def testQuantPickle(self): # " testing QuantDataSet pickling " self.setUpQuantLoad() DataUtils.WritePickledData( RDConfig.RDCodeDir + '/ML/Data/test_data/testquant.qdat.pkl', self.d) with open(RDConfig.RDCodeDir + '/ML/Data/test_data/testquant.qdat.pkl', 'rb') as f: vNames = pickle.load(f) qBounds = pickle.load(f) ptNames = pickle.load(f) examples = pickle.load(f) d = MLData.MLQuantDataSet(examples, varNames=vNames, qBounds=qBounds, ptNames=ptNames) assert self.d.GetNPts() == d.GetNPts(), 'nPts wrong' assert self.d.GetNVars() == d.GetNVars(), 'nVars wrong' assert self.d.GetNResults() == d.GetNResults(), 'nResults wrong' assert self.d.GetVarNames() == d.GetVarNames(), 'varNames wrong' assert self.d.GetPtNames() == d.GetPtNames(), 'ptNames wrong' assert self.d.GetNPossibleVals() == d.GetNPossibleVals( ), 'nPossible Wrong' assert self.d.GetQuantBounds() == d.GetQuantBounds( ), 'quantBounds Wrong' assert self.d.GetResults() == d.GetResults(), 'GetResults wrong' assert self.d.GetAllData()[1] == d.GetAllData()[1], 'GetAllData wrong' assert self.d.GetInputData()[3] == d.GetInputData( )[3], 'GetInputData wrong' assert self.d.GetNamedData()[2] == d.GetNamedData( )[2], 'GetNamedData wrong'
def _setupMultiTree(self): examples = [[0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 2], [0, 1, 1, 2], [1, 0, 0, 2], [1, 0, 1, 2], [1, 1, 0, 2], [1, 1, 1, 0]] data = MLData.MLQuantDataSet(examples) attrs = range(0, data.GetNVars()) t1 = ID3.ID3Boot(data.GetAllData(), attrs, data.GetNPossibleVals()) self.t1 = t1 self.examples = examples
def _setupPyMultiTree(self): from rdkit.ML.InfoTheory import entropy ID3.entropy.InfoEntropy = entropy.PyInfoEntropy ID3.entropy.InfoGain = entropy.PyInfoGain examples = [[0, 1, 0, 0], [0, 0, 0, 1], [0, 0, 1, 2], [0, 1, 1, 2], [1, 0, 0, 2], [1, 0, 1, 2], [1, 1, 0, 2], [1, 1, 1, 0]] data = MLData.MLQuantDataSet(examples) attrs = range(0, data.GetNVars()) t1 = ID3.ID3Boot(data.GetAllData(), attrs, data.GetNPossibleVals()) self.t1 = t1 self.examples = examples
def BuildQuantDataSet(fileName): """ builds a data set from a .qdat file **Arguments** - fileName: the name of the .qdat file **Returns** an _MLData.MLQuantDataSet_ """ with open(fileName, 'r') as inFile: varNames, qBounds = ReadVars(inFile) ptNames, examples = ReadQuantExamples(inFile) data = MLData.MLQuantDataSet(examples, qBounds=qBounds, varNames=varNames, ptNames=ptNames) return data