Python FormatingDataSets.get_abs_file_path方法代碼示例

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def analise(calcDb, topRank,TestGraph, util, method):
    order = sorted( list({ 'node1': r['node1'], 'node2': r['node2'], 'value' : r[method]} for r in calcDb)  , key=lambda value: value['value'], reverse=True)
    BD = None
    if not os.path.exists(FormatingDataSets.get_abs_file_path(util.calculated_file + '.' + method +'.base.pdl')):
        BD = generate_finalResult(order, topRank, TestGraph, FormatingDataSets.get_abs_file_path(util.calculated_file + '.' + method +'.base.pdl'))
    
    else:
        BD = reading_Database(FormatingDataSets.get_abs_file_path(util.calculated_file + '.' + method +'.base.pdl'))
    
    return get_results(BD, method)

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile):
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'T.EXPERIMENTO_ATUAL_CORE03.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    resultFile.write("\n")

    
    #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 CONcvb FIG FILE T1 AND T1_
    myparams.generating_Test_Graph()
    nodesSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    #GET THE AUTHORS THAT PUBLISH AT TRAINNING AND TEST 
    #A NUMBER OF PAPERS DEFINED AT MIN_EDGES IN CONFIG FILE
    nodes = nodesSelection.get_NowellAuthorsCore()
    #GET A PAIR OF AUTHORS THAT PUBLISH AT LEAST ONE ARTICLE AT TRAINNING AND TEST.
    #DID NOT SEE ANY NEED
    collaborations = nodesSelection.get_NowellColaboration()
    #GET THE FIRST EDGES MADE BY THE COMBINATION OF NODES IN TRAINNING GRAPH
    eOld = nodesSelection.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 = nodesSelection.get_NowellE2(nodes, eOld, myparams.testGraph)
    #GET THE NODES NOT LINKED OVER THE COMBINATION NODES.
    nodesNotLinked = nodesSelection.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.write("Fim da Operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def step05(paramFile):
    #util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_example_1994_1999.txt')
    util = ParameterUtil(parameter_file = paramFile)

    myparams = Parameterization(util.keyword_decay, util.lengthVertex, util.t0, util.t0_, util.t1, util.t1_, util.FeaturesChoiced, util.graph_file, util.trainnig_graph_file, util.test_graph_file, util.decay)
    calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
    myparams.generating_Test_Graph()
    analise = Analyse(myparams, FormatingDataSets.get_abs_file_path(util.calculated_file), FormatingDataSets.get_abs_file_path(util.analysed_file) + '.random.analised.txt', calc.qtyDataCalculated)

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile):
    
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'core03.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    resultFile.write("\n")

    
    #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 CONcvb FIG FILE T1 AND T1_
    myparams.generating_Test_Graph()
    
    nodeSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    #if not os.path.exists(FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.fuzzyinputy.txt')):
    data = calculatingInputToFuzzy(myparams.trainnigGraph,nodeSelection.nodesNotLinked,  myparams)
    saving_files_calculting_input(FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.inputFuzzy.txt'), data)
    
    for item in data:
        calc = FuzzyCalculation(item['intensityno1'], item['intensityno2'], item['similarity'], item['ageno1'], item['ageno2'])
        print item['no1'], item['no2'], calc.potencial_ligacao, calc.grau_potencial_ligacao
        
        
       
    
    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(nodeSelection.get_NowellColaboration())*2)+ "\t\t" + str(len(nodeSelection.nodes)) + "\t" + str(len(nodeSelection.eOld))+"\t" + str(len(nodeSelection.eNeW)))
     
 
    resultFile.write("\n")

    resultFile.write("Fim da Operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile, metricas):
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'core03.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    resultFile.write("\n")
    
    #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 CONcvb FIG FILE T1 AND T1_
    myparams.generating_Test_Graph()
    
    nodeSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    
    #CREATING CALCULATION OBJECT
    weights = {'cn' : 1, 'aas': 1, 'pa':1, 'jc': 1, 'ts08':1,'ts05': 1, 'ts02':1}
    
    calc = CalculatingCombinationOnlyNowell(myparams, nodeSelection.nodesNotLinked,weights,False )

    saving_files_calculting(FormatingDataSets.get_abs_file_path(util.calculated_file), calc.results, metricas)
    
    Analise = nodeSelection.AnalyseAllNodesNotLinkedInFuture(nodeSelection.nodesNotLinked, myparams.testGraph)
    salvar_analise(FormatingDataSets.get_abs_file_path(util.analysed_file) + '.allNodes.csv', Analise)
    
    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(nodeSelection.get_NowellColaboration())*2)+ "\t\t" + str(len(nodeSelection.nodes)) + "\t" + str(len(nodeSelection.eOld))+"\t" + str(len(nodeSelection.eNeW)))
     
 
    resultFile.write("\n")

    resultFile.write("Fim da Operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile):
    
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'core03.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    resultFile.write("\n")

    
    #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 CONcvb FIG FILE T1 AND T1_
    myparams.generating_Test_Graph()
    
    nodeSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    #if not os.path.exists(FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.fuzzyinputy.txt')):
    data = calculatingInputToFuzzy(myparams.trainnigGraph,nodeSelection.nodesNotLinked,  myparams)
    dataSorted = sorted(data, key=lambda value: value['result'], reverse=True)
    
    topRank = len(nodeSelection.eNeW)
    totalCalculated = len(dataSorted)
    dataToAnalysed = []
    if (topRank >= totalCalculated):
        for item in range(totalCalculated):
            dataToAnalysed.append({'no1':  dataSorted[item]['no1'], 'no2': dataSorted[item]['no2'], 'result':  dataSorted[item]['result'] })
    else:
        for item in range(topRank):
            dataToAnalysed.append({'no1':  dataSorted[item]['no1'], 'no2': dataSorted[item]['no2'], 'result':  dataSorted[item]['result'] })
            
    
    analise = AnalyseNodesInFuture(dataToAnalysed, myparams.testGraph)
    
    resultFile.write( repr(get_TotalSucess(analise)) )   
    
    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(nodeSelection.get_NowellColaboration())*2)+ "\t\t" + str(len(nodeSelection.nodes)) + "\t" + str(len(nodeSelection.eOld))+"\t" + str(len(nodeSelection.eNeW)))
     
 
    resultFile.write("\n")

    resultFile.write("Fim da Operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile):
   
    
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'wTScore03_010304.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    resultFile.write("\n")

    
    #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 CONcvb FIG FILE T1 AND T1_
    myparams.generating_Test_Graph()
    
    nodeSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    db = None
    if not os.path.exists(FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.base.pdl')):
        db = generateWeights(myparams.trainnigGraph, FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.base.pdl') , myparams)
    else:
        db = reading_Database(FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.base.pdl'))
    calcDb = None
    if not os.path.exists(FormatingDataSets.get_abs_file_path(util.calculated_file + '.base.pdl')):
        calcDb = calculatingWeights(myparams.trainnigGraph, nodeSelection.nodesNotLinked, db, FormatingDataSets.get_abs_file_path(util.calculated_file) + '.base.pdl')
    else:
        calcDb = reading_Database(FormatingDataSets.get_abs_file_path(util.calculated_file + '.base.pdl'))
        
    ordering = get_ordering(calcDb, len(nodeSelection.eNeW))
    
    result = get_analyseNodesInFuture(ordering, myparams.testGraph)
    
    resultFile.write(repr(result))
    
    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(nodeSelection.get_NowellColaboration())*2)+ "\t\t" + str(len(nodeSelection.nodes)) + "\t" + str(len(nodeSelection.eOld))+"\t" + str(len(nodeSelection.eNeW)))
     
 
    resultFile.write("\n")

    resultFile.write("Fim da Operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile):
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'core03_execucaoFinal_cstT02.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    resultFile.write("\n")
    
    #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 CONcvb FIG FILE T1 AND T1_
    myparams.generating_Test_Graph()
    
    nodeSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    #CREATING CALCULATION OBJECT
    calc = CalculatingTogether(myparams, nodeSelection.nodesNotLinked)
    
    ordering = calc.ordering(len(nodeSelection.eNeW))
    
    #calc.saving_orderedResult(util.ordered_file, ordering)
    
    calc.AnalyseNodesInFuture(ordering, myparams.testGraph)
    
    resultFile.write(repr(calc.get_TotalSucess()))
    
    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(nodeSelection.get_NowellColaboration())*2)+ "\t\t" + str(len(nodeSelection.nodes)) + "\t" + str(len(nodeSelection.eOld))+"\t" + str(len(nodeSelection.eNeW)))
     
 
    resultFile.write("\n")

    resultFile.write("Fim da Operacao\n")
    resultFile.write(str(datetime.datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
def execution(configFile, weights):
    #DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
    resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'core03.txt'), 'w')
    
    resultFile.write("Inicio da operacao\n")
    resultFile.write(str(datetime.now()))
    resultFile.write("\n")
    #READING THE CONFIG FILE
    util = ParameterUtil(parameter_file = configFile)
    
    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)
    
    myparams.generating_Test_Graph()
    myparams.generating_Training_Graph()
    
    nodeSelection = NodeSelection(myparams.trainnigGraph, myparams.testGraph, util)
    #CREATING CALCULATION OBJECT
    calc = CalculatingCombinationOnlyNowell(myparams, nodeSelection.nodesNotLinked, weights, True)
        
    ordering = calc.ordering(len(nodeSelection.eNeW))
    
    calc.AnalyseNodesInFuture(ordering, myparams.testGraph)
    
    resultFile.write(repr(calc.get_TotalSucess()))
    
    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(nodeSelection.get_NowellColaboration())*2)+ "\t\t" + str(len(nodeSelection.nodes)) + "\t" + str(len(nodeSelection.eOld))+"\t" + str(len(nodeSelection.eNeW)))
     
 
    resultFile.write("\n")

    resultFile.write("Fim da Operacao\n")
    resultFile.write(str(datetime.now()))
    
    resultFile.close()

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
if __name__ == '__main__':
    util = ParameterUtil(parameter_file = 'data/formatado/exemplomenor/config/config.txt')
    myparams = Parameterization(t0 = util.t0, t0_ = util.t0_, t1 = util.t1, t1_ = util.t1_, 
                                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)

    myparams.generating_Training_Graph()
    myparams.generating_Test_Graph()
    
    selection = VariableSelection(myparams.trainnigGraph, util.min_edges)
    nodesNotLinked = selection.get_pair_nodes_not_linked()
    calc = CalculateInMemory(myparams, nodesNotLinked)
    resultsCalculate = calc.executingCalculate()
    
    
    calc.Separating_calculateFile()
    analise = Analyse(myparams, FormatingDataSets.get_abs_file_path(util.calculated_file), FormatingDataSets.get_abs_file_path(util.analysed_file) + '.random.analised.txt', calc.qtyDataCalculated)
    topRank = Analyse.getTopRank(util.analysed_file + '.random.analised.txt')
    calc.Ordering_separating_File(topRank)
    for OrderingFilePath in calc.getfilePathOrdered_separeted():
        analise = Analyse(myparams, OrderingFilePath, OrderingFilePath + '.analised.txt', topRank )
    
    
    print "Trainning Period:", myparams.t0, " - ", myparams.t0_
    print "Test Period:", myparams.t1, " - ", myparams.t1_
    
    print "# Papers in Trainning: ",  myparams.get_edges(myparams.trainnigGraph)
    print "# Authors in Training: ", myparams.get_nodes(myparams.trainnigGraph)
    print "# Papers in Test: ",  myparams.get_edges(myparams.testGraph)
    print "# Authors in Test", myparams.get_nodes(myparams.testGraph)
    
    print "# pair of Authors with at least 3 articles Calculated: ", calc.qtyDataCalculated  #FormatingDataSets.getTotalLineNumbers(FormatingDataSets.get_abs_file_path(util.calculated_file))

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
'''
Created on Aug 22, 2015

@author: cptullio
Analysing the results
'''
from parametering.ParameterUtil import ParameterUtil
from parametering.Parameterization import Parameterization
from calculating.Calculate import Calculate
from analysing.Analyse import Analyse
from calculating.VariableSelection import VariableSelection
from formating.FormatingDataSets import FormatingDataSets
import networkx

if __name__ == '__main__':
    util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_example_1994_1999.txt')
    myparams = Parameterization(util.keyword_decay, util.lengthVertex, util.t0, util.t0_, util.t1, util.t1_, util.FeaturesChoiced, util.graph_file, util.trainnig_graph_file, util.test_graph_file, util.decay)
    myparams.generating_Training_Graph()
    selection = VariableSelection(myparams.trainnigGraph, util.nodes_notlinked_file,util.min_edges, True)
    calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
    wg = calc.adding_normalize_values_tograph(myparams.trainnigGraph)
    networkx.write_graphml(wg, FormatingDataSets.get_abs_file_path(util.trainnig_graph_file + '.weighted.txt'))
    node993 =set(n for n,d in wg.edges(data=True) if n == 993 and d == 994)
    print node993
    
    

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
 def getTopRank(relativeFilePathRandomAnalised):
     absFile = FormatingDataSets.get_abs_file_path(relativeFilePathRandomAnalised)
     f = open(absFile, 'r')
     for last in f:
         pass
     return int(last.split('\t')[1])

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
from analysing.Analyse import Analyse
from calculating.VariableSelection import VariableSelection
from formating.FormatingDataSets import FormatingDataSets
import networkx
import mysql.connector

if __name__ == '__main__':
    util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_astroph_1994_1999.txt')
    myparams = Parameterization(util.keyword_decay, util.lengthVertex, util.t0, util.t0_, util.t1, util.t1_, util.FeaturesChoiced, util.graph_file, util.trainnig_graph_file, util.test_graph_file, util.decay)
    myparams.generating_Training_Graph()
    AllNodes = VariableSelection(myparams.trainnigGraph, util.nodes_file,util.min_edges, True)
    calc = Calculate(myparams, util.nodes_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
    print 'armazenando resultados'
    cnx = mysql.connector.connect(user='root', password='1234',
                              host='127.0.0.1',
                              database='calculos')
    add_result = ("INSERT INTO resultadopesos "
               "(no1, no2, resultados) "
               "VALUES (%s, %s, %s)")
    cursor = cnx.cursor()
    calculatedFile = open(FormatingDataSets.get_abs_file_path(util.calculated_file), 'r')
    for linha in calculatedFile:
        dado = Calculate.reading_calculateLine(linha)
        data_result = (dado[1], dado[2].replace('\n',''),str(dado[0]))
        cursor.execute(add_result, data_result)
    calculatedFile.close()
    cnx.commit()
    cursor.close()
    cnx.close()
    
    

# 需要導入模塊: from formating.FormatingDataSets import FormatingDataSets [as 別名]
# 或者: from formating.FormatingDataSets.FormatingDataSets import get_abs_file_path [as 別名]
    
    
    for line in calculatedFile:
        if texto in line:
            result = line
            break
        elif textov2 in line:
            result = line
            break
    calculatedFile.seek(0)
    return result
    

if __name__ == '__main__':
    util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_astroph_1994_1999.txt')
    calculatedFile = open(FormatingDataSets.get_abs_file_path(util.calculated_file), 'r')
    for linha in calculatedFile:
        x.append(Calculate.reading_calculateLine(linha))
    calculatedFile.close()
    myparams = Parameterization(util.keyword_decay, util.lengthVertex, util.t0, util.t0_, util.t1, util.t1_, util.FeaturesChoiced, util.graph_file, util.trainnig_graph_file, util.test_graph_file, util.decay)
    myparams.generating_Training_Graph()
    Nodes_notLinked = VariableSelection(myparams.trainnigGraph, util.nodes_notlinked_file,util.min_edges)
    nodes_notlinkedFile = open(FormatingDataSets.get_abs_file_path(util.nodes_notlinked_file), 'r')
    qtyLine = 0
    qtyCalculated = 0
    f = open(FormatingDataSets.get_abs_file_path(util.calculated_file )+ '.weight.txt', 'w')
    minValueCalculated = list(99999 for x in myparams.featuresChoice)
    maxValueCalculated = list(0 for x in myparams.featuresChoice)
    qtyFeatures = len(myparams.featuresChoice)
    for line in nodes_notlinkedFile:
        qtyLine = qtyLine + 1