How to use makeState method in avocado
Best Python code snippet using avocado_python
nkhetan-hw5.py
Source:nkhetan-hw5.py 
...192 successors.append(succ)193 return successors194 195# Create state from initial and goal state196def makeState(nw, n, ne, w, c, e, sw, s, se):197 statelist = [nw, n, ne, w, c, e, sw, s, se]198 for i in range(len(statelist)):199 # Replace blank with 0200 if statelist[i] == "blank":201 statelist[i] = 0202 return statelist203 204205def testInformedSearch(initialState, goalState, limit):206 '''print "\nHueristic: No of mispalced Tiles"207 t1 = time.time()208 informedSearch ([initialState], limit, 0, "one")209 print "Time taken for Informed Search(Misplaced Tiles): ", (time.time()-t1) ," Seconds"210 print "\nHueristic: Manhatten Distance"'''211 t2 = time.time()212 informedSearch ([initialState], limit, 0, "two")213 print "Time taken for Informed Search(Manhatten Distance): ", (time.time()-t2) ," Seconds"214 return215216217'''---------------------------------------------------------------------------------------------------------------------------'''218'''-----------------------------------------------------CODE FOR CBR----------------------------------------------------------'''219'''---------------------------------------------------------------------------------------------------------------------------'''220'''New code added here for Case Based Reasoning: @author: Nihar Khetan'''221222223def getPositionInGoalState(valueOfElement, gstate):224 '''It returns the position of a particular number which is in initial state, in Goal state225 number -> (number,number)'''226 for i in range(3):227 for j in range(3):228 if valueOfElement == gstate[i][j]:229 return (i,j)230231def calcEucledianDistance(initialState, gstate):232 '''It calculates Euclidean Distance for 8 Puzzle233 for an initialState Euclidean distance is the sum of moves for each number in initial state, to move it to the respective goal state234 so Heuristic Function 2 is based on Euclidean Distance235 initialState -> pathCost'''236 pathCost = 0237 for i in range(3):238 for j in range(3):239 if int(initialState[i][j]) != 0: 240 if int(initialState[i][j]) != int((gstate)[i][j]):241 x,y = getPositionInGoalState(initialState[i][j], gstate)242 pathCost = pathCost + (abs(x-i)+abs(y-j))243 return pathCost244245def convertToMatrice(state):246 '''converts the given state to a matrice like it looks for a 8- Puzzle'''247 count = 0248 newArr = [[" "," "," "],[" "," "," "],[" "," "," "]] 249 for i in range(3):250 for j in range(3): 251 newArr[i][j] = state[count]252 count+=1 253 return newArr254255def computeSimilarity(I0, I1, G1, G0):256 '''this function computes similarity between given initial and goal states to initial and goal states in case based database257 It uses sum of Manhattan distance : dist(I1-I0) + dist(G1, G0)258 where I0: given initial state I1: initial state from CBR database 259 G0: given goal state G1: goal state from CBR database260 '''261 scoreI0I1 = calcEucledianDistance(convertToMatrice(I0), convertToMatrice(I1)) 262 scoreG0G1 = calcEucledianDistance(convertToMatrice(G0), convertToMatrice(G1))263 264 return (scoreI0I1 + scoreG0G1)265266def getKeyForMostSimilar(I1, G1):267 ''' Gets the most similar case from case based reasoning and return the key for the same ''' 268 cbrDb = readFromDict()269 scoreDict = {}270 print ("++-------------------------------------+------------------- CBR Database -------------------+--------------------------------------++")271 print ("\tKey\t\t\t\tInitial State\t\t\t\tGoal State\t\t\t\tSimilarity Score ")272 for key in cbrDb.keys():273 scoreDict[key] = computeSimilarity(I1, cbrDb[key][0], cbrDb[key][len(cbrDb[key])-1], G1) 274 print ("\t%s\t\t\t\t%s\t\t%s\t\t%s " %(str(key), str(cbrDb[key][0]), str(cbrDb[key][len(cbrDb[key])-1]), str(computeSimilarity(I1, cbrDb[key][0], cbrDb[key][len(cbrDb[key])-1], G1))))275 return ((sorted(scoreDict.items(), key=lambda x:x[1]))[0][0], (sorted(scoreDict.items(), key=lambda x:x[1]))[0][1]) 276 277def getKey(initial, goal):278 ''' Gets the key form case based reasoning and returns the same for a given initial and goal states'''279 cbrDb = readFromDict()280 for key in cbrDb.keys():281 if ((cbrDb[key][0] == initial) and (cbrDb[key][len(cbrDb[key])-1] == goal)):282 return key283 return -1284 285def checkIfPresent(initial, goal):286 ''' Checks if initial and goal states are exactly present in the case based reasoning --> returns boolean'''287 cbrDB = readFromDict() 288 for eachProblem in cbrDB.values() : 289 if ((eachProblem[0] == initial) and (eachProblem[len(eachProblem)-1] == goal)):290 return True 291 return False 292293def checkIfPresentInAnyState(initial, goal):294 '''Function checks if given initial and goal exists in any of sub paths of solutions in CBR database295 list, list -> boolean'''296 cbrDB = readFromDict() 297 print ("Exact Match not found thus checking all states of all paths stored in CBR Database")298 299 for eachProblem in cbrDB.values() : 300 if ((initial in eachProblem) and (goal in eachProblem)):301 if (eachProblem.index(initial) < (eachProblem.index(goal))): 302 return True 303 else:304 return False 305 return False 306307def computePathFromAnyOtherState(initial, goal):308 '''Try to look at sub-paths of solutions in CBR database and if it is found returns the same 309 initial state, goal state --> list '''310 cbrDB = readFromDict() 311 counter = 0312 for eachProblem in cbrDB.values() : 313 if ((initial in eachProblem) and (goal in eachProblem)):314 if (eachProblem.index(initial) < (eachProblem.index(goal))):315 print ("MATCH FOUND in a path for Case Based Reasoning Database")316 print ("Key for case matched : " + str(counter)) 317 print ("Similarity Score = 0\n") 318 return eachProblem[eachProblem.index(initial):eachProblem.index(goal)+1] 319 else:320 return []321 counter += 1322 return [] 323324def readFromDict():325 '''Reader to read the cases stored in case based reasoning and returns the dictionery326 ---> returns a dictionery'''327 with open('cbr_database.pickle', 'rb') as handle:328 savedCases = pickle.load(handle)329 return savedCases330331def writeToDict(caseToWrite):332 '''Opens the case bases reasoning and write a new case to it, while persisting the older ones333 ---> does not return anything'''334 current = readFromDict()335 current.update(caseToWrite)336 with open('cbr_database.pickle', 'wb') as handle:337 pickle.dump(current, handle)338 return339340 341342def testCaseBasedSearch(listOfProblems): 343 '''Function which goes through each problem in list of problems and solves it using Case Based Search''' 344 345 for i in range(len(listOfProblems)): 346 initial1 = listOfProblems[i][0]347 goal1 = listOfProblems[i][1]348 global goalState349 print ("++---------------------------------------------------------------------------------------------------------------------------------------------++")350 print ("++---------------------------------------------------------------------------------------------------------------------------------------------++\n")351 352 print("Solving Problem : " + str(i+1))353 print("Given Initial State : " + str(initial1))354 print("Given Goal State : " + str(goal1) + "\n")355 '''If CBR database is empty solve the first problem and store it'''356 cbrCheck = readFromDict();357 if (cbrCheck == {}):358 print("+-+- Empty CBR Database Solving from scratch -+-+")359 goalState = goal1360 pathSearched = informedSearch ([initial1], 20000, 0, "two")361 outputProcedure(pathSearched)362 print("++-----Appending new Path to CBR Database------++\n")363 cbrDB = readFromDict()364 dictToAppend = {0:pathSearched}365 writeToDict(dictToAppend) 366 367 else:368 '''Case to check if initial state and goal state matches exactly :: BEST CASE''' 369 if (checkIfPresent(initial1,goal1)): 370 key = getKey(initial1,goal1)371 372 goalState = goal1373 print ("Exact Match Found in CBR at Key : " + str(key))374 print ("\tSimilarity Score = 0\n") 375 outputProcedure(readFromDict()[key])376 elif (checkIfPresentInAnyState(initial1, goal1) == True): 377 outputProcedure(computePathFromAnyOtherState(initial1, goal1))378 else:379 print ("\nInitial State and Goal State not found in sub paths hence computing SIMILARITY SCORES ::")380 (key, score) = getKeyForMostSimilar(initial1,goal1)381 382 if (score < 9):383 #use case based reasoning384 print ("\nScore less than THRESHOLD thus applying CBR")385 print ("\tMost Similar Key : " + str(key) + "\tSimilarity Score : " + str(score))386 cbrDB = readFromDict()387 #goal state is I0388 389 goalState = cbrDB[key][0]390 391 pathSearchedI0toI1 = informedSearch ([initial1], 20000, 0, "two")392 print("\tPath From I0 to I1 : " + str(pathSearchedI0toI1))393 pathSearchedI1toG1 = cbrDB[key]394 print("\tPath From I1 to G1 (CBR) : " + str(pathSearchedI1toG1)) 395 goalState = goal1396 pathSearchedG1toG0 = informedSearch ([cbrDB[key][len(cbrDB[key])-1]], 20000, 0, "two")397 print("\tPath From G1 to G0 : " + str(pathSearchedG1toG0)) 398 pathSearched = pathSearchedI0toI1 + pathSearchedI1toG1[1:-1] + pathSearchedG1toG0399 print("\nCombined Path I0 --> I1 --> G1 --> G0") 400 outputProcedure(pathSearched)401 print("++-----Appending new Path to CBR Database------++\n")402 dictToAppend = {(cbrDB.keys()[len(cbrDB.keys())-1]+1):pathSearched}403 writeToDict(dictToAppend)404 else:405 #find solution from scratch and add it to Case Based Reasoning Database406 print ("\nComputed Score : " + str(score) + ", Which is Greater than THRESHOLD : 8") 407 print("Solving from scratch using A* Search\n")408 goalState = goal1409 pathSearched = informedSearch ([initial1], 20000, 0, "two")410 outputProcedure(pathSearched)411 print("++-----Appending new Path to CBR Database------++\n")412 cbrDB = readFromDict() 413 if (cbrDB.keys() == []):414 dictToAppend = {0:pathSearched}415 writeToDict(dictToAppend) 416 else:417 dictToAppend = {(cbrDB.keys()[len(cbrDB.keys())-1]+1):pathSearched}418 writeToDict(dictToAppend) 419 420 421422def generateTestProblems(listOfProblems):423 '''This function generated a set of Random Problems.424 I have followed approach 1 where I give a predefined set of problems as input425 so this acts as a dummy function'''426427 testCaseBasedSearch(listOfProblems)428 429# Main()430if __name__ == "__main__":431 global goalState432 goalState = []433 print "<<<< :::::: CASE BASED REASONING TO SOLVE 8 PUZZLE :::::: >>>>\n"434 try:435 with open('cbr_database.pickle', 'rb') as handle:436 savedCases = pickle.load(handle)437 print ("printing the CBR Database")438 for eachKey in savedCases.keys():439 print (str(eachKey) + " : " + str(savedCases[eachKey])) 440 print("")441 except IOError: 442 emptyDict = {}443 with open('cbr_database.pickle', 'wb') as handle:444 pickle.dump(emptyDict, handle)445 446 447 '''Given sample list of problems'''448 listOfProblems = [449 [makeState("blank", 5, 3, 2, 1, 6, 4, 7, 8), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],450 [makeState("blank", 3, 6, 5, 7, 8, 2, 1, 4), makeState(1, 2, 3, 4, 5, 6, 7, "blank", 8)],451 [makeState(3, 6, "blank", 5, 7, 8, 2, 1, 4), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],452 [makeState("blank", 2, 5, 3, 1, 6, 4, 7, 8), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],453 [makeState(3, 2, 5, "blank", 1, 6, 4, 7, 8), makeState(1, "blank", 3, 4, 2, 5, 7, 8, 6)],454 [makeState("blank", 2, 1, 5, 3, 6, 4, 7, 8), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],455 [makeState(2, 5, "blank", 4, 6, 3, 7, 1, 8), makeState(1, 2, 3, 4, 5, 6, 7, "blank", 8)],456 [makeState(2, 6, 5, 4, "blank", 3, 7, 1, 8), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],457 [makeState(1, "blank", 3, 5, 2, 6, 4, 7, 8), makeState(1, 2, 3, 4, 8, 5, 7, "blank", 6)],458 [makeState("blank", 2, 3, 1, 5, 6, 4, 7, 8), makeState(2, 6, 5, 4, "blank", 3, 7, 1, 8)],459 [makeState(2, 3, 8, 1, 6, 5, 4, 7, "blank"), makeState("blank", 2, 3, 1, 5, 6, 4, 7, 8)],460 [makeState(2, 5, 3, 4, "blank", 8, 6, 1, 7), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],461 [makeState(3, 8, 5, 1, 6, 7, 4, 2, "blank"), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],462 [makeState(3, 8, 5, 1, "blank", 6, 4, 2, 7), makeState(1, 2, 3, 4, "blank", 5, 7, 8, 6)],463 [makeState(3, 8, 5, 1, 6, "blank", 4, 2, 7), makeState(1, 2, 3, 4, 8, 5, "blank", 7, 6)],464 [makeState(1, 3, 5, "blank", 8, 6, 4, 2, 7), makeState(1, 2, 3, 4, 5, "blank", 7, 8, 6)],465 [makeState(3, 8, 5, 1, 6, "blank", 4, 2, 7), makeState(1, 2, 3, 4, 8, 5, 7, "blank", 6)],466 [makeState("blank", 3, 5, 1, 8, 6, 4, 2, 7), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],467 [makeState("blank", 3, 5, 1, 8, 6, 4, 2, 7), makeState(1, 2, 3, 4, 5, 6, 7, 8, "blank")],468 [makeState(2, 5, 3, 4, "blank", 8, 6, 1, 7), makeState(1, 2, 3, 4, 5, 6, "blank", 7, 8)]469 ]470 t1 = time.time()471 generateTestProblems(listOfProblems)472 t2 = time.time()473 print "\n\nTime taken for solving by CBR: ", (t2-t1), " Seconds"474
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dataCollector.py
Source:dataCollector.py
...65 #write result to file66 logFile.writerow([index+1,searchCost,level,timeDiff,limit])67def main():68 69 goalState = makeState(1,2,3,4,5,6,7,8,'blank') 70 # First group of test cases - should have solutions with depth <= 571 initialState1 = makeState(2, "blank", 3, 1, 5, 6, 4, 7, 8)72 initialState2 = makeState(1, 2, 3, "blank", 4, 6, 7, 5, 8)73 initialState3 = makeState(1, 2, 3, 4, 5, 6, 7, "blank", 8)74 initialState4 = makeState(1, "blank", 3, 5, 2, 6, 4, 7, 8)75 initialState5 = makeState(1, 2, 3, 4, 8, 5, 7, "blank", 6)76 # Second group of test cases - should have solutions with depth <= 1077 initialState6 = makeState(2, 8, 3, 1, "blank", 5, 4, 7, 6)78 initialState7 = makeState(1, 2, 3, 4, 5, 6, "blank", 7, 8)79 initialState8 = makeState("blank", 2, 3, 1, 5, 6, 4, 7, 8)80 initialState9 = makeState(1, 3, "blank", 4, 2, 6, 7, 5, 8)81 initialState10 = makeState(1, 3, "blank", 4, 2, 5, 7, 8, 6)82 # Third group of test cases - should have solutions with depth <= 2083 initialState11 = makeState("blank", 5, 3, 2, 1, 6, 4, 7, 8)84 initialState12 = makeState(5, 1, 3, 2, "blank", 6, 4, 7, 8)85 initialState13 = makeState(2, 3, 8, 1, 6, 5, 4, 7, "blank")86 initialState14 = makeState(1, 2, 3, 5, "blank", 6, 4, 7, 8)87 initialState15 = makeState("blank", 3, 6, 2, 1, 5, 4, 7, 8)88 # Fourth group of test cases - should have solutions with depth <= 5089 initialState16 = makeState(2, 6, 5, 4, "blank", 3, 7, 1, 8)90 initialState17 = makeState(3, 6, "blank", 5, 7, 8, 2, 1, 4)91 initialState18 = makeState(1, 5, "blank", 2, 3, 8, 4, 6, 7)92 initialState19 = makeState(2, 5, 3, 4, "blank", 8, 6, 1, 7)93 initialState20 = makeState(3, 8, 5, 1, 6, 7, 4, 2, "blank")94 testcases = [initialState1,initialState2,initialState3,initialState4,initialState5,initialState6,initialState7,initialState8,initialState9,initialState10,initialState11,initialState12,initialState13,initialState14,initialState15,initialState16,initialState17,initialState18,initialState19,initialState20]95 #executeTestCases(testcases[0:20],goalState,SearchMethod.CELL_DIFF)96 #executeTestCases(testcases[0:20],goalState,SearchMethod.MANHATTAN)97 #executeTestCases(testcases[0:20],goalState,SearchMethod.BFS)98if __name__ == "__main__":...
tester.py
Source:tester.py
...6import time7"""8from armajrik_uninformed import makeState9from armajrik_uninformed import testUninformedSearch10goalState = makeState(1,2,3,4,5,6,7,8,'blank') 11# First group of test cases - should have solutions with depth <= 512initialState1 = makeState(2, "blank", 3, 1, 5, 6, 4, 7, 8)13initialState2 = makeState(1, 2, 3, "blank", 4, 6, 7, 5, 8)14initialState3 = makeState(1, 2, 3, 4, 5, 6, 7, "blank", 8)15initialState4 = makeState(1, "blank", 3, 5, 2, 6, 4, 7, 8)16initialState5 = makeState(1, 2, 3, 4, 8, 5, 7, "blank", 6)17# Second group of test cases - should have solutions with depth <= 1018initialState6 = makeState(2, 8, 3, 1, "blank", 5, 4, 7, 6)19initialState7 = makeState(1, 2, 3, 4, 5, 6, "blank", 7, 8)20initialState8 = makeState("blank", 2, 3, 1, 5, 6, 4, 7, 8)21initialState9 = makeState(1, 3, "blank", 4, 2, 6, 7, 5, 8)22initialState10 = makeState(1, 3, "blank", 4, 2, 5, 7, 8, 6)23# Third group of test cases - should have solutions with depth <= 2024initialState11 = makeState("blank", 5, 3, 2, 1, 6, 4, 7, 8)25initialState12 = makeState(5, 1, 3, 2, "blank", 6, 4, 7, 8)26initialState13 = makeState(2, 3, 8, 1, 6, 5, 4, 7, "blank")27initialState14 = makeState(1, 2, 3, 5, "blank", 6, 4, 7, 8)28initialState15 = makeState("blank", 3, 6, 2, 1, 5, 4, 7, 8)29# Fourth group of test cases - should have solutions with depth <= 5030initialState16 = makeState(2, 6, 5, 4, "blank", 3, 7, 1, 8)31initialState17 = makeState(3, 6, "blank", 5, 7, 8, 2, 1, 4)32initialState18 = makeState(1, 5, "blank", 2, 3, 8, 4, 6, 7)33initialState19 = makeState(2, 5, 3, 4, "blank", 8, 6, 1, 7)34initialState20 = makeState(3, 8, 5, 1, 6, 7, 4, 2, "blank")35initialState = initialState1336#testInformedSearchTwo(initialState,goalState,2000)37#raw_input()38#testInformedSearchOne(initialState,goalState,5000)39#raw_input()40testUninformedSearch(initialState,goalState,3500)41#testInformedSearch(initialState,goalState,2000)...
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