def ndFindNANA(inString):
# the list of strings to look for
strings = ['CACA', 'GAGA', 'TATA', 'AAAA']
# create an empty list that will store our threads
threads = [ ]
# create an object that can store a nondeterministic solution
# computed by other threads
nonDetSolution = utils.NonDetSolution()
# create the threads that will perform the nondeterministic
# computation
for string in strings:
# create a thread that will execute
# findString(string, inString, nonDetSolution) when started
t = Thread(target=findString, args = (string,inString,nonDetSolution))
# append the newly-created thread to our list of threads
threads.append(t)
# Perform the nondeterministic computation. By definition, this
# means that each thread is started, and we get a return value if
# either: (a) any thread reports a positive solution, or (b) all
# threads report negative solutions.
solution = utils.waitForOnePosOrAllNeg(threads, nonDetSolution)
return solution
def ndContainsNANA(inString):
# the list of strings to look for
strings = ['CACA', 'GAGA', 'TATA', 'AAAA']
# create an empty list that will store our threads
threads = [ ]
# create an object that can store a nondeterministic solution computed by
# other threads
ndSoln = utils.NonDetSolution()
# create the threads that will perform the nondeterministic computation
for s in strings:
# create a thread that will execute findString(s, inString, ndSoln)
# when started; findString is a helper function defined below
t = Thread(target=findString,
args = (s, inString, ndSoln))
# append the newly created thread to our list of threads
threads.append(t)
# Perform the nondeterministic computation. By definition, this means
# that each thread is started, and we get a return value if either (a)
# any thread reports a positive solution, or (b) all threads report
# negative solutions.
solution = utils.waitForOnePosOrAllNeg(threads, ndSoln)
return solution
def ndFindNANAHelper(text, parentNdSoln, depth=0):
if depth == maxDepth:
# We are at a leaf of the computation tree.
solution = findNANA(text)
parentNdSoln.setSolution(solution)
else:
# We are at an internal node of the computation tree. Split the
# given text into two halves, and launch new threads to search
# each half separately.
threads = []
childNdSoln = utils.NonDetSolution()
halfway = int(len(text) / 2)
# We will split the input text in half, but we could get
# unlucky and find that one of the desired substrings
# straddles the point of the split. Therefore, extend both
# halves by the maximum length of a desired substring.
upperLimit = min(halfway + maxDesiredStringLen, len(text))
lowerLimit = max(halfway - maxDesiredStringLen, 0)
text1 = text[:upperLimit]
text2 = text[lowerLimit:]
t1 = Thread(target=ndFindNANAHelper,
args=(text1, childNdSoln, depth + 1))
t2 = Thread(target=ndFindNANAHelper,
args=(text2, childNdSoln, depth + 1))
threads.append(t1)
threads.append(t2)
solution = utils.waitForOnePosOrAllNeg(threads, childNdSoln)
parentNdSoln.setSolution(solution)
def hasMultipleOfK (nums):
integers = []
integers = map(int, input().split())
k = int(input(":")).append(integers)
mkSoln = utils.NonDetSolution()
for k in integers:
t = Thread(target=findInt, args = (k, nums, mkSoln))
integers.append(t)
solution = utils.waitForOnePosOrAllNeg(integers, mkSoln)
return solution
def GthenOneT(inString):
threads = [ ]
ndSoln = utils.NonDetSolution()
for i in range(0, len(inString)):
if inString[i] == 'G':
leftString = inString[:i]
leftThread = Thread(target=findT, args = (leftString, ndSoln))
threads.append(leftThread)
rightString = inString[i+1:]
rightThread = Thread(target=findT, args = (rightString, ndSoln))
threads.append(rightThread)
return utils.waitForOnePosOrAllNeg(threads, ndSoln)
def findMultipleOfK():
integers = []
integers = map(int, input().split())
output = []
k = int(input(":")).append(integers)
nonDetSolution = utils.NonDetSolution()
for k in integers:
if integers % k == 0:
output.append(integers[k])
t = Thread(target=findInt, args = (integers, nonDetSolution))
integers.append(t)
solution = utils.waitForOnePosOrAllNeg(integers, nonDetSolution)
return solution
def ndFactor(inNum, K):
num = int(inNum)
numRt = int(math.sqrt(num))
threads = []
ndSoln = utils.NonDetSolution()
numList = numpy.array_split(range(2, numRt + 1), K)
for L in numList:
t = Thread(target=findFactor, args=(L, num, ndSoln))
threads.append(t)
solution = utils.waitForOnePosOrAllNeg(threads, ndSoln)
return solution
def main(args):
M = int(args.inString)
M_prime = int(np.sqrt(M))
search_range = np.array([i + 2 for i in range(M_prime - 2)])
splitted = np.array_split(search_range, args.K)
ndSoln = utils.NonDetSolution()
threads = []
for split_range in splitted:
t = Thread(target=factor_opt, args=(M, split_range, ndSoln))
threads.append(t)
res = utils.waitForOnePosOrAllNeg(threads, ndSoln)
return res
def ndFactorHelper(M, low, high, nonDetSolution):
if high <= low:
# There is nothing to search.
return
elif high - low == 1:
# The search interval includes only one possibility (low), so test it.
if M % low == 0:
# low is a factor of M, so store this solution
nonDetSolution.setSolution(str(low))
return
else:
# Split the search interval in two, and launch new threads to
# search those intervals.
threads = []
childNdSoln = utils.NonDetSolution()
mid = int((high + low) / 2)
t1 = Thread(target=ndFactorHelper, args=(M, low, mid, childNdSoln))
t2 = Thread(target=ndFactorHelper, args=(M, mid, high, childNdSoln))
threads.append(t1)
threads.append(t2)
solution = utils.waitForOnePosOrAllNeg(threads, childNdSoln)
nonDetSolution.setSolution(solution)