} initConfig(para) ######################################################### startTime = time.clock() # start timing logger.info('==============================================') logger.info('Approach: HMF [He et al., ICWS\'2014].') # load the dataset dataMatrix = dataloader.load(para) logger.info('Loading data done.') # get the location groups for users as well as for services locGroup = dataloader.getLocGroup(para) logger.info('Clustering done.') # run for each density if para['parallelMode']: # run on multiple processes pool = multiprocessing.Pool() for density in para['density']: pool.apply_async(evaluator.execute, (dataMatrix, locGroup, density, para)) pool.close() pool.join() else: # run on single processes for density in para['density']: evaluator.execute(dataMatrix, locGroup, density, para) logger.info(time.strftime('All done. Total running time: %d-th day - %Hhour - %Mmin - %Ssec.', time.gmtime(time.clock() - startTime)))
} initConfig(para) ######################################################### startTime = time.clock() # start timing logger.info("==============================================") logger.info("Approach: HMF [He et al., ICWS'2014].") # load the dataset dataMatrix = dataloader.load(para) logger.info("Loading data done.") # get the location groups for users as well as for services locGroup = dataloader.getLocGroup(para) logger.info("Clustering done.") # run for each density if para["parallelMode"]: # run on multiple processes pool = multiprocessing.Pool() for density in para["density"]: pool.apply_async(evaluator.execute, (dataMatrix, locGroup, density, para)) pool.close() pool.join() else: # run on single processes for density in para["density"]: evaluator.execute(dataMatrix, locGroup, density, para) logger.info( time.strftime(