]))
for col in range(1, factors):
idx = np.flatnonzero(pf[:, col])
dbOut = np.vstack((dbOut, np.column_stack((axis[idx], np.repeat(col, len(idx)), pf[idx, col]))))
return dbOut
refX = sptensor.loadTensor(inputFile.format(0, "data"))
refAxis = decompTools.loadAxisInfo(inputFile.format(0, "info"))
## Find the factors for the first one
klp, M, mstats = findFactors(refX, R=rank, outerIter=outerIter, innerIter=10)
## Store off the factors to be loaded into a database
M.writeRawFile(MrawFile)
Mout = decompTools.getDBOutput(M, refAxis)
Mout = np.column_stack((np.repeat(exptID, Mout.shape[0]), Mout))
np.savetxt(Moutfile, Yout, fmt="%s", delimiter="|")
sqlOut = file(Ysqlfile, "w")
## write the factors and the models into the database
sqlOut.write(
"load client from /home/joyceho/workspace/tensor/{0} of del modified by coldel| insert into joyceho.tensor_factors;\n".format(
Youtfile
)
)
sqlOut.write(
"insert into joyceho.tensor_models values({0}, {1}, '{2}','{3}', {4}, {5}, {6}, {7}, {8});\n".format(
exptID, labelID, patientSet, exptDesc, iter, innerIter, mstats["LS"], mstats["LL"], mstats["KKT"]
)
)
sqlOutfile = "results/rank-sql-{0}.sql".format(exptID)
rawFilePattern = "results/rank-raw-{0}-{1}.dat"
dbOutPattern = "results/rank-db-{0}-{1}.dat"
dbTimePattern = "results/rank-time-db-{0}-{1}.dat"
print "Starting Tensor Rank Experiment with ID:{0}".format(exptID)
sqlOut = file(sqlOutfile, "w")
for r in R:
np.random.seed(seed)
Y, ystats, mstats = decompTools.decomposeCountTensor(inputFile, R=r, outerIters=iter, innerIters=innerIter, convergeTol=tol, zeroTol=zeroThr)
Y.writeRawFile(rawFilePattern.format(exptID, r)) # output the raw file
# output the saved db file
dbYFile = dbOutPattern.format(exptID, r)
Yout = decompTools.getDBOutput(Y, yaxis)
Yout = np.column_stack((np.repeat(exptID, Yout.shape[0]), Yout))
np.savetxt(dbYFile, Yout, fmt="%s", delimiter="|")
sqlOut.write("load client from /home/joyceho/workspace/tensor/{0} of del modified by coldel| insert into joyceho.tensor_rank_factors;\n".format(dbYFile))
# output the rank_times
timeStats = np.delete(ystats, range(2,6), axis=1)
timeStats = np.column_stack((np.repeat(exptID, timeStats.shape[0]), np.repeat(r, timeStats.shape[0]), timeStats))
timeFile = dbTimePattern.format(exptID, r)
np.savetxt(timeFile, timeStats, delimiter="|")
sqlOut.write("load client from /home/joyceho/workspace/tensor/{0} of del modified by coldel| insert into joyceho.tensor_rank_times;\n".format(timeFile))
# output the model results
sqlOut.write("insert into joyceho.tensor_rank_models values({0},{1},\'{2}\',{3},{4},{5},{6},{7},{8});\n".format(exptID, labelID, exptDesc, iter, innerIter, r, mstats['LS'], mstats['LL'], mstats['KKT']))
sqlOut.close()
print "Complete Tensor Rank Experiment with ID:{0}".format(exptID)
print "Import sql file " + sqlOutfile
idx = np.flatnonzero(pf[:, col])
dbOut = np.vstack(
(dbOut,
np.column_stack((axis[idx], np.repeat(col, len(idx)), pf[idx,
col]))))
return dbOut
refX = sptensor.loadTensor(inputFile.format(0, "data"))
refAxis = decompTools.loadAxisInfo(inputFile.format(0, "info"))
## Find the factors for the first one
klp, M, mstats = findFactors(refX, R=rank, outerIter=outerIter, innerIter=10)
## Store off the factors to be loaded into a database
M.writeRawFile(MrawFile)
Mout = decompTools.getDBOutput(M, refAxis)
Mout = np.column_stack((np.repeat(exptID, Mout.shape[0]), Mout))
np.savetxt(Moutfile, Yout, fmt="%s", delimiter="|")
sqlOut = file(Ysqlfile, "w")
## write the factors and the models into the database
sqlOut.write(
"load client from /home/joyceho/workspace/tensor/{0} of del modified by coldel| insert into joyceho.tensor_factors;\n"
.format(Youtfile))
sqlOut.write(
"insert into joyceho.tensor_models values({0}, {1}, \'{2}\',\'{3}\', {4}, {5}, {6}, {7}, {8});\n"
.format(exptID, labelID, patientSet, exptDesc, iter, innerIter,
mstats['LS'], mstats['LL'], mstats['KKT']))
output = np.zeros((1, 4))
for i in timeRange:
