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src/a/z/AZOrange-HEAD/azorange/AZutilities/getUnbiasedAccuracy.py   AZOrange(Download)
                                    optAcc[ml].append(R2)
                    else:
                            runPath = miscUtilities.createScratchDir(baseDir = AZOC.NFS_SCRATCHDIR, desc = "AccWOptParam", seed = id(trainData))
                            trainData.save(os.path.join(runPath,"trainData.tab"))
                            tunedPars = paramOptUtilities.getOptParam(

src/a/z/AZOrange-HEAD/orange/OrangeWidgets/Classify/OWParamOpt.py   AZOrange(Download)
        randNr = random.randint(0,10000)
        if self.execEnv == 0:
            scratchdir = miscUtilities.createScratchDir(desc = "OWParamOpt_Serial")
        else:
            scratchdir = miscUtilities.createScratchDir(desc ="OWParamOpt_MPI", baseDir = AZOC.NFS_SCRATCHDIR)

src/a/z/AZOrange-HEAD/azorange/AZutilities/paramOptUtilities.py   AZOrange(Download)
                    # WARNING! Do not specify a dir inside self.runPath. This would create a circular reference!
                    #          This path must ba a path accessible by all nodes running each point
                    GSPath = miscUtilities.createScratchDir(desc ="GRidSearchFiles", baseDir = AZOC.NFS_SCRATCHDIR)
                    GS_script = self.__CreateGridSearchFiles(paramKeys)
                    from AZutilities import AZGridSearch
    # Create a directory for running appspack (if not defined it will use the present working directory)
    if not runPath:
        runPath = miscUtilities.createScratchDir(desc ="optQsubTest", baseDir = AZOC.NFS_SCRATCHDIR)
 
    if responseType == "Classification":

src/a/z/AZOrange-HEAD/azorange/AZutilities/sgeUtilities.py   AZOrange(Download)
def arrayJob(jobName = "AZOarray",jobNumber =1 ,jobParams = [], jobParamFile = "Params.pkl", jobQueue = "quick.q", jobScript = "", memSize = "150M", environSource = os.path.join(os.environ["AZORANGEHOME"],"templateProfile.bash")):   
 
        runPath = miscUtilities.createScratchDir(desc ="optQsub"+jobName, baseDir = AZOC.NFS_SCRATCHDIR)
        cwd = os.getcwd()
        os.chdir(runPath)
        if wd == "temporary":
            qsub = qsub + "#$ -cwd"             + "\n"
            self.wd = miscUtilities.createScratchDir(desc ="optQsub"+name, baseDir = AZOC.NFS_SCRATCHDIR)
        else:
            qsub = qsub + "#$ -wd " + wd        + "\n"

src/a/z/AZOrange-HEAD/azorange/AZutilities/competitiveWorkflow.py   AZOrange(Download)
            learners[ML] = MLMETHODS[ML](name = ML)
 
            runPath = miscUtilities.createScratchDir(baseDir = AZOC.NFS_SCRATCHDIR, desc = "competitiveWorkflow_BuildModel")
            trainData.save(os.path.join(runPath,"trainData.tab"))
 
        print "ERROR: modelSavePath or statisticsSavePath already exists."
        return {}
    runPath = miscUtilities.createScratchDir(baseDir = os.path.realpath(runningDir), desc = "competitiveWorkflow")
    statistics = getStatistics(data, runPath, os.path.join(runPath,"statistics.pkl"), mlList, queueType = queueType, getAllModels = False, callBack = callBack)
    model = getModel(data, mlList, savePath = os.path.join(runPath,"modelStat.pkl"), queueType = queueType, callBack = callBack)

src/a/z/AZOrange-HEAD/orange/OrangeWidgets/Classify/OWCombiQSAR.py   AZOrange(Download)
        else:
            statPath =  os.path.join(str(self.statPath),"statistics.pkl")
        runPath = miscUtilities.createScratchDir(desc = "CombiQSAR", baseDir = AZOC.NFS_SCRATCHDIR)
 
 

src/a/z/AZOrange-HEAD/azorange/trainingMethods/AZorngPLS.py   AZOrange(Download)
        trainingData = dataUtilities.getDataWithoutUnusedValues(trainingData,True)
        # Create path for the Orange data
        scratchdir = miscUtilities.createScratchDir(desc="PLS")
        OrngFile = os.path.join(scratchdir,"OrngData.tab")
 

src/a/z/AZOrange-HEAD/tests/source/AZorngParamOptMPITest.py   AZOrange(Download)
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest_RF_MPI")
        evalM = "AZutilities.evalUtilities.CA"
        fMin = False
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest_CvANN_MPI")
        evalM = "AZutilities.evalUtilities.CA"
        fMin = False
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest_CvSVM_MPI")
        evalM = "AZutilities.evalUtilities.CA"
        fMin = False
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest_SVM_MPI")
        evalM = "AZutilities.evalUtilities.CA"
        fMin = False
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest_SVM_MPI_2")
        evalM = "AZutilities.evalUtilities.CA"
        fMin = False

src/a/z/AZOrange-HEAD/tests/source/AZorngParamOptTest.py   AZOrange(Download)
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="RFTest")
 
        # Create an interface for setting optimizer parameters
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest")
 
        # Load the optimization parameters from the default configuration (AZLearnersParamsConfig.py)
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest")
 
        # Run the appspack which will configure the input learner and aditionaly return 
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="ParamOptTest")
 
        # Run the appspack which will configure the input learner and aditionaly return 
 
        # Create a directory for running the appspack (if not defined it will use the present working directory)
        runPath = miscUtilities.createScratchDir(desc="RFTest")
 
        # Create an interface for setting optimizer parameters

src/a/z/AZOrange-HEAD/tests/source/AZorngConsensus.py   AZOrange(Download)
            predictions.append(classifier(ex))
 
        scratchdir = miscUtilities.createScratchDir(desc="ConsensusSaveLoadTest")
        classifier.write(os.path.join(scratchdir,"./CM.model"))
 
            predictions.append(classifier(ex))
 
        scratchdir = miscUtilities.createScratchDir(desc="ConsensusSaveLoadTest")
        print scratchdir
        classifier.write(os.path.join(scratchdir,"./CM.model"))
            predictions.append(classifier(ex))
 
        scratchdir = miscUtilities.createScratchDir(desc="ConsensusSaveLoadTest")
        classifier.write(os.path.join(scratchdir,"./CM.model"))
 
 
        # Act
        scratchdir = miscUtilities.createScratchDir(desc="ConsensusSaveLoadTest")
        discreteClassifier.write(os.path.join(scratchdir,"./CM.model"))
 
 
        # Act
        scratchdir = miscUtilities.createScratchDir(desc="ConsensusSaveLoadTest")
        expressionClassifier.write(os.path.join(scratchdir,"./CM.model"))
 

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