else:
cascade = args.cascade
if not args.experimental:
# Independent simulation for each chromosome
from repli1d.fast_sim import get_fast_MRT_RFDs
for (start, end, ch, ndiff), [x, d3p, stallp] in zip(list_task, d3pl):
# simulate
lres.append(
get_fast_MRT_RFDs(
nsim,
d3p + np.ones_like(d3p) * np.sum(d3p) * noise / len(d3p),
ndiff,
kon=kon,
fork_speed=fork_speed,
dori=args.dori * 5 / resolution,
single_mol_exp=args.single,
continuous=args.continuous,
cascade=cascade))
#print("check", np.sum(d3p), np.sum(np.ones_like(d3p)*np.sum(d3p)*0.1/len(d3p)))
print("End Simeeeeuuuuuuuuuuuuuuuuuuuu")
else:
from repli1d.fast_sim_break import get_fast_MRT_RFDs
#print(d3p)
if args.cutholes is None:
bigch = np.concatenate([d3p for x, d3p, stallp in d3pl])
def run(profile, tndiff, tstart, tend, actualProfile=None):
res = args.resolution
if actualProfile is not None:
tmpProfile = actualProfile.copy()
#print(tmpProfile.shape,np.array(profile).shape,start,tstart,tend,tmpProfile[tstart-start:tend-start].shape,tstart-start,tend-start)
weight_t = np.sum(tmpProfile[tstart - start:tend - start])
tmpProfile[tstart - start:tend -
start] = weight_t * np.array(profile) / np.sum(profile)
else:
tmpProfile = profile
MRTp, MRTs, RFDs, Rept_time, single_mol_exp, pos_time_activated_ori, It, wRFD = get_fast_MRT_RFDs(
nsim,
tmpProfile,
tndiff,
kon=kon,
fork_speed=fork_speed,
dori=20 * 5 / resolution,
single_mol_exp=False,
continuous=args.continuous,
wholeRFD=True)
#print("check", np.sum(d3p), np.sum(np.ones_like(d3p)*np.sum(d3p)*0.1/len(d3p)))
#print("Start, end",tstart,tend,tndiff)
# Compare to exp data
"""
MRTpearson, MRTstd, MRT = compare(
MRTp[::10//resolution], "MRT", cell, res=10, ch=ch, start=start, end=end, return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs, "OKSeq", cell, res=resolution, ch=ch,
start=start, end=end, return_exp=True, rescale=1/resolution)
"""
if cell != "Cerevisae":
if actualProfile is not None:
MRTpearsonl, MRTstdl, MRTl = compare(
MRTp[int((tstart - start) / res):int((tend - start) /
res)][::10 // resolution],
"MRT",
cell,
res=10,
ch=ch,
start=tstart,
end=tend,
return_exp=True)
RFDpearsonl, RFDstdl, RFDl = compare(
RFDs[int((tstart - start) / res):int((tend - start) / res)],
"OKSeq",
cell,
res=resolution,
ch=ch,
start=tstart,
end=tend,
return_exp=True,
rescale=1 / resolution)
else:
RFDstdl = 0
MRTpearson, MRTstd, MRT = compare(MRTp[::10 // resolution],
"MRT",
cell,
res=10,
ch=ch,
start=start,
end=end,
return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs,
"OKSeq",
cell,
res=resolution,
ch=ch,
start=start,
end=end,
return_exp=True,
rescale=1 / resolution)
else:
if actualProfile is not None:
MRTpearsonl, MRTstdl, MRTl = compare(
MRTp[int((tstart - start) / res):int((tend - start) / res)],
"MRT",
cell,
res=1,
ch=ch,
start=tstart,
end=tend,
return_exp=True)
RFDpearsonl, RFDstdl, RFDl = compare(
RFDs[int((tstart - start) / res):int((tend - start) / res)],
"OKSeq",
cell,
res=1,
ch=ch,
start=tstart,
end=tend,
return_exp=True,
rescale=1,
nanpolate=True,
smoothf=2)
else:
RFDstdl = 0
MRTpearson, MRTstd, MRT = compare(MRTp,
"MRT",
cell,
res=1,
ch=ch,
start=start,
end=end,
return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs,
"OKSeq",
cell,
res=1,
ch=ch,
start=start,
end=end,
return_exp=True,
rescale=1,
nanpolate=True,
smoothf=2)
RFDs = smooth(RFDs, 2)
if args.RFDo:
print(RFDstd, RFDstdl)
return RFDstd + RFDstdl, MRTp, MRT, RFD, RFDs, wRFD
else:
return MRTstd + RFDstd, MRTp, MRT, RFD, RFDs, wRFD
def run(profile):
MRTp, MRTs, RFDs, Rept_time, single_mol_exp, pos_time_activated_ori, It = get_fast_MRT_RFDs(
nsim,
profile,
ndiff,
kon=kon,
fork_speed=fork_speed,
dori=20 * 5 / resolution,
single_mol_exp=False,
continuous=args.continuous)
#print("check", np.sum(d3p), np.sum(np.ones_like(d3p)*np.sum(d3p)*0.1/len(d3p)))
# Compare to exp data
"""
MRTpearson, MRTstd, MRT = compare(
MRTp[::10//resolution], "MRT", cell, res=10, ch=ch, start=start, end=end, return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs, "OKSeq", cell, res=resolution, ch=ch,
start=start, end=end, return_exp=True, rescale=1/resolution)
"""
if cell != "Cerevisae":
MRTpearson, MRTstd, MRT = compare(MRTp[::10 // resolution],
"MRT",
cell,
res=10,
ch=ch,
start=start,
end=end,
return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs,
"OKSeq",
cell,
res=resolution,
ch=ch,
start=start,
end=end,
return_exp=True,
rescale=1 / resolution)
else:
MRTpearson, MRTstd, MRT = compare(MRTp,
"MRT",
cell,
res=1,
ch=ch,
start=start,
end=end,
return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs,
"OKSeq",
cell,
res=1,
ch=ch,
start=start,
end=end,
return_exp=True,
rescale=1,
nanpolate=True,
smoothf=2)
if args.RFDo:
#print(RFDstd)
return RFDstd, MRTp, MRT, RFD, RFDs
else:
return MRTstd + RFDstd, MRTp, MRT, RFD, RFDs
start=start, end=end,
resolution=5, raw=False, oData=False,
bp=True, bpc=False)
if args.correct:
x, CNV = replication_data(cell, "CNV", chromosome=ch,
start=start, end=end,
resolution=5, raw=False)
CNV[CNV == 0] = 2
d3p /= CNV
d3p[np.isnan(d3p)] = 0
print("Simu")
sim = get_fast_MRT_RFDs(
nsim, d3p+np.ones_like(d3p)*np.sum(d3p)*random_activation/len(d3p), ndiff, kon=kon,
fork_speed=fork_speed, dori=dori)
with open(filename, "wb") as f:
pickle.dump(sim, f)
MRTp, MRTs, RFDs, Rep_Time, single_mol_exp, pos_time_activated_ori, It = sim
# Compare to exp data
MRTpearson, MRTstd, MRT = compare(
MRTp[::2], "MRT", compMRT, res=10, ch=ch, start=start, end=end, return_exp=True)
RFDpearson, RFDstd, RFD = compare(RFDs, "OKSeq", compRFD, res=5, ch=ch,
start=start, end=end, return_exp=True, rescale=1/5)
print(MRTpearson, MRTstd, RFDpearson, RFDstd)
M.append(mark)
D.append(ndiff)