本文整理匯總了Python中parametering.Parameterization.Parameterization.get_NowellAuthorsCore方法的典型用法代碼示例。如果您正苦於以下問題：Python Parameterization.get_NowellAuthorsCore方法的具體用法？Python Parameterization.get_NowellAuthorsCore怎麽用？Python Parameterization.get_NowellAuthorsCore使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類parametering.Parameterization.Parameterization的用法示例。
在下文中一共展示了Parameterization.get_NowellAuthorsCore方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: execution
# 需要導入模塊: from parametering.Parameterization import Parameterization [as 別名]
# 或者: from parametering.Parameterization.Parameterization import get_NowellAuthorsCore [as 別名]
def execution(configFile):
#DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
resultFile = open(FormatingDataSets.get_abs_file_path(configFile + '.firstTabletsALLCORE02DECAY02.txt'), 'w')
#READING THE CONFIG FILE
util = ParameterUtil(parameter_file = configFile)
#CREATING PARAMETRIZATION OBJECT WITH THE INFORMATIONS OF THE CONFIG FILE.
myparams = Parameterization(t0 = util.t0, t0_ = util.t0_, t1 = util.t1, t1_ = util.t1_, linear_combination=util.linear_combination,
filePathGraph = util.graph_file, filePathTrainingGraph = util.trainnig_graph_file, filePathTestGraph = util.test_graph_file, decay = util.decay, domain_decay = util.domain_decay, min_edges = util.min_edges, scoreChoiced = util.ScoresChoiced, weightsChoiced = util.WeightsChoiced, weightedScoresChoiced = util.WeightedScoresChoiced, FullGraph = None, result_random_file=util.result_random_file)
#GENERATING TRAINNING GRAPH BASED ON CONFIG FILE T0 AND T0_
myparams.generating_Training_Graph()
#GENERATING TEST GRAPH BASED ON CONFIG FILE T1 AND T1_
myparams.generating_Test_Graph()
#GET THE AUTHORS THAT PUBLISH AT TRAINNING AND TEST
#A NUMBER OF PAPERS DEFINED AT MIN_EDGES IN CONFIG FILE
nodes = myparams.get_NowellAuthorsCore()
#GET A PAIR OF AUTHORS THAT PUBLISH AT LEAST ONE ARTICLE AT TRAINNING AND TEST.
#DID NOT SEE ANY NEED
collaborations = myparams.get_NowellColaboration()
#GET THE FIRST EDGES MADE BY THE COMBINATION OF NODES IN TRAINNING GRAPH
eOld = myparams.get_NowellE(nodes,myparams.trainnigGraph)
#GET THE FIRST EDGES MADE BY THE COMBINATION OF NODES IN TEST GRAPH THAT DO NOT HAVE EDGES IN TRAINNING
eNew = myparams.get_NowellE2(nodes, eOld, myparams.testGraph)
#GET THE NODES NOT LINKED OVER THE COMBINATION NODES.
nodesNotLinked = myparams.get_PairsofNodesNotinEold(nodes)
#CREATING CALCULATION OBJECT
calc = CalculateInMemory(myparams,nodesNotLinked)
#CALCULATING THE SCORES.
resultsofCalculation = calc.executingCalculate()
#ORDERNING THE RESULTS RETURNING THE TOP N
orderingResults = calc.ordering(len(eNew), resultsofCalculation)
#SAVING THE ORDERED RESULTS.
calc.saving_orderedResult(util.ordered_file, orderingResults)
#ANALISE THE ORDERED RESULTS AND CHECK THE FUTURE.
ScoresResults = Analyse.AnalyseNodesWithScoresInFuture(orderingResults, myparams.testGraph)
#SAVING THE RESULTS.
for index in range(len(ScoresResults)):
Analyse.saving_analyseResult(ScoresResults[index], util.analysed_file + str(myparams.ScoresChoiced[index][0] ) + '.txt')
resultFile.write("TOTAL OF SUCESSS USING METRIC " + str(myparams.ScoresChoiced[index][0]) + " = " + str(Analyse.get_TotalSucess(ScoresResults[index]) ))
resultFile.write("\n")
resultFile.write("\n")
resultFile.write("Authors\tArticles\tCollaborations\tAuthors\tEold\tEnew\n")
resultFile.write( str(myparams.get_nodes(myparams.trainnigGraph))+ "\t" + str(myparams.get_edges(myparams.trainnigGraph)) + "\t\t" + str(len(collaborations)*2)+ "\t\t" + str(len(nodes)) + "\t" + str(len(eOld))+"\t" + str(len(eNew)))
resultFile.write("\n")
resultFile.close()