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)
