def __call__(self, profile):
#only want to define a scan for a 1d model at this point.
assert(isinstance(self.model, NFW_MC_Model))
self.model.setData(profile.beta_s, profile.beta_s2, profile.zcluster, zlens = profile.zlens)
pdfs = {}
masses = self.masses
for delta in self.deltas:
logprob = np.zeros(len(masses))
if delta == 200:
workingmasses = masses
c200s = np.array([self.model.massconRelation(np.abs(curm)*nfwutils.global_cosmology.h,
profile.zcluster, float(delta)) for curm in workingmasses])
elif delta != 200:
workingmasses = np.zeros_like(masses)
c200s = np.zeros_like(masses)
for i, curm in enumerate(masses):
c200 = self.model.massconRelation(np.abs(curm)*nfwutils.global_cosmology.h,
profile.zcluster, float(delta))
rscale = nfwutils.rscaleConstM(np.abs(curm), c200, profile.zcluster, float(delta))
m200 = nfwutils.Mdelta(rscale, c200, profile.zcluster, 200)
if curm < 0:
m200 = -m200
workingmasses[i] = m200
c200s[i] = c200
for i in range(len(workingmasses)):
mass = workingmasses[i]
c200 = c200s[i]
logprob[i] = tools.shearprofile_like(mass, c200,
profile.r_mpc,
profile.ghat,
profile.sigma_ghat,
self.model.beta_s,
self.model.beta_s2,
self.model.rho_c,
self.model.rho_c_over_sigma_c,
200.)
pdf = np.exp(logprob - np.max(logprob))
pdf = pdf/scipy.integrate.trapz(pdf, masses)
pdfs[delta] = pdf
if np.any(np.logical_not(np.isfinite(pdf))):
raise BadPDFException
return (masses, pdfs)
def convertLikelihoodScan(model, delta, masses, pdf200, zcluster):
#treats input pdf as a likelihood scan & rescales axis. Does not transform like a PDF!!!
targetmasses = np.zeros_like(masses)
for i, curm in enumerate(masses):
c200 = model.massconRelation(
np.abs(curm) * nfwutils.global_cosmology.h, zcluster, 200.)
r200 = nfwutils.rdeltaConstM(np.abs(curm), zcluster, 200.)
rscale = r200 / c200
m_target = nfwutils.Mdelta(rscale, c200, zcluster, delta)
if curm < 0:
m_target = -m_target
targetmasses[i] = m_target
targetpdf = np.interp(masses, targetmasses, pdf200)
targetpdf = targetpdf / np.trapz(targetpdf, masses)
return targetpdf
def consolidateFits(workdir, simtype, outdir):
failfile = open('{0}/fails'.format(outdir), 'w')
idpattern = idpatterns[simtype]
answers = cPickle.load(
open('{0}/{1}_answers.pkl'.format(workdir, simtype), 'rb'))
outputfiles = glob.glob('%s/*.out' % outdir)
nhalos = len(outputfiles)
ids = []
measured_m200s = np.zeros(nhalos)
measured_m200errs = np.zeros(nhalos)
measured_m500s = np.zeros(nhalos)
measured_m500errs = np.zeros(nhalos)
measured_cs = np.zeros(nhalos)
measured_rs = np.zeros(nhalos)
true_m200s = np.zeros(nhalos)
true_m500s = np.zeros(nhalos)
true_cs = np.zeros(nhalos)
redshifts = np.zeros(nhalos)
results = dict(ids=ids,
measured_m200s=measured_m200s,
measured_m200errs=measured_m200errs,
measured_m500s=measured_m500s,
measured_m500errss=measured_m500errs,
measured_cs=measured_cs,
measured_rs=measured_rs,
true_m200s=true_m200s,
true_m500s=true_m500s,
true_cs=true_cs,
redshifts=redshifts)
class WeirdException(Exception):
pass
#load up the environment for cosmology, and mc relation if used
config = nfwfit.readConfiguration('{0}/config.sh'.format(outdir))
simreader = nfwfit.buildSimReader(config)
nfwutils.global_cosmology.set_cosmology(simreader.getCosmology())
fitter = nfwfit.buildFitter(config)
configname = os.path.basename(outdir)
for i, output in enumerate(outputfiles):
filebase = os.path.basename(output)
match = idpattern.match(filebase)
try:
haloid = int(match.group(1))
except AttributeError as e:
print filebase
raise e
except ValueError:
haloid = match.group(1)
try:
truth = answers[haloid]
except KeyError:
print 'Failure at {0}'.format(output)
raise
ids.append(haloid)
true_m200s[i] = truth['m200']
true_m500s[i] = truth['m500']
true_cs[i] = truth['concen']
redshifts[i] = truth['redshift']
input = open(output)
measured = cPickle.load(input)
input.close()
if measured is None:
print 'Fail {0} {1}'.format(configname, haloid)
failfile.write('Fail {0} {1}\n'.format(configname, haloid))
continue
measured_m200s[i] = measured[0][
'm200'] * fitter.model.massScale * nfwutils.global_cosmology.h
measured_m200errs[i] = np.mean(np.abs(
measured[1]
['m200'])) * fitter.model.massScale * nfwutils.global_cosmology.h
if 'c200' in measured:
measured_cs[i] = measured['c200']
else:
## need to dig up the mc relation
measured_cs[i] = fitter.model.massconRelation(
np.abs(measured_m200s[i]), redshifts[i],
fitter.model.overdensity)
#####
#calculate m500
measured_rs[i] = nfwutils.rscaleConstM(np.abs(measured_m200s[i]),
measured_cs[i], redshifts[i],
fitter.model.overdensity)
measured_m500s[i] = nfwutils.Mdelta(measured_rs[i], measured_cs[i],
redshifts[i], 500)
if measured_m200s[i] < 0:
measured_m500s[i] = -measured_m500s[i]
if not np.isfinite(measured_m500s[i]):
print 'NOT FINITE'
print haloid
print measured
cPickle.dump(results, open('%s/consolidated.pkl' % outdir, 'w'))
failfile.close()
#
# simdat1 = data['c4'][radrange]
# simdat2 = data['cfree'][radrange]
#
# massbin1, ratiobin1, ratioerr1 = bbb.summary2DMass(simdat1)
# massbin2, ratiobin2, ratioerr2 = bbb.summary2DMass(simdat2)
#
# massbins2.append(massbin1)
# offset.append((np.array(ratiobin1)/ np.array(ratiobin2)) - 1.)
#
##
figure()
mlow500 = nfwutils.Mdelta(
nfwutils.rscaleConstM(10**massbins[0][0], 4.0, 1.0, 200), 4.0, 1.0,
500) / 1e14
mid500 = nfwutils.Mdelta(
nfwutils.rscaleConstM(10**massbins[0][8], 4.0, 1.0, 200), 4.0, 1.0,
500) / 1e14
mhigh500 = nfwutils.Mdelta(
nfwutils.rscaleConstM(10**massbins[0][-1], 4.0, 1.0, 200), 4.0, 1.0,
500) / 1e14
plot(outerrange[:-1],
100 * np.array([scatter[8] for scatter in scatters[:-1]]),
c='k',
linewidth=1.8,
label='Intrinsic Scatter')
twincolor = '#B366B3'