def fit(obs, flux, gaussprior, res):
# Image total flux with bispectrum
out = eh.imager_func(obs,
gaussprior,
gaussprior,
flux,
d1='bs',
s1='simple',
alpha_s1=1,
alpha_d1=100,
alpha_flux=100,
alpha_cm=50,
maxit=100,
ttype=ttype,
show_updates=False)
# Blur the image with a circular beam and image again to help convergance
out = out.blur_circ(res)
out = eh.imager_func(obs,
out,
out,
flux,
d1='bs',
s1='tv',
alpha_s1=1,
alpha_d1=50,
alpha_flux=100,
alpha_cm=50,
maxit=100,
ttype=ttype,
show_updates=False)
out = out.blur_circ(res / 2.0)
out = eh.imager_func(obs,
out,
out,
flux,
d1='bs',
s1='tv',
alpha_s1=1,
alpha_d1=10,
alpha_flux=100,
alpha_cm=50,
maxit=100,
ttype=ttype,
show_updates=False)
return out
#obs.save_uvfits('obs.uvp') # exports a UVFITS file modeled on template.UVP
# Generate an image prior
npix = 32
fov = 1*im.fovx()
zbl = im.total_flux() # total flux
prior_fwhm = 200*eh.RADPERUAS # Gaussian size in microarcssec
emptyprior = eh.image.make_square(obs, npix, fov)
flatprior = emptyprior.add_flat(zbl)
gaussprior = emptyprior.add_gauss(zbl, (prior_fwhm, prior_fwhm, 0, 0, 0))
# Image total flux with bispectrum
flux = zbl
out = eh.imager_func(obs, gaussprior, gaussprior, flux,
d1='bs', s1='simple',
alpha_s1=1, alpha_d1=100,
alpha_flux=100, alpha_cm=50,
maxit=100, ttype='fast')
# Blur the image with a circular beam and image again to help convergance
out = out.blur_circ(res)
out = eh.imager_func(obs, out, out, flux,
d1='bs', s1='tv',
alpha_s1=1, alpha_d1=50,
alpha_flux=100, alpha_cm=50,
maxit=100,ttype='fast')
out = out.blur_circ(res/2.0)
out = eh.imager_func(obs, out, out, flux,
d1='bs', s1='tv',
alpha_s1=1, alpha_d1=10,
##
zbl = 2.5
prior_fwhm = 100 * eh.RADPERUAS
gaussparams = (prior_fwhm, prior_fwhm, 0.0)
emptyprior = eh.image.make_square(obs, npix, fov)
gaussprior = emptyprior.add_gauss(zbl, gaussparams)
gaussprior.display()
##
out = eh.imager_func(obs,
gaussprior,
gaussprior,
zbl,
d1="vis",
alpha_d1=50,
s1="gs",
maxit=100)
##
outblur = out.blur_gauss(beamparams, 0.5)
out = outblur
outblur = eh.imager_func(obs,
out,
out,
zbl,
d1="vis",
alpha_d1=10,
s1="gs",
zbl = im.total_flux() # total flux
prior_fwhm = 200*eh.RADPERUAS # Gaussian size in microarcssec
emptyprior = eh.image.make_square(obs, npix, fov)
flatprior = emptyprior.add_flat(zbl)
gaussprior = emptyprior.add_gauss(zbl, (prior_fwhm, prior_fwhm, 0, 0, 0))
# Define the data products
d1 = 'vis'
d2 = False
alpha_d1 = 100.0
alpha_d2 = 0.0
# Image using MEM
flux = zbl
out = eh.imager_func(obs, gaussprior, gaussprior, flux,
d1=d1, d2=d2, alpha_d1=alpha_d1, alpha_d2=alpha_d2, s1='simple', alpha_s1=10, ttype='nfft',
maxit=100, show_updates=False, beam_size=res, norm_reg=True)
for repeat in range(5):
out = eh.imager_func(obs, out.blur_circ(res), gaussprior, flux,
d1=d1, d2=d2, alpha_d1=alpha_d1, alpha_d2=alpha_d2, s1='simple', alpha_s1=10, ttype='nfft',
maxit=300, show_updates=False, beam_size=res, norm_reg=True)
out.display()
out.display(scale='log')
# Now with the tunable sparsity regularizer and tv2
alpha_A = 100.0
out2 = out.copy()
for repeat in range(5):
alpha_A *= 2.0
def main(vis, closure_tels='DE601;DE602;DE603;DE604;DE605;FR606;SE607;UK608;DE609;PL610;PL611;PL612;IE613', npix=128, fov_arcsec=6., maxarcmin=2.0, zbl=0., prior_fwhm_arcsec=1., doplots=False, imfile='myim', remove_tels='', niter=300, cfloor=0.001, conv_criteria=0.0001, use_bs=False, scratch_model=False, do_diagnostic_plots=False, lotss_file=''):
use_first = not(scratch_model)
## for the generic pipeline, force the data types
npix = int(npix)
fov_arcsec = float(fov_arcsec)
maxarcmin = float(maxarcmin)
zbl = float(zbl)
prior_fwhm_arcsec = float(prior_fwhm_arcsec)
niter = int(niter)
cfloor = float(cfloor)
conv_criteria = float(conv_criteria)
## set output files
vis1 = vis.rstrip('/') + '.ms' ## so the next line will work if it doesn't end in ms
fitsout = vis1.replace('.MS','.fits').replace('.ms','.fits')
tmp_name = 'tmp_clphase_' + vis1
src_name = vis1.split('_')[0]
## remove any telescopes from the default list
r_tels = remove_tels.split(';')
for r_tel in r_tels:
closure_tels = closure_tels.replace(r_tel,'')
tmp_tel = closure_tels.split(';')
tel = [ t for t in tmp_tel if t != '' ]
## starting from a measurement set, get a smaller ms with just the list of antennas
## use taql to get a list of telescopes
ss = 'taql \'select NAME from %s/ANTENNA\' > closure_txt'%(vis)
os.system(ss)
os.system('grep -v select closure_txt > closure_which')
idxtel = np.loadtxt('closure_which',dtype='S')
os.system('cat closure_which')
atel = np.unique(np.ravel(tel))
notfound = []
aidx = np.array([],dtype='int')
for a in atel:
found_this = False
for i in range(len(idxtel)):
if a==idxtel[i][:len(a)]:
aidx = np.append(aidx,i)
found_this = True
if not found_this:
notfound.append (a)
if len(notfound):
print 'The following telescopes were not found:',notfound
os.system( 'rm closure_*' )
aidx_s = np.sort(aidx)
if os.path.exists (tmp_name):
os.system('rm -fr %s'%tmp_name)
ss = 'taql \'select from %s where ' % vis
for i in range (len(aidx_s)):
for j in range (i+1, len(aidx_s)):
ss += ('ANTENNA1==%d and ANTENNA2==%d' %(aidx_s[i],aidx_s[j]))
if i==len(aidx_s)-2 and j==len(aidx_s)-1:
ss += (' giving %s as plain\''%tmp_name)
else:
ss += (' or ')
print 'Selecting smaller MS %s this will take about 4s/Gb:'%tmp_name
os.system (ss)
## get the coordinates for the phase center
ss = "taql 'select PHASE_DIR from %s/FIELD' > phase_dir.txt"%tmp_name
os.system( ss )
with open( 'phase_dir.txt', 'r' ) as f:
lines = f.readlines()
f.close()
phase_dir = lines[-1].lstrip('[').rstrip(']\n')
ra_sexg = phase_dir.split(',')[0]
dec_sexg = phase_dir.split(',')[1]
c = SkyCoord( ra_sexg, dec_sexg, frame='icrs' )
ra = float(c.ra.degree)
dec = float(c.dec.degree)
## check if weights are appropriate
print 'Checking if weights are sensible values, updating them if not'
ss = "taql 'select WEIGHT_SPECTRUM from %s limit 1' > weight_check.txt"%tmp_name
print( ss )
os.system(ss)
with open( 'weight_check.txt', 'r' ) as f:
lines = f.readlines()
f.close()
first_weight = np.float(lines[3].lstrip('[').split(',')[0])
if first_weight < 1e-9:
ss = "taql 'update %s set WEIGHT_SPECTRUM=WEIGHT_SPECTRUM*1e11'"%tmp_name
os.system(ss)
if lotss_file != '':
print 'LoTSS file is specified, using zero baseline flux from catalogue.'
lotss_cat = ascii.read( lotss_file )
src_index = np.where( lotss_cat['Source_id'] == src_name )
flux_mJy = float( lotss_cat['Total_flux'][src_index[0]] )
zbl = flux_mJy * 1e-3
else:
print 'LoTSS file is not specified.'
if zbl == 0:
## find the zero baseline amplitudes if it isn't set
print 'Calculating the zero baseline flux (mean of amplitudes on DE601 -- DE605)'
## use baseline DE601 -- DE605, failing that the first two in list
try:
de601_idx = aidx[[ i for i, val in enumerate(tel) if 'DE601' in val ]][0]
de605_idx = aidx[[ i for i, val in enumerate(tel) if 'DE605' in val ]][0]
except:
print '...Not present. Using %s %s instead'%(tel[0],tel[1])
de601_idx, de605_idx = aidx[0],aidx[1]
ss = "taql 'select medians(gaggr(abs(DATA)),0,1) from %s' where ANTENNA1==%s and ANTENNA2=%s > amp_check.txt"%(tmp_name, de601_idx, de605_idx)
os.system(ss)
with open( 'amp_check.txt', 'r' ) as f:
lines = f.readlines()
f.close()
amps = np.asarray(lines[2].lstrip('[').rstrip(']\n').split(', '),dtype=float)
zbl = np.median(amps)
os.system('rm *_check.txt')
print( 'Zero baseline flux:', zbl )
## convert vis to uv-fits
if os.path.isfile(fitsout):
os.system('rm '+fitsout)
ss = 'ms2uvfits in=%s out=%s writesyscal=F'%(tmp_name, fitsout)
os.system(ss)
## observe the uv-fits
print 'Reading in the observation %s to the EHT imager.' %fitsout
obs = eh.obsdata.load_uvfits(fitsout)
## flag the data?
fov = as2rad(fov_arcsec)
if do_diagnostic_plots:
print 'Plotting u-v coverage and amplitude vs. uv-distance'
obs.plotall('u','v', conj=True, show=False, export_pdf=fitsout.replace('fits','u-v.pdf') ) ## u-v coverage
obs.plotall('uvdist','amp', show=False, export_pdf=fitsout.replace('fits','uvdist-amp.pdf') ) ## etc
## the dirty beam
print 'Calculating the dirty beam.'
dbeam = obs.dirtybeam(npix,fov)
dbeam.save_fits(fitsout.replace('fits','dirty_beam.fits'))
## the clean beam
print 'Calculating the clean beam.'
cbeam = obs.cleanbeam(npix,fov)
cbeam.save_fits(fitsout.replace('fits','clean_beam.fits'))
## dirty image
print 'Calculating the dirty image.'
dimage = obs.dirtyimage(npix,fov)
dimage.save_fits(fitsout.replace('fits','dirty_image.fits'))
## beam parameters (in radians)
beamparams = obs.fit_beam()
print 'The beam is ' + str(rad2as(beamparams[0])) + ' by ' + str(rad2as(beamparams[1])) + ' arcsec.'
## maximum resolution (in radians)
res = obs.res()
print 'Maximum resolution is ' + str(res*206265.)
print use_first
## set up the gaussian prior
if use_first:
print( 'Using FIRST.' )
if not os.path.isfile('./first_2008.simple.npy'):
os.system('wget http://www.jb.man.ac.uk/~njj/first_2008.simple.npy')
first = np.load('first_2008.simple.npy')
# firstdata = first_download(ra,dec,imsize=maxarcmin)
# lkm - this is the else statement, it may not work
spatial_separations = sepn(np.deg2rad(ra),np.deg2rad(dec),np.deg2rad(first[:,0]),np.deg2rad(first[:,1]))
corrfirst = np.where( spatial_separations <= as2rad(maxarcmin*60.0) )[0]
if not len(corrfirst): # no FIRST, fall back to default
print 'No FIRST sources, using default'
prior_fwhm = as2rad(prior_fwhm_arcsec)
gaussparams = ( prior_fwhm, prior_fwhm, 0.0 )
emptyprior = eh.image.make_square( obs, npix, fov )
gaussprior = emptyprior.add_gauss( zbl, gaussparams )
print 'Prior image: circular Gaussian %f arcsec' % prior_fwhm_arcsec
else:
gaussparams, gflux = np.array([]),np.array([])
for i in corrfirst:
this = first[int(i)]
gflux = np.append(gflux,this[3])
decdiff = np.deg2rad(this[1]-dec)
radiff = np.deg2rad(this[0]-ra)*np.cos(np.deg2rad(dec))
gnew = np.array([as2rad(max(7.0,this[4])), as2rad(max(5.0,this[5])),\
np.deg2rad(this[6]),radiff,decdiff])
try:
gaussparams = np.vstack((gaussparams,gnew))
except:
gaussparams = np.copy([gnew])
fov_arcsec = max(fov_arcsec,2.5*np.hypot(rad2as(gnew[3]),rad2as(gnew[4])))
print 'Adjusted FOV to %f arcsec'%fov_arcsec
# gaussparams[0,4]*=0.8; gaussparams[0,3]*=0.8 #sabotage
fov = as2rad(fov_arcsec)
gaussprior = eh.image.make_square( obs, npix, fov )
zbl = np.sum(gflux) * 4.0/1000 # total flux in FIRST * 4
for i in range(len(gaussparams)):
g = gaussparams[i]
print 'Prior: adding %.1fmJy Gaussian %.2f*%.2f asec, PA %.1f, at (%.3f,%.3f)asec' % \
(gflux[i],rad2as(g[0]),rad2as(g[1]),np.rad2deg(g[2]),rad2as(g[3]),rad2as(g[4]))
gaussprior = gaussprior.add_gauss( gflux[i], g )
firstdata = first_download(ra,dec,imsize=fov_arcsec/60.0)
else:
print 'Not using FIRST'
# obs=eh.obsdata.load_uvfits('../data/L1327+5504_vvsmall.fits') ##
prior_fwhm = as2rad(prior_fwhm_arcsec)
gaussparams = ( prior_fwhm, prior_fwhm, 0.0 )
emptyprior = eh.image.make_square( obs, npix, fov )
print npix,fov,zbl,gaussparams
gaussprior = emptyprior.add_gauss( zbl, gaussparams )
out=eh.imager_func(obs,gaussprior,gaussprior,5.0,d1='bs',clipfloor=cfloor)
if use_bs:
print 'Using bispectrum mode rather than cphase and camp separately.'
out = eh.imager_func( obs, gaussprior, gaussprior, zbl, d1='bs', \
clipfloor=cfloor, maxit=300)
outblur = out.blur_gauss(beamparams, 0.5)
out1 = eh.imager_func( obs, outblur, outblur, zbl, d1='bs', \
clipfloor=cfloor, maxit=300 )
# out = eh.imager_func( obs, gaussprior, gaussprior, zbl, d1='bs', s1='gs', \
# alpha_d1=50, clipfloor=0.00, maxit=300, stop=0.0001 )
# outblur = out.blur_gauss(beamparams, 0.5)
# out1 = eh.imager_func( obs, outblur, outblur, zbl, d1='bs', s1='gs', \
# alpha_d1=50, clipfloor=0.00, maxit=300, stop=0.0001 )
else:
print 'Using closure phase and closure amplitude separately.'
## using d1 = closure phase and d2 = closure amplitude
out = eh.imager_func( obs, gaussprior, gaussprior, zbl, d1='cphase', d2='camp', s1='gs', s2='gs', alpha_d1=50, alpha_d2=50, clipfloor=cfloor, maxit=niter, stop=conv_criteria )
outblur = out.blur_gauss(beamparams, 0.5)
out1 = eh.imager_func( obs, outblur, outblur, zbl, d1='cphase', d2='camp', s1='gs', s2='gs', alpha_d1=50,alpha_d2=50, clipfloor=cfloor, maxit=niter, stop=conv_criteria )
outblur1 = out1.blur_gauss((res,res,0),0.5)
finalout = out1.blur_gauss(beamparams,0.5)
# saving final fits file and some intermediate ones
gaussprior.save_fits('./' + imfile + 'prior.fits')
out.save_fits('./' + imfile + '_0_im.fits')
outblur.save_fits('./' + imfile + '_0_im_blur.fits')
out1.save_fits('./' + imfile + 'im.fits')
finalout.save_fits('./' + imfile + 'im_blur.fits')
insert_radec ('./' + imfile + 'prior.fits', ra, dec)
insert_radec ('./' + imfile + 'im_blur.fits', ra, dec)
if doplots and use_first and firstdata != None:
a1,a2 = gcmake ('first_out.fits','./%s_p1.png'%imfile)
a1,a2 = gcmake ('./%sprior.fits'%imfile,'./%s_p2.png'%imfile)
a1,a2 = gcmake ('./%sim_blur.fits'%imfile,'./%s_p3.png'%imfile,vmax=a2)
os.system('montage -geometry 600x600 -tile 3x1 %s_p1.png %s_p2.png %s_p3.png %s_plots.png'%\
(imfile,imfile,imfile,imfile))
elif doplots:
plt.subplot(121);plt.imshow(pyfits.getdata('./'+imfile+'im_blur.fits'))
plt.subplot(122);plt.imshow(pyfits.getdata('./'+imfile+'prior.fits'))
plt.savefig('./'+imfile+'_plots.png',bbox_inches='tight')
print 'done.'
def main(
vis,
closure_tels='DE601;DE602;DE603;DE604;DE605;FR606;SE607;UK608;DE609;PL610;PL611;PL612;IE613',
npix=128,
fov_arcsec=6.,
zbl=0.,
prior_fwhm_arcsec=1.,
doplots=False,
imfile='myim',
remove_tels='',
niter=300,
cfloor=0.001,
conv_criteria=0.0001,
use_bs=False,
use_first=False):
## for the generic pipeline, force the data types
npix = int(npix)
fov_arcsec = float(fov_arcsec)
zbl = float(zbl)
prior_fwhm_arcsec = float(prior_fwhm_arcsec)
niter = int(niter)
cfloor = float(cfloor)
conv_criteria = float(conv_criteria)
vis1 = vis.rstrip(
'/') + '.ms' ## so the next line will work if it doesn't end in ms
fitsout = vis1.replace('.MS', '.fits').replace('.ms', '.fits')
## remove any telescopes from the default list
r_tels = remove_tels.split(';')
for r_tel in r_tels:
closure_tels = closure_tels.replace(r_tel, '')
tmp_tel = closure_tels.split(';')
tel = [t for t in tmp_tel if t != '']
## starting from a measurement set, get a smaller ms with just the list of antennas
## use taql to get a list of telescopes
ss = 'taql \'select NAME from %s/ANTENNA\' > closure_txt' % (vis)
os.system(ss)
os.system('grep -v select closure_txt > closure_which')
idxtel = np.loadtxt('closure_which', dtype='S')
atel = np.unique(np.ravel(tel))
notfound = []
aidx = np.array([], dtype='int')
for a in atel:
found_this = False
for i in range(len(idxtel)):
if a == idxtel[i][:len(a)]:
aidx = np.append(aidx, i)
found_this = True
if not found_this:
notfound.append(a)
if len(notfound):
print 'The following telescopes were not found:', notfound
os.system('rm closure_*')
aidx_s = np.sort(aidx)
if os.path.exists('cl_temp.ms'):
os.system('rm -fr cl_temp.ms')
ss = 'taql \'select from %s where ' % vis
for i in range(len(aidx_s)):
for j in range(i + 1, len(aidx_s)):
ss += ('ANTENNA1==%d and ANTENNA2==%d' % (aidx_s[i], aidx_s[j]))
if i == len(aidx_s) - 2 and j == len(aidx_s) - 1:
ss += (' giving cl_temp.ms as plain\'')
else:
ss += (' or ')
print 'Selecting smaller MS cl_temp.ms, this will take about 4s/Gb:'
print ss
os.system(ss)
## check if weights are appropriate
print 'Checking if weights are sensible values, updating them if not'
ss = "taql 'select WEIGHT_SPECTRUM from cl_temp.ms limit 1' > weight_check.txt"
os.system(ss)
with open('weight_check.txt', 'r') as f:
lines = f.readlines()
f.close()
first_weight = np.float(lines[3].lstrip('[').split(',')[0])
if first_weight < 1e-9:
ss = "taql 'update cl_temp.ms set WEIGHT_SPECTRUM=WEIGHT_SPECTRUM*1e11'"
os.system(ss)
## find the zero baseline amplitudes if it isn't set
if zbl == 0:
print 'Calculating the zero baseline flux (mean of amplitudes on DE601 -- DE605'
## use baseline DE601 -- DE605 (shortest international to interational baseline)
## njj - failing that, use the first two
try:
de601_idx = aidx[[
i for i, val in enumerate(tel) if 'DE601' in val
]][0]
de605_idx = aidx[[
i for i, val in enumerate(tel) if 'DE605' in val
]][0]
except:
print '...Not present. Using %s %s instead' % (tel[0], tel[1])
de601_idx, de605_idx = aidx[0], aidx[1]
ss = "taql 'select means(gaggr(abs(DATA)),0,1) from cl_temp.ms' where ANTENNA1==%s and ANTENNA2=%s > amp_check.txt" % (
de601_idx, de605_idx)
os.system(ss)
with open('amp_check.txt', 'r') as f:
lines = f.readlines()
f.close()
amps = np.asarray(lines[2].lstrip('[').rstrip(']\n').split(', '),
dtype=float)
zbl = np.max(amps)
os.system('rm *_check.txt')
## convert vis to uv-fits
if os.path.isfile(fitsout):
os.system('rm ' + fitsout)
ss = 'ms2uvfits in=cl_temp.ms out=%s writesyscal=F' % (fitsout)
os.system(ss)
## observe the uv-fits
print 'Reading in the observation to the EHT imager.'
obs = eh.obsdata.load_uvfits(fitsout)
if doplots:
## make plots
print 'Plotting u-v coverage and amplitude vs. uv-distance'
obs.plotall('u',
'v',
conj=True,
show=False,
export_pdf=fitsout.replace('fits',
'u-v.pdf')) ## u-v coverage
obs.plotall('uvdist',
'amp',
show=False,
export_pdf=fitsout.replace('fits',
'uvdist-amp.pdf')) ## etc
## the eht imager's default units is microarcseconds
fov = fov_arcsec * 1e6 * RADPERUAS
## set up the gaussian prior
if use_first:
if not os.path.isfile('./first_2008.simple.npy'):
os.system(
'wget http://www.jb.man.ac.uk/~njj/first_2008.simple.npy')
import math, pyrap
from pyrap import tables
table = pyrap.tables.table('cl_temp.ms/FIELD', readonly=True)
ra = math.degrees(
float(table.getcol('PHASE_DIR')[0][0][0]) % (2 * math.pi))
dec = math.degrees(float(table.getcol('PHASE_DIR')[0][0][-1]))
table.close()
first = np.load('first_2008.simple.npy')
MAXARCMIN, RADASEC = 2.0, 206265.0
corrfirst = correlate.correlate(np.array([[
ra,
dec,
]]), 0, 1, first, 0, 1, MAXARCMIN / 60.0)
if not len(corrfirst): # no FIRST, fall back to default
prior_fwhm = prior_fwhm_arcsec * 1e6 * RADPERUAS
gaussparams = (prior_fwhm, prior_fwhm, 0.0)
emptyprior = eh.image.make_square(obs, npix, fov)
gaussprior = emptyprior.add_gauss(zbl, gaussparams)
print 'Prior image: circular Gaussian %f arcsec' % prior_fwhm * RADASEC
else:
fov_arcsec = max(10.0, 2.2 * corrfirst[:, 2].max() * 3600.0)
fov = fov_arcsec * 1e6 * RADPERUAS
emptyprior = eh.image.make_square(obs, npix, fov)
for i in corrfirst:
this = first[int(i[1])]
zbl = this[
3] * 4.0 / 1000.0 # multiply first flux by 4 - bit rough
gaussparams = (np.deg2rad((max(7.0,this[4]))/3600.),\
np.deg2rad((max(5.0,this[5]))/3600.),\
np.deg2rad(this[6]),\
np.deg2rad(this[0]-ra),np.deg2rad(this[1]-dec))
print 'Prior: adding %.1fmJy Gaussian %.2f*%.2f asec, PA %.1f, at (%.3f,%.3f)asec' % \
(zbl*1000.,gaussparams[0]*RADASEC,gaussparams[1]*RADASEC,\
np.rad2deg(gaussparams[2]),\
gaussparams[3]*RADASEC,gaussparams[4]*RADASEC)
else:
prior_fwhm = prior_fwhm_arcsec * 1e6 * RADPERUAS
gaussparams = (prior_fwhm, prior_fwhm, 0.0)
emptyprior = eh.image.make_square(obs, npix, fov)
gaussprior = emptyprior.add_gauss(zbl, gaussparams)
gaussprior.display()
## the dirty beam
print 'Calculating the dirty beam.'
dbeam = obs.dirtybeam(npix, fov)
dbeam.save_fits(fitsout.replace('fits', 'dirty_beam.fits'))
## the clean beam
print 'Calculating the clean beam.'
cbeam = obs.cleanbeam(npix, fov)
cbeam.save_fits(fitsout.replace('fits', 'clean_beam.fits'))
# dirty image
print 'Calculating the dirty image.'
dimage = obs.dirtyimage(npix, fov)
dimage.save_fits(fitsout.replace('fits', 'dirty_image.fits'))
## beam parameters (in radians)
beamparams = obs.fit_beam()
print 'The beam is ' + str(beamparams[0] * 206265.) + ' by ' + str(
beamparams[1] * 206265.) + ' arcsec.'
## maximum resolution (in radians)
res = obs.res()
print 'Maximum resolution is ' + str(res * 206265.)
if use_bs:
print 'Using bispectrum mode rather than cphase and camp separately.'
## try using bispectrum
# bs_out = eh.imager_func( obs, gaussprior, gaussprior, zbl, d1='bs', maxit=100)
bs_out = eh.imager_func(obs,
gaussprior,
gaussprior,
zbl,
d1='bs',
s1='gs',
alpha_d1=50,
clipfloor=0.001,
maxit=300,
stop=0.0001)
bs_outblur = bs_out.blur_gauss(beamparams, 0.5)
# bs_out1 = eh.imager_func( obs, bs_outblur, bs_outblur, zbl, d1='bs', s1='gs', alpha_d1=50, maxit=300, stop=0.0001 )
bs_out1 = eh.imager_func(obs,
bs_outblur,
bs_outblur,
zbl,
d1='bs',
s1='gs',
alpha_d1=50,
clipfloor=0.001,
maxit=300,
stop=0.0001)
bs_outblur1 = bs_out1.blur_gauss((res, res, 0), 0.5)
bs_finalout = bs_out1.blur_gauss(beamparams, 0.5)
## save to fits
bs_out1.save_fits('./bs_' + imfile + 'im.fits')
bs_finalout.save_fits('./bs_' + imfile + 'im_blur.fits')
else:
print 'Using closure phase and closure amplitude separately.'
## using d1 = closure phase and d2 = closure amplitude
# out = eh.imager_func( obs, gaussprior, gaussprior, zbl, d1='cphase', maxit=niter, stop=conv_criteria )
out = eh.imager_func(obs,
gaussprior,
gaussprior,
zbl,
d1='cphase',
d2='camp',
s1='gs',
s2='gs',
alpha_d1=50,
alpha_d2=50,
clipfloor=cfloor,
maxit=niter,
stop=conv_criteria)
outblur = out.blur_gauss(beamparams, 0.5)
# out1 = eh.imager_func( obs, outblur, outblur, zbl, d1='cphase', maxit=niter, stop=conv_criteria )
out1 = eh.imager_func(obs,
outblur,
outblur,
zbl,
d1='cphase',
d2='camp',
s1='gs',
s2='gs',
alpha_d1=50,
alpha_d2=50,
clipfloor=cfloor,
maxit=niter,
stop=conv_criteria)
out1blur = out1.blur_gauss((res, res, 0), 0.5)
finalout = out1.blur_gauss(beamparams, 0.5)
## save to fits
out.save_fits('./' + imfile + '_0_im.fits')
outblur.save_fits('./' + imfile + '_0_im_blur.fits')
out1.save_fits('./' + imfile + 'im.fits')
finalout.save_fits('./' + imfile + 'im_blur.fits')
print 'done.'
zbl = im.total_flux() # total flux
prior_fwhm = 200 * eh.RADPERUAS # Gaussian size in microarcssec
emptyprior = eh.image.make_square(obs, npix, fov)
flatprior = emptyprior.add_flat(zbl)
gaussprior = emptyprior.add_gauss(zbl, (prior_fwhm, prior_fwhm, 0, 0, 0))
# Image total flux with bispectrum
flux = zbl
tt = time.time()
out = eh.imager_func(obs,
gaussprior,
gaussprior,
flux,
d1='bs',
s1='simple',
alpha_s1=1,
alpha_d1=100,
alpha_flux=100,
alpha_cm=50,
maxit=100,
ttype=ttype,
show_updates=False)
# Blur the image with a circular beam and image again to help convergance
out = out.blur_circ(res)
out = eh.imager_func(obs,
out,
out,
flux,
d1='bs',
s1='tv',
