def compute_value(grid, goal, cost):
value = get_init_value_grid(grid, goal, MAX_COST)
policy = get_init_policy(grid, goal)
change = OrderedSet()
change |= (get_neighbors(grid, goal))
while change:
current_cell = change.pop()
stochastic_cost, optimal_direction = get_min_cost(
grid, value, current_cell)
if stochastic_cost + cost < value[current_cell[0]][current_cell[1]]:
value[current_cell[0]][current_cell[1]] = stochastic_cost + cost
policy[current_cell[0]][current_cell[1]] = optimal_direction
neighbors = get_neighbors(grid, current_cell)
change |= (neighbors)
return value, policy
def compute_value(grid, goal, cost):
value = get_init_value_grid(grid, goal, 99)
policy = get_init_policy(grid, goal)
change = OrderedSet()
change |= (get_neighbors(grid, goal))
while change:
current_cell = change.pop(last=False)
min_cost, min_direction = get_min_cost(grid, value, current_cell)
if min_cost + cost < value[current_cell[0]][current_cell[1]]:
value[current_cell[0]][current_cell[1]] = min_cost + cost
policy[current_cell[0]][current_cell[1]] = min_direction
neighbors = get_neighbors(grid, current_cell)
change |= (neighbors)
for row in policy: print(row)
for row in value: print(row)
return value
class KBucket(object):
def __init__(self, rangeLower, rangeUpper, ksize):
self.range = (rangeLower, rangeUpper)
self.nodes = OrderedDict()
self.replacementNodes = OrderedSet()
self.touchLastUpdated()
self.ksize = ksize
def touchLastUpdated(self):
self.lastUpdated = time.time()
def getNodes(self):
return self.nodes.values()
def split(self):
midpoint = (self.range[0] + self.range[1]) / 2
one = KBucket(self.range[0], midpoint, self.ksize)
two = KBucket(midpoint + 1, self.range[1], self.ksize)
for node in self.nodes.values():
bucket = one if node.long_id <= midpoint else two
bucket.nodes[node.id] = node
return (one, two)
def removeNode(self, node):
if node.id not in self.nodes:
return
# delete node, and see if we can add a replacement
del self.nodes[node.id]
if len(self.replacementNodes) > 0:
newnode = self.replacementNodes.pop()
self.nodes[newnode.id] = newnode
def hasInRange(self, node):
return self.range[0] <= node.long_id <= self.range[1]
def isNewNode(self, node):
return node.id not in self.nodes
def addNode(self, node):
"""
Add a C{Node} to the C{KBucket}. Return True if successful,
False if the bucket is full.
If the bucket is full, keep track of node in a replacement list,
per section 4.1 of the paper.
"""
if node.id in self.nodes:
del self.nodes[node.id]
self.nodes[node.id] = node
elif len(self) < self.ksize:
self.nodes[node.id] = node
else:
self.replacementNodes.push(node)
return False
return True
def depth(self):
sp = shared_prefix([n.id for n in self.nodes.values()])
return len(sp)
def head(self):
return self.nodes.values()[0]
def __getitem__(self, id):
return self.nodes.get(id, None)
def __len__(self):
return len(self.nodes)