num_samples = 200
num_times = 5
# num_gens = 901
# treefile = sps.run_slim(script = script,
# seed = 23,
# SIGMA = 3.0,
# W = 50.0,
# K = 5.0,
# NUMGENS = num_gens,
# BURNIN=1)
# outbase = ".".join(treefile.split(".")[:-1])
# num_samples = 20
# num_times = 3
ts = sps.SpatialSlimTreeSequence(pyslim.load(treefile), dim=2)
for time in np.floor(np.linspace(0, num_gens - 1, num_times)):
datafile = outbase + ".{}.admixture.txt".format(time)
if os.path.isfile(datafile):
print(datafile, "already exists.")
data = np.loadtxt(datafile)
samples = np.array([np.int(u) for u in data[:, 0]])
admixture = data[:, 1:]
else:
print(datafile, "does not exist, computing.")
samples, admixture = compute_admixture(ts, time, num_gens - 1,
num_samples)
data = np.column_stack([samples, admixture])
np.savetxt(datafile, data)
# for script in ("valleys.slim", "flat_map.slim"):
## pass in script on command-line
num_gens = 1
treefile = sps.run_slim(script=script,
seed=23,
SIGMA=0.4,
W=50.0,
NUMGENS=num_gens,
BURNIN=10000)
outbase = ".".join(treefile.split(".")[:-1])
recapfile = outbase + ".recap.trees"
if os.path.isfile(recapfile):
ts = sps.SpatialSlimTreeSequence(pyslim.load(recapfile), dim=2)
else:
ts = pyslim.load(treefile)
ts = sps.SpatialSlimTreeSequence(ts.recapitate(Ne=1e3,
recombination_rate=1e-9),
dim=2)
ts.dump(recapfile)
num_targets = 4
num_indivs = 200
locs = ts.individual_locations()
xmax = max(locs[:, 0])
ymax = max(locs[:, 1])
alive = ts.individuals_alive(0)
left_third = np.logical_and(alive, locs[:, 0] < xmax / 3)
right_third = np.logical_and(alive, locs[:, 0] > 2 * xmax / 3)
