for k in isf.flatten(sampleProblems): iw, iv, ic, ip, instanceType, solution = isf.extractInstance(dataDec, k) isf.exportInstance(iw, iv, ic, ip, k, instanceType, solution, folderOut, instanceNumber) instanceNumber = instanceNumber + 1 ## INSTANCE ORDER GENERATION and param2.txt + paramMRI.txt export # Generates the instance randomization order for bN blocks of tN trials for nTypes instance types nInstances = tN * bN for i in range(0, nOrderRandomizations): instanceOrder = isf.generateInstanceOrder(tN, bN, sampleSizePerBin) #Exports 'param2.txt' with the required input for the task isf.exportTaskInfo(tN, bN, instanceOrder, nInstances, folderOut, i) #Generates Intertrial intervals and exports it to paramMRI.txt isf.exportITIs(tN, bN, folderOut) ###################### # SAT and MZN instanceType Comparison # dataS = dataSAT[0] dataS = isf.binCapProf(dataS, nbins) dataS = isf.addInstanceType(dataS, nCap, nProf, nProfNO, nProfYES, quantileLow, quantileUpper, 'decisions') #Subset the data frame and change the name of dataInstance dataM = dataMZN[0] dataM = isf.binCapProf(dataM, nbins)
nTypesDec = 6 # Samples randomly from each instance-type sampleSizePerBin # Output: list of sublists. Each sublist has sampleSizePerBin size with the instances ID sizePerBin = int(tNDec * bNDec / (nTypesDec + 2)) #Total number (Including all blocks) instances per Type sampleSizePerBin = [ sizePerBin, sizePerBin, sizePerBin, sizePerBin, 2 * sizePerBin, 2 * sizePerBin ] nInstances = tNDec * bNDec for i in range(nOrderRandomizationsMin, nOrderRandomizations): instanceOrder = isf.generateInstanceOrder(tNDec, bNDec, sampleSizePerBin) isf.exportTaskInfo( tNDec, bNDec, instanceOrder, nInstances, folderOutDec, i) #Exports 'param2.txt' with the required input for the task #Optimisation folderOutOpt = folder + 'KS-IC/Data/Simulations/instanceSelectionOutput/optimisation/' #folderOutOpt='/Users/juanpf/Google Drive/Melbourne/UNIMELB/Complexity Project/Code/Instance Selection/output/optimization/' #bN blocks of tN trials #requires tN to be multiple of the number of instances types there are tNOpt = 9 bNOpt = 2 possibleTypesOpt = [1, 3, 5] nTypesOpt = len(possibleTypesOpt) sizePerBin = int(tNOpt * bNOpt / (nTypesOpt)) sampleSizePerBin = [sizePerBin, sizePerBin, sizePerBin]