def ZDTtest(): z = ZDT4(5) hi = [1] + [5] * 4 lo = [0] + [-5] * 4 gengine = GALE(hi, lo, z.argD, z.objD, 50, z.getObj, z.vaildX, z.candidate) pdb.set_trace() out = gengine.gale() pdb.set_trace() print out
def main(): """ Runs independently from command line to test the GALE algorithm. """ graphPerformance = False # Built in graphing ability, currently not functional, but mechanism is in place. trainData = "2_1000_0_1600_0_0_CV_0_Train.txt" testData = "2_1000_0_1600_0_0_CV_0_Test.txt" outProg = "GH_GALE_ProgressTrack" outPop = "GH_GALE_PopulationOut" bitLength = 1 # This implementation is not yet set up to handle other rule representations, or bit encoding lengths. CVpartitions = 10 trackCycles = 1 iterInput = '5.10.20' xdim = 10 ydim = 10 dist = 2 wild = 0.75 prune = 1 #Figure out the iteration stops for evaluation, and the max iterations. iterList = iterInput.split('.') for i in range(len(iterList)): iterList[i] = int(iterList[i]) lastIter = iterList[len(iterList)-1] #Sets up up algorithm to be run. GALEConstants.setConstants(prune, wild) e = GALE_Environment(trainData,testData,bitLength) sampleSize = e.getNrSamples() gale = GALE(e, outProg, outPop, bitLength, CVpartitions, graphPerformance, xdim, ydim, dist) #Set some GALE parameters. if trackCycles == 'Default': gale.setTrackingIterations(sampleSize) else: gale.setTrackingIterations(trackCycles) gale.setNumberOfTrials(lastIter, iterList) #Run the GALE Algorithm gale.runGALE()
13: Wild frequency - 0.5, 0.75 """ # ************************************************************************************************* graphPerformance = False # Built in graphing ability, currently not functional, but mechanism is in place. NOT MEANT TO BE USED ON CLUSTER. numArgs = len(argv) print "Arguments: " + str(numArgs) if numArgs == 14: if argv[1] == 'gh': #Different rule representations could be programmed but have not been in this implementation. print ("Format Training data: "+argv[2]+" using a "+argv[6]+" bit coding scheme.") #Sets up up algorithm to be run. GALEConstants.setConstants(int(argv[12]), float(argv[13])) e = GALE_Environment(str(argv[2]), str(argv[3]), int(argv[6])) sampleSize = e.getNrSamples() gale = GALE(e, argv[4], argv[5], int(argv[6]), int(argv[7]), graphPerformance, int(argv[10]), int(argv[10]), int(argv[11])) #Figure out the iteration stops for evaluation, and the max iterations. iterList = argv[9].split('.') for i in range(len(iterList)): iterList[i] = int(iterList[i]) lastIter = iterList[len(iterList)-1] #Set some GALE parameters. if argv[9] == 'Default': gale.setTrackingIterations(sampleSize) else: gale.setTrackingIterations(int(argv[8])) gale.setNumberOfTrials(lastIter, iterList) #Run the GALE Algorithm
def schafferTest(): s = Schaffer() gengine = GALE(s.hi, s.lo, s.argD, s.objD, 100, s.getObj, s.validX, s.candidate) #pdb.set_trace() out = gengine.gale() print out
def squareTest(): q = Square() gengine = GALE(q.hi, q.lo, q.argD, q.objD, 100, q.getObj, q.validX, q.candidate) out = gengine.gale() print out