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]