for smoothv, weightv in weights:
d3p += smooth(raw, int(smoothv)) * weightv
raw = d3p
else:
#print(type(weights),np.nanmean(raw))
if weights == "submed":
raw -= np.nanmedian(raw)
d3p = raw
#print(weights, "here")
if args.nan0 and "Exp" not in signal:
d3p[np.isnan(d3p)] = 0
btosee.append([x, d3p, signal])
if sup_sig != None:
btosee.append(sup_sig)
sup_sig = None
ToSee.append(btosee)
"""
for signal in args.filename:
print(signal)
x, d3p = replication_data(cell, "", chromosome=ch,
start=start, end=end,
resolution=resolution, raw=False,filename=signal)
ToSee += [[[x,d3p, signal]]]
"""
plotly_blocks(x, ToSee, name=args.name, default="lines")
weight_t = np.sum(x0[tstart - start:tend - start])
x0[tstart - start:tend -
start] = weight_t * np.array(opti.best) / np.sum(opti.best)
end_error, gMRTp, gMRT, gRFD, gRFDs, wRFD = run(x0, ndiff, start, end)
print("New Global error", initerror)
if cell != "Cerevisae":
ToSee = [[[1 - gMRTpi, "MRTi"], [1 - gMRTp, "MRT"],
[
x[::10 // resolution],
1 - gMRT[:len(x[::10 // resolution])], "MRTexp"
]],
[[gRFD, "RFDExp"], [gRFDsi, "RFDsimi_init"],
[gRFDs, "RFDsim_end"]]]
else:
ToSee = [[[1 - gMRTpi, "MRTi"], [1 - gMRTp, "MRT"],
[x, 1 - gMRT, "MRTexp"]],
[[gRFD, "RFDExp"], [gRFDsi, "RFDsimi_init"],
[gRFDs, "RFDsim_end"]]]
ToSee += [[[init, "init"], [x0, "Optimised"]],
[[smooth(np.abs(gRFD - gRFDs), 250), "dsm"]]]
plotly_blocks(x, ToSee, name=args.name + "global_%i" % i, default="lines")
pd.DataFrame({
"signalValue": x0,
"chromStart": x * 1000,
"chromEnd": x * 1000,
"chrom": ["chr%i" % ch] * len(x)
}).to_csv(args.name + "optimised_signal.csv", index=False, sep="\t")
print(initerrorg, end_error)
# print(mask_RFD)
if args.input:
ToSee += [[[d3ps, "initiation"]]]
if "Yeast" in cell:
_, tere = replication_data(cell,
"ter",
chromosome=ch,
start=start,
end=end,
resolution=1,
raw=False)
#print(tere)
ToSee += [[[tere * 20, "TerExp"], [Pt, "ProbaTer"]]]
ToSee += [[[stallp, "stalling"]]]
if not args.only_one or (args.only_one and ch == 1):
plotly_blocks(x, ToSee, name=name_w + ".html", default="lines")
print(len(GData), len(d3p))
GData["signal"] = d3p
GData.to_csv(args.name + "global_profiles.csv",
index=False,
float_format="%.2f")
ldatg.to_csv(args.name + "global_scores.csv", index=False)
pRFD = stats.pearsonr(np.concatenate(gRFD), np.concatenate(gRFDe)),
sRFD = np.std(np.concatenate(gRFD) - np.concatenate(gRFDe))
pMRT = stats.pearsonr(np.concatenate(gMRT), np.concatenate(gMRTe)),
sMRT = np.std(np.concatenate(gMRT) - np.concatenate(gMRTe))
meanCodire = np.mean(codire)
print(args.name + "global_corre.csv")
initerror,MRTpi,MRTi,RFDi,RFDsi,wRFDt = evaluate(x0t,score=False)
print("Initial local error",initerror)
opti = PSO(evaluate,bounds=[0,1],x0=x0t,num_particles=15,maxiter=20,velocity_scale=100/len(x0t))
end_error,MRTp,MRT,RFD,RFDs,wRFDt = evaluate(opti.best,score=False)
#print("End error",end_error)
if cell != "Cerevisae":
ToSee = [[[1-MRTpi, "MRTi"],[1-MRTp, "MRT"], [x[::10//resolution], 1 - MRT[:len(x[::10//resolution])], "MRTexp"]],
[[RFD, "RFDExp"], [RFDsi, "RFDsimi_init"],[RFDs, "RFDsim_end"]]]
else:
ToSee = [[[1-MRTpi, "MRTi"],[1-MRTp, "MRT"], [x[tstart:tend], 1 - MRT, "MRTexp"]],
[[RFD, "RFDExp"], [RFDsi, "RFDsimi_init"],[RFDs, "RFDsim_end"],[RFDs+np.mean(left+right,axis=0),"Corrected2"],[gRFDsi[int((tstart-start)/res):int((tend-start)/res)]]]]
ToSee += [[[initt,"init"],[opti.best,"Optimised"]],[[np.mean(left,axis=0)],[np.mean(right,axis=0)]]]
plotly_blocks(x[tstart:tend],ToSee, name=args.name+"local_%i" % i, default="lines")
#Print reconneect:
exclude = int(len(x0t) * 0.1)
weight_t = np.sum(x0[tstart-start:tend-start][exclude:-exclude])
x0[tstart-start:tend-start][exclude:-exclude] = weight_t * np.array(opti.best)[exclude:-exclude] / np.sum(opti.best[exclude:-exclude])
end_error,gMRTp,gMRT,gRFD,gRFDs,wRFD = run(x0,ndiff,start,end)
print("New Global error",initerror)
if cell != "Cerevisae":
ToSee = [[[1-gMRTpi, "MRTi"],[1-gMRTp, "MRT"], [x[::10//resolution], 1 - gMRT[:len(x[::10//resolution])], "MRTexp"]],
[[gRFD, "RFDExp"], [gRFDsi, "RFDsimi_init"],[gRFDs, "RFDsim_end"]]]
else:
ToSee = [[[1-gMRTpi, "MRTi"],[1-gMRTp, "MRT"], [x, 1 - gMRT, "MRTexp"]],