def evalFunc_FBasicMin(individual, Original, weights, constraints=[]):
userSize = Original.shape[0]
permissionSize = Original.shape[1]
if (constraints and
not feasible(individual, userSize, permissionSize, constraints)):
fitness = len(weights)
else:
numberOfRoles = len(individual[0])
array = decoder.resolveRoleModelChromosomeIntoBoolArray(
individual[0], userSize, permissionSize)
conf, accs = matrixOps.compareMatrices(array, Original)
w1 = weights[0]
w2 = weights[1]
w3 = weights[2]
numberOfRoles_normalized = utils.normalization(
numberOfRoles, 1, min(userSize, permissionSize))
accs_normalized = utils.normalization(accs, 0, Original.sum())
conf_normalized = utils.normalization(conf, 0,
Original.size - Original.sum())
fitness = w1 * numberOfRoles_normalized + w2 * conf_normalized + w3 * accs_normalized
return fitness,
def evalFunc_WSC(individual, Original, weights, constraints=[]):
userSize = Original.shape[0]
permissionSize = Original.shape[1]
if (constraints and
not feasible(individual, userSize, permissionSize, constraints)):
fitness = len(weights)
else:
numberOfRoles = len(individual[0])
array = decoder.resolveRoleModelChromosomeIntoBoolArray(
individual[0], userSize, permissionSize)
conf, accs = matrixOps.compareMatrices(array, Original)
numberOfUR = statistics.URCnt(individual[0])
numberOfRP = statistics.RPCnt(individual[0])
w1 = weights[0]
w2 = weights[1]
w3 = weights[2]
w4 = weights[3]
worstCase_numberOfRoles = min(userSize, permissionSize)
numberOfRoles_normalized = utils.normalization(
numberOfRoles, 1, worstCase_numberOfRoles)
accs_normalized = utils.normalization(accs, 0, Original.sum())
numberOfUR_normalized = utils.normalization(
numberOfUR, userSize, userSize * worstCase_numberOfRoles)
numberOfRP_normalized = utils.normalization(
numberOfRP, permissionSize,
permissionSize * worstCase_numberOfRoles)
fitness = (w1 * numberOfRoles_normalized + w2 * numberOfUR_normalized +
w3 * numberOfRP_normalized + w4 * accs_normalized)
return fitness,
def evalFunc_WSC_Star_RoleDis(individual,
Original,
weights,
population,
constraints=[]):
userSize = Original.shape[0]
permissionSize = Original.shape[1]
if (constraints and
not feasible(individual, userSize, permissionSize, constraints)):
fitness = len(weights)
else:
numberOfRoles = len(individual[0])
array = decoder.resolveRoleModelChromosomeIntoBoolArray(
individual[0], userSize, permissionSize)
conf, accs = matrixOps.compareMatrices(array, Original)
numberOfUR = statistics.URCnt(individual[0])
numberOfRP = statistics.RPCnt(individual[0])
count = 0
for rm in population:
count += len(rm[0])
numberOfRolesInPop = count / len(population)
roleDis = abs(numberOfRolesInPop - numberOfRoles)
if (roleDis < 3):
roleDis = 0
w1 = weights[0]
w2 = weights[1]
w3 = weights[2]
w4 = weights[3]
w5 = weights[4]
w6 = weights[5]
worstCase_numberOfRoles = min(userSize, permissionSize)
numberOfRoles_normalized = utils.normalization(
numberOfRoles, 1, worstCase_numberOfRoles)
accs_normalized = utils.normalization(accs, 0, Original.sum())
conf_normalized = utils.normalization(conf, 0,
Original.size - Original.sum())
numberOfUR_normalized = utils.normalization(
numberOfUR, userSize, userSize * worstCase_numberOfRoles)
numberOfRP_normalized = utils.normalization(
numberOfRP, permissionSize,
permissionSize * worstCase_numberOfRoles)
roleDis_normalized = utils.normalization(
roleDis, 0,
max(numberOfRolesInPop, permissionSize - numberOfRolesInPop,
userSize - numberOfRolesInPop))
fitness = (w1 * numberOfRoles_normalized + w2 * numberOfUR_normalized +
w3 * numberOfRP_normalized + w4 * accs_normalized +
w5 * conf_normalized + w6 * roleDis_normalized)
return fitness,
def evalFunc_Int_AssignmentCnt(individual,
Original,
userAttributeValues,
constraints=[]):
userSize = Original.shape[0]
permissionSize = Original.shape[1]
if (constraints and
not feasible(individual, userSize, permissionSize, constraints)):
worstCase_interp = 1
fitness = worstCase_interp
else:
AssignmentCnt = statistics.URCnt(individual[0]) + statistics.RPCnt(
individual[0])
AssignmentCnt_normalized = utils.normalization(
AssignmentCnt, userSize + permissionSize,
userSize * permissionSize)
interp = statistics.Interp(individual[0], userAttributeValues)
fitness = AssignmentCnt_normalized - interp + 1
return fitness,