Python PathDefaults.getTempDir方法代码示例

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testLoadParams(self):
        try:
            lmbda = 0.01

            alterRegressor = PrimalRidgeRegression(lmbda)
            egoRegressor = PrimalRidgeRegression(lmbda)
            predictor = EgoEdgeLabelPredictor(alterRegressor, egoRegressor)

            params = [0.1, 0.2]
            paramFuncs = [egoRegressor.setLambda, alterRegressor.setLambda]
            fileName = PathDefaults.getTempDir() + "tempParams.pkl"

            predictor.saveParams(params, paramFuncs, fileName)

            params2 = predictor.loadParams(fileName)

            self.assertTrue(params2[0][0] == "apgl.predictors.PrimalRidgeRegression")
            self.assertTrue(params2[0][1] == "setLambda")
            self.assertTrue(params2[0][2] == 0.1)

            self.assertTrue(params2[1][0] == "apgl.predictors.PrimalRidgeRegression")
            self.assertTrue(params2[1][1] == "setLambda")
            self.assertTrue(params2[1][2] == 0.2)
        except IOError as e:
            logging.warn(e)

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testEstimate(self):
        #Lets set up a simple model based on normal dist
        abcParams = ABCParameters()
        
        epsilonArray = numpy.array([0.5, 0.2, 0.1])
        posteriorSampleSize = 20

        #Lets get an empirical estimate of Sprime
        model = NormalModel(abcMetrics)
        model.setMu(theta[0])
        model.setSigma(theta[1])
        
        Sprime = abcMetrics.summary(model.simulate()) 
        logging.debug(("Real summary statistic: " + str(Sprime)))

        thetaDir = PathDefaults.getTempDir()
        
        abcSMC = ABCSMC(epsilonArray, createNormalModel, abcParams, thetaDir)
        abcSMC.maxRuns = 100000
        abcSMC.setPosteriorSampleSize(posteriorSampleSize)
        thetasArray = abcSMC.run()
        thetasArray = numpy.array(thetasArray)

        meanTheta = numpy.mean(thetasArray, 0)
        logging.debug((thetasArray.shape))
        logging.debug(thetasArray)
        logging.debug(meanTheta)

        print(thetasArray.shape[0], posteriorSampleSize)

        #Note only mean needs to be similar
        self.assertTrue(thetasArray.shape[0] >= posteriorSampleSize)
        self.assertEquals(thetasArray.shape[1], 2)
        self.assertTrue(numpy.linalg.norm(theta[0] - meanTheta[0]) < 0.2)

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testReadFromMatFile(self):
        numExamples = 10
        dir = PathDefaults.getTempDir()
        fileName = dir + "examplesList1"
        X = rand(numExamples, 10)
        
        ml = ExamplesList(numExamples)
        ml.addDataField("X", X)
        ml.writeToMatFile(fileName)
        
        ml2 = ExamplesList.readFromMatFile(fileName)
        self.assertTrue(ml == ml2)

        Y = rand(numExamples, 20)

        ml.addDataField("Y", Y)
        ml.writeToMatFile(fileName)
        
        ml2 = ExamplesList.readFromMatFile(fileName)
        self.assertTrue(ml == ml2)
        
        Z = rand(numExamples, 50)

        ml.addDataField("Z", Z)
        ml.writeToMatFile(fileName)
        
        ml2 = ExamplesList.readFromMatFile(fileName)
        self.assertTrue(ml == ml2)

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testSaveParams(self):
        try:
            lmbda = 0.01

            alterRegressor = PrimalRidgeRegression(lmbda)
            egoRegressor = PrimalRidgeRegression(lmbda)
            predictor = EgoEdgeLabelPredictor(alterRegressor, egoRegressor)

            params = [0.1, 0.2]
            paramFuncs = [egoRegressor.setLambda, alterRegressor.setLambda]
            fileName = PathDefaults.getTempDir() + "tempParams.pkl"

            predictor.saveParams(params, paramFuncs, fileName)
        except IOError as e:
            logging.warn(e)

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testSaveLoad(self):
        try:
            vList = VertexList(self.numVertices, self.numFeatures)
            vList.setVertex(0, numpy.array([1, 2, 3]))
            vList.setVertex(1, numpy.array([4, 5, 6]))
            vList.setVertex(2, numpy.array([7, 8, 9]))

            tempDir = PathDefaults.getTempDir()
            fileName = tempDir + "vList"

            vList.save(fileName)
            vList2 = VertexList.load(fileName)

            self.assertTrue((vList.getVertices() == vList2.getVertices()).all())
        except IOError as e:
            logging.warn(e)
            pass 

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testWriteToMatFile(self):
        numExamples = 100
        X = rand(numExamples, 10)
        ml = ExamplesList(numExamples)

        dir = PathDefaults.getTempDir()
        fileName = dir + "examplesList1"
        
        #Try writing with no examples 
        self.assertRaises(ValueError, ml.writeToMatFile, fileName)
        
        #Now, add a data field and try writing 
        ml.addDataField("X", X)
        ml.writeToMatFile(fileName)
        
        ml.addDataField("Y", X)
        ml.writeToMatFile(fileName)

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def testSaveLoad(self):
        try:
            vList = GeneralVertexList(self.numVertices)
            vList.setVertex(0, "abc")
            vList.setVertex(1, 12)
            vList.setVertex(2, "num")

            tempDir = PathDefaults.getTempDir()
            fileName = tempDir + "vList"

            vList.save(fileName)

            vList2 = GeneralVertexList.load(fileName)

            for i in range(self.numVertices):
                self.assertEquals(vList.getVertex(i), vList2.getVertex(i))
        except IOError as e:
            logging.warn(e)
            pass 

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
    def profile(command, globalVars, localVars, numStats=30):
        """
        Just profile the given command with the global and local variables
        and print out the cumulative and function times. 
        """
        try:
            import pstats
            import cProfile
        except ImportError:
            raise ImportError("profile() requires pstats and cProfile")

        tempDirectory = PathDefaults.getTempDir()
        profileFileName = tempDirectory + "profile.cprof"

        logging.info("Starting to profile ...")
        cProfile.runctx(command, globalVars, localVars, profileFileName)
        logging.info("Done")
        stats = pstats.Stats(profileFileName)
        stats.strip_dirs().sort_stats("cumulative").print_stats(numStats)
        stats.strip_dirs().sort_stats("time").print_stats(numStats)

# 需要导入模块: from apgl.util.PathDefaults import PathDefaults [as 别名]
# 或者: from apgl.util.PathDefaults.PathDefaults import getTempDir [as 别名]
 def setUp(self):
     tempDir = PathDefaults.getTempDir()
     self.fileName = tempDir + "abc"