def homologousonePointcrossover(eaObj, inParent):
similarpoints = [] # Creating a list to store points with similar angles found
randParent = Pose()
# Searching for similar angles
while (len(similarpoints) == 0):
randParent.assign(randomParent(eaObj, inParent))
for i in range(1, inParent.pose.size()):
if((inParent.pose.phi(i) == randParent.phi(i)) and
(inParent.pose.psi(i) == randParent.psi(i)) and
(inParent.pose.omega(i) == randParent.omega(i))):
similarpoints.append(i)
child = Pose()
child.assign(inParent.pose)
# Now we select a random point from the list of points that had similar angles as our crossOverPoint
crossOverPoint = random.choice(similarpoints)
# We should switch the values from the parents
for residue in range(1, crossOverPoint):
Pose.replace_residue(
child, residue, Pose.residue(randParent, residue), True)
inParent.pose.assign(child)
def twoPointcrossover(eaObj, inParent):
randParent = Pose()
randParent.assign(randomParent(eaObj, inParent))
crossOverPoint1 = randint(1, inParent.pose.size())
crossOverPoint2 = randint(1, inParent.pose.size())
# the first crossover point should be smaller than the second one.
while(crossOverPoint1 >= crossOverPoint2):
crossOverPoint1 = randint(1, inParent.pose.size())
crossOverPoint2 = randint(1, inParent.pose.size())
# The crossover'd child
child = Pose()
child.assign(inParent.pose)
# We switch the values between the two crossover points with values from the random parent
for residue in range(crossOverPoint1, crossOverPoint2):
Pose.replace_residue(
child, residue, Pose.residue(randParent, residue), True)
inParent.pose.assign(child)
def onePointcrossover(eaObj, inParent):
# Get random parent from population, ensure that we didn't get the same one.
randParent = Pose()
randParent.assign(randomParent(eaObj, inParent))
# Pick a random point in the sequence of the strand of amino acids to crossover
crossOverPoint = randint(1, inParent.pose.size())
# Create a new pose to be crossover'd by the two parents
child = Pose()
child.assign(inParent.pose)
"""
We iterate through the size of the crossover point (since we already have one of the parents copied)
one by one until the offspring has reached it's crossoverpoint and we should have a fully newborn
offspring by the end of the loop.
"""
for residue in range(1, crossOverPoint):
Pose.replace_residue(
child, residue, Pose.residue(randParent, residue), True)
inParent.pose.assign(child)
