def dust_model(DUST_I=50,
DUST_Q=10 / 1.41,
DUST_U=10 / 1.41,
DUST_BETA=1.6,
DUST_T=20.):
dust_model = models.DustMBB(amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_Q),
amp_U=rj2cmb(353e9, DUST_U),
dust_beta=DUST_BETA,
dust_T=DUST_T)
return dust_model
def hd_fe_model(DUST_I=50,
DUST_Q=10 / 1.41,
DUST_U=10 / 1.41,
FCAR_IN=1.e3,
FSILFE_IN=1.e3,
UVAL_IN=0.0):
hd_fe_model = models.DustHD(amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_Q),
amp_U=rj2cmb(353e9, DUST_U),
fcar=FCAR_IN,
fsilfe=FSILFE_IN,
uval=UVAL_IN)
return hd_fe_model
def two_comp_silcar_model(DUST_I=50,
DUST_Q=10 / 1.41,
DUST_U=10 / 1.41,
DUST_BETA=1.6,
DUST_DBETA=0.2,
DUST_T1=18.,
DUST_T2=22.,
DUST_fI=0.25,
DUST_fQ=0.25,
DUST_fU=0.25):
two_comp_silcar_model = models.DustGen(
amp_I=rj2cmb(353e9, DUST_I), #/ ( 1 + DUST_fI ) ),
amp_Q=rj2cmb(353e9, DUST_Q), #/ ( 1 + DUST_fQ ) ),
amp_U=rj2cmb(353e9, DUST_U), #/ ( 1 + DUST_fU ) ),
beta=DUST_BETA,
dbeta=DUST_DBETA,
Td1=DUST_T1,
Td2=DUST_T2,
fI=DUST_fI,
fQ=DUST_fQ,
fU=DUST_fU)
return two_comp_silcar_model
def ff_model(FF_I=30, FF_Q=0, FF_U=0, FF_BETA=-0.118):
ff_model = models.FreeFreeUnpol(amp_I=rj2cmb(30e9, FF_I),
amp_Q=rj2cmb(30e9, FF_Q),
amp_U=rj2cmb(30e9, FF_U),
ff_beta=FF_BETA)
return ff_model
def sync_model(SYNC_I=30, SYNC_Q=10, SYNC_U=10, SYNC_BETA=-3.2):
sync_model = models.SyncPow(amp_I=rj2cmb(30e9, SYNC_I),
amp_Q=rj2cmb(30e9, SYNC_Q),
amp_U=rj2cmb(30e9, SYNC_U),
sync_beta=SYNC_BETA)
return sync_model
import models
from utils import rj2cmb
DUST_I = 50.
DUST_P = 5. / 1.41
# Define input models and their amplitudes/parameters
dust_model = models.DustMBB( amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_P),
amp_U=rj2cmb(353e9, DUST_P),
dust_beta=1.6, dust_T=20. )
prob1mbb_model = models.ProbSingleMBB( amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_P),
amp_U=rj2cmb(353e9, DUST_P),
dust_beta=1.6, dust_T=20.,
sigma_beta=.2, sigma_temp=4. )
simple_dust_model = models.DustSimpleMBB( amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_P),
amp_U=rj2cmb(353e9, DUST_P),
dust_beta=1.6, dust_T=20. )
simple_dust_model_shifted = models.DustSimpleMBB(
amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_P),
amp_U=rj2cmb(353e9, DUST_P),
dust_beta=1.7, dust_T=20. )
ame_model = models.AMEModel( amp_I=rj2cmb(30e9, 30.),
np.random.seed(SEED)
numin_vals = [15., 20., 25., 30., 35., 40.]
numax_vals = [300., 400., 500., 600., 700., 800.]
#numin_vals = [5., 10., 20., 30., 40., 50., 60., 70.]
#numax_vals = [200., 300., 400., 500., 600., 700.]
#numin_vals = [5., ] #10., 20., 30., 40., 50., 60., 70.]
#numax_vals = [700.,] # 300., 400., 500., 600., 700.]
# Temperature/polarisation noise rms for all bands, as a fraction of T_cmb
fsigma_T = 1. #0.01
fsigma_P = 2. #0.01
# Define input models and their amplitudes/parameters
#dust_model = models.DustMBB(amp_I=150., amp_Q=10., amp_U=10., dust_beta=1.6, dust_T=20.)
dust_model = models.DustMBB( amp_I=rj2cmb(353e9, 150.),
amp_Q=rj2cmb(353e9, 10.),
amp_U=rj2cmb(353e9, 10.),
dust_beta=1.6, dust_T=20. )
sync_model = models.SyncPow( amp_I=30., amp_Q=10., amp_U=10., sync_beta=-3.2 )
cmb_model = models.CMB( amp_I=50., amp_Q=0.6, amp_U=0.6 )
name_in = "MBBSync"
#name_in = "SimpleMBBSync"
mods_in = [cmb_model, dust_model, sync_model]
#mods_in = [sync_model, cmb_model]
amps_in = np.array([m.amps() for m in mods_in])
params_in = np.array([m.params() for m in mods_in])
# Define models to use for the fitting
name_fit = "MBBSync"
print "hello!"
mean_beta = 1.6
mean_temp = 20.
sigma_beta = .2
sigma_temp = 4.
pMBB_broad = model_list.prob1mbb_model
sMBB = model_list.dust_model
cmb = model_list.cmb_model
sync = model_list.sync_model
DUST_I = 50.
DUST_P = 5. / 1.41
amp_I=rj2cmb(353e9, DUST_I)
amp_Q=rj2cmb(353e9, DUST_P)
amp_U=rj2cmb(353e9, DUST_P)
pMBB_narrow = models.ProbSingleMBB(amp_I=rj2cmb(353e9, DUST_I),
amp_Q=rj2cmb(353e9, DUST_P),
amp_U=rj2cmb(353e9, DUST_P),
dust_beta=1.6, dust_T=20.,
sigma_beta=.1 * sigma_beta, sigma_temp=.1 * sigma_temp)
nu_pico = np.asarray([21,25,30, 36.0,43.2,51.8,62.2,74.6,89.6,
107.5,129.0,154.8,185.8,222.9,267.5,321.0,
385.2,462.2,554.7,665.6,798.7]) * 1e9
models_sMBB = [sMBB, cmb, sync]
models_pMBB_broad = [pMBB_broad, cmb, sync]
