prioravg = np.array([])
priorwth = np.array([])
priorvals = np.array([prioravg,priorwth])
parlist_cat = np.append(fixlist, parlist)
parvals_cat = np.append(fixvals,parvals)
#print parlist_cat
#print parvals_cat
start = time.time()
filedir = '/Users/nab/Desktop/Projects/ACTPol_Cluster_Like/'
filename = args.chain_name #,'mockCat_v1'
if args.testMock:
print("Testing Mockcat Numbers")
MC = lk.MockCatalog(iniFile,pardict,nemoOutputDir,noise_file,parvals,parlist,mass_grid_log=[mmin,15.7,0.01],z_grid=[0.1,2.01,0.1])
saveNum = []
for i in range(args.testMock):
Nums = MC.test_Mockcat_Nums(mmin)
saveNum = np.append(saveNum,Nums)
if (np.mod(i,old_div(args.testMock,10)) == 0):
print(".")
#print saveNum
f = open(filedir+filename+'.txt', "w")
np.savetxt(f,saveNum)
print('sample time',time.time() - start)
sys.exit(0)
else:
check = os.path.isfile(filedir+filename+'.fits')
if (check == False):
MC = lk.MockCatalog(iniFile,pardict,nemoOutputDir,noise_file,parvals,parlist,mass_grid_log=[mmin,15.7,0.01],z_grid=[0.1,2.01,0.1])
priorwth = np.array([0.002, 0.014, 3.6, 0.11, 0.1])
# prioravg = np.array([0.0223,0.96,67.3,0.8,0.2])
# priorwth = np.array([0.0009,0.02,3.6,0.12,0.1])
priorvals = np.array([prioravg, priorwth])
if args.mockcat or args.randcat:
parlist = [
'omch2', 'ombh2', 'H0', 'As', 'ns', 'tau', 'massbias', 'yslope', 'scat'
]
parvals = [0.1225, 0.0245, 70, 2.0e-09, 0.97, 0.06, 1.0, 0.08, 0.2]
if args.mockcat:
MC = lk.MockCatalog(iniFile,
pardict,
nemoOutputDir,
noise_file,
parvals,
parlist,
mass_grid_log=[13.6, 15.7, 0.01],
z_grid=[0.1, 2.01, 0.1])
if args.randcat:
MC = lk.MockCatalog(
iniFile,
pardict,
nemoOutputDir,
noise_file,
parvals,
parlist,
mass_grid_log=[np.log10(2e14),
np.log10(7e15), 0.01],
z_grid=[0.1, 1.01, 0.1],
randoms=True)