def hopkroft(graph, structure):
transformed_graph = {}
supervisors = graph.getEdges()
students = graph.getStuEdges()
correspondence = {}
sup_name = 0
list_supervisors = [supervisor for supervisor in supervisors]
list_students = [student for student in students]
random.shuffle(list_supervisors)
random.shuffle(list_students)
a_to_b = {}
for i in range(len(list_students)):
a_to_b[list_students[i]] = 'stu' + str(i)
for supervisor in list_supervisors:
cardinality = structure[supervisor]
for i in range(cardinality):
for stu in supervisors[supervisor]:
transformed_graph.setdefault(sup_name, set()).add(a_to_b[stu])
correspondence[sup_name] = supervisor
sup_name = sup_name + 1
m = HopcroftKarp(transformed_graph).maximum_matching()
result = BipartiteGraph()
for student in students:
sup_code = m[a_to_b[student]]
result.addEdge(correspondence[sup_code], student)
return result
def test_case18(self):
"""Testing the isValid function - passing a null graph"""
graph = BipartiteGraph()
solution = Solution(graph)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case6(self):
"""Testing the removeEdge function in a graph with existing nodes and edges"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
graph.removeEdge("supervisor1", "student1")
val1 = graph.getStudentDegree("student1")
val2 = graph.getSupervisorDegree("supervisor1")
self.assertEqual((val1, val2), (0, 0))
def uniform(solution1, solution2, supervisors, students, k=None):
"""
An implementation of uniform crossover
"""
graph1 = solution1.getGraph()
graph2 = solution2.getGraph()
stuEdges1 = graph1.getStuEdges()
stuEdges2 = graph2.getStuEdges()
g = BipartiteGraph()
for stu in students:
if random.random() < 0.5:
sup = stuEdges1[stu][0]
else:
sup = stuEdges2[stu][0]
g.addEdge(sup, stu)
fixSolution(g, supervisors, students)
return Solution(g)
def test_case8(self):
"""Testing the create random graph function"""
graph = BipartiteGraph.createRandomGraph(self.students,
self.supervisors)
solution = Solution(graph)
result = solution.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case3(self):
"""Testing addEdge function when adding an edge that already exists"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
graph.addEdge("supervisor1", "student1")
val1 = graph.getSupervisorDegree("supervisor1")
val2 = graph.getStudentDegree("student1")
self.assertEqual((val1, val2), (1, 1))
def test_case20(self):
"""Testing the isValid function - when number of students less than actual"""
graph = BipartiteGraph()
graph.addEdge("supervisor1","student1")
graph.addEdge("supervisor3","student3")
graph.addEdge("supervisor2","student2")
solution = Solution(graph)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case1(self):
"""Testing addEdge function in an empty graph"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
val1 = graph.getStudents("supervisor1")
val2 = graph.getSupervisors("student1")
expected1 = ["student1"]
expected2 = ["supervisor1"]
self.assertEqual((val1, val2), (expected1, expected2))
def setUp(self):
#Creating a list of students and supervisors
topicNames, topicPaths, topicIDs, levels = parseFile(
"pystsup/test/acm.txt")
self.supervisors = {}
self.students = {}
stuID = "student"
supID = "supervisor"
stuList1 = [
"MapReduce-based systems", "Multidimensional range search",
"Open source software", "Data mining", "Online shopping"
]
stuList2 = [
"Heuristic function construction", "Multi-agent systems",
"Open source software", "Data mining", "Speech recognition"
]
stuList3 = [
"Multi-agent systems", "Speech recognition",
"Heuristic function construction", "Data mining",
"Object identification"
]
stuList4 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList1 = [
"Multi-agent systems", "Intelligent agents",
"MapReduce-based systems", "Object identification",
"Heuristic function construction"
]
supList2 = [
"Open source software", "Data mining", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList3 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList = [supList1, supList2, supList3]
supQuota = [2, 2, 1]
stuList = [stuList1, stuList2, stuList3, stuList4]
for i in range(3):
toAdd = []
sup_list = {}
rank = 0
for kw in supList[i]:
rank += 1
sup_list[rank] = [
kw, getPath(kw, topicNames, topicPaths, topicIDs)
]
sup = supID + str(i + 1)
quota = supQuota[i]
supervisorObject = Supervisor(sup, sup_list, quota)
self.supervisors[sup] = supervisorObject
for i in range(4):
toAdd = []
stu_list = {}
rank = 0
for kw in stuList[i]:
rank += 1
stu_list[rank] = [
kw, getPath(kw, topicNames, topicPaths, topicIDs)
]
stu = stuID + str(i + 1)
studentObject = Student(stu, stu_list)
self.students[stu] = studentObject
# Generating rank weights for c = 0.5
self.rankWeights = Solution.calcRankWeights()
#Creating fitness cache
self.dummySolution = Solution()
self.fitnessCache = {}
for sup in self.supervisors:
supervisorKeywords = self.supervisors[sup].getKeywords()
for stu in self.students:
studentKeywords = self.students[stu].getKeywords()
f_stu, f_sup = self.dummySolution.kw_similarity(
studentKeywords, supervisorKeywords, self.rankWeights)
self.fitnessCache[str((stu, sup))] = (f_stu, f_sup)
# Creating two graphs and solutions
self.graph1 = BipartiteGraph()
self.graph2 = BipartiteGraph()
self.graph1.addEdge("supervisor1", "student2")
self.graph1.addEdge("supervisor2", "student4")
self.graph1.addEdge("supervisor3", "student1")
self.graph1.addEdge("supervisor1", "student3")
self.solution1 = Solution(self.graph1)
self.graph2.addEdge("supervisor1", "student2")
self.graph2.addEdge("supervisor2", "student1")
self.graph2.addEdge("supervisor3", "student4")
self.graph2.addEdge("supervisor1", "student3")
self.solution2 = Solution(self.graph2)
class MutationTest(unittest.TestCase):
def setUp(self):
#Creating a list of students and supervisors
topicNames, topicPaths, topicIDs, levels = parseFile(
"pystsup/test/acm.txt")
self.supervisors = {}
self.students = {}
stuID = "student"
supID = "supervisor"
stuList1 = [
"MapReduce-based systems", "Multidimensional range search",
"Open source software", "Data mining", "Online shopping"
]
stuList2 = [
"Heuristic function construction", "Multi-agent systems",
"Open source software", "Data mining", "Speech recognition"
]
stuList3 = [
"Multi-agent systems", "Speech recognition",
"Heuristic function construction", "Data mining",
"Object identification"
]
stuList4 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList1 = [
"Multi-agent systems", "Intelligent agents",
"MapReduce-based systems", "Object identification",
"Heuristic function construction"
]
supList2 = [
"Open source software", "Data mining", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList3 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList = [supList1, supList2, supList3]
supQuota = [2, 2, 1]
stuList = [stuList1, stuList2, stuList3, stuList4]
for i in range(3):
toAdd = []
sup_list = {}
rank = 0
for kw in supList[i]:
rank += 1
sup_list[rank] = [
kw, getPath(kw, topicNames, topicPaths, topicIDs)
]
sup = supID + str(i + 1)
quota = supQuota[i]
supervisorObject = Supervisor(sup, sup_list, quota)
self.supervisors[sup] = supervisorObject
for i in range(4):
toAdd = []
stu_list = {}
rank = 0
for kw in stuList[i]:
rank += 1
stu_list[rank] = [
kw, getPath(kw, topicNames, topicPaths, topicIDs)
]
stu = stuID + str(i + 1)
studentObject = Student(stu, stu_list)
self.students[stu] = studentObject
# Generating rank weights for c = 0.5
self.rankWeights = Solution.calcRankWeights()
#Creating fitness cache
self.dummySolution = Solution()
self.fitnessCache = {}
for sup in self.supervisors:
supervisorKeywords = self.supervisors[sup].getKeywords()
for stu in self.students:
studentKeywords = self.students[stu].getKeywords()
f_stu, f_sup = self.dummySolution.kw_similarity(
studentKeywords, supervisorKeywords, self.rankWeights)
self.fitnessCache[str((stu, sup))] = (f_stu, f_sup)
# Creating two graphs and solutions
self.graph1 = BipartiteGraph()
self.graph2 = BipartiteGraph()
self.graph1.addEdge("supervisor1", "student2")
self.graph1.addEdge("supervisor2", "student4")
self.graph1.addEdge("supervisor3", "student1")
self.graph1.addEdge("supervisor1", "student3")
self.solution1 = Solution(self.graph1)
self.graph2.addEdge("supervisor1", "student2")
self.graph2.addEdge("supervisor2", "student1")
self.graph2.addEdge("supervisor3", "student4")
self.graph2.addEdge("supervisor1", "student3")
self.solution2 = Solution(self.graph2)
def test_case1(self):
"""Testing mutation function for solution 1"""
mutationProbability = 0.3
swapProbability = 0.5
transferProbability = 0.5
solution3 = mutate(self.solution1, self.supervisors,
mutationProbability, swapProbability,
transferProbability)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case2(self):
"""Testing mutation function for solution 1 - only swap operation"""
mutationProbability = 0.3
swapProbability = 0.5
transferProbability = 0
solution3 = mutate(self.solution1, self.supervisors,
mutationProbability, swapProbability,
transferProbability)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case3(self):
"""Testing mutation function for solution 1 - only transfer operation"""
mutationProbability = 0.3
swapProbability = 0
transferProbability = 0.5
solution3 = mutate(self.solution1, self.supervisors,
mutationProbability, swapProbability,
transferProbability)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case4(self):
"""Testing mutation function for solution 2"""
mutationProbability = 0.3
swapProbability = 0.5
transferProbability = 0.3
solution4 = mutate(self.solution2, self.supervisors,
mutationProbability, swapProbability,
transferProbability)
result = solution4.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case5(self):
"""Testing mutation function for a randomly created solution 1"""
mutationProbability = 0.3
swapProbability = 0.2
transferProbability = 0.8
solution1 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution2 = mutate(solution1, self.supervisors, mutationProbability,
swapProbability, transferProbability)
result = solution2.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case6(self):
"""Testing mutation function for a randomly created solution 2"""
mutationProbability = 0.3
swapProbability = 0.7
transferProbability = 0
solution1 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution2 = mutate(solution1, self.supervisors, mutationProbability,
swapProbability, transferProbability)
result = solution2.isValid(self.students, self.supervisors)
self.assertTrue(result)
class CrossoverTest(unittest.TestCase):
def setUp(self):
#Creating a list of students and supervisors
topicNames, topicPaths, topicIDs, levels = parseFile(
"pystsup/test/acm.txt")
self.supervisors = {}
self.students = {}
stuID = "student"
supID = "supervisor"
stuList1 = [
"MapReduce-based systems", "Multidimensional range search",
"Open source software", "Data mining", "Online shopping"
]
stuList2 = [
"Heuristic function construction", "Multi-agent systems",
"Open source software", "Data mining", "Speech recognition"
]
stuList3 = [
"Multi-agent systems", "Speech recognition",
"Heuristic function construction", "Data mining",
"Object identification"
]
stuList4 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList1 = [
"Multi-agent systems", "Intelligent agents",
"MapReduce-based systems", "Object identification",
"Heuristic function construction"
]
supList2 = [
"Open source software", "Data mining", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList3 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList = [supList1, supList2, supList3]
supQuota = [2, 2, 1]
stuList = [stuList1, stuList2, stuList3, stuList4]
for i in range(3):
toAdd = []
sup_list = {}
rank = 0
for kw in supList[i]:
rank += 1
sup_list[rank] = [
kw, getPath(kw, topicNames, topicPaths, topicIDs)
]
sup = supID + str(i + 1)
quota = supQuota[i]
supervisorObject = Supervisor(sup, sup_list, quota)
self.supervisors[sup] = supervisorObject
for i in range(4):
toAdd = []
stu_list = {}
rank = 0
for kw in stuList[i]:
rank += 1
stu_list[rank] = [
kw, getPath(kw, topicNames, topicPaths, topicIDs)
]
stu = stuID + str(i + 1)
studentObject = Student(stu, stu_list)
self.students[stu] = studentObject
# Generating rank weights for c = 0.5
self.rankWeights = Solution.calcRankWeights()
#Creating fitness cache
self.dummySolution = Solution()
self.fitnessCache = {}
for sup in self.supervisors:
supervisorKeywords = self.supervisors[sup].getKeywords()
for stu in self.students:
studentKeywords = self.students[stu].getKeywords()
f_stu, f_sup = self.dummySolution.kw_similarity(
studentKeywords, supervisorKeywords, self.rankWeights)
self.fitnessCache[str((stu, sup))] = (f_stu, f_sup)
# Creating two graphs and solutions
self.graph1 = BipartiteGraph()
self.graph2 = BipartiteGraph()
self.graph1.addEdge("supervisor1", "student2")
self.graph1.addEdge("supervisor2", "student4")
self.graph1.addEdge("supervisor3", "student1")
self.graph1.addEdge("supervisor1", "student3")
self.solution1 = Solution(self.graph1)
self.graph2.addEdge("supervisor1", "student2")
self.graph2.addEdge("supervisor2", "student1")
self.graph2.addEdge("supervisor3", "student4")
self.graph2.addEdge("supervisor1", "student3")
self.solution2 = Solution(self.graph2)
# Creating test for simplify function
self.graph3 = BipartiteGraph()
self.graph3.addEdge("s1", "st1")
self.graph3.addEdge("s1", "st4")
self.graph3.addEdge("s2", "st1")
self.graph3.addEdge("s2", "st2")
self.graph3.addEdge("s3", "st3")
self.graph3.addEdge("s3", "st5")
self.graph3.addEdge("s4", "st3")
self.graph3.addEdge("s4", "st5")
self.structure3 = {"s1": 2, "s2": 1, "s3": 1, "s4": 1}
self.graph4 = BipartiteGraph()
self.graph4.addEdge("s1", "st1")
self.graph4.addEdge("s1", "st3")
self.graph4.addEdge("s1", "st4")
self.graph4.addEdge("s2", "st3")
self.graph4.addEdge("s2", "st4")
self.graph4.addEdge("s3", "st1")
self.graph4.addEdge("s3", "st2")
self.structure4 = {"s1": 1, "s2": 2, "s3": 1}
#Creating 60-400 data set
self.students2, self.supervisors2 = createRandomData(60, 400, 405)
# m,n,quotaSum,level=3,maxQuota=10,minQuota=4,no_topics=5
self.students3, self.supervisors3 = createRandomData(3,
5,
8,
minQuota=1,
maxQuota=3)
self.problem_instances = [ #createRandomData(6,10,16,minQuota=1)
createRandomData(60, 400, 405)
]
#def test_case_special_cr(self):
#for (students,supervisors) in self.problem_instances :
#for i in range(100):
# sol1 = Solution.generateRandomSolution(students,supervisors)
# sol2 = Solution.generateRandomSolution(students,supervisors)
# sp_crossover(sol1,sol2)
def test_case_simplify1(self):
response, already_set = simplify(self.graph3, self.structure3)
self.assertTrue(("s1", "st1") in response)
self.assertTrue(("s1", "st4") in response)
self.assertTrue(("s2", "st2") in response)
self.assertEqual(self.structure3["s1"], 0)
self.assertEqual(self.structure3["s2"], 0)
self.assertEqual(self.structure3["s3"], 1)
self.assertEqual(self.structure3["s4"], 1)
self.assertTrue(("stu", "st1") in already_set)
self.assertTrue(("stu", "st4") in already_set)
self.assertTrue(("stu", "st2") in already_set)
self.assertTrue(("sup", "s1") in already_set)
self.assertTrue(("sup", "s2") in already_set)
self.assertEqual(len(response), 3)
def test_case_simplify2(self):
response, already_set = simplify(self.graph4, self.structure4)
self.assertTrue(("s1", "st1") in response)
self.assertTrue(("s2", "st3") in response)
self.assertTrue(("s2", "st4") in response)
self.assertTrue(("s3", "st2") in response)
self.assertEqual(self.structure4["s1"], 0)
self.assertEqual(self.structure4["s2"], 0)
self.assertEqual(self.structure4["s3"], 0)
self.assertTrue(("stu", "st1") in already_set)
self.assertTrue(("stu", "st3") in already_set)
self.assertTrue(("stu", "st4") in already_set)
self.assertTrue(("stu", "st2") in already_set)
self.assertTrue(("sup", "s1") in already_set)
self.assertTrue(("sup", "s2") in already_set)
self.assertTrue(("sup", "s3") in already_set)
self.assertEqual(len(response), 4)
def test_case1(self):
"""Testing the ERX Modified Crossover function - for 3sup:4stu solution"""
solution3 = crossover(self.solution1, self.solution2, self.supervisors,
self.students)
structureResult = (solution3.getGraph().getStructure()
== self.solution1.getGraph().getStructure()) or (
solution3.getGraph().getStructure()
== self.solution2.getGraph().getStructure())
result = (solution3.isValid(self.students,
self.supervisors)) and (structureResult)
self.assertTrue(result)
def test_case2(self):
"""Testing the kPoint crossover function - for 3sup:4stu solution"""
solution3 = kPoint(self.solution1,
self.solution2,
self.supervisors,
self.students,
k=3)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case3(self):
"""Testing the EDX Modified crossover function - when one valid and one dummy solution are passed"""
self.assertRaises(
KeyError, lambda: crossover(self.solution1, self.dummySolution,
self.supervisors, self.students))
def test_case4(self):
"""Testing the K Point Crossover function - when one valid and one dummy solution are passed"""
self.assertRaises(
KeyError, lambda: kPoint(self.solution2,
self.dummySolution,
self.supervisors,
self.students,
k=3))
def test_case5(self):
"""Testing the ERX Modified Crossover function - for random 3sup:4stu solution"""
solution1 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution2 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution3 = crossover(solution1, solution2, self.supervisors,
self.students)
structureResult = (solution3.getGraph().getStructure()
== solution1.getGraph().getStructure()) or (
solution3.getGraph().getStructure()
== solution2.getGraph().getStructure())
result = (solution3.isValid(self.students,
self.supervisors)) and (structureResult)
self.assertTrue(result)
def test_case6(self):
"""Testing the K Point Crossover function - for random 3sup:4stu solution"""
solution1 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution2 = Solution.generateRandomSolution(self.students,
self.supervisors)
solution3 = kPoint(solution1,
solution2,
self.supervisors,
self.students,
k=3)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case7(self):
"""Testing the K Point crossover function - when k=0"""
solution3 = kPoint(self.solution1,
self.solution2,
self.supervisors,
self.students,
k=0)
structureResult = (solution3.getGraph().getStructure()
== self.solution1.getGraph().getStructure()) or (
solution3.getGraph().getStructure()
== self.solution2.getGraph().getStructure())
result = (solution3.isValid(self.students,
self.supervisors)) and (structureResult)
self.assertTrue(result)
def test_case8(self):
"""Testing the K Point crossover function - when k=1"""
solution3 = kPoint(self.solution1,
self.solution2,
self.supervisors,
self.students,
k=1)
result = solution3.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case9(self):
"""Testing the K Point crossover function - when k > no_students"""
self.assertRaises(
ValueError, lambda: kPoint(self.solution1,
self.solution2,
self.supervisors,
self.students,
k=6))
def test_case10(self):
"""Testing the ERX Modified crossover function - for random 60sup:400stu solution"""
solution1 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution2 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution3 = crossover(solution1, solution2, self.supervisors2,
self.students2)
structureResult = (solution3.getGraph().getStructure()
== solution1.getGraph().getStructure()) or (
solution3.getGraph().getStructure()
== solution2.getGraph().getStructure())
result = (solution3.isValid(self.students2,
self.supervisors2)) and (structureResult)
self.assertTrue(result)
def test_case11(self):
"""Testing the ERX Modified crossover function - for random 60sup:400stu solution"""
solution1 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution2 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution3 = crossover(solution1, solution2, self.supervisors,
self.supervisors2, self.students2)
structureResult = (solution3.getGraph().getStructure()
== solution1.getGraph().getStructure()) or (
solution3.getGraph().getStructure()
== solution2.getGraph().getStructure())
result = (solution3.isValid(self.students2,
self.supervisors2)) and (structureResult)
self.assertTrue(result)
def test_case12(self):
"""Testing the kPoint crossover function - for random 60sup:400stu solution"""
solution1 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution2 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution3 = kPoint(solution1,
solution2,
self.supervisors2,
self.students2,
k=15)
result = solution3.isValid(self.students2, self.supervisors2)
self.assertTrue(result)
def test_case13(self):
"""Testing the kPoint crossover function - for random 60sup:400stu solution"""
solution1 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution2 = Solution.generateRandomSolution(self.students2,
self.supervisors2)
solution3 = kPoint(solution1,
solution2,
self.supervisors2,
self.students2,
k=15)
result = solution3.isValid(self.students2, self.supervisors2)
self.assertTrue(result)
def kPoint(solution1, solution2, supervisors, students, k=5):
"""
An Implementation of K-Point crossover for this problem.
"""
graph1 = solution1.getGraph()
graph2 = solution2.getGraph()
stuEdges1 = graph1.getStuEdges()
stuEdges2 = graph2.getStuEdges()
supEdges1 = graph1.getEdges()
#Randomly getting the structure from the two graphs
num = random.randint(1, 2)
if num == 1:
structure = graph1.getStructure()
else:
structure = graph2.getStructure()
#Setting up the vectors
students = list(stuEdges1.keys())
sol1 = []
sol2 = []
for i in range(len(students)):
sol1.append(stuEdges1[students[i]][0])
sol2.append(stuEdges2[students[i]][0])
#Dividing the both solutions into k-points
sol1Points = []
sol2Points = []
points = sorted(random.sample(range(1, len(students)), k))
curr = 0
for i in range(k - 1):
sol1Points.append(sol1[curr:points[i]])
sol2Points.append(sol2[curr:points[i]])
curr = points[i]
sol1Points.append(sol1[curr:])
sol2Points.append(sol2[curr:])
#Perform the crossover
result = []
if k == 0:
n = random.randint(1, 2)
if n == 1:
result = sol1
else:
result = sol2
else:
for point in range(k):
n = random.randint(1, 2)
if n == 1:
result.extend(sol1Points[point])
else:
result.extend(sol2Points[point])
graph = BipartiteGraph()
for i in range(len(students)):
graph.addEdge(result[i], students[i])
fixSolution(graph, supervisors, students)
#supEdges = graph.getEdges()
#availableStudents = set()
#reqSup = set(list(supEdges1.keys())).difference(set(list(supEdges.keys())))
#sol3 = Solution(graph)
#canTransferFrom,canTransferTo = sol3.getTransferable(supervisors)
#for sup in supEdges:
# supDegree = len(supEdges[sup])
# supQuota = supervisors[sup].getQuota()
# if supDegree > supQuota:
# excess = supDegree - supQuota
# for i in random.sample(supEdges[sup],excess):
# availableStudents.add(i)
# elif supDegree == 0:
# reqSup.add(sup)
#for sup in reqSup:
# if len(availableStudents)==0:
# fromSup = random.choice(list(canTransferFrom))
# stu = random.choice(graph.getStudents(fromSup))
# availableStudents.add(stu)
# x = random.choice(list(availableStudents))
# availableStudents.remove(x)
# oldSup = graph.getSupervisors(x)[0]
# graph.transferStudent1(x,oldSup,sup,supervisors)
#sol3 = Solution(graph)
#canTransferFrom,canTransferTo = sol3.getTransferable(supervisors)
#for stu in availableStudents:
# con = False
# oldSup = graph.getSupervisors(stu)[0]
# if oldSup in canTransferTo:
# canTransferTo.remove(oldSup)
# con=True
# toSup = random.choice(list(canTransferTo))
# graph.transferStudent1(stu,oldSup,toSup,supervisors)
# if con:
# canTransferTo.add(oldSup)
# if not(graph.getSupervisorDegree(toSup) < supervisors[toSup].getQuota()):
# canTransferTo.remove(toSup)
return Solution(graph)
class SolutionTest(unittest.TestCase):
def setUp(self):
#Creating a list of students and supervisors
topicNames,topicPaths, topicIDs, levels = parseFile("pystsup/test/acm.txt")
self.supervisors = {}
self.students = {}
stuID = "student"
supID = "supervisor"
stuList1 = ["MapReduce-based systems","Multidimensional range search","Open source software","Data mining","Online shopping"]
stuList2 = ["Heuristic function construction","Multi-agent systems","Open source software","Data mining","Speech recognition"]
stuList3 = ["Multi-agent systems","Speech recognition","Heuristic function construction","Data mining","Object identification"]
stuList4 = ["Multi-agent systems","Intelligent agents","Speech recognition","Object identification","Heuristic function construction"]
supList1 = ["Multi-agent systems","Intelligent agents","MapReduce-based systems","Object identification","Heuristic function construction"]
supList2 = ["Open source software","Data mining","Speech recognition","Object identification","Heuristic function construction"]
supList3 = ["Multi-agent systems","Intelligent agents","Speech recognition","Object identification","Heuristic function construction"]
supList = [supList1,supList2,supList3]
supQuota = [2,2,1]
stuList = [stuList1,stuList2,stuList3,stuList4]
for i in range(3):
toAdd = []
sup_list = {}
rank = 0
for kw in supList[i]:
rank+=1
sup_list[rank]=[kw,getPath(kw,topicNames,topicPaths, topicIDs)]
sup = supID + str(i+1)
quota = supQuota[i]
supervisorObject = Supervisor(sup,sup_list,quota)
self.supervisors[sup]=supervisorObject
for i in range(4):
toAdd = []
stu_list = {}
rank = 0
for kw in stuList[i]:
rank+=1
stu_list[rank] = [kw,getPath(kw,topicNames,topicPaths, topicIDs)]
stu = stuID + str(i+1)
studentObject = Student(stu,stu_list)
self.students[stu]=studentObject
# Generating rank weights for c = 0.5
self.rankWeights = Solution.calcRankWeights()
#Creating fitness cache
self.dummySolution = Solution()
self.fitnessCache = {}
for sup in self.supervisors:
supervisorKeywords = self.supervisors[sup].getKeywords()
for stu in self.students:
studentKeywords = self.students[stu].getKeywords()
f_stu,f_sup = self.dummySolution.kw_similarity(studentKeywords,supervisorKeywords, self.rankWeights)
self.fitnessCache[str((stu,sup))] = (f_stu,f_sup)
# Creating two graphs and solutions
self.graph1 = BipartiteGraph()
self.graph2 = BipartiteGraph()
self.graph1.addEdge("supervisor1","student2")
self.graph1.addEdge("supervisor2","student4")
self.graph1.addEdge("supervisor3","student1")
self.graph1.addEdge("supervisor1","student3")
self.solution1 = Solution(self.graph1)
self.graph2.addEdge("supervisor1","student2")
self.graph2.addEdge("supervisor2","student1")
self.graph2.addEdge("supervisor3","student4")
self.graph2.addEdge("supervisor1","student3")
self.solution2 = Solution(self.graph2)
def test_case1(self):
"""Testing the create random solution function"""
solution1 = Solution.generateRandomSolution(self.students,self.supervisors)
result = solution1.isValid(self.students,self.supervisors)
self.assertEqual(result,True)
def test_case2(self):
"""Testing the calculate Rank Weights function when c = 1"""
rankWeights = Solution.calcRankWeights(c=1)
result = True
expected = 0.2
for i in rankWeights:
if rankWeights[i] != expected:
result = False
break
self.assertTrue(result)
def test_case3(self):
"""Testing the calculate rank weights function when c = 0.3"""
rankWeights = Solution.calcRankWeights(c=0.3)
result = round(sum(rankWeights.values()),15)
expected = {1: 0.701705143, 2: 0.210511543, 3: 0.063153463, 4: 0.0189460389, 5: 0.005683812}
result2 = True
for i in rankWeights:
if round(rankWeights[i],8) != round(expected[i],8):
result2 = False
break
self.assertEqual((result,result2),(1,True))
def test_case4(self):
"""Testing the calculate rank weights function when c=0 and n=0"""
rankWeights = Solution.calcRankWeights(c=0,n=0)
expected = {}
self.assertEqual(rankWeights,expected)
def test_case5(self):
"""Testing similarity function with 2 non-similar profiles (0)"""
dummySolution = Solution()
supervisorKeywords = self.supervisors["supervisor3"].getKeywords()
studentKeywords = self.students["student1"].getKeywords()
f_stu,f_sup = dummySolution.kw_similarity(studentKeywords,supervisorKeywords,self.rankWeights)
expected_fstu = 0.1217742
expected_fsup = 0.1416129
expected = (round(expected_fstu,6),round(expected_fsup,6))
retrieved = (round(f_stu,6),round(f_sup,6))
self.assertEqual(retrieved,expected)
def test_case6(self):
"""Testing similarity function with 2 identical profiles (1)"""
dummySolution = Solution()
supervisorKeywords = self.supervisors["supervisor3"].getKeywords()
studentKeywords = self.students["student4"].getKeywords()
f_stu,f_sup = dummySolution.kw_similarity(studentKeywords,supervisorKeywords,self.rankWeights)
self.assertEqual((f_stu,f_sup),(1,1))
def test_case7(self):
"""Testing similarity function between 2 mostly similar profiles """
dummySolution = Solution()
supervisorKeywords = self.supervisors["supervisor3"].getKeywords()
studentKeywords = self.students["student3"].getKeywords()
f_stu,f_sup = dummySolution.kw_similarity(studentKeywords,supervisorKeywords,self.rankWeights)
expected_fstu = 0.708333
expected_fsup = 0.726882
expected = (round(expected_fstu,6),round(expected_fsup,6))
retrieved = (round(f_stu,6),round(f_sup,6))
self.assertEqual(retrieved,expected)
def test_case8(self):
"""Testing similarity function between 2 less similar profiles """
dummySolution = Solution()
supervisorKeywords = self.supervisors["supervisor3"].getKeywords()
studentKeywords = self.students["student2"].getKeywords()
f_stu,f_sup = dummySolution.kw_similarity(studentKeywords,supervisorKeywords,self.rankWeights)
expected_fstu = 0.255645
expected_fsup = 0.522043
expected = (round(expected_fstu,6),round(expected_fsup,6))
retrieved = (round(f_stu,6),round(f_sup,6))
self.assertEqual(retrieved,expected)
def test_case9(self):
"""Testing intersection function - between 2 non-intersecting lists"""
list1 = self.supervisors["supervisor1"].getKeywords()[1][1]
list2 = self.students["student1"].getKeywords()[1][1]
result = self.dummySolution._intersection(list1,list2)
self.assertEqual(result,1)
def test_case10(self):
"""Testing intersection function - between 2 lists with 1 common element"""
list1 = ["Document types","General and reference"]
list2 = ["Cross-computing tools and techniques","General and reference"]
result = self.dummySolution._intersection(list1,list2)
self.assertEqual(result,1)
def test_case11(self):
"""Testing intersection function - between 2 lists with 2 common element"""
list1 = ["Reference works","Document types","General and reference"]
list2 = ["Surveys and overviews","Document types","General and reference"]
result = self.dummySolution._intersection(list1,list2)
self.assertEqual(result,2)
def test_case12(self):
"""Testing intersection function - between 2 lists with 3 common element"""
list1 = ["Digital signal processing","Signal processing systems","Communication hardware, interfaces and storage","Hardware"]
list2 = ["Beamforming","Signal processing systems","Communication hardware, interfaces and storage","Hardware"]
result = self.dummySolution._intersection(list1,list2)
self.assertEqual(result,3)
def test_case13(self):
"""Testing intersection function - between 2 identical lists"""
list1 = self.supervisors["supervisor1"].getKeywords()[1][1]
list2 = self.students["student4"].getKeywords()[1][1]
result = self.dummySolution._intersection(list1,list2)
self.assertEqual(result,5)
def test_case14(self):
"""Testing the calc fitness function for a bad solution"""
self.solution1.calcFitness(self.students,self.supervisors,self.rankWeights,self.fitnessCache)
F_st = self.solution1.getFst()
F_sup = self.solution1.getFsup()
retrieved = (round(F_sup,6),round(F_st,6))
expected = (0.600813,1.457903)
self.assertEqual(retrieved,expected)
def test_case15(self):
"""Testing the calc fitness function for a fairly good solution"""
self.solution2.calcFitness(self.students,self.supervisors,self.rankWeights,self.fitnessCache)
F_st = self.solution2.getFst()
F_sup = self.solution2.getFsup()
retrieved = (round(F_sup,7),round(F_st,7))
expected = (1.1482502,2.1678495)
self.assertEqual(retrieved,expected)
def test_case16(self):
"""Testing transfer function - a valid transfer"""
self.solution1.transferStudent("student3","supervisor1","supervisor2",self.supervisors)
solutionGraph = self.solution1.getGraph()
val1 = solutionGraph.getStudents("supervisor1")
val2 = solutionGraph.getStudents("supervisor2")
val3 = solutionGraph.getSupervisors("student3")
expected = (['student2'],['student4','student3'],['supervisor2'])
self.assertEqual((val1,val2,val3),expected)
def test_case17(self):
"""Testing getGraph function"""
solutionGraph = self.solution1.getGraph()
val1 = isinstance(solutionGraph,BipartiteGraph)
val2 = solutionGraph.getStuEdges()
result = (val1,val2)
expected1 = True
expected2 = {'student1':['supervisor3'],'student2':['supervisor1'],'student3':['supervisor1'],'student4':['supervisor2']}
expected = (expected1,expected2)
self.assertEqual(result,expected)
def test_case18(self):
"""Testing the isValid function - passing a null graph"""
graph = BipartiteGraph()
solution = Solution(graph)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case19(self):
"""Testing the isValid function - when number of supervisors less than actual"""
graph = BipartiteGraph()
graph.addEdge("supervisor1","student1")
graph.addEdge("supervisor2","student4")
graph.addEdge("supervisor2","student3")
graph.addEdge("supervisor1","student2")
solution = Solution(graph)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case20(self):
"""Testing the isValid function - when number of students less than actual"""
graph = BipartiteGraph()
graph.addEdge("supervisor1","student1")
graph.addEdge("supervisor3","student3")
graph.addEdge("supervisor2","student2")
solution = Solution(graph)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case21(self):
"""Testing the isValid function - when a supervisor's allocation exceeds their quota"""
self.graph1.addEdge("supervisor3","student2")
solution = Solution(self.graph1)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case22(self):
"""Testing the isValid function - when a supervisor's degree is 0"""
self.graph1.removeEdge("supervisor3","student1")
solution = Solution(self.graph1)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case23(self):
"""Testing the isValid function - when a student's degree is not equal to 1"""
self.graph1.addEdge("supervisor2","student3")
solution = Solution(self.graph1)
result = solution.isValid(self.students,self.supervisors)
self.assertFalse(result)
def test_case24(self):
"""Testing is valid function - when a correct graph is passed"""
result1 = self.solution1.isValid(self.students,self.supervisors)
result2 = self.solution2.isValid(self.students,self.supervisors)
self.assertEqual((result1,result2),(True,True))
def test_case25(self):
"""Testing 'dominates' function - when both Fst and Fsup are greater in solution1 than solution2"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(29.5)
solution1.setFsup(0.4)
solution2.setFst(27.5)
solution2.setFsup(0.2)
result = solution1.dominates(solution2)
self.assertTrue(result)
def test_case26(self):
"""Testing 'dominates' function - when only Fsup is greater in solution2 than solution1"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(29.5)
solution1.setFsup(0.4)
solution2.setFst(27.5)
solution2.setFsup(0.6)
result = solution1.dominates(solution2)
self.assertFalse(result)
def test_case27(self):
"""Testing 'dominates' function - when Fsup is same in solution2 and solution1"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(29.5)
solution1.setFsup(0.4)
solution2.setFst(27.5)
solution2.setFsup(0.4)
result = solution1.dominates(solution2)
self.assertTrue(result)
def test_case28(self):
"""Testing 'dominates' function - when only Fst is greater in solution2 and solution1"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(26.5)
solution1.setFsup(0.4)
solution2.setFst(27.5)
solution2.setFsup(0.2)
result = solution1.dominates(solution2)
self.assertFalse(result)
def test_case29(self):
"""Testing 'dominates' function - when both Fst and Fsup are lesser in solution1 than solution2"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(26.5)
solution1.setFsup(0.2)
solution2.setFst(27.5)
solution2.setFsup(0.4)
result = solution1.dominates(solution2)
self.assertFalse(result)
def test_case30(self):
"""Testing 'dominates' function - when Fst is same in solution2 and solution1"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(29.5)
solution1.setFsup(0.6)
solution2.setFst(29.5)
solution2.setFsup(0.4)
result = solution1.dominates(solution2)
self.assertTrue(result)
def test_case31(self):
"""Testing 'dominates' function - when Fst is same in solution2 and solution1"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(29.5)
solution1.setFsup(0.2)
solution2.setFst(29.5)
solution2.setFsup(0.4)
result = solution1.dominates(solution2)
self.assertFalse(result)
def test_case32(self):
"""Testing 'dominates' function - when Fst and Fsup are same in solution2 and solution1"""
solution1 = Solution()
solution2 = Solution()
solution1.setFst(29.5)
solution1.setFsup(0.4)
solution2.setFst(29.5)
solution2.setFsup(0.4)
result = solution1.dominates(solution2)
self.assertFalse(result)
def setUp(self):
self.graph1 = BipartiteGraph()
self.graph2 = BipartiteGraph()
self.graph1.addEdge("supervisor1", "student1")
self.graph1.addEdge("supervisor2", "student4")
self.graph1.addEdge("supervisor3", "student3")
self.graph1.addEdge("supervisor1", "student2")
self.graph2.addEdge("supervisor1", "student4")
self.graph2.addEdge("supervisor2", "student1")
self.graph2.addEdge("supervisor2", "student3")
self.graph2.addEdge("supervisor3", "student2")
#Creating a list of students and supervisors
topicNames, topicPaths, topicIDs, levels = parseFile(
"pystsup/test/acm.txt")
self.supervisors = {}
self.students = {}
stuID = "student"
supID = "supervisor"
stuList1 = [
"MapReduce-based systems", "Multidimensional range search",
"Open source software", "Data mining", "Online shopping"
]
stuList2 = [
"Heuristic function construction", "Multi-agent systems",
"Open source software", "Data mining", "Speech recognition"
]
stuList3 = [
"Multi-agent systems", "Speech recognition",
"Heuristic function construction", "Data mining",
"Object identification"
]
stuList4 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList1 = [
"Multi-agent systems", "Intelligent agents",
"MapReduce-based systems", "Object identification",
"Heuristic function construction"
]
supList2 = [
"Open source software", "Data mining", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList3 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList = [supList1, supList2, supList3]
supQuota = [2, 2, 1]
stuList = [stuList1, stuList2, stuList3, stuList4]
for i in range(3):
toAdd = []
sup_list = {}
rank = 0
for kw in supList[i]:
rank += 1
sup_list[kw] = [
rank, getPath(kw, topicNames, topicPaths, topicIDs)
]
sup = supID + str(i + 1)
quota = supQuota[i]
supervisorObject = Supervisor(sup, sup_list, quota)
self.supervisors[sup] = supervisorObject
for i in range(4):
toAdd = []
stu_list = {}
rank = 0
for kw in stuList[i]:
rank += 1
stu_list[kw] = [
rank, getPath(kw, topicNames, topicPaths, topicIDs)
]
stu = stuID + str(i + 1)
studentObject = Student(stu, stu_list)
self.students[stu] = studentObject
class BipartiteGraphTest(unittest.TestCase):
def setUp(self):
self.graph1 = BipartiteGraph()
self.graph2 = BipartiteGraph()
self.graph1.addEdge("supervisor1", "student1")
self.graph1.addEdge("supervisor2", "student4")
self.graph1.addEdge("supervisor3", "student3")
self.graph1.addEdge("supervisor1", "student2")
self.graph2.addEdge("supervisor1", "student4")
self.graph2.addEdge("supervisor2", "student1")
self.graph2.addEdge("supervisor2", "student3")
self.graph2.addEdge("supervisor3", "student2")
#Creating a list of students and supervisors
topicNames, topicPaths, topicIDs, levels = parseFile(
"pystsup/test/acm.txt")
self.supervisors = {}
self.students = {}
stuID = "student"
supID = "supervisor"
stuList1 = [
"MapReduce-based systems", "Multidimensional range search",
"Open source software", "Data mining", "Online shopping"
]
stuList2 = [
"Heuristic function construction", "Multi-agent systems",
"Open source software", "Data mining", "Speech recognition"
]
stuList3 = [
"Multi-agent systems", "Speech recognition",
"Heuristic function construction", "Data mining",
"Object identification"
]
stuList4 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList1 = [
"Multi-agent systems", "Intelligent agents",
"MapReduce-based systems", "Object identification",
"Heuristic function construction"
]
supList2 = [
"Open source software", "Data mining", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList3 = [
"Multi-agent systems", "Intelligent agents", "Speech recognition",
"Object identification", "Heuristic function construction"
]
supList = [supList1, supList2, supList3]
supQuota = [2, 2, 1]
stuList = [stuList1, stuList2, stuList3, stuList4]
for i in range(3):
toAdd = []
sup_list = {}
rank = 0
for kw in supList[i]:
rank += 1
sup_list[kw] = [
rank, getPath(kw, topicNames, topicPaths, topicIDs)
]
sup = supID + str(i + 1)
quota = supQuota[i]
supervisorObject = Supervisor(sup, sup_list, quota)
self.supervisors[sup] = supervisorObject
for i in range(4):
toAdd = []
stu_list = {}
rank = 0
for kw in stuList[i]:
rank += 1
stu_list[kw] = [
rank, getPath(kw, topicNames, topicPaths, topicIDs)
]
stu = stuID + str(i + 1)
studentObject = Student(stu, stu_list)
self.students[stu] = studentObject
def test_case1(self):
"""Testing addEdge function in an empty graph"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
val1 = graph.getStudents("supervisor1")
val2 = graph.getSupervisors("student1")
expected1 = ["student1"]
expected2 = ["supervisor1"]
self.assertEqual((val1, val2), (expected1, expected2))
def test_case2(self):
"""Testing addEdge function in a graph with existing nodes and edges"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
graph.addEdge("supervisor2", "student4")
graph.addEdge("supervisor3", "student3")
val1 = graph.getSupervisorDegree("supervisor1")
graph.addEdge("supervisor1", "student2")
curr = graph.getSupervisorDegree("supervisor1")
val2 = graph.getSupervisors("student2")
expected2 = ["supervisor1"]
self.assertEqual((curr - 1, expected2), (val1, val2))
def test_case3(self):
"""Testing addEdge function when adding an edge that already exists"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
graph.addEdge("supervisor1", "student1")
val1 = graph.getSupervisorDegree("supervisor1")
val2 = graph.getStudentDegree("student1")
self.assertEqual((val1, val2), (1, 1))
def test_case4(self):
"""Testing the remove edge function in an empty graph"""
graph = BipartiteGraph()
self.assertRaises(KeyError,
lambda: graph.removeEdge("supervisor1", "student1"))
def test_case5(self):
"""Testing the removeEdge function when trying to remove an edge that doesn't exist"""
self.assertRaises(
ValueError,
lambda: self.graph1.removeEdge("supervisor2", "student1"))
def test_case6(self):
"""Testing the removeEdge function in a graph with existing nodes and edges"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
graph.removeEdge("supervisor1", "student1")
val1 = graph.getStudentDegree("student1")
val2 = graph.getSupervisorDegree("supervisor1")
self.assertEqual((val1, val2), (0, 0))
def test_case7(self):
"""Testing the merge function in two graphs"""
graph3 = self.graph1.merge(self.graph2)
expected = {
'supervisor1': ['student1', 'student2', 'student4'],
'supervisor2': ['student4', 'student1', 'student3'],
'supervisor3': ['student3', 'student2']
}
result = True
for sup in expected:
for stu in expected[sup]:
if not graph3.isEdge(sup, stu):
result = False
break
self.assertTrue(result)
def test_case8(self):
"""Testing the create random graph function"""
graph = BipartiteGraph.createRandomGraph(self.students,
self.supervisors)
solution = Solution(graph)
result = solution.isValid(self.students, self.supervisors)
self.assertTrue(result)
def test_case9(self):
"""Testing transfer function - Cannnot transfer student when a supervisor has less than 2 students"""
self.graph1.transferStudent("student3", "supervisor3", "supervisor2",
self.supervisors)
val1 = self.graph1.getStudentDegree("student3")
val2 = self.graph1.getSupervisors("student3")
expected = (1, ['supervisor3'])
self.assertEqual((val1, val2), expected)
def test_case10(self):
"""Testing transfer function - cannot transfer student to a supervisor who reached their maximum quota"""
self.graph1.transferStudent("student1", "supervisor1", "supervisor3",
self.supervisors)
val1 = self.graph1.getSupervisorDegree("supervisor1")
val2 = self.graph1.getSupervisors("student1")
val3 = self.graph1.getStudents("supervisor3")
expected = (2, ['supervisor1'], ['student3'])
self.assertEqual((val1, val2, val3), expected)
def test_case11(self):
"""Testing transfer function - cannot transfer student if student doesn't exist in the graph"""
self.graph1.transferStudent("student5", "supervisor1", "supervisor2",
self.supervisors)
val1 = self.graph1.getSupervisorDegree("supervisor1")
val2 = self.graph1.getStudents("supervisor3")
expected = (2, ['student3'])
self.assertEqual((val1, val2), expected)
def test_case12(self):
"""Testing transfer function - cannot transfer student if the edge doesn't exist in the graph"""
self.graph1.transferStudent("student3", "supervisor1", "supervisor2",
self.supervisors)
val1 = self.graph1.getSupervisorDegree("supervisor1")
val2 = self.graph1.getStudents("supervisor2")
val3 = self.graph1.getStudents("supervisor1")
expected = (2, ['student4'], ['student1', 'student2'])
self.assertEqual((val1, val2, val3), expected)
def test_case13(self):
"""Testing transfer function - cannot transfer student if edge already exists in the supervisor transferring to"""
self.graph1.transferStudent("student4", "supervisor1", "supervisor2",
self.supervisors)
val1 = self.graph1.getSupervisorDegree("supervisor1")
val2 = self.graph1.getStudents("supervisor2")
val3 = self.graph1.getStudents("supervisor1")
expected = (2, ['student4'], ['student1', 'student2'])
self.assertEqual((val1, val2, val3), expected)
def test_case14(self):
"""Testing transfer function - a valid transfer"""
self.graph1.transferStudent("student2", "supervisor1", "supervisor2",
self.supervisors)
val1 = self.graph1.getStudents("supervisor1")
val2 = self.graph1.getStudents("supervisor2")
val3 = self.graph1.getSupervisors("student2")
expected = (['student1'], ['student4', 'student2'], ['supervisor2'])
self.assertEqual((val1, val2, val3), expected)
def test_case15(self):
"""Testing supervisor Exists function - when a supervisor does not exist"""
result = self.graph1.supervisorExists("supervisor4")
self.assertFalse(result)
def test_case16(self):
"""Testing supervisor Exists function - when a supervisor exists"""
result = self.graph1.supervisorExists("supervisor1")
self.assertTrue(result)
def test_case17(self):
"""Testing student exists function - when a student does not exists"""
result = self.graph1.studentExists("student5")
self.assertFalse(result)
def test_case18(self):
"""Testing student exists function - when a student exists"""
result = self.graph1.studentExists("student1")
self.assertTrue(result)
def test_case19(self):
"""Testing isEdge function - when a supervisor does not exist in graph"""
result = self.graph1.isEdge("supervisor5", "student1")
self.assertFalse(result)
def test_case20(self):
"""Testing isEdge function - when a student does not exist in graph"""
result = self.graph1.isEdge("supervisor1", "student5")
self.assertFalse(result)
def test_case21(self):
"""Testing isEdge function - when a edge does not exist"""
result = self.graph1.isEdge("supervisor2", "student1")
self.assertFalse(result)
def test_case22(self):
"""Testing isEdge function - when a edge exists"""
result = self.graph1.isEdge("supervisor1", "student1")
self.assertTrue(result)
def test_case23(self):
"""Testing getStudents function"""
result = self.graph1.getStudents("supervisor3")
expected = ['student3']
self.assertEqual(result, expected)
def test_case24(self):
"""Testing getSupervisors function"""
result = self.graph1.getSupervisors("student1")
expected = ['supervisor1']
self.assertEqual(result, expected)
def test_case25(self):
"""Testing getSupervisorDegree function"""
result = self.graph1.getSupervisorDegree("supervisor1")
expected = 2
self.assertEqual(result, expected)
def test_case26(self):
"""Testing getStudentDegree function"""
result = self.graph1.getStudentDegree("student2")
expected = 1
self.assertEqual(result, expected)
def test_case27(self):
"""Testing getStructure function"""
result = self.graph1.getStructure()
expected = {'supervisor1': 2, 'supervisor2': 1, 'supervisor3': 1}
self.assertEqual(result, expected)
def test_case28(self):
"""Testing getEdges function"""
result = self.graph1.getEdges()
expected = {
'supervisor1': ['student1', 'student2'],
'supervisor2': ['student4'],
'supervisor3': ['student3']
}
self.assertEqual(result, expected)
def test_case29(self):
"""Testing getStuEdges function"""
result = self.graph1.getStuEdges()
expected = {
'student1': ['supervisor1'],
'student2': ['supervisor1'],
'student3': ['supervisor3'],
'student4': ['supervisor2']
}
self.assertEqual(result, expected)
def test_case30(self):
"""Testing getNumberofEdges function"""
result = self.graph1.getNumberofEdges()
expected = 4
self.assertEqual(result, expected)
def test_case31(self):
"""Testing the swap function - when 2 non-existing pairs of edges are passed"""
self.assertRaises(
ValueError, lambda: self.graph1.swapStudents(
"student1", "supervisor2", "student3", "supervisor1"))
def test_case32(self):
"""Testing the swap function - when 2 non-existing students and supervisors are passed"""
self.assertRaises(
KeyError, lambda: self.graph1.swapStudents(
"student5", "supervisor5", "student6", "supervisor6"))
def test_case33(self):
"""Testing the swap function - when 2 existing edges are passed"""
self.graph1.swapStudents("student1", "supervisor1", "student3",
"supervisor3")
result1 = self.graph1.getSupervisors("student3")
result2 = self.graph1.getSupervisors("student1")
expected1 = ['supervisor1']
expected2 = ['supervisor3']
self.assertEqual((result1, result2), (expected1, expected2))
def test_case34(self):
"""Testing the swap function - when swaping students of same supervisor"""
self.graph1.swapStudents("student1", "supervisor1", "student2",
"supervisor1")
result1 = self.graph1.getSupervisors("student1")
result2 = self.graph1.getSupervisors("student2")
expected1 = ['supervisor1']
expected2 = ['supervisor1']
self.assertEqual((result1, result2), (expected1, expected2))
def crossover(solution1, solution2, supervisors=None, students=None, k=None):
"""
Function to perfrom crossover on two solutions.
Parameters:
solution1 (Solution) - parent solution 1
solution2 (Solution) - parent solution 2
Returns:
A New Solution Object - an offspring solution from both the parent solutions.
"""
#Merging the two Graphs
graph1 = solution1.getGraph()
graph2 = solution2.getGraph()
mergedGraph = graph1.merge(graph2)
stuEdges = mergedGraph.getStuEdges()
supEdges = mergedGraph.getEdges()
#Randomly getting the structure from the two graphs
stf1 = solution1.getStructuralFitness(supervisors)
stf2 = solution2.getStructuralFitness(supervisors)
if random.random() <= (stf1) / (stf1 + stf2):
structure = graph1.getStructure()
else:
structure = graph2.getStructure()
lockedEdges = set()
lockedVertices = set()
allStudents = set(list(stuEdges.keys()))
result = BipartiteGraph()
counts = {
} #stores the degree of the supervisors in the new offspring graph
for sup in supEdges:
counts[sup] = 0
#Simplify first time here
simplified = True
prev_count = {}
while prev_count != counts:
prev_count = dict(counts)
for sup in supEdges:
supDegree = len(supEdges[sup])
reqDegree = structure[sup]
for stu in supEdges[sup]:
if len(stuEdges[stu]) == 1 and not stu in lockedVertices:
mergedGraph.removeExcept(sup, stu)
result.addEdge(sup, stu)
lockedVertices.add(stu)
counts[sup] += 1
if counts[sup] == reqDegree:
toKeep = result.getStudents(sup)
toRemove = mergedGraph.getRemainingStu(sup, toKeep)
for i in toRemove:
mergedGraph.removeEdge(sup, i)
prev = set()
toContinue = False
while len(lockedVertices) != len(stuEdges):
for sup in supEdges:
#If the supervisor degree is not equal to degree we want
if counts[sup] != structure[sup]:
supDegree = mergedGraph.getSupervisorDegree(sup)
reqSupDegree = structure[sup]
students = mergedGraph.getStudents(sup)
#Pick a random student that is not locked from the supervior's list of students
curr = random.choice(students)
if (curr not in lockedVertices):
#If that edge can be locked, then lock it.
if mergedGraph.canLock(sup, curr, structure, counts,
lockedVertices):
#Remove other supervisors in student's list of supervisors
mergedGraph.removeExcept(sup, curr)
#Add it to the new graph and also locked vertices
result.addEdge(sup, curr)
lockedVertices.add(curr)
#Increment the degree of the supervisor
counts[sup] += 1
#If the degee is the degree we want
if counts[sup] == reqSupDegree:
toKeep = result.getStudents(
sup) #Get the students we want to keep
toRemove = mergedGraph.getRemainingStu(
sup,
toKeep) #Get students we dont want to keep
#Remove those students (edges)
for stu in toRemove:
mergedGraph.removeEdge(sup, stu)
#If we can lock any further, then we break the loop
if len(prev) != len(lockedVertices):
prev = set(list(lockedVertices))
else:
toContinue = True
break
#Allocate remaining students to supervisors that don't meet the required degree
if toContinue:
availableStudents = allStudents.difference(lockedVertices)
for sup in supEdges:
reqDegree = structure[sup]
supDegree = counts[sup]
supNeeds = reqDegree - supDegree
if supDegree != reqDegree:
toAdd = random.sample(availableStudents, supNeeds)
for stu in toAdd:
result.addEdge(sup, stu)
lockedVertices.add(stu)
counts[sup] += supNeeds
availableStudents.remove(stu)
return Solution(result)
def test_case4(self):
"""Testing the remove edge function in an empty graph"""
graph = BipartiteGraph()
self.assertRaises(KeyError,
lambda: graph.removeEdge("supervisor1", "student1"))
def test_case2(self):
"""Testing addEdge function in a graph with existing nodes and edges"""
graph = BipartiteGraph()
graph.addEdge("supervisor1", "student1")
graph.addEdge("supervisor2", "student4")
graph.addEdge("supervisor3", "student3")
val1 = graph.getSupervisorDegree("supervisor1")
graph.addEdge("supervisor1", "student2")
curr = graph.getSupervisorDegree("supervisor1")
val2 = graph.getSupervisors("student2")
expected2 = ["supervisor1"]
self.assertEqual((curr - 1, expected2), (val1, val2))