def wfirst_phaseb(lambda_m, output_dim0, PASSVALUE={'dummy': 0}):
# "output_dim" is used to specify the output dimension in pixels at the final image plane.
# Computational grid sizes are hardcoded for each coronagraph.
# Based on Zemax prescription "WFIRST_CGI_DI_LOWFS_Sep24_2018.zmx" by Hong Tang.
data_dir = wfirst_phaseb_proper.data_dir
if 'PASSVALUE' in locals():
if 'data_dir' in PASSVALUE: data_dir = PASSVALUE['data_dir']
map_dir = data_dir + wfirst_phaseb_proper.map_dir
polfile = data_dir + wfirst_phaseb_proper.polfile
cor_type = 'hlc' # coronagraph type ('hlc', 'spc', 'none')
source_x_offset_mas = 0 # source offset in mas (tilt applied at primary)
source_y_offset_mas = 0
source_x_offset = 0 # source offset in lambda0_m/D radians (tilt applied at primary)
source_y_offset = 0
polaxis = 0 # polarization axis aberrations:
# -2 = -45d in, Y out
# -1 = -45d in, X out
# 1 = +45d in, X out
# 2 = +45d in, Y out
# 5 = mean of modes -1 & +1 (X channel polarizer)
# 6 = mean of modes -2 & +2 (Y channel polarizer)
# 10 = mean of all modes (no polarization filtering)
use_errors = 1 # use optical surface phase errors? 1 or 0
zindex = np.array([0, 0]) # array of Zernike polynomial indices
zval_m = np.array([0, 0]) # array of Zernike coefficients (meters RMS WFE)
use_aperture = 0 # use apertures on all optics? 1 or 0
cgi_x_shift_pupdiam = 0 # X,Y shear of wavefront at FSM (bulk displacement of CGI); normalized relative to pupil diameter
cgi_y_shift_pupdiam = 0
cgi_x_shift_m = 0 # X,Y shear of wavefront at FSM (bulk displacement of CGI) in meters
cgi_y_shift_m = 0
fsm_x_offset_mas = 0 # offset in focal plane caused by tilt of FSM in mas
fsm_y_offset_mas = 0
fsm_x_offset = 0 # offset in focal plane caused by tilt of FSM in lambda0/D
fsm_y_offset = 0
end_at_fsm = 0 # end propagation after propagating to FSM (no FSM errors)
focm_z_shift_m = 0 # offset (meters) of focus correction mirror (+ increases path length)
use_hlc_dm_patterns = 0 # use Dwight's HLC default DM wavefront patterns? 1 or 0
use_dm1 = 0 # use DM1? 1 or 0
use_dm2 = 0 # use DM2? 1 or 0
dm_sampling_m = 0.9906e-3 # actuator spacing in meters
dm1_xc_act = 23.5 # for 48x48 DM, wavefront centered at actuator intersections: (0,0) = 1st actuator center
dm1_yc_act = 23.5
dm1_xtilt_deg = 0 # tilt around X axis (deg)
dm1_ytilt_deg = 5.7 # effective DM tilt in deg including 9.65 deg actual tilt and pupil ellipticity
dm1_ztilt_deg = 0 # rotation of DM about optical axis (deg)
dm2_xc_act = 23.5 # for 48x48 DM, wavefront centered at actuator intersections: (0,0) = 1st actuator center
dm2_yc_act = 23.5
dm2_xtilt_deg = 0 # tilt around X axis (deg)
dm2_ytilt_deg = 5.7 # effective DM tilt in deg including 9.65 deg actual tilt and pupil ellipticity
dm2_ztilt_deg = 0 # rotation of DM about optical axis (deg)
use_pupil_mask = 1 # SPC only: use SPC pupil mask (0 or 1)
mask_x_shift_pupdiam = 0 # X,Y shear of shaped pupil mask; normalized relative to pupil diameter
mask_y_shift_pupdiam = 0
mask_x_shift_m = 0 # X,Y shear of shaped pupil mask in meters
mask_y_shift_m = 0
use_fpm = 1 # use occulter? 1 or 0
fpm_x_offset = 0 # FPM x,y offset in lambda0/D
fpm_y_offset = 0
fpm_x_offset_m = 0 # FPM x,y offset in meters
fpm_y_offset_m = 0
fpm_z_shift_m = 0 # occulter offset in meters along optical axis (+ = away from prior optics)
pinhole_diam_m = 0 # FPM pinhole diameter in meters
end_at_fpm_exit_pupil = 0 # return field at FPM exit pupil?
output_field_rootname = '' # rootname of FPM exit pupil field file (must set end_at_fpm_exit_pupil=1)
use_lyot_stop = 1 # use Lyot stop? 1 or 0
lyot_x_shift_pupdiam = 0 # X,Y shear of Lyot stop mask; normalized relative to pupil diameter
lyot_y_shift_pupdiam = 0
lyot_x_shift_m = 0 # X,Y shear of Lyot stop mask in meters
lyot_y_shift_m = 0
use_field_stop = 1 # use field stop (HLC)? 1 or 0
field_stop_radius_lam0 = 0 # field stop radius in lambda0/D (HLC or SPC-wide mask only)
field_stop_x_offset = 0 # field stop offset in lambda0/D
field_stop_y_offset = 0
field_stop_x_offset_m = 0 # field stop offset in meters
field_stop_y_offset_m = 0
use_pupil_lens = 0 # use pupil imaging lens? 0 or 1
use_defocus_lens = 0 # use defocusing lens? Options are 1, 2, 3, 4, corresponding to +18.0, +9.0, -4.0, -8.0 waves P-V @ 550 nm
defocus = 0 # instead of specific lens, defocus in waves P-V @ 550 nm (-8.7 to 42.0 waves)
final_sampling_m = 0 # final sampling in meters (overrides final_sampling_lam0)
final_sampling_lam0 = 0 # final sampling in lambda0/D
output_dim = output_dim0 # dimension of output in pixels (overrides output_dim0)
if 'PASSVALUE' in locals():
if 'use_fpm' in PASSVALUE: use_fpm = PASSVALUE['use_fpm']
if 'cor_type' in PASSVALUE: cor_type = PASSVALUE['cor_type']
is_spc = False
is_hlc = False
if cor_type == 'hlc':
is_hlc = True
file_directory = data_dir + '/hlc_20190210/' # must have trailing "/"
prefix = file_directory + 'run461_'
pupil_diam_pix = 309.0
pupil_file = prefix + 'pupil_rotated.fits'
lyot_stop_file = prefix + 'lyot.fits'
lambda0_m = 0.575e-6
lam_occ = [
5.4625e-07, 5.49444444444e-07, 5.52638888889e-07, 5.534375e-07,
5.55833333333e-07, 5.59027777778e-07, 5.60625e-07,
5.62222222222e-07, 5.65416666667e-07, 5.678125e-07,
5.68611111111e-07, 5.71805555556e-07, 5.75e-07, 5.78194444444e-07,
5.81388888889e-07, 5.821875e-07, 5.84583333333e-07,
5.87777777778e-07, 5.89375e-07, 5.90972222222e-07,
5.94166666667e-07, 5.965625e-07, 5.97361111111e-07,
6.00555555556e-07, 6.0375e-07
]
lam_occs = [
'5.4625e-07', '5.49444444444e-07', '5.52638888889e-07',
'5.534375e-07', '5.55833333333e-07', '5.59027777778e-07',
'5.60625e-07', '5.62222222222e-07', '5.65416666667e-07',
'5.678125e-07', '5.68611111111e-07', '5.71805555556e-07',
'5.75e-07', '5.78194444444e-07', '5.81388888889e-07',
'5.821875e-07', '5.84583333333e-07', '5.87777777778e-07',
'5.89375e-07', '5.90972222222e-07', '5.94166666667e-07',
'5.965625e-07', '5.97361111111e-07', '6.00555555556e-07',
'6.0375e-07'
]
lam_occs = [
prefix + 'occ_lam' + s + 'theta6.69polp_' for s in lam_occs
]
# find nearest matching FPM wavelength
wlam = (np.abs(lambda_m - np.array(lam_occ))).argmin()
occulter_file_r = lam_occs[wlam] + 'real.fits'
occulter_file_i = lam_occs[wlam] + 'imag.fits'
n_default = 1024 # gridsize in non-critical areas
if use_fpm == 1:
n_to_fpm = 2048
else:
n_to_fpm = 1024
n_from_lyotstop = 1024
field_stop_radius_lam0 = 9.0
elif cor_type == 'hlc_erkin':
is_hlc = True
file_directory = data_dir + '/hlc_20190206_v3/' # must have trailing "/"
prefix = file_directory + 'dsn17d_run2_pup310_fpm2048_'
pupil_diam_pix = 310.0
pupil_file = prefix + 'pupil.fits'
lyot_stop_file = prefix + 'lyot.fits'
lambda0_m = 0.575e-6
lam_occ = [
5.4625e-07, 5.4944e-07, 5.5264e-07, 5.5583e-07, 5.5903e-07,
5.6222e-07, 5.6542e-07, 5.6861e-07, 5.7181e-07, 5.75e-07,
5.7819e-07, 5.8139e-07, 5.8458e-07, 5.8778e-07, 5.9097e-07,
5.9417e-07, 5.9736e-07, 6.0056e-07, 6.0375e-07
]
lam_occs = [
'5.4625e-07', '5.4944e-07', '5.5264e-07', '5.5583e-07',
'5.5903e-07', '5.6222e-07', '5.6542e-07', '5.6861e-07',
'5.7181e-07', '5.75e-07', '5.7819e-07', '5.8139e-07', '5.8458e-07',
'5.8778e-07', '5.9097e-07', '5.9417e-07', '5.9736e-07',
'6.0056e-07', '6.0375e-07'
]
lam_occs = [
prefix + 'occ_lam' + s + 'theta6.69pols_' for s in lam_occs
]
# find nearest matching FPM wavelength
wlam = (np.abs(lambda_m - np.array(lam_occ))).argmin()
occulter_file_r = lam_occs[wlam] + 'real_rotated.fits'
occulter_file_i = lam_occs[wlam] + 'imag_rotated.fits'
n_default = 1024 # gridsize in non-critical areas
if use_fpm == 1:
n_to_fpm = 2048
else:
n_to_fpm = 1024
n_from_lyotstop = 1024
field_stop_radius_lam0 = 9.0
elif cor_type == 'spc-ifs_short' or cor_type == 'spc-ifs_long' or cor_type == 'spc-spec_short' or cor_type == 'spc-spec_long':
is_spc = True
file_dir = data_dir + '/spc_20190130/' # must have trailing "/"
pupil_diam_pix = 1000.0
pupil_file = file_dir + 'pupil_SPC-20190130_rotated.fits'
pupil_mask_file = file_dir + 'SPM_SPC-20190130.fits'
fpm_file = file_dir + 'fpm_0.05lamdivD.fits'
fpm_sampling = 0.05 # sampling in fpm_sampling_lambda_m/D of FPM mask
if cor_type == 'spc-ifs_short' or cor_type == 'spc-spec_short':
fpm_sampling_lambda_m = 0.66e-6
lambda0_m = 0.66e-6
else:
fpm_sampling_lambda_m = 0.73e-6
lambda0_m = 0.73e-6 # FPM scaled for this central wavelength
lyot_stop_file = file_dir + 'LS_SPC-20190130.fits'
n_default = 2048 # gridsize in non-critical areas
n_to_fpm = 2048 # gridsize to/from FPM
n_mft = 1400 # gridsize to FPM (propagation to/from FPM handled by MFT)
n_from_lyotstop = 4096
elif cor_type == 'spc-wide':
is_spc = True
file_dir = data_dir + '/spc_20181220/' # must have trailing "/"
pupil_diam_pix = 1000.0
pupil_file = file_dir + 'pupil_SPC-20181220_1k_rotated.fits'
pupil_mask_file = file_dir + 'SPM_SPC-20181220_1000_rounded9_gray.fits'
fpm_file = file_dir + 'fpm_0.05lamdivD.fits'
fpm_sampling = 0.05 # sampling in lambda0/D of FPM mask
fpm_sampling_lambda_m = 0.825e-6
lambda0_m = 0.825e-6 # FPM scaled for this central wavelength
lyot_stop_file = file_dir + 'LS_SPC-20181220_1k.fits'
n_default = 2048 # gridsize in non-critical areas
n_to_fpm = 2048 # gridsize to/from FPM
n_mft = 1400
n_from_lyotstop = 4096
elif cor_type == 'none':
file_directory = data_dir + '/hlc_20190210/' # must have trailing "/"
prefix = file_directory + 'run461_'
pupil_diam_pix = 309.0
pupil_file = prefix + 'pupil_rotated.fits'
lambda0_m = 0.575e-6
use_fpm = 0
use_lyot_stop = 0
use_field_stop = 0
n_default = 1024
n_to_fpm = 1024
n_from_lyotstop = 1024
else:
raise Exception('ERROR: Unsupported cor_type: ' + cor_type)
if 'PASSVALUE' in locals():
if 'lam0' in PASSVALUE: lamba0_m = PASSVALUE['lam0'] * 1.0e-6
if 'lambda0_m' in PASSVALUE: lambda0_m = PASSVALUE['lambda0_m']
mas_per_lamD = lambda0_m * 360.0 * 3600.0 / (
2 * np.pi * 2.363) * 1000 # mas per lambda0/D
if 'source_x_offset' in PASSVALUE:
source_x_offset = PASSVALUE['source_x_offset']
if 'source_y_offset' in PASSVALUE:
source_y_offset = PASSVALUE['source_y_offset']
if 'source_x_offset_mas' in PASSVALUE:
source_x_offset = PASSVALUE['source_x_offset_mas'] / mas_per_lamD
if 'source_y_offset_mas' in PASSVALUE:
source_y_offset = PASSVALUE['source_y_offset_mas'] / mas_per_lamD
if 'use_errors' in PASSVALUE: use_errors = PASSVALUE['use_errors']
if 'polaxis' in PASSVALUE: polaxis = PASSVALUE['polaxis']
if 'zindex' in PASSVALUE: zindex = np.array(PASSVALUE['zindex'])
if 'zval_m' in PASSVALUE: zval_m = np.array(PASSVALUE['zval_m'])
if 'end_at_fsm' in PASSVALUE: end_at_fsm = PASSVALUE['end_at_fsm']
if 'cgi_x_shift_pupdiam' in PASSVALUE:
cgi_x_shift_pupdiam = PASSVALUE['cgi_x_shift_pupdiam']
if 'cgi_y_shift_pupdiam' in PASSVALUE:
cgi_y_shift_pupdiam = PASSVALUE['cgi_y_shift_pupdiam']
if 'cgi_x_shift_m' in PASSVALUE:
cgi_x_shift_m = PASSVALUE['cgi_x_shift_m']
if 'cgi_y_shift_m' in PASSVALUE:
cgi_y_shift_m = PASSVALUE['cgi_y_shift_m']
if 'fsm_x_offset' in PASSVALUE:
fsm_x_offset = PASSVALUE['fsm_x_offset']
if 'fsm_y_offset' in PASSVALUE:
fsm_y_offset = PASSVALUE['fsm_y_offset']
if 'fsm_x_offset_mas' in PASSVALUE:
fsm_x_offset = PASSVALUE['fsm_x_offset_mas'] / mas_per_lamD
if 'fsm_y_offset_mas' in PASSVALUE:
fsm_y_offset = PASSVALUE['fsm_y_offset_mas'] / mas_per_lamD
if 'focm_z_shift_m' in PASSVALUE:
focm_z_shift_m = PASSVALUE['focm_z_shift_m']
if 'use_hlc_dm_patterns' in PASSVALUE:
use_hlc_dm_patterns = PASSVALUE['use_hlc_dm_patterns']
if 'use_dm1' in PASSVALUE: use_dm1 = PASSVALUE['use_dm1']
if 'dm1_m' in PASSVALUE: dm1_m = PASSVALUE['dm1_m']
if 'dm1_xc_act' in PASSVALUE: dm1_xc_act = PASSVALUE['dm1_xc_act']
if 'dm1_yc_act' in PASSVALUE: dm1_yc_act = PASSVALUE['dm1_yc_act']
if 'dm1_xtilt_deg' in PASSVALUE:
dm1_xtilt_deg = PASSVALUE['dm1_xtilt_deg']
if 'dm1_ytilt_deg' in PASSVALUE:
dm1_ytilt_deg = PASSVALUE['dm1_ytilt_deg']
if 'dm1_ztilt_deg' in PASSVALUE:
dm1_ztilt_deg = PASSVALUE['dm1_ztilt_deg']
if 'use_dm2' in PASSVALUE: use_dm2 = PASSVALUE['use_dm2']
if 'dm2_m' in PASSVALUE: dm2_m = PASSVALUE['dm2_m']
if 'dm2_xc_act' in PASSVALUE: dm2_xc_act = PASSVALUE['dm2_xc_act']
if 'dm2_yc_act' in PASSVALUE: dm2_yc_act = PASSVALUE['dm2_yc_act']
if 'dm2_xtilt_deg' in PASSVALUE:
dm2_xtilt_deg = PASSVALUE['dm2_xtilt_deg']
if 'dm2_ytilt_deg' in PASSVALUE:
dm2_ytilt_deg = PASSVALUE['dm2_ytilt_deg']
if 'dm2_ztilt_deg' in PASSVALUE:
dm2_ztilt_deg = PASSVALUE['dm2_ztilt_deg']
if 'use_pupil_mask' in PASSVALUE:
use_pupil_mask = PASSVALUE['use_pupil_mask']
if 'mask_x_shift_pupdiam' in PASSVALUE:
mask_x_shift_pupdiam = PASSVALUE['mask_x_shift_pupdiam']
if 'mask_y_shift_pupdiam' in PASSVALUE:
mask_y_shift_pupdiam = PASSVALUE['mask_y_shift_pupdiam']
if 'mask_x_shift_m' in PASSVALUE:
mask_x_shift_m = PASSVALUE['mask_x_shift_m']
if 'mask_y_shift_m' in PASSVALUE:
mask_y_shift_m = PASSVALUE['mask_y_shift_m']
if 'fpm_x_offset' in PASSVALUE:
fpm_x_offset = PASSVALUE['fpm_x_offset']
if 'fpm_y_offset' in PASSVALUE:
fpm_y_offset = PASSVALUE['fpm_y_offset']
if 'fpm_x_offset_m' in PASSVALUE:
fpm_x_offset_m = PASSVALUE['fpm_x_offset_m']
if 'fpm_y_offset_m' in PASSVALUE:
fpm_y_offset_m = PASSVALUE['fpm_y_offset_m']
if 'fpm_z_shift_m' in PASSVALUE:
fpm_z_shift_m = PASSVALUE['fpm_z_shift_m']
if 'pinhole_diam_m' in PASSVALUE:
pinhole_diam_m = PASSVALUE['pinhole_diam_m']
if 'end_at_fpm_exit_pupil' in PASSVALUE:
end_at_fpm_exit_pupil = PASSVALUE['end_at_fpm_exit_pupil']
if 'output_field_rootname' in PASSVALUE:
output_field_rootname = PASSVALUE['output_field_rootname']
if 'use_lyot_stop' in PASSVALUE:
use_lyot_stop = PASSVALUE['use_lyot_stop']
if 'lyot_x_shift_pupdiam' in PASSVALUE:
lyot_x_shift_pupdiam = PASSVALUE['lyot_x_shift_pupdiam']
if 'lyot_y_shift_pupdiam' in PASSVALUE:
lyot_y_shift_pupdiam = PASSVALUE['lyot_y_shift_pupdiam']
if 'lyot_x_shift_m' in PASSVALUE:
lyot_x_shift_m = PASSVALUE['lyot_x_shift_m']
if 'lyot_y_shift_m' in PASSVALUE:
lyot_y_shift_m = PASSVALUE['lyot_y_shift_m']
if 'use_field_stop' in PASSVALUE:
use_field_stop = PASSVALUE['use_field_stop']
if 'field_stop_x_offset' in PASSVALUE:
field_stop_x_offset = PASSVALUE['field_stop_x_offset']
if 'field_stop_y_offset' in PASSVALUE:
field_stop_y_offset = PASSVALUE['field_stop_y_offset']
if 'field_stop_x_offset_m' in PASSVALUE:
field_stop_x_offset_m = PASSVALUE['field_stop_x_offset_m']
if 'field_stop_y_offset_m' in PASSVALUE:
field_stop_y_offset_m = PASSVALUE['field_stop_y_offset_m']
if 'use_pupil_lens' in PASSVALUE:
use_pupil_lens = PASSVALUE['use_pupil_lens']
if 'use_defocus_lens' in PASSVALUE:
use_defocus_lens = PASSVALUE['use_defocus_lens']
if 'defocus' in PASSVALUE: defocus = PASSVALUE['defocus']
if 'output_dim' in PASSVALUE: output_dim = PASSVALUE['output_dim']
if 'final_sampling_m' in PASSVALUE:
final_sampling_m = PASSVALUE['final_sampling_m']
if 'final_sampling_lam0' in PASSVALUE:
final_sampling_lam0 = PASSVALUE['final_sampling_lam0']
diam = 2.3633372
fl_pri = 2.83459423440 * 1.0013
d_pri_sec = 2.285150515460035
d_focus_sec = d_pri_sec - fl_pri
fl_sec = -0.653933011 * 1.0004095
d_sec_focus = 3.580188916677103
diam_sec = 0.58166
d_sec_fold1 = 2.993753476654728
d_fold1_focus = 0.586435440022375
diam_fold1 = 0.09
d_fold1_m3 = 1.680935841598811
fl_m3 = 0.430216463069001
d_focus_m3 = 1.094500401576436
d_m3_pupil = 0.469156807701977
d_m3_focus = 0.708841602661368
diam_m3 = 0.2
d_m3_m4 = 0.943514749358944
fl_m4 = 0.116239114833590
d_focus_m4 = 0.234673014520402
d_m4_pupil = 0.474357941656967
d_m4_focus = 0.230324117970585
diam_m4 = 0.07
d_m4_m5 = 0.429145636743193
d_m5_focus = 0.198821518772608
fl_m5 = 0.198821518772608
d_m5_pupil = 0.716529242882632
diam_m5 = 0.07
d_m5_fold2 = 0.351125431220770
diam_fold2 = 0.06
d_fold2_fsm = 0.365403811661862
d_fsm_oap1 = 0.354826767220001
fl_oap1 = 0.503331895563883
diam_oap1 = 0.06
d_oap1_focm = 0.768005607094041
d_focm_oap2 = 0.314483210543378
fl_oap2 = 0.579156922073536
diam_oap2 = 0.06
d_oap2_dm1 = 0.775775726154228
d_dm1_dm2 = 1.0
d_dm2_oap3 = 0.394833855161549
fl_oap3 = 1.217276467668519
diam_oap3 = 0.06
d_oap3_fold3 = 0.505329955078121
diam_fold3 = 0.06
d_fold3_oap4 = 1.158897671642761
fl_oap4 = 0.446951159052363
diam_oap4 = 0.06
d_oap4_pupilmask = 0.423013568764728
d_pupilmask_oap5 = 0.408810648253099
fl_oap5 = 0.548189351937178
diam_oap5 = 0.06
d_oap5_fpm = 0.548189083164429
d_fpm_oap6 = 0.548189083164429
fl_oap6 = 0.548189083164429
diam_oap6 = 0.06
d_oap6_lyotstop = 0.687567667550736
d_lyotstop_oap7 = 0.401748843470518
fl_oap7 = 0.708251083480054
diam_oap7 = 0.06
d_oap7_fieldstop = 0.708251083480054
d_fieldstop_oap8 = 0.210985967281651
fl_oap8 = 0.210985967281651
diam_oap8 = 0.06
d_oap8_pupil = 0.238185804200797
d_oap8_filter = 0.368452268225530
diam_filter = 0.01
d_filter_lens = 0.170799548215162
fl_lens = 0.246017378417573 + 0.050001306014153
diam_lens = 0.01
d_lens_fold4 = 0.246017378417573
diam_fold4 = 0.02
d_fold4_image = 0.050001578514650
fl_pupillens = 0.149260576823040
n = n_default # start off with less padding
wavefront = proper.prop_begin(diam, lambda_m, n, float(pupil_diam_pix) / n)
pupil = proper.prop_fits_read(pupil_file)
proper.prop_multiply(wavefront, trim(pupil, n))
pupil = 0
if polaxis != 0: polmap(wavefront, polfile, pupil_diam_pix, polaxis)
proper.prop_define_entrance(wavefront)
proper.prop_lens(wavefront, fl_pri)
if source_x_offset != 0 or source_y_offset != 0:
# compute tilted wavefront to offset source by xoffset,yoffset lambda0_m/D
xtilt_lam = -source_x_offset * lambda0_m / lambda_m
ytilt_lam = -source_y_offset * lambda0_m / lambda_m
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0), (n, 1))
y = np.transpose(x)
proper.prop_multiply(
wavefront,
np.exp(complex(0, 1) * np.pi * (xtilt_lam * x + ytilt_lam * y)))
x = 0
y = 0
if zindex[0] != 0: proper.prop_zernikes(wavefront, zindex, zval_m)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_PRIMARY_phase_error_V1.0.fits',
WAVEFRONT=True)
proper.prop_errormap(
wavefront,
map_dir +
'wfirst_phaseb_GROUND_TO_ORBIT_4.2X_phase_error_V1.0.fits',
WAVEFRONT=True)
proper.prop_propagate(wavefront, d_pri_sec, 'secondary')
proper.prop_lens(wavefront, fl_sec)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_SECONDARY_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_sec / 2.0)
proper.prop_propagate(wavefront, d_sec_fold1, 'FOLD_1')
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FOLD1_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_fold1 / 2.0)
proper.prop_propagate(wavefront, d_fold1_m3, 'M3')
proper.prop_lens(wavefront, fl_m3)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_M3_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_m3 / 2.0)
proper.prop_propagate(wavefront, d_m3_m4, 'M4')
proper.prop_lens(wavefront, fl_m4)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_M4_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_m4 / 2.0)
proper.prop_propagate(wavefront, d_m4_m5, 'M5')
proper.prop_lens(wavefront, fl_m5)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_M5_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_m5 / 2.0)
proper.prop_propagate(wavefront, d_m5_fold2, 'FOLD_2')
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FOLD2_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_fold2 / 2.0)
proper.prop_propagate(wavefront, d_fold2_fsm, 'FSM')
if end_at_fsm == 1:
(wavefront, sampling_m) = proper.prop_end(wavefront, NOABS=True)
wavefront = trim(wavefront, n)
return wavefront, sampling_m
if cgi_x_shift_pupdiam != 0 or cgi_y_shift_pupdiam != 0 or cgi_x_shift_m != 0 or cgi_y_shift_m != 0: # bulk coronagraph pupil shear
# FFT the field, apply a tilt, FFT back
if cgi_x_shift_pupdiam != 0 or cgi_y_shift_pupdiam != 0:
# offsets are normalized to pupil diameter
xt = -cgi_x_shift_pupdiam * pupil_diam_pix * float(
pupil_diam_pix) / n
yt = -cgi_y_shift_pupdiam * pupil_diam_pix * float(
pupil_diam_pix) / n
else:
# offsets are meters
d_m = proper.prop_get_sampling(wavefront)
xt = -cgi_x_shift_m / d_m * float(pupil_diam_pix) / n
yt = -cgi_y_shift_m / d_m * float(pupil_diam_pix) / n
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0), (n, 1))
y = np.transpose(x)
tilt = complex(0, 1) * np.pi * (x * xt + y * yt)
x = 0
y = 0
wavefront0 = proper.prop_get_wavefront(wavefront)
wavefront0 = ffts(wavefront0, -1)
wavefront0 *= np.exp(tilt)
wavefront0 = ffts(wavefront0, 1)
tilt = 0
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FSM_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_fsm / 2.0)
if (fsm_x_offset != 0.0 or fsm_y_offset != 0.0):
# compute tilted wavefront to offset source by fsm_x_offset,fsm_y_offset lambda0_m/D
xtilt_lam = fsm_x_offset * lambda0_m / lambda_m
ytilt_lam = fsm_y_offset * lambda0_m / lambda_m
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0), (n, 1))
y = np.transpose(x)
proper.prop_multiply(
wavefront,
np.exp(complex(0, 1) * np.pi * (xtilt_lam * x + ytilt_lam * y)))
x = 0
y = 0
proper.prop_propagate(wavefront, d_fsm_oap1, 'OAP1')
proper.prop_lens(wavefront, fl_oap1)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP1_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap1 / 2.0)
proper.prop_propagate(wavefront, d_oap1_focm + focm_z_shift_m, 'FOCM')
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FOCM_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_focm / 2.0)
proper.prop_propagate(wavefront, d_focm_oap2 + focm_z_shift_m, 'OAP2')
proper.prop_lens(wavefront, fl_oap2)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP2_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap2 / 2.0)
proper.prop_propagate(wavefront, d_oap2_dm1, 'DM1')
if use_dm1 != 0:
proper.prop_dm(wavefront,
dm1_m,
dm1_xc_act,
dm1_yc_act,
dm_sampling_m,
XTILT=dm1_xtilt_deg,
YTILT=dm1_ytilt_deg,
ZTILT=dm1_ztilt_deg)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_DM1_phase_error_V1.0.fits',
WAVEFRONT=True)
if is_hlc == True and use_hlc_dm_patterns == 1:
dm1wfe = proper.prop_fits_read(prefix + 'dm1wfe.fits')
proper.prop_add_phase(wavefront, trim(dm1wfe, n))
dm1wfe = 0
proper.prop_propagate(wavefront, d_dm1_dm2, 'DM2')
if use_dm2 == 1:
proper.prop_dm(wavefront,
dm2_m,
dm2_xc_act,
dm2_yc_act,
dm_sampling_m,
XTILT=dm2_xtilt_deg,
YTILT=dm2_ytilt_deg,
ZTILT=dm2_ztilt_deg)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_DM2_phase_error_V1.0.fits',
WAVEFRONT=True)
if is_hlc == True:
if use_hlc_dm_patterns == 1:
dm2wfe = proper.prop_fits_read(prefix + 'dm2wfe.fits')
proper.prop_add_phase(wavefront, trim(dm2wfe, n))
dm2wfe = 0
dm2mask = proper.prop_fits_read(prefix + 'dm2mask.fits')
proper.prop_multiply(wavefront, trim(dm2mask, n))
dm2mask = 0
proper.prop_propagate(wavefront, d_dm2_oap3, 'OAP3')
proper.prop_lens(wavefront, fl_oap3)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP3_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap3 / 2.0)
proper.prop_propagate(wavefront, d_oap3_fold3, 'FOLD_3')
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FOLD3_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_fold3 / 2.0)
proper.prop_propagate(wavefront, d_fold3_oap4, 'OAP4')
proper.prop_lens(wavefront, fl_oap4)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP4_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap4 / 2.0)
proper.prop_propagate(wavefront, d_oap4_pupilmask,
'PUPIL_MASK') # flat/reflective shaped pupil
if is_spc == True and use_pupil_mask != 0:
pupil_mask = proper.prop_fits_read(pupil_mask_file)
pupil_mask = trim(pupil_mask, n)
if mask_x_shift_pupdiam != 0 or mask_y_shift_pupdiam != 0 or mask_x_shift_m != 0 or mask_y_shift_m != 0:
# shift SP mask by FFTing it, applying tilt, and FFTing back
if mask_x_shift_pupdiam != 0 or mask_y_shift_pupdiam != 0:
# offsets are normalized to pupil diameter
xt = -mask_x_shift_pupdiam * pupil_diam_pix * float(
pupil_diam_pix) / n
yt = -mask_y_shift_pupdiam * pupil_diam_pix * float(
pupil_diam_pix) / n
else:
d_m = proper.prop_get_sampling(wavefront)
xt = -mask_x_shift_m / d_m * float(pupil_diam_pix) / n
yt = -mask_y_shift_m / d_m * float(pupil_diam_pix) / n
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0),
(n, 1))
y = np.transpose(x)
tilt = complex(0, 1) * np.pi * (x * xt + y * yt)
x = 0
y = 0
pupil_mask = ffts(pupil_mask, -1)
pupil_mask *= np.exp(tilt)
pupil_mask = ffts(pupil_mask, 1)
pupil_mask = pupil_mask.real
tilt = 0
proper.prop_multiply(wavefront, pupil_mask)
pupil_mask = 0
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_PUPILMASK_phase_error_V1.0.fits',
WAVEFRONT=True)
# while at a pupil, use more padding to provide 2x better sampling at FPM
diam = 2 * proper.prop_get_beamradius(wavefront)
(wavefront, dx) = proper.prop_end(wavefront, NOABS=True)
n = n_to_fpm
wavefront0 = trim(wavefront, n)
wavefront = proper.prop_begin(diam, lambda_m, n, float(pupil_diam_pix) / n)
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
proper.prop_propagate(wavefront, d_pupilmask_oap5, 'OAP5')
proper.prop_lens(wavefront, fl_oap5)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP5_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap5 / 2.0)
proper.prop_propagate(wavefront,
d_oap5_fpm + fpm_z_shift_m,
'FPM',
TO_PLANE=True)
if use_fpm == 1:
if fpm_x_offset != 0 or fpm_y_offset != 0 or fpm_x_offset_m != 0 or fpm_y_offset_m != 0:
# To shift FPM, FFT field to pupil, apply tilt, FFT back to focus,
# apply FPM, FFT to pupil, take out tilt, FFT back to focus
if fpm_x_offset != 0 or fpm_y_offset != 0:
# shifts are specified in lambda0/D
x_offset_lamD = fpm_x_offset * lambda0_m / lambda_m
y_offset_lamD = fpm_y_offset * lambda0_m / lambda_m
else:
d_m = proper.prop_get_sampling(wavefront)
x_offset_lamD = fpm_x_offset_m / d_m * float(
pupil_diam_pix) / n
y_offset_lamD = fpm_y_offset_m / d_m * float(
pupil_diam_pix) / n
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0),
(n, 1))
y = np.transpose(x)
tilt = complex(0,
1) * np.pi * (x * x_offset_lamD + y * y_offset_lamD)
x = 0
y = 0
wavefront0 = proper.prop_get_wavefront(wavefront)
wavefront0 = ffts(wavefront0, -1)
wavefront0 *= np.exp(tilt)
wavefront0 = ffts(wavefront0, 1)
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
if is_hlc == True:
occ_r = proper.prop_fits_read(occulter_file_r)
occ_i = proper.prop_fits_read(occulter_file_i)
occ = np.array(occ_r + 1j * occ_i, dtype=np.complex128)
proper.prop_multiply(wavefront, trim(occ, n))
occ_r = 0
occ_i = 0
occ = 0
elif is_spc == True:
# super-sample FPM
wavefront0 = proper.prop_get_wavefront(wavefront)
wavefront0 = ffts(wavefront0, 1) # to virtual pupil
wavefront0 = trim(wavefront0, n_mft)
fpm = proper.prop_fits_read(fpm_file)
nfpm = fpm.shape[1]
fpm_sampling_lam = fpm_sampling * fpm_sampling_lambda_m / lambda_m
wavefront0 = mft2(wavefront0, fpm_sampling_lam, pupil_diam_pix,
nfpm, -1) # MFT to highly-sampled focal plane
wavefront0 *= fpm
fpm = 0
wavefront0 = mft2(wavefront0, fpm_sampling_lam, pupil_diam_pix, n,
+1) # MFT to virtual pupil
wavefront0 = ffts(wavefront0,
-1) # back to normally-sampled focal plane
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
if fpm_x_offset != 0 or fpm_y_offset != 0 or fpm_x_offset_m != 0 or fpm_y_offset_m != 0:
wavefront0 = proper.prop_get_wavefront(wavefront)
wavefront0 = ffts(wavefront0, -1)
wavefront0 *= np.exp(-tilt)
wavefront0 = ffts(wavefront0, 1)
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
tilt = 0
if pinhole_diam_m != 0:
# "pinhole_diam_m" is pinhole diameter in meters
dx_m = proper.prop_get_sampling(wavefront)
dx_pinhole_diam_m = pinhole_diam_m / 101.0 # 101 samples across pinhole
n_out = 105
m_per_lamD = dx_m * n / float(
pupil_diam_pix) # current focal plane sampling in lambda_m/D
dx_pinhole_lamD = dx_pinhole_diam_m / m_per_lamD # pinhole sampling in lambda_m/D
n_in = int(round(pupil_diam_pix * 1.2))
wavefront0 = proper.prop_get_wavefront(wavefront)
wavefront0 = ffts(wavefront0, +1) # to virtual pupil
wavefront0 = trim(wavefront0, n_in)
m = dx_pinhole_lamD * n_in * float(n_out) / pupil_diam_pix
wavefront0 = mft2(wavefront0, dx_pinhole_lamD, pupil_diam_pix, n_out,
-1) # MFT to highly-sampled focal plane
p = (radius(n_out) * dx_pinhole_diam_m) <= (pinhole_diam_m / 2.0)
p = p.astype(np.int)
wavefront0 *= p
p = 0
wavefront0 = mft2(wavefront0, dx_pinhole_lamD, pupil_diam_pix, n,
+1) # MFT back to virtual pupil
wavefront0 = ffts(wavefront0,
-1) # back to normally-sampled focal plane
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
proper.prop_propagate(wavefront, d_fpm_oap6 - fpm_z_shift_m, 'OAP6')
proper.prop_lens(wavefront, fl_oap6)
if use_errors != 0 and end_at_fpm_exit_pupil == 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP6_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap6 / 2.0)
proper.prop_propagate(wavefront, d_oap6_lyotstop, 'LYOT_STOP')
# while at a pupil, switch back to less padding
diam = 2 * proper.prop_get_beamradius(wavefront)
(wavefront, dx) = proper.prop_end(wavefront, NOABS=True)
n = n_from_lyotstop
wavefront = trim(wavefront, n)
if output_field_rootname != '':
lams = format(lambda_m * 1e6, "6.4f")
pols = format(int(round(polaxis)))
hdu = pyfits.PrimaryHDU()
hdu.data = np.real(wavefront)
hdu.writeto(output_field_rootname + '_' + lams + 'um_' + pols +
'_real.fits',
overwrite=True)
hdu = pyfits.PrimaryHDU()
hdu.data = np.imag(wavefront)
hdu.writeto(output_field_rootname + '_' + lams + 'um_' + pols +
'_imag.fits',
overwrite=True)
if end_at_fpm_exit_pupil == 1:
return wavefront, dx
wavefront0 = wavefront.copy()
wavefront = 0
wavefront = proper.prop_begin(diam, lambda_m, n, float(pupil_diam_pix) / n)
wavefront.wfarr[:, :] = proper.prop_shift_center(wavefront0)
wavefront0 = 0
if use_lyot_stop != 0:
lyot = proper.prop_fits_read(lyot_stop_file)
lyot = trim(lyot, n)
if lyot_x_shift_pupdiam != 0 or lyot_y_shift_pupdiam != 0 or lyot_x_shift_m != 0 or lyot_y_shift_m != 0:
# apply shift to lyot stop by FFTing the stop, applying a tilt, and FFTing back
if lyot_x_shift_pupdiam != 0 or lyot_y_shift_pupdiam != 0:
# offsets are normalized to pupil diameter
xt = -lyot_x_shift_pupdiam * pupil_diam_pix * float(
pupil_diam_pix) / n
yt = -lyot_y_shift_pupdiam * pupil_diam_pix * float(
pupil_diam_pix) / n
else:
d_m = proper.prop_get_sampling(wavefront)
xt = -lyot_x_shift_m / d_m * float(pupil_diam_pix) / n
yt = -lyot_y_shift_m / d_m * float(pupil_diam_pix) / n
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0),
(n, 1))
y = np.transpose(x)
tilt = complex(0, 1) * np.pi * (x * xt + y * yt)
x = 0
y = 0
lyot = ffts(lyot, -1)
lyot *= np.exp(tilt)
lyot = ffts(lyot, 1)
lyot = lyot.real
tilt = 0
proper.prop_multiply(wavefront, lyot)
lyot = 0
if use_pupil_lens != 0 or pinhole_diam_m != 0:
proper.prop_circular_aperture(wavefront, 1.1, NORM=True)
proper.prop_propagate(wavefront, d_lyotstop_oap7, 'OAP7')
proper.prop_lens(wavefront, fl_oap7)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP7_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap7 / 2.0)
proper.prop_propagate(wavefront, d_oap7_fieldstop, 'FIELD_STOP')
if use_field_stop != 0 and (cor_type == 'hlc' or cor_type == 'hlc_erkin'):
sampling_lamD = float(
pupil_diam_pix) / n # sampling at focus in lambda_m/D
stop_radius = field_stop_radius_lam0 / sampling_lamD * (
lambda0_m / lambda_m) * proper.prop_get_sampling(wavefront)
if field_stop_x_offset != 0 or field_stop_y_offset != 0:
# convert offsets in lambda0/D to meters
x_offset_lamD = field_stop_x_offset * lambda0_m / lambda_m
y_offset_lamD = field_stop_y_offset * lambda0_m / lambda_m
pupil_ratio = float(pupil_diam_pix) / n
field_stop_x_offset_m = x_offset_lamD / pupil_ratio * proper.prop_get_sampling(
wavefront)
field_stop_y_offset_m = y_offset_lamD / pupil_ratio * proper.prop_get_sampling(
wavefront)
proper.prop_circular_aperture(wavefront, stop_radius,
-field_stop_x_offset_m,
-field_stop_y_offset_m)
proper.prop_propagate(wavefront, d_fieldstop_oap8, 'OAP8')
proper.prop_lens(wavefront, fl_oap8)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_OAP8_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_oap8 / 2.0)
proper.prop_propagate(wavefront, d_oap8_filter, 'filter')
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FILTER_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_filter / 2.0)
proper.prop_propagate(wavefront, d_filter_lens, 'LENS')
if use_pupil_lens == 0 and use_defocus_lens == 0 and defocus == 0:
# use imaging lens to create normal focus
proper.prop_lens(wavefront, fl_lens)
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_LENS_phase_error_V1.0.fits',
WAVEFRONT=True)
elif use_pupil_lens != 0:
# use pupil imaging lens
proper.prop_lens(wavefront, fl_pupillens)
if use_errors != 0:
proper.prop_errormap(
wavefront,
map_dir + 'wfirst_phaseb_PUPILLENS_phase_error_V1.0.fits',
WAVEFRONT=True)
else:
# table is waves P-V @ 575 nm
z4_pv_waves = np.array([
-9.0545, -8.5543, -8.3550, -8.0300, -7.54500, -7.03350, -6.03300,
-5.03300, -4.02000, -2.51980, 0.00000000, 3.028000, 4.95000,
6.353600, 8.030000, 10.10500, 12.06000, 14.06000, 20.26000,
28.34000, 40.77500, 56.65700
])
fl_defocus_lens = np.array([
5.09118, 1.89323, 1.54206, 1.21198, 0.914799, 0.743569, 0.567599,
0.470213, 0.406973, 0.350755, 0.29601868, 0.260092, 0.24516,
0.236606, 0.228181, 0.219748, 0.213278, 0.207816, 0.195536,
0.185600, 0.176629, 0.169984
])
# subtract ad-hoc function to make z4 vs f_length more accurately spline interpolatible
f = fl_defocus_lens / 0.005
f0 = 59.203738
z4t = z4_pv_waves - (0.005 * (f0 - f - 40)) / f**2 / 0.575e-6
if use_defocus_lens != 0:
# use one of 4 defocusing lenses
defocus = np.array([18.0, 9.0, -4.0, -8.0]) # waves P-V @ 575 nm
f = interp1d(z4_pv_waves, z4t, kind='cubic')
z4x = f(defocus)
f = interp1d(z4t, fl_defocus_lens, kind='cubic')
lens_fl = f(z4x)
proper.prop_lens(wavefront, lens_fl[use_defocus_lens - 1])
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir + 'wfirst_phaseb_DEFOCUSLENS' +
str(use_defocus_lens) +
'_phase_error_V1.0.fits',
WAVEFRONT=True)
defocus = defocus[use_defocus_lens - 1]
else:
# specify amount of defocus (P-V waves @ 575 nm)
f = interp1d(z4_pv_waves, z4t, kind='cubic')
z4x = f(defocus)
f = interp1d(z4t, fl_defocus_lens, kind='cubic')
lens_fl = f(z4x)
proper.prop_lens(wavefront, lens_fl)
if use_errors != 0:
proper.prop_errormap(
wavefront,
map_dir +
'wfirst_phaseb_DEFOCUSLENS1_phase_error_V1.0.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_lens / 2.0)
proper.prop_propagate(wavefront, d_lens_fold4, 'FOLD_4')
if use_errors != 0:
proper.prop_errormap(wavefront,
map_dir +
'wfirst_phaseb_FOLD4_phase_error_V1.1.fits',
WAVEFRONT=True)
if use_aperture != 0:
proper.prop_circular_aperture(wavefront, diam_fold4 / 2.0)
if defocus != 0 or use_defocus_lens != 0:
if np.abs(defocus) <= 4:
proper.prop_propagate(wavefront,
d_fold4_image,
'IMAGE',
TO_PLANE=True)
else:
proper.prop_propagate(wavefront, d_fold4_image, 'IMAGE')
else:
proper.prop_propagate(wavefront, d_fold4_image, 'IMAGE')
(wavefront, sampling_m) = proper.prop_end(wavefront, NOABS=True)
if final_sampling_lam0 != 0 or final_sampling_m != 0:
if final_sampling_m != 0:
mag = sampling_m / final_sampling_m
sampling_m = final_sampling_m
else:
mag = (float(pupil_diam_pix) /
n) / final_sampling_lam0 * (lambda_m / lambda0_m)
sampling_m = sampling_m / mag
wavefront = proper.prop_magnify(wavefront,
mag,
output_dim,
AMP_CONSERVE=True)
else:
wavefront = trim(wavefront, output_dim)
return wavefront, sampling_m
def propcustom_dm(wf, dm_z0, dm_xc, dm_yc, spacing=0., **kwargs):
"""
Generate a deformable mirror surface almost exactly like PROPER.
Simulate a deformable mirror of specified actuator spacing, including the
effects of the DM influence function. Has two more optional keywords
compared to proper.prop_dm
Parameters
----------
wf : obj
WaveFront class object
dm_z0 : str or numpy ndarray
Either a 2D numpy array containing the surface piston of each DM
actuator in meters or the name of a 2D FITS image file containing the
above
dm_xc, dm_yc : list or numpy ndarray
The location of the optical axis (center of the wavefront) on the DM in
actuator units (0 ro num_actuator-1). The center of the first actuator
is (0.0, 0.0)
spacing : float
Defines the spacing in meters between actuators; must not be used when
n_act_across_pupil is specified.
Returns
-------
dmap : numpy ndarray
Returns DM surface (not wavefront) map in meters
Other Parameters
----------------
FIT : bool
Switch that tells routine that the values in "dm_z" are the desired
surface heights rather than commanded actuator heights, and so the
routine should fit this map, accounting for actuator influence functions,
to determine the necessary actuator heights. An iterative error-minimizing
loop is used for the fit.
NO_APPLY : bool
If set, the DM pattern is not added to the wavefront. Useful if the DM
surface map is needed but should not be applied to the wavefront
N_ACT_ACROSS_PUPIL : int
Specifies the number of actuators that span the X-axis beam diameter. If
it is a whole number, the left edge of the left pixel is aligned with
the left edge of the beam, and the right edge of the right pixel with
the right edge of the beam. This determines the spacing and size of the
actuators. Should not be used when "spacing" value is specified.
XTILT, YTILT, ZTILT : float
Specify the rotation of the DM surface with respect to the wavefront plane
in degrees about the X, Y, Z axes, respectively, with the origin at the
center of the wavefront. The DM surface is interpolated and orthographically
projected onto the wavefront grid. The coordinate system assumes that
the wavefront and initial DM surface are in the X,Y plane with a lower
left origin with Z towards the observer. The rotations are left handed.
The default rotation order is X, Y, then Z unless the /ZYX switch is set.
XYZ or ZYX : bool
Specifies the rotation order if two or more of XTILT, YTILT, or ZTILT
are specified. The default is /XYZ for X, Y, then Z rotations.
inf_fn : string
specify a new influence function as a FITS file with the same header keywords as
PROPER's default influence function. Needs these values in info.PrimaryData.Keywords:
'P2PDX_M' % pixel width x (m)
'P2PDY_M' % pixel width y (m)
'C2CDX_M' % actuator pitch x (m)
'C2CDY_M' % actuator pitch y (m)
inf_sign : {+,-}
specifies the sign (+/-) of the influence function. Given as an option because
the default influence function file is positive, but positive DM actuator
commands make a negative deformation for Xinetics and BMC DMs.
Raises
------
ValueError:
User cannot specify both actuator spacing and N_ACT_ACROSS_PUPIL
ValueError:
User must specify either actuator spacing or N_ACT_ACROSS_PUPIL
"""
if "ZYX" in kwargs and "XYZ" in kwargs:
raise ValueError('PROP_DM: Error: Cannot specify both XYZ and ZYX ' +
'rotation orders. Stopping')
elif "ZYX" not in kwargs and 'XYZ' not in kwargs:
XYZ = 1 # default is rotation around X, then Y, then Z
# ZYX = 0
elif "ZYX" in kwargs:
# ZYX = 1
XYZ = 0
elif "XYZ" in kwargs:
XYZ = 1
# ZYX = 0
if "XTILT" in kwargs:
xtilt = kwargs["XTILT"]
else:
xtilt = 0.
if "YTILT" in kwargs:
ytilt = kwargs["YTILT"]
else:
ytilt = 0.
if "ZTILT" in kwargs:
ztilt = kwargs["ZTILT"]
else:
ztilt = 0.
if type(dm_z0) == str:
dm_z = proper.prop_fits_read(dm_z0) # Read DM setting from FITS file
else:
dm_z = dm_z0
if "inf_fn" in kwargs:
inf_fn = kwargs["inf_fn"]
else:
inf_fn = "influence_dm5v2.fits"
if "inf_sign" in kwargs:
if(kwargs["inf_sign"] == '+'):
sign_factor = 1.
elif(kwargs["inf_sign"] == '-'):
sign_factor = -1.
else:
sign_factor = 1.
n = proper.prop_get_gridsize(wf)
dx_surf = proper.prop_get_sampling(wf) # sampling of surface in meters
beamradius = proper.prop_get_beamradius(wf)
# Default influence function sampling is 0.1 mm, peak at (x,y)=(45,45)
# Default influence function has shape = 1x91x91. Saving it as a 2D array
# before continuing with processing
dir_path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"data")
inf = proper.prop_fits_read(os.path.join(dir_path, inf_fn))
inf = sign_factor*np.squeeze(inf)
s = inf.shape
nx_inf = s[1]
ny_inf = s[0]
xc_inf = nx_inf // 2
yc_inf = ny_inf // 2
dx_inf = 0.1e-3 # influence function spacing in meters
dx_dm_inf = 1.0e-3 # nominal spacing between DM actuators in meters
inf_mag = 10
if spacing != 0 and "N_ACT_ACROSS_PUPIL" in kwargs:
raise ValueError("PROP_DM: User cannot specify both actuator spacing" +
"and N_ACT_ACROSS_PUPIL. Stopping.")
if spacing == 0 and "N_ACT_ACROSS_PUPIL" not in kwargs:
raise ValueError("PROP_DM: User must specify either actuator spacing" +
" or N_ACT_ACROSS_PUPIL. Stopping.")
if "N_ACT_ACROSS_PUPIL" in kwargs:
dx_dm = 2. * beamradius / int(kwargs["N_ACT_ACROSS_PUPIL"])
else:
dx_dm = spacing
dx_inf = dx_inf * dx_dm / dx_dm_inf # Influence function sampling scaled
# to specified DM actuator spacing
if "FIT" in kwargs:
x = (np.arange(5, dtype=np.float64) - 2) * dx_dm
if proper.use_cubic_conv:
inf_kernel = proper.prop_cubic_conv(inf.T, x/dx_inf+xc_inf,
x/dx_inf+yc_inf, GRID=True)
else:
xygrid = np.meshgrid(x/dx_inf+xc_inf, x/dx_inf+yc_inf)
inf_kernel = map_coordinates(inf.T, xygrid, order=3,
mode="nearest")
(dm_z_commanded, dms) = proper.prop_fit_dm(dm_z, inf_kernel)
else:
dm_z_commanded = dm_z
s = dm_z.shape
nx_dm = s[1]
ny_dm = s[0]
# Create subsampled DM grid
margin = 9 * inf_mag
nx_grid = nx_dm * inf_mag + 2 * margin
ny_grid = ny_dm * inf_mag + 2 * margin
xoff_grid = margin + inf_mag/2 # pixel location of 1st actuator center in subsampled grid
yoff_grid = xoff_grid
dm_grid = np.zeros([ny_grid, nx_grid], dtype = np.float64)
x = np.arange(nx_dm, dtype=int) * int(inf_mag) + int(xoff_grid)
y = np.arange(ny_dm, dtype=int) * int(inf_mag) + int(yoff_grid)
dm_grid[np.tile(np.vstack(y), (nx_dm,)),
np.tile(x, (ny_dm, 1))] = dm_z_commanded
dm_grid = ss.fftconvolve(dm_grid, inf, mode='same')
# 3D rotate DM grid and project orthogonally onto wavefront
xdim = int(np.round(np.sqrt(2) * nx_grid * dx_inf / dx_surf)) # grid dimensions (pix) projected onto wavefront
ydim = int(np.round(np.sqrt(2) * ny_grid * dx_inf / dx_surf))
if xdim > n: xdim = n
if ydim > n: ydim = n
x = np.ones((ydim, 1), dtype=int) * ((np.arange(xdim) - xdim // 2) * dx_surf)
y = (np.ones((xdim, 1), dtype=int) * ((np.arange(ydim) - ydim // 2) * dx_surf)).T
a = xtilt * np.pi / 180
b = ytilt * np.pi / 180
g = ztilt * np.pi /180
if XYZ:
m = np.array([[cos(b)*cos(g), -cos(b)*sin(g), sin(b), 0],
[cos(a)*sin(g) + sin(a)*sin(b)*cos(g), cos(a)*cos(g)-sin(a)*sin(b)*sin(g), -sin(a)*cos(b), 0],
[sin(a)*sin(g)-cos(a)*sin(b)*cos(g), sin(a)*cos(g)+cos(a)*sin(b)*sin(g), cos(a)*cos(b), 0],
[0, 0, 0, 1] ])
else:
m = np.array([ [cos(b)*cos(g), cos(g)*sin(a)*sin(b)-cos(a)*sin(g), cos(a)*cos(g)*sin(b)+sin(a)*sin(g), 0],
[cos(b)*sin(g), cos(a)*cos(g)+sin(a)*sin(b)*sin(g), -cos(g)*sin(a)+cos(a)*sin(b)*sin(g), 0],
[-sin(b), cos(b)*sin(a), cos(a)*cos(b), 0],
[0, 0, 0, 1] ])
# Forward project a square
edge = np.array([[-1.0, -1.0, 0.0, 0.0],
[1.0, -1.0, 0.0, 0.0],
[1.0, 1.0, 0.0, 0.0],
[-1.0, 1.0, 0.0, 0.0]])
new_xyz = np.dot(edge, m)
# determine backward projection for screen-raster-to-DM-surce computation
dx_dxs = (new_xyz[0, 0] - new_xyz[1, 0]) / (edge[0, 0] - edge[1, 0])
dx_dys = (new_xyz[1, 0] - new_xyz[2, 0]) / (edge[1, 1] - edge[2, 1])
dy_dxs = (new_xyz[0, 1] - new_xyz[1, 1]) / (edge[0, 0] - edge[1, 0])
dy_dys = (new_xyz[1, 1] - new_xyz[2, 1]) / (edge[1, 1] - edge[2, 1])
xs = (x/dx_dxs - y*dx_dys/(dx_dxs*dy_dys)) / \
(1 - dy_dxs*dx_dys/(dx_dxs*dy_dys))
ys = (y/dy_dys - x*dy_dxs/(dx_dxs*dy_dys)) / \
(1 - dx_dys*dy_dxs/(dx_dxs*dy_dys))
xdm = (xs + dm_xc * dx_dm) / dx_inf + xoff_grid
ydm = (ys + dm_yc * dx_dm) / dx_inf + yoff_grid
if proper.use_cubic_conv:
grid = proper.prop_cubic_conv(dm_grid.T, xdm, ydm, GRID = False)
grid = grid.reshape([xdm.shape[1], xdm.shape[0]])
else:
grid = map_coordinates(dm_grid.T, [xdm, ydm], order=3,
mode="nearest", prefilter = True)
dmap = np.zeros([n, n], dtype=np.float64)
nx_grid, ny_grid = grid.shape
xmin, xmax = n // 2 - xdim // 2, n // 2 - xdim // 2 + nx_grid
ymin, ymax = n // 2 - ydim // 2, n // 2 - ydim // 2 + ny_grid
dmap[ymin:ymax, xmin:xmax] = grid
if "NO_APPLY" not in kwargs:
proper.prop_add_phase(wf, 2 * dmap) # convert surface to WFE
return dmap
def derotate_resize_surface(surfaceToFit, dx, Nact, dm_xc, dm_yc, spacing,
**kwargs):
"""
Derotate and resize a DM surface to size and alignment of actuator grid.
Does the order of operations in the reverse order of PROPER's prop_dm.
Parameters
----------
surfaceToFit : numpy ndarray
2-D DM surface map to be fitted
dx : float
width of a pixel in meters
Nact : int
number of actuators across the DM array
dm_xc, dm_yc : list or numpy ndarray
The location of the optical axis (center of the wavefront) on the DM in
actuator units (0 ro num_actuator-1). The center of the first actuator
is (0.0, 0.0)
spacing : float
Spacing in meters between actuator centers (aka the pitch).
Returns
-------
gridDerotAtActRes : numpy ndarray
Returns DM surface at same alignment and resolution as the DM actuator
array.
Other Parameters
----------------
XTILT, YTILT, ZTILT : float
Specify the rotation of the DM surface with respect to the wavefront plane
in degrees about the X, Y, Z axes, respectively, with the origin at the
center of the wavefront. The DM surface is interpolated and orthographically
projected onto the wavefront grid. The coordinate system assumes that
the wavefront and initial DM surface are in the X,Y plane with a lower
left origin with Z towards the observer. The rotations are left handed.
The default rotation order is X, Y, then Z unless the /ZYX switch is set.
XYZ or ZYX : bool
Specifies the rotation order if two or more of XTILT, YTILT, or ZTILT
are specified. The default is /XYZ for X, Y, then Z rotations.
inf_fn : string
specify a new influence function as a FITS file with the same header keywords as
PROPER's default influence function. Needs these values in info.PrimaryData.Keywords:
'P2PDX_M' % pixel width x (m)
'P2PDY_M' % pixel width y (m)
'C2CDX_M' % actuator pitch x (m)
'C2CDY_M' % actuator pitch y (m)
inf_sign : {+,-}
specifies the sign (+/-) of the influence function. Given as an option because
the default influence function file is positive, but positive DM actuator
commands make a negative deformation for Xinetics and BMC DMs.
Raises
------
ValueError:
User cannot specify both ZYX and XYZ rotations.
"""
check.twoD_array(surfaceToFit, 'surfaceToFit', TypeError)
check.real_positive_scalar(dx, 'dx', TypeError)
check.real_scalar(dm_xc, 'dm_xc', TypeError)
check.real_scalar(dm_yc, 'dm_yc', TypeError)
check.real_positive_scalar(spacing, 'spacing', TypeError)
if "ZYX" in kwargs and "XYZ" in kwargs:
raise ValueError('Error: Cannot specify both XYZ and ZYX rotation' +
' orders. Stopping')
elif "ZYX" not in kwargs and 'XYZ' not in kwargs:
XYZ = 1 # default is rotation around X, then Y, then Z
# ZYX = 0
elif "ZYX" in kwargs:
# ZYX = 1
XYZ = 0
elif "XYZ" in kwargs:
XYZ = 1
# ZYX = 0
if "XTILT" in kwargs:
xtilt = kwargs["XTILT"]
else:
xtilt = 0.
if "YTILT" in kwargs:
ytilt = kwargs["YTILT"]
else:
ytilt = 0.
if "ZTILT" in kwargs:
ztilt = kwargs["ZTILT"]
else:
ztilt = 0.
dm_z = np.eye(Nact)
if "inf_fn" in kwargs:
inf_fn = kwargs["inf_fn"]
else:
inf_fn = "influence_dm5v2.fits"
if "inf_sign" in kwargs:
if(kwargs["inf_sign"] == '+'):
sign_factor = 1.
elif(kwargs["inf_sign"] == '-'):
sign_factor = -1.
else:
sign_factor = 1.
n = surfaceToFit.shape[0]
dx_surf = dx # sampling of current surface in meters
# Default influence function sampling is 0.1 mm, peak at (x,y)=(45,45)
# Default influence function has shape = 1x91x91. Saving it as a 2D array
# before continuing with processing
dir_path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"data")
inf = proper.prop_fits_read(os.path.join(dir_path, inf_fn))
inf = sign_factor*np.squeeze(inf)
s = inf.shape
nx_inf = s[1]
ny_inf = s[0]
xc_inf = nx_inf // 2
yc_inf = ny_inf // 2
dx_inf = 0.1e-3 # influence function spacing in meters
dx_dm_inf = 1.e-3 # spacing between DM actuators in meters assumed by influence function
inf_mag = 10
dx_dm = spacing
dx_inf = dx_inf * dx_dm / dx_dm_inf # Influence function sampling scaled
# to specified DM actuator spacing
dm_z_commanded = dm_z
s = dm_z.shape
nx_dm = s[1]
ny_dm = s[0]
# Create subsampled DM grid
margin = 9 * inf_mag
nx_grid = nx_dm * inf_mag + 2 * margin
ny_grid = ny_dm * inf_mag + 2 * margin
xoff_grid = margin + inf_mag/2 # pixel location of 1st actuator center in subsampled grid
yoff_grid = xoff_grid
dm_grid = np.zeros([ny_grid, nx_grid], dtype = np.float64)
x = np.arange(nx_dm, dtype=int) * int(inf_mag) + int(xoff_grid)
y = np.arange(ny_dm, dtype=int) * int(inf_mag) + int(yoff_grid)
dm_grid[np.tile(np.vstack(y), (nx_dm,)), np.tile(x, (ny_dm, 1))] = dm_z_commanded
dm_grid = ss.fftconvolve(dm_grid, inf, mode='same')
# 3D rotate DM grid and project orthogonally onto wavefront
xdim = int(np.round(np.sqrt(2) * nx_grid * dx_inf / dx_surf)) # grid dimensions (pix) projected onto wavefront
ydim = int(np.round(np.sqrt(2) * ny_grid * dx_inf / dx_surf))
if xdim > n: xdim = n
if ydim > n: ydim = n
x = np.ones((ydim,1), dtype=int) * ((np.arange(xdim) - xdim // 2) * dx_surf)
y = (np.ones((xdim,1), dtype=int) * ((np.arange(ydim) - ydim // 2) * dx_surf)).T
a = xtilt * np.pi / 180
b = ytilt * np.pi / 180
g = ztilt * np.pi / 180
if XYZ:
m = np.array([ [cos(b)*cos(g), -cos(b)*sin(g), sin(b), 0],
[cos(a)*sin(g) + sin(a)*sin(b)*cos(g), cos(a)*cos(g)-sin(a)*sin(b)*sin(g), -sin(a)*cos(b), 0],
[sin(a)*sin(g)-cos(a)*sin(b)*cos(g), sin(a)*cos(g)+cos(a)*sin(b)*sin(g), cos(a)*cos(b), 0],
[0, 0, 0, 1] ])
else:
m = np.array([ [cos(b)*cos(g), cos(g)*sin(a)*sin(b)-cos(a)*sin(g), cos(a)*cos(g)*sin(b)+sin(a)*sin(g), 0],
[cos(b)*sin(g), cos(a)*cos(g)+sin(a)*sin(b)*sin(g), -cos(g)*sin(a)+cos(a)*sin(b)*sin(g), 0],
[-sin(b), cos(b)*sin(a), cos(a)*cos(b), 0],
[0, 0, 0, 1] ])
# Compute xdm0 and ydm0 for use in de-rotating the DM surface
edge = np.array([[-1.0,-1.0,0.0,0.0], [1.0,-1.0,0.0,0.0], [1.0,1.0,0.0,0.0], [-1.0,1.0,0.0,0.0]])
new_xyz = edge #np.dot(edge, m)
# determine backward projection for screen-raster-to-DM-surce computation
dx_dxs = (new_xyz[0, 0] - new_xyz[1, 0]) / (edge[0, 0] - edge[1, 0])
dx_dys = (new_xyz[1, 0] - new_xyz[2, 0]) / (edge[1, 1] - edge[2, 1])
dy_dxs = (new_xyz[0, 1] - new_xyz[1, 1]) / (edge[0, 0] - edge[1, 0])
dy_dys = (new_xyz[1, 1] - new_xyz[2, 1]) / (edge[1, 1] - edge[2, 1])
xs = (x/dx_dxs - y*dx_dys/(dx_dxs*dy_dys) ) / ( 1 - dy_dxs*dx_dys/(dx_dxs*dy_dys))
ys = (y/dy_dys - x*dy_dxs/(dx_dxs*dy_dys) ) / ( 1 - dx_dys*dy_dxs/(dx_dxs*dy_dys))
xdm0 = (xs + dm_xc * dx_dm) / dx_inf + xoff_grid
ydm0 = (ys + dm_yc * dx_dm) / dx_inf + yoff_grid
######
# Forward project a square
# edge = np.array([[-1.0,-1.0,0.0,0.0], [1.0,-1.0,0.0,0.0],
# [1.0,1.0,0.0,0.0], [-1.0,1.0,0.0,0.0]])
new_xyz = np.dot(edge, m)
# determine backward projection for screen-raster-to-DM-surce computation
dx_dxs = (new_xyz[0, 0] - new_xyz[1, 0]) / (edge[0, 0] - edge[1, 0])
dx_dys = (new_xyz[1, 0] - new_xyz[2, 0]) / (edge[1, 1] - edge[2, 1])
dy_dxs = (new_xyz[0, 1] - new_xyz[1, 1]) / (edge[0, 0] - edge[1, 0])
dy_dys = (new_xyz[1, 1] - new_xyz[2, 1]) / (edge[1, 1] - edge[2, 1])
xs = (x/dx_dxs - y*dx_dys/(dx_dxs*dy_dys)) / \
(1 - dy_dxs*dx_dys/(dx_dxs*dy_dys))
ys = (y/dy_dys - x*dy_dxs/(dx_dxs*dy_dys)) / \
(1 - dx_dys*dy_dxs/(dx_dxs*dy_dys))
xdm = (xs + dm_xc * dx_dm) / dx_inf + xoff_grid
ydm = (ys + dm_yc * dx_dm) / dx_inf + yoff_grid
# if proper.use_cubic_conv:
# grid = proper.prop_cubic_conv(dm_grid.T, xdm, ydm, GRID = False)
# grid = grid.reshape([xdm.shape[1], xdm.shape[0]])
# else:
# grid = map_coordinates(dm_grid.T, [xdm, ydm], order=3,
# mode="nearest", prefilter = True)
# dm_grid = falco.util.pad_crop(surfaceToFit, xdm.shape[0])
# Derotate the DM surface
dm_grid = falco.util.pad_crop(surfaceToFit, xdm.shape[0])
gridDerot = griddata((xdm.flatten(), ydm.flatten()), dm_grid.flatten(),
(xdm0, ydm0), method='cubic', fill_value=0.)
# gridDerot(isnan(gridDerot)) = 0
# Resize and decimate the DM surface to get it at the same size as the DM
# actuator command array.
# The result will be fed to fit_surf_to_act() for deconvolution with the
# influence function.
xOffsetInAct = ((Nact/2 - 1/2) - dm_xc)
yOffsetInAct = ((Nact/2 - 1/2) - dm_yc)
multipleOfCommandGrid = int(falco.util.ceil_odd(spacing/dx))
N1 = Nact*multipleOfCommandGrid
N2 = dm_grid.shape[0]
xs1 = np.linspace(-(N1-1)/2, (N1-1)/2, N1)/N1 # interpixel centered
if(N2 % 2 == 0):
xs2 = np.linspace(-N2/2, (N2/2)-1, N2)/N2*(N2*dx/(Nact*spacing))
else:
xs2 = np.linspace(-(N2-1)/2, (N2-1)/2, N2)/N2*(N2*dx/(Nact*spacing))
interp_spline = RectBivariateSpline(xs2, xs2, gridDerot)
gridDerotResize = interp_spline(xs1-xOffsetInAct/Nact,
xs1-yOffsetInAct/Nact)
xyOffset = int(np.floor(multipleOfCommandGrid/2.))
gridDerotAtActRes = gridDerotResize[xyOffset::multipleOfCommandGrid,
xyOffset::multipleOfCommandGrid]
#
# plt.figure(11); plt.imshow(dm_grid); plt.colorbar(); plt.pause(0.1)
# plt.figure(12); plt.imshow(gridDerot); plt.colorbar(); plt.pause(0.1)
# plt.figure(13); plt.imshow(gridDerotResize); plt.colorbar(); plt.pause(0.1)
# plt.figure(14); plt.imshow(gridDerotAtActRes); plt.colorbar(); plt.pause(0.1)
# plt.figure(15); plt.imshow(gridDerot-gridDerot[::-1,::-1]); plt.colorbar(); plt.pause(0.1)
# plt.figure(16); plt.imshow(gridDerotResize-gridDerotResize[::-1,::-1]); plt.colorbar(); plt.pause(0.1)
return gridDerotAtActRes
def polab( polfile, lambda_m, pupil_diam_pix, condition ):
if abs(condition) == 1:
dir_out = 0
else:
dir_out = 1 # dir_out: output polarization (1=X, 2=Y)
if condition < 0:
dir_in = 0
else:
dir_in = 1 # dir_in: input polarization (negative=-45d, positive=+45d)
# zernike coefficient files are [nzer, nlam, ndir_in, ndir_out]
# nzer = 22 (number of zernikes)
# nlam = 6 or 11 (450 - 950 nm in 100 or 50 nm steps)
# ndir_in = 2 (input polarization direction, 0=-45 deg, 1=+45 deg)
# ndir_out = 2 (output polarization direction, 0=X, 1=Y)
zamp_array = proper.prop_fits_read( polfile+'_amp.fits' )
zpha_array = proper.prop_fits_read( polfile+'_pha.fits' )
nlam = zamp_array.shape[2]
if nlam == 6:
lam_array_m = (np.arange(6) * 100 + 450) * 1.0e-9
else:
lam_array_m = (np.arange(11) * 50 + 450) * 1.0e-9
# interpolate to get zernikes at specified wavelength
zamp = np.zeros([22])
zpha = np.zeros([22])
for iz in range(0, 22):
famp = interp1d( lam_array_m, zamp_array[dir_out, dir_in, :, iz], kind='cubic' )
fpha = interp1d( lam_array_m, zpha_array[dir_out, dir_in, :, iz], kind='cubic' )
lam = lambda_m
if lam < 0.45e-6: lam = 0.45e-6
if lam > 0.95e-6: lam = 0.95e-6
zamp[iz] = famp( lambda_m )
zpha[iz] = fpha( lambda_m )
n = int(round(pupil_diam_pix * 1.1))
n = (n // 2) * 2 # force even
x = (np.arange(n) - n//2) / (pupil_diam_pix/2.0)
amp = np.zeros([n,n])
pha = np.zeros([n,n])
for j in range(0, n):
y = x[j]
r2 = x**2 + y**2
r = np.sqrt(r2)
r3 = r**3
r4 = r**4
r5 = r**5
r6 = r**6
t = np.arctan2(y,x)
for itype in range(0,2): # 0 = amp, 1 = phase
map = np.zeros([n])
if itype == 0:
z = zamp
map += z[0] # include piston if amplitude map
else:
z = zpha
map += (z[1] * 2 * x) # x tilt
map += (z[2] * 2 * y) # y tilt
map += (z[3] * np.sqrt(3) * (2*r2 - 1)) # focus
map += (z[4] * np.sqrt(6) * r2 * np.sin(2*t)) # 45 deg astig
map += (z[5] * np.sqrt(6) * r2 * np.cos(2*t)) # 0 deg astig
map += (z[6] * np.sqrt(8) * (3*r3 - 2*r) * np.sin(t)) # y coma
map += (z[7] * np.sqrt(8) * (3*r3 - 2*r) * np.cos(t)) # x coma
map += (z[8] * np.sqrt(8) * r3 * np.sin(3*t)) # y trefoil
map += (z[9] * np.sqrt(8) * r3 * np.cos(3*t)) # x trefoil
map += (z[10] * np.sqrt(5) * (6*r4 - 6*r2 + 1)) # spherical
map += (z[11] * np.sqrt(10) * (4*r4 - 3*r2) * np.cos(2*t))
map += (z[12] * np.sqrt(10) * (4*r4 - 3*r2) * np.sin(2*t))
map += (z[13] * np.sqrt(10) * r4 * np.cos(4*t))
map += (z[14] * np.sqrt(10) * r4 * np.sin(4*t))
map += (z[15] * np.sqrt(12) * (10*r5 - 12*r3 + 3*r) * np.cos(t))
map += (z[16] * np.sqrt(12) * (10*r5 - 12*r3 + 3*r) * np.sin(t))
map += (z[17] * np.sqrt(12) * (5*r5 - 4*r3) * np.cos(3*t))
map += (z[18] * np.sqrt(12) * (5*r5 - 4*r3) * np.sin(3*t))
map += (z[19] * np.sqrt(12) * r5 * np.cos(5*t))
map += (z[20] * np.sqrt(12) * r5 * np.sin(5*t))
map += (z[21] * np.sqrt(7) * (20*r6 - 30*r4 + 12*r2 - 1))
if itype == 0:
amp[j,:] = map
else:
pha[j,:] = map
return amp, pha
def run_hlc():
nlam = 7
lam0 = 0.575
bandwidth = 0.1
minlam = lam0 * (1 - bandwidth / 2)
maxlam = lam0 * (1 + bandwidth / 2)
lam_array = np.linspace(minlam, maxlam, nlam)
n = 256 # output image dimension (must be power of 2)
final_sampling = 0.1 # output sampling in lam0/D
# compute unaberrated coronagraphic field using Dwight's DM wavefront maps
print(
"Computing unaberrated coronagraphic field using DM wavefront map...")
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'hlc','use_errors':0,'zindex':[4],'zval_m':[0.19e-9],
'use_hlc_dm_patterns':1,'final_sampling_lam0':final_sampling} )
images = np.abs(fields)**2
image = np.sum(images, 0) / nlam
# compute unaberrated coronagraphic field using DM actuator settings
print(
"Computing unaberrated coronagraphic field using DM actuator pistons..."
)
dm1 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/hlc_dm1.fits')
dm2 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/hlc_dm2.fits')
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'hlc','use_errors':0,'zindex':[4],'zval_m':[0.19e-9],
'use_hlc_dm_patterns':0,'final_sampling_lam0':final_sampling,
'use_dm1':1, 'dm1_m':dm1, 'use_dm2':1, 'dm2_m':dm2} )
images = np.abs(fields)**2
image_dm = np.sum(images, 0) / nlam
# compute aberrated coronagraphic field using DM actuator settings
print(
"Computing aberrated coronagraphic field using DM actuator pistons...")
dm1 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/hlc_with_aberrations_dm1.fits')
dm2 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/hlc_with_aberrations_dm2.fits')
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'hlc', 'use_errors':1, 'polaxis':10,
'use_hlc_dm_patterns':0, 'final_sampling_lam0':final_sampling,
'use_dm1':1, 'dm1_m':dm1, 'use_dm2':1, 'dm2_m':dm2} )
images = np.abs(fields)**2
image_ab = np.sum(images, 0) / nlam
# move source to 7 lam/D
print("Computing offset source to compute NI...")
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb_compact', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'hlc','source_x_offset':7.0,'use_hlc_dm_patterns':1,'final_sampling_lam0':final_sampling} )
psfs = np.abs(fields)**2
psf = np.sum(psfs, 0) / nlam
max_psf = np.max(psf)
ni = image / max_psf
ni_dm = image_dm / max_psf
ni_ab = image_ab / max_psf
fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(11, 4))
im = ax[0].imshow(ni,
norm=LogNorm(vmin=1e-10, vmax=1e-7),
cmap=plt.get_cmap('jet'))
circ_in = Circle((n / 2, n / 2),
3 / final_sampling,
edgecolor='white',
facecolor='none')
circ_out = Circle((n / 2, n / 2),
9 / final_sampling,
edgecolor='white',
facecolor='none')
ax[0].add_patch(circ_in)
ax[0].add_patch(circ_out)
ax[0].set_title('Unaberrated,\nUsing wavefront maps')
fig.colorbar(im, ax=ax[0], shrink=0.5)
im = ax[1].imshow(ni_dm,
norm=LogNorm(vmin=1e-10, vmax=1e-7),
cmap=plt.get_cmap('jet'))
circ_in = Circle((n / 2, n / 2),
3 / final_sampling,
edgecolor='white',
facecolor='none')
circ_out = Circle((n / 2, n / 2),
9 / final_sampling,
edgecolor='white',
facecolor='none')
ax[1].add_patch(circ_in)
ax[1].add_patch(circ_out)
ax[1].set_title('Unaberrated,\nUsing DM piston maps')
fig.colorbar(im, ax=ax[1], shrink=0.5)
im = ax[2].imshow(ni_ab,
norm=LogNorm(vmin=1e-10, vmax=1e-7),
cmap=plt.get_cmap('jet'))
circ_in = Circle((n / 2, n / 2),
3 / final_sampling,
edgecolor='white',
facecolor='none')
circ_out = Circle((n / 2, n / 2),
9 / final_sampling,
edgecolor='white',
facecolor='none')
ax[2].add_patch(circ_in)
ax[2].add_patch(circ_out)
ax[2].set_title('Aberrated,\nUsing DM piston maps')
fig.colorbar(im, ax=ax[2], shrink=0.5)
plt.show()
def wfirst_phaseb_compact(lambda_m, output_dim0, PASSVALUE={'dummy': 0}):
# "output_dim" is used to specify the output dimension in pixels at the final image plane.
# Computational grid sizes are hardcoded for each coronagraph.
# Based on Zemax prescription "WFIRST_CGI_DI_LOWFS_Sep24_2018.zmx" by Hong Tang.
data_dir = wfirst_phaseb_proper.data_dir
if 'PASSVALUE' in locals():
if 'data_dir' in PASSVALUE: data_dir = PASSVALUE['data_dir']
cor_type = 'hlc' # coronagraph type ('hlc', 'spc', 'none')
input_field_rootname = '' # rootname of files containing aberrated pupil
polaxis = 0 # polarization condition (only used with input_field_rootname)
source_x_offset = 0 # source offset in lambda0_m/D radians (tilt applied at primary)
source_y_offset = 0
use_hlc_dm_patterns = 0 # use Dwight's HLC default DM wavefront patterns? 1 or 0
use_dm1 = 0 # use DM1? 1 or 0
use_dm2 = 0 # use DM2? 1 or 0
dm_sampling_m = 0.9906e-3 # actuator spacing in meters
dm1_xc_act = 23.5 # for 48x48 DM, wavefront centered at actuator intersections: (0,0) = 1st actuator center
dm1_yc_act = 23.5
dm1_xtilt_deg = 0 # tilt around X axis (deg)
dm1_ytilt_deg = 5.7 # effective DM tilt in deg including 9.65 deg actual tilt and pupil ellipticity
dm1_ztilt_deg = 0 # rotation of DM about optical axis (deg)
dm2_xc_act = 23.5 # for 48x48 DM, wavefront centered at actuator intersections: (0,0) = 1st actuator center
dm2_yc_act = 23.5
dm2_xtilt_deg = 0 # tilt around X axis (deg)
dm2_ytilt_deg = 5.7 # effective DM tilt in deg including 9.65 deg actual tilt and pupil ellipticity
dm2_ztilt_deg = 0 # rotation of DM about optical axis (deg)
fpm_axis = 'p' # HLC FPM axis: '', 's', 'p'
final_sampling_lam0 = 0 # final sampling in lambda0/D
output_dim = output_dim0 # dimension of output in pixels (overrides output_dim0)
if 'PASSVALUE' in locals():
if 'cor_type' in PASSVALUE: cor_type = PASSVALUE['cor_type']
if 'fpm_axis' in PASSVALUE: fpm_axis = PASSVALUE['fpm_axis']
is_hlc = False
is_spc = False
if cor_type == 'hlc':
is_hlc = True
file_directory = data_dir + '/hlc_20190210/' # must have trailing "/"
prefix = file_directory + 'run461_'
pupil_diam_pix = 309.0
pupil_file = prefix + 'pupil_rotated.fits'
lyot_stop_file = prefix + 'lyot.fits'
lambda0_m = 0.575e-6
lam_occ = [
5.4625e-07, 5.49444444444e-07, 5.52638888889e-07, 5.534375e-07,
5.55833333333e-07, 5.59027777778e-07, 5.60625e-07,
5.62222222222e-07, 5.65416666667e-07, 5.678125e-07,
5.68611111111e-07, 5.71805555556e-07, 5.75e-07, 5.78194444444e-07,
5.81388888889e-07, 5.821875e-07, 5.84583333333e-07,
5.87777777778e-07, 5.89375e-07, 5.90972222222e-07,
5.94166666667e-07, 5.965625e-07, 5.97361111111e-07,
6.00555555556e-07, 6.0375e-07
]
lam_occs = [
'5.4625e-07', '5.49444444444e-07', '5.52638888889e-07',
'5.534375e-07', '5.55833333333e-07', '5.59027777778e-07',
'5.60625e-07', '5.62222222222e-07', '5.65416666667e-07',
'5.678125e-07', '5.68611111111e-07', '5.71805555556e-07',
'5.75e-07', '5.78194444444e-07', '5.81388888889e-07',
'5.821875e-07', '5.84583333333e-07', '5.87777777778e-07',
'5.89375e-07', '5.90972222222e-07', '5.94166666667e-07',
'5.965625e-07', '5.97361111111e-07', '6.00555555556e-07',
'6.0375e-07'
]
lam_occs = [
prefix + 'occ_lam' + s + 'theta6.69pol' + fpm_axis + '_'
for s in lam_occs
]
# find nearest matching FPM wavelength
wlam = (np.abs(lambda_m - np.array(lam_occ))).argmin()
occulter_file_r = lam_occs[wlam] + 'real_rotated.fits'
occulter_file_i = lam_occs[wlam] + 'imag_rotated.fits'
n_small = 1024 # gridsize in non-critical areas
n_big = 2048 # gridsize to/from FPM
elif cor_type == 'hlc_erkin':
is_hlc = True
file_directory = data_dir + '/hlc_20190206_v3/' # must have trailing "/"
prefix = file_directory + 'dsn17d_run2_pup310_fpm2048_'
pupil_diam_pix = 310.0
pupil_file = prefix + 'pupil.fits'
lyot_stop_file = prefix + 'lyot.fits'
lambda0_m = 0.575e-6
lam_occ = [
5.4625e-07, 5.4944e-07, 5.5264e-07, 5.5583e-07, 5.5903e-07,
5.6222e-07, 5.6542e-07, 5.6861e-07, 5.7181e-07, 5.75e-07,
5.7819e-07, 5.8139e-07, 5.8458e-07, 5.8778e-07, 5.9097e-07,
5.9417e-07, 5.9736e-07, 6.0056e-07, 6.0375e-07
]
lam_occs = [
'5.4625e-07', '5.4944e-07', '5.5264e-07', '5.5583e-07',
'5.5903e-07', '5.6222e-07', '5.6542e-07', '5.6861e-07',
'5.7181e-07', '5.75e-07', '5.7819e-07', '5.8139e-07', '5.8458e-07',
'5.8778e-07', '5.9097e-07', '5.9417e-07', '5.9736e-07',
'6.0056e-07', '6.0375e-07'
]
fpm_axis = 's'
lam_occs = [
prefix + 'occ_lam' + s + 'theta6.69pol' + fpm_axis + '_'
for s in lam_occs
]
# find nearest matching FPM wavelength
wlam = (np.abs(lambda_m - np.array(lam_occ))).argmin()
occulter_file_r = lam_occs[wlam] + 'real.fits'
occulter_file_i = lam_occs[wlam] + 'imag.fits'
n_small = 1024 # gridsize in non-critical areas
n_big = 2048 # gridsize to/from FPM
elif cor_type == 'spc-ifs_short' or cor_type == 'spc-ifs_long' or cor_type == 'spc-spec_short' or cor_type == 'spc-spec_long':
is_spc = True
file_dir = data_dir + '/spc_20190130/' # must have trailing "/"
pupil_diam_pix = 1000.0
pupil_file = file_dir + 'pupil_SPC-20190130_rotated.fits'
pupil_mask_file = file_dir + 'SPM_SPC-20190130_rotated.fits'
fpm_file = file_dir + 'fpm_0.05lamdivD.fits'
fpm_sampling = 0.05 # sampling in lambda0/D of FPM mask
if cor_type == 'spc-ifs_short' or cor_type == 'spc-spec_short':
fpm_sampling_lambda_m = 0.66e-6
lambda0_m = 0.66e-6
else:
fpm_sampling_lambda_m = 0.73e-6
lambda0_m = 0.73e-6 # FPM scaled for this central wavelength
lyot_stop_file = file_dir + 'lyotstop_0.5mag.fits'
n_small = 2048 # gridsize in non-critical areas
n_big = 1400 # gridsize to FPM (propagation to/from FPM handled by MFT)
elif cor_type == 'spc-wide':
is_spc = True
file_dir = data_dir + '/spc_20181220/' # must have trailing "/"
pupil_diam_pix = 1000.0
pupil_file = file_dir + 'pupil_SPC-20181220_1k_rotated.fits'
pupil_mask_file = file_dir + 'SPM_SPC-20181220_1000_rounded9_gray_rotated.fits'
fpm_file = file_dir + 'fpm_0.05lamdivD.fits'
fpm_sampling = 0.05 # sampling in lambda0/D of FPM mask
lyot_stop_file = file_dir + 'LS_half_symm_CGI180718_Str3.20pct_38D91_N500_pixel.fits'
fpm_sampling_lambda_m = 0.825e-6
lambda0_m = 0.825e-6 # FPM scaled for this central wavelength
n_small = 2048 # gridsize in non-critical areas
n_big = 1400 # gridsize to FPM (propagation to/from FPM handled by MFT)
elif cor_type == 'none':
file_directory = data_dir + '/hlc_20190210/' # must have trailing "/"
prefix = file_directory + 'run461_'
pupil_diam_pix = 309.0
pupil_file = prefix + 'pupil_rotated.fits'
use_fpm = 0
use_lyot_stop = 0
n_small = 1024
n_big = 1024
else:
raise Exception('wfirst_phaseb_compact: Unsuported cor_type: ' +
cor_type)
if 'PASSVALUE' in locals():
if 'lam0' in PASSVALUE: lamba0_m = PASSVALUE['lam0'] * 1.0e-6
if 'lambda0_m' in PASSVALUE: lambda0_m = PASSVALUE['lambda0_m']
if 'input_field_rootname' in PASSVALUE:
input_field_rootname = PASSVALUE['input_field_rootname']
if 'polaxis' in PASSVALUE: polaxis = PASSVALUE['polaxis']
if 'source_x_offset' in PASSVALUE:
source_x_offset = PASSVALUE['source_x_offset']
if 'source_y_offset' in PASSVALUE:
source_y_offset = PASSVALUE['source_y_offset']
if 'use_hlc_dm_patterns' in PASSVALUE:
use_hlc_dm_patterns = PASSVALUE['use_hlc_dm_patterns']
if 'use_dm1' in PASSVALUE: use_dm1 = PASSVALUE['use_dm1']
if 'dm1_m' in PASSVALUE: dm1_m = PASSVALUE['dm1_m']
if 'dm1_xc_act' in PASSVALUE: dm1_xc_act = PASSVALUE['dm1_xc_act']
if 'dm1_yc_act' in PASSVALUE: dm1_yc_act = PASSVALUE['dm1_yc_act']
if 'dm1_xtilt_deg' in PASSVALUE:
dm1_xtilt_deg = PASSVALUE['dm1_xtilt_deg']
if 'dm1_ytilt_deg' in PASSVALUE:
dm1_ytilt_deg = PASSVALUE['dm1_ytilt_deg']
if 'dm1_ztilt_deg' in PASSVALUE:
dm1_ztilt_deg = PASSVALUE['dm1_ztilt_deg']
if 'use_dm2' in PASSVALUE: use_dm2 = PASSVALUE['use_dm2']
if 'dm2_m' in PASSVALUE: dm2_m = PASSVALUE['dm2_m']
if 'dm2_xc_act' in PASSVALUE: dm2_xc_act = PASSVALUE['dm2_xc_act']
if 'dm2_yc_act' in PASSVALUE: dm2_yc_act = PASSVALUE['dm2_yc_act']
if 'dm2_xtilt_deg' in PASSVALUE:
dm2_xtilt_deg = PASSVALUE['dm2_xtilt_deg']
if 'dm2_ytilt_deg' in PASSVALUE:
dm2_ytilt_deg = PASSVALUE['dm2_ytilt_deg']
if 'dm2_ztilt_deg' in PASSVALUE:
dm2_ztilt_deg = PASSVALUE['dm2_ztilt_deg']
if 'final_sampling_lam0' in PASSVALUE:
final_sampling_lam0 = PASSVALUE['final_sampling_lam0']
if 'output_dim' in PASSVALUE: output_dim = PASSVALUE['output_dim']
if polaxis != 0 and input_field_rootname == '':
raise Exception(
'wfirst_phaseb_compact: polaxis can only be defined when input_field_rootname is given'
)
diam_at_dm1 = 0.0463
d_dm1_dm2 = 1.0
n = n_small # start off with less padding
wavefront = proper.prop_begin(diam_at_dm1, lambda_m, n,
float(pupil_diam_pix) / n)
if input_field_rootname == '':
pupil = proper.prop_fits_read(pupil_file)
proper.prop_multiply(wavefront, trim(pupil, n))
pupil = 0
else:
lams = format(lambda_m * 1e6, "6.4f")
pols = format(int(round(polaxis)))
rval = proper.prop_fits_read(input_field_rootname + '_' + lams +
'um_' + pols + '_real.fits')
ival = proper.prop_fits_read(input_field_rootname + '_' + lams +
'um_' + pols + '_imag.fits')
proper.prop_multiply(wavefront, trim(rval + 1j * ival, n))
rval = 0
ival = 0
proper.prop_define_entrance(wavefront)
if source_x_offset != 0 or source_y_offset != 0:
# compute tilted wavefront to offset source by xoffset,yoffset lambda0_m/D
xtilt_lam = -source_x_offset * lambda0_m / lambda_m
ytilt_lam = -source_y_offset * lambda0_m / lambda_m
x = np.tile((np.arange(n) - n // 2) / (pupil_diam_pix / 2.0), (n, 1))
y = np.transpose(x)
proper.prop_multiply(
wavefront,
np.exp(complex(0, 1) * np.pi * (xtilt_lam * x + ytilt_lam * y)))
x = 0
y = 0
if use_dm1 != 0:
prop_dm(wavefront,
dm1_m,
dm1_xc_act,
dm1_yc_act,
dm_sampling_m,
XTILT=dm1_xtilt_deg,
YTILT=dm1_ytilt_deg,
ZTILT=dm1_ztilt_deg)
if is_hlc == True and use_hlc_dm_patterns == 1:
dm1wfe = proper.prop_fits_read(prefix + 'dm1wfe.fits')
proper.prop_add_phase(wavefront, trim(dm1wfe, n))
dm1wfe = 0
proper.prop_propagate(wavefront, d_dm1_dm2, 'DM2')
if use_dm2 == 1:
prop_dm(wavefront,
dm2_m,
dm2_xc_act,
dm2_yc_act,
dm_sampling_m,
XTILT=dm2_xtilt_deg,
YTILT=dm2_ytilt_deg,
ZTILT=dm2_ztilt_deg)
if is_hlc == True:
if use_hlc_dm_patterns == 1:
dm2wfe = proper.prop_fits_read(prefix + 'dm2wfe.fits')
proper.prop_add_phase(wavefront, trim(dm2wfe, n))
dm2wfe = 0
dm2mask = proper.prop_fits_read(prefix + 'dm2mask.fits')
proper.prop_multiply(wavefront, trim(dm2mask, n))
dm2mask = 0
proper.prop_propagate(wavefront, -d_dm1_dm2, 'back to DM1')
(wavefront, sampling_m) = proper.prop_end(wavefront, NOABS=True)
# apply shape pupil mask
if is_spc == True:
pupil_mask = proper.prop_fits_read(pupil_mask_file)
wavefront *= trim(pupil_mask, n)
pupil_mask = 0
# propagate to FPM and apply FPM
if is_hlc == True:
n = n_big
wavefront = trim(wavefront, n)
wavefront = ffts(wavefront, -1) # to focus
occ_r = proper.prop_fits_read(occulter_file_r)
occ_i = proper.prop_fits_read(occulter_file_i)
occ = np.array(occ_r + 1j * occ_i, dtype=np.complex128)
wavefront *= trim(occ, n)
occ_r = 0
occ_i = 0
occ = 0
wavefront = ffts(wavefront, +1) # to lyot stop
elif is_spc == True:
n = n_big
wavefront = trim(wavefront, n)
fpm = proper.prop_fits_read(fpm_file)
nfpm = fpm.shape[1]
fpm_sampling_lam = fpm_sampling * fpm_sampling_lambda_m / lambda_m
wavefront = mft2(wavefront, fpm_sampling_lam, pupil_diam_pix, nfpm,
-1) # MFT to highly-sampled focal plane
wavefront *= fpm
fpm = 0
pupil_diam_pix = pupil_diam_pix / 2.0 # Shrink pupil by 1/2
wavefront = mft2(wavefront, fpm_sampling_lam, pupil_diam_pix,
int(pupil_diam_pix),
+1) # MFT to Lyot stop with 1/2 magnification
n = n_small
wavefront = trim(wavefront, n)
lyot = proper.prop_fits_read(lyot_stop_file)
wavefront *= trim(lyot, n)
lyot = 0
wavefront *= n
wavefront = ffts(wavefront, -1) # to focus
# rotate to convention used by full prescription
wavefront[:, :] = np.rot90(wavefront, 2)
wavefront[:, :] = np.roll(wavefront, 1, axis=0)
wavefront[:, :] = np.roll(wavefront, 1, axis=1)
if final_sampling_lam0 != 0:
mag = (float(pupil_diam_pix) / n) / final_sampling_lam0 * (lambda_m /
lambda0_m)
wavefront = proper.prop_magnify(wavefront,
mag,
output_dim,
AMP_CONSERVE=True)
else:
wavefront = trim(wavefront, output_dim)
sampling_m = 0.0
return wavefront, sampling_m
def run_flatten():
nlam = 7
lam0 = 0.575
bandwidth = 0.1
minlam = lam0 * (1 - bandwidth / 2)
maxlam = lam0 * (1 + bandwidth / 2)
lam_array = np.linspace(minlam, maxlam, nlam)
n = 256
final_sampling = 0.1
# compute field before flattening (use HLC DM WFE maps)
print("Computing field before flattening...")
fields, sampling = proper.prop_run_multi( 'wfirst_phaseb', lam_array, n, QUIET=True, \
PASSVALUE={'final_sampling_lam0':final_sampling, 'use_hlc_dm_patterns':1, 'use_errors':1, 'polaxis':10} )
images = np.abs(fields)**2
image_before = np.sum(images, 0) / nlam
# compute field after flattening
dm1 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/errors_polaxis10_dm.fits')
print("Computing field after flattening...")
fields, sampling = proper.prop_run_multi( 'wfirst_phaseb', lam_array, n, QUIET=True, \
PASSVALUE={'final_sampling_lam0':final_sampling, 'use_dm1':1, 'dm1_m':dm1, 'use_hlc_dm_patterns':1, 'use_errors':1, 'polaxis':10} )
images = np.abs(fields)**2
image_after = np.sum(images, 0) / nlam
# move source by 7.0 lam/D
print("Computing offset source to compute NI...")
fields, sampling = proper.prop_run_multi( 'wfirst_phaseb_compact', lam_array, n, QUIET=True, \
PASSVALUE={'source_x_offset':7.0,'final_sampling_lam0':final_sampling,'use_hlc_dm_patterns':1} )
images = np.abs(fields)**2
psf = np.sum(images, 0) / nlam
max_psf = np.max(psf)
ni_before = image_before / max_psf
ni_after = image_after / max_psf
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(9, 4))
im = ax[0].imshow(ni_before,
norm=LogNorm(vmin=1e-7, vmax=1e-2),
cmap=plt.get_cmap('jet'))
circ = Circle((n / 2, n / 2),
3 / final_sampling,
edgecolor='white',
facecolor='none')
ax[0].add_patch(circ)
circ = Circle((n / 2, n / 2),
9 / final_sampling,
edgecolor='white',
facecolor='none')
ax[0].add_patch(circ)
ax[0].set_title('Before')
fig.colorbar(im, ax=ax[0], shrink=0.5)
im = ax[1].imshow(ni_after,
norm=LogNorm(vmin=1e-7, vmax=1e-2),
cmap=plt.get_cmap('jet'))
circ = Circle((n / 2, n / 2),
3 / final_sampling,
edgecolor='white',
facecolor='none')
ax[1].add_patch(circ)
circ = Circle((n / 2, n / 2),
9 / final_sampling,
edgecolor='white',
facecolor='none')
ax[1].add_patch(circ)
ax[1].set_title('After')
fig.colorbar(im, ax=ax[1], shrink=0.5)
plt.show()
def run_spc_wide_new():
nlam = 7
lam0 = 0.825
bandwidth = 0.1
minlam = lam0 * (1 - bandwidth / 2)
maxlam = lam0 * (1 + bandwidth / 2)
lam_array = np.linspace(minlam, maxlam, nlam)
n = 512 # output image dimension (must be power of 2)
final_sampling = 0.1 # output sampling in lam0/D
# compute unaberrated coronagraphic field
print("Computing unaberrated coronagraphic field using compact model...")
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb_compact', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'spc-wide','final_sampling_lam0':final_sampling} )
images = np.abs(fields)**2
image_noab = np.sum(images, 0) / nlam
# compute aberrated coronagraphic field using EFC-derived DM actuator settings
print(
"Computing aberrated coronagraphic field using DM actuator pistons...")
dm1 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/spc-wide_with_aberrations_dm1.fits')
dm2 = proper.prop_fits_read(wfirst_phaseb_proper.lib_dir +
'/examples/spc-wide_with_aberrations_dm2.fits')
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'spc-wide', 'use_errors':1, 'polaxis':10,
'final_sampling_lam0':final_sampling, 'use_dm1':1, 'dm1_m':dm1, 'use_dm2':1, 'dm2_m':dm2} )
images = np.abs(fields)**2
image_ab = np.sum(images, 0) / nlam
# move source to 10 lam/D
print("Computing offset source to compute NI...")
(fields, sampling) = proper.prop_run_multi('wfirst_phaseb_compact', lam_array, n, QUIET=True, \
PASSVALUE={'cor_type':'spc-wide','source_x_offset':10.0,'final_sampling_lam0':final_sampling} )
psfs = np.abs(fields)**2
psf = np.sum(psfs, 0) / nlam
max_psf = np.max(psf)
ni_noab = image_noab / max_psf
ni_ab = image_ab / max_psf
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))
im = ax[0].imshow(ni_noab,
norm=LogNorm(vmin=1e-10, vmax=1e-7),
cmap=plt.get_cmap('jet'))
circ_in = Circle((n / 2, n / 2),
5.4 / final_sampling,
edgecolor='white',
facecolor='none')
circ_out = Circle((n / 2, n / 2),
20 / final_sampling,
edgecolor='white',
facecolor='none')
ax[0].add_patch(circ_in)
ax[0].add_patch(circ_out)
ax[0].set_title('Unaberrated')
fig.colorbar(im, ax=ax[0], shrink=0.5)
im = ax[1].imshow(ni_ab,
norm=LogNorm(vmin=1e-10, vmax=1e-7),
cmap=plt.get_cmap('jet'))
circ_in = Circle((n / 2, n / 2),
5.4 / final_sampling,
edgecolor='white',
facecolor='none')
circ_out = Circle((n / 2, n / 2),
20 / final_sampling,
edgecolor='white',
facecolor='none')
ax[1].add_patch(circ_in)
ax[1].add_patch(circ_out)
ax[1].set_title('Aberrated,\nUsing DM piston maps')
fig.colorbar(im, ax=ax[1], shrink=0.5)
plt.show()