RESIDUES = enum('A', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'K', 'L', 'M', 'N', 'P', 'Q', 'R', 'S', 'T', 'V', 'W', 'Y') # parameter reanges to optimize ensembleSizes = numpy.array([60, 70, 80, 90, 100]) backrubTemps = numpy.array([0.9]) #boltzmannTemps = numpy.array([-1.0]) # set below steepnessRange = numpy.array([0.5, 5]) minWeights = numpy.array([0, 0, 0, 0, 0, 0]) maxWeights = numpy.array([1, 1, 1, 1, 1, 1]) optimizer = Optimizer(MACROSTATES) optimizer.readTargetFrequencies(targetFreqs) print('pos before loading data: ', optimizer.nPositions) #optimizer.readData(data) optimizer.readMicrostateData(data, minPosition=minPosition) print('pos after loading data: ', optimizer.nPositions) # examine model for model_id in optimizer.models: if verbose: print('id:', model_id) print('obj:', optimizer.models[model_id]) print(optimizer.models[model_id].nMacrostates) print(optimizer.models[model_id].ensembleSize) print(optimizer.models[model_id].backrubTemp) print(optimizer.models[model_id].boltzmannTemp) print(optimizer.models[model_id].weights) print(optimizer.models[model_id].steepness) print(optimizer.models[model_id].nPositions) print(optimizer.models[model_id].macrostatesUsed) print(optimizer.models[model_id].useMicrostateData)