def __init__(self, paths):
self.distanceMatrix = None
self.distanceDict = dict()
self.paths = sorted(paths, key=lambda x: x.label)
self.pathNames = sorted(list(map(lambda x: x.label, paths)))
self.allCourseNames = abstract.extractAllCourseNames(paths)
np.set_printoptions(suppress=True)
def calculatePathDistance(self, pathA, pathB):
coursesA = abstract.extractAllCourseNames([pathA])
coursesB = abstract.extractAllCourseNames([pathB])
courseNames = abstract.extractAllCourseNames([pathA, pathB])
semesterA, semesterB = abstract.createExtendedLookUpList(
pathA, pathB, courseNames)
distanceA = self.generateDistanceMatrix(semesterA)
distanceB = self.generateDistanceMatrix(semesterB)
distanceA = self.setNonOverlap(distanceA, courseNames, coursesA, 0)
distanceB = self.setNonOverlap(distanceB, courseNames, coursesB, 1)
distanceDiff = np.absolute(np.sign(np.subtract(distanceA, distanceB)))
n, m = distanceDiff.shape
size = n - 1
tri = np.fliplr(distanceDiff)[np.triu_indices(size)]
distance = sum(tri) / len(tri)
return distance
def calculatePathDistance(self, pathA, pathB):
coursesA = abstract.extractAllCourseNames([pathA])
coursesB = abstract.extractAllCourseNames([pathB])
coursesCombined = np.intersect1d(coursesA, coursesB)
courseNames = abstract.extractAllCourseNames([pathA, pathB])
semesterA, semesterB = abstract.createExtendedLookUpList(
pathA, pathB, courseNames)
distanceA = self.generateDistanceMatrix(semesterA)
distanceB = self.generateDistanceMatrix(semesterB)
#distanceA = self.setNonOverlap(distanceA, courseNames, coursesA, 0)
#distanceB = self.setNonOverlap(distanceB, courseNames, coursesB, 1)
distanceA = self.setNonOverlap(distanceA, courseNames, coursesA, 0)
distanceB = self.setNonOverlap(distanceB, courseNames, coursesB, 1)
distanceDiff = np.absolute(np.sign(np.subtract(distanceA, distanceB)))
tri = distanceDiff[np.triu_indices_from(distanceDiff, 1)]
distance = sum(tri) / len(tri)
return distance
def createSemesterWords(self, pathA, pathB):
courseNames = abstract.extractAllCourseNames([pathA, pathB])
idDict = dict()
for i, n in enumerate(courseNames):
idDict[n] = i
semesterA, semesterB = [], []
for sem in pathA.semester:
tempArr = []
for c in sem:
tempArr.append(chr(idDict[c.name]))
tempArr.sort()
semesterA.append(''.join(tempArr))
for sem in pathB.semester:
tempArr = []
for c in sem:
tempArr.append(chr(idDict[c.name]))
tempArr.sort()
semesterB.append(''.join(tempArr))
return semesterA, semesterB
def calculatePathDistance(self, pathA, pathB):
courseNames = abstract.extractAllCourseNames([pathA, pathB])
idDict = dict()
for i, n in enumerate(courseNames):
idDict[n] = i
semesterA, semesterB = [], []
for sem in pathA.semester:
tempArr = []
for c in sem:
tempArr.append(chr(idDict[c.name]))
tempArr.sort()
semesterA.append(''.join(tempArr))
for sem in pathB.semester:
tempArr = []
for c in sem:
tempArr.append(chr(idDict[c.name]))
tempArr.sort()
semesterB.append(''.join(tempArr))
strSemesterA = ''.join(semesterA)
strSemesterB = ''.join(semesterB)
distance = normalized_damerau_levenshtein_distance(
strSemesterA, strSemesterB)
return distance
def calculatePathDistance(self, pathA, pathB):
courseNames = abstract.extractAllCourseNames([pathA, pathB])
semesterA, semesterB = abstract.createExtendedLookUpList(
pathA, pathB, courseNames)
distance = energy_distance(semesterA, semesterB)
return distance
