def get_wf(wavelength, gridsize, PASSVALUE={}):
diam = PASSVALUE.get('diam', 0.3) # telescope diameter in meters
m1_fl = PASSVALUE.get('m1_fl', 0.5717255) # primary focal length (m)
#beam_ratio = PASSVALUE.get('beam_ratio',0.99) # initial beam width/grid width
tilt_x = PASSVALUE.get('tilt_x', 0.) # Tilt angle along x (arc seconds)
tilt_y = PASSVALUE.get('tilt_y', 0.) # Tilt angle along y (arc seconds)
beam_ratio = 0.99
# Define the wavefront
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
# Point off-axis
prop_tilt(wfo, tilt_x, tilt_y)
# Input aperture
proper.prop_circular_aperture(wfo, diam / 2.)
# Define entrance
proper.prop_define_entrance(wfo)
proper.prop_lens(wfo, m1_fl, "primary")
opd1_func = PASSVALUE['opd_func']
def build_m1_opd():
return gen_opdmap(opd1_func, proper.prop_get_gridsize(wfo),
proper.prop_get_sampling(wfo))
wfo.wfarr *= build_phase_map(
wfo, load_cacheable_grid(opd1_func.__name__, wfo, build_m1_opd, False))
wf = proper.prop_get_wavefront(wfo)
return wf
def simple_telescope(wavelength, gridsize):
d_objective = 0.060
fl_objective = 15.0 * d_objective
fl_eyepiece = 0.021
fl_eye = 0.022
beam_ratio = 0.5
wfo = proper.propbegin(d_objective, wavelength, gridsize, beam_ratio)
proper.prop_circular_aperture(wfo, d_objective / 2)
proper.prop_define_entrance(wfo)
proper.prop_lens(wfo, fl_objective, "objective")
proper.prop_propagate(wfo, fl_objective + fl_eyepiece, "eyepiece")
proper.prop_lens(wfo, fl_eyepiece, "eyepiece")
exit_pupil_distance = fl_eyepiece / (1 - fl_eyepiece /
(fl_objective + fl_eyepiece))
proper.prop_propagate(wfo, exit_pupil_distance, "exit pupil at eye lens:")
proper.prop_lenx(wfo, fl_eye, "eye")
proper.prop_propagate(wfo, fl_eye, "retina")
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
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 falco_gen_annular_FPM(pixresFPM,
rhoInner,
rhoOuter,
FPMampFac,
centering,
rot180=False):
dxiUL = 1.0 / pixresFPM # lambda_c/D per pixel. "UL" for unitless
if np.isinf(rhoOuter):
if centering == "interpixel":
# number of points across the inner diameter of the FPM.
Narray = utils.ceil_even((2 * rhoInner / dxiUL))
else:
# number of points across the inner diameter of the FPM. Another half pixel added for pixel-centered masks.
Narray = utils.ceil_even(2 * (rhoInner / dxiUL + 0.5))
else:
if centering == "interpixel":
# number of points across the outer diameter of the FPM.
Narray = utils.ceil_even(2 * rhoOuter / dxiUL)
else:
# number of points across the outer diameter of the FPM. Another half pixel added for pixel-centered masks.
Narray = utils.ceil_even(2 * (rhoOuter / dxiUL + 0.5))
xshift = 0 # translation in x of FPM (in lambda_c/D)
yshift = 0 # translation in y of FPM (in lambda_c/D)
Darray = Narray * dxiUL # width of array in lambda_c/D
diam = Darray
wl_dummy = 1e-6 # wavelength (m); Dummy value--no propagation here, so not used.
if centering == "interpixel":
cshift = -diam / 2 / Narray
elif rot180:
cshift = -diam / Narray
else:
cshift = 0
wf = proper.prop_begin(diam, wl_dummy, Narray, 1.0)
if not np.isinf(rhoOuter):
# Outer opaque ring of FPM
cx_OD = 0 + cshift + xshift
cy_OD = 0 + cshift + yshift
proper.prop_circular_aperture(wf, rhoOuter, cx_OD, cy_OD)
# Inner spot of FPM (Amplitude transmission can be nonzero)
ra_ID = (rhoInner)
cx_ID = 0 + cshift + xshift
cy_ID = 0 + cshift + yshift
innerSpot = proper.prop_ellipse(
wf, rhoInner, rhoInner, cx_ID, cy_ID,
DARK=True) * (1 - FPMampFac) + FPMampFac
mask = np.fft.ifftshift(np.abs(wf.wfarr)) # undo PROPER's fftshift
return mask * innerSpot # Include the inner FPM spot
def falco_gen_DM_stop(dx, Dmask, centering):
diam = Dmask # diameter of the mask (meters)
# minimum even number of points across to fully contain the actual aperture (if interpixel centered)
NapAcross = Dmask / dx
wf = _init_proper(Dmask, dx, centering)
# 0 shift for pixel-centered pupil, or -dx shift for inter-pixel centering
cshift = -dx / 2 * (centering == "interpixel")
# Outer diameter of aperture
proper.prop_circular_aperture(wf, diam / 2, cshift, cshift)
return np.fft.ifftshift(np.abs(wf.wfarr))
def initialize_proper(self, set_up_beam=False):
"""
Initialize the Wavefronts in Proper
:param set_up_beam: bool applies prop_circular_aperture and prop_define_entrance before spectral scaling
instead of during prescription wher it normally goes
returns wf_colllection attribute array of wavefronts
"""
for iw, wavelength in enumerate(self.wsamples):
# Scale beam ratio by wavelength for polychromatic imaging
# see Proper manual pg 37
# Proper is devised such that you get a Nyquist sampled image in the focal plane. If you optical system
# goes directly from pupil plane to focal plane, then you need to scale the beam ratio such that sampling
# in the focal plane is constant. You can check this with check_sampling, which returns the value from
# prop_get_sampling. If the optical system does not go directly from pupil-to-object plane at each optical
# plane, the beam ratio does not need to be scaled by wavelength, because of some optics wizardry that
# I don't fully understand. KD 2019
if sp.focused_sys:
beam_ratio = sp.beam_ratio
else:
beam_ratio = sp.beam_ratio * ap.wvl_range[0] / wavelength
# dprint(f"iw={iw}, w={w}, beam ratio is {self.beam_ratios[iw]}")
# Initialize the wavefront at entrance pupil
wfp = proper.prop_begin(tp.entrance_d, wavelength, sp.grid_size, beam_ratio)
if set_up_beam:
proper.prop_circular_aperture(wfp, radius = tp.entrance_d / 2)
proper.prop_define_entrance(wfp) # normalizes the intensity
wfp.wfarr = np.multiply(wfp.wfarr, np.sqrt(self.spectra[0][iw]), out=wfp.wfarr, casting='unsafe')
wfs = [wfp]
names = ['star']
# Initiate wavefronts for companion(s)
if ap.companion:
for ix in range(len(ap.contrast)):
wfc = proper.prop_begin(tp.entrance_d, wavelength, sp.grid_size, beam_ratio)
if set_up_beam:
proper.prop_circular_aperture(wfc, radius=tp.entrance_d / 2)
proper.prop_define_entrance(wfc) # normalizes the intensity
wfc.wfarr = np.multiply(wfc.wfarr, np.sqrt(self.spectra[ix][iw]), out=wfc.wfarr, casting='unsafe')
wfs.append(wfc)
names.append('companion_%i' % ix)
for io, (name, wf) in enumerate(zip(names, wfs)):
self.wf_collection[iw, io] = Wavefront(wf, wavelength, name, beam_ratio, iw, io)
def prefocal_image(wavelength, gridsize, PASSVAL):
diam = PASSVAL['diam']
focal_length = PASSVAL['focal_length']
beam_ratio = PASSVAL['beam_ratio']
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
proper.prop_circular_aperture(wfo, diam/2)
proper.prop_define_entrance(wfo)
proper.prop_zernikes(wfo, [i+1 for i in range(len(PASSVAL['ZERN']))], PASSVAL['ZERN'])
#print(proper.prop_get_phase(wfo)[gridsize//2,:])
proper.prop_lens(wfo, focal_length)
proper.prop_propagate(wfo, focal_length - PASSVAL['DEFOCUS'], TO_PLANE=False)
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
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 simple_telescope(wavelength, gridsize):
diam = 1.0
focal_ratio = 15.0
focal_length = diam * focal_ratio
beam_ratio = 0.5
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
proper.prop_circular_aperture(wfo, diam / 2)
proper.prop_zernikes(wfo, [5], [1e-6])
proper.prop_define_entrance(wfo)
proper.prop_lens(wfo, focal_length * 0.98)
proper.prop_propagate(wfo, focal_length)
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
def lens(wf,
focal=660,
offset_before=0,
offset_after=0,
offset_light_trap=0,
diam_light_trap=0,
**conf):
# propagation before lens
proper.prop_propagate(wf, focal + offset_before)
# Fourier transform of an image using a lens
proper.prop_lens(wf, focal)
# check for light trap
if offset_light_trap == 0 and diam_light_trap == 0:
# propagation after lens
proper.prop_propagate(wf, focal + offset_after)
else:
# add light trap
proper.prop_propagate(wf, focal - offset_light_trap)
proper.prop_circular_aperture(wf, diam_light_trap, 0, 0, NORM=True)
proper.prop_propagate(wf, offset_light_trap + offset_after)
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 prescription_quad_tiltafter(wavelength, gridsize,
PASSVALUE = {'diam': 0.3,
'm1_fl': 0.5717255,
'beam_ratio': 0.2,
'tilt_x': 0.0,
'tilt_y': 0.0
}):
diam = PASSVALUE['diam'] # telescope diameter in meters
m1_fl = PASSVALUE['m1_fl'] # primary focal length (m)
beam_ratio = PASSVALUE['beam_ratio'] # initial beam width/grid width
tilt_x = PASSVALUE['tilt_x'] # Tilt angle along x (arc seconds)
tilt_y = PASSVALUE['tilt_y'] # Tilt angle along y (arc seconds)
# Define the wavefront
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
# Input aperture
proper.prop_circular_aperture(wfo, diam/2)
# Define entrance
proper.prop_define_entrance(wfo)
# Primary mirror (treat as quadratic lens)
proper.prop_lens(wfo, m1_fl, "primary")
# Point off-axis
prop_tilt(wfo, tilt_x, tilt_y)
# Focus
proper.prop_propagate(wfo, m1_fl, "focus", TO_PLANE=True)
# End
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
def apply_lyot(self, wf):
"""
applies the appropriately sized Lyot stop depending on the coronagraph type
:param wf: 2D wavefront
:return:
"""
if not hasattr(tp, 'lyot_size'):
raise ValueError(
"must set tp.lyot_size in units fraction of the beam radius at the current surface"
)
if self.mode is 'Gaussian':
proper.prop_circular_aperture(wf, tp.lyot_size, NORM=True)
elif self.mode is 'Solid':
proper.prop_circular_aperture(wf, tp.lyot_size, NORM=True)
elif self.mode is '8th_Order':
proper.prop_circular_aperture(wf, tp.lyot_size, NORM=True)
def scexao_model(lmda, grid_size, kwargs):
"""
propagates instantaneous complex E-field thru Subaru from the DM through SCExAO
uses PyPROPER3 to generate the complex E-field at the pupil plane, then propagates it through SCExAO 50x50 DM,
then coronagraph, to the focal plane
:returns spectral cube at instantaneous time in the focal_plane()
"""
# print("Propagating Broadband Wavefront Through Subaru")
# Initialize the Wavefront in Proper
wfo = proper.prop_begin(entrance_d, lmda, grid_size, beam_ratio)
# Defines aperture (baffle-before primary)
proper.prop_circular_aperture(wfo, entrance_d / 2)
proper.prop_define_entrance(wfo) # normalizes abs intensity
# Test Sampling
if kwargs['verbose'] and kwargs['ix'] == 0:
check1 = proper.prop_get_sampling(wfo)
print(
f"\n\tDM Pupil Plane\n"
f"sampling at aperture is {check1 * 1e3:.4f} mm\n"
f"Total Sim is {check1 * 1e3 * grid_size:.2f}x{check1 * 1e3 * grid_size:.2f} mm\n"
f"Diameter of beam is {check1 * 1e3 * grid_size * beam_ratio:.4f} mm over {grid_size * beam_ratio} pix"
)
# SCExAO Reimaging 1
proper.prop_lens(
wfo, fl_SxOAPG) # produces f#14 beam (approx exit beam of AO188)
proper.prop_propagate(wfo, fl_SxOAPG * 2) # move to second pupil
if kwargs['verbose'] and kwargs['ix'] == 0:
print(f"initial f# is {proper.prop_get_fratio(wfo):.2f}\n")
########################################
# Import/Apply Actual DM Map
# #######################################
plot_flag = False
if kwargs['verbose'] and kwargs['ix'] == 0:
plot_flag = True
dm_map = kwargs['map']
errormap(wfo,
dm_map,
SAMPLING=dm_pitch,
MIRROR_SURFACE=True,
MASKING=True,
BR=beam_ratio,
PLOT=plot_flag) # MICRONS=True
if kwargs['verbose'] and kwargs['ix'] == 0:
fig, subplot = plt.subplots(nrows=1, ncols=2, figsize=(12, 5))
ax1, ax2 = subplot.flatten()
fig.suptitle('SCExAO Model WFO after errormap',
fontweight='bold',
fontsize=14)
ax1.imshow(proper.prop_get_amplitude(wfo), interpolation='none'
) # np.abs(proper.prop_shift_center(wfo.wfarr))**2
ax1.set_title('Amplitude')
ax2.imshow(
proper.prop_get_phase(wfo),
interpolation=
'none', # np.angle(proper.prop_shift_center(wfo.wfarr))
vmin=-1 * np.pi,
vmax=1 * np.pi,
cmap='hsv') # , cmap='hsv'
ax2.set_title('Phase')
# ------------------------------------------------
# SCExAO Reimaging 2
proper.prop_lens(wfo, fl_SxOAPG)
proper.prop_propagate(wfo,
fl_SxOAPG) # focus at exit of DM telescope system
proper.prop_lens(wfo, fl_SxOAPG)
proper.prop_propagate(wfo,
fl_SxOAPG) # focus at exit of DM telescope system
# # Coronagraph
SubaruPupil(wfo) # focal plane mask
# if kwargs['verbose'] and kwargs['ix']==0:
# fig, subplot = plt.subplots(nrows=1, ncols=2, figsize=(12, 5))
# ax1, ax2 = subplot.flatten()
# fig.suptitle('SCExAO Model WFO after FPM', fontweight='bold', fontsize=14)
# # ax.imshow(dm_map, interpolation='none')
# ax1.imshow(np.abs(proper.prop_shift_center(wfo.wfarr))**2, interpolation='none', norm=LogNorm(vmin=1e-7,vmax=1e-2))
# ax1.set_title('Amplitude')
# ax2.imshow(np.angle(proper.prop_shift_center(wfo.wfarr)), interpolation='none',
# vmin=-2*np.pi, vmax=2*np.pi, cmap='hsv') # , cmap='hsv'
# ax2.set_title('Phase')
proper.prop_propagate(wfo, fl_SxOAPG)
proper.prop_lens(wfo, fl_SxOAPG)
proper.prop_propagate(wfo, fl_SxOAPG) # middle of 2f system
proper.prop_circular_aperture(wfo, lyot_size, NORM=True) # lyot stop
proper.prop_propagate(wfo, fl_SxOAPG) #
proper.prop_lens(wfo, fl_SxOAPG) # exit lens of gaussian telescope
proper.prop_propagate(wfo, fl_SxOAPG) # to focus
# MEC Pickoff reimager.
proper.prop_propagate(wfo, mec_parax_fl) # to another pupil
proper.prop_lens(
wfo, mec_parax_fl) # collimating lens, pupil size should be 8 mm
proper.prop_propagate(wfo, mec1_fl +
.0142557) # mec1_fl .054 mec1_fl+.0101057
# if kwargs['verbose'] and kwargs['ix']==0:
# current = proper.prop_get_beamradius(wfo)
# print(f'Beam Radius after SCExAO exit (at MEC foreoptics entrance) is {current*1e3:.3f} mm\n'
# f'current f# is {proper.prop_get_fratio(wfo):.2f}\n')
# ##################################
# MEC Optics Box
# ###################################
proper.prop_circular_aperture(wfo,
0.00866) # reading off the zemax diameter
proper.prop_lens(wfo, mec1_fl) # MEC lens 1
proper.prop_propagate(wfo,
mec_l1_l2) # there is a image plane at z=mec1_fl
proper.prop_lens(wfo, mec2_fl) # MEC lens 2 (tiny lens)
proper.prop_propagate(wfo, mec_l2_l3)
proper.prop_lens(wfo, mec3_fl) # MEC lens 3
proper.prop_propagate(wfo, mec3_fl,
TO_PLANE=False) # , TO_PLANE=True mec_l3_focus
# #######################################
# Focal Plane
# #######################################
# Check Sampling in focal plane
# shifts wfo from Fourier Space (origin==lower left corner) to object space (origin==center)
# wf, samp = proper.prop_end(wfo, NoAbs=True)
wf = proper.prop_shift_center(wfo.wfarr)
wf = extract_center(wf, new_size=np.array(kwargs['psf_size']))
samp = proper.prop_get_sampling(wfo)
smp_asec = proper.prop_get_sampling_arcsec(wfo)
if kwargs['verbose'] and kwargs['ix'] == 0:
fig, subplot = plt.subplots(nrows=1, ncols=2, figsize=(12, 5))
fig.subplots_adjust(left=0.08, hspace=.4, wspace=0.2)
ax1, ax2 = subplot.flatten()
fig.suptitle('SCExAO Model Focal Plane',
fontweight='bold',
fontsize=14)
tic_spacing, tic_labels, axlabel = scale_lD(
wfo, newsize=kwargs['psf_size'][0])
tic_spacing[0] = tic_spacing[0] + 1 # hack for edge effects
tic_spacing[-1] = tic_spacing[-1] - 1 # hack for edge effects
im = ax1.imshow(
np.abs(wf)**2,
interpolation='none',
norm=LogNorm(
vmin=1e-7,
vmax=1e-2)) # np.abs(proper.prop_shift_center(wfo.wfarr))**2
ax1.set_xticks(tic_spacing)
ax1.set_xticklabels(tic_labels)
ax1.set_yticks(tic_spacing)
ax1.set_yticklabels(tic_labels)
ax1.set_ylabel(axlabel, fontsize=8)
add_colorbar(im)
im = ax2.imshow(np.angle(wf),
interpolation='none',
vmin=-np.pi,
vmax=np.pi,
cmap='hsv')
ax2.set_xticks(tic_spacing)
ax2.set_xticklabels(tic_labels)
ax2.set_yticks(tic_spacing)
ax2.set_yticklabels(tic_labels)
ax2.set_ylabel(axlabel, fontsize=8)
add_colorbar(im)
if kwargs['verbose'] and kwargs['ix'] == 0:
print(
f"\nFocal Plane\n"
f"sampling at focal plane is {samp*1e6:.1f} um ~= {smp_asec * 1e3:.4f} mas\n"
f"\tfull FOV is {samp * kwargs['psf_size'][0] * 1e3:.2f} x {samp * kwargs['psf_size'][1] * 1e3:.2f} mm "
)
# s_rad = proper.prop_get_sampling_radians(wfo)
# print(f"sampling at focal plane is {s_rad * 1e6:.6f} urad")
print(f'final focal ratio is {proper.prop_get_fratio(wfo)}')
print(f"Finished simulation")
return wf, samp
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 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 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 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 falco_gen_pupil_WFIRSTcycle6_LS(Nbeam,
Dbeam,
ID,
OD,
strut_width,
centering,
rot180deg=False):
strut_width = strut_width * Dbeam # now in meters
dx = Dbeam / Nbeam
clock_deg = 0
magfacD = 1
xshift = 0
yshift = 0
pad_strut = 0
Dmask = Dbeam # % width of the beam (so can have zero padding if LS is undersized) (meters)
diam = Dmask # width of the mask (meters)
# minimum even number of points across to fully contain the actual aperture (if interpixel centered)
NapAcross = Dmask / dx
wf = _init_proper(Dmask, dx, centering)
# 0 shift for pixel-centered pupil, or -dx shift for inter-pixel centering
if centering == "interpixel":
cshift = -dx / 2
elif rot180deg:
cshift = -dx
else:
cshift = 0
# DATA FROM THE VISIO FILE
D0 = 8 # inches, pupil diameter in Visio file
x0 = -26 # inches, pupil center in x in Visio file
y0 = 20.25 # inches, pupil center in y in Visio file
Dconv = diam / D0 # conversion factor from inches and Visio units to meters
# PRIMARY MIRROR (OUTER DIAMETER)
ra_OD = (Dbeam * OD / 2) * magfacD
cx_OD = cshift + xshift
cy_OD = cshift + yshift
proper.prop_circular_aperture(wf, ra_OD, cx_OD, cy_OD)
# SECONDARY MIRROR (INNER DIAMETER)
ra_ID = (Dbeam * ID / 2) * magfacD
cx_ID = cshift + xshift
cy_ID = cshift + yshift
proper.prop_circular_obscuration(wf, ra_ID, cx_ID, cy_ID)
sx_s = magfacD * (3.6 * (diam / D0) + pad_strut)
sy_s = magfacD * (strut_width + pad_strut)
clock_rot = np.array(
[[np.cos(np.radians(clock_deg)), -np.sin(np.radians(clock_deg))],
[np.sin(np.radians(clock_deg)),
np.cos(np.radians(clock_deg))]])
def _get_strut_cxy(x, y):
cx_s = (x - x0) * Dconv
cy_s = (y - y0) * Dconv
cxy = magfacD * clock_rot.dot([cx_s, cy_s]) + cshift
return cxy + [xshift, yshift]
# STRUT 1
rot_s1 = 77.56 + clock_deg # degrees
cx_s1, cy_s1 = _get_strut_cxy(-24.8566, 22.2242)
proper.prop_rectangular_obscuration(wf,
sx_s,
sy_s,
cx_s1,
cy_s1,
ROTATION=rot_s1)
# STRUT 2
rot_s2 = -17.56 + clock_deg # degrees
cx_s2, cy_s2 = _get_strut_cxy(-23.7187, 20.2742)
proper.prop_rectangular_obscuration(wf,
sx_s,
sy_s,
cx_s2,
cy_s2,
ROTATION=rot_s2)
# STRUT 3
rot_s3 = -42.44 + clock_deg # degrees
cx_s3, cy_s3 = _get_strut_cxy(-24.8566, 18.2758)
proper.prop_rectangular_obscuration(wf,
sx_s,
sy_s,
cx_s3,
cy_s3,
ROTATION=rot_s3)
# STRUT 4
rot_s4 = 42.44 + clock_deg # degrees
cx_s4, cy_s4 = _get_strut_cxy(-27.1434, 18.2758)
proper.prop_rectangular_obscuration(wf,
sx_s,
sy_s,
cx_s4,
cy_s4,
ROTATION=rot_s4)
# STRUT 5
rot_s5 = 17.56 + clock_deg # degrees
cx_s5, cy_s5 = _get_strut_cxy(-28.2813, 20.2742)
proper.prop_rectangular_obscuration(wf,
sx_s,
sy_s,
cx_s5,
cy_s5,
ROTATION=rot_s5)
# STRUT 6
rot_s6 = 102.44 + clock_deg # degrees
cx_s6, cy_s6 = _get_strut_cxy(-27.1434, 22.2242)
proper.prop_rectangular_obscuration(wf,
sx_s,
sy_s,
cx_s6,
cy_s6,
ROTATION=rot_s6)
mask = np.fft.ifftshift(np.abs(wf.wfarr))
if rot180deg:
mask = np.rot90(mask, 2)
return mask
def dummy_telescope(lmda, grid_size, kwargs):
"""
propagates instantaneous complex E-field thru Subaru from the DM through SCExAO
uses PyPROPER3 to generate the complex E-field at the pupil plane, then propagates it through SCExAO 50x50 DM,
then coronagraph, to the focal plane
:returns spectral cube at instantaneous time in the focal_plane()
"""
# print("Propagating Broadband Wavefront Through Subaru")
# Initialize the Wavefront in Proper
wfo = proper.prop_begin(entrance_d, lmda, grid_size, beam_ratio)
# Defines aperture (baffle-before primary)
proper.prop_circular_aperture(wfo, entrance_d / 2)
proper.prop_define_entrance(wfo) # normalizes abs intensity
# SCExAO Reimaging 1
proper.prop_lens(wfo, fl_SxOAPG)
proper.prop_propagate(wfo, fl_SxOAPG * 2) # move to second pupil
########################################
# Import/Apply Actual DM Map
# #######################################
plot_flag = False
if kwargs['verbose'] and kwargs['ix'] == 0:
plot_flag = True
dm_map = kwargs['map']
# flat = proper.prop_zernikes(wfo, [2, 3], np.array([5, 1])) # zernike[2,3] = x,y tilt
# adding a tilt for shits and giggles
# proper.prop_propagate(wfo, fl_SxOAPG) # from tweeter-DM to OAP2
errormap(wfo,
dm_map,
SAMPLING=dm_pitch,
MIRROR_SURFACE=True,
MICRONS=True,
BR=beam_ratio,
PLOT=plot_flag) # WAVEFRONT=True
# errormap(wfo, dm_map, SAMPLING=dm_pitch, AMPLITUDE=True, BR=beam_ratio, PLOT=plot_flag) # WAVEFRONT=True
# proper.prop_circular_aperture(wfo, entrance_d/2)
if kwargs['verbose'] and kwargs['ix'] == 0:
fig, subplot = plt.subplots(nrows=1, ncols=2, figsize=(12, 5))
ax1, ax2 = subplot.flatten()
fig.suptitle('SCExAO Model WFO after errormap',
fontweight='bold',
fontsize=14)
# ax.imshow(dm_map, interpolation='none')
ax1.imshow(np.abs(proper.prop_shift_center(wfo.wfarr))**2,
interpolation='none')
ax1.set_title('Amplitude')
ax2.imshow(np.angle(proper.prop_shift_center(wfo.wfarr)),
interpolation='none',
vmin=-2 * np.pi,
vmax=2 * np.pi) # , cmap='hsv'
ax2.set_title('Phase')
# ------------------------------------------------
# proper.prop_propagate(wfo, fl_SxOAPG) # from tweeter-DM to OAP2
# SCExAO Reimaging 2
proper.prop_lens(wfo, fl_SxOAPG)
proper.prop_propagate(wfo,
fl_SxOAPG) # focus at exit of DM telescope system
proper.prop_lens(wfo, fl_SxOAPG)
proper.prop_propagate(wfo,
fl_SxOAPG) # focus at exit of DM telescope system
# ########################################
# # Focal Plane
# # #######################################
# Check Sampling in focal plane
# shifts wfo from Fourier Space (origin==lower left corner) to object space (origin==center)
# proper.prop_shift_center(wfo.wfarr)
# wf, samp = proper.prop_end(wfo, NoAbs=True)
wf = proper.prop_shift_center(wfo.wfarr)
samp = proper.prop_get_sampling(wfo)
# smp_asec = proper.prop_get_sampling_arcsec(wfo)
if kwargs['verbose'] and kwargs['ix'] == 0:
fig, ax = plt.subplots(nrows=1, ncols=1)
fig.suptitle('SCExAO Model Focal Plane',
fontweight='bold',
fontsize=14)
ax.imshow(
np.abs(wf)**2,
interpolation='none',
norm=LogNorm(
vmin=1e-7,
vmax=1e-2)) # np.abs(proper.prop_shift_center(wfo.wfarr))**2
#
# if kwargs['verbose'] and kwargs['ix']==0:
# print(f"\n\tFocal Plane\n"
# f"sampling at focal plane is {smp_asec * 1e3:.4f} mas\n"
# f"\tfull FOV is {smp_asec * grid_size * 1e3:.2f} mas")
# s_rad = proper.prop_get_sampling_radians(wfo)
# print(f"sampling at focal plane is {s_rad * 1e6:.6f} urad")
# print(f"Finished simulation")
return wf, samp
def simple_telescope(wavelength, gridsize):
# Define entrance aperture diameter and other quantities
d_objective = 5.0 # objective diameter in meters
fl_objective = 20.0 * d_objective # objective focal length in meters
fl_eyepiece = 0.021 # eyepiece focal length
fl_eye = 0.022 # human eye focal length
beam_ratio = 0.3 # initial beam width/grid width
# Define the wavefront
wfo = proper.prop_begin(d_objective, wavelength, gridsize, beam_ratio)
# print d_objective, wavelength, gridsize, beam_ratio
# Define a circular aperture
proper.prop_circular_aperture(wfo, d_objective / 2)
# proper.prop_propagate(wfo, fl_objective)
# proper.prop_propagate(wfo, fl_objective)
# proper.prop_propagate(wfo, fl_objective)
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Define entrance
proper.prop_define_entrance(wfo)
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# proper.prop_propagate(wfo, fl_objective+fl_eyepiece, "eyepiece")
# # plt.imshow(proper.prop_get_amplitude(wfo))
# # plt.show()
#
# proper.prop_propagate(wfo, fl_objective+fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
#
# proper.prop_propagate(wfo, fl_objective+fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Define a lens
proper.prop_lens(wfo, fl_objective, "objective")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Propagate the wavefront
proper.prop_propagate(wfo, fl_objective + fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Define another lens
proper.prop_lens(wfo, fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
exit_pupil_distance = fl_eyepiece / (1 - fl_eyepiece /
(fl_objective + fl_eyepiece))
proper.prop_propagate(wfo, exit_pupil_distance, "exit pupil at eye lens")
# quicklook_wf(wfo)
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
proper.prop_lens(wfo, fl_eye, "eye")
proper.prop_propagate(wfo, fl_eye, "retina")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
quicklook_wf(wfo)
phase_map = proper.prop_get_phase(wfo)
amp_map = proper.prop_get_amplitude(wfo)
# quicklook_im(phase_map)
amp_map[80:100, 80:100] = 0
quicklook_im(amp_map, logAmp=True)
import numpy as np
wfo.wfarr = proper.prop_shift_center(amp_map * np.cos(phase_map) +
1j * amp_map * np.sin(phase_map))
# quicklook_wf(wf_array[iw,0])
proper.prop_propagate(wfo, fl_eye, "retina")
proper.prop_lens(wfo, fl_eye, "eye")
quicklook_wf(wfo)
# End
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
def run_system(empty_lamda, grid_size, PASSVALUE): #'dm_disp':0
passpara = PASSVALUE['params']
ap.__dict__ = passpara[0].__dict__
tp.__dict__ = passpara[1].__dict__
iop.__dict__ = passpara[2].__dict__
# params.ap = passpara[0]
# params.tp = passpara[1]
#
# ap = params.ap
# tp = params.tp
# print 'line 23', tp.occulter_type
# print 'propagating frame:', PASSVALUE['iter']
wsamples = np.linspace(tp.band[0], tp.band[1], tp.nwsamp) / 1e9
# print wsamples
datacube = []
# print proper.prop_get_sampling(wfp), proper.prop_get_nyquistsampling(wfp), proper.prop_get_fratio(wfp)
# global phase_map, Imaps
# Imaps = np.zeros((4,tp.grid_size,tp.grid_size))
# phase_map = np.zeros((tp.grid_size, tp.grid_size))
# wavefronts = np.empty((len(wsamples),1+len(ap.contrast)), dtype=object)
for iw, w in enumerate(wsamples):
# Define the wavefront
beam_ratio = tp.beam_ratio * tp.band[0] / w * 1e-9
wfp = proper.prop_begin(tp.diam, w, tp.grid_size, beam_ratio)
wfs = [wfp]
names = ['primary']
if ap.companion:
for id in range(len(ap.contrast)):
wfc = proper.prop_begin(tp.diam, w, tp.grid_size, beam_ratio)
wfs.append(wfc)
names.append('companion_%i' % id)
# proper.prop_circular_aperture(wfo, tp.diam / 2)
# for iw, wf in enumerate([wfo, wfc]):
wframes = np.zeros((tp.grid_size, tp.grid_size))
for iwf, wf in zip(names, wfs):
# wavefronts[iw,iwf] = wf
proper.prop_circular_aperture(wf, tp.diam / 2)
# quicklook_wf(wf, show=True)
if tp.use_atmos:
tdm.add_atmos(wf,
tp.f_lens,
w,
atmos_map=PASSVALUE['atmos_map'])
if tp.rot_rate:
tdm.rotate_atmos(wf, PASSVALUE['atmos_map'])
# quicklook_wf(wf, show=True)
# if tp.use_spiders:
# tdm.add_spiders(wf, tp.diam)
if tp.use_hex:
tdm.add_hex(wf)
proper.prop_define_entrance(wf) # normalizes the intensity
if iwf[:9] == 'companion':
tdm.offset_companion(wf, int(iwf[10:]), PASSVALUE['atmos_map'])
# quicklook_wf(wf, show=True)
if tp.use_apod:
tdm.do_apod(wf, tp.grid_size, tp.beam_ratio, tp.apod_gaus)
# quicklook_wf(wf, show=True)
# obj_map = tdm.wfs_measurement(wfo)#, obj_map, tp.wfs_scale)
proper.prop_propagate(wf, tp.f_lens)
if tp.aber_params['CPA']:
tdm.add_aber(wf,
tp.f_lens,
tp.aber_params,
tp.aber_vals,
PASSVALUE['iter'],
Loc='CPA')
# if tp.CPA_type == 'test':
# tdm.add_single_speck(wf, PASSVALUE['iter'] )
# if tp.CPA_type == 'Static':
# tdm.add_static(wf, tp.f_lens, loc = 'CPA')
# if tp.CPA_type == 'Amp':
# tdm.add_static(wf, tp.f_lens, loc = 'CPA', type='Amp')
# if tp.CPA_type == 'Quasi':
# tdm.add_quasi(wf, tp.f_lens, PASSVALUE['iter'])
# rawImageIO.save_wf(wf, iop.datadir+'/beforeAO.pkl')
# quicklook_wf(wf)
# quicklook_im(obj_map, logAmp=False)
proper.prop_propagate(wf, tp.f_lens)
if tp.quick_ao:
if iwf == 'primary': # and PASSVALUE['iter'] == 0:
# quicklook_wf(wf, show=True)
r0 = float(PASSVALUE['atmos_map'][-10:-5])
# dprint((r0, 'r0'))
CPA_map = tdm.quick_wfs(wf, PASSVALUE['iter'],
r0=r0) # , obj_map, tp.wfs_scale)
# dprint('quick_ao')
# quicklook_wf(wf, show=True)
if tp.use_ao:
tdm.quick_ao(wf, iwf, tp.f_lens, beam_ratio,
PASSVALUE['iter'], CPA_map)
# dprint('quick_ao')
# quicklook_wf(wf, show=True)
else:
if tp.use_ao:
tdm.adaptive_optics(wf, iwf, iw, tp.f_lens, beam_ratio,
PASSVALUE['iter'])
if iwf == 'primary': # and PASSVALUE['iter'] == 0:
# quicklook_wf(wf, show=True)
r0 = float(PASSVALUE['atmos_map'][-10:-5])
# dprint((r0, 'r0'))
# if iw == np.ceil(tp.nwsamp/2):
tdm.wfs_measurement(wf, PASSVALUE['iter'], iw,
r0=r0) #, obj_map, tp.wfs_scale)
proper.prop_propagate(wf, tp.f_lens)
# rawImageIO.save_wf(wf, iop.datadir+'/loopAO_8act.pkl')
# if iwf == 'primary':
# quicklook_wf(wf, show=True)
# if tp.active_modulate:
# tdm.modulate(wf, w, PASSVALUE['iter'])
# if iwf == 'primary':
# quicklook_wf(wf, show=True)
if tp.aber_params['NCPA']:
tdm.add_aber(wf,
tp.f_lens,
tp.aber_params,
tp.aber_vals,
PASSVALUE['iter'],
Loc='NCPA')
# if tp.NCPA_type == 'Static':
# tdm.add_static(wf, tp.f_lens, loc = 'NCPA')
# if tp.NCPA_type == 'Wave':
# tdm.add_IFS_ab(wf, tp.f_lens, w)
# if tp.NCPA_type == 'Quasi':
# tdm.add_quasi(wf, tp.f_lens, PASSVALUE['iter'])
# quicklook_wf(wf, show=True)
# if iwf == 'primary':
# NCPA_phasemap = proper.prop_get_phase(wf)
# quicklook_im(NCPA_phasemap, logAmp=False, show=False, colormap="jet", vmin=-3.14, vmax=3.14)
# if iwf == 'primary':
# global obj_map
# r0 = float(PASSVALUE['atmos_map'][-10:-5])
# obj_map = tdm.wfs_measurement(wf, r0 = r0)#, obj_map, tp.wfs_scale)
# # quicklook_im(obj_map, logAmp=False)
proper.prop_propagate(wf, tp.f_lens)
# spiders are introduced here for now since the phase unwrapping seems to ignore them and hence so does the DM
# Check out http://scikit-image.org/docs/dev/auto_examples/filters/plot_phase_unwrap.html for masking argument
if tp.use_spiders:
tdm.add_spiders(wf, tp.diam)
tdm.prop_mid_optics(wf, tp.f_lens)
# if iwf == 'primary':
# if PASSVALUE['iter']>ap.numframes-2 or PASSVALUE['iter']==0:
# quicklook_wf(wf, show=True)
# print proper.prop_get_sampling(wfp), proper.prop_get_sampling_arcsec(wfp), 'here'
if tp.satelite_speck and iwf == 'primary':
tdm.add_speckles(wf)
# tp.variable = proper.prop_get_phase(wfo)[20,20]
# print 'speck phase', tp.variable
# import cPickle as pickle
# dprint('just saved')
# with open(iop.phase_ideal, 'wb') as handle:
# pickle.dump(proper.prop_get_phase(wf), handle, protocol=pickle.HIGHEST_PROTOCOL)
# exit()
if tp.active_null and iwf == 'primary':
FPWFS.active_null(wf, PASSVALUE['iter'], w)
# if tp.speckle_kill and iwf == 'primary':
# tdm.speckle_killer(wf)
# tdm.speck_kill(wf)
# iwf == 'primary':
# parent_bright = aper_phot(proper.prop_get_amplitude(wf),0,8)
# if iwf == 'primary' and iop.saveIQ:
# save_pix_IQ(wf)
# complex_map = proper.prop_shift_center(wf.wfarr)
# complex_pix = complex_map[64, 64]
# print complex_pix
# if np.real(complex_pix) < 0.2:
# quicklook_IQ(wf)
#
# if iwf == 'primary':
# # print np.sum(proper.prop_get_amplitude(wf)), 'before', aper_phot(proper.prop_get_amplitude(wf),0,4)
# quicklook_wf(wf, show=True, logAmp=True)
# if iwf == 'primary':
# quicklook_wf(wf, show=True)
# if tp.active_modulate and PASSVALUE['iter'] >=8:
# coronagraph(wf, tp.f_lens, tp.occulter_type, tp.occult_loc, tp.diam)
# if not tp.active_modulate:
coronagraph(wf, tp.f_lens, tp.occulter_type, tp.occult_loc,
tp.diam)
# dprint(proper.prop_get_sampling_arcsec(wf))
# exit()
# tp.occult_factor = aper_phot(proper.prop_get_amplitude(wf),0,8)/parent_bright
# if PASSVALUE['iter'] % 10 == 0:
# with open(iop.logfile, 'a') as the_file:
# the_file.write('\n', tp.occult_factor)
# quicklook_wf(wf, show=True)
if tp.occulter_type != 'None' and iwf == 'primary': #kludge for now until more sophisticated coronapraph has been installed
wf.wfarr *= 0.1
# # print np.sum(proper.prop_get_amplitude(wf)), 'after', aper_phot(proper.prop_get_amplitude(wf), 0, 4)
# quicklook_wf(wf, show=True)
# print proper.prop_get_sampling(wfp), proper.prop_get_sampling_arcsec(wfp), 'here'
# if iwf == 'primary':
# quicklook_wf(wf, show=True)
if tp.use_zern_ab:
tdm.add_zern_ab(wf, tp.f_lens)
(wframe, sampling) = proper.prop_end(wf)
# dprint((np.sum(wframe), 'sum'))
# wframe = proper.prop_get_amplitude(wf)
# planet = np.roll(np.roll(wframe, 20, 1), 20, 0) * 0.1 # [92,92]
# if ap.companion:
# from scipy.ndimage.interpolation import shift
# companion = shift(wframe, shift= np.array(ap.comp_loc[::-1])- np.array([tp.grid_size/2,tp.grid_size/2])) * ap.contrast
# # planet = np.roll(wframe, 15, 0) * 0.1 # [92,92]
#
# wframe = (wframe + companion)
# quicklook_im(wframe, logAmp=True)
# '''test conserve=True on prop_magnify!'''
# wframe = proper.prop_magnify(wframe, (w*1e9)/tp.band[0])
# wframe = tdm.scale_wframe(wframe, w, iwf)
# print np.shape(wframe)
quicklook_im(wframe)
# quicklook_im(wframe)
# mid = int(len(wframe)/2)
# wframe = wframe[mid - tp.grid_size/2 : mid +tp.grid_size/2, mid - tp.grid_size/2 : mid +tp.grid_size/2]
# if max(mp.array_size) < tp.grid_size:
# # Photons seeded outside the array cannot have pixel phase uncertainty applied to them. Instead make both grids match in size
# wframe = rawImageIO.resize_image(wframe, newsize=(max(mp.array_size),max(mp.array_size)))
# dprint(np.sum(wframe))
# dprint(iwf)
# if iwf == 'companion_0':
wframes += wframe
# if sp.show_wframe:
# quicklook_im(wframes, logAmp=True, show=True)
datacube.append(wframes)
datacube = np.array(datacube)
datacube = np.abs(datacube)
# #normalize
# datacube = np.transpose(np.transpose(datacube) / np.sum(datacube, axis=(1, 2)))/float(tp.nwsamp)
# print 'Some pixels have negative values, possibly because of some Gaussian uncertainy you introduced. Taking abs for now.'
# view_datacube(datacube)
# # End
# print type(wfo[0,0]), type(wfo)
# # proper.prop_savestate(wfo)
# # else:
# # wfo = proper.prop_state(wfo)
return (datacube, sampling)
def toliman_prescription_simple(wavelength, gridsize):
# Values from Eduardo's RC Toliman system
diam = 0.3 # telescope diameter in meters
fl_pri = 0.5 * 1.143451 # primary focal length (m)
# BN 20180208
d_pri_sec = 0.549337630333726 # primary to secondary separation (m)
# d_pri_sec = 0.559337630333726 # primary to secondary separation (m)
fl_sec = -0.5 * 0.0467579189727913 # secondary focal length (m)
d_sec_to_focus = 0.528110658881 # nominal distance from secondary to focus (from eqn)
# d_sec_to_focus = 0.589999999989853 # nominal distance from secondary to focus
beam_ratio = 0.2 # initial beam width/grid width
m2_rad = 0.059 # Secondary half-diameter (m)
m2_strut_width = 0.01 # Width of struts supporting M2 (m)
m2_supports = 5
# Define the wavefront
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
# Input aperture
proper.prop_circular_aperture(wfo, diam / 2)
# NOTE: could prop_propagate() here if some baffling included
# Secondary and structs obscuration
proper.prop_circular_obscuration(wfo,
m2_rad) # secondary mirror obscuration
# Spider struts/vanes, arranged evenly radiating out from secondary
strut_length = diam / 2 - m2_rad
strut_step = 360 / m2_supports
strut_centre = m2_rad + strut_length / 2
for i in range(0, m2_supports):
angle = i * strut_step
radians = math.radians(angle)
xoff = math.cos(radians) * strut_centre
yoff = math.sin(radians) * strut_centre
proper.prop_rectangular_obscuration(wfo,
m2_strut_width,
strut_length,
xoff,
yoff,
ROTATION=angle + 90)
# Define entrance
proper.prop_define_entrance(wfo)
# Primary mirror (treat as quadratic lens)
proper.prop_lens(wfo, fl_pri, "primary")
# Propagate the wavefront
proper.prop_propagate(wfo, d_pri_sec, "secondary")
# Secondary mirror (another quadratic lens)
proper.prop_lens(wfo, fl_sec, "secondary")
# NOTE: hole through primary?
# Focus
# BN 20180208 - Need TO_PLANE=True if you want an intermediate plane
proper.prop_propagate(wfo, d_sec_to_focus, "focus", TO_PLANE=True)
# proper.prop_propagate(wfo, d_sec_to_focus, "focus", TO_PLANE = False)
# End
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
def prescription_quad(wavelength, gridsize, PASSVALUE={}):
# Assign parameters from PASSVALUE struct or use defaults
diam = PASSVALUE.get('diam', 0.3) # telescope diameter in meters
m1_fl = PASSVALUE.get('m1_fl', 0.5717255) # primary focal length (m)
beam_ratio = PASSVALUE.get('beam_ratio',
0.2) # initial beam width/grid width
tilt_x = PASSVALUE.get('tilt_x', 0.) # Tilt angle along x (arc seconds)
tilt_y = PASSVALUE.get('tilt_y', 0.) # Tilt angle along y (arc seconds)
noabs = PASSVALUE.get('noabs', False) # Output complex amplitude?
m1_hole_rad = PASSVALUE.get('m1_hole_rad', None) # Inner hole diameter
use_caching = PASSVALUE.get('use_caching',
False) # Use cached files if available?
get_wf = PASSVALUE.get('get_wf', False) # Return wavefront
"""
Prescription for a single quad lens system
"""
if 'phase_func' in PASSVALUE:
print('DEPRECATED setting "phase_func": use "opd_func" instead')
if 'opd_func' not in PASSVALUE:
PASSVALUE['opd_func'] = PASSVALUE['phase_func']
elif 'opd_func' not in PASSVALUE:
print("no phase function")
if 'phase_func_sec' in PASSVALUE:
print(
'DEPRECATED setting "phase_func_sec": use "opd_func_sec" instead')
if 'opd_func_sec' not in PASSVALUE:
PASSVALUE['opd_func_sec'] = PASSVALUE['phase_func_sec']
# Define the wavefront
wfo = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
# Point off-axis
prop_tilt(wfo, tilt_x, tilt_y)
###
# Change to build ciruclar aperture??
# Input aperture
proper.prop_circular_aperture(wfo, diam / 2.)
###
# Define entrance
proper.prop_define_entrance(wfo)
proper.prop_lens(wfo, m1_fl, "primary")
if 'opd_func' in PASSVALUE:
opd1_func = PASSVALUE['opd_func']
def build_m1_opd():
return gen_opdmap(opd1_func, proper.prop_get_gridsize(wfo),
proper.prop_get_sampling(wfo))
wfo.wfarr *= build_phase_map(
wfo,
load_cacheable_grid(opd1_func.__name__, wfo, build_m1_opd,
use_caching))
if get_wf:
wf = proper.prop_get_wavefront(wfo)
print('Got wavefront')
if m1_hole_rad is not None:
proper.prop_circular_obscuration(wfo, m1_hole_rad)
#if get_wf:
# wf = proper.prop_get_wavefront(wfo)
# print('Got wavefront')
# Focus
proper.prop_propagate(wfo, m1_fl, "focus", TO_PLANE=True)
# End
(wfo, sampling) = proper.prop_end(wfo)
if get_wf:
return (wfo, wf, sampling)
else:
return (wfo, sampling)
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
def create_pupil(nhr=2**10,
npupil=285,
pupil_img_size=40,
diam_ext=37,
diam_int=11,
spi_width=0.5,
spi_angles=[0, 60, 120],
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=[],
seed=123456,
**conf):
''' Create a pupil.
Args:
nhr: int
high resolution grid
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
'''
# create a high res pupil with PROPER of even size (nhr)
nhr_size = pupil_img_size * nhr / (nhr - 1)
wf_tmp = proper.prop_begin(nhr_size, 1, nhr, diam_ext / nhr_size)
if diam_ext > 0:
proper.prop_circular_aperture(wf_tmp, 1, NORM=True)
if diam_int > 0:
proper.prop_circular_obscuration(wf_tmp,
diam_int / diam_ext,
NORM=True)
if spi_width > 0:
for angle in spi_angles:
proper.prop_rectangular_obscuration(wf_tmp, spi_width/nhr_size, 2, \
ROTATION=angle, NORM=True)
pup = proper.prop_get_amplitude(wf_tmp)
# crop the pupil to odd size (nhr-1), and resize to npupil
pup = pup[1:, 1:]
pup = resize_img(pup, npupil)
# add segments
if seg_width > 0:
segments = np.zeros((nhr, nhr))
# sampling in meters/pixel
sampling = pupil_img_size / nhr
# dist between center of two segments, side by side
seg_d = seg_width * np.cos(np.pi / 6) + seg_gap
# segment radius
seg_r = seg_width / 2
# segment radial distance wrt x and y axis
seg_ny = np.array(seg_ny)
seg_nx = len(seg_ny)
seg_rx = np.arange(seg_nx) - (seg_nx - 1) / 2
seg_ry = (seg_ny - 1) / 2
# loop through segments
np.random.seed(seed)
for i in range(seg_nx):
seg_x = seg_rx[i] * seg_d * np.cos(np.pi / 6)
seg_y = -seg_ry[i] * seg_d
for j in range(1, seg_ny[i] + 1):
# removes secondary and if any missing segment is present
if (np.sqrt(seg_x**2 + seg_y**2) <= 4.01*seg_d) \
or ((seg_rx[i], j) in seg_missing):
seg_y += seg_d
else:
# creates one hexagonal segment at x, y position in meters
segment = create_hexagon(nhr, seg_r, seg_y, seg_x,
sampling)
# multiply by segment reflectivity and add to segments
seg_refl = np.random.normal(1, seg_rms)
segments += segment * seg_refl
seg_y += seg_d
# need to transpose, due to the orientation of hexagons in create_hexagon
segments = segments.T
# resize to npupil, and add to pupil
segments = resize_img(segments, npupil)
pup *= segments
return pup
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
