def fitLag(linfile,
linfchain,
conthpd,
names=None,
lagrange=[50, 300],
lagbinsize=1,
threads=1,
set_plot=False,
nwalkers=100,
nburn=100,
nchain=100,
mode="test"):
""" fit the Rmap model.
"""
if mode == "run":
linfile = ".".join([linfile, "myrun"])
zydata = get_data(linfile, names=names)
rmap = Rmap_Model(zydata)
if mode == "test":
if zydata.nlc == 2:
print(rmap([np.log(sigma), np.log(tau), lagy, widy, scaley]))
elif zydata.nlc == 3:
print(
rmap([
np.log(sigma),
np.log(tau), lagy, widy, scaley, lagz, widz, scalez
]))
return (None)
elif mode == "show":
rmap.load_chain(linfchain, set_verbose=False)
elif mode == "run":
laglimit = [
[0.0, tau],
] * (zydata.nlc - 1)
print(laglimit)
# laglimit = "baseline"
linfchain = ".".join([linfchain, "myrun"])
rmap.do_mcmc(conthpd=conthpd,
lagtobaseline=0.5,
laglimit=laglimit,
nwalkers=nwalkers,
nburn=nburn,
nchain=nchain,
fburn=None,
fchain=linfchain,
threads=threads)
if set_plot:
rmap.break_chain([
lagrange,
] * (zydata.nlc - 1))
rmap.get_hpd()
if zydata.nlc == 2:
figout = "mcmc1"
else:
figout = "mcmc2"
rmap.show_hist(bins=100,
lagbinsize=lagbinsize,
figout=figout,
figext=figext)
return (rmap.hpd)
def fitLag(linfile, linfchain, conthpd, names=None, lagrange=[50, 300], lagbinsize=1, threads=1, set_plot=False, nwalkers=100, nburn=50, nchain=50, mode="test") :
""" fit the Rmap model.
"""
if mode == "run" :
linfile = ".".join([linfile, "myrun"])
zydata = get_data(linfile, names=names)
rmap = Rmap_Model(zydata)
if mode == "test" :
if zydata.nlc == 2 :
print(rmap([np.log(2.), np.log(100), lagy, widy, scaley ]))
elif zydata.nlc == 3 :
print(rmap([np.log(2.), np.log(100), lagy, widy, scaley, lagz, widz, scalez]))
return(None)
elif mode == "show" :
rmap.load_chain(linfchain, set_verbose=False)
elif mode == "run" :
laglimit = [[0.0, 400.0],]*(zydata.nlc-1)
print(laglimit)
# laglimit = "baseline"
linfchain = ".".join([linfchain, "myrun"])
rmap.do_mcmc(conthpd=conthpd, lagtobaseline=0.5, laglimit=laglimit,
nwalkers=nwalkers, nburn=nburn, nchain=nchain,
fburn=None, fchain=linfchain, threads=threads)
if set_plot :
rmap.break_chain([lagrange,]*(zydata.nlc-1))
rmap.get_hpd()
if zydata.nlc == 2 :
figout = "mcmc1"
else :
figout = "mcmc2"
rmap.show_hist(bins=100, lagbinsize=lagbinsize, figout=figout, figext=figext)
return(rmap.hpd)
def rm_single(rmid, nwalker, nchain, nburn, min_lag, max_lag, fig_out):
# Input and output data position and name
file_con = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/cont.txt"
file_hbeta = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/Hbetab.txt"
lc_plot = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/lightcurve"
data_out = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/cont-hbeta.txt"
last_mcmc = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/last_mcmc"
# Fit continuum
c = get_data([file_con])
cmod = Cont_Model(c)
cmod.do_mcmc(threads=100, nwalkers=nwalker, nchain=nchain, nburn=nburn)
# Do mcmc
cy = get_data([file_con, file_hbeta], names=["Continuum", "Hbeta"])
cy.plot(figout=lc_plot, figext="png")
cymod = Rmap_Model(cy)
cymod.do_mcmc(conthpd=cmod.hpd,
threads=100,
fchain=data_out,
nwalkers=nwalker,
nchain=2.0 * nchain,
nburn=2.0 * nburn,
laglimit=[[min_lag, max_lag]])
# Output mcmc result
cymod.show_hist(figout=fig_out, figext="png")
cypred = cymod.do_pred()
cypred.plot(set_pred=True, obs=cy, figout=last_mcmc, figext="png")
return [cymod.hpd[0][2], cymod.hpd[1][2], cymod.hpd[2][2]]
def rm_single(rmid, nwalker, nchain, nburn, min_lag, max_lag, fig_out):
# Input and output data position and name
file_con = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/cont.txt"
file_hbeta = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/Hbetab.txt"
lc_plot = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/lightcurve"
data_out = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/cont-hbeta.txt"
last_mcmc = Location.project_loca + "result/light_curve/" + str(rmid) + \
"/last_mcmc"
# Fit continuum
c = get_data([file_con])
cmod = Cont_Model(c)
cmod.do_mcmc(threads=100, nwalkers=nwalker, nchain=nchain, nburn=nburn)
# Do mcmc
cy = get_data([file_con, file_hbeta], names=["Continuum", "Hbeta"])
cy.plot(figout=lc_plot, figext="png")
cymod = Rmap_Model(cy)
cymod.do_mcmc(conthpd=cmod.hpd, threads=100, fchain=data_out,
nwalkers=nwalker, nchain=2.0 * nchain, nburn=2.0 * nburn,
laglimit=[[min_lag, max_lag]])
# Output mcmc result
cymod.show_hist(figout=fig_out, figext="png")
cypred = cymod.do_pred()
cypred.plot(set_pred=True, obs=cy, figout=last_mcmc, figext="png")
return [cymod.hpd[0][2], cymod.hpd[1][2], cymod.hpd[2][2]]
x = cont_best.jlist[:]
y = cont_best.mlist[:] + cont_best.blist[:]
ey = cont_best.elist[:]
plt.plot(x[0], y[0] + javdata_con.cont_mean)
plt.fill_between(x[0],
y[0] - ey[0] + javdata_con.cont_mean,
y[0] + ey[0] + javdata_con.cont_mean,
where=None,
color='grey')
x = javdata_con.jlist[:]
y = javdata_con.mlist[:] + javdata_con.blist[:]
ey = javdata_con.elist[:]
plt.errorbar(x[0],
y[0] + javdata_con.cont_mean,
yerr=ey[0],
ls='none',
marker='o')
plt.show()
rmap1 = Rmap_Model(javdata_rm)
#rmap1.do_mcmc(conthpd=conthpd, fchain="mychain1.dat", laglimit=[[0, 10],], nwalkers=100, nburn=200, nchain=1000)
rmap1.load_chain("mychain1.dat")
rmap1.show_hist()
rmap1.get_hpd()
rmap1hpd = rmap1.hpd
par_best = rmap1hpd[1, :]
print(par_best)
javdata_best = rmap1.do_pred(par_best)
javdata_best.plot(set_pred=True, obs=javdata_rm)
from javelin.zylc import get_data
from javelin.lcmodel import Cont_Model
from javelin.lcmodel import Rmap_Model
import numpy as np
c = get_data(["dat/continuum.dat"])
cmod = Cont_Model(c)
cmod.do_mcmc(nwalkers=100, nburn=100, nchain=100, threads=1)
cmod.show_hist()
print cmod.hpd
javdata4 = get_data(["dat/continuum.dat", "dat/yelm.dat"],
names=["Continuum", "Yelm"])
rmap2 = Rmap_Model(javdata4)
rmap2.do_mcmc(conthpd=cmod.hpd,
nwalkers=100,
nburn=100,
nchain=100,
threads=1,
laglimit=[
[10, 200],
],
fixed=[1, 0, 1, 0, 1],
p_fix=[np.log(0.1), np.log(400), 10, 2.0, 5.0])
rmap2.show_hist()
print rmap2.hpd
