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_Training_Graph()
selection = VariableSelection(myparams.trainnigGraph, util.min_edges)
nodesNotLinked = selection.readingResultsFile(util.nodes_notlinked_file)
calc = CalculateInMemory(myparams, nodesNotLinked)
resultsofCalculation = calc.executingCalculate()
#print resultsofCalculation
calc.saving_calculateResult(util.calculated_file, resultsofCalculation)
calc.saving_calculateResult_normalized(
util.calculated_file + '_normalizated.csv', resultsofCalculation)
result2 = calc.reading_calculateResult_normalized(util.calculated_file)
calc.save_Max_min_file(util.maxmincalculated_file, calc.qtyDataCalculated,
calc.minValueCalculated, calc.maxValueCalculated)
print resultsofCalculation
print result2
from parametering.ParameterUtil import ParameterUtil
from parametering.Parameterization import Parameterization
from calculating.CalculateInMemory import CalculateInMemory
from calculating.VariableSelection import VariableSelection
if __name__ == '__main__':
util = ParameterUtil(parameter_file = 'data/formatado/arxiv/exemplomenor/config/config.txt')
#util = ParameterUtil(parameter_file = 'data/formatado/arxiv/nowell_astroph_1994_1999/config/configuration_forAG.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)
myparams.generating_Training_Graph()
selection = VariableSelection(myparams.trainnigGraph, util.min_edges)
nodesNotLinked = selection.readingResultsFile(util.nodes_notlinked_file)
calc = CalculateInMemory(myparams,nodesNotLinked)
resultsofCalculation = calc.executingCalculate()
#print resultsofCalculation
calc.saving_calculateResult(util.calculated_file, resultsofCalculation)
calc.saving_calculateResult_normalized(util.calculated_file + '_normalizated.csv', resultsofCalculation)
result2 = calc.reading_calculateResult_normalized(util.calculated_file)
calc.save_Max_min_file(util.maxmincalculated_file, calc.qtyDataCalculated, calc.minValueCalculated, calc.maxValueCalculated)
print resultsofCalculation
print result2
