def run_burnin(sampler,startPos,nSteps,storechain=False):
iStep = 0
bar = ProgressBar()
for pos, prob, state in sampler.sample(startPos,iterations=nSteps,storechain=storechain):
bar.render(int(100*iStep/nSteps),'running Burn In')
iStep += 1
return pos, prob, state
def run_ptmcmc_save(sampler, startPos, nSteps, file, **kwargs):
'''runs PT MCMC and saves zero temperature chain to file'''
if not os.path.exists(file):
f = open(file, "w")
f.close()
iStep = 0
bar = ProgressBar()
for pos, prob, like in sampler.sample(startPos,
iterations=nSteps,
storechain=True,
**kwargs):
bar.render(int(100 * iStep / nSteps), 'running MCMC')
iStep += 1
f = open(file, "a")
# pos is shape (ntemps, nwalkers, npars)
# prob is shape (ntemps, nwalkers)
# loop over all walkers for zero temp and append to file
zpos = pos[0, ...]
zprob = prob[0, ...]
for k in range(zpos.shape[0]):
thisPos = zpos[k]
thisProb = zprob[k]
f.write("{0:4d} {1:s} {2:f}\n".format(k,
" ".join(map(str, thisPos)),
thisProb))
f.close()
return sampler
def run_mcmc_save(sampler, startPos, nSteps, rState, file, **kwargs):
'''runs and MCMC chain with emcee, and saves steps to a file'''
#open chain save file
if file:
f = open(file, "w")
f.close()
iStep = 0
bar = ProgressBar()
for pos, prob, state in sampler.sample(startPos,
iterations=nSteps,
rstate0=rState,
storechain=True,
**kwargs):
if file:
f = open(file, "a")
bar.render(int(100 * iStep / nSteps), 'running MCMC')
iStep += 1
for k in range(pos.shape[0]):
# loop over all walkers and append to file
thisPos = pos[k]
thisProb = prob[k]
if file:
f.write("{0:4d} {1:s} {2:f}\n".format(
k, " ".join(map(str, thisPos)), thisProb))
if file:
f.close()
return sampler
def run_burnin(sampler, startPos, nSteps, storechain=False):
iStep = 0
bar = ProgressBar()
for pos, prob, state in sampler.sample(startPos,
iterations=nSteps,
storechain=storechain):
bar.render(int(100 * iStep / nSteps), 'running Burn In')
iStep += 1
return pos, prob, state
def run_mcmc_save(sampler,startPos,nSteps,rState,file,**kwargs):
'''runs and MCMC chain with emcee, and saves steps to a file'''
#open chain save file
if file:
f = open(file,"w")
f.close()
iStep = 0
bar = ProgressBar()
for pos, prob, state in sampler.sample(startPos,iterations=nSteps,rstate0=rState,storechain=True,**kwargs):
if file:
f = open(file,"a")
bar.render(int(100*iStep/nSteps),'running MCMC')
iStep += 1
for k in range(pos.shape[0]):
# loop over all walkers and append to file
thisPos = pos[k]
thisProb = prob[k]
if file:
f.write("{0:4d} {1:s} {2:f}\n".format(k," ".join(map(str,thisPos)),thisProb ))
if file:
f.close()
return sampler
def run_ptmcmc_save(sampler,startPos,nSteps,file,**kwargs):
'''runs PT MCMC and saves zero temperature chain to file'''
if not os.path.exists(file):
f = open(file,"w")
f.close()
iStep = 0
bar = ProgressBar()
for pos, prob, like in sampler.sample(startPos,iterations=nSteps,storechain=True,**kwargs):
bar.render(int(100*iStep/nSteps),'running MCMC')
iStep += 1
f = open(file,"a")
# pos is shape (ntemps, nwalkers, npars)
# prob is shape (ntemps, nwalkers)
# loop over all walkers for zero temp and append to file
zpos = pos[0,...]
zprob = prob[0,...]
for k in range(zpos.shape[0]):
thisPos = zpos[k]
thisProb = zprob[k]
f.write("{0:4d} {1:s} {2:f}\n".format(k," ".join(map(str,thisPos)),thisProb ))
f.close()
return sampler
# white dwarf temp
twdVals = np.random.normal(loc=args.twd,scale=args.e_twd,size=chainLength)*units.K
# period
pVals = np.random.normal(loc=args.p,scale=args.e_p,size=chainLength)*units.d
# loop over the MCMC chain, calculating system parameters as we go
# table for results
results = Table(names=('q','Mw','Rw','Mr','Rr','a','Kw','Kr','incl'))
# need to be a little careful about astropy versions here, since only
# versions >=1.0 allow quantities in tables
# function below extracts value from quantity and floats alike
getval = lambda el: getattr(el,'value',el)
psolve = partial(solve,baseDir=baseDir)
data = zip(qVals,dphiVals,rwVals,twdVals,pVals)
solvedParams = PB.map(psolve,data,multiprocess=True)
print 'Writing out results...'
# loop over these results and put all the solutions in our results table
iStep = 0
bar = ProgressBar()
for thisResult in solvedParams:
bar.render(int(100*iStep/(len(solvedParams))),'Combining data')
iStep += 1
if thisResult is not None:
results.add_row(thisResult)
print 'Found solutions for %d percent of samples in MCMC chain' % (100*float(len(results))/float(chainLength))
results.write('physicalparams.log',format='ascii.commented_header')
