maxLocalAuc.numProcesses = multiprocessing.cpu_count()
maxLocalAuc.numRecordAucSamples = 100
maxLocalAuc.numRowSamples = 30
maxLocalAuc.rate = "constant"
maxLocalAuc.recordStep = 10
maxLocalAuc.rho = 1.0
maxLocalAuc.t0 = 1.0
maxLocalAuc.t0s = 2.0**-numpy.arange(7, 12, 1)
maxLocalAuc.validationSize = 3
maxLocalAuc.validationUsers = 0
newM = X.shape[0]/4
modelSelectX, userInds = Sampling.sampleUsers(X, newM)
if saveResults:
meanObjs1, stdObjs1 = maxLocalAuc.modelSelect2(X)
meanObjs2, stdObjs2 = maxLocalAuc.modelSelect2(trainX)
meanObjs3, stdObjs3 = maxLocalAuc.modelSelect2(modelSelectX)
numpy.savez(outputFile, meanObjs1, meanObjs2, meanObjs3)
else:
data = numpy.load(outputFile)
meanObjs1, meanObjs2, meanObjs3 = data["arr_0"], data["arr_1"], data["arr_2"]
meanObjs1 = numpy.squeeze(meanObjs1)
meanObjs2 = numpy.squeeze(meanObjs2)
meanObjs3 = numpy.squeeze(meanObjs3)
import matplotlib
matplotlib.use("GTK3Agg")
