def step08(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)
myparams.generating_Training_Graph()
myparams.generating_Test_Graph()
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)
calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file,
util.ordered_file, util.maxmincalculated_file)
calc.reading_Max_min_file()
print "# pair of Authors with at least 3 articles Calculated: ", calc.qtyDataCalculated #FormatingDataSets.getTotalLineNumbers(FormatingDataSets.get_abs_file_path(util.calculated_file))
topRank = Analyse.getTopRank(util.analysed_file + '.random.analised.txt')
print "# pair of Authors with at least 3 articles that is connected in Test Graph in a random way: ", topRank
print "Max values found in calculations: ", str(calc.maxValueCalculated)
print "Min Values found in calculations: ", str(calc.minValueCalculated)
for pathFile in calc.getfilePathOrdered_separeted():
print "File Analised: ", pathFile + '.analised.txt'
number_connected = Analyse.getTopRankABSPathFiles(pathFile +
'.analised.txt')
print "# pair of Authors that is connected in Test Graph: ", number_connected
print "%: ", Analyse.getLastInfosofResultsABSPathFiles(
pathFile + '.analised.txt', topRank)
print "---------------------------------"
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)
def step03( paramFile, num_people):
#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)
myparams.generating_Training_Graph()
selection = VariableSelection(myparams.trainnigGraph, util.nodes_notlinked_file,util.min_edges, False, num_people)
return
def step04(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)
myparams.generating_Training_Graph()
calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
calc.Separating_calculateFile()
def step04(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)
myparams.generating_Training_Graph()
calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
calc.Separating_calculateFile()
def step08(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)
myparams.generating_Training_Graph()
myparams.generating_Test_Graph()
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)
calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
calc.reading_Max_min_file()
print "# pair of Authors with at least 3 articles Calculated: ", calc.qtyDataCalculated #FormatingDataSets.getTotalLineNumbers(FormatingDataSets.get_abs_file_path(util.calculated_file))
topRank = Analyse.getTopRank(util.analysed_file+ '.random.analised.txt')
print "# pair of Authors with at least 3 articles that is connected in Test Graph in a random way: ", topRank
print "Max values found in calculations: ", str(calc.maxValueCalculated)
print "Min Values found in calculations: ", str(calc.minValueCalculated)
for pathFile in calc.getfilePathOrdered_separeted():
print "File Analised: ", pathFile + '.analised.txt'
number_connected = Analyse.getTopRankABSPathFiles(pathFile + '.analised.txt')
print "# pair of Authors that is connected in Test Graph: ", number_connected
print "%: ", Analyse.getLastInfosofResultsABSPathFiles(pathFile + '.analised.txt', topRank)
print "---------------------------------"
def step07(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()
topRank = Analyse.getTopRank(util.analysed_file + '.random.analised.txt')
print 'Analising Files with TopRank', str(topRank)
for OrderingFilePath in calc.getfilePathOrdered_separeted():
analise = Analyse(myparams, OrderingFilePath, OrderingFilePath + '.analised.txt', topRank )
def step03(paramFile, num_people):
#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)
myparams.generating_Training_Graph()
selection = VariableSelection(myparams.trainnigGraph,
util.nodes_notlinked_file, util.min_edges,
False, num_people)
return
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()
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)
def execution(configFile):
#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')):
calculatingInputToFuzzy(myparams.trainnigGraph,nodeSelection.nodesNotLinked, myparams)
def step07(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()
topRank = Analyse.getTopRank(util.analysed_file + '.random.analised.txt')
print 'Analising Files with TopRank', str(topRank)
for OrderingFilePath in calc.getfilePathOrdered_separeted():
analise = Analyse(myparams, OrderingFilePath,
OrderingFilePath + '.analised.txt', topRank)
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()
def execution(configFile):
#DEFINE THE FILE THAT WILL KEEP THE RESULT DATA
resultFile = open(FormatingDataSets.get_abs_file_path(configFile + 'core03_onlyinteraction.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()
class SFrame:
#util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_astroph_1994_1999/AllExecutionScores/configToAG.txt')
util = ParameterUtil(parameter_file = 'data/configuration/arxiv/exemplo_1994_1999/CombinationLinear/configToAG.txt')
#util = ParameterUtil(parameter_file = 'data/configuration/arxiv/condmat_1994_1999/CombinationLinear/configToAG.txt')
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)
metrics = sframe.SFrame.read_csv(FormatingDataSets.get_abs_file_path(util.calculated_file+'_normalizated.csv'))
results = sframe.SFrame.read_csv(FormatingDataSets.get_abs_file_path(util.result_random_file))
top = 20
def __init__(self):
pass
@classmethod
def evaluate(cls, individual):
new_metric = float(0)
##print 'individuos: ', individual
for index_score in range(len(cls.myparams.ScoresChoiced)):
#print cls.myparams.ScoresChoiced[index_score][0].getName()
valorMetrica = cls.metrics[ cls.myparams.ScoresChoiced[index_score][0].getName() ]
valorIndividual = individual[index_score]
#print "valores ", valorMetrica, valorIndividual
new_metric = new_metric + (valorMetrica * valorIndividual )
##print 'nova metrica', new_metric
copy_metrics = cls.metrics.copy()
copy_metrics.add_column(new_metric, name='new_metric')
copy_metrics = copy_metrics.topk('new_metric', k=cls.top)
#print 'metrics after topk \n\n', copy_metrics
copy_results = cls.results.copy()
#print 'copy_results before join', copy_results
copy_metrics = copy_metrics.join(copy_results)
#print 'metrics after join \n\n', copy_metrics
copy_metrics = copy_metrics.sort('new_metric', ascending=False)
##print 'copy metrics ', copy_metrics
aux = [0]
copy_metrics = copy_metrics.filter_by(aux,'result')
zero = copy_metrics.num_rows()
#print 'zero', zero
del copy_metrics
del copy_results
result = float(zero) / cls.top,
#print 'resultado ', result
return result
def step06(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)
topRank = Analyse.getTopRank(util.analysed_file + '.random.analised.txt')
calc.Ordering_separating_File(topRank)
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()
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()
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)
#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)
Analise = nodeSelection.AnalyseAllNodesNotLinkedInFuture(nodeSelection.nodesNotLinked, myparams.testGraph)
salvar_analise(FormatingDataSets.get_abs_file_path(util.analysed_file) + '.allNodes.csv', Analise)
resultFile.write("Fim da Operacao\n")
resultFile.write(str(datetime.datetime.now()))
resultFile.close()
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)
#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()
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()
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()
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()
def execution(configFile):
#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')):
calculatingInputToFuzzy(myparams.trainnigGraph,nodeSelection.nodesNotLinked, myparams)
class SFrame:
util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_astroph_1994_1999/AllExecutionScores/configToAG.txt')
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)
metrics = sframe.SFrame.read_csv(FormatingDataSets.get_abs_file_path(util.calculated_file+'_normalizated.csv'))
results = sframe.SFrame.read_csv(FormatingDataSets.get_abs_file_path(util.result_random_file))
top = 20
def __init__(self):
pass
@classmethod
def evaluate(cls, individual):
new_metric = float(0)
for index_score in range(len(cls.myparams.ScoresChoiced)):
new_metric = new_metric + (cls.metrics[ cls.myparams.ScoresChoiced[index_score][0].getName() ] * individual[index_score] )
print new_metric
copy_metrics = cls.metrics.copy()
copy_metrics.add_column(new_metric, name='new_metric')
copy_metrics = copy_metrics.topk('new_metric', k=cls.top)
copy_results = cls.results.copy()
copy_metrics = copy_metrics.join(copy_results)
copy_metrics = copy_metrics.sort('new_metric', ascending=False)
aux = [0]
copy_metrics = copy_metrics.filter_by(aux,'result')
zero = copy_metrics.num_rows()
del copy_metrics
del copy_results
return float(zero) / cls.top,
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()
Created on Aug 22, 2015
@author: cptullio
Analysing the results
'''
from parametering.ParameterUtil import ParameterUtil
from parametering.Parameterization import Parameterization
from analysing.Analyse import Analyse
from calculating.VariableSelection import VariableSelection
from formating.FormatingDataSets import FormatingDataSets
import networkx
from calculating.CalculateInMemory import CalculateInMemory
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():
import networkx
from matplotlib import pyplot
if __name__ == '__main__':
#util = ParameterUtil(parameter_file = 'data/formatado/arxiv/exemplomenor/config/configuration_weights.txt')
util = ParameterUtil(
parameter_file=
'data/formatado/duarte/1994_1999/config/configuration.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()
calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file,
util.ordered_file, util.maxmincalculated_file)
calc.Separating_calculateFile()
#networkx.networkx.draw_networkx(myparams.trainnigGraph) # networkx draw()
#pyplot.draw() # pyplot draw()
'''
Created on Aug 22, 2015
@author: cptullio
Selecting all Nodes that will be calculated.
'''
from parametering.ParameterUtil import ParameterUtil
from parametering.Parameterization import Parameterization
from calculating.VariableSelection import VariableSelection
from calculating.Calculate import Calculate
from analysing.Analyse import Analyse
from formating.FormatingDataSets import FormatingDataSets
if __name__ == '__main__':
util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_condmat_1994_1999.txt')
myparams = Parameterization(util.top_rank, util.distanceNeighbors,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)
calc = Calculate(myparams, util.nodes_notlinked_file, util.calculated_file, util.ordered_file, util.maxmincalculated_file)
calc.Separating_calculateFile()
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)
topRank = Analyse.getTopRank(util.analysed_file + '.random.analised.txt')
calc.Ordering_separating_File(topRank)
'''
Created on Aug 22, 2015
@author: cptullio
Generating TopRank
'''
from parametering.ParameterUtil import ParameterUtil
from parametering.Parameterization import Parameterization
from calculating.Calculate import Calculate
from analysing.Analyse import Analyse
from formating.FormatingDataSets import FormatingDataSets
if __name__ == '__main__':
util = ParameterUtil(
parameter_file='data/formatado/duarte/nowell_duarte_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)
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)
def step02(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)
myparams.generating_Training_Graph()
myparams.generating_Test_Graph()
'''
Created on 28 de ago de 2015
@author: CarlosPM
For statistics results
'''
from parametering.ParameterUtil import ParameterUtil
from parametering.Parameterization import Parameterization
from formating.FormatingDataSets import FormatingDataSets
from analysing.Analyse import Analyse
from calculating.Calculate import Calculate
if __name__ == '__main__':
util = ParameterUtil(parameter_file = 'data/formatado/duarte/nowell_duarte_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()
myparams.generating_Test_Graph()
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)
