def main(datacube, outdir, DIT, NDIT, grating, spax, seeing, zenith_ang, telescope='E-ELT', user_PSF='None',
AO='SCAO', res_jitter=0, site_temp=280.5, combine_ndits=True, Spec_nyquist=True, Spec_samp=1.,
noise_force_seed=0, remove_background='False', return_object='False', return_transmission='False',
adr_switch='True', version='1', nprocs=mp.cpu_count()-1):
'''Main body of code: gathers all inputs and calls all functions
to generate outputs.
Inputs:
datacube: Input high resolution datacube (RA, DEC, lambda)
outdir: Output file directory
DIT: Exposure time [s]
NDIT: No. of exposures
grating: Spectral grating
spax: spatial pixel (spaxel) scale [mas]
seeing: Atmospheric seeing FWHM [arcsec]
zenith_ang: Zenith angle [deg]
telescope: Telescope type (E-ELT, VLT)
user_PSF: Path to user uploaded PSF file
AO: AO mode (LTAO, SCAO, Gaussian)
res_jitter: Residual telescope jitter [mas]
site_temp: Telescope temperature [K]
combine_ndits: Boolean - Combine NDITS
spec_Nyquist: Boolean - Set spectral sampling to Nyquist sample spectral resolution element
Spec_samp: Spectral sampling [A/pix] - used if spec_Nyquist = False
noise_force_seed: Force random number seed to take a set value (0=No, 1-10=yes and takes that value)
remove_background: Boolean - Subtract background spectrum
return_object: Boolean - Return object cube
return_transmission: Boolean - Return throughput cube
adr_switch: Boolean - turn ADR on or off.
version: Version of code. Equal to SVN revision number'
nprocs: no. of processes to use for parallel processing
Outputs:
observed_cube: FITS file of datacube representing HARMONI observation of input cube
background_cube: FITS file of datacube representing background sources
reduced_cube: FITS file of observed datacube after subtracting background
noise_cube: FITS file of noise for each pixel in datacube
'''
print 'Filename: ', datacube
print 'Output dir: ', outdir
print 'DIT = ', DIT
print 'NINT = ', NDIT
print 'X spaxels = ', spax[0]
print 'Y spaxels = ', spax[1]
print 'Grating = ', grating
print 'Telescope: ', telescope
print 'AO = ', AO
print 'Seeing = ', seeing
print 'Zenith angle = ', zenith_ang
print 'Residual jitter = ', res_jitter
print 'Temperature = ', site_temp
print 'combine NINTS? ', combine_ndits
print 'Noise seed = ', noise_force_seed
print 'Spectral Nyquist sampling? ', Spec_nyquist
print 'Subtract background? ', remove_background
print 'User PSF? ' , user_PSF
print 'Return Object cube?', return_object
print 'Return transmission?', return_transmission
print 'ADR off?', adr_switch
print 'No. of processes = ', nprocs
#Generate random number seed
seednum = generate_seed(noise_force_seed)
n.random.seed(seednum)
#OPEN INPUT FITS file
if os.path.isfile(datacube) == True and os.path.splitext(datacube)[1].lower() == '.fits':
cube, head = p.getdata(datacube, 0, header=True, memmap=True)
#If not FITS file, try passing datacube directly
else:
try:
cube = datacube.data
head = datacube.header
except:
raise ValueError('UNKNOWN INPUT FILE FORMAT: Please use FITS file')
#Check that datacube has required headers to be processed in simulator
#Required headers = ['CDELT1/2/3'], ['CRVAL3'], ['NAXIS1/2/3'], ['FUNITS'], ['CRPIX3'] = 1,
#['CTYPE1/2/3'] = 'RA, DEC, WAVELENGTH, ['CUNIT1/2/3'] = MAS, MAS, microns/angstroms/etc,
#['SPECRES'].
fits_header_check(head)
pp.pprint(head)
#telescope options = 'VLT', 'E-ELT'
#Sets diameter D, M1 collecting area and obscuration ratio eps
if telescope == 'VLT':
D = config_data['VLT']['diam']
area = config_data['VLT']['area']
eps = config_data['VLT']['obsc']
elif telescope == 'E-ELT':
D = config_data['E-ELT']['diam']
area = config_data['E-ELT']['area']
eps = config_data['E-ELT']['obsc']
else:
raise ValueError('UNKNOWN TELESCOPE CHOICE: choose E-ELT or VLT')
#Seeing value at zenith distance calculated as:
#X = 1/(n.cos(n.radians(zenith_ang)))
#seeing = seeing*X***(3/5.)
X = 1./(n.cos(n.radians(zenith_ang)))
seeing = seeing*X**(3./5.)
if AO == 'LATO' or AO == 'GLAO' or AO == 'SCAO':
if seeing > 1.1:
print "AO PSFs currently don't support seeing > 1.1'' FWHM"
seeing = 1.1
if seeing < 0.67:
print "AO PSFs currently don't support seeing < 0.67'' FWHM"
seeing = 0.67
print 'Seeing at chosen zenith angle = %.3f arcsec FWHM' % seeing
#CREATE WAVELENGTH ARRAY IN MICRONS
lambs, head = wavelength_array(head)
#Check limits of wavelength array and cut cube into HARMONI wavelength range if neccessary
if grating=='None' and lambs[0] < config_data['gratings']['V+R'][0]:
print 'Cube lowest wavelength lower than HARMONI range'
llim = n.where(lambs > config_data['gratings']['V+R'][0])[0][0]
lambs = lambs[llim:]
cube = cube[llim:,:,:]
head['CRVAL3'] = lambs[0]
if grating=='None' and lambs[-1] > config_data['gratings']['H+K'][1]:
print 'Cube longest wavelength longer than HARMONI range'
hlim = n.where(lambs < config_data['gratings']['H+K'][1])[0][-1]
lambs = lambs[:hlim+1]
cube = cube[:hlim+1,:,:]
head['NAXIS3'] = len(lambs)
#RESCALE DATACUBE TO CHOSEN SPECTRAL RESOLUTION.
if grating == 'Iz+J+H+K':
print 'R = 500 low resolution mode chosen'
cube, head, lambs, delta_lambda, pix_disp, R = low_res_mode(cube, head, lambs)
else:
cube, head, lambs, delta_lambda, pix_disp, R = spectral_res(cube, head, grating, lambs, config_data['gratings'],
spec_nyquist=Spec_nyquist, spec_samp=Spec_samp)
#PSF GENERATION CODE
cube, head, psfspax, psfparams, psfsize, upsf, upsflams = psf_setup(cube, head, lambs, spax,
user_PSF, AO, seeing, [D,eps])
#POINT SOURCE CHECK
if (head['NAXIS1']*head['CDELT1'])/float(spax[0]) < 1. or (head['NAXIS2']*head['CDELT2'])/float(spax[1]) < 1.:
print 'Point source - single spaxel output'
config_data['ADR'] = 'OFF'
cube, head = point_source(cube, head, spax)
#CALCULATE ADR
airmass = 1./n.cos(n.radians(zenith_ang))
refr = calc_ref(lambs, site_temp)
optlam = optimalguide(lambs[0], lambs[-1], site_temp)
adr = calc_adr(lambs, refr, airmass, optlam)
if adr_switch == 'True':
print 'Turning ADR off'
config_data['ADR'] = 'OFF'
#Empty output cube
out_cube = n.zeros((len(lambs),int(head['CDELT2']*head['NAXIS2']/spax[1]),
int(head['CDELT1']*head['NAXIS1']/spax[0])), dtype=n.float64)
print 'Cube shape (lam, y, x) = ', cube.shape
print 'Chosen spaxel scales (x, y) = ', spax
print 'Output cube shape (lam, y, x) = ', out_cube.shape
print 'PSF generation size = ', psfsize
#WAVELENGTH CHANNEL LOOP
print 'Entering loop over wavelength channels'
psfvars = [psfparams, psfspax, psfsize, [D, eps], res_jitter, seeing, upsf, upsflams]
ncpus = nprocs
print 'No. of CPUs: ', ncpus
try:
import pprocess
print 'Using ', str(ncpus), ' CPUs'
except:
print 'No pprocess module'
print 'Using 1 CPU'
ncpus = 1
PSFs = ['LTAO', 'SCAO', 'Gaussian']
if AO in PSFs and ncpus >= 3:
out_cube, head = pp_wavelength_loop(cube, head, lambs, out_cube, AO, psfvars, adr,
(head['NAXIS1']*head['CDELT1']/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
spax, adr_switch=config_data['ADR'], usecpus=ncpus)
elif AO in PSFs and ncpus < 3:
# print 'Using 1 CPU'
out_cube, head = wavelength_loop(cube, head, lambs, out_cube, AO, psfvars, adr,
(head['NAXIS1']*head['CDELT1']/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
spax, adr_switch=config_data['ADR'])
# elif AO == 'Gaussian':
# out_cube, head = pp_wavelength_loop(cube, head, lambs, out_cube, AO, psfvars, adr,
# (head['NAXIS1']*head['CDELT1']/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
# spax, adr_switch=config_data['ADR'])
else:
raise ValueError('UNKNOWN AO CHOICE: choose LTAO, SCAO or Gaussian')
inspax = n.array([head['CDELT1'],head['CDELT2']])*1.E-3
outspax = n.array([spax[0],spax[1]])*1.E-3
head['CDELT1'] = (spax[0], "mas")
head['CDELT2'] = (spax[1], "mas")
head['NAXIS1'] = int(head['NAXIS1']*head['CDELT1']/float(spax[0]))
head['NAXIS2'] = int(head['NAXIS2']*head['CDELT2']/float(spax[1]))
#Remove input cube from memory!
cube = n.zeros((1,1,1))
print 'PSF convolution, ADR effect, spaxel rebinning - all done!'
#Energy-to-Photons Conversion factor will depend on head['FUNITS'] value
if head['FUNITS'] == 'J/s/m2/um/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c)/(lambs*1.E-6) #J
elif head['FUNITS'] == 'erg/s/cm2/A/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c * 1.E7)/(lambs*1.E-6 * 1.E4 * 1.E4) #erg/1.E4(cm2->m2)/1.E4(A->um)
elif head['FUNITS'] == 'J/s/m2/A/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c)/(lambs*1.E-6 * 1.E4) #J/1.E4(A->um)
elif head['FUNITS'] == 'erg/s/cm2/um/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c * 1.E7)/(lambs*1.E-6 * 1.E4) #erg/1.E4(cm2->m2)
else:
raise ValueError('UNKNOWN FLUX UNITS: Please change FUNITS header key to erg/s/cm2/A/arcsec2')
en2ph_conv_fac.shape = (len(lambs),1,1)
#Total throughput cube
throughput_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating,
[config_data['trans_w_grat'],config_data['trans_wo_grat']], sky=True, telescope=True, instrument=True, QE=True)
#Create object cube (enter spaxel as arcsec = mas*1.E-3)
#[units of passed values: lambs: [um], DIT: [s], outspax: [arcsec], pix_disp: [um/pixel], area: [m2]]
out_cube = n.divide(out_cube, en2ph_conv_fac)
object_cube, object_shot_noise, noiseless_object = generate_object_cube(out_cube, lambs, throughput_cube, DIT,
NDIT, outspax, pix_disp, area)
#Instrument + Quantum efficiency cube
inst_qe_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating,
[config_data['trans_w_grat'],config_data['trans_wo_grat']], sky=False, telescope=False, instrument=True, QE=True)
#Quantum efficiency cube
qe_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating,
[config_data['trans_w_grat'],config_data['trans_wo_grat']], sky=False, telescope=False, instrument=False, QE=True)
#Create background cube [sky + telescope + instrument photons]
background_cube, background_shot_noise, noiseless_background = create_background_cube(out_cube.shape, lambs, throughput_cube, inst_qe_cube,
qe_cube, DIT, NDIT, outspax, delta_lambda, pix_disp, area, site_temp, sky=True,
telescope=True, instrument=False, emis=config_data['emissivity'])
#Create observed cube [source + background + dark + SQRT(NDIT)*read]
read_cube, nrc = generate_read_cube(out_cube.shape, lambs, DIT, NDIT, readsig_vis=config_data['read_noise_vis'],
readsig_nirs=[config_data['read_noise_nir'],config_data['read_noise_nir_lowexp']])
dark_cube, noiseless_dark = generate_dark_cube(out_cube.shape, lambs, DIT, NDIT,
vis_dark=config_data['dark_current_vis'], nir_dark=config_data['dark_current_nir'])
observed_cube = object_cube + background_cube + dark_cube + read_cube
observed_noise = generate_noise_cube(noiseless_object, noiseless_background, noiseless_dark, nrc)
#Create separate background measurement cube
background_cube2, background_shot_noise2, noiseless_background2 = create_background_cube(out_cube.shape, lambs, throughput_cube, inst_qe_cube,
qe_cube, DIT, NDIT, outspax, delta_lambda, pix_disp, area, site_temp, sky=True,
telescope=True, instrument=False, emis=config_data['emissivity'])
dark_cube2, noiseless_dark2 = generate_dark_cube(out_cube.shape, lambs, DIT, NDIT,
vis_dark=config_data['dark_current_vis'], nir_dark=config_data['dark_current_nir'])
read_cube2, nrc2 = generate_read_cube(out_cube.shape, lambs, DIT, NDIT, readsig_vis=config_data['read_noise_vis'],
readsig_nirs=[config_data['read_noise_nir'],config_data['read_noise_nir_lowexp']])
background_cube2 = background_cube2 + dark_cube2 + read_cube2
background_noise2 = generate_noise_cube(n.zeros_like(noiseless_object), noiseless_background2, noiseless_dark2, nrc2)
#Return cubes: Observed and background each with noise, or reduced (observed-background) with noise.
#Return as FITS files
#Common headers to add to all cubes
common_header_info = {'DIT': DIT, 'NDIT': NDIT, 'SEEING': seeing, 'ZENITH': zenith_ang, 'AOMODE': AO,
'USER_PSF': user_PSF, 'R': R, 'Grating': grating, 'RES_JITT': res_jitter,
'FUNITS': 'electrons', 'VERSION': version}
outFile_objcube = datacube.split('/')[-1].split('.fits')[0] + '_Object_cube'
outFile_nlobjcube = datacube.split('/')[-1].split('.fits')[0] + '_Noiseless_Object_cube'
outFile_obscube = datacube.split('/')[-1].split('.fits')[0] + '_Observed_cube'
outFile_bgrcube = datacube.split('/')[-1].split('.fits')[0] + '_Background_cube'
outFile_nbgrcube = datacube.split('/')[-1].split('.fits')[0] + '_Noiseless_Background_cube'
outFile_snr = datacube.split('/')[-1].split('.fits')[0] + '_Obs_SNR_cube'
outFile_redcube = datacube.split('/')[-1].split('.fits')[0] + '_Reduced_cube'
outFile_redsnr = datacube.split('/')[-1].split('.fits')[0] + '_Red_SNR_cube'
outFile_trans = datacube.split('/')[-1].split('.fits')[0] + '_Transmission_cube'
#return observed_cube, observed_noise, background_cube2, background_noise2
generate_fits_cube(observed_cube, head, lambs, outFile_obscube, common_header_info, outdir, varext=n.power(observed_noise,2))
generate_fits_cube(background_cube2, head, lambs, outFile_bgrcube, common_header_info, outdir, varext=n.power(background_noise2,2))
generate_fits_cube((noiseless_background2+noiseless_dark2), head, lambs, outFile_nbgrcube, common_header_info, outdir)
generate_fits_cube((noiseless_object/observed_noise), head, lambs, outFile_snr, common_header_info, outdir)
if return_object == 'True':
generate_fits_cube(object_cube, head, lambs, outFile_objcube, common_header_info, outdir)
generate_fits_cube(noiseless_object, head, lambs, outFile_nlobjcube, common_header_info, outdir)
if remove_background == 'True':
reduced_cube = n.subtract(observed_cube, background_cube2)
reduced_noise = generate_noise_cube(noiseless_object, 2.*noiseless_background,
2.*noiseless_dark, n.sqrt(2.)*nrc2)
generate_fits_cube(reduced_cube, head, lambs, outFile_redcube, common_header_info, outdir, varext=n.power(reduced_noise,2))
generate_fits_cube((noiseless_object/reduced_noise), head, lambs, outFile_redsnr, common_header_info, outdir)
if return_transmission == 'True':
generate_fits_cube(throughput_cube, head, lambs, outFile_trans, common_header_info, outdir)
print 'Output cubes created!'
print ' -------- '
print 'Inbuilt Telescope Parameters'
print ' -------- '
print 'Telescope diameter = %.1f [m]' % D
print 'Telescope obscuration ratio = %.2f' % eps
print 'Telescope area = %.2f [m^2]' % area
print 'Telescope emissivity = %.2f ' % config_data['emissivity']
print 'Telescope temperature = %.1f [K]' % site_temp
print 'AO mode = ', AO
print ' -------- '
print 'Inbuilt Instrument Parameters'
print ' -------- '
print 'Wavelength range = %.4g [A] to %.4g [A]' % (lambs[0]*10000., lambs[-1]*10000.)
print 'Spectral resolving power = %.0i' % R
if R == 500.:
print 'Spectral resolution = variable'
print 'Spectral sampling = 2 pixels per FWHM'
else:
print 'Spectral resolution = %.3f [A]' % (delta_lambda*10000.)
print 'Spectral sampling = %.3f [A/pix]' % (pix_disp*10000.)
print 'Spatial scale = (%.1f mas, %.1f mas)' % (spax[0], spax[1])
print 'Detector dark current = %.4f [e-/s/pixel] for visible' % config_data['dark_current_vis']
print ' = %.4f [e-/s/pixel] for near-IR' % config_data['dark_current_nir']
print 'Detector read noise = %.3f [e-/pixel] RMS for visible' % config_data['read_noise_vis']
print ' = %.3f [e-/pixel] RMS for near-IR [DIT>120s]' % config_data['read_noise_nir']
print ' = %.3f [e-/pixel] RMS for near-IR [DIT<=120s]' % config_data['read_noise_nir_lowexp']
print ' Cut-off at 0.8 um.'
print ' '
print 'Simulation Complete!'
def main(datacube, outdir, DIT, NDIT, grating, spax, seeing, zenith_ang, telescope='E-ELT', user_PSF='None',
AO='SCAO', res_jitter=0, site_temp=280.5, combine_ndits=True, Spec_nyquist=True, Spec_samp=1.,
noise_force_seed=0, remove_background='False', return_object='False', return_transmission='False',
adr_switch='True', version='1', nprocs=mp.cpu_count()-1):
'''Main body of code: gathers all inputs and calls all functions
to generate outputs.
Inputs:
datacube: Input high resolution datacube (RA, DEC, lambda)
outdir: Output file directory
DIT: Exposure time [s]
NDIT: No. of exposures
grating: Spectral grating
spax: spatial pixel (spaxel) scale [mas]
seeing: Atmospheric seeing FWHM [arcsec]
zenith_ang: Zenith angle [deg]
telescope: Telescope type (E-ELT, VLT)
user_PSF: Path to user uploaded PSF file
AO: AO mode (LTAO, SCAO, Gaussian)
res_jitter: Residual telescope jitter [mas]
site_temp: Telescope temperature [K]
combine_ndits: Boolean - Combine NDITS
spec_Nyquist: Boolean - Set spectral sampling to Nyquist sample spectral resolution element
Spec_samp: Spectral sampling [A/pix] - used if spec_Nyquist = False
noise_force_seed: Force random number seed to take a set value (0=No, 1-10=yes and takes that value)
remove_background: Boolean - Subtract background spectrum
return_object: Boolean - Return object cube
return_transmission: Boolean - Return throughput cube
adr_switch: Boolean - turn ADR on or off.
version: Version of code. Equal to SVN revision number'
nprocs: no. of processes to use for parallel processing
Outputs:
observed_cube: FITS file of datacube representing HARMONI observation of input cube
background_cube: FITS file of datacube representing background sources
reduced_cube: FITS file of observed datacube after subtracting background
noise_cube: FITS file of noise for each pixel in datacube
'''
print 'Filename: ', datacube
print 'Output dir: ', outdir
print 'DIT = ', DIT
print 'NINT = ', NDIT
print 'X spaxels = ', spax[0]
print 'Y spaxels = ', spax[1]
print 'Grating = ', grating
print 'Telescope: ', telescope
print 'AO = ', AO
print 'Seeing = ', seeing
print 'Zenith angle = ', zenith_ang
print 'Residual jitter = ', res_jitter
print 'Temperature = ', site_temp
print 'combine NINTS? ', combine_ndits
print 'Noise seed = ', noise_force_seed
print 'Spectral Nyquist sampling? ', Spec_nyquist
print 'Subtract background? ', remove_background
print 'User PSF? ' , user_PSF
print 'Return Object cube?', return_object
print 'Return transmission?', return_transmission
print 'ADR off?', adr_switch
print 'No. of processes = ', nprocs
#Generate random number seed
seednum = generate_seed(noise_force_seed)
n.random.seed(seednum)
#OPEN INPUT FITS file
if os.path.isfile(datacube) == True and os.path.splitext(datacube)[1].lower() == '.fits':
cube, head = p.getdata(datacube, 0, header=True, memmap=True)
#If not FITS file, try passing datacube directly
else:
try:
cube = datacube.data
head = datacube.header
except:
raise ValueError('UNKNOWN INPUT FILE FORMAT: Please use FITS file')
#Check that datacube has required headers to be processed in simulator
#Required headers = ['CDELT1/2/3'], ['CRVAL3'], ['NAXIS1/2/3'], ['FUNITS'], ['CRPIX3'] = 1,
#['CTYPE1/2/3'] = 'RA, DEC, WAVELENGTH, ['CUNIT1/2/3'] = MAS, MAS, microns/angstroms/etc,
#['SPECRES'].
fits_header_check(head)
pp.pprint(head)
#telescope options = 'VLT', 'E-ELT'
#Sets diameter D, M1 collecting area and obscuration ratio eps
if telescope == 'VLT':
D = config_data['VLT']['diam']
area = config_data['VLT']['area']
eps = config_data['VLT']['obsc']
elif telescope == 'E-ELT':
D = config_data['E-ELT']['diam']
area = config_data['E-ELT']['area']
eps = config_data['E-ELT']['obsc']
else:
raise ValueError('UNKNOWN TELESCOPE CHOICE: choose E-ELT or VLT')
#Seeing value at zenith distance calculated as:
#X = 1/(n.cos(n.radians(zenith_ang)))
#seeing = seeing*X***(3/5.)
X = 1./(n.cos(n.radians(zenith_ang)))
seeing = seeing*X**(3./5.)
if AO == 'LTAO' or AO == 'GLAO' or AO == 'SCAO':
if seeing > 1.1:
print "AO PSFs currently don't support seeing > 1.1'' FWHM"
seeing = 1.1
if seeing < 0.67:
print "AO PSFs currently don't support seeing < 0.67'' FWHM"
seeing = 0.67
print 'Seeing at chosen zenith angle = %.3f arcsec FWHM' % seeing
#CREATE WAVELENGTH ARRAY IN MICRONS
lambs, head = wavelength_array(head)
#Check limits of wavelength array and cut cube into HARMONI wavelength range if neccessary
if grating=='None' and lambs[0] < config_data['gratings']['V+R'][0]:
print 'Cube lowest wavelength lower than HARMONI range'
llim = n.where(lambs > config_data['gratings']['V+R'][0])[0][0]
lambs = lambs[llim:]
cube = cube[llim:,:,:]
head['CRVAL3'] = lambs[0]
if grating=='None' and lambs[-1] > config_data['gratings']['H+K'][1]:
print 'Cube longest wavelength longer than HARMONI range'
hlim = n.where(lambs < config_data['gratings']['H+K'][1])[0][-1]
lambs = lambs[:hlim+1]
cube = cube[:hlim+1,:,:]
head['NAXIS3'] = len(lambs)
#RESCALE DATACUBE TO CHOSEN SPECTRAL RESOLUTION.
if grating == 'Iz+J+H+K':
print 'R = 500 low resolution mode chosen'
cube, head, lambs, delta_lambda, pix_disp, R = low_res_mode(cube, head, lambs)
else:
cube, head, lambs, delta_lambda, pix_disp, R = spectral_res(cube, head, grating, lambs, config_data['gratings'],
spec_nyquist=Spec_nyquist, spec_samp=Spec_samp)
#PSF GENERATION CODE
cube, head, psfspax, psfparams, psfsize, upsf, upsflams = psf_setup(cube, head, lambs, spax,
user_PSF, AO, seeing, [D,eps])
#POINT SOURCE CHECK
if (head['NAXIS1']*head['CDELT1'])/float(spax[0]) < 1. or (head['NAXIS2']*head['CDELT2'])/float(spax[1]) < 1.:
print 'Point source - single spaxel output'
config_data['ADR'] = 'OFF'
cube, head = point_source(cube, head, spax)
#CALCULATE ADR
airmass = 1./n.cos(n.radians(zenith_ang))
refr = calc_ref(lambs, site_temp)
optlam = optimalguide(lambs[0], lambs[-1], site_temp)
adr = calc_adr(lambs, refr, airmass, optlam)
if adr_switch == 'True':
print 'Turning ADR off'
config_data['ADR'] = 'OFF'
#Empty output cube
out_cube = n.zeros((len(lambs),int(head['CDELT2']*head['NAXIS2']/spax[1]),
int(head['CDELT1']*head['NAXIS1']/spax[0])), dtype=n.float64)
print 'Cube shape (lam, y, x) = ', cube.shape
print 'Chosen spaxel scales (x, y) = ', spax
print 'Output cube shape (lam, y, x) = ', out_cube.shape
print 'PSF generation size = ', psfsize
#WAVELENGTH CHANNEL LOOP
print 'Entering loop over wavelength channels'
psfvars = [psfparams, psfspax, psfsize, [D, eps], res_jitter, seeing, upsf, upsflams]
ncpus = nprocs
print 'No. of CPUs: ', ncpus
try:
import pprocess
print 'Using ', str(ncpus), ' CPUs'
except:
print 'No pprocess module'
print 'Using 1 CPU'
ncpus = 1
PSFs = ['LTAO', 'SCAO', 'Gaussian']
if AO in PSFs and ncpus >= 3:
out_cube, head = pp_wavelength_loop(cube, head, lambs, out_cube, AO, psfvars, adr,
(head['NAXIS1']*head['CDELT1']/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
spax, adr_switch=config_data['ADR'], usecpus=ncpus)
elif AO in PSFs and ncpus < 3:
# print 'Using 1 CPU'
out_cube, head = wavelength_loop(cube, head, lambs, out_cube, AO, psfvars, adr,
(head['NAXIS1']*head['CDELT1']/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
spax, adr_switch=config_data['ADR'])
# elif AO == 'Gaussian':
# out_cube, head = pp_wavelength_loop(cube, head, lambs, out_cube, AO, psfvars, adr,
# (head['NAXIS1']*head['CDELT1']/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
# spax, adr_switch=config_data['ADR'])
else:
raise ValueError('UNKNOWN AO CHOICE: choose LTAO, SCAO or Gaussian')
inspax = n.array([head['CDELT1'],head['CDELT2']])*1.E-3
outspax = n.array([spax[0],spax[1]])*1.E-3
head['CDELT1'] = (spax[0], "mas")
head['CDELT2'] = (spax[1], "mas")
head['NAXIS1'] = int(head['NAXIS1']*head['CDELT1']/float(spax[0]))
head['NAXIS2'] = int(head['NAXIS2']*head['CDELT2']/float(spax[1]))
#Remove input cube from memory!
cube = n.zeros((1,1,1))
print 'PSF convolution, ADR effect, spaxel rebinning - all done!'
#Energy-to-Photons Conversion factor will depend on head['FUNITS'] value
if head['FUNITS'] == 'J/s/m2/um/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c)/(lambs*1.E-6) #J
elif head['FUNITS'] == 'erg/s/cm2/A/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c * 1.E7)/(lambs*1.E-6 * 1.E4 * 1.E4) #erg/1.E4(cm2->m2)/1.E4(A->um)
elif head['FUNITS'] == 'J/s/m2/A/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c)/(lambs*1.E-6 * 1.E4) #J/1.E4(A->um)
elif head['FUNITS'] == 'erg/s/cm2/um/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c * 1.E7)/(lambs*1.E-6 * 1.E4) #erg/1.E4(cm2->m2)
else:
raise ValueError('UNKNOWN FLUX UNITS: Please change FUNITS header key to erg/s/cm2/A/arcsec2')
en2ph_conv_fac.shape = (len(lambs),1,1)
#Total throughput cube
throughput_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating, zenith_ang,
[config_data['trans_w_grat'],config_data['trans_wo_grat']], sky=True, telescope=True, instrument=True, QE=True)
#Create object cube (enter spaxel as arcsec = mas*1.E-3)
#[units of passed values: lambs: [um], DIT: [s], outspax: [arcsec], pix_disp: [um/pixel], area: [m2]]
out_cube = n.divide(out_cube, en2ph_conv_fac)
object_cube, object_shot_noise, noiseless_object = generate_object_cube(out_cube, lambs, throughput_cube, DIT,
NDIT, outspax, pix_disp, area)
#Instrument + Quantum efficiency cube
inst_qe_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating, zenith_ang,
[config_data['trans_w_grat'],config_data['trans_wo_grat']], sky=False, telescope=False, instrument=True, QE=True)
#Quantum efficiency cube
qe_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating, zenith_ang,
[config_data['trans_w_grat'],config_data['trans_wo_grat']], sky=False, telescope=False, instrument=False, QE=True)
#Create background cube [sky + telescope + instrument photons]
background_cube, background_shot_noise, noiseless_background = create_background_cube(out_cube.shape, lambs, throughput_cube, inst_qe_cube,
qe_cube, DIT, NDIT, outspax, delta_lambda, pix_disp, area, site_temp, sky=True,
telescope=True, instrument=False, emis=config_data['emissivity'])
#Create observed cube [source + background + dark + SQRT(NDIT)*read]
read_cube, nrc = generate_read_cube(out_cube.shape, lambs, DIT, NDIT, readsig_vis=config_data['read_noise_vis'],
readsig_nirs=[config_data['read_noise_nir'],config_data['read_noise_nir_lowexp']])
dark_cube, noiseless_dark = generate_dark_cube(out_cube.shape, lambs, DIT, NDIT,
vis_dark=config_data['dark_current_vis'], nir_dark=config_data['dark_current_nir'])
observed_cube = object_cube + background_cube + dark_cube + read_cube
observed_noise = generate_noise_cube(noiseless_object, noiseless_background, noiseless_dark, nrc)
#Create separate background measurement cube
background_cube2, background_shot_noise2, noiseless_background2 = create_background_cube(out_cube.shape, lambs, throughput_cube, inst_qe_cube,
qe_cube, DIT, NDIT, outspax, delta_lambda, pix_disp, area, site_temp, sky=True,
telescope=True, instrument=False, emis=config_data['emissivity'])
dark_cube2, noiseless_dark2 = generate_dark_cube(out_cube.shape, lambs, DIT, NDIT,
vis_dark=config_data['dark_current_vis'], nir_dark=config_data['dark_current_nir'])
read_cube2, nrc2 = generate_read_cube(out_cube.shape, lambs, DIT, NDIT, readsig_vis=config_data['read_noise_vis'],
readsig_nirs=[config_data['read_noise_nir'],config_data['read_noise_nir_lowexp']])
background_cube2 = background_cube2 + dark_cube2 + read_cube2
background_noise2 = generate_noise_cube(n.zeros_like(noiseless_object), noiseless_background2, noiseless_dark2, nrc2)
#Return cubes: Observed and background each with noise, or reduced (observed-background) with noise.
#Return as FITS files
#Common headers to add to all cubes
common_header_info = {'DIT': DIT, 'NDIT': NDIT, 'SEEING': seeing, 'ZENITH': zenith_ang, 'AOMODE': AO,
'USER_PSF': user_PSF, 'R': R, 'Grating': grating, 'RES_JITT': res_jitter,
'FUNITS': 'electrons', 'VERSION': version}
outFile_objcube = datacube.split('/')[-1].split('.fits')[0] + '_Object_cube'
outFile_nlobjcube = datacube.split('/')[-1].split('.fits')[0] + '_Noiseless_Object_cube'
outFile_obscube = datacube.split('/')[-1].split('.fits')[0] + '_Observed_cube'
outFile_bgrcube = datacube.split('/')[-1].split('.fits')[0] + '_Background_cube'
outFile_nbgrcube = datacube.split('/')[-1].split('.fits')[0] + '_Noiseless_Background_cube'
outFile_snr = datacube.split('/')[-1].split('.fits')[0] + '_Obs_SNR_cube'
outFile_redcube = datacube.split('/')[-1].split('.fits')[0] + '_Reduced_cube'
outFile_redsnr = datacube.split('/')[-1].split('.fits')[0] + '_Red_SNR_cube'
outFile_trans = datacube.split('/')[-1].split('.fits')[0] + '_Transmission_cube'
#return observed_cube, observed_noise, background_cube2, background_noise2
generate_fits_cube(observed_cube, head, lambs, outFile_obscube, common_header_info, outdir, varext=n.power(observed_noise,2))
generate_fits_cube(background_cube2, head, lambs, outFile_bgrcube, common_header_info, outdir, varext=n.power(background_noise2,2))
generate_fits_cube((noiseless_background2+noiseless_dark2), head, lambs, outFile_nbgrcube, common_header_info, outdir)
generate_fits_cube((noiseless_object/observed_noise), head, lambs, outFile_snr, common_header_info, outdir)
if return_object == 'True':
generate_fits_cube(object_cube, head, lambs, outFile_objcube, common_header_info, outdir)
generate_fits_cube(noiseless_object, head, lambs, outFile_nlobjcube, common_header_info, outdir)
if remove_background == 'True':
reduced_cube = n.subtract(observed_cube, background_cube2)
reduced_noise = generate_noise_cube(noiseless_object, 2.*noiseless_background,
2.*noiseless_dark, n.sqrt(2.)*nrc2)
generate_fits_cube(reduced_cube, head, lambs, outFile_redcube, common_header_info, outdir, varext=n.power(reduced_noise,2))
generate_fits_cube((noiseless_object/reduced_noise), head, lambs, outFile_redsnr, common_header_info, outdir)
if return_transmission == 'True':
generate_fits_cube(throughput_cube, head, lambs, outFile_trans, common_header_info, outdir)
print 'Output cubes created!'
print ' -------- '
print 'Inbuilt Telescope Parameters'
print ' -------- '
print 'Telescope diameter = %.1f [m]' % D
print 'Telescope obscuration ratio = %.2f' % eps
print 'Telescope area = %.2f [m^2]' % area
print 'Telescope emissivity = %.2f ' % config_data['emissivity']
print 'Telescope temperature = %.1f [K]' % site_temp
print 'AO mode = ', AO
print ' -------- '
print 'Inbuilt Instrument Parameters'
print ' -------- '
print 'Wavelength range = %.4g [A] to %.4g [A]' % (lambs[0]*10000., lambs[-1]*10000.)
print 'Spectral resolving power = %.0i' % R
if R == 500.:
print 'Spectral resolution = variable'
print 'Spectral sampling = 2 pixels per FWHM'
else:
print 'Spectral resolution = %.3f [A]' % (delta_lambda*10000.)
print 'Spectral sampling = %.3f [A/pix]' % (pix_disp*10000.)
print 'Spatial scale = (%.1f mas, %.1f mas)' % (spax[0], spax[1])
print 'Detector dark current = %.4f [e-/s/pixel] for visible' % config_data['dark_current_vis']
print ' = %.4f [e-/s/pixel] for near-IR' % config_data['dark_current_nir']
print 'Detector read noise = %.3f [e-/pixel] RMS for visible' % config_data['read_noise_vis']
print ' = %.3f [e-/pixel] RMS for near-IR [DIT>120s]' % config_data['read_noise_nir']
print ' = %.3f [e-/pixel] RMS for near-IR [DIT<=120s]' % config_data['read_noise_nir_lowexp']
print ' Cut-off at 0.8 um.'
print ' '
print 'Simulation Complete!'
def main(datacube, outdir, DIT, NDIT, grating, ignoreLSF, res_jitter=0,
site_temp=280.5, combine_ndits=True, Spec_nyquist=True, Spec_samp=1.,
noise_force_seed=0, remove_background='False', return_object='False',
return_transmission='False', drizzle=0, version='1', nprocs=mp.cpu_count()-1):
'''Main body of code: gathers all inputs and calls all functions
to generate outputs.
Inputs:
datacube: Input high resolution datacube (RA, DEC, lambda)
outdir: Output file directory
DIT: Exposure time [s]
NDIT: No. of exposures
grating: Spectral grating
ignoreLSF: turn off LSF convolution in spectral dimension
res_jitter: Residual telescope jitter [mas]
site_temp: Telescope temperature [K]
combine_ndits: Boolean - Combine NDITS
spec_Nyquist: Boolean - Set spectral sampling to Nyquist sample spectral resolution element
Spec_samp: Spectral sampling [A/pix] - used if spec_Nyquist = False
noise_force_seed: Force random number seed to take a set value (0=No, 1-10=yes and takes that value)
remove_background: Boolean - Subtract background spectrum
return_object: Boolean - Return object cube
return_transmission: Boolean - Return throughput cube
drizzle: Boolean - Output sampling of 50 mas
version: Version of code. Equal to SVN revision number'
nprocs: no. of processes to use for parallel processing
Outputs:
observed_cube: FITS file of datacube representing HARMONI observation of input cube
background_cube: FITS file of datacube representing background sources
reduced_cube: FITS file of observed datacube after subtracting background
noise_cube: FITS file of noise for each pixel in datacube
'''
print 'Filename: ', datacube
print 'Output dir: ', outdir
print 'DIT = ', DIT
print 'NINT = ', NDIT
print 'Grating = ', grating
print 'Ignore LSF?', ignoreLSF
print 'Residual jitter = ', res_jitter
print 'Temperature = ', site_temp
print 'combine NINTS? ', combine_ndits
print 'Noise seed = ', noise_force_seed
print 'Spectral Nyquist sampling? ', Spec_nyquist
print 'Subtract background? ', remove_background
print 'Return Object cube?', return_object
print 'Return transmission?', return_transmission
print 'Drizzle?', drizzle
print 'No. of processes = ', nprocs
#Generate random number seed
seednum = generate_seed(noise_force_seed)
n.random.seed(seednum)
#Spaxels
if drizzle:
spax = (50., 50.)
else:
spax = config_data['spaxels']
#OPEN INPUT FITS file
if os.path.isfile(datacube) == True and os.path.splitext(datacube)[1].lower() == '.fits':
cube, head = p.getdata(datacube, 0, header=True, memmap=True)
#If not FITS file, try passing datacube directly
else:
try:
cube = datacube.data
head = datacube.header
except:
raise ValueError('UNKNOWN INPUT FILE FORMAT: Please use FITS file')
#Check that datacube has required headers to be processed in simulator
#Required headers = ['CDELT1/2/3'], ['CRVAL3'], ['NAXIS1/2/3'], ['FUNITS'], ['CRPIX3'] = 1,
#['CTYPE1/2/3'] = 'RA, DEC, WAVELENGTH, ['CUNIT1/2/3'] = MAS, MAS, microns/angstroms/etc,
#['SPECRES'].
fits_header_check(head)
pp.pprint(head)
#CREATE WAVELENGTH ARRAY IN MICRONS
lambs, head = wavelength_array(head)
#RESCALE DATACUBE TO CHOSEN SPECTRAL RESOLUTION.
if grating == 'Prism':
print 'Prism low resolution mode chosen'
cube, head, lambs, delta_lambda, pix_disp, R = low_res_mode(cube, head, lambs)
else:
cube, head, lambs, delta_lambda, pix_disp, R = spectral_res(cube, head, grating, lambs, config_data['gratings'],
spec_nyquist=Spec_nyquist, spec_samp=Spec_samp,
ignoreLSF=ignoreLSF)
#POINT SOURCE CHECK
if (head['NAXIS1']*head['CDELT1'])/float(spax[0]) < 1. or (head['NAXIS2']*head['CDELT2'])/float(spax[1]) < 1.:
print 'Point source - single spaxel output'
config_data['ADR'] = 'OFF'
cube, head = point_source(cube, head, spax)
#REBIN CUBE TO 10 MAS
print 'Input datacube sampling = (%.1f, %.1f) mas' % (head['CDELT1'], head['CDELT2'])
print 'Input PSF sampling = (%.1f, %.1f) mas' % (spax[0]/10.,spax[1]/10.)
if head['CDELT1'] != spax[0] and head['CDELT2'] != spax[1]:
print 'Rebinning input datacube to %.0f mas (same as PSF generation scale)' % (spax[0]/10.)
cube *= (head['CDELT1']*head['CDELT2']*1.E-6)
cube, head = spaxel_scale(cube, head, (spax[0]/10.,spax[0]/10.))
cube /= (head['CDELT1']*head['CDELT2']*1.E-6)
#Empty output cube
out_cube = n.zeros((len(lambs),int(head['CDELT2']*head['NAXIS2']/spax[1]),
int(head['CDELT1']*head['NAXIS1']/spax[0])), dtype=n.float64)
print 'Input spaxel scale (x, y)', (head['CDELT1'], head['CDELT2']), ' mas'
print 'Cube shape (lam, y, x) = ', cube.shape
print 'Output spaxel scale (x, y) = ', spax, ' mas'
print 'Output cube shape (lam, y, x) = ', out_cube.shape
#WAVELENGTH CHANNEL LOOP
print 'Entering loop over wavelength channels'
ncpus = nprocs
print 'No. of CPUs: ', ncpus
try:
import pprocess
print 'Using ', str(ncpus), ' CPUs'
except:
print 'No pprocess module'
print 'Using 1 CPU'
ncpus = 1
if ncpus >= 3:
out_cube, head = pp_wavelength_loop(cube, head, lambs, out_cube,
((head['NAXIS1']*head['CDELT1'])/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
spax, usecpus=ncpus)
elif ncpus < 3:
print 'Using 1 CPU'
out_cube, head = wavelength_loop(cube, head, lambs, out_cube,
((head['NAXIS1']*head['CDELT1'])/float(spax[0]),head['NAXIS2']*head['CDELT2']/float(spax[1])),
spax)
else:
raise ValueError('Something went wrong at Loop stage!')
inspax = n.array([head['CDELT1'],head['CDELT2']])*1.E-3
outspax = n.array([spax[0],spax[1]])*1.E-3
head['CDELT1'] = (spax[0], "mas")
head['CDELT2'] = (spax[1], "mas")
head['NAXIS1'] = int(head['NAXIS1']*head['CDELT1']/float(spax[0]))
head['NAXIS2'] = int(head['NAXIS2']*head['CDELT2']/float(spax[1]))
#Remove input cube from memory!
cube = n.zeros((1,1,1))
print 'PSF convolution, ADR effect, spaxel rebinning - all done!'
#Energy-to-Photons Conversion factor will depend on head['FUNITS'] value
if head['FUNITS'] == 'J/s/m2/um/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c)/(lambs*1.E-6) #J
elif head['FUNITS'] == 'erg/s/cm2/A/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c * 1.E7)/(lambs*1.E-6 * 1.E4 * 1.E4) #erg/1.E4(cm2->m2)/1.E4(A->um)
elif head['FUNITS'] == 'J/s/m2/A/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c)/(lambs*1.E-6 * 1.E4) #J/1.E4(A->um)
elif head['FUNITS'] == 'erg/s/cm2/um/arcsec2':
print 'Flux units = ', head['FUNITS']
en2ph_conv_fac = (sc.h * sc.c * 1.E7)/(lambs*1.E-6 * 1.E4) #erg/1.E4(cm2->m2)
else:
raise ValueError('UNKNOWN FLUX UNITS: Please change FUNITS header key to erg/s/cm2/A/arcsec2')
en2ph_conv_fac.shape = (len(lambs),1,1)
#Total throughput cube
throughput_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating, telescope=True, instrument=True)
#Create object cube (enter spaxel as arcsec = mas*1.E-3)
#[units of passed values: lambs: [um], DIT: [s], outspax: [arcsec], pix_disp: [um/pixel], area: [m2]]
out_cube = n.divide(out_cube, en2ph_conv_fac)
object_cube, object_shot_noise, noiseless_object = generate_object_cube(out_cube, lambs, throughput_cube, DIT,
NDIT, outspax, pix_disp, config_data['area'])
#Instrument throughput cube
inst_qe_cube = create_thruput_cube(out_cube.shape, lambs, delta_lambda, grating, telescope=False, instrument=True)
#Create background cube [sky + telescope + instrument photons]
background_cube, background_shot_noise, noiseless_background = create_background_cube(out_cube.shape, lambs, throughput_cube, inst_qe_cube,
DIT, NDIT, outspax, delta_lambda, pix_disp, config_data['area'], site_temp,
sky=True, telescope=False, emis=config_data['emissivity'])
#Create observed cube [source + background + dark + SQRT(NDIT)*read]
read_cube, nrc = generate_read_cube(out_cube.shape, lambs, DIT, NDIT, readsig_vis=config_data['read_noise'],
readsig_nirs=[config_data['read_noise'],config_data['read_noise']])
dark_cube, noiseless_dark = generate_dark_cube(out_cube.shape, lambs, DIT, NDIT,
vis_dark=config_data['dark_current'], nir_dark=config_data['dark_current'])
observed_cube = object_cube + background_cube + dark_cube + read_cube
observed_noise = generate_noise_cube(noiseless_object, noiseless_background, noiseless_dark, nrc)
#Create separate background measurement cube
background_cube2, background_shot_noise2, noiseless_background2 = create_background_cube(out_cube.shape, lambs, throughput_cube, inst_qe_cube,
DIT, NDIT, outspax, delta_lambda, pix_disp, config_data['area'], site_temp,
sky=True, telescope=False, emis=config_data['emissivity'])
dark_cube2, noiseless_dark2 = generate_dark_cube(out_cube.shape, lambs, DIT, NDIT,
vis_dark=config_data['dark_current'], nir_dark=config_data['dark_current'])
read_cube2, nrc2 = generate_read_cube(out_cube.shape, lambs, DIT, NDIT, readsig_vis=config_data['read_noise'],
readsig_nirs=[config_data['read_noise'],config_data['read_noise']])
background_cube2 = background_cube2 + dark_cube2 + read_cube2
background_noise2 = generate_noise_cube(n.zeros_like(noiseless_object), noiseless_background2, noiseless_dark2, nrc2)
#Return cubes: Observed and background each with noise, or reduced (observed-background) with noise.
#Return as FITS files
#Common headers to add to all cubes
common_header_info = {'DIT': DIT, 'NDIT': NDIT, 'R': R, 'Grating': grating,
'RES_JITT': res_jitter, 'FUNITS': 'electrons', 'VERSION': version}
outFile_objcube = datacube.split('/')[-1].split('.fits')[0] + '_Object_cube'
outFile_nlobjcube = datacube.split('/')[-1].split('.fits')[0] + '_Noiseless_Object_cube'
outFile_obscube = datacube.split('/')[-1].split('.fits')[0] + '_Observed_cube'
outFile_bgrcube = datacube.split('/')[-1].split('.fits')[0] + '_Background_cube'
outFile_nbgrcube = datacube.split('/')[-1].split('.fits')[0] + '_Noiseless_Background_cube'
outFile_snr = datacube.split('/')[-1].split('.fits')[0] + '_Obs_SNR_cube'
outFile_redcube = datacube.split('/')[-1].split('.fits')[0] + '_Reduced_cube'
outFile_redsnr = datacube.split('/')[-1].split('.fits')[0] + '_Red_SNR_cube'
outFile_trans = datacube.split('/')[-1].split('.fits')[0] + '_Transmission_cube'
#return observed_cube, observed_noise, background_cube2, background_noise2
generate_fits_cube(observed_cube, head, lambs, outFile_obscube, common_header_info, outdir, varext=n.power(observed_noise,2))
generate_fits_cube(background_cube2, head, lambs, outFile_bgrcube, common_header_info, outdir, varext=n.power(background_noise2,2))
generate_fits_cube((noiseless_background2+noiseless_dark2), head, lambs, outFile_nbgrcube, common_header_info, outdir)
generate_fits_cube((noiseless_object/observed_noise), head, lambs, outFile_snr, common_header_info, outdir)
if return_object == 'True':
generate_fits_cube(object_cube, head, lambs, outFile_objcube, common_header_info, outdir)
generate_fits_cube(noiseless_object, head, lambs, outFile_nlobjcube, common_header_info, outdir)
if remove_background == 'True':
reduced_cube = n.subtract(observed_cube, background_cube2)
reduced_noise = generate_noise_cube(noiseless_object, 2.*noiseless_background,
2.*noiseless_dark, n.sqrt(2.)*nrc2)
generate_fits_cube(reduced_cube, head, lambs, outFile_redcube, common_header_info, outdir, varext=n.power(reduced_noise,2))
generate_fits_cube((noiseless_object/reduced_noise), head, lambs, outFile_redsnr, common_header_info, outdir)
if return_transmission == 'True':
generate_fits_cube(throughput_cube, head, lambs, outFile_trans, common_header_info, outdir)
print 'Output cubes created!'
print ' -------- '
print 'Inbuilt Telescope Parameters'
print ' -------- '
print 'Telescope area = %.2f [m^2]' % config_data['area']
print 'Telescope emissivity = %.2f ' % config_data['emissivity']
print 'Telescope temperature = %.1f [K]' % site_temp
print ' -------- '
print 'Inbuilt Instrument Parameters'
print ' -------- '
print 'Wavelength range = %.4g [A] to %.4g [A]' % (lambs[0]*10000., lambs[-1]*10000.)
print 'Spectral resolving power = %.0i' % R
if R == 100.:
print 'Spectral resolution = variable'
print 'Spectral sampling = 2 pixels per FWHM'
else:
print 'Spectral resolution = %.3f [A]' % (delta_lambda*10000.)
print 'Spectral sampling = %.3f [A/pix]' % (pix_disp*10000.)
print 'Spatial scale = (%.1f mas, %.1f mas)' % (spax[0], spax[1])
print 'Detector dark current = %.4f [e-/s/pixel]' % config_data['dark_current']
print 'Detector read noise = %.4f [e-/pixel] RMS [DIT>120s]' % config_data['read_noise']
print ' = %.4f [e-/pixel] RMS [DIT<=120s]' % config_data['read_noise']
print ' '
print 'Simulation Complete!'
