def lnlike(self, theta, parlist):
param_vals = alter_fparams(self.fparams, parlist, theta)
for key in self.fix_params:
if key not in list(param_vals.keys()):
param_vals[key] = self.fix_params[key]
int_cc = ClusterCosmology(
param_vals, self.constDict,
clTTFixFile=self.clttfile) # internal HMF call
int_HMF = Halo_MF(int_cc, self.mgrid, self.zgrid) # internal HMF call
self.s8 = int_HMF.cc.s8
if np.nan_to_num(self.s8) < 0.1 or np.nan_to_num(
self.s8) > 10. or not (np.isfinite(self.s8)):
self.s8 = 0.
dndm_int = int_HMF.inter_dndmLogm(200.) # delta = 200
cluster_prop = np.array(
[self.clst_z, self.clst_zerr, 10**self.clst_m, self.clst_merr])
Ntot = self.Ntot_survey(int_HMF, self.fsky)
print("Ntot comparion, and catalog")
print(self.Ntot_survey_TEST(int_HMF, self.fsky), Ntot,
len(self.clst_z))
Nind = 0
for i in range(len(self.clst_z)):
N_per = self.Prob_per_cluster(int_HMF, cluster_prop[:, i],
dndm_int)
Nind = Nind + np.log(N_per)
print("-NTOT, Nind, Total, As")
print(-Ntot, Nind, -Ntot + Nind, theta)
return -Ntot + Nind
def lnlike(self, theta, parlist):
param_vals = alter_fparams(self.fparams, parlist, theta)
for key in self.fix_params:
if key not in list(param_vals.keys()):
param_vals[key] = self.fix_params[key]
print(param_vals)
int_cc = ClusterCosmology(
param_vals, self.constDict,
clTTFixFile=self.clttfile) # internal HMF call
int_HMF = Halo_MF(int_cc, self.mgrid, self.zgrid) # internal HMF call
self.s8 = int_HMF.cc.s8
if np.nan_to_num(self.s8) < 0.1 or np.nan_to_num(
self.s8) > 10. or not (np.isfinite(self.s8)):
self.s8 = 0.
# return -np.inf
#dndm_int = int_HMF.inter_dndm(200.) # delta = 200
dndm_int = int_HMF.inter_dndmLogm(200.) # delta = 200
cluster_prop = np.array([
self.clst_z, self.clst_zerr, self.clst_y0 * 1e-4,
self.clst_y0err * 1e-4
])
if self.test:
Ntot = 60.
else:
Ntot = 0.
for i in range(len(self.frac_of_survey)):
Ntot += self.Ntot_survey(
int_HMF, self.area_rads * self.frac_of_survey[i],
self.thresh_bin[i], param_vals)
#print 'NTOT', Ntot
Nind = 0
#Nind2 = 1.
for i in range(len(self.clst_z)):
N_per = self.Prob_per_cluster(int_HMF, cluster_prop[:, i],
dndm_int, param_vals)
#if (i < 3):
#print np.log(N_per)
Nind = Nind + np.log(N_per)
#Nind2 *= N_per
#print N_per
print(-Ntot, Nind, -Ntot + Nind, theta) #, np.log(np.exp(-Ntot)*Nind2)
return -Ntot + Nind
param_vals = lk.alter_fparams(fparams, parlist, parvals)
cluster_props = np.array(
[CL.clst_z, CL.clst_zerr, CL.clst_y0 * 1e-4, CL.clst_y0err * 1e-4])
start = time.time()
int_cc = ClusterCosmology(param_vals,
CL.constDict,
clTTFixFile=CL.clttfile)
print('CC', time.time() - start)
start = time.time()
int_HMF = Halo_MF(int_cc, CL.mgrid, CL.zgrid)
print('HMF', time.time() - start)
dn_dzdm_int = int_HMF.inter_dndmLogm(200.)
zbins = 10
LgYa = np.outer(np.ones(len(int_HMF.M.copy())), CL.LgY)
Y = 10**LgYa
Ma = np.outer(int_HMF.M.copy(), np.ones(len(LgYa[0, :])))
clustind = 1
print(cluster_props[:, clustind])
print(parlist)
print(parvals)
print(
"ln prob",
np.log(
CL.Prob_per_cluster(int_HMF, cluster_props[:, clustind],
dn_dzdm_int, param_vals)))
