def test_run_through_Telescope_methods():
duet = Telescope()
duet_offax = Telescope(config='reduced_baseline')
duet.info()
duet.update_bandpass()
duet.calc_radial_profile()
duet.calc_psf_fwhm()
duet.update_effarea()
duet.fluence_to_rate(1 * u.ph / u.s / u.cm**2)
duet.psf_model()
duet.compute_psf_norms()
def sim_galaxy(patch_size,
pixel_size,
gal_type=None,
gal_params=None,
duet=None,
band=None,
duet_no=None):
'''
Return 2D array of a Sersic profile to simulate a galaxy
Required inputs:
patch_size = Axis sizes of returned galaxy patch in pixels (15,15)
pixel_size = Angular size of pixel (6 * ur.arcsec)
Optional inputs:
gal_type = String that loads a pre-built 'average' galaxy or allows custom definition
gal_params = Dictionary of parameters for Sersic model: ...
duet = Telescope instance
band = duet.bandpass (defaults to DUET1; deprecated)
duet_no = integer (1 or 2) for DUET bandpass
'''
from astropy.modeling.models import Sersic2D
from astroduet.utils import duet_abmag_to_fluence, duet_no_from_band
if duet is None:
duet = Telescope()
if band is None:
band = duet.bandpass1
if duet_no is None:
duet_no = duet_no_from_band(band)
x = np.linspace(-(patch_size[0] // 2), patch_size[0] // 2, patch_size[0])
y = np.linspace(-(patch_size[1] // 2), patch_size[1] // 2, patch_size[1])
x, y = np.meshgrid(x, y)
# Takes either a keyword or Sersic profile parameters
# Typical galaxy parameters based on Bai et al. (2013)
# Hardcoded for now, to-do: take distance as an input
if gal_type == 'spiral':
# A typical spiral galaxy at 100 Mpc
surface_mag = 26.2 * u.ABmag # surface brightness (per arcsec**2)
surface_rate = duet.fluence_to_rate(
duet_abmag_to_fluence(surface_mag, duet_no,
duet=duet)) # surface count rate at r_eff
amplitude = surface_rate * pixel_size.value**2 # surface brightness (per pixel)
r_eff = 16.5 / pixel_size.value
n = 1
theta = 0
ellip = 0.5
x_0, y_0 = r_eff, 0
elif gal_type == 'elliptical':
# A typical elliptical galaxy at 100 Mpc
surface_mag = 25.0 * u.ABmag
surface_rate = duet.fluence_to_rate(
duet_abmag_to_fluence(surface_mag, duet_no,
duet=duet)) # surface count rate at r_eff
amplitude = surface_rate * pixel_size.value**2 # surface brightness (per pixel)
r_eff = 12.5 / pixel_size.value
n = 4
theta = 0
ellip = 0.5
x_0, y_0 = r_eff, 0
elif gal_type == 'dwarf':
# A typical dwarf galaxy at 10 Mpc
surface_mag = 25.8 * u.ABmag
surface_rate = duet.fluence_to_rate(
duet_abmag_to_fluence(surface_mag, duet_no,
duet=duet)) # surface count rate at r_eff
amplitude = surface_rate * pixel_size.value**2 # surface brightness (per pixel)
r_eff = 70 / pixel_size
r_eff = r_eff.value
n = 4
theta = 0
ellip = 0.5
x_0, y_0 = r_eff, 0
elif (gal_type == 'custom') | (gal_type == None):
# Get args from gal_params, default to spiral values
surface_mag = gal_params.get('magnitude', 26) * u.ABmag
surface_rate = duet.fluence_to_rate(
duet_abmag_to_fluence(surface_mag, duet_no,
duet=duet)) # surface count rate at r_eff
amplitude = surface_rate * pixel_size.value**2 # surface brightness (per pixel)
r_eff = gal_params.get('r_eff', 16.5 / pixel_size.value)
n = gal_params.get('n', 1)
theta = gal_params.get('theta', 0)
ellip = gal_params.get('ellip', 0.5)
x_0 = gal_params.get('x_0', 16.5 / pixel_size.value)
y_0 = gal_params.get('y_0', 0)
mod = Sersic2D(amplitude=amplitude,
r_eff=r_eff,
n=n,
x_0=x_0,
y_0=y_0,
ellip=ellip,
theta=theta)
gal = mod(x, y)
return gal
def imsim_srcdetect_combined(run='050719',
gal='spiral',
zodi='low',
nmags=71,
sfb=[20, 30],
stack=1):
"""
Run background estimation, image differencing and source detection on stacked simulated images
Assumes that the script is run in the directory that contains the run_... directory tree
Parameters
----------
run: string (date, as in '050719')
To track runs
zodi: 'low', 'med' or 'high', default is low
gal: 'spiral', 'elliptical', 'dwarf', or 'none'
sfb: [sfb_low, sfb_high], default is [20,30]
List of lowest and highest surface brightness that have been simulated
nmags: float, default is 71
Number of source magnitudes used in image simulations
stack: int, default is 1
Number of stacked exposures
Returns
-------
run_gal_zodi_band.fits: fits table with source detection results
"""
# Get telescope configuration from teldef file:
with open('run_' + run + '/teldef') as origin:
for line in origin:
if 'DUET Telescope State' in line:
tel = line.split(':')[1].strip('\n').strip()
# Initialize parameters
duet = Telescope(config=tel)
# Set up path
path1 = 'run_' + run + '/gal_' + gal + '/zodi_' + zodi + '/duet1/'
path2 = 'run_' + run + '/gal_' + gal + '/zodi_' + zodi + '/duet2/'
# Make galaxy surface brightness array
if gal != 'none':
sfb_arr = np.arange(sfb[0], sfb[1] + 1.).astype(str)
# Make source magnitude array
src_arr = np.linspace(20.5 - 0.5 * (nmags - 1) * 0.1,
20.5 + 0.5 * (nmags - 1) * 0.1,
num=nmags,
endpoint=True) # Currently in steps of 0.1 mag
# Set up results table
# columns: galaxy mag, source input mag, source input count rate, distance from galaxy center, reference depth, source detected True/False,
# if True: retrieved count rate, count rate error; number of false positives
tab = Table(np.zeros(9),
names=('galmag', 'srcmag', 'src-ctrate', 'dist', 'ref_depth',
'detected', 'ctrate', 'ctrate_err', 'false-pos'),
dtype=('f8', 'f8', 'f8', 'f8', 'i8', 'b', 'f8', 'f8', 'i8'),
meta={'name': gal + ' - ' + zodi + 'zodi - combined'})
print('Finding sources...')
if gal == 'none':
reffile1 = run + '_duet1_zodi-' + zodi + '_reference.fits'
hdu_ref1 = fits.open(path1 + reffile1)
reffile2 = run + '_duet2_zodi-' + zodi + '_reference.fits'
hdu_ref2 = fits.open(path2 + reffile2)
for srcmag in src_arr:
imfile1 = run + '_duet1_zodi-' + zodi + '_stack-' + str(
stack) + '_src-' + "{:5.2f}".format(srcmag) + '.fits'
hdu_im1 = fits.open(path1 + imfile1)
imfile2 = run + '_duet2_zodi-' + zodi + '_stack-' + str(
stack) + '_src-' + "{:5.2f}".format(srcmag) + '.fits'
hdu_im2 = fits.open(path2 + imfile2)
# Get input countrate
src_ctrate1 = duet.fluence_to_rate(
duet_abmag_to_fluence(srcmag * u.ABmag, 1, duet=duet))
src_ctrate2 = duet.fluence_to_rate(
duet_abmag_to_fluence(srcmag * u.ABmag, 2, duet=duet))
src_ctrate_comb = src_ctrate1 + src_ctrate2
# Run source detection for this set of HDUs:
tab = run_srcdetect_combined(hdu_ref1=hdu_ref1,
hdu_ref2=hdu_ref2,
hdu_im1=hdu_im1,
hdu_im2=hdu_im2,
tab=tab,
duet=duet,
sfb=np.nan,
srcmag=srcmag,
src_ctrate=src_ctrate_comb)
hdu_im1.close()
hdu_im2.close()
hdu_ref1.close()
hdu_ref2.close()
else:
for sfb in sfb_arr:
print('SFB: ' + sfb)
reffile1 = run + '_duet1_' + gal + '_' + sfb + '_zodi-' + zodi + '_reference.fits'
hdu_ref1 = fits.open(path1 + reffile1)
reffile2 = run + '_duet2_' + gal + '_' + sfb + '_zodi-' + zodi + '_reference.fits'
hdu_ref2 = fits.open(path2 + reffile2)
for srcmag in src_arr:
imfile1 = run + '_duet1_' + gal + '_' + sfb + '_zodi-' + zodi + '_stack-' + str(
stack) + '_src-' + "{:5.2f}".format(srcmag) + '.fits'
hdu_im1 = fits.open(path1 + imfile1)
imfile2 = run + '_duet2_' + gal + '_' + sfb + '_zodi-' + zodi + '_stack-' + str(
stack) + '_src-' + "{:5.2f}".format(srcmag) + '.fits'
hdu_im2 = fits.open(path2 + imfile2)
# Get input countrate
src_ctrate1 = duet.fluence_to_rate(
duet_abmag_to_fluence(srcmag * u.ABmag, 1, duet=duet))
src_ctrate2 = duet.fluence_to_rate(
duet_abmag_to_fluence(srcmag * u.ABmag, 2, duet=duet))
src_ctrate_comb = src_ctrate1 + src_ctrate2
# Run source detection for this set of HDUs:
tab = run_srcdetect_combined(hdu_ref1=hdu_ref1,
hdu_ref2=hdu_ref2,
hdu_im1=hdu_im1,
hdu_im2=hdu_im2,
tab=tab,
duet=duet,
sfb=float(sfb),
srcmag=srcmag,
src_ctrate=src_ctrate)
hdu_im1.close()
hdu_im2.close()
hdu_ref1.close()
hdu_ref2.close()
# Save output table
print('Writing file')
tab.remove_row(0)
tab.write('run' + run + '_gal-' + gal + '_zodi-' + zodi + '_stack-' +
str(stack) + '-combined.fits',
format='fits',
overwrite=True)
print('Done')