parser.add_option("--snapshots", dest="snapshots",default=None,help="A comma separated list of generations at which the frequency of the SNPs should be recorded")
(options, args) = parser.parse_args()
repsim = int(options.repsim)
twone = int(options.ne)*2
r = float(options.r)
p1 = float(options.p1)
p2 = float(options.p2)
rsquared = float(options.rsquared)
snapshots=set(map(int, options.snapshots.split(",")))
maxgen = max(snapshots)
selectiondictionary=FitnessFunctionParser.get_fitnessFunctionDictionary(options.selection)
print "# snp_id\tgeneration\tfrequency\treplicate"
for i in range(0,repsim):
pop=PopGenerator.ini_ld(twone,p1,p2,rsquared)
print "{0}\t{1}\t{2}\t{3}".format("A",0,pop.get_frequencyA() ,i+1)
print "{0}\t{1}\t{2}\t{3}".format("B",0,pop.get_frequencyB() ,i+1)
counter=0
ff=None
while(True):
if (counter+1) in selectiondictionary:
ff=selectiondictionary[(counter+1)]
pop=pop.getNextGeneration(twone,ff,r)
counter+=1
if counter in snapshots:
print "{0}\t{1}\t{2}\t{3}".format("A",counter,pop.get_frequencyA() ,i+1)
print "{0}\t{1}\t{2}\t{3}".format("B",counter,pop.get_frequencyB() ,i+1)
if counter>=maxgen:
break
p2 = float(options.p2)
maxgen = float(options.maxgen)
assert p1 + p2 <= 1.0
ff = FitnessFunctionNormal(s1, h1, s2, h2)
for i in range(0, repsim):
sA = "S"
sB = "S"
sab = "S"
genA = int(maxgen)
genB = int(maxgen)
genab = int(maxgen)
pop = PopGenerator.ini_competition(twone, p1, p2)
counter = 0
while not pop.is_fixed():
pop = pop.getNextGeneration(twone, ff, r)
counter += 1
if sA == "S" and pop.is_fixedA():
sA = pop.status(pop.countA())
genA = counter
if sB == "S" and pop.is_fixedB():
sB = pop.status(pop.countB())
genB = counter
if sab == "S" and pop.is_fixedab():
sab = pop.status(pop.countab())
genab = counter
if counter >= maxgen:
p1 = float(options.p1)
p2 = float(options.p2)
maxgen = float(options.maxgen)
assert (p1 + p2 <= 1.0)
ff = FitnessFunctionNormal(s1, h1, s2, h2)
for i in range(0, repsim):
sA = "S"
sB = "S"
sab = "S"
genA = int(maxgen)
genB = int(maxgen)
genab = int(maxgen)
pop = PopGenerator.ini_competition(twone, p1, p2)
counter = 0
while (not pop.is_fixed()):
pop = pop.getNextGeneration(twone, ff, r)
counter += 1
if (sA == "S" and pop.is_fixedA()):
sA = pop.status(pop.countA())
genA = counter
if (sB == "S" and pop.is_fixedB()):
sB = pop.status(pop.countB())
genB = counter
if (sab == "S" and pop.is_fixedab()):
sab = pop.status(pop.countab())
genab = counter
if counter >= maxgen:
r = float(options.r)
h1 = float(options.het1)
h2 = float(options.het2)
p = float(options.p)
maxgen = float(options.maxgen)
output = options.output
ff=FitnessFunctionNormal(s1,h1,s2,h2)
trajectories_selected1=[]
trajectories_selected2=[]
trajectories_AB=[]
ld_decay=[]
for i in range(0,repsim):
pop=PopGenerator.ini_complete_linkage(twone,p)
freqsA=[]
freqsB=[]
freqsAB=[]
ld=[]
freqsA.append(pop.get_frequencyA())
freqsB.append(pop.get_frequencyB())
freqsAB.append(pop.get_frequencyAB())
ld.append(pop.get_rsquared())
counter=0
while(not pop.is_fixed()):
pop=pop.getNextGeneration(twone,ff,r)
freqsA.append(pop.get_frequencyA())
freqsB.append(pop.get_frequencyB())
freqsAB.append(pop.get_frequencyAB())
ld.append(pop.get_rsquared())
r = float(options.r)
h1 = float(options.het1)
h2 = float(options.het2)
p = float(options.p)
maxgen = float(options.maxgen)
output = options.output
ff = FitnessFunctionNormal(s1, h1, s2, h2)
trajectories_selected1 = []
trajectories_selected2 = []
trajectories_AB = []
ld_decay = []
for i in range(0, repsim):
pop = PopGenerator.ini_complete_linkage(twone, p)
freqsA = []
freqsB = []
freqsAB = []
ld = []
freqsA.append(pop.get_frequencyA())
freqsB.append(pop.get_frequencyB())
freqsAB.append(pop.get_frequencyAB())
ld.append(pop.get_rsquared())
counter = 0
while (not pop.is_fixed()):
pop = pop.getNextGeneration(twone, ff, r)
freqsA.append(pop.get_frequencyA())
freqsB.append(pop.get_frequencyB())
freqsAB.append(pop.get_frequencyAB())
ld.append(pop.get_rsquared())
r = float(options.r)
h1 = float(options.het1)
h2 = float(options.het2)
p1 = float(options.p1)
p2 = float(options.p2)
snapshots=set(map(int, options.snapshots.split(",")))
maxgen = max(snapshots)
assert(p1+p2<=1.0)
ff=FitnessFunctionNormal(s1,h1,s2,h2)
print "# snp_id\tgeneration\tfrequency\treplicate"
for i in range(0,repsim):
pop=PopGenerator.ini_subfrequency(twone,p1,p2)
print "{0}\t{1}\t{2}\t{3}".format("A",0,pop.get_frequencyA() ,i+1)
print "{0}\t{1}\t{2}\t{3}".format("B",0,pop.get_frequencyB() ,i+1)
counter=0
while(True):
pop=pop.getNextGeneration(twone,ff,r)
counter+=1
if counter in snapshots:
print "{0}\t{1}\t{2}\t{3}".format("A",counter,pop.get_frequencyA() ,i+1)
print "{0}\t{1}\t{2}\t{3}".format("B",counter,pop.get_frequencyB() ,i+1)
if counter>=maxgen:
break
s1 = float(options.s1)
s2 = float(options.s2)
r = float(options.r)
h1 = float(options.het1)
h2 = float(options.het2)
p1 = float(options.p1)
p2 = float(options.p2)
snapshots = set(map(int, options.snapshots.split(",")))
maxgen = max(snapshots)
assert (p1 + p2 <= 1.0)
ff = FitnessFunctionNormal(s1, h1, s2, h2)
print "# snp_id\tgeneration\tfrequency\treplicate"
for i in range(0, repsim):
pop = PopGenerator.ini_subfrequency(twone, p1, p2)
print "{0}\t{1}\t{2}\t{3}".format("A", 0, pop.get_frequencyA(), i + 1)
print "{0}\t{1}\t{2}\t{3}".format("B", 0, pop.get_frequencyB(), i + 1)
counter = 0
while (True):
pop = pop.getNextGeneration(twone, ff, r)
counter += 1
if counter in snapshots:
print "{0}\t{1}\t{2}\t{3}".format("A", counter,
pop.get_frequencyA(), i + 1)
print "{0}\t{1}\t{2}\t{3}".format("B", counter,
pop.get_frequencyB(), i + 1)
if counter >= maxgen:
break