def compute(self, fromState, toState):
from problems import MapProblem
mapSubProblem = MapProblem(self.roads, fromState.junctionIdx,
toState.junctionIdx)
_, l, _, _ = self.astar.run(mapSubProblem)
return l
def solve(self, problem):
pickingOrder = self._findPickingOrder(problem)
pickingPath = [problem.initialState.junctionIdx]
# Build the picking path itself using A* between every two locations in the picking order
for source, target in zip(pickingOrder[:-1], pickingOrder[1:]):
mapSubProblem = MapProblem(self.roads, source, target)
statesSubpath = self.astar.run(mapSubProblem)[0]
delta = [s.junctionIdx for s in statesSubpath[1:]]
pickingPath = pickingPath + delta
from path import Path
return Path(self.roads, pickingPath)
# Plot the orders
plotOrders(roads, prob.orders)
plt.title("Showing orders. Click to show path")
plt.title("Showing orders. Click to show path")
plt.show(block=False)
plt.waitforbuttonpress()
colors = ['red', 'blue', 'green', 'orange', 'grey']
plt.title("Showing paths")
totalDistance = 0
# Plot each order at a time
for i,order in enumerate(prob.orders):
# Create a sub-problem to solve with A* (getting the optimal path for each order separately)
subProblem = MapProblem(roads, order[0], order[1])
subPath, distance, _, _ = mapAstar.run(subProblem)
print("Shortest distance for order from #{} to #{}: {:.2f}km".format(order[0], order[1], distance / 1000))
totalDistance += distance
# Plot the path
plotPath(Path(roads, [s.junctionIdx for s in subPath]), color=colors[i])
plt.show(block=False)
plt.waitforbuttonpress()
print("Total distance: {:.2f}km".format(totalDistance / 1000 ))