def __init__(
self,
domain,
logger,
initial_representation,
discretization=20,
maxBatchDicovery=1,
batchThreshold=0,
bagSize=100000,
sparsify=False,
):
self.selectedFeatures = []
self.iFDD_ONLINETHRESHOLD = 1 # This is dummy since omptd will not use ifdd in the online fashion
self.maxBatchDicovery = maxBatchDicovery
self.batchThreshold = batchThreshold
self.initial_representation = initial_representation
self.iFDD = iFDD(
domain,
logger,
self.iFDD_ONLINETHRESHOLD,
initial_representation,
sparsify=0,
discretization=discretization,
useCache=1,
)
self.bagSize = bagSize
self.features_num = self.initial_representation.features_num
self.isDynamic = True
super(OMPTD, self).__init__(domain, logger, discretization)
self.fillBag()
self.totalFeatureSize = self.bagSize
self.selectedFeatures = range(
self.initial_representation.features_num
) # Add initial features to the selected list
self.remainingFeatures = arange(
self.features_num, self.bagSize
) # Array of indicies of features that have not been selected
self.show()
if self.logger:
self.logger.log("Initial Representation:\t%s" % className(self.initial_representation))
self.logger.log("Bag Size:\t\t%d" % self.bagSize)
self.logger.log("Batch Threshold:\t\t%0.3f" % self.batchThreshold)
self.logger.log("Max Batch Discovery:\t%d" % self.maxBatchDicovery)
def featureType(self):
return self.initial_representation.featureType()
if __name__ == "__main__":
STDOUT_FILE = "out.txt"
JOB_ID = 1
OUT_PATH = "Results/Temp"
# logger = Logger('%s/%d-%s'%(OUT_PATH,JOB_ID,STDOUT_FILE))
logger = Logger()
discovery_threshold = 1
# domain = MountainCar()
domain = SystemAdministrator("/../Domains/SystemAdministratorMaps/20MachTutorial.txt")
initialRep = IndependentDiscretizationCompactBinary(domain, logger)
rep = iFDD(domain, logger, discovery_threshold, initialRep, debug=0, useCache=1)
rep.theta = arange(rep.features_num * domain.actions_num) * 10
print "Initial [0,1,20] => ",
print rep.findFinalActiveFeatures([0, 1, 20])
print "Initial [0,20] => ",
print rep.findFinalActiveFeatures([0, 20])
rep.showCache()
print "discover 0,20"
phi_s = zeros(rep.features_num)
phi_s[0] = 1
phi_s[20] = 1
rep.discover(phi_s, discovery_threshold + 1)
rep.showFeatures()
rep.showCache()
print "Initial [0,20] => ",
print rep.findFinalActiveFeatures([0, 20])
