def evaluteFrontier(self,parent,utilities,tfam,pca,cmodels):
from SongData import SongData, findevent
from generate_random_policy import updateNodeAndFeature
terminus = None
candidates = []
prospects = copy.deepcopy(parent.transformedprospects)
for action in prospects.keys():
candidate = copy.deepcopy(parent)
candidate.generatedbyaction = action
event = findevent(action, candidate.context.songPitchMap.getPitchMax(SongData.REST))
updateNodeAndFeature(candidate,event,tfam,pca,cmodels)
if action == SongData.END:
terminus = candidate
elif candidate.transformedfeature not in utilities[candidate.feature.vector[0]]:
utilities[candidate.feature.vector[0]][candidate.transformedfeature] = 0
candidates.append(candidate)
reward = max([utilities[c.feature.vector[0]][c.transformedfeature] for c in candidates if c.feature != SongData.END])
maxlist = [(c,prospects[c.generatedbyaction]) for c in candidates if c.feature!=SongData.END and utilities[c.feature.vector[0]][c.transformedfeature]==reward]
#if tie for best action, draw based on corpus incidence, otherwise list will only have one element anywayz
drawbest= lambda s : random.choice(sum(([v]*wt for v,wt in s),[]))
argcand = drawbest(maxlist)
if terminus is not None:
total_prospects = sum([prospects[pro] for pro in prospects])
if np.random.uniform(0,1) < float(prospects[SongData.END])/total_prospects:
reward, argcand = 0, terminus
return reward, argcand
#def actions(self, feature):
# if state in self.terminals:
# return [None]
# else:
# total = sum([ tfam[state.feature][action] for action in tfam[state.feature].keys() ])
# return [ [float(count) / total, nextstate(state, action)] for action in tfam[state.feature].keys() ]
def spawn(self, node):
children = []
encountered = node.feature in self.encounteredstates
if not encountered:
self.encounteredstates[node.feature] = dict()
encountered_children = self.encounteredstates[node.feature]
for action in node.prospects.keys():
if action != SongData.END:
if action not in encountered_children:
encountered_children[action] = Counter()
newevent = findevent(action, node.context.songPitchMap.getPitchMax(SongData.REST))
context = copy.deepcopy(node.context)
context.update(newevent)
candidate = Node(context, None, node, None, None)
candidate.feature = context.feature.vector
if candidate.feature in self.tfam:
encountered_children[action][candidate.feature] += 1
if not encountered or candidate.feature not in encountered_children[action]:
candidate.prospects = copy.deepcopy(self.tfam[candidate.feature])
candidate.generatedbyaction = action
children.append(candidate)
self.frontier += children
return children
