def atmosphere(wf, npupil, atm_screen, Debug_print, Debug):
n = int(proper.prop_get_gridsize(wf))
lamda=proper.prop_get_wavelength(wf) #save the wavelength value [m] into lamda
screen = atm_screen # read the phase screen
if (Debug_print == True):
print ("screen", screen.shape)
screen_pixels = (screen.shape)[0] # size of the phase screen
scaling_factor_screen = float(npupil)/float(screen_pixels) # scaling factor the phase screen to the simulation pupil size
if (Debug_print == True):
print ("scaling_factor_screen: ", scaling_factor_screen)
screen_scale = cv2.resize(screen.astype(np.float32), (0,0), fx=scaling_factor_screen, fy=scaling_factor_screen, interpolation=cv2.INTER_LINEAR) # scale the the phase screen to the simulation pupil size
if (Debug_print == True):
print ("screen_resample", screen_scale.shape)
screen_large = np.zeros((n,n)) # define an array of n-0s, where to insert the screen
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
screen_large[int(n/2)+1-int(npupil/2)-1:int(n/2)+1+int(npupil/2),int(n/2)+1-int(npupil/2)-1:int(n/2)+1+int(npupil/2)] =screen_scale # insert the scaled screen into the 0s grid
lambda2=lamda/(1e-6) # need to use lambda in microns
screen_atm = np.exp(1j*screen_large/lambda2*2*math.pi)
proper.prop_multiply(wf, screen_atm) # multiply the atm screen to teh wavefront
return wf
def add_errors(wf,
onaxis=True,
phase_screen=None,
amp_screen=None,
tiptilt=None,
misalign=[0, 0, 0, 0, 0, 0],
ngrid=1024,
verbose=False,
**conf):
# apply phase screen (scao residuals, ncpa, petal piston)
if phase_screen is not None:
assert phase_screen.ndim == 2, "phase_screen dim must be 2."
proper.prop_add_phase(wf, pad_img(phase_screen, ngrid))
# apply amplitude screen (Talbot effect)
if amp_screen is not None:
assert amp_screen.ndim == 2, "amp_screen dim must be 2."
proper.prop_multiply(wf, pad_img(amp_screen, ngrid))
# apply tip-tilt (Zernike 2,3)
if tiptilt is not None:
proper.prop_zernikes(wf, [2, 3], np.array(tiptilt, ndmin=1))
# pupil-plane apodization (already preloaded if no RA misalign)
if onaxis == False or ('RAVC' in conf['mode'] and misalign is not None):
conf.update(ravc_misalign=misalign)
wf = apodizer(wf, onaxis=onaxis, verbose=verbose, **conf)
return wf
def NCPA_application(wf, npupil, NCPA, path, Debug_print, Debug):
n = int(proper.prop_get_gridsize(wf))
lamda=proper.prop_get_wavelength(wf) #save the wavelength value [m] into lamda
if (Debug_print == True):
print ("NCPA", NCPA.shape)
NCPA_pixels = (NCPA.shape)[0] # size of the phase screen
scaling_factor_NCPA = float(npupil)/float(NCPA_pixels) # scaling factor the phase screen to the simulation pupil size
if (Debug_print == True):
print ("scaling_factor_NCPA: ", scaling_factor_NCPA)
NCPA_scale = cv2.resize(NCPA.astype(np.float32), (0,0), fx=scaling_factor_NCPA, fy=scaling_factor_NCPA, interpolation=cv2.INTER_LINEAR) # scale the the phase screen to the simulation pupil size
if (Debug_print == True):
print ("NCPA_resample", NCPA_scale.shape)
NCPA_large = np.zeros((n,n)) # define an array of n-0s, where to insert the screen
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
NCPA_large[int(n/2)+1-int(npupil/2)-1:int(n/2)+1+int(npupil/2),int(n/2)+1-int(npupil/2)-1:int(n/2)+1+int(npupil/2)] =NCPA_scale # insert the scaled screen into the 0s grid
if (Debug == 1):
fits.writeto(path + 'NCPA_large.fits', NCPA_large, overwrite=True) # fits file for the screen
lambda2=lamda/(1e-6) # need to use lambda in microns
screen_atm = np.exp(1j*NCPA_large/lambda2*2*math.pi)
proper.prop_multiply(wf, screen_atm) # multiply the atm screen to teh wavefront
#rms_error = NCPA[0]#30nm-- RMS wavefront error in meters
#c_freq = NCPA[1]# 5 ;-- correlation frequency (cycles/meter)
#high_power = NCPA[2]#3.0 ;-- high frequency falloff (r^-high_power)
#RANDOM_MAP = readfits('RANDOM_MAP.fits')
#proper.prop_psd_errormap_mod( wf, rms_error, c_freq, high_power, RMS=True)
return
def lyot_stop(wf, mode='RAVC', ravc_r=0.6, ls_dRext=0.03, ls_dRint=0.05,
ls_dRspi=0.04, spi_width=0.5, spi_angles=[0,60,120], diam_ext=37,
diam_int=11, ls_misalign=None, file_app_phase='', file_app_amp='',
ngrid=1024, npupil=285, margin=50, get_amp=False,
get_phase=False, verbose=False, **conf):
"""Add a Lyot stop, or an APP."""
# case 1: Lyot stop
if mode in ['CVC', 'RAVC']:
# LS parameters
r_obstr = ravc_r if mode in ['RAVC'] else diam_int/diam_ext
ls_int = r_obstr + ls_dRint
ls_ext = 1 - ls_dRext
ls_spi = spi_width/diam_ext + ls_dRspi
# LS misalignments
ls_misalign = [0,0,0,0,0,0] if ls_misalign is None else list(ls_misalign)
dx_amp, dy_amp, dz_amp = ls_misalign[0:3]
dx_phase, dy_phase, dz_phase = ls_misalign[3:6]
# create Lyot stop
proper.prop_circular_aperture(wf, ls_ext, dx_amp, dy_amp, NORM=True)
if diam_int > 0:
proper.prop_circular_obscuration(wf, ls_int, dx_amp, dy_amp, NORM=True)
if spi_width > 0:
for angle in spi_angles:
proper.prop_rectangular_obscuration(wf, ls_spi, 2, \
dx_amp, dy_amp, ROTATION=angle, NORM=True)
if verbose is True:
print('Create Lyot stop')
print(' ls_int=%3.4f, ls_ext=%3.4f, ls_spi=%3.4f'\
%(ls_int, ls_ext, ls_spi))
print('')
# case 2: APP
elif mode in ['APP']:
if verbose is True:
print('Load APP from files\n')
# get amplitude and phase data
APP_amp = fits.getdata(file_app_amp) if os.path.isfile(file_app_amp) \
else np.ones((npupil, npupil))
APP_phase = fits.getdata(file_app_phase) if os.path.isfile(file_app_phase) \
else np.zeros((npupil, npupil))
# resize to npupil
APP_amp = impro.resize_img(APP_amp, npupil)
APP_phase = impro.resize_img(APP_phase, npupil)
# pad with zeros to match PROPER ngrid
APP_amp = impro.pad_img(APP_amp, ngrid, 1)
APP_phase = impro.pad_img(APP_phase, ngrid, 0)
# multiply the loaded APP
proper.prop_multiply(wf, APP_amp*np.exp(1j*APP_phase))
# get the LS amplitude and phase for output
LS_amp = impro.crop_img(proper.prop_get_amplitude(wf), npupil, margin)\
if get_amp is True else None
LS_phase = impro.crop_img(proper.prop_get_phase(wf), npupil, margin)\
if get_phase is True else None
return wf, LS_amp, LS_phase
def coronagraph(wfo, f_lens, occulter_type, diam):
proper.prop_lens(wfo, f_lens, "coronagraph imaging lens")
proper.prop_propagate(wfo, f_lens, "occulter")
# occulter sizes are specified here in units of lambda/diameter;
# convert lambda/diam to radians then to meters
lamda = proper.prop_get_wavelength(wfo)
occrad = 4. # occulter radius in lam/D
occrad_rad = occrad * lamda / diam # occulter radius in radians
dx_m = proper.prop_get_sampling(wfo)
dx_rad = proper.prop_get_sampling_radians(wfo)
occrad_m = occrad_rad * dx_m / dx_rad # occulter radius in meters
plt.figure(figsize=(12,8))
if occulter_type == "GAUSSIAN":
r = proper.prop_radius(wfo)
h = np.sqrt(-0.5 * occrad_m**2 / np.log(1 - np.sqrt(0.5)))
gauss_spot = 1 - np.exp(-0.5 * (r/h)**2)
proper.prop_multiply(wfo, gauss_spot)
plt.suptitle("Gaussian spot", fontsize = 18)
elif occulter_type == "SOLID":
proper.prop_circular_obscuration(wfo, occrad_m)
plt.suptitle("Solid spot", fontsize = 18)
elif occulter_type == "8TH_ORDER":
proper.prop_8th_order_mask(wfo, occrad, CIRCULAR = True)
plt.suptitle("8th order band limited spot", fontsize = 18)
# After occulter
plt.subplot(1,2,1)
plt.imshow(np.sqrt(proper.prop_get_amplitude(wfo)), origin = "lower", cmap = plt.cm.gray)
plt.text(200, 10, "After Occulter", color = "w")
proper.prop_propagate(wfo, f_lens, "pupil reimaging lens")
proper.prop_lens(wfo, f_lens, "pupil reimaging lens")
proper.prop_propagate(wfo, 2*f_lens, "lyot stop")
plt.subplot(1,2,2)
plt.imshow(proper.prop_get_amplitude(wfo)**0.2, origin = "lower", cmap = plt.cm.gray)
plt.text(200, 10, "Before Lyot Stop", color = "w")
plt.show()
if occulter_type == "GAUSSIAN":
proper.prop_circular_aperture(wfo, 0.25, NORM = True)
elif occulter_type == "SOLID":
proper.prop_circular_aperture(wfo, 0.84, NORM = True)
elif occulter_type == "8TH_ORDER":
proper.prop_circular_aperture(wfo, 0.50, NORM = True)
proper.prop_propagate(wfo, f_lens, "reimaging lens")
proper.prop_lens(wfo, f_lens, "reimaging lens")
proper.prop_propagate(wfo, f_lens, "final focus")
return
def do_apod(wfo, grid_size, beam_ratio, apod_gaus):
# print 'Including Apodization'
r = proper.prop_radius(wfo)
rad = int(np.round(grid_size * (1 - beam_ratio) /
2)) # beam is a fraction (0.3) of the grid size
r = r / r[grid_size / 2, rad]
w = apod_gaus
gauss_spot = np.exp(-(r / w)**2)
# plt.imshow(gauss_spot)
# plt.figure()
# plt.plot(gauss_spot[128])
# plt.show()
proper.prop_multiply(wfo, gauss_spot)
def fp_mask(wf,
mode='RAVC',
vc_zoffset=0,
add_chrom_leak=None,
verbose=False,
**conf):
# case 1: vortex coronagraphs
if mode in ['CVC', 'RAVC']:
# load chromtic leakage
if conf['add_vort_chrom_leak'] is True:
wf_cl = deepcopy(wf)
proper.prop_multiply(wf_cl, np.sqrt(conf['vc_chrom_leak']))
if verbose is True:
print(' apply vortex phase mask')
# load vortex calibration files: psf_num, vvc, perf_num
conf = vortex_init(verbose=verbose, **conf)
# propagate to vortex
lens(wf, offset_after=vc_zoffset, **conf)
# apply vortex
scale_psf = wf._wfarr[0, 0] / conf['psf_num'][0, 0]
wf_corr = (conf['psf_num'] * conf['vvc'] -
conf['perf_num']) * scale_psf
wf._wfarr = wf._wfarr * conf['vvc'] - wf_corr
# propagate to lyot stop
lens(wf, offset_before=-vc_zoffset, **conf)
# add chromtic leakage
if conf['add_vort_chrom_leak'] is True:
if verbose is True:
print(' Add chromatic leakage in vortex plane')
wf._wfarr += np.transpose(wf_cl._wfarr)
# case 2: classical Lyot
elif mode in ['CLC']:
if verbose is True:
print(' apply classical lyot mask')
# load lyotmask amplitude file
conf = lyotmask_init(verbose=verbose, **conf)
# propagate to lyot mask
lens(wf, **conf)
# apply lyot mask
wf._wfarr.real *= conf['lyotmask']
# propagate to lyot stop
lens(wf, **conf)
return wf
def detector(wf,
phase_screen=None,
amp_screen=None,
tiptilt=None,
misalign=[0, 0, 0, 0, 0, 0],
ngrid=1024,
ndet=365,
onaxis=False,
dir_output='output_files',
savefits=False,
verbose=False,
**conf):
assert (ngrid >=
ndet), 'Error: final image is bigger than initial grid size'
# propagate to detector
lens(wf, **conf)
# add chromatic leakage
if conf['add_det_chrom_leak'] is True and onaxis == True:
if verbose == True:
print(' Add chromatic leakage in detector plane')
wf_cl = pupil(savefits=False, verbose=False, **conf)
wf_cl = add_errors(wf_cl, phase_screen=phase_screen, amp_screen=amp_screen, \
tiptilt=tiptilt, misalign=misalign, **conf)
wf_cl = lyot_stop(wf_cl, verbose=False, **conf)
lens(wf_cl, **conf)
proper.prop_multiply(wf_cl, np.sqrt(conf['vc_chrom_leak']))
wf._wfarr += np.transpose(wf_cl._wfarr)
# get intensity (A^2)
(psf, _) = proper.prop_end(wf, NOABS=False)
# crop to detector size
start = int(ngrid / 2 - ndet / 2) + 1
end = int(ngrid / 2 + ndet / 2) + 1
psf = psf[start:end, start:end]
if verbose is True:
print(" extract PSF on the detector: ndet=%s" % ndet)
# save psf as fits file
if savefits == True:
os.makedirs(dir_output, exist_ok=True)
filename = os.path.join(dir_output, 'PSF_IMG_%s.fits' % conf['band'])
fits.writeto(filename, np.float32(psf), overwrite=True)
return psf
def lyot_stop(wf, mode='RAVC', ravc_r=0.6, ls_dRext=0.03, ls_dRint=0.05,
ls_dRspi=0.04, spi_width=0.5, spi_angles=[0,60,120], diam_ext=37,
diam_int=11, diam_nominal=37, ls_misalign=None, ngrid=1024, npupil=285,
file_lyot_stop='', verbose=False, **conf):
""" Add a Lyot stop for a focal plane mask """
if mode in ['CVC', 'RAVC', 'CLC']:
# load lyot stop from file if provided
if os.path.isfile(file_lyot_stop):
if verbose is True:
print(" apply lyot stop from '%s'"%os.path.basename(file_lyot_stop))
# get amplitude and phase data
ls_mask = fits.getdata(file_lyot_stop)
# resize to npupil
ls_mask = resize_img(ls_mask, npupil)
# pad with zeros and add to wavefront
proper.prop_multiply(wf, pad_img(ls_mask, ngrid))
# if no lyot stop, create one
else:
# scale nominal values to pupil external diameter
scaling = diam_nominal/diam_ext
# LS parameters
r_obstr = ravc_r if mode in ['RAVC'] else diam_int/diam_ext
ls_int = r_obstr + ls_dRint*scaling
ls_ext = 1 - ls_dRext*scaling
ls_spi = spi_width/diam_ext + ls_dRspi*scaling
# LS misalignments
ls_misalign = [0,0,0,0,0,0] if ls_misalign is None else list(ls_misalign)
dx_amp, dy_amp, dz_amp = ls_misalign[0:3]
dx_phase, dy_phase, dz_phase = ls_misalign[3:6]
# create Lyot stop
proper.prop_circular_aperture(wf, ls_ext, dx_amp, dy_amp, NORM=True)
if diam_int > 0:
proper.prop_circular_obscuration(wf, ls_int, dx_amp, dy_amp, NORM=True)
if spi_width > 0:
for angle in spi_angles:
proper.prop_rectangular_obscuration(wf, 2*ls_spi, 2, \
dx_amp, dy_amp, ROTATION=angle, NORM=True)
if verbose is True:
print(' apply Lyot stop: ls_int=%s, ls_ext=%s, ls_spi=%s'\
%(round(ls_int, 4), round(ls_ext, 4), round(ls_spi, 4)))
return wf
def apply_occulter(self, wf):
"""
applies the occulter by type spcified when class object was initiated
:param wf: 2D wavefront
:return:
"""
# Code here pulled directly from Proper Manual pg 86
if self.mode == "Gaussian":
r = proper.prop_radius(wf)
h = np.sqrt(-0.5 * self.size**2 / np.log(1 - np.sqrt(0.5)))
gauss_spot = 1 - np.exp(-0.5 * (r / h)**2)
# gauss_spot = shift(gauss_spot, shift=occult_loc, mode='wrap') # ???
proper.prop_multiply(wf, gauss_spot)
elif self.mode == "Solid":
proper.prop_circular_obscuration(wf, self.size)
elif self.mode == "8th_Order":
proper.prop_8th_order_mask(wf, self.size, CIRCULAR=True)
def island_effect_piston(wf, npupil, Island_Piston, path, Debug_print, Debug):
n = int(proper.prop_get_gridsize(wf))
lamda=proper.prop_get_wavelength(wf) #save the wavelength value [m] into lamda
PACKAGE_PATH = os.path.abspath(os.path.join(__file__, os.pardir))
petal1 = fits.getdata(PACKAGE_PATH+'/1024_pixelsize5mas_petal1_243px.fits')
petal2 = fits.getdata(PACKAGE_PATH+'/1024_pixelsize5mas_petal2_243px.fits')
petal3 = fits.getdata(PACKAGE_PATH+'/1024_pixelsize5mas_petal3_243px.fits')
petal4 = fits.getdata(PACKAGE_PATH+'/1024_pixelsize5mas_petal4_243px.fits')
petal5 = fits.getdata(PACKAGE_PATH+'/1024_pixelsize5mas_petal5_243px.fits')
petal6 = fits.getdata(PACKAGE_PATH+'/1024_pixelsize5mas_petal6_243px.fits')
piston_petal1 = Island_Piston[0]*petal1
piston_petal2 = Island_Piston[1]*petal2
piston_petal3 = Island_Piston[2]*petal3
piston_petal4 = Island_Piston[3]*petal4
piston_petal5 = Island_Piston[4]*petal5
piston_petal6 = Island_Piston[5]*petal6
piston = piston_petal1 + piston_petal2 + piston_petal3 + piston_petal4 + piston_petal5 + piston_petal6
piston_pixels = (piston.shape)[0]## fits file size
scaling_factor = float(npupil)/float(piston_pixels) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print==True):
print ("scaling_factor: ", scaling_factor)
piston_scale = cv2.resize(piston.astype(np.float32), (0,0), fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_LINEAR) # scale the pupil to the pupil size of the simualtions
if (Debug_print==True):
print ("piston_resample", piston_scale.shape)
piston_large = np.zeros((n,n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print==True):
print("n: ", n)
print("npupil: ", npupil)
piston_large[int(n/2)+1-int(npupil/2)-1:int(n/2)+1+int(npupil/2),int(n/2)+1-int(npupil/2)-1:int(n/2)+1+int(npupil/2)] =piston_scale # insert the scaled pupil into the 0s grid
if (Debug == 1):
fits.writeto(path+'piston_phase.fits', piston_large, overwrite=True) # fits file for the screen
lambda2=lamda/(1e-6) # need to use lambda in microns
piston_phase = np.exp(1j*piston_large/lambda2*2*math.pi)
proper.prop_multiply(wf, piston_phase) # multiply the atm screen to teh wavefront
return
def polmap( wavefront, polfile, pupil_diam_pix, condition, MUF=1.0 ):
n = proper.prop_get_gridsize( wavefront )
lambda_m = proper.prop_get_wavelength(wavefront)
if condition <= 2:
(amp, pha) = polab( polfile, lambda_m, pupil_diam_pix, condition )
elif condition == 5:
(amp_m45_x, pha_m45_x) = polab( polfile, lambda_m, pupil_diam_pix, -1 )
(amp_p45_x, pha_p45_x) = polab( polfile, lambda_m, pupil_diam_pix, +1 )
amp = (amp_m45_x + amp_p45_x) / 2
pha = (pha_m45_x + pha_p45_x) / 2
elif condition == 6:
(amp_m45_y, pha_m45_y) = polab( polfile, lambda_m, pupil_diam_pix, -2 )
(amp_p45_y, pha_p45_y) = polab( polfile, lambda_m, pupil_diam_pix, +2 )
amp = (amp_m45_y + amp_p45_y) / 2
pha = (pha_m45_y + pha_p45_y) / 2
elif condition == 10:
(amp_m45_x, pha_m45_x) = polab( polfile, lambda_m, pupil_diam_pix, -1 )
(amp_p45_x, pha_p45_x) = polab( polfile, lambda_m, pupil_diam_pix, +1 )
(amp_m45_y, pha_m45_y) = polab( polfile, lambda_m, pupil_diam_pix, -2 )
(amp_p45_y, pha_p45_y) = polab( polfile, lambda_m, pupil_diam_pix, +2 )
amp = (amp_m45_x + amp_p45_x + amp_m45_y + amp_p45_y) / 4
pha = (pha_m45_x + pha_p45_x + pha_m45_y + pha_p45_y) / 4
else:
raise Exception( 'POLMAP: unmatched condition' )
proper.prop_multiply( wavefront, trim(amp,n) )
proper.prop_add_phase( wavefront, trim(MUF*pha,n) )
amp = 0
phase = 0
amp_p45x = 0
amp_m45x = 0
amp_p45y = 0
amp_m45y = 0
pha_p45x = 0
pha_m45x = 0
pha_p45y = 0
pha_m45y = 0
return
def lyotstop(wf, conf, RAVC):
input_dir = conf['INPUT_DIR']
diam = conf['DIAM']
npupil = conf['NPUPIL']
spiders_angle = conf['SPIDERS_ANGLE']
r_obstr = conf['R_OBSTR']
Debug = conf['DEBUG']
Debug_print = conf['DEBUG_PRINT']
LS_amplitude_apodizer_file = conf['AMP_APODIZER']
LS_misalignment = np.array(conf['LS_MIS_ALIGN'])
if conf['PHASE_APODIZER_FILE'] == 0:
LS_phase_apodizer_file = 0
else:
LS_phase_apodizer_file = fits.getdata(input_dir + '/' +
conf['PHASE_APODIZER_FILE'])
LS = conf['LYOT_STOP']
LS_parameters = np.array(conf['LS_PARA'])
n = proper.prop_get_gridsize(wf)
if (RAVC == True): # define the inner radius of the Lyot Stop
t1_opt = 1. - 1. / 4 * (
r_obstr**2 + r_obstr * (math.sqrt(r_obstr**2 + 8.))
) # define the apodizer transmission [Mawet2013]
R1_opt = (r_obstr / math.sqrt(1. - t1_opt)
) # define teh apodizer radius [Mawet2013]
r_LS = R1_opt + LS_parameters[
1] # when a Ring apodizer is present, the inner LS has to have at least the value of the apodizer radius
else:
r_LS = r_obstr + LS_parameters[
1] # when no apodizer, the LS has to have at least the radius of the pupil central obstruction
if LS == True: # apply the LS
if (Debug_print == True):
print("LS parameters: ", LS_parameters)
proper.prop_circular_aperture(wf,
LS_parameters[0],
LS_misalignment[0],
LS_misalignment[1],
NORM=True)
proper.prop_circular_obscuration(wf,
r_LS,
LS_misalignment[0],
LS_misalignment[1],
NORM=True)
if (LS_parameters[2] != 0):
for iter in range(0, len(spiders_angle)):
if (Debug_print == True):
print("LS_misalignment: ", LS_misalignment)
proper.prop_rectangular_obscuration(
wf,
LS_parameters[2],
2 * diam,
LS_misalignment[0],
LS_misalignment[1],
ROTATION=spiders_angle[iter]) # define the spiders
if (Debug == True):
out_dir = str('./output_files/')
fits.writeto(
out_dir + '_Lyot_stop.fits',
proper.prop_get_amplitude(wf)[int(n / 2) -
int(npupil / 2 + 50):int(n / 2) +
int(npupil / 2 + 50),
int(n / 2) -
int(npupil / 2 + 50):int(n / 2) +
int(npupil / 2 + 50)],
overwrite=True)
if (isinstance(LS_phase_apodizer_file, (list, tuple, np.ndarray)) == True):
xc_pixels = int(LS_misalignment[3] * npupil)
yc_pixels = int(LS_misalignment[4] * npupil)
apodizer_pixels = (LS_phase_apodizer_file.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
apodizer_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
# scaling_factor = float(npupil)/float(pupil_pixels) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(
LS_phase_apodizer_file.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("npupil: ", npupil)
apodizer_large[
int(n / 2) + 1 - int(npupil / 2) - 1 + xc_pixels:int(n / 2) + 1 +
int(npupil / 2) + xc_pixels,
int(n / 2) + 1 - int(npupil / 2) - 1 + yc_pixels:int(n / 2) + 1 +
int(npupil / 2) +
yc_pixels] = apodizer_scale # insert the scaled pupil into the 0s grid
phase_multiply = np.array(np.zeros((n, n)),
dtype=complex) # create a complex array
phase_multiply.imag = apodizer_large # define the imaginary part of the complex array as the atm screen
apodizer = np.exp(phase_multiply)
proper.prop_multiply(wf, apodizer)
if (Debug == True):
fits.writeto('LS_apodizer.fits',
proper.prop_get_phase(wf),
overwrite=True)
if (isinstance(LS_amplitude_apodizer_file,
(list, tuple, np.ndarray)) == True):
print('4th')
xc_pixels = int(LS_misalignment[0] * npupil)
yc_pixels = int(LS_misalignment[1] * npupil)
apodizer_pixels = (
LS_amplitude_apodizer_file.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
pupil_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(
amplitude_apodizer_file.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("grid_size: ", n)
print("npupil: ", npupil)
apodizer_large[
int(n / 2) + 1 - int(npupil / 2) - 1 + xc_pixels:int(n / 2) + 1 +
int(npupil / 2) + xc_pixels,
int(n / 2) + 1 - int(npupil / 2) - 1 + yc_pixels:int(n / 2) + 1 +
int(npupil / 2) +
yc_pixels] = apodizer_scale # insert the scaled pupil into the 0s grid
apodizer = apodizer_large
proper.prop_multiply(wf, apodizer)
if (Debug == True):
fits.writeto('LS_apodizer.fits',
proper.prop_get_amplitude(wf),
overwrite=True)
return wf
def lyotstop(self, wf, RAVC=None, APP=None, get_pupil='no', dnpup=50):
"""Add a Lyot stop, or an APP."""
# load parameters
npupil = 1 #conf['NPUPIL']
pad = int((210 - npupil) / 2)
# get LS misalignments
LS_misalignment = (np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0]) *
npupil).astype(int)
dx_amp, dy_amp, dz_amp = LS_misalignment[0:3]
dx_phase, dy_phase, dz_phase = LS_misalignment[3:6]
# case 1: Lyot stop (no APP)
if APP is not True:
# Lyot stop parameters: R_out, dR_in, spi_width
# outer radius (absolute %), inner radius (relative %), spider width (m)
(R_out, dR_in, spi_width) = [0.98, 0.03, 0]
# Lyot stop inner radius at least as large as obstruction radius
R_in = 0.15
# case of a ring apodizer
if RAVC is True:
# define the apodizer transmission and apodizer radius [Mawet2013]
# apodizer radius at least as large as obstruction radius
T_ravc = 1 - (R_in**2 + R_in * np.sqrt(R_in**2 + 8)) / 4
R_in /= np.sqrt(1 - T_ravc)
# oversize Lyot stop inner radius
R_in += dR_in
# create Lyot stop
proper.prop_circular_aperture(wf, R_out, dx_amp, dy_amp, NORM=True)
if R_in > 0:
proper.prop_circular_obscuration(wf,
R_in,
dx_amp,
dy_amp,
NORM=True)
if spi_width > 0:
for angle in [10]:
proper.prop_rectangular_obscuration(wf,
0.05 * 8,
8 * 1.3,
ROTATION=20)
proper.prop_rectangular_obscuration(wf,
8 * 1.3,
0.05 * 8,
ROTATION=20)
# proper.prop_rectangular_obscuration(wf, spi_width, 2 * 8, \
# dx_amp, dy_amp, ROTATION=angle)
# case 2: APP (no Lyot stop)
else:
# get amplitude and phase files
APP_amp_file = os.path.join(conf['INPUT_DIR'],
conf['APP_AMP_FILE'])
APP_phase_file = os.path.join(conf['INPUT_DIR'],
conf['APP_PHASE_FILE'])
# get amplitude and phase data
APP_amp = getdata(APP_amp_file) if os.path.isfile(APP_amp_file) \
else np.ones((npupil, npupil))
APP_phase = getdata(APP_phase_file) if os.path.isfile(APP_phase_file) \
else np.zeros((npupil, npupil))
# resize to npupil
APP_amp = resize(APP_amp, (npupil, npupil),
preserve_range=True,
mode='reflect')
APP_phase = resize(APP_phase, (npupil, npupil),
preserve_range=True,
mode='reflect')
# pad with zeros to match PROPER gridsize
APP_amp = np.pad(APP_amp, [(pad + 1 + dx_amp, pad - dx_amp), \
(pad + 1 + dy_amp, pad - dy_amp)], mode='constant')
APP_phase = np.pad(APP_phase, [(pad + 1 + dx_phase, pad - dx_phase), \
(pad + 1 + dy_phase, pad - dy_phase)], mode='constant')
# multiply the loaded APP
proper.prop_multiply(wf, APP_amp * np.exp(1j * APP_phase))
# get the pupil amplitude or phase for output
if get_pupil.lower() in 'amplitude':
return wf, proper.prop_get_amplitude(wf)[pad + 1 - dnpup:-pad +
dnpup, pad + 1 -
dnpup:-pad + dnpup]
elif get_pupil.lower() in 'phase':
return wf, proper.prop_get_phase(wf)[pad + 1 - dnpup:-pad + dnpup,
pad + 1 - dnpup:-pad + dnpup]
else:
return wf
def occulter(self, wf):
n = int(proper.prop_get_gridsize(wf))
ofst = 0 # no offset
ramp_sign = 1 # sign of charge is positive
ramp_oversamp = 11. # vortex is oversampled for a better discretization
# f_lens = tp.f_lens #conf['F_LENS']
# diam = tp.diam#conf['DIAM']
charge = 2 #conf['CHARGE']
pixelsize = 5 #conf['PIXEL_SCALE']
Debug_print = False #conf['DEBUG_PRINT']
coron_temp = os.path.join(iop.testdir, 'coron_maps/')
if not os.path.exists(coron_temp):
os.mkdir(coron_temp)
if charge != 0:
wavelength = proper.prop_get_wavelength(wf)
gridsize = proper.prop_get_gridsize(wf)
beam_ratio = pixelsize * 4.85e-9 / (wavelength / tp.entrance_d)
# dprint((wavelength,gridsize,beam_ratio))
calib = str(charge) + str('_') + str(int(
beam_ratio * 100)) + str('_') + str(gridsize)
my_file = str(coron_temp + 'zz_perf_' + calib + '_r.fits')
if (os.path.isfile(my_file) == True):
if (Debug_print == True):
print("Charge ", charge)
vvc = self.readfield(
coron_temp,
'zz_vvc_' + calib) # read the theoretical vortex field
vvc = proper.prop_shift_center(vvc)
scale_psf = wf._wfarr[0, 0]
psf_num = self.readfield(coron_temp, 'zz_psf_' +
calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = self.readfield(
coron_temp,
'zz_perf_' + calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wf._wfarr = (
wf._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
else: # CAL==1: # create the vortex for a perfectly circular pupil
if (Debug_print == True):
dprint(f"Vortex Charge= {charge}")
f_lens = 200.0 * tp.entrance_d
wf1 = proper.prop_begin(tp.entrance_d, wavelength, gridsize,
beam_ratio)
proper.prop_circular_aperture(wf1, tp.entrance_d / 2)
proper.prop_define_entrance(wf1)
proper.prop_propagate(wf1, f_lens,
'inizio') # propagate wavefront
proper.prop_lens(
wf1, f_lens,
'focusing lens vortex') # propagate through a lens
proper.prop_propagate(wf1, f_lens, 'VC') # propagate wavefront
self.writefield(coron_temp, 'zz_psf_' + calib,
wf1.wfarr) # write the pre-vortex field
nramp = int(n * ramp_oversamp) # oversamp
# create the vortex by creating a matrix (theta) representing the ramp (created by atan 2 gradually varying matrix, x and y)
y1 = np.ones((nramp, ), dtype=np.int)
y2 = np.arange(0, nramp,
1.) - (nramp / 2) - int(ramp_oversamp) / 2
y = np.outer(y2, y1)
x = np.transpose(y)
theta = np.arctan2(y, x)
x = 0
y = 0
vvc_tmp = np.exp(1j * (ofst + ramp_sign * charge * theta))
theta = 0
vvc_real_resampled = cv2.resize(
vvc_tmp.real, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc_imag_resampled = cv2.resize(
vvc_tmp.imag, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc = np.array(vvc_real_resampled, dtype=complex)
vvc.imag = vvc_imag_resampled
vvcphase = np.arctan2(vvc.imag,
vvc.real) # create the vortex phase
vvc_complex = np.array(np.zeros((n, n)), dtype=complex)
vvc_complex.imag = vvcphase
vvc = np.exp(vvc_complex)
vvc_tmp = 0.
self.writefield(coron_temp, 'zz_vvc_' + calib,
vvc) # write the theoretical vortex field
proper.prop_multiply(wf1, vvc)
proper.prop_propagate(wf1, f_lens, 'OAP2')
proper.prop_lens(wf1, f_lens)
proper.prop_propagate(wf1, f_lens, 'forward to Lyot Stop')
proper.prop_circular_obscuration(
wf1, 1.,
NORM=True) # null the amplitude iside the Lyot Stop
proper.prop_propagate(wf1, -f_lens) # back-propagation
proper.prop_lens(wf1, -f_lens)
proper.prop_propagate(wf1, -f_lens)
self.writefield(
coron_temp, 'zz_perf_' + calib,
wf1.wfarr) # write the perfect-result vortex field
vvc = self.readfield(coron_temp, 'zz_vvc_' + calib)
vvc = proper.prop_shift_center(vvc)
scale_psf = wf._wfarr[0, 0]
psf_num = self.readfield(coron_temp, 'zz_psf_' +
calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = self.readfield(
coron_temp,
'zz_perf_' + calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wf._wfarr = (
wf._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
return wf
def pupil(diam,
gridsize,
spiders_width,
spiders_angle,
pixelsize,
r_obstr,
wavelength,
pupil_file,
missing_segments_number=0,
Debug='False',
Debug_print='False',
prefix='test'):
beam_ratio = pixelsize * 4.85e-9 / (wavelength / diam)
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
n = int(gridsize)
npupil = np.ceil(
gridsize * beam_ratio
) # compute the pupil size --> has to be ODD (proper puts the center in the up right pixel next to the grid center)
if npupil % 2 == 0:
npupil = npupil + 1
if (Debug_print == True):
print("npupil: ", npupil)
print("lambda: ", wavelength)
if (missing_segments_number == 0):
if (isinstance(pupil_file, (list, tuple, np.ndarray)) == True):
pupil = pupil_file
pupil_pixels = (pupil.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
pupil_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
pupil_scale = cv2.resize(
pupil.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("pupil_resample", pupil_scale.shape)
pupil_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
pupil_large[
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil / 2),
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil / 2
)] = pupil_scale # insert the scaled pupil into the 0s grid
proper.prop_circular_aperture(
wfo, diam / 2) # create a wavefront with a circular pupil
if (isinstance(pupil_file, (list, tuple, np.ndarray)) == True):
proper.prop_multiply(wfo, pupil_large) # multiply the saved pupil
else:
proper.prop_circular_obscuration(
wfo, r_obstr, NORM=True
) # create a wavefront with a circular central obscuration
if (spiders_width != 0):
for iter in range(0, len(spiders_angle)):
proper.prop_rectangular_obscuration(
wfo, spiders_width, 2 * diam,
ROTATION=spiders_angle[iter]) # define the spiders
else:
if (missing_segments_number == 1):
pupil = fits.getdata(
input_dir +
'/ELT_2048_37m_11m_5mas_nospiders_1missing_cut.fits')
if (missing_segments_number == 2):
pupil = fits.getdata(
input_dir +
'/ELT_2048_37m_11m_5mas_nospiders_2missing_cut.fits')
if (missing_segments_number == 4):
pupil = fits.getdata(
input_dir +
'/ELT_2048_37m_11m_5mas_nospiders_4missing_cut.fits')
if (missing_segments_number == 7):
pupil = fits.getdata(
input_dir +
'/ELT_2048_37m_11m_5mas_nospiders_7missing_1_cut.fits')
pupil_pixels = (pupil.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
pupil_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
pupil_scale = cv2.resize(
pupil.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("pupil_resample", pupil_scale.shape)
pupil_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
pupil_large[
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil / 2),
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil /
2)] = pupil_scale # insert the scaled pupil into the 0s grid
proper.prop_multiply(wfo, pupil_large) # multiply the saved pupil
if (spiders_width != 0):
for iter in range(0, len(spiders_angle)):
proper.prop_rectangular_obscuration(
wfo, spiders_width, 2 * diam,
ROTATION=spiders_angle[iter]) # define the spiders
if (Debug == True):
fits.writeto(
out_dir + prefix + '_intial_pupil.fits',
proper.prop_get_amplitude(wfo)[int(n / 2) -
int(npupil / 2 + 50):int(n / 2) +
int(npupil / 2 + 50),
int(n / 2) -
int(npupil / 2 + 50):int(n / 2) +
int(npupil / 2 + 50)],
overwrite=True)
proper.prop_define_entrance(wfo) #define the entrance wavefront
wfo.wfarr *= 1. / np.amax(wfo._wfarr) # max(amplitude)=1
return (npupil, wfo)
def apodizer(wf,
mode='RAVC',
ravc_t=0.8,
ravc_r=0.6,
ravc_misalign=None,
ngrid=1024,
npupil=285,
file_ravc_amp='',
file_ravc_phase='',
margin=50,
get_amp=False,
get_phase=False,
verbose=False,
**conf):
''' Create a wavefront object at the entrance pupil plane.
The pupil is either loaded from a fits file, or created using
pupil parameters.
Can also select only one petal and mask the others.
wf: WaveFront
PROPER wavefront object
mode: str
HCI mode
ravc_t: float
RA transmittance
ravc_r: float
RA radius
ravc_misalign: list of float
RA misalignment
ngrid: int
number of pixels of the wavefront array
npupil: int
number of pixels of the pupil
file_ravc_amp: str
file_ravc_phase: str
ring apodizer files (optional)
'''
if mode in ['RAVC']:
# load apodizer from files if provided
if os.path.isfile(file_ravc_amp) and os.path.isfile(file_ravc_phase):
if verbose is True:
print('Load ring apodizer from files\n')
# get amplitude and phase data
RAVC_amp = fits.getdata(file_ravc_amp)
RAVC_phase = fits.getdata(file_ravc_phase)
# resize to npupil
RAVC_amp = impro.resize_img(RAVC_amp, npupil)
RAVC_phase = impro.resize_img(RAVC_phase, npupil)
# pad with zeros to match PROPER gridsize
RAVC_amp = impro.pad_img(RAVC_amp, ngrid)
RAVC_phase = impro.pad_img(RAVC_phase, ngrid)
# build complex apodizer
apo = RAVC_amp * np.exp(1j * RAVC_phase)
# or else, define the apodizer as a ring (with % misalignments)
else:
# RAVC misalignments
ravc_misalign = [
0, 0, 0, 0, 0, 0
] if ravc_misalign is None else list(ravc_misalign)
dx_amp, dy_amp, dz_amp = ravc_misalign[0:3]
dx_phase, dy_phase, dz_phase = ravc_misalign[3:6]
# create apodizer
apo = circular_apodization(wf, ravc_r, 1., ravc_t, xc=dx_amp, \
yc=dy_amp, NORM=True)
apo = proper.prop_shift_center(apo)
if verbose is True:
print('Create ring apodizer')
print(' ravc_t=%3.4f, ravc_r=%3.4f'\
%(ravc_t, ravc_r))
print(' ravc_misalign=%s' % ravc_misalign)
print('')
# multiply the loaded apodizer
proper.prop_multiply(wf, apo)
# get the apodizer amplitude and phase for output
apo_amp = impro.crop_img(proper.prop_get_amplitude(wf), npupil,\
margin) if get_amp is True else None
apo_phase = impro.crop_img(proper.prop_get_phase(wf), npupil,\
margin) if get_phase is True else None
return wf, apo_amp, apo_phase
else: # no ring apodizer
return wf, None, None
def pupil(wfo, CAL, npupil, diam, r_obstr, spiders_width, spiders_angle,
pupil_file, missing_segments_number, Debug, Debug_print):
n = int(proper.prop_get_gridsize(wfo))
if (missing_segments_number == 0):
if (isinstance(pupil_file, (list, tuple, np.ndarray)) == True):
pupil = pupil_file
pupil_pixels = (pupil.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
pupil_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
pupil_scale = cv2.resize(
pupil.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("pupil_resample", pupil_scale.shape)
pupil_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
pupil_large[
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil / 2),
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil / 2
)] = pupil_scale # insert the scaled pupil into the 0s grid
proper.prop_circular_aperture(
wfo, diam / 2) # create a wavefront with a circular pupil
if CAL == 0: # CAL=1 is for the back-propagation
if (isinstance(pupil_file, (list, tuple, np.ndarray)) == True):
proper.prop_multiply(wfo,
pupil_large) # multiply the saved pupil
else:
proper.prop_circular_obscuration(
wfo, r_obstr, NORM=True
) # create a wavefront with a circular central obscuration
if (spiders_width != 0):
for iter in range(0, len(spiders_angle)):
proper.prop_rectangular_obscuration(
wfo,
spiders_width,
2 * diam,
ROTATION=spiders_angle[iter]) # define the spiders
else:
PACKAGE_PATH = os.path.abspath(os.path.join(__file__, os.pardir))
if (missing_segments_number == 1):
pupil = fits.getdata(
PACKAGE_PATH +
'/ELT_2048_37m_11m_5mas_nospiders_1missing_cut.fits')
if (missing_segments_number == 2):
pupil = fits.getdata(
PACKAGE_PATH +
'/ELT_2048_37m_11m_5mas_nospiders_2missing_cut.fits')
if (missing_segments_number == 4):
pupil = fits.getdata(
PACKAGE_PATH +
'/ELT_2048_37m_11m_5mas_nospiders_4missing_cut.fits')
if (missing_segments_number == 7):
pupil = fits.getdata(
PACKAGE_PATH +
'/ELT_2048_37m_11m_5mas_nospiders_7missing_1_cut.fits')
pupil_pixels = (pupil.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
pupil_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
pupil_scale = cv2.resize(
pupil.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("pupil_resample", pupil_scale.shape)
pupil_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
pupil_large[
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil / 2),
int(n / 2) + 1 - int(npupil / 2) - 1:int(n / 2) + 1 +
int(npupil /
2)] = pupil_scale # insert the scaled pupil into the 0s grid
if CAL == 0: # CAL=1 is for the back-propagation
proper.prop_multiply(wfo, pupil_large) # multiply the saved pupil
if (spiders_width != 0):
for iter in range(0, len(spiders_angle)):
proper.prop_rectangular_obscuration(
wfo,
spiders_width,
2 * diam,
ROTATION=spiders_angle[iter]) # define the spiders
return
def propagate_cube(wf,
phase_screens,
amp_screens,
tiptilts,
apo_misaligns,
ls_misaligns,
nframes=10,
nstep=1,
mode='RAVC',
ngrid=1024,
cpu_count=1,
vc_chrom_leak=2e-3,
add_cl_det=False,
add_cl_vort=False,
tag=None,
onaxis=True,
send_to=None,
savefits=False,
verbose=False,
**conf):
# update conf
conf.update(mode=mode,
ngrid=ngrid,
cpu_count=cpu_count,
vc_chrom_leak=vc_chrom_leak,
add_cl_det=add_cl_det,
add_cl_vort=add_cl_vort,
tag=tag,
onaxis=onaxis)
# keep a copy of the input wavefront
wf1 = deepcopy(wf)
if verbose == True:
print('Create %s-axis PSF cube' % {True: 'on', False: 'off'}[onaxis])
if add_cl_det is True:
print(' adding chromatic leakage at detector plane: %s' %
vc_chrom_leak)
if add_cl_vort is True:
print(' adding chromatic leakage at vortex plane: %s' %
vc_chrom_leak)
# preload amp screen if only one frame
if len(amp_screens) == 1 and np.any(amp_screens) != None:
proper.prop_multiply(wf1, pad_img(amp_screens, ngrid))
# then create a cube of None values
amp_screens = [None] * int(nframes / nstep + 0.5)
if verbose == True:
print(' preloading amplitude screen')
# preload apodizer when no drift
if ('APP' in mode) or ('RAVC' in mode and np.all(apo_misaligns) == None):
wf1 = apodizer(wf1, verbose=False, **conf)
conf['apo_loaded'] = True
if verbose == True:
print(' preloading %s apodizer' % mode)
else:
conf['apo_loaded'] = False
# preload Lyot stop when no drift
if ('VC' in mode or 'LC' in mode) and np.all(ls_misaligns) == None:
conf['ls_mask'] = lyot_stop(wf1, apply_ls=False, verbose=False, **conf)
if verbose == True:
print(' preloading Lyot stop')
# run simulation
posvars = [
phase_screens, amp_screens, tiptilts, apo_misaligns, ls_misaligns
]
kwargs = dict(verbose=False, **conf)
psfs = multiCPU(propagate_one,
posargs=[wf1],
posvars=posvars,
kwargs=kwargs,
case='e2e simulation',
cpu_count=cpu_count)
# if only one wavefront, make dim = 2
if len(psfs) == 1:
psfs = psfs[0]
# save cube of PSFs to fits file, and notify by email
if savefits == True:
tag = '' if tag is None else '%s_' % tag
name = '%s%s_PSF' % (tag, {True: 'onaxis', False: 'offaxis'}[onaxis])
filename = save2fits(psfs, name, **conf)
notify('saved to %s' % filename, send_to)
return psfs
def pupil(file_pupil='',
lam=3.8e-6,
ngrid=1024,
npupil=285,
pupil_img_size=40,
diam_ext=37,
diam_int=11,
spi_width=0.5,
spi_angles=[0, 60, 120],
npetals=6,
seg_width=0,
seg_gap=0,
seg_rms=0,
seg_ny=[
10, 13, 16, 19, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 30, 31,
30, 31, 30, 31, 30, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 19,
16, 13, 10
],
seg_missing=[],
select_petal=None,
savefits=False,
verbose=False,
**conf):
''' Create a wavefront object at the entrance pupil plane.
The pupil is either loaded from a fits file, or created using
pupil parameters.
Can also select only one petal and mask the others.
Args:
dir_output (str):
path to saved pupil file
band (str):
spectral band (e.g. 'L', 'M', 'N1', 'N2')
mode (str):
HCI mode: RAVC, CVC, APP, CLC
file_pupil: str
path to a pupil fits file
lam: float
wavelength in m
ngrid: int
number of pixels of the wavefront array
npupil: int
number of pixels of the pupil
pupil_img_size: float
pupil image (for PROPER) in m
diam_ext: float
outer circular aperture in m
diam_int: float
central obscuration in m
spi_width: float
spider width in m
spi_angles: list of float
spider angles in deg
seg_width: float
segment width in m
seg_gap: float
gap between segments in m
seg_rms: float
rms of the reflectivity of all segments
seg_ny: list of int
number of hexagonal segments per column (from left to right)
seg_missing: list of tupples
coordinates of missing segments
npetals: int
number of petals
select_petal: int
selected petal in range npetals, default to None
'''
# initialize wavefront using PROPER
beam_ratio = npupil / ngrid * (diam_ext / pupil_img_size)
wf = proper.prop_begin(pupil_img_size, lam, ngrid, beam_ratio)
# load pupil file
if os.path.isfile(file_pupil):
if verbose is True:
print("Load pupil from '%s'" % os.path.basename(file_pupil))
#conf.update()
pup = fits.getdata(file_pupil).astype(np.float32)
# resize to npupil
pup = resize_img(pup, npupil)
# if no pupil file, create a pupil
else:
if verbose is True:
print("Create pupil: spi_width=%s m, seg_width=%s m, seg_gap=%s m, seg_rms=%s"\
%(spi_width, seg_width, seg_gap, seg_rms))
conf.update(npupil=npupil,
pupil_img_size=pupil_img_size,
diam_ext=diam_ext,
diam_int=diam_int,
spi_width=spi_width,
spi_angles=spi_angles,
seg_width=seg_width,
seg_gap=seg_gap,
seg_ny=seg_ny,
seg_missing=seg_missing,
seg_rms=seg_rms)
pup = create_pupil(**conf)
# normalize the entrance pupil intensity (total flux = 1)
I_pup = pup**2
pup = np.sqrt(I_pup / np.sum(I_pup))
# pad with zeros and add to wavefront
proper.prop_multiply(wf, pad_img(pup, ngrid))
# select one petal (optional)
if select_petal in range(npetals) and npetals > 1:
if verbose is True:
print(" select_petal=%s" % select_petal)
# petal start and end angles
pet_angle = 2 * np.pi / npetals
pet_start = pet_angle / 2 + (select_petal - 1) * pet_angle
pet_end = pet_start + pet_angle
# petal angles must be 0-2pi
ti %= (2 * np.pi)
pet_start %= (2 * np.pi)
pet_end %= (2 * np.pi)
# check if petal crosses 0 angle
if pet_end - pet_start < 0:
pet_start = (pet_start + np.pi) % (2 * np.pi) - np.pi
pet_end = (pet_end + np.pi) % (2 * np.pi) - np.pi
ti = (ti + np.pi) % (2 * np.pi) - np.pi
# create petal and add to grid
petal = ((ti >= pet_start) * (ti <= pet_end)).astype(int)
petal = resize_img(petal, ngrid)
proper.prop_multiply(wf, petal)
# save pupil as fits file
if savefits == True:
save2fits(pup, 'pupil', **conf)
if verbose is True:
print(' diam=%s m, resize to %s pix, zero-pad to %s pix\n'\
%(round(diam_ext, 2), npupil, ngrid))
return wf
def apodization(wf, r_obstr, npupil, RAVC, phase_apodizer_file,
amplitude_apodizer_file, apodizer_misalignment, Debug_print,
Debug):
n = int(proper.prop_get_gridsize(wf))
if (RAVC == True):
t1_opt = 1. - 1. / 4 * (
r_obstr**2 + r_obstr * (math.sqrt(r_obstr**2 + 8.))
) # define the apodizer transmission [Mawet2013]
R1_opt = (r_obstr / math.sqrt(1. - t1_opt)
) # define the apodizer radius [Mawet2013]
if (Debug_print == True):
print("r1_opt: ", R1_opt)
print("t1_opt: ", t1_opt)
apodizer = circular_apodization(wf,
R1_opt,
1.,
t1_opt,
xc=apodizer_misalignment[0],
yc=apodizer_misalignment[1],
NORM=True) # define the apodizer
apodizer = proper.prop_shift_center(apodizer)
if (isinstance(phase_apodizer_file, (list, tuple, np.ndarray)) == True):
xc_pixels = int(apodizer_misalignment[3] * npupil)
yc_pixels = int(apodizer_misalignment[4] * npupil)
apodizer_pixels = (phase_apodizer_file.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
apodizer_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(
phase_apodizer_file.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
apodizer_large[
int(n / 2) + 1 - int(npupil / 2) - 1 + xc_pixels:int(n / 2) + 1 +
int(npupil / 2) + xc_pixels,
int(n / 2) + 1 - int(npupil / 2) - 1 + yc_pixels:int(n / 2) + 1 +
int(npupil / 2) +
yc_pixels] = apodizer_scale # insert the scaled pupil into the 0s grid
apodizer = np.exp(1j * apodizer_large)
if (isinstance(amplitude_apodizer_file,
(list, tuple, np.ndarray)) == True):
xc_pixels = int(apodizer_misalignment[0] * npupil)
yc_pixels = int(apodizer_misalignment[1] * npupil)
apodizer_pixels = (amplitude_apodizer_file.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
apodizer_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(
amplitude_apodizer_file.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
apodizer_large[
int(n / 2) + 1 - int(npupil / 2) - 1 + xc_pixels:int(n / 2) + 1 +
int(npupil / 2) + xc_pixels,
int(n / 2) + 1 - int(npupil / 2) - 1 + yc_pixels:int(n / 2) + 1 +
int(npupil / 2) +
yc_pixels] = apodizer_scale # insert the scaled pupil into the 0s grid
apodizer = apodizer_large
proper.prop_multiply(wf, apodizer)
return
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 lyotstop(wf, diam, r_obstr, npupil, RAVC, LS, LS_parameters, spiders_angle, LS_phase_apodizer_file, LS_amplitude_apodizer_file, LS_misalignment, path, Debug_print, Debug):
if (RAVC==True): # define the inner radius of the Lyot Stop
t1_opt = 1. - 1./4*(r_obstr**2 + r_obstr*(math.sqrt(r_obstr**2 + 8.))) # define the apodizer transmission [Mawet2013]
R1_opt = (r_obstr/math.sqrt(1. - t1_opt)) # define teh apodizer radius [Mawet2013]
r_LS = R1_opt + LS_parameters[1] # when a Ring apodizer is present, the inner LS has to have at least the value of the apodizer radius
else:
r_LS = r_obstr + LS_parameters[1] # when no apodizer, the LS has to have at least the radius of the pupil central obstruction
if LS==True: # apply the LS
if (Debug_print==True):
print("LS parameters: ", LS_parameters)
proper.prop_circular_aperture(wf, LS_parameters[0], LS_misalignment[0], LS_misalignment[1], NORM=True)
proper.prop_circular_obscuration(wf, r_LS, LS_misalignment[0], LS_misalignment[1], NORM=True)
if (LS_parameters[2]!=0):
for iter in range(0,len(spiders_angle)):
if (Debug_print==True):
print("LS_misalignment: ", LS_misalignment)
proper.prop_rectangular_obscuration(wf, LS_parameters[2], 2*diam,LS_misalignment[0], LS_misalignment[1], ROTATION=spiders_angle[iter]) # define the spiders
if (isinstance(LS_phase_apodizer_file, (list, tuple, np.ndarray)) == True):
xc_pixels = int(LS_misalignment[3]*npupil)
yc_pixels = int(LS_misalignment[4]*npupil)
apodizer_pixels = (LS_phase_apodizer_file.shape)[0]## fits file size
scaling_factor = float(npupil)/float(pupil_pixels) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print==True):
print ("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(phase_apodizer_file.astype(np.float32), (0,0), fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_LINEAR) # scale the pupil to the pupil size of the simualtions
if (Debug_print==True):
print ("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros((n,n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print==True):
print("n: ", n)
print("npupil: ", npupil)
apodizer_large[int(n/2)+1-int(npupil/2)-1 + xc_pixels:int(n/2)+1+int(npupil/2)+ xc_pixels,int(n/2)+1-int(npupil/2)-1+ yc_pixels:int(n/2)+1+int(npupil/2)+ yc_pixels] =apodizer_scale # insert the scaled pupil into the 0s grid
phase_multiply = np.array(np.zeros((n,n)), dtype=complex) # create a complex array
phase_multiply.imag = apodizer_large # define the imaginary part of the complex array as the atm screen
apodizer = np.exp(phase_multiply)
proper.prop_multiply(wf, apodizer)
if (Debug == True):
fits.writeto(path + 'LS_apodizer.fits', proper.prop_get_phase(wf), overwrite=True)
if (isinstance(LS_amplitude_apodizer_file, (list, tuple, np.ndarray)) == True):
xc_pixels = int(LS_misalignment[0]*npupil)
yc_pixels = int(LS_misalignment[1]*npupil)
apodizer_pixels = (LS_amplitude_apodizer_file.shape)[0]## fits file size
scaling_factor = float(npupil)/float(pupil_pixels) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print==True):
print ("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(amplitude_apodizer_file.astype(np.float32), (0,0), fx=scaling_factor, fy=scaling_factor, interpolation=cv2.INTER_LINEAR) # scale the pupil to the pupil size of the simualtions
if (Debug_print==True):
print ("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros((n,n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print==True):
print("n: ", n)
print("npupil: ", npupil)
apodizer_large[int(n/2)+1-int(npupil/2)-1 + xc_pixels:int(n/2)+1+int(npupil/2)+ xc_pixels,int(n/2)+1-int(npupil/2)-1+ yc_pixels:int(n/2)+1+int(npupil/2)+ yc_pixels] =apodizer_scale # insert the scaled pupil into the 0s grid
apodizer = apodizer_large
proper.prop_multiply(wf, apodizer)
if (Debug == True):
fits.writeto(path + 'LS_apodizer.fits', proper.prop_get_amplitude(wf), overwrite=True)
return
def propagate_cube(wf,
phase_screens,
amp_screens,
tiptilts,
misaligns,
cpu_count=1,
vc_chrom_leak=2e-3,
add_cl_det=False,
add_cl_vort=False,
tag=None,
onaxis=True,
send_to=None,
savefits=False,
verbose=False,
**conf):
# update conf
conf.update(cpu_count=cpu_count, vc_chrom_leak=vc_chrom_leak, \
add_cl_det=add_cl_det, add_cl_vort=add_cl_vort, tag=tag, onaxis=onaxis)
# preload amp screen if only one frame
if len(amp_screens) == 1 and np.any(amp_screens) != None:
import proper
from heeps.util.img_processing import pad_img, resize_img
amp_screens = np.nan_to_num(amp_screens[0])
amp_screens = pad_img(resize_img(amp_screens, conf['npupil']),
conf['ngrid'])
proper.prop_multiply(wf, amp_screens)
# then create a cube of None values
amp_screens = [None] * int((conf['nframes'] / conf['nstep']) + 0.5)
# preload apodizer when no drift
if np.all(misaligns) == None or 'APP' in conf['mode']:
wf = apodizer(wf, verbose=False, **conf)
if verbose == True:
print('Create %s-axis PSF cube' % {True: 'on', False: 'off'}[onaxis])
if add_cl_det is True:
print(' adding chromatic leakage at detector plane: %s' %
vc_chrom_leak)
if add_cl_vort is True:
print(' adding chromatic leakage at vortex plane: %s' %
vc_chrom_leak)
# run simulation
posvars = [phase_screens, amp_screens, tiptilts, misaligns]
kwargs = dict(verbose=False, **conf)
psfs = multiCPU(propagate_one, posargs=[wf], posvars=posvars, kwargs=kwargs, \
case='e2e simulation', cpu_count=cpu_count)
# if only one wavefront, make dim = 2
if len(psfs) == 1:
psfs = psfs[0]
# save cube of PSFs to fits file, and notify by email
if savefits == True:
tag = '' if tag is None else '%s_' % tag
name = '%s%s_PSF' % (tag, {True: 'onaxis', False: 'offaxis'}[onaxis])
filename = save2fits(psfs, name, **conf)
notify('saved to %s' % filename, send_to)
return psfs
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 pupil(pup=None,
f_pupil='',
lam=3.8e-6,
ngrid=1024,
npupil=285,
pupil_img_size=40,
diam_ext=37,
diam_int=11,
spi_width=0.5,
spi_angles=[0, 60, 120],
npetals=6,
seg_width=0,
seg_gap=0,
seg_rms=0,
seg_ny=[
10, 13, 16, 19, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 30, 31,
30, 31, 30, 31, 30, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 19,
16, 13, 10
],
seg_missing=[],
select_petal=None,
norm_I=True,
savefits=False,
verbose=False,
**conf):
''' Create a wavefront object at the entrance pupil plane.
The pupil is either loaded from a fits file, or created using
pupil parameters.
Can also select only one petal and mask the others.
Args:
dir_output (str):
path to saved pupil file
band (str):
spectral band (e.g. 'L', 'M', 'N1', 'N2')
mode (str):
HCI mode: RAVC, CVC, APP, CLC
f_pupil: str
path to a pupil fits file
lam: float
wavelength in m
ngrid: int
number of pixels of the wavefront array
npupil: int
number of pixels of the pupil
pupil_img_size: float
pupil image (for PROPER) in m
diam_ext: float
outer circular aperture in m
diam_int: float
central obscuration in m
spi_width: float
spider width in m
spi_angles: list of float
spider angles in deg
seg_width: float
segment width in m
seg_gap: float
gap between segments in m
seg_rms: float
rms of the reflectivity of all segments
seg_ny: list of int
number of hexagonal segments per column (from left to right)
seg_missing: list of tupples
coordinates of missing segments
npetals: int
number of petals
select_petal: int
selected petal in range npetals, default to None
'''
# initialize wavefront using PROPER
beam_ratio = npupil / ngrid * (diam_ext / pupil_img_size)
wf = proper.prop_begin(diam_ext, lam, ngrid, beam_ratio)
# case 1: load pupil from data
if pup is not None:
if verbose is True:
print("Load pupil data from 'pup'")
pup = resize_img(pup, npupil)
# case 2: load pupil from file
elif os.path.isfile(f_pupil):
if verbose is True:
print("Load pupil from '%s'" % os.path.basename(f_pupil))
pup = resize_img(fits.getdata(f_pupil), npupil)
# case 3: create a pupil
else:
if verbose is True:
print("Create pupil: spi_width=%s m, seg_width=%s m, seg_gap=%s m, seg_rms=%s"\
%(spi_width, seg_width, seg_gap, seg_rms))
conf.update(npupil=npupil,
pupil_img_size=pupil_img_size,
diam_ext=diam_ext,
diam_int=diam_int,
spi_width=spi_width,
spi_angles=spi_angles,
seg_width=seg_width,
seg_gap=seg_gap,
seg_ny=seg_ny,
seg_missing=seg_missing,
seg_rms=seg_rms)
pup = create_pupil(**conf)
# select one petal (optional)
if select_petal in range(npetals) and npetals > 1:
if verbose is True:
print(" select_petal=%s" % select_petal)
petal = create_petal(select_petal, npetals, npupil)
pup *= petal
# normalize the entrance pupil intensity (total flux = 1)
if norm_I is True:
I_pup = pup**2
pup = np.sqrt(I_pup / np.sum(I_pup))
# save pupil as fits file
if savefits == True:
save2fits(pup, 'pupil', **conf)
# pad with zeros and add to wavefront
proper.prop_multiply(wf, pad_img(pup, ngrid))
return wf
def apodizer(wf,
mode='RAVC',
ravc_t=0.8,
ravc_r=0.6,
ngrid=1024,
npupil=285,
f_app_amp='',
f_app_phase='',
f_ravc_amp='',
f_ravc_phase='',
apo_misalign=None,
onaxis=True,
verbose=False,
**conf):
''' Create a wavefront object at the entrance pupil plane.
The pupil is either loaded from a fits file, or created using
pupil parameters.
Can also select only one petal and mask the others.
wf: WaveFront
PROPER wavefront object
mode: str
HCI mode
ravc_t: float
RA transmittance
ravc_r: float
RA radius
ngrid: int
number of pixels of the wavefront array
npupil: int
number of pixels of the pupil
f_app_amp: str
f_app_phase: str
apodizing phase plate files
f_ravc_amp: str
f_ravc_phase: str
ring apodizer files (optional)
apo_misalign: list of float
apodizer misalignment
'''
# case 1: Ring Apodizer
if 'RAVC' in mode and ravc_r > 0:
# load apodizer from files if provided
if os.path.isfile(f_ravc_amp) and os.path.isfile(f_ravc_phase):
if verbose is True:
print(' apply ring apodizer from files')
# get amplitude and phase data
RAVC_amp = fits.getdata(f_ravc_amp)
RAVC_phase = fits.getdata(f_ravc_phase)
# resize to npupil
RAVC_amp = impro.resize_img(RAVC_amp, npupil)
RAVC_phase = impro.resize_img(RAVC_phase, npupil)
# pad with zeros to match PROPER gridsize
RAVC_amp = impro.pad_img(RAVC_amp, ngrid)
RAVC_phase = impro.pad_img(RAVC_phase, ngrid)
# build complex apodizer
ring = RAVC_amp * np.exp(1j * RAVC_phase)
# else, define the apodizer as a ring (with % misalignments)
else:
# RAVC misalignments
dx, dy = [0, 0
] if apo_misalign is None else list(apo_misalign)[0:2]
# create apodizer
ring = circular_apodization(wf,
ravc_r,
1,
ravc_t,
xc=dx,
yc=dy,
NORM=True)
if verbose is True:
print(' apply ring apodizer: ravc_t=%s, ravc_r=%s' %
(round(ravc_t, 4), round(ravc_r, 4)))
# multiply the loaded apodizer
proper.prop_multiply(wf, ring)
# case 2: Apodizing Phase Plate
elif 'APP' in mode:
# get amplitude and phase data
if os.path.isfile(f_app_amp):
if verbose is True:
print(' apply APP stop (amplitude)')
APP_amp = fits.getdata(f_app_amp)
else:
APP_amp = np.ones((npupil, npupil))
if os.path.isfile(f_app_phase) and onaxis == True:
if verbose is True:
print(' apply APP phase')
APP_phase = fits.getdata(f_app_phase)
else:
APP_phase = np.zeros((npupil, npupil))
# resize to npupil
APP_amp = impro.resize_img(APP_amp, npupil)
APP_phase = impro.resize_img(APP_phase, npupil)
# rotate for negative PSF
if 'neg' in mode:
APP_amp = np.rot90(APP_amp, 2)
APP_phase = np.rot90(APP_phase, 2)
# pad with zeros to match PROPER ngrid
APP_amp = impro.pad_img(APP_amp, ngrid, 0)
APP_phase = impro.pad_img(APP_phase, ngrid, 0)
# multiply the loaded APP
proper.prop_multiply(wf, APP_amp * np.exp(1j * APP_phase))
return wf
def propagate_cube(wf,
phase_screens,
amp_screens,
tiptilts,
misaligns,
cpu_count=1,
send_to=None,
tag=None,
onaxis=True,
savefits=False,
verbose=False,
**conf):
# preload amp screen if only one frame
if len(amp_screens) == 1 and np.any(amp_screens) != None:
import proper
from heeps.util.img_processing import pad_img, resize_img
amp_screens = np.nan_to_num(amp_screens[0])
amp_screens = pad_img(resize_img(amp_screens, conf['npupil']),
conf['ngrid'])
proper.prop_multiply(wf, amp_screens)
# then create a cube of None values
amp_screens = [None] * int((conf['nframes'] / conf['nstep']) + 0.5)
# preload apodizer when no drift
if np.all(misaligns) == None or 'APP' in conf['mode']:
wf = apodizer(wf, verbose=False, **conf)
if verbose == True:
print('Create %s-axis PSF cube' % {True: 'on', False: 'off'}[onaxis])
# run simulation
t0 = time.time()
if cpu_count != 1 and platform in ['linux', 'linux2', 'darwin']:
if cpu_count == None:
cpu_count = mpro.cpu_count() - 1
if verbose is True:
print(' %s: e2e simulation starts, using %s cores'\
%(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), cpu_count))
p = mpro.Pool(cpu_count)
func = partial(propagate_one, wf, onaxis=onaxis, verbose=False, **conf)
psfs = np.array(
p.starmap(func, zip(phase_screens, amp_screens, tiptilts,
misaligns)))
p.close()
p.join()
else:
if verbose is True:
print(' %s: e2e simulation starts, using 1 core'\
%(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())))
for i, (phase_screen, amp_screen, tiptilt, misalign) \
in enumerate(zip(phase_screens, amp_screens, tiptilts, misaligns)):
psf = propagate_one(wf, phase_screen, amp_screen, tiptilt, misalign, \
onaxis=onaxis, verbose=True, **conf)
psfs = psf if i == 0 else np.dstack((psfs.T, psf.T)).T
if verbose is True:
print(' %s: finished, elapsed %.3f seconds'\
%(time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), time.time() - t0))
# if only one wavefront, make dim = 2
if len(psfs) == 1:
psfs = psfs[0]
# save cube of PSFs to fits file, and notify by email
if savefits == True:
tag = '' if tag is None else '%s_' % tag
name = '%s%s_PSF' % (tag, {True: 'onaxis', False: 'offaxis'}[onaxis])
filename = save2fits(psfs, name, **conf)
notify('saved to %s' % filename, send_to)
return psfs
def vortex_init(vortex_calib='',
dir_temp='',
diam_ext=37,
lam=3.8,
ngrid=1024,
beam_ratio=0.26,
focal=660,
vc_charge=2,
verbose=False,
**conf):
'''
Creates/writes vortex back-propagation fitsfiles, or loads them if files
already exist.
The following parameters will be added to conf:
vortex_calib, psf_num, perf_num, vvc
Returns: conf (updated and sorted)
'''
# update conf with local variables (remove unnecessary)
conf.update(locals())
[conf.pop(key) for key in ['conf', 'verbose'] if key in conf]
# check if back-propagation params already loaded for this calib
calib = 'vortex_%s_%s_%3.4f' % (vc_charge, ngrid, beam_ratio)
if vortex_calib == calib:
return conf
else:
# check for existing file
filename = os.path.join(dir_temp, '%s.fits' % calib)
if os.path.isfile(filename):
if verbose is True:
print(' loading vortex back-propagation params')
data = fits.getdata(os.path.join(dir_temp, filename))
# read the pre-vortex field
psf_num = data[0] + 1j * data[1]
# read the theoretical vortex field
vvc = data[2] + 1j * data[3]
# read the perfect-result vortex field
perf_num = data[4] + 1j * data[5]
# create files
else:
if verbose is True:
print(" writing vortex back-propagation params")
# create circular pupil
wf_tmp = proper.prop_begin(diam_ext, lam, ngrid, beam_ratio)
proper.prop_circular_aperture(wf_tmp, 1, NORM=True)
# propagate to vortex
lens(wf_tmp, focal)
# pre-vortex field
psf_num = deepcopy(wf_tmp.wfarr)
# vortex phase ramp is oversampled for a better discretization
ramp_oversamp = 11.
nramp = int(ngrid * ramp_oversamp)
start = -nramp / 2 - int(ramp_oversamp) / 2 + 0.5
end = nramp / 2 - int(ramp_oversamp) / 2 + 0.5
Vp = np.arange(start, end, 1.)
# Pancharatnam Phase = arg<Vref,Vp> (horizontal input polarization)
Vref = np.ones(Vp.shape)
prod = np.outer(Vref, Vp)
phiPan = np.angle(prod + 1j * prod.T)
# vortex phase ramp exp(ilphi)
ofst = 0
ramp_sign = 1
vvc_tmp = np.exp(1j * (ramp_sign * vc_charge * phiPan + ofst))
vvc = np.array(impro.resize_img(vvc_tmp.real, ngrid),
dtype=complex)
vvc.imag = impro.resize_img(vvc_tmp.imag, ngrid)
phase_ramp = np.angle(vvc)
# theoretical vortex field
vvc_complex = np.array(np.zeros((ngrid, ngrid)), dtype=complex)
vvc_complex.imag = phase_ramp
vvc = np.exp(vvc_complex)
# apply vortex
proper.prop_multiply(wf_tmp, vvc)
# null the amplitude inside the Lyot Stop, and back propagate
lens(wf_tmp, focal)
proper.prop_circular_obscuration(wf_tmp, 1., NORM=True)
lens(wf_tmp, -focal)
# perfect-result vortex field
perf_num = deepcopy(wf_tmp.wfarr)
# write all fields
data = np.dstack((psf_num.real.T, psf_num.imag.T, vvc.real.T, vvc.imag.T,\
perf_num.real.T, perf_num.imag.T)).T
fits.writeto(os.path.join(dir_temp, filename),
np.float32(data),
overwrite=True)
# shift the phase ramp
vvc = proper.prop_shift_center(vvc)
# add vortex back-propagation parameters at the end of conf
conf = {k: v for k, v in sorted(conf.items())}
conf.update(vortex_calib=calib,
psf_num=psf_num,
vvc=vvc,
perf_num=perf_num)
if verbose is True:
print(' vc_charge=%s, ngrid=%s, beam_ratio=%3.4f'%\
(vc_charge, ngrid, beam_ratio))
return conf
def vortex(wfo, charge, f_lens, diam, pixelsize, Debug_print=False):
n = int(proper.prop_get_gridsize(wfo))
ofst = 0 # no offset
ramp_sign = 1 #sign of charge is positive
ramp_oversamp = 11. # vortex is oversampled for a better discretization
if charge != 0:
wavelength = proper.prop_get_wavelength(wfo)
gridsize = proper.prop_get_gridsize(wfo)
beam_ratio = pixelsize * 4.85e-9 / (wavelength / diam)
calib = str(charge) + str('_') + str(int(
beam_ratio * 100)) + str('_') + str(gridsize)
my_file = str(tmp_dir + 'zz_perf_' + calib + '_r.fits')
proper.prop_propagate(wfo, f_lens, 'inizio') # propagate wavefront
proper.prop_lens(wfo, f_lens,
'focusing lens vortex') # propagate through a lens
proper.prop_propagate(wfo, f_lens, 'VC') # propagate wavefront
if (os.path.isfile(my_file) == True):
if (Debug_print == True):
print("Charge ", charge)
vvc = readfield(tmp_dir, 'zz_vvc_' +
calib) # read the theoretical vortex field
vvc = proper.prop_shift_center(vvc)
scale_psf = wfo._wfarr[0, 0]
psf_num = readfield(tmp_dir,
'zz_psf_' + calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = readfield(tmp_dir, 'zz_perf_' +
calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wfo._wfarr = (
wfo._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
else: # CAL==1: # create the vortex for a perfectly circular pupil
if (Debug_print == True):
print("Charge ", charge)
wfo1 = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
proper.prop_circular_aperture(wfo1, diam / 2)
proper.prop_define_entrance(wfo1)
proper.prop_propagate(wfo1, f_lens,
'inizio') # propagate wavefront
proper.prop_lens(
wfo1, f_lens,
'focusing lens vortex') # propagate through a lens
proper.prop_propagate(wfo1, f_lens, 'VC') # propagate wavefront
writefield(tmp_dir, 'zz_psf_' + calib,
wfo1.wfarr) # write the pre-vortex field
nramp = int(n * ramp_oversamp) #oversamp
# create the vortex by creating a matrix (theta) representing the ramp (created by atan 2 gradually varying matrix, x and y)
y1 = np.ones((nramp, ), dtype=np.int)
y2 = np.arange(0, nramp, 1.) - (nramp / 2) - int(ramp_oversamp) / 2
y = np.outer(y2, y1)
x = np.transpose(y)
theta = np.arctan2(y, x)
x = 0
y = 0
vvc_tmp = np.exp(1j * (ofst + ramp_sign * charge * theta))
theta = 0
vvc_real_resampled = cv2.resize(
vvc_tmp.real, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc_imag_resampled = cv2.resize(
vvc_tmp.imag, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc = np.array(vvc_real_resampled, dtype=complex)
vvc.imag = vvc_imag_resampled
vvcphase = np.arctan2(vvc.imag,
vvc.real) # create the vortex phase
vvc_complex = np.array(np.zeros((n, n)), dtype=complex)
vvc_complex.imag = vvcphase
vvc = np.exp(vvc_complex)
vvc_tmp = 0.
writefield(tmp_dir, 'zz_vvc_' + calib,
vvc) # write the theoretical vortex field
proper.prop_multiply(wfo1, vvc)
proper.prop_propagate(wfo1, f_lens, 'OAP2')
proper.prop_lens(wfo1, f_lens)
proper.prop_propagate(wfo1, f_lens, 'forward to Lyot Stop')
proper.prop_circular_obscuration(
wfo1, 1., NORM=True) # null the amplitude iside the Lyot Stop
proper.prop_propagate(wfo1, -f_lens) # back-propagation
proper.prop_lens(wfo1, -f_lens)
proper.prop_propagate(wfo1, -f_lens)
writefield(tmp_dir, 'zz_perf_' + calib,
wfo1.wfarr) # write the perfect-result vortex field
vvc = readfield(tmp_dir, 'zz_vvc_' + calib)
vvc = proper.prop_shift_center(vvc)
scale_psf = wfo._wfarr[0, 0]
psf_num = readfield(tmp_dir,
'zz_psf_' + calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = readfield(tmp_dir, 'zz_perf_' +
calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wfo._wfarr = (
wfo._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
proper.prop_propagate(wfo, f_lens, "propagate to pupil reimaging lens")
proper.prop_lens(wfo, f_lens, "apply pupil reimaging lens")
proper.prop_propagate(wfo, f_lens, "lyot stop")
return wfo
