def testSix():
runs = 10
for p in np.arange(0, 0.41, 0.05):
count = {}
count[h.returnZero.__name__] = 0
count[h.Manhattan.__name__] = 0
count[h.Euc.__name__] = 0
numSolved = 0
while (numSolved < 3 * runs):
dimm = 100
start = (0, 0)
goal = (dimm - 1, dimm - 1)
grid = gd.generateFireGrid(dimm, p)
solved, _ = BDBFS(grid, start, goal)
for heuristic in [h.returnZero, h.Manhattan, h.Euc]:
if (solved):
solved, solvedPath, testingData = aStar(
grid, start, goal, heuristic, True)
if (heuristic == h.returnZero):
solved, solvedPath, testingData = BFS(
grid, start, goal)
numSolved += 1
closedLen, *_ = testingData
count[heuristic.__name__] += closedLen
print(
math.ceil(p * 100) / 100, " : ",
math.floor(count[h.returnZero.__name__] / runs),
math.floor(count[h.Manhattan.__name__] / runs),
math.floor(count[h.Euc.__name__] / runs))
def testTwo():
heuristic = h.Manhattan
p = 0.3
dimm = 50
start = (0, 0)
goal = (dimm - 1, dimm - 1)
grid = gd.generateFireGrid(dimm, p)
solved1, solvedPathaStar1, testingDataaStar1 = aStar(grid,
start,
goal,
heuristic,
tieSort=False)
solved2, solvedPathaStar2, testingDataaStar2 = aStar(grid,
start,
goal,
heuristic,
tieSort=True)
assert (solved1 == solved2)
if (solved1):
(_, t1, _) = testingDataaStar1
(_, t2, _) = testingDataaStar2
print(len(t1), " : ", len(t2))
else:
print(len(testingDataaStar1), ":", len(testingDataaStar2))
print("unsolved")
print(str(grid))
def testFour():
start = (0, 0)
p = 0.3
dimm = 5
goal = (dimm - 1, dimm - 1)
heuristic = h.Manhattan
grid = gd.generateFireGrid(dimm, 0)
previousFireGrids = dict()
solved, solvedPath, testingData = aStar(grid, start, goal, heuristic, True,
True, 0.5, 0.3)
print(generateFireGrids(previousFireGrids, grid, len(solvedPath) - 1, 0.3))
print(solvedPath)
print(fireEval(grid, solvedPath, 0.3))
def testFive():
for q in np.arange(0, 1.04, 0.05):
runs = 100
success = 0
tries = 0
while (tries < runs):
#thresh = 0.5
start = (0, 0)
dimm = 30
bottomLeft = (dimm - 1, 0)
upperRight = (0, dimm - 1)
p = 0.2
goal = (dimm - 1, dimm - 1)
heuristic = h.Manhattan
grid = gd.generateFireGrid(dimm, p)
#print(grid)
previousFireGrids = dict()
#solvedStrong, solvedPath, testingData = aStar(grid, start, goal, heuristic, False, True, thresh, q)
solved, _ = BDBFS(grid, start, goal)
fireHasPath, _ = BDBFS(grid, bottomLeft, upperRight)
if (solved and fireHasPath):
listings = [i for i in np.arange(0, 1.05, 0.05)]
for i in listings:
_, solvedPath, testData = aStar(grid, start, goal,
h.Manhattan, False, True,
i, q, previousFireGrids)
if (solvedPath):
_, _, _, previousFireGrids = testData
#print(listings)
tries += 1
fireSolved, _ = fireEval(grid, solvedPath, q)
if (fireSolved):
success += 1
break
#print(grid)
#print(solvedPath)
print("for", q, ":", success / tries, " : ", success, "/", tries)
def testThree():
p = 0.3
dimm = 10
grid = gd.generateFireGrid(dimm, 0)
previousFireGrids = dict()
print(generateFireGrids(previousFireGrids, grid, 1, 0.3))