def setDefaultParameters(self): self.super__clearParametersVector() V = Vector() V.addElement("1D") V.addElement("2D") butt = RadioButtonPG("Output", V) self.addParameter(butt) BoolPG = BooleanPG("Use Defaults", Boolean(3 == 3)) self.addParameter(BoolPG) #----------- 1D ----------------- Qbins = QbinsPG("Enter Q bins", None) #-------------2D---------------- Qxmin = FloatPG("Enter Min Qx", -.5) Qxmax = FloatPG("Enter Min Qx", .5) Qymin = FloatPG("Enter Min Qx", -.5) Qymax = FloatPG("Enter Min Qx", .5) NQxDivs = IntegerPG("Number bins in Qx dir", 200) NQyDivs = IntegerPG("Number bins in Qy dir", 200) self.addParameter(Qbins) self.addParameter(Qxmin) self.addParameter(Qxmax) self.addParameter(Qymin) self.addParameter(Qymax) self.addParameter(NQxDivs) self.addParameter(NQyDivs) #parameter 8 S = [ self.getParameter(3), self.getParameter(4), self.getParameter(5), self.getParameter(6), self.getParameter(7), self.getParameter(8) ]
def __call__(self): params = Vector() params.addElement(Integer(6)) params.addElement(Integer(3)) result = client.execute("sample.sumAndDifference", params) sum = result.get("sum") grinder.logger.info("SUM %d" % sum)
def getResult(self): SampleFileName = self.getParameter(0).value BackGroundFileName = self.getParameter(1).value useCadmium = self.getParameter(2).getbooleanValue() if useCadmium: CadmiumFileName = self.getParameter(3).value else: CadmiumFileName = "" calcTransmission = self.getParameter(4).getbooleanValue() if calcTransmission: TransmissionFileName = "" else: TransmissionFileName = self.getParameter(5).value SampleDataSets = ScriptUtil.load(SampleFileName) if SampleDataSets == None: return ErrorString("Could not load Sample File") BackGroundDataSets = ScriptUtil.load(BackGroundFileName) if BackGroundDataSets == None: return ErrorString("Could not load BackGroundFile") if useCadmium: CadmiumDataSets = ScriptUtil.load(CadmiumFileName) if CadmiumDataSets == None: return ErrorString("Cannot load Cadmium File") else: pass else: CadmiumDataSets = [DataSet.EMPTY_DATA_SET, DataSet.EMPTY_DATA_SET] n = SampleDataSets[1].getData_entry(0).getX_scale().getNum_x() - 1 if calcTransmission: NeutronDelay = self.getParameter(6).getfloatValue() polyfitIndx1 = self.getParameter(7).getintValue() polyfitIndx2 = self.getParameter(8).getintValue() polyDegree = self.getParameter(9).getintValue() sqrtWeight = self.getParameter(10).getbooleanValue() TransmissionDataSet = CalcTransmission( SampleDataSets[0], BackGroundDataSets[0], CadmiumDataSets[0], SampleDataSets[1], useCadmium, NeutronDelay, polyfitIndx1, polyfitIndx2, polyDegree, sqrtWeight).getResult() if isinstance(TransmissionDataSet, ErrorString): return TransmissionDataSet else: TransmissionDataSet = ReadTransmission(TransmissionFileName, n).getResult() if isinstance(TransmissionDataSet, ErrorString): return TransmissionDataSet V = Vector() V.addElement(SampleDataSets[0]) V.addElement(SampleDataSets[1]) V.addElement(BackGroundDataSets[0]) V.addElement(BackGroundDataSets[1]) V.addElement(CadmiumDataSets[0]) V.addElement(CadmiumDataSets[1]) V.addElement(Boolean(useCadmium)) V.addElement(TransmissionDataSet) return V
def test_enumerations(self): vec = Vector() items = range(10) for i in items: vec.addElement(i) expected = 0 for i in vec: self.assertEquals(i, expected, 'testing __iter__ on java.util.Vector') expected = expected + 1 expected = 0 for i in iter(vec): self.assertEquals(i, expected, 'testing iter(java.util.Vector)') expected = expected + 1
def test_enumerations(self): vec = Vector() items = list(range(10)) for i in items: vec.addElement(i) expected = 0 for i in vec: self.assertEqual(i, expected, 'testing __iter__ on java.util.Vector') expected = expected + 1 expected = 0 for i in iter(vec): self.assertEqual(i, expected, 'testing iter(java.util.Vector)') expected = expected + 1
def getResult(self): SensitivityFilename=self.getParameter(0).value EfficiencyFilename=self.getParameter(1).value useBackGroundTransmission =self.getParameter(2).value if useBackGroundTransmission: BackGroundTransmissionFilename=self.getParameter(3).value else: BackGroundTransmissionFilename ="" SensitivityDataSets = ReadFlood(SensitivityFilename, 128,128).getResult() if isinstance( SensitivityDataSets, ErrorString): return SensitivityDataSets EfficiencyDataSet =Read3Col1D( EfficiencyFilename,"Efficiency").getResult() if isinstance( EfficiencyDataSet, ErrorString): return EfficiencyDataSet D = EfficiencyDataSet.getData_entry(0) xsc = D.getX_scale() n=xsc.getNum_x() if useBackGroundTransmission: BackGroundTransmissionDataSet =ReadTransmission(BackGroundTransmissionFilename,n).getResult() if isinstance( BackGroundTransmissionDataSet, ErrorString): return BackGroundTransmissionDataSet else: pass else: BackGroundTransmissionDataSet = EMPTY_DATA_SET V = Vector() V.addElement( SensitivityDataSets.elementAt(0)) V.addElement( EfficiencyDataSet) V.addElement( BackGroundTransmissionDataSet) return V;
def _add_nodes(self, curTop, dir): """ Recursive implementation to fill the tree with filenames and directories :param curTop: current top directory :param dir: next directory :return: None """ curPath = dir.getPath() if os.path.isdir(curPath): nodePath = os.path.basename(curPath) curDir = DefaultMutableTreeNode(nodePath) if curTop != None: # should only be null at root curTop.add(curDir) ol = Vector() tmp = dir.list() for i in xrange(0, len(tmp)): ol.addElement(tmp[i]) thisObject = None files = Vector() # Make two passes, one for Dirs and one for Files. This is #1. for i in xrange(0, ol.size()): thisObject = ol.elementAt(i) if curPath == self._dir: newPath = thisObject else: newPath = os.path.join(curPath, thisObject) f = File(newPath) if f.isDirectory(): self._add_nodes(curDir, f) else: files.addElement(thisObject) # Pass two: for files. Collections.sort(files) for i in xrange(0, files.size()): f = files.elementAt(i) #if f.split('.')[-1] != 'html': curDir.add(DefaultMutableTreeNode(files.elementAt(i))) return curDir
def getResult(self): Dimension = self.getParameter(0).getStringValue() useDefaults = self.getParameter(1).value if Dimension == "1D": self.getParameter(7).setValue(Integer(-200)) self.getParameter(8).setValue(Integer(-200)) if useDefaults: Q = Vector() Q.addElement(Float(.0035)) X = .0035 for i in range(1, 117, 1): X = X * 1.05 Y = Float(X) Q.addElement(Float(X)) return Q else: return self.getParameter(2).getValue() else: Q = Vector() Q.addElement(self.getParameter(3).getValue()) Q.addElement(self.getParameter(4).getValue()) Q.addElement(self.getParameter(5).getValue()) Q.addElement(self.getParameter(6).getValue()) return Q
print_test('strings', 3) from java.lang import Integer, String assert Integer.valueOf('42') == 42, 'Python string to Java string' print_test('arrays', 3) chars = ['a', 'b', 'c'] assert String.valueOf(chars) == 'abc', 'char array' print_test('Enumerations', 3) from java.util import Vector vec = Vector() items = range(10) for i in items: vec.addElement(i) expected = 0 for i in vec: assert i == expected, 'testing __iter__ on java.util.Vector' expected = expected + 1 expected = 0 for i in iter(vec): assert i == expected, 'testing iter(java.util.Vector)' expected = expected + 1 print_test('create java objects', 2) from java.math import BigInteger
print 'strings' from java.lang import Integer, String assert Integer.valueOf('42') == 42, 'Python string to Java string' print 'arrays' chars = ['a', 'b', 'c'] assert String.valueOf(chars) == 'abc', 'char array' print 'Enumerations' from java.util import Vector vec = Vector() items = range(10) for i in items: vec.addElement(i) expected = 0 for i in vec: assert i == expected, 'testing __iter__ on java.util.Vector' expected = expected+1 expected = 0 for i in iter(vec): assert i == expected, 'testing iter(java.util.Vector)' expected = expected+1 print 'create java objects' from java.math import BigInteger
raise TestFailed except io.FileNotFoundException: pass try: io.FileInputStream("doesnotexist") raise TestFailed except IOError: pass print 'java.util.Vector\'s can\'t be used in for loops #7' from java.util import Vector vec = Vector() vec.addElement(1) vec.addElement(10) vec.addElement(100) sum = 0 for x in vec: sum = sum + x assert sum == 111 print 'Exception tuple contains nulls #8' str(Exception) print '0.001 comes out as 0.0010 #11' assert str(0.001) == '0.001'
except io.FileNotFoundException: pass try: io.FileInputStream("doesnotexist") raise TestFailed except IOError: pass print_test('java.util.Vector\'s can\'t be used in for loops #7') from java.util import Vector vec = Vector() vec.addElement(1) vec.addElement(10) vec.addElement(100) sum = 0 for x in vec: sum = sum+x assert sum == 111 print_test('Exception tuple contains nulls #8') str(Exception) print_test('0.001 comes out as 0.0010 #11') assert str(0.001) == '0.001'
def mimicGATest(): popBegin = 1 popEnd = 101 keepBegin = 1 keepEnd = 90 mutBegin = 1 mutEnd = 90 itersBegin = 1 itersEnd = 200 samples = 10 keep = 2 problemSize = N mimicRange = (problemSize) iters = 1 paramRanges = Vector(8) paramRanges.addElement(popBegin) paramRanges.addElement(popEnd) paramRanges.addElement(keepBegin) paramRanges.addElement(keepEnd) paramRanges.addElement(mutBegin) paramRanges.addElement(mutEnd) paramRanges.addElement(itersBegin) paramRanges.addElement(itersEnd) totalParamSize1 = (popEnd - popBegin + 1) + (keepEnd - keepBegin + 1) + ( mutEnd - mutBegin + 1) + (itersEnd - itersBegin + 1) allParamValues = range(popBegin, popEnd + 1) + range( keepBegin, keepEnd + 1) + range(mutBegin, mutEnd + 1) + range( itersBegin, itersEnd + 1) totalParamSize = len(allParamValues) metaFun = RamysEvalMetafunc(ranges) discreteDist = RamysMimicDistribution( paramRanges) #DiscreteUniformDistribution(problemSize) distFunc = DiscreteDependencyTree(.1, allParamValues) findGA = GenericProbabilisticOptimizationProblem(metaFun, discreteDist, distFunc) mimic = MIMIC(samples, keep, findGA) fit = FixedIterationTrainer(mimic, iters) fit.train() print str(N) + ": MIMIC finds GA : " + str(ef.value(mimic.getOptimal()))
def mimicGATest(): popBegin = 1 popEnd = 101 keepBegin = 1 keepEnd = 90 mutBegin = 1 mutEnd = 90 itersBegin = 1 itersEnd = 200 samples = 10 keep = 2 problemSize = N mimicRange = (problemSize) iters = 1 paramRanges = Vector(8) paramRanges.addElement(popBegin) paramRanges.addElement(popEnd) paramRanges.addElement(keepBegin) paramRanges.addElement(keepEnd) paramRanges.addElement(mutBegin) paramRanges.addElement(mutEnd) paramRanges.addElement(itersBegin) paramRanges.addElement(itersEnd) totalParamSize1 = (popEnd - popBegin +1) + (keepEnd - keepBegin +1) + (mutEnd - mutBegin +1) + (itersEnd - itersBegin +1) allParamValues = range(popBegin, popEnd+1)+range(keepBegin, keepEnd+1)+range(mutBegin, mutEnd+1)+range(itersBegin, itersEnd+1) totalParamSize = len(allParamValues) metaFun = RamysEvalMetafunc(ranges) discreteDist = RamysMimicDistribution(paramRanges) #DiscreteUniformDistribution(problemSize) distFunc = DiscreteDependencyTree(.1, allParamValues) findGA = GenericProbabilisticOptimizationProblem(metaFun, discreteDist, distFunc) mimic = MIMIC(samples, keep, findGA) fit = FixedIterationTrainer(mimic, iters) fit.train() print str(N) + ": MIMIC finds GA : " + str(ef.value(mimic.getOptimal()))
def to_vect(it): v = Vector() for e in it: v.addElement(e) return v