parser.add_argument("-r", "--runLDA", action="store_true", help="Run Latent Dirchlet Allocation")
args = parser.parse_args()
averagePrecisionN = 50
similarityCutoff = 0.30
ns = numpy.arange(5, 105, 5)
runLSI = not args.runLDA
dataset = ArnetMinerDataset(runLSI=runLSI)
#dataset.dataFilename = dataset.dataDir + "DBLP-citation-100000.txt"
#dataset.dataFilename = dataset.dataDir + "DBLP-citation-1000000.txt"
dataset.dataFilename = dataset.dataDir + "DBLP-citation-1000000.txt"
#dataset.dataFilename = dataset.dataDir + "DBLP-citation-7000000.txt"
#dataset.dataFilename = dataset.dataDir + "DBLP-citation-Feb21.txt"
dataset.overwriteGraph = True
dataset.overwriteModel = True
dataset.overwriteVectoriser = True
dataset.vectoriseDocuments()
dataset.loadVectoriser()
X = scipy.io.mmread(dataset.docTermMatrixFilename + ".mtx")
X = X.tocsc()
X.data[:] = 1
print(numpy.max(X.data), numpy.min(X.data))
rowSums = numpy.array(X.sum(0), numpy.int).flatten()
colSums = numpy.array(X.sum(1), numpy.int).flatten()
