dataParser.add_argument("--dataset", type=str, help="The dataset to use: either Doc or Keyword (default: %(default)s)", default=dataParser.dataset)
devNull, remainingArgs = dataParser.parse_known_args(namespace=dataArgs)
if dataArgs.help:
helpParser = argparse.ArgumentParser(description="", add_help=False, parents=[dataParser, RankingExpHelper.newAlgoParser(defaultAlgoArgs)])
helpParser.print_help()
exit()
# print args #
logging.info("Data params:")
keys = list(vars(dataArgs).keys())
keys.sort()
for key in keys:
logging.info(" " + str(key) + ": " + str(dataArgs.__getattribute__(key)))
logging.info("Creating the exp-runner")
#Load/create the dataset - sample at most a million nnzs
X = DatasetUtils.mendeley(dataset=dataArgs.dataset)
numpy.random.seed(21)
X, userInds = Sampling.sampleUsers2(X, 10**6, prune=True)
m, n = X.shape
dataArgs.extendedDirName = ""
dataArgs.extendedDirName += "MendeleyCoauthors" + dataParser.dataset
rankingExpHelper = RankingExpHelper(remainingArgs, defaultAlgoArgs, dataArgs.extendedDirName)
rankingExpHelper.printAlgoArgs()
rankingExpHelper.runExperiment(X)
