def __call__(self, graph, start_node, target_node):
frontier = PriorityQueue()
current_node = start_node
distance_dict = defaultdict(lambda: infinity)
distance_dict[current_node] = 0
ancestors_dict = {}
visited_set = set()
while True:
neighbors = graph.get_neighbors(current_node)
current_distance = distance_dict[current_node]
for neighbor in neighbors:
if neighbor not in visited_set and (current_distance + 1) < distance_dict[neighbor]:
distance_dict[neighbor] = current_distance + 1
ancestors_dict[neighbor] = current_node
frontier.put((self.cost_function(distance_dict[neighbor], neighbor, target_node), neighbor))
self.nodes_expanded += 1
visited_set.add(current_node)
self.nodes_visited += 1
if current_node == target_node:
return list(reversed(find_ancestors(ancestors_dict, current_node, start_node)))
else:
try:
current_node = frontier.get_nowait()[1]
except Empty:
break
def __init__(self, name, directory_scenarii,
clean_func, state_file, cmd_display_func):
self.name = name
self.list_scenario = []
self.selected_scenario = []
self.directory_scenarii = directory_scenarii
self.clean_system = clean_func
self.cmd_display_func = cmd_display_func
self.state_file = state_file
# save the current context to restaure it at the end of the testsuite
backends = [ line for line in process.execute(['get', 'config',
'backends'])[0].split('\n') if 'U' in line
and line != '' ]
self.user_context = backends[0].split('(')[0]
self.current_context = self.user_context
self.to_run = PriorityQueue()
self.failed = PriorityQueue()
self.passed = []
self.best_state = 1
self.working = Event()
# used to modify the best state behaviour when running one one test
# or the whole TS.
self.best_state_only_one = 0
# used to build initial testsuite data
self.batch_run = False
self.interactive = False
def getAlphaBeta( game, player, other, reward=AlphaBeta(-100,100), depth=10, tab=0 ):
'''
alpha: minimum bound of the outcome -- currently, evaluate of best move possible by other
beta: maximum bound of the outcome -- currently, evaluate of best move possible by player
returns: (alpha, beta, evaluation, move)
'''
# evaluation is the current value of board, assuming no more moves in future
# alpha == beta == finalvalue if we figure out the outcome.
reward.evaluation = game.evaluate_cached( player )
move = Move(-1,-1)
# base case: can't play further, lost
if (reward.evaluation==reward.beta):
# print 'Player', player, 'won!!!'
return AlphaBetaOfMove(AlphaBeta(reward.beta, reward.beta, reward.beta), move)
# base case: can't evaluate further
if (depth == 0):
return AlphaBetaOfMove(reward, move )
q = PriorityQueue()
for m in game.next_moves( ):
# g2 = copy.deepcopy( game )
assert game.move( player, m)
try:
oponent_reward = AlphaBeta(-reward.beta, -reward.alpha, -reward.evaluation)
oponent_reward = getAlphaBeta(game, other, player, reward=oponent_reward, depth=depth-1, tab=tab+1 ).alphabeta
player_reward = AlphaBeta(-oponent_reward.beta, -oponent_reward.alpha, -oponent_reward.evaluation)
q.put_nowait( AlphaBetaOfMove( player_reward, m ) )
finally:
assert game.unmove(player, m)
# if( tab < 1 ):
# print ("\t"*tab), (player,row,col), (other,other_r,other_c), (other_alpha,other_beta,other_evaluation), (next_alpha,next_beta,evaluation), update
if( q.empty() ):
return AlphaBetaOfMove( reward, Move(-1,-1) )
else:
return q.get_nowait()
def longestIncreasingPath(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: int
"""
m = len(matrix)
if m == 0: return 0
n = len(matrix[0])
queue = PriorityQueue()
res = 0
mem = [[0] * n for _ in range(m)]
dirs = [(-1,0),(1,0),(0,-1),(0,1)]
def next_smalles(i,j):
results = [0]
for di, dj in dirs:
ni, nj = di + i, dj + j
if ni >= 0 and ni < m and nj >= 0 and nj < n and matrix[i][j] > matrix[ni][nj]:
results += mem[ni][nj],
return results
for i in range(m):
for j in range(n):
queue.put((matrix[i][j],i,j))
while not queue.empty():
v, i, j = queue.get()
mem[i][j] = max(next_smalles(i,j)) + 1
res = max(res, mem[i][j])
return res
class EventQueue(object):
def __init__(self):
"""Event queue for executing events at
specific timepoints.
In current form it is NOT thread safe."""
self.q = PriorityQueue()
def schedule(self, f, ts):
"""Schedule f to be execute at time ts"""
self.q.put(EqItem(ts, f))
def schedule_recurring(self, f, interval):
"""Schedule f to be run every interval seconds.
It will be run for the first time interval seconds
from now"""
def recuring_f():
f()
self.schedule(recuring_f, time.time() + interval)
self.schedule(recuring_f, time.time() + interval)
def run(self):
"""Execute events in the queue as timely as possible."""
while True:
event = self.q.get()
now = time.time()
if now < event.ts:
time.sleep(event.ts - now)
event.f()
def prepPriorityQueue(game):
global sudokuQueue
sudokuQueue = PriorityQueue()
for i in range(0,N):
for j in range(0,N):
if((not game[i][j].domain==None) and (len(game[i][j].domain )!=0)):
sudokuQueue.put((len(game[i][j].domain),game[i][j]))
def conflicts(board):
conlist=PriorityQueue()
clist=[]
global conflictval,n,m,k
#consistency check along col,row and grid
for row in range(int(n)):
for col in range(int(n)):
recurval=0
for c in range(int(n)):
#print "row check",board[row][c]
if board[row][c] == board[row][col]:
recurval=recurval+1
for r in range(int(n)):
if board[r][col] == board[row][col]:
recurval=recurval+1
for r1 in range(int(m)):
for c1 in range(int(k)):
if (board[r1+row-(row%int(m))][c1+col-(col%int(k))] == board[row][col]):
recurval=recurval+1
if(recurval>3):
clist.append((row,col))
conlist.put((recurval,(row,col)))
#conflictval[(row,col)]=recurval
return clist
class PoolStreamData(StreamData):
def __init__(self, feat_path, feature_maker, label_path=None, fold_in_cv=None):
self.pool = PriorityQueue(100000)
super(PoolStreamData, self).__init__(feat_path, feature_maker, label_path, fold_in_cv)
self.fill_pool()
def fill_pool(self):
while not self.pool.full():
try:
ins = super(PoolStreamData,self).next()
self.pool.put((random.random(),ins)) # insert ins with random priority --> kind of random shuffle
except StopIteration:
break
def rewind(self):
self.pool = PriorityQueue(100000)
super(PoolStreamData,self).rewind()
self.fill_pool()
def next(self):
try:
(_,ins) = self.pool.get(False)
except Empty:
raise StopIteration
self.fill_pool()
return ins
def __buildFromDB(self):
try:
dbConnection = self.pool.connection()
cursor = dbConnection.cursor()
cursor.execute("""select request_spec, id from priority_queue""")
moreDBElement = True
while moreDBElement:
item = cursor.fetchone()
if item:
request_spec = json.loads(item[0])
idRecord = item[1]
instance_properties = request_spec.get("instance_properties")
userId = instance_properties.get("user_id")
projectId = instance_properties.get("project_id")
timestamp = instance_properties.get("created_at")
requestPQ = {
"priority": 0,
"userId": userId,
"projectId": projectId,
"timestamp": timestamp,
"retryCount": 0,
"idRecord": idRecord,
}
PriorityQueue.put(self, (0, requestPQ))
else:
moreDBElement = False
except MySQLdb.Error, e:
if dbConnection:
dbConnection.rollback()
LOG.info("Error %d: %s" % (e.args[0], e.args[1]))
class MinimumWeightMatchingWithEdges:
"""Find a minimum weight matching using a greedy method.
Attributes
----------
graph : input undirected graph
mate : dict with nodes (values are edges or None)
cardinality : number
"""
# Bedzie potrzebne do problemu chinskiego listonosza.
def __init__(self, graph):
"""The algorithm initialization."""
if graph.is_directed():
raise ValueError("the graph is directed")
self.graph = graph
self.mate = dict((node, None) for node in self.graph.iternodes())
self.cardinality = 0
self._pq = PriorityQueue()
def run(self):
"""Executable pseudocode."""
for edge in self.graph.iteredges():
self._pq.put((edge.weight, edge))
while not self._pq.empty():
_, edge = self._pq.get()
if (self.mate[edge.source] is None and
self.mate[edge.target] is None):
self.mate[edge.source] = edge
self.mate[edge.target] = ~edge
self.cardinality += 1
def run(self): """ basically calculate the shortest path with A* search algorithm """ origin = Node(self.startPose) #PriorityQueue of nodes pq = PriorityQueue() currentNode = origin # Compute the AStar search algorithm while not currentNode.pos.equals(self.goalPose) and not rospy.is_shutdown(): children = self.expandNode(currentNode) for node in children: pq.put((node.cost(), node)) #it is ranked by the cost if(pq.qsize() == 0): #no more nodes to be expanded print "didn't find a path" currentNode = origin break # pop the "closest" node to the goal currentNode = pq.get()[1] self.calcPathWayPoints(currentNode) #lastNode
def find_corners_for_room(self, room_center):
"""
returns the 4 corners of given room center
:param room_center:
:return: [right_up, left_up, left_down, right_down]
"""
[x, y] = room_center
prio_q = PriorityQueue()
[right_up, left_up, left_down, right_down] = [None, None, None, None]
# find the 4 closest corners
for corner in self.found_corners:
dist = Calc.get_dist_from_point_to_point(room_center, corner)
prio_q.put([dist, corner])
for i in xrange(4):
[x_c, y_c] = prio_q.get()[1]
if x_c < x and y_c > y:
left_up = [x_c, y_c]
elif x_c < x and y_c < y:
left_down = [x_c, y_c]
elif x_c > x and y_c > y:
right_up = [x_c, y_c]
elif x_c > x and y_c < y:
right_down = [x_c, y_c]
return [right_up, left_up, left_down, right_down]
def segment(img) :
g = numpy.array(img.getdata())
g = g.reshape(img.size)
gx = g[:-1,1:] - g[:-1,:-1]
gy = g[1:,:-1] - g[:-1,:-1]
gms = gx * gx + gy * gy
seg = Image.new('L', gms.shape)
taken = numpy.zeros(seg.size)
#print 'original local mininum'
for i in range(seg.size[0]) :
for j in range(seg.size[1]) :
if localmin(gms, i, j) :
taken[i][j] = 1
seg.putpixel((j, i), img.getpixel((j, i)))
#print (j, i), img.getpixel((j, i))
q = PriorityQueue(-1)
#print 'expand'
for i in range(seg.size[0]) :
for j in range(seg.size[1]) :
if taken[i][j] > 0 :
addNeighbor(seg, gms, taken, i, j, q)
#print q.qsize()
while not q.empty() :
(i, j) = q.get()[1]
addNeighbor(seg, gms, taken, i, j, q)
#print q.qsize()
return seg
class EventManager(object):
""" Keeps track of and triggers events in our network simulation
Instance Properties:
Q - A priority queue of events ordered by time
"""
def __init__(self):
self._Q = PriorityQueue()
self.t = 0
def add_event(self, t, event, args):
""" Add an event onto the event queue
:param t: The time of the event
:param event: The event to add
:param args: A list of args for the event
"""
self._Q.put((t, event, args))
def pop_event(self):
""" Getting the first event off of the event queue.
:return: Returns a tuple consisting of the time, event, and the args
for the event
"""
return self._Q.get()
def has_events(self):
""" Whether or not the manager has any more events on its queue
:return: True or False based on whether its empty
"""
return not self._Q.empty()
class PriorityScheduler():
def __init__(self):
self._readyq = PriorityQueue()
self._pcbsQ = []
self._counter = 0
self._quantum = -1
def add(self, pcb):
self._readyq.put((pcb._priority, self._counter, pcb))
self._pcbsQ.append(pcb)
self._counter += 1
def get_pcb(self):
#El [2] es porque el next() me devuelve la tupla que guarda la PQ, por lo que le pido el objeto.
self.pcb_to_give = self._readyq.get()[2]
self._pcbsQ.remove(self.pcb_to_give)
for pcb in self._pcbsQ:
pcb.increase_priority()
return self.pcb_to_give
def set_scheduler(self, scheduler):
scheduler.set_as_pq()
def get_quantum(self):
return self._quantum
def consume_solution_queue(q):
priority_queue = PriorityQueue()
proposed_solutions = set()
try:
while True:
fetch = True
while fetch:
try:
item = q.get_nowait()
if item[1] not in proposed_solutions:
priorized_item = (-1 * (item[0] / len(item[1])), item[0], item[1])
priority_queue.put(priorized_item)
proposed_solutions.add(item[1])
except Empty:
fetch = False
try:
solution = priority_queue.get_nowait()
print_solution(solution[1], solution[2])
except Empty:
pass
time.sleep(2)
except KeyboardInterrupt:
pass
def get(self, time, *args, **kwargs):
a, b, item = PriorityQueue.get(self, *args, **kwargs)
if a == time:
return item
else:
PriorityQueue.put(self, (a, 0, item))
raise NameError("No more tasks scheduled!")
def solve(self): nexts = PriorityQueue() while True: self.step += 1 self.current.visited = True possibilities = visitable_points(self.current, self.maze) for node in possibilities: nexts.put((node.get_cost(), node)) next = nexts.get() try: while next[1].visited or (not are_neighbors(next[1].coords(), self.current.coords())): next = nexts.get(False) self.current = next[1] self.solution.append((self.step,self.current, str(self))) except Queue.Empty: try: self.current = self.solution.pop()[1] self.step -= 1 except IndexError: print "No solution" exit(1) self.update()
class CrawlManager(object):
def __init__(self, config):
try: self.queue_size = int(config.get('queue_size'))
except: self.queue_size = 1000
try: self.num_threads = int(config.get('num_threads'))
except: self.num_threads = 10
self.queue = PriorityQueue(maxsize=self.queue_size)
self.processors = ProcessorManager(config)
for i in range(self.num_threads):
t = Thread(target=self.queue_target,
name="CrawlDaemon-%s" % i)
t.daemon = True
t.start()
def queue_target(self):
while True:
try:
queue_entry = self.queue.get(True)
self.handle(queue_entry[1])
self.queue.task_done()
except Exception, e:
log.exception(e)
class MaxHeap(object):
"""
Max Heap for the greedy algorithms
"""
def __init__(self):
self.popped = set()
self.pq = PriorityQueue()
def pop(self):
"""
returns next item and its priority on the priority queue and removes item from the priority queue.
Returns (-1, 0) if queue is empty
"""
while not self.pq.empty():
a = self.pq.get()
if a[1] not in self.popped:
self.popped.add(a[1])
return a[1], -a[0], a[2]
return (-1, 0, None)
def update(self, x, v, aux = None):
"""
updates key x with value v. If x is currently not in the priority queue, x is inserted
"""
if x in self.popped:
self.popped.remove(x)
self.pq.put((-v, x, aux))
def __main__():
#check aruguments
if len(sys.argv) == 1:
details()
sys.exit()
if len(sys.argv) < 2:
usage()
try:
opts, args = getopt.getopt(sys.argv[2:],"l:")
except getopt.GetoptError:
usage()
for opt, arg in opts:
if opt == "-l":
global _log
_log = str(arg)
else:
print ("Unrecognized option: "+opt+"\n")
usage()
annot = open(sys.argv[1],"r")
if (annot == None):
print ("Bad annotation name: "+sys.argv[1])
sys.exit()
logfile = open(_log,"w")
if (logfile == None):
print ("Bad logfile name: "+_log)
sys.exit()
#reg ex
annotpat = re.compile("\w+_(\d+)\s+(\S+)\s+(\S+)\s+(\S+)\s+(\S+)(.*)")
negQueue = PriorityQueue()
#read the vcf file...
for line in annot:
line = line.rstrip()
m = annotpat.match(line)
if (m == None):# if we find a weird line...
sys.stderr.write("Non-standard line (annot):\n\t"+line+"\n")
continue
else:
scaf = int(m.group(1))
start = int(m.group(2))
direction = m.group(5)
if direction == "-":
negQueue.put_nowait((start, line))
continue
else:
while not negQueue.empty():
print(negQueue.get()[1])
print(line)
def expand_tree(node):
priorityqueue = PriorityQueue()
while True:
# Check if current node is the goal node
if node.pixels == goal:
break
surrounding_area = get_surrounding_pixels(node.pixels)
# Iterate through the all 8 pixels around the current x, y point
for current_pixel in surrounding_area:
# Only add pixel is a child if it isn't visisted already
if current_pixel[0] not in visited and isFree(current_pixel[0]):
# Create new node
#weight = edge_weight_distance(node.value)
next = Node(node, current_pixel[0])
next.set_value(current_pixel[1])
visited.add(next.pixels)
#nodesToExplore.append(next)
next = priorityqueue.put((next, next.value))
#node = nodesToExplore.popleft()
node = priorityqueue.get()[0]
# Once breaking, return the full path of the goal node
return node.return_full_path()
def __init__ (self, sock, addr, cwnd, ploss, pcorr): self.init = False self.end = False self.requesting = False self.sock = sock self.addr = addr self.ploss = ploss self.pcorr = pcorr self.cwnd = cwnd if self.cwnd <= 0: self.cwnd = WINDOW_SIZE self.attempt = 0 self.timer = None self.lock = threading.Lock() # PQueue will sort packets by segnum, so when inserting in queue, packets will be like: # Acks - segnum = 0 # Failed packets (for their segnum is securely < unset packets) # Unsent packets # So ordering is guaranteed and ACKs should be sent immediately self.buff = PQueue() # packets to send self.waiting = PQueue(cwnd) # packets wating for ACK self.seg = 0 # current packet self.ack = 0 # last valid ack self.nextSeg = random.randint(1,1000) # next expected packet
def p_mod_abs(domain_config, problem_config, solvers_config, max_iter=100):
hl_solver, ll_solver = ParseSolversConfig.parse(solvers_config, domain_config)
domain = ParseDomainConfig.parse(domain_config)
problem = ParseProblemConfig.parse(problem_config, domain)
if problem.goal_test():
return False, "Goal is already satisfied. No planning done."
n0 = HLSearchNode(hl_solver.translate_problem(problem), domain, problem)
Q = PriorityQueue()
Q.put((0, n0))
for _ in range(max_iter):
n = Q.get()[1]
if n.is_hl_node():
c_plan = n.plan(hl_solver)
c = LLSearchNode(c_plan)
Q.put((-n.heuristic(), n))
Q.put((-c.heuristic(), c))
elif n.is_ll_node():
n.plan(ll_solver)
if n.solved():
return n.curr_plan, None
Q.put((-n.heuristic(), n))
if n.gen_child():
fail_step, fail_pred = n.get_failed_pred()
n_problem = n.get_problem(fail_step, fail_pred)
c = HLSearchNode(hl_solver.translate_problem(n_problem), domain, n_problem, prefix=n.curr_plan.prefix(fail_step))
Q.put((-c.heuristic(), c))
return False, "Hit iteration limit, aborting."
def update(self): #Queues to manage downloading dateQ = Queue(0) xmlTrialQ = PriorityQueue(100) # Create the single SQLAlchemy thread to update DB records sqlaThread = threading.Thread(target=self.updateTrials, args=(dateQ, xmlTrialQ)) sqlaThread.daemon = True sqlaThread.start() startDate = self.fetchStartDate() delta = dt.date.today() - startDate dateList = [startDate + dt.timedelta(days=x) for x in range(0, delta.days)] print dateList # Add relevant dates to the list to be fetched for currentDate in dateList: dateQ.put(currentDate) print dateQ.queue numWorkerThreads = min(10, dateQ.qsize()) # Create n worker threads to fetch the zip files of updated content and produce xmlTrial objects for i in range(numWorkerThreads): t = threading.Thread(target=self.fetchUpdatedTrials, args=(dateQ, xmlTrialQ)) t.daemon = True t.start() dateQ.join() # block until all dates have been fetched xmlTrialQ.join() # block until all xmlTrials have been created
def _solve(board, searchfun):
"""
This is the top level function of the program. `board` is given to the
search function by placing it into an empty `PriorityQueue`.
A path to the result is returned.
"""
cost = manhattan_distance(board)
start = Node(0, cost, board, None)
queue = PriorityQueue()
queue.put(start)
visited = set()
result = searchfun(queue, visited)
def getpath(node, path):
path.append(node)
if node.parent is not None:
return getpath(node.parent, path)
else:
return path
if queue.empty():
# Something went wrong with the search algorithm.
raise ValueError("Bad search")
return getpath(result, [])
def order_domain_values(csp, variable):
"""Returns a list of (ordered) domain values for the given variable.
This method implements the least-constraining-value (LCV) heuristic; that is, the value
that rules out the fewest choices for the neighboring variables in the constraint graph
are placed before others.
"""
rating = 0 #To prioritize
queue = PriorityQueue()
lister = [] #List that is going to be returned
for value in variable.domain:
rating = 0 #Reset back to 0 for rating of a new value in the domain of the variable
for constraint in csp.constraints[variable]: #Get the constraints of the variable
for dim in constraint.var2.domain: #Check with all the value of the constraint varaibles domain to check if the value can be satisfied with these domain values
if (constraint.is_satisfied(value, dim)):
rating = rating + 1
queue.put((rating, value)) # Ordered by rating
while not queue.empty(): #Putting into a list
i = 0
holder = queue.get()
lister.insert(i, holder[1])
i = i + 1
return lister
def dijkstraQ(graph, initial):
visited = {initial: 0}
path = {}
nodes = PriorityQueue()
for node in graph.nodes:
nodes.put()
while nodes:
min_node = None
for node in nodes:
if node in visited:
if min_node is None:
min_node = node
elif visited[node] < visited[min_node]:
min_node = node
if min_node is None:
break
nodes.remove(min_node)
current_weight = visited[min_node]
for edge in graph.edges[min_node]:
try:
weight = current_weight + graph.distances[(min_node, edge)]
except:
continue
if edge not in visited or weight < visited[edge]:
visited[edge] = weight
path[edge] = min_node
return visited, path
def mapper():
reader = csv.reader(sys.stdin, delimiter='\t')
writer = csv.writer(sys.stdout, delimiter='\t',
quotechar='"', quoting=csv.QUOTE_ALL)
pq = PriorityQueue()
topsize = 10
result = []
for line in reader:
# YOUR CODE HERE
post = line[4]
if pq.qsize() < topsize:
pq.put((len(post), line))
else:
minpost = pq.get()
if minpost[0] >= post[0]:
pq.put((len(minpost), line))
else:
pq.put((len(post), line))
for i in range(topsize):
result.append(pq.get())
# writer.writerow(line)
result.sort(key=lambda x: x[0])
for r in result:
writer.writerow(r[1])
def neighbors(self): aux = PriorityQueue() neighbors = [] dx = [0, 0, 1, -1 ] dy = [1, -1, 0, 0 ] posx = 0 posy = 0 for i in range(self.size()): for j in range(self.size()): if self.blocks[i][j] == 0: posx = i posy = j break for k in range(4): nx = posx + dx[k] ny = posy + dy[k] if nx >= 0 and nx < self.size() and ny >= 0 and ny < self.size(): tmp = copy.deepcopy(self.blocks) tmp[posx][posy] = tmp[nx][ny] tmp[nx][ny] = 0 b = Board(tmp) aux.put((b.hamming(),b)) while not aux.empty(): neighbors.append(aux.get()[1]) return neighbors
def put(self, tup):
newtup = tup[0] * -1, tup[1], tup[2]
PriorityQueue.put(self, newtup)
def findOptimalPath(ghostCrd, pManCrd, scene):
global graph
drc = isAdjacent(Node(pManCrd),Node(ghostCrd),scene)
if drc:
return [(Node(ghostCrd),drc),(Node(ghostCrd),None)]
graph = generateStateGraph(ghostCrd, pManCrd, scene)
frontier = PriorityQueue()
# create start node
start = graph[repr(Node(ghostCrd))]
start.g = 0
# create frontier
frontier.put(start)
# keep track of visited states and previous min cost with
# dictionary
visited = {repr(start):start}
while not frontier.empty():
current_node = frontier.get()
# if node has already been pruned, ignore
if current_node.pruned:
continue
# check if node represents solution
if current_node == Node(pManCrd):
# reconstruct path using parent attribute
path = []
dest = current_node
while dest.parent:
path.append((dest.parent,[e.drc for e in dest.parent.edges if e.adjNode == dest][0]))
dest = path[-1][0]
return list(reversed(path))
# expand node by generating child nodes from legal moves
for edge in current_node.edges:
c = edge.adjNode
c.edges = graph[str(c)].edges
if any(c == edge.adjNode for edge in graph[repr(Node(pManCrd))].edges):
if c.crd[1] == pManCrd[1]:
minDist = min((abs(c.crd[0]-pManCrd[0]),'LEFT'),
(len(scene[0])-abs(c.crd[0]-pManCrd[0]),'RIGHT'))
else:
if c.crd[1] < pManCrd[1]:
minDist = (pManCrd[1]-c.crd[1],'DOWN')
else:
minDist = (c.crd[1]-pManCrd[1],'UP')
c.edges.add(Edge(graph[repr(Node(pManCrd))], *minDist))
c.g = current_node.g+edge.weight
c.h = heuristic(c, pManCrd,scene)
c.f = c.g+c.h
c.parent = current_node
# ignore if visited or path is not more efficient
# if path is more efficient, prune previous node
if repr(c) in visited:
if c.g >= visited[repr(c)].g:
continue
else:
visited[repr(c)].pruned = True
# add to visited nodes
visited[repr(c)] = c
# add to frontier
frontier.put(c)
def __init__(self):
self._timers = PriorityQueue()
self._map = {}
def __init__(self):
PriorityQueue.__init__(self)
self.counter = 0
def getItemAndPriority(self, *args, **kwargs):
_, _, item = PriorityQueue.get(self, *args, **kwargs)
return item, self.ppp[item]
def get(self, *args, **kwargs):
_, _, item = PriorityQueue.get(self, *args, **kwargs)
return item
def put(self, item, priority):
PriorityQueue.put(self, (priority, self.counter, item))
self.counter += 1
'''
Node class
and sample Priority Queue
'''
from Queue import PriorityQueue
pq = PriorityQueue()
class Node(object):
def __init__(self, level=None, path=None, bound=None):
self.level = level
self.path = path
self.bound = bound
def __cmp__(self, other):
return cmp(self.bound, other.bound)
def __str__(self):
return str(tuple([self.level, self.path, self.bound]))
if __name__ == '__main__':
pq = PriorityQueue()
pq.put(Node(2, [1, 2, 3], 6))
pq.put(Node(4, [1, 3, 2], 1))
pq.put(Node(1, [1, 2], 7))
while not pq.empty():
print pq.get()
pq.put(Node(3, [1, 2, 5], 12))
def __init__(self):
PriorityQueue.__init__(self)
self.first_element_changed = Condition(self.mutex)
class AsyncoreReactor(object):
_thread = None
_is_live = False
logger = logging.getLogger("Reactor")
def __init__(self):
self._timers = PriorityQueue()
self._map = {}
def start(self):
self._is_live = True
self._thread = threading.Thread(target=self._loop,
name="hazelcast-reactor")
self._thread.daemon = True
self._thread.start()
def _loop(self):
self.logger.debug("Starting Reactor Thread")
Future._threading_locals.is_reactor_thread = True
while self._is_live:
try:
asyncore.loop(count=10, timeout=0.01, map=self._map)
self._check_timers()
except select.error as err:
# TODO: parse error type to catch only error "9"
self.logger.warn("Connection closed by server.")
pass
except:
self.logger.exception("Error in Reactor Thread")
# TODO: shutdown client
return
self.logger.debug("Reactor Thread exited. %s" % self._timers.qsize())
self._cleanup_all_timers()
def _check_timers(self):
now = time.time()
while not self._timers.empty():
try:
_, timer = self._timers.queue[0]
except IndexError:
return
if timer.check_timer(now):
try:
self._timers.get_nowait()
except Empty:
pass
else:
return
def add_timer_absolute(self, timeout, callback):
timer = Timer(timeout, callback, self._cleanup_timer)
self._timers.put_nowait((timer.end, timer))
return timer
def add_timer(self, delay, callback):
return self.add_timer_absolute(delay + time.time(), callback)
def shutdown(self):
if not self._is_live:
return
self._is_live = False
for connection in self._map.values():
try:
connection.close(HazelcastError("Client is shutting down"))
except OSError, connection:
if connection.args[0] == socket.EBADF:
pass
else:
raise
self._map.clear()
self._thread.join()
def find_path(source, destination, mesh):
print "I'm in the method"
sx, sy = source
dx, dy = destination
sourcebox = None
destbox = None
visited = []
path = []
detail_points = {}
for box in mesh['boxes']:
x1, x2, y1, y2 = box
if x1 < sx and x2 > sx and y1 < sy and y2 > sy:
#visited.append(box)
sourcebox = box
if x1 < dx and x2 > dx and y1 < dy and y2 > dy:
#visited.append(box)
destbox = box
if sourcebox == destbox:
return [(source, destination)], [sourcebox]
#Dijkstra's Algorithm/ANY SEARCH THINGY HERE
dist = {}
prev = {}
dist[sourcebox] = 0
prev[sourcebox] = None
firstboxsource = (dist[sourcebox], sourcebox)
priorityQ = PriorityQueue()
priorityQ.put(firstboxsource)
standing_point = source
path = []
while not priorityQ.empty():
#print "I'm in an infinite loop!"
current = priorityQ.get()
visited.append(current[1])
if current[1] == destbox:
end = current[1]
boxes = []
while end is not None:
boxes.append(end)
#print prev[end]
end = prev[end]
stand = source
print boxes
for box in boxes:
path.append((stand, find_point(stand, box)))
stand = find_point(stand, box)
path.append((stand, destination))
print path
return path, visited
neighbors = mesh['adj'][current[1]]
for n in neighbors:
alt = dist[current[1]] + point_distance(
standing_point, find_point(standing_point, current[1]))
if n not in dist or alt < dist[n]:
standing_point = find_point(standing_point, current[1])
dist[n] = alt
prior = alt + heuristic_basic(destbox, current[1])
priorityQ.put((prior, n))
prev[n] = current[1]
'''#breadth first search
vertex = None
prev = {}
counter = 0
q = Queue()
q.put(sourcebox)
prev[sourcebox] = None
visited.append(sourcebox)
finalbox = None
while not q.empty():
v = q.get()
if box_equal(v, destbox):
finalbox = v
break
for n in mesh['adj'][v]:
if n not in visited:
q.put(n)
visited.append(n)
prev[n] = v'''
'''end = finalbox
path.append(((dx, dy), (get_midpoint(end))))
while prev[end] is not None:
path.append((get_midpoint(prev[end]), get_midpoint(end)))
end = prev[end]
path.append(((sx, sy), get_midpoint(end)))'''
print "No path!"
return [], visited
envObj.graph[b].adjList.append(Edge(a, wt))
#agent.budget = int(raw_input())
#envObj.congestion = int(raw_input())
# Calculate heuristic-----------------------DIJKSTRA----
#We will assume that agent always takes bus except when dist<3
agent = Agent(5) #agent(budget)
calcHeuristic(envObj, agent)
#-------------------------------------------
for i in range(3):
print("===============================================")
destinationNode = None
pq = PriorityQueue()
pq.put(QueueNode(envObj.source, 0, 0, None, State(envObj.source,Mode.bus, agent.budget)))
agent = Agent(10) #agent(budget)
envObj.congestion = (2 - i) * 50
print("Congestion = ", envObj.getCongestion(),"%")
print("Budget = ", agent.budget)
print("Source = ", envObj.graph[envObj.source].coord.toString())
print("Goal = ", envObj.graph[envObj.goal].coord.toString())
print("BusSpeed = ", agent.getBusSpeed(envObj))
print("BusFare = ", agent.busFare)
print("CycleSpeed = ", agent.getCycleSpeed())
while(not pq.empty()):
curr = pq.get()
# print(curr.state.toString())
if(envObj.isGoal(curr.ind)): #if agent reached the goal
destinationNode = curr
GLOBAL_FLOOD_COOLDOWN = timedelta(
seconds=config.getint('regexbot', 'global_flood_cooldown'))
MAX_MESSAGES = config.getint('regexbot', 'max_messages')
MAX_MESSAGE_SIZE = config.getint('regexbot', 'max_message_size')
try:
NICKSERV_PASS = str(config.get('regexbot', 'nickserv_pass'))
except:
NICKSERV_PASS = None
message_buffer = {}
last_message = datetime.now()
last_message_times = {}
flooders = {}
ignore_list = []
channel_list = []
user_timeouts = PriorityQueue()
channel_timeouts = PriorityQueue()
if config.has_section('ignore'):
for k, v in config.items('ignore'):
try:
ignore_list.append(regex.compile(str(v), regex.I))
except Exception, ex:
print "Error compiling regular expression in ignore list (%s):" % k
print " %s" % v
print ex
exit(1)
for channel in CHANNELS:
c = channel.lower()
message_buffer[c] = []
l3 = ListNode(2)
l3.next = ListNode(6)
lists = [l1, l2, l3]
# foreachListNode(mergeKLists1(lists))
foreachListNode(mergeKLists2(lists))
def HeapSort(list):
# 将 list 构建成堆
heapq.heapify(list)
heap = []
while list:
heap.append(heapq.heappop(lists))
list[:] = heap
return list
from Queue import PriorityQueue
q = PriorityQueue()
q.put(1)
q.put(5)
q.put(4)
q.put(3)
print q.task_done()
def __init__(self, _k):
self.q = PriorityQueue()
self.k = _k
self.s = 0
self.min = 0
def aStar(self, start, goal):
visited = []
goal = [int(goal[0]), int(goal[1])]
start = [int(start[0]), int(start[1])]
frontier = PriorityQueue()
path = []
bestPathSoFar = [9999999, []]
found = False
mult = 75
print(goal)
#if (self.gridToInd(start) == False):
# print("Robot is out of map!")
# return None
H = self.heuristic(start, goal)
frontier.put((H, 0, start, [start]))
print("H:", H, "*", mult, "=", H * mult)
#if (self.gridToInd(goal) == False):
# print("Goal is out of map!")
# return None
#goalInd = self.tmp
dist = [[1, 0], [-1, 0], [0, 1], [0, -1], [1, 1], [-1, 1], [1, -1],
[-1, -1]]
print(self.width * self.height)
print(self.grid[start[0]][start[1]])
print(self.grid[goal[0]][goal[1]])
H = H * mult
while not frontier.empty():
#for i in range(0,10):
current = frontier.get()
#print("New iter #")
#print(current)
#print(frontier.qsize())
#print(current[2], goal)
if current[2] == goal:
path = current[3]
break
if (current[2] in visited): continue
else: visited.append(current[2])
if (len(visited) > H): break
for k in range(len(dist)):
try:
#print("Cons: ", current[2][0] + dist[k][0], current[2][1] + dist[k][1])
if ([
current[2][0] + dist[k][0],
current[2][1] + dist[k][1]
] == goal):
print("GOAL IS FOUND!")
found = True
cost = current[1] + 1
if (k >= 4): cost += 0.41
#ind_cp =
path_cp = current[3][:]
path_cp.append(goal)
frontier = PriorityQueue()
frontier.put((priority, cost, goal, path_cp))
else:
#print(current[2][0] + dist[k][0], current[2][1] + dist[k][1], dist[k], self.grid[current[2][0] + dist[k][0]][current[2][1] + dist[k][1]])
if (not found and
((self.grid[current[2][0] +
dist[k][0]][current[2][1] + dist[k][1]]
< 26 and self.grid[current[2][0] + dist[k][0]][
current[2][1] + dist[k][1]] >= 0)
or len(current[3]) < self.threshould)):
ind = [
current[2][0] + dist[k][0],
current[2][1] + dist[k][1]
]
if (ind not in visited):
cost = current[1] + 1
if (k >= 4): cost += 0.41
#print("HERE")
heur = self.heuristic(ind, goal)
priority = cost + heur
path_cp = current[3][:]
path_cp.append(ind)
frontier.put((priority, cost, ind, path_cp))
#print("ADDED: ", priority, cost, ind, path_cp)
if bestPathSoFar[0] > heur:
bestPathSoFar = [heur, path_cp]
#visited.append(ind)
if (self.toPlot): self.plotPlan(ind)
except:
pass
print(frontier.qsize(), len(visited))
path_fin = []
# else:
# print("WTF IS GOING ON???")
if (len(path) == 0):
print("CANNOT FIND A PATH!")
print(bestPathSoFar)
#return bestPathSoFar[1]
if (bestPathSoFar[0] < 35
and len(bestPathSoFar[1]) > 12): #self.threshould+5
path = bestPathSoFar[1]
if (len(path) <= 10 or len(path) > 75): path = []
for ind2, n in enumerate(path):
# if (self.indToGrid(n)):
#print(self.grid[n[0]][n[1]])
print(ind2, n, self.grid[n[0]][n[1]])
#path_fin.append(np.array((n[0],n[1]), dtype=float))
if (ind2 < (self.threshould) or
(self.grid[n[0]][n[1]] <= 26 and self.grid[n[0]][n[1]] >= 0)):
path_fin.append(np.array((int(n[0]), int(n[1])), dtype=int))
return path_fin
class ConnectionPool(object):
"""
Container holding the :class:`~elasticsearch.Connection` instances,
managing the selection process (via a
:class:`~elasticsearch.ConnectionSelector`) and dead connections.
It's only interactions are with the :class:`~elasticsearch.Transport` class
that drives all the actions within `ConnectionPool`.
Initially connections are stored on the class as a list and, along with the
connection options, get passed to the `ConnectionSelector` instance for
future reference.
Upon each request the `Transport` will ask for a `Connection` via the
`get_connection` method. If the connection fails (it's `perform_request`
raises a `ConnectionError`) it will be marked as dead (via `mark_dead`) and
put on a timeout (if it fails N times in a row the timeout is exponentially
longer - the formula is `default_timeout * 2 ** (fail_count - 1)`). When
the timeout is over the connection will be resurrected and returned to the
live pool. A connection that has been peviously marked as dead and
succeedes will be marked as live (it's fail count will be deleted).
"""
def __init__(self,
connections,
dead_timeout=60,
timeout_cutoff=5,
selector_class=RoundRobinSelector,
randomize_hosts=True,
**kwargs):
"""
:arg connections: list of tuples containing the
:class:`~elasticsearch.Connection` instance and it's options
:arg dead_timeout: number of seconds a connection should be retired for
after a failure, increases on consecutive failures
:arg timeout_cutoff: number of consecutive failures after which the
timeout doesn't increase
:arg selector_class: :class:`~elasticsearch.ConnectionSelector`
subclass to use if more than one connection is live
:arg randomize_hosts: shuffle the list of connections upon arrival to
avoid dog piling effect across processes
"""
if not connections:
raise ImproperlyConfigured("No defined connections, you need to "
"specify at least one host.")
self.connection_opts = connections
self.connections = [c for (c, opts) in connections]
# remember original connection list for resurrect(force=True)
self.orig_connections = tuple(self.connections)
# PriorityQueue for thread safety and ease of timeout management
self.dead = PriorityQueue(len(self.connections))
self.dead_count = {}
if randomize_hosts:
# randomize the connection list to avoid all clients hitting same node
# after startup/restart
random.shuffle(self.connections)
# default timeout after which to try resurrecting a connection
self.dead_timeout = dead_timeout
self.timeout_cutoff = timeout_cutoff
self.selector = selector_class(dict(connections))
def mark_dead(self, connection, now=None):
"""
Mark the connection as dead (failed). Remove it from the live pool and
put it on a timeout.
:arg connection: the failed instance
"""
# allow inject for testing purposes
now = now if now else time.time()
try:
self.connections.remove(connection)
except ValueError:
# connection not alive or another thread marked it already, ignore
return
else:
dead_count = self.dead_count.get(connection, 0) + 1
self.dead_count[connection] = dead_count
timeout = self.dead_timeout * 2**min(dead_count - 1,
self.timeout_cutoff)
self.dead.put((now + timeout, connection))
logger.warning(
'Connection %r has failed for %i times in a row, putting on %i second timeout.',
connection, dead_count, timeout)
def mark_live(self, connection):
"""
Mark connection as healthy after a resurrection. Resets the fail
counter for the connection.
:arg connection: the connection to redeem
"""
try:
del self.dead_count[connection]
except KeyError:
# race condition, safe to ignore
pass
def resurrect(self, force=False):
"""
Attempt to resurrect a connection from the dead pool. It will try to
locate one (not all) eligible (it's timeout is over) connection to
return to the live pool. Any resurrected connection is also returned.
:arg force: resurrect a connection even if there is none eligible (used
when we have no live connections). If force is specified resurrect
always returns a connection.
"""
# no dead connections
if self.dead.empty():
# we are forced to return a connection, take one from the original
# list. This is to avoid a race condition where get_connection can
# see no live connections but when it calls resurrect self.dead is
# also empty. We assume that other threat has resurrected all
# available connections so we can safely return one at random.
if force:
return random.choice(self.orig_connections)
return
try:
# retrieve a connection to check
timeout, connection = self.dead.get(block=False)
except Empty:
# other thread has been faster and the queue is now empty. If we
# are forced, return a connection at random again.
if force:
return random.choice(self.orig_connections)
return
if not force and timeout > time.time():
# return it back if not eligible and not forced
self.dead.put((timeout, connection))
return
# either we were forced or the connection is elligible to be retried
self.connections.append(connection)
logger.info('Resurrecting connection %r (force=%s).', connection,
force)
return connection
def get_connection(self):
"""
Return a connection from the pool using the `ConnectionSelector`
instance.
It tries to resurrect eligible connections, forces a resurrection when
no connections are availible and passes the list of live connections to
the selector instance to choose from.
Returns a connection instance and it's current fail count.
"""
self.resurrect()
connections = self.connections[:]
# no live nodes, resurrect one by force and return it
if not connections:
return self.resurrect(True)
# only call selector if we have a selection
if len(connections) > 1:
return self.selector.select(self.connections)
# only one connection, no need for a selector
return connections[0]
def calc_max_coverage_coor(xmin, ymin, zmin, xmax, ymax, zmax, rmax):
def bot_clips_bbox(bot, bbox_xmin, bbox_ymin, bbox_zmin, bbox_xmax,
bbox_ymax, bbox_zmax):
## test if this bot's octahedral sensor-volume
## intersects the bbox {x,y,z}min - {x,y,z}max
assert (bbox_xmin <= bbox_xmax)
assert (bbox_ymin <= bbox_ymax)
assert (bbox_zmin <= bbox_zmax)
dist = 0
dist += (bbox_xmin - bot[0]) * (bot[0] < bbox_xmin)
dist += (bot[0] - bbox_xmax) * (bot[0] > bbox_xmax)
dist += (bbox_ymin - bot[1]) * (bot[1] < bbox_ymin)
dist += (bot[1] - bbox_ymax) * (bot[1] > bbox_ymax)
dist += (bbox_zmin - bot[2]) * (bot[2] < bbox_zmin)
dist += (bot[2] - bbox_zmax) * (bot[2] > bbox_zmax)
return (dist <= bot[3])
def pq_add(pq, bbox_xmin, bbox_ymin, bbox_zmin, cur_bbox_size):
bbox_xmax = bbox_xmin + cur_bbox_size - 1
bbox_ymax = bbox_ymin + cur_bbox_size - 1
bbox_zmax = bbox_zmin + cur_bbox_size - 1
num_bots_in_bbox = 0
for bot in bots:
num_bots_in_bbox += bot_clips_bbox(bot, bbox_xmin, bbox_ymin,
bbox_zmin, bbox_xmax,
bbox_ymax, bbox_zmax)
if (num_bots_in_bbox == 0):
return False
## find Manhattan distance from origin to the closest corner of the bounding-box
## box with largest number of bots clipping it should be processed first, negate
## the count since PQ is constructed as a min-heap
## in case of ties, PQ will yield the box with smallest origin distance and size
## (ordering by size first and distance second also works and is slightly faster
## on the given input)
## this processing order ensures the problem is solved when reaching a 1x1x1 box
## since 1) no larger box can intersect more bot sensor-volumes, and 2) no other
## 1x1x1 box intersecting as many sensor-volumes can be closer to the origin
##
min_orig_dist_x = min(abs(bbox_xmin), abs(bbox_xmax))
min_orig_dist_y = min(abs(bbox_ymin), abs(bbox_ymax))
min_orig_dist_z = min(abs(bbox_zmin), abs(bbox_zmax))
min_orig_dist = min_orig_dist_x + min_orig_dist_y + min_orig_dist_z
##!! pq.put((-num_bots_in_bbox, min_orig_dist, cur_bbox_size, bbox_xmin, bbox_ymin, bbox_zmin))
pq.put((-num_bots_in_bbox, cur_bbox_size, min_orig_dist, bbox_xmin,
bbox_ymin, bbox_zmin))
return True
## determine size of the power-of-two bounding cube
max_size = max(xmax - xmin, ymax - ymin, zmax - zmin, rmax)
bbox_size = next_power_of_two(max_size)
bbox_queue = PriorityQueue()
pq_add(bbox_queue, xmin, ymin, zmin, bbox_size)
while (bbox_queue.qsize() > 0):
##!! (num_bots, orig_dist, bb_size, x, y, z) = bbox_queue.get()
(num_bots, bb_size, orig_dist, x, y, z) = bbox_queue.get()
if (bb_size == 1):
return ((x, y, z), orig_dist, -num_bots)
bb_size >>= 1
## insert top-left corner coordinates of each child bounding-box
pq_add(bbox_queue, x, y, z, bb_size)
pq_add(bbox_queue, x, y, z + bb_size, bb_size)
pq_add(bbox_queue, x, y + bb_size, z, bb_size)
pq_add(bbox_queue, x, y + bb_size, z + bb_size, bb_size)
pq_add(bbox_queue, x + bb_size, y, z, bb_size)
pq_add(bbox_queue, x + bb_size, y, z + bb_size, bb_size)
pq_add(bbox_queue, x + bb_size, y + bb_size, z, bb_size)
pq_add(bbox_queue, x + bb_size, y + bb_size, z + bb_size, bb_size)
return ((0, 0, 0), 0, 0)
from Queue import Queue
from Queue import PriorityQueue
a1 = 'a1'
a2 = 'a2'
a3 = 'a3'
a4 = 'a4'
a5 = 'a5'
b1 = 'b1'
b2 = 'b2'
b3 = 'b3'
b4 = 'b4'
b5 = 'b5'
q = Queue()
pq = PriorityQueue()
for i in xrange(5):
p = 5 - i
q.put("a" + str(p))
q.put("b" + str(p))
pq.put((p, "a" + str(p)))
pq.put((p, "b" + str(p)))
for i in xrange(5):
p = 5 - i
q.put("a" + str(p) + str(i + 5))
q.put("b" + str(p) + str(i + 5))
pq.put((p, "a" + str(p) + str(i + 5)))
pq.put((p, "b" + str(p) + str(i + 5)))
from pritunl import logger
from pritunl import mongo
from pritunl import listener
from Queue import PriorityQueue
import pymongo
import random
import bson
import datetime
import threading
import time
import bson
import collections
running_queues = {}
runner_queues = [PriorityQueue() for _ in xrange(3)]
thread_limits = [
threading.Semaphore(x) for x in (
settings.app.queue_low_thread_limit,
settings.app.queue_med_thread_limit,
settings.app.queue_high_thread_limit,
)
]
def add_queue_item(queue_item):
if queue_item.id in running_queues:
return
running_queues[queue_item.id] = queue_item
logger.debug(
class SchedulingController(object):
""" The SchedulingController keeps track of the actions that are scheduled and calls a callback
when the actions has to be executed. The SchedulingController handles actions as String, it is
the callers responsibility to create a string representation of the action. """
def __init__(self, db_filename, callback, action_timeout=60):
new_database = not os.path.exists(db_filename)
self.__connection = sqlite3.connect(
db_filename,
detect_types=sqlite3.PARSE_DECLTYPES,
check_same_thread=False,
isolation_level=None)
self.__cursor = self.__connection.cursor()
if new_database:
self.__create_tables()
self.__callback = callback
self.__action_timeout = action_timeout
self.__stop = False
self.__input_queue = Queue()
self.__action_queue = PriorityQueue()
for action in self.__read_actions():
self.__action_queue.put(action)
self.__thread = Thread(target=self.__run,
name="SchedulingController thread")
self.__thread.daemon = True
def __create_tables(self):
""" Create the Scheduled actions table. """
self.__cursor.execute(
"CREATE TABLE actions (id INTEGER PRIMARY KEY, description TEXT, "
"action TEXT, timestamp INTEGER);")
def __read_actions(self):
""" Read the actions from the table. """
ret = []
for row in self.__cursor.execute(
"SELECT timestamp, id, description, action FROM actions;"):
ret.append((row[0], row[1], row[2], row[3]))
return ret
def __create_action(self, timestamp, description, action):
""" Create an action with a given timestamp in the database.
Returns the id of the action in the datbase.
"""
self.__cursor.execute(
"INSERT INTO actions (timestamp, description, action) VALUES (?,?,?)",
(timestamp, description, action))
return (timestamp, self.__cursor.lastrowid, description, action)
def __remove_action_from_db(self, id):
""" Remove an action from the database. """
self.__cursor.execute("DELETE FROM actions WHERE id = ?;", (id, ))
def __execute_action(self, id, description, action):
""" Execute a scheduled action, delete the action from the database and execute it. """
LOGGER.info("Executing scheduled action '%s'", description)
self.__remove_action_from_db(id)
def run_callback():
""" Run the callback. """
try:
self.__callback(action)
except:
LOGGER.exception(
"Exception while executing scheduled action '%s'",
description)
callback_thread = Thread(target=run_callback)
callback_thread.daemon = True
callback_thread.start()
callback_thread.join(self.__action_timeout)
if callback_thread.isAlive():
LOGGER.error(
"Scheduled action '%s' is still executing after %d sec",
description, self.__action_timeout)
def start(self):
""" Start the background thread. """
self.__thread.start()
def stop(self):
""" Stop the SchedulingController. """
self.__stop = True
self.__input_queue.put(None)
self.__thread.join()
def __run(self):
""" Code for the background thread. """
while not self.__stop:
# Wait on the input_queue, take actions from the action_queue when scheduled.
timeout = None
while self.__action_queue.qsize() > 0:
element = self.__action_queue.get()
(timestamp, id, description, action) = element
if timestamp <= time():
self.__execute_action(id, description, action)
else:
timeout = timestamp - time()
self.__action_queue.put(element)
break
try:
value = self.__input_queue.get(True, timeout)
if value == None: # Stop signal !
continue
elif value == REFRESH: # Refresh the action queue
self.__action_queue = PriorityQueue()
for action in self.__read_actions():
self.__action_queue.put(action)
else: # Got a new action
(timestamp, description, action) = value
self.__action_queue.put(
self.__create_action(timestamp, description, action))
except Empty:
pass # Timeout - do the loop
def schedule_action(self, timestamp, description, action):
""" Schedule a new action, that should be executed at a given timestamp. """
self.__input_queue.put((timestamp, description, action))
def list_scheduled_actions(self):
""" Get a list of all scheduled actions.
:returns: a list of dictionaries with keys (id, timestamp, description, action)
"""
actions = self.__read_actions()
ret = []
for action in actions:
ret.append({
'timestamp': action[0],
'id': action[1],
'description': action[2],
'action': action[3]
})
return ret
def remove_scheduled_action(self, id):
""" Remove a scheduled action, when the id of the scheduled action is provided. """
self.__remove_action_from_db(id)
self.__input_queue.put(REFRESH)
def close(self):
""" Commit the changes and close the database connection. """
self.__connection.commit()
self.__connection.close()
class srQueue(threading.Thread):
def __init__(self, name="QUEUE"):
super(srQueue, self).__init__(name=name)
self._queue = PriorityQueue()
self.currentItem = None
self.min_priority = 0
self.amActive = False
self.lock = threading.Lock()
self.stop = threading.Event()
self.daemon = True
def run(self):
"""
Process items in this queue
"""
while not self.stop.is_set():
with self.lock:
self.amActive = True
if self.currentItem is None or not self.currentItem.is_alive():
if self.currentItem:
self.currentItem = None
self.currentItem = self.get()
if self.currentItem.priority < self.min_priority:
self.put(self.currentItem)
self.currentItem = None
else:
self.currentItem.start()
self.amActive = False
@property
def queue(self):
return self._queue.queue
def get(self, *args, **kwargs):
_, item = self._queue.get(*args, **kwargs)
return item
def put(self, item, *args, **kwargs):
"""
Adds an item to this queue
:param item: Queue object to add
:return: item
"""
item.added = datetime.now()
item.name = "{}-{}".format(self.name, item.name)
self._queue.put((item.priority, item), *args, **kwargs)
return item
def pause(self):
"""Pauses this queue"""
sickrage.srCore.srLogger.info("Pausing queue")
self.min_priority = 999999999999
def unpause(self):
"""Unpauses this queue"""
sickrage.srCore.srLogger.info("Unpausing queue")
self.min_priority = 0
def shutdown(self):
self.stop.set()
try:
self.join(10)
except:
pass
import os
import sys
from Queue import PriorityQueue
pq = PriorityQueue()
visited_states = set()
class Puzzle(object):
"""
A* search with MANHATTAN HEURISTIC
"""
def __init__(self, init_state, goal_state):
# you may add more attributes if you think is useful
self.cost = 0
self.init_state = init_state
self.goal_state = goal_state
self.actions = list()
self.explored = [0]
self.explored_tot = 0
self.num_nodes = [0]
self.total_prev_h_cost = 0
def __cmp__(self, other):
return cmp(self.cost, other.cost)
def to_int_rep(self):
return tuple(map(tuple, self.init_state))
def is_solvable(self):
"""Checks if state is solvable."""
class MulticastChat:
multicast_group = ('224.3.29.71', 10000)
multicast_ip = '224.3.29.71'
hostIp = '0.0.0.0'
pid = os.getpid()
queueMsg = PriorityQueue()
numberAckList = {}
pid_list = [pid]
time = 0
server_address = ((hostIp, 10000))
conversationList = []
sendDelay = 0
def __init__(self, numberOfProcesses):
self.numberOfProcesses = numberOfProcesses
self.sock = self.initConnection()
self.synchronize(self.numberOfProcesses)
self.pid_list.sort()
self.pid = self.pid_list.index(self.pid)
thread.start_new_thread(self.recvListener, ())
print "Ready - " + self.presentationMsg()
print "Send your message:"
while True:
msg = raw_input()
if msg[:5] == "DELAY":
stopPid = int(msg[5:].split("-s")[0])
seconds = int(msg[5:].split("-s")[1])
self.sendDelayMsg(stopPid, seconds)
elif msg[:4] == "LIST":
self.printConversationLog()
elif msg[:3] == "PID":
print self.presentationMsg()
elif msg[:3] == "STP":
pidStop = int(msg[4:].split("-s")[0])
seconds = int(msg[4:].split("-s")[1])
self.sendStopMsg(pidStop, seconds)
else:
self.sendMsg(msg)
print "end"
def presentationMsg(self):
return "I'm the process no: " + str(self.pid)
def printConversationLog(self):
for i in self.conversationList:
print i
def sendDelayMsg(self, pidDelay, seconds):
msg = "DELAY " + str(pidDelay) + " -s" + str(seconds)
self.sock.sendto(msg, self.multicast_group)
def initConnection(self):
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
membership = socket.inet_aton(self.multicast_ip) + socket.inet_aton(
self.hostIp)
sock.setsockopt(socket.IPPROTO_IP, socket.IP_ADD_MEMBERSHIP,
membership)
sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEPORT, 1)
sock.bind(self.server_address)
return sock
def synchronize(self, numberOfProcesses):
print '\nSynchronizing..'
#print 'Recv %s'%self.pid
synchroMsg = 'SYN ' + str(self.pid)
while len(self.pid_list) < self.numberOfProcesses:
self.sock.sendto(synchroMsg, self.multicast_group)
data, address = self.sock.recvfrom(1024)
pidRecv = int(data[4:])
if not (pidRecv in self.pid_list):
self.pid_list.append(pidRecv)
#print 'Recv %s'%data
self.sock.sendto(synchroMsg, self.multicast_group)
def sendStopMsg(self, pidNo, seconds):
msg = "STP " + str(pidNo) + " -s " + str(seconds)
self.sock.sendto(msg, self.multicast_group)
def sendMsg(self, msg):
self.time += 1
msgTosend = "MSG ID:" + str(self.time) + "-" + str(
self.pid) + "\r\nContent:" + msg
#print "sended: "+msgTosend
if self.sendDelay > 0:
print "delaying on send for %d seconds" % self.sendDelay
time.sleep(self.sendDelay)
self.sendDelay = 0
self.sock.sendto(msgTosend, self.multicast_group)
def recvMsg(self, msg, msgId, timestamp, senderId):
msgGuard = str(senderId) + " - Time " + str(
timestamp) + ": " + msg.split(":")[1]
self.queueMsg.put((msgId, msgGuard))
self.time = 1 + max(self.time, timestamp)
self.ackMsg(msgId)
def ackMsg(self, msgId):
self.time += 1
ack = "ACK " + str(msgId) + ":" + str(self.time)
if self.sendDelay > 0:
print "delaying on ACK for %d seconds" % self.sendDelay
time.sleep(self.sendDelay)
print "sending"
self.sendDelay = 0
self.sock.sendto(ack, self.multicast_group)
def recvAck(self, msgId, timestamp):
self.time = 1 + max(self.time, timestamp)
if msgId in self.numberAckList:
self.numberAckList[msgId] += 1
else:
self.numberAckList[msgId] = 1
def deliverMsg(self, msgId):
if self.numberAckList[msgId] < self.numberOfProcesses:
return
time, msg = self.queueMsg.get(False)
if time != msgId:
self.queueMsg.put((time, msg))
return
self.conversationList.append(msg)
print msg
self.time += 1
del self.numberAckList[msgId]
while not (self.queueMsg.empty()):
time, msg = self.queueMsg.get(False)
if (self.numberAckList[time] < self.numberOfProcesses):
self.queueMsg.put((time, msg))
break
self.conversationList.append(msg)
print msg
self.time += 1
del self.numberAckList[time]
def recvListener(self):
while True:
data, address = self.sock.recvfrom(1024)
cmd = data[:3]
if data[:5] == "DELAY":
stopPid = int(data[5:].split("-s")[0])
seconds = int(data[5:].split("-s")[1])
if (stopPid == self.pid):
self.sendDelay = seconds
print "Delayed on send"
elif cmd == "ACK":
msgID = int(data.split(":")[0][4:])
timestamp = int(data.split(":")[1])
self.recvAck(msgID, timestamp)
self.deliverMsg(msgID)
elif cmd == "MSG":
msgId, contentMsg = data.split("\r\n")
timeRecv = int(msgId[7:].split("-")[0])
senderId = int(msgId[7:].split("-")[1])
msgId = int("".join(msgId[7:].split("-")))
content = str(msgId) + ": " + contentMsg[8:]
self.recvMsg(content, msgId, timeRecv, senderId)
elif cmd == "STP":
stopPid = int(data[4:].split("-s")[0])
seconds = int(data[4:].split("-s")[1])
if stopPid != self.pid:
continue
print "Stopped to listen for %d seconds" % seconds
time.sleep(seconds)
print "Woke up"
def __init__(self):
self._queue = PriorityQueue()
def get(self):
tup = PriorityQueue.get(self)
newtup = tup[0] * -1, tup[1], tup[2]
return newtup
def __init__(self, start, goal): self.path = [] self.visitedQueue = [] self.priorityQueue = PriorityQueue() self.start = start self.goal = goal
def __init__(self, maxlength=0, length_tol=1000):
self.pq = PriorityQueue()
self.decrease_length = multiprocessing.Lock()
self.maxlength = maxlength
self.length_tol = length_tol
def compute(self, start, goal):
frontier = PriorityQueue()
frontier.put((0, start))
frontier_nodes = [start]
already_explored = [start]
came_from = {start: None}
cost_so_far = {start: 0}
while not frontier.empty():
queue_entry = frontier.get()
current = queue_entry[1]
if self.draw and (current in frontier_nodes):
frontier_nodes.remove(current)
for next_node in current.neighbors:
# Get the current node from the graph
next_node = self._graph[next_node]
new_cost = cost_so_far[current] + 1
#self._costmap.data[current.y * self._costmap.info.height + current.x]
if (next_node not in cost_so_far) or (new_cost <
cost_so_far[next_node]):
cost_so_far[next_node] = new_cost
priority = new_cost + self.heuristic(next_node, goal)
frontier.put((priority, next_node))
came_from[next_node] = current
if self.draw and (next_node not in frontier_nodes):
frontier_nodes.append(next_node)
if current not in already_explored:
already_explored.append(current)
# Update visualization
if self.draw:
self.drawNodes(frontier_nodes, "frontier")
self.drawNodes(already_explored, "explored")
if current == goal:
break
# Work our way back through the came_from chain from the goal to the start
path = [goal]
previous_node = came_from[goal]
while previous_node is not None:
path.insert(0, previous_node)
previous_node = came_from[previous_node]
self.drawNodes(path, "path")
# Compute ros Path
waypoints = []
index = 0
current_dir = None
for node in path:
try:
next_node = path[index + 1]
# If we've changed directions, and add a waypoint if so
this_dir = math.atan2((next_node.y - node.y),
(next_node.x - node.x))
if current_dir == None or this_dir != current_dir:
current_dir = this_dir
# copied some stuff from
# https://www.programcreek.com/python/example/70252/geometry_msgs.msg.PoseStamped
pose = PoseStamped()
pose.header.seq = len(waypoints)
pose.header.frame_id = "map"
pose.header.stamp = rospy.Time.now()
(xc, yc) = self.mapCoordsToWorld(node.x, node.y)
pose.pose.position.x = xc
pose.pose.position.y = yc
pose.pose.position.z = 0
q = quaternion_from_euler(0.0, 0.0, current_dir)
pose.pose.orientation = Quaternion(*q)
waypoints.append(pose)
index += 1
except IndexError:
# We've reached the end of the loop, add last waypoint
pose = PoseStamped()
pose.header.seq = len(waypoints)
pose.header.frame_id = "map"
pose.header.stamp = rospy.Time.now()
(xc, yc) = self.mapCoordsToWorld(node.x, node.y)
pose.pose.position.x = xc
pose.pose.position.y = yc
pose.pose.position.z = 0
q = quaternion_from_euler(0.0, 0.0, current_dir)
pose.pose.orientation = Quaternion(*q)
waypoints.append(pose)
path_msg = Path()
path_msg.header.frame_id = "map"
path_msg.header.stamp = rospy.Time.now()
path_msg.poses = waypoints
return path_msg
def __init__(self, limit = 0):
PriorityQueue.__init__(self, limit)
self.max_prio = 0
self.none_send = False
