# model = Model(stokes=stokes)
# model.add_components(*new_dfm_model)
# model.add_components(ccmodel)
if stokes == "I":
use_V = True
else:
use_V = False
noise = uvdata_template.noise(use_V=use_V)
params = list()
for i in range(n_mc):
uvdata_template.substitute([ccmodel])
uvdata_template.uvdata = uvdata_template.uvdata * corrections
uvdata_template.noise_add(noise)
uvdata_template.save(os.path.join(data_dir, "artificial.uvf"),
rewrite=True,
downscale_by_freq=True)
# Self-calibrate
selfcal_difmap(
fname="artificial.uvf",
outfname="artificial.uvf",
path=data_dir,
path_to_script="/home/ilya/github/ve/difmap/auto_selfcal",
outpath=data_dir,
show_difmap_output=True)
modelfit_difmap("artificial.uvf",
"{}.mod".format(epoch),
freq: mojave_uv_fits_fname(source, freq, epoch)
for freq in ('x', 'j', 'u')
}
for freq, uv_fits_fname in uv_fits_fnames.items():
uv_fits_path = os.path.join(data_dir, uv_fits_fname)
cg1 = CGComponent(2.0, 0., 0., 0.2)
cg2 = CGComponent(1.0, 0., 0.3, 0.3)
cg3 = CGComponent(0.5, 0., 1.5, 0.4)
mdl = Model(stokes='I')
mdl.add_components(cg1, cg2, cg3)
uvdata = UVData(uv_fits_path)
noise = uvdata.noise()
for i in range(1, 101):
uvdata = UVData(uv_fits_path)
uvdata.substitute([mdl])
uvdata.noise_add(noise)
art_fits_fname = 'art_{}_{}.fits'.format(freq, i)
art_fits_path = os.path.join(data_dir, art_fits_fname)
uvdata.save(art_fits_path)
# Here we should MCMC posterior
modelfit_difmap(art_fits_fname,
'initial.mdl',
'out_{}_{}.mdl'.format(freq, i),
niter=100,
path=data_dir,
mdl_path=data_dir,
out_path=data_dir)
params = list()
for i in range(1, 101):
# DOESNT WORK - ERRORS STILL SMALL
import os
from mojave import mojave_uv_fits_fname
from uv_data import UVData
from bootstrap import bootstrap_uvfits_with_difmap_model
data_dir = '/home/ilya/silke'
epoch = '2017_01_28'
original_model_fname = '2017_01_28us'
original_model_path = os.path.join(data_dir, original_model_fname)
uv_fits_fname = mojave_uv_fits_fname('0851+202', 'u', epoch)
uv_fits_path = os.path.join(data_dir, uv_fits_fname)
uvdata = UVData(uv_fits_path)
uvdata.noise_add({baseline: [0.137] for baseline in uvdata.baselines})
new_fits_path = os.path.join(data_dir, 'added_noise.fits')
uvdata.save(new_fits_path)
bootstrap_uvfits_with_difmap_model(new_fits_path,
original_model_path,
boot_dir=os.path.join(data_dir, 'boot'))
