def _copyAllocatedStates(self):
<EOL>if self.verbosity > <NUM_LIT:1> or self.retrieveLearningStates:<EOL><INDENT>(activeT, activeT1, predT, predT1) = self.cells4.getLearnStates()<EOL>self.lrnActiveState['<STR_LIT>'] = activeT1.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.lrnActiveState['<STR_LIT:t>'] = activeT.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.lrnPredictedState['<STR_LIT>'] = predT1.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.lrnPredictedState['<STR_LIT:t>'] = predT.reshape((self.numberOfCols, self.cellsPerColumn))<EOL><DEDENT>if self.allocateStatesInCPP:<EOL><INDENT>assert False<EOL>(activeT, activeT1, predT, predT1, colConfidenceT, colConfidenceT1, confidenceT,<EOL>confidenceT1) = self.cells4.getStates()<EOL>self.cellConfidence['<STR_LIT:t>'] = confidenceT.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.cellConfidence['<STR_LIT>'] = confidenceT1.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.colConfidence['<STR_LIT:t>'] = colConfidenceT.reshape(self.numberOfCols)<EOL>self.colConfidence['<STR_LIT>'] = colConfidenceT1.reshape(self.numberOfCols)<EOL>self.infActiveState['<STR_LIT>'] = activeT1.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.infActiveState['<STR_LIT:t>'] = activeT.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.infPredictedState['<STR_LIT>'] = predT1.reshape((self.numberOfCols, self.cellsPerColumn))<EOL>self.infPredictedState['<STR_LIT:t>'] = predT.reshape((self.numberOfCols, self.cellsPerColumn))<EOL><DEDENT>
If state is allocated in CPP, copy over the data into our numpy arrays.