def check_sampling(wf, tstep, location, line_info, units=None):
"""
checks the sampling of the wavefront at the given location and prints to console
mostly reformats the output of proper.prop_get_sampling into human-readable format
:param wf: wavefront object
:param tstep: timestep, will only check for first timestep, so when tstep==0
:param location: string that identifies where call is being made
:param line_info: info on the line number and function name from where check_sampling was called
example: getframeinfo(stack()[0][0])
via: from inspect import getframeinfo, stack
:param units: desired units of returned print statement; options are 'mm,'um','nm','arcsec','rad'
:return: prints sampling to the command line
"""
if tstep == 0 and wf.ib == 0:
if wf.iw == 0:
print(f"\nFrom {line_info.filename}:{line_info.lineno}\n Sampling at {location}")
check_sampling = proper.prop_get_sampling(wf)
if units == 'mm':
print(f"sampling at wavelength={wf.lamda * 1e9:.0f}nm is {check_sampling*1e3:.4f} mm")
elif units == 'um':
print(f"sampling at wavelength={wf.lamda * 1e9:.0f}nm is {check_sampling*1e6:.1f} um")
elif units == 'nm':
print(f"sampling at wavelength={wf.lamda * 1e9:.0f}nm is {check_sampling*1e9:.1f} nm")
elif units == 'arcsec':
check_sampling = proper.prop_get_sampling_arcsec(wf)
print(f"sampling at wavelength={wf.lamda * 1e9:.0f}nm is {check_sampling*1e3:.2f} mas")
elif units == 'rad':
check_sampling = proper.prop_get_sampling_radians(wf)
print(f"sampling at wavelength={wf.lamda * 1e9:.0f}nm is {check_sampling:.3f} rad")
else:
print(f"sampling at wavelength={wf.lamda * 1e9:.0f}nm is {check_sampling} m")
def scale_lD(wfo, newsize=None):
"""
scales the focal plane into lambda/D units. First convert the sampling in m/pix to rad/pix, then scale by the
center wavelength lambda/D [rad].
:param wfo: proper wavefront object
:return:
"""
samp = proper.prop_get_sampling(wfo)
fn = proper.prop_get_fratio(wfo)
bd = wfo.diam
lmda = wfo.lamda
if newsize is None:
size = wfo.ngrid
else:
size = newsize
# Convert to Angular Sampling Units via platescale
fl = fn * bd
rad_scale = samp / fl
res = lmda / bd
tic_spacing = np.linspace(0, size, 5) # 5 (number of ticks) is set by hand, arbitrarily chosen
tic_labels = np.round(np.linspace(-rad_scale * size / 2 , rad_scale * size / 2 , 5)/res) # nsteps must be same as tic_spacing
tic_spacing[0] = tic_spacing[0] + 1 # hack for edge effects
tic_spacing[-1] = tic_spacing[-1] - 1 # hack for edge effects
axlabel = (r'$\lambda$' + f'/D')
return tic_spacing, tic_labels, axlabel
def save_plane(self, location=None):
"""
Saves the complex field at a specified location in the optical system. If the function is called by
wfo.loop_collection, the plane is saved AFTER the function is applied
Note that the complex planes saved are not summed by object, interpolated over wavelength, nor masked down
to the sp.maskd_size.
:param location: name of plane where field is being saved
:return: self.save_E_fields
"""
if sp.verbose:
dprint(f"saving plane at {location}")
if location is not None and location in sp.save_list:
E_field = np.zeros(
(1, np.shape(self.wf_collection)[0],
np.shape(self.wf_collection)[1], sp.grid_size, sp.grid_size),
dtype=np.complex64)
samp_lambda = np.zeros(ap.n_wvl_init)
for iw, sources in enumerate(self.wf_collection):
samp_lambda[iw] = proper.prop_get_sampling(
self.wf_collection[iw, 0])
for io, wavefront in enumerate(sources):
wf = proper.prop_shift_center(wavefront.wfarr)
E_field[0, iw, io] = copy.copy(wf)
self.Efield_planes = np.vstack((self.Efield_planes, E_field))
self.saved_planes.append(location)
self.plane_sampling.append(samp_lambda)
def gen_cached_name(label, wfo):
prefix = 'cached'
# Most of the cacheable steps depend upon wfo for:
ngrid = proper.prop_get_gridsize(wfo)
beamradius = proper.prop_get_beamradius(wfo)
sampling = proper.prop_get_sampling(wfo)
return '{}_{}_{}_{}_{}.npy'.format(prefix, label, ngrid, sampling,
beamradius)
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 add_atmos(wfo, f_lens, w, atmos_map, correction=False):
# print 'Including Atmospheric Aberations'
# rms_error = 5e-9#500.e-9 # RMS wavefront error in meters
# c_freq = 5e9 # correlation frequency (cycles/meter)
# high_power = 8. # high frewquency falloff (r^-high_power)
# print atmos_map, 'here'
samp = proper.prop_get_sampling(wfo) * tp.band[0] * 1e-9 / w
# samp = 0.125 # from caos ATM GUI: ((r0 sampling [px/r0]) /r0)*0.1
# print samp
dprint(atmos_map)
try:
# rawImageIO.scale_image(atmos_map, 1e6)
obj_map = proper.prop_errormap(
wfo,
atmos_map,
MULTIPLY=1.0,
WAVEFRONT=True,
MAP="obj_map",
SAMPLING=tp.samp) # )##FILE='telescope_objtest.fits'
# quicklook_im(obj_map, logAmp=False)
except IOError:
print '*** Using exception hack for name rounding error ***',
i = 0
up = True
indx = float(atmos_map[-19:-11])
while not os.path.isfile(atmos_map):
# print atmos_map[:11], atmos_map[13:]
# atmos_map = atmos_map[:-12]+ str(i) + atmos_map[-11:]
# print atmos_map
# print indx, indx +i, '%1.6f' % (indx +i)
atmos_map = atmos_map[:-19] + '%1.6f' % (indx +
i) + atmos_map[-11:]
print atmos_map
if up:
i += 1e-6
else:
i -= 1e-6
if i >= 50e-6:
i = 0
up = 0
elif i <= -50e-6:
print 'No file found'
exit()
# rawImageIO.scale_image(atmos_map, 1e-6)
obj_map = proper.prop_errormap(wfo,
atmos_map,
MULTIPLY=1.0,
WAVEFRONT=True,
MAP="obj_map",
SAMPLING=tp.samp)
# quicklook_im(obj_map, logAmp=False)
return obj_map
def check_sampling(tstep, wfo, location, line_info, units=None):
"""
checks the sampling of the wavefront at the given location and prints to console
:param tstep: timestep, will only check for first timestep, so when tstep==0
:param wfo: wavefront object
:param location: string that identifies where call is being made
:param line_info: info on the line number and function name from where check_sampling was called
example: getframeinfo(stack()[0][0])
via: from inspect import getframeinfo, stack
:param units: desired units of returned print statement; options are 'mm,'um','nm','arcsec','rad'
:return: prints sampling to the command line
"""
if tstep == 0:
print(
f"From {line_info.filename}:{line_info.lineno}\n Sampling at {location}"
)
for w in range(wfo.wf_collection.shape[0]):
check_sampling = proper.prop_get_sampling(wfo.wf_collection[w, 0])
if units == 'mm':
print(
f"sampling at wavelength={wfo.wsamples[w]*1e9:.0f}nm is {check_sampling:.4f} m"
)
elif units == 'um':
print(
f"sampling at wavelength={wfo.wsamples[w] * 1e9:.0f}nm is {check_sampling*1e6:.1f} um"
)
elif units == 'nm':
print(
f"sampling at wavelength={wfo.wsamples[w] * 1e9:.0f}nm is {check_sampling*1e9:.1f} nm"
)
elif units == 'arcsec':
check_sampling = proper.prop_get_sampling_arcsec(
wfo.wf_collection[w, 0])
print(
f"sampling at wavelength={wfo.wsamples[w] * 1e9:.0f}nm is {check_sampling*1e3:.2f} mas"
)
elif units == 'rad':
check_sampling = proper.prop_get_sampling_radians(
wfo.wf_collection[w, 0])
print(
f"sampling at wavelength={wfo.wsamples[w] * 1e9:.0f}nm is {check_sampling:.3f} rad"
)
else:
print(
f"sampling at wavelength={wfo.wsamples[w] * 1e9:.0f}nm is {check_sampling} m"
)
def prop_tilt(wf, tilt_x, tilt_y):
"""Tilt a wavefront in X and Y.
based on tilt(self, Xangle, Yangle) from Poppy (poppy_core.py)
From that function's docs:
The sign convention is chosen such that positive Yangle tilts move the star upwards in the
array at the focal plane. (This is sort of an inverse of what physically happens in the propagation
to or through focus, but we're ignoring that here and trying to just work in sky coords)
Parameters
----------
wf : obj
WaveFront class object
tilt_x : float
Tilt angle along x in arc seconds
tilt_y : float
Tilt angle along y in arc seconds
Returns
-------
None
Modifies wavefront array in wf object.
"""
if np.abs(tilt_x) > 0 or np.abs(tilt_y) > 0:
sampling = proper.prop_get_sampling(wf) # m/pixel
xangle_rad = tilt_x * np.pi / 648000. # rad.
yangle_rad = tilt_y * np.pi / 648000. # rad.
ngrid = proper.prop_get_gridsize(wf) # pixels
U, V = np.indices(wf.wfarr.shape, dtype=float)
U -= (ngrid - 1) / 2.0 # pixels X
U *= sampling # m
V -= (ngrid - 1) / 2.0 # pixels Y
V *= sampling # m
# Not totally comfortable that these are combined linearly
# but go with Poppy for now
phase = V * xangle_rad + U * yangle_rad # rad. m
proper.prop_add_phase(wf, phase)
def set_size(self, wf, size_in_lambda_d=0, size_in_m=0):
"""
sets size of occulter in m, depending on if input is in units of lambda/D or in m
:param wf: 2D wavefront
:param size_in_lambda_d: desired occulter size in units of lambda/D
:param size_in_m: desired occulter size in m
:return: occulter size in m
"""
lamda = proper.prop_get_wavelength(wf)
dx_m = proper.prop_get_sampling(wf)
dx_rad = proper.prop_get_sampling_radians(wf)
if size_in_lambda_d is not 0:
occrad_rad = size_in_lambda_d * lamda / tp.entrance_d # occulter radius in radians
self.size = occrad_rad * dx_m / dx_rad # occulter radius in meters
elif size_in_m is not 0:
self.size = size_in_m
else:
raise ValueError('must set occulter size in either m or lambda/D units')
def build_m1_opd():
return gen_opdmap(opd1_func, proper.prop_get_gridsize(wfo), proper.prop_get_sampling(wfo))
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 propcustom_dm(wf, dm_z0, dm_xc, dm_yc, spacing=0., **kwargs):
"""
Generate a deformable mirror surface almost exactly like PROPER.
Simulate a deformable mirror of specified actuator spacing, including the
effects of the DM influence function. Has two more optional keywords
compared to proper.prop_dm
Parameters
----------
wf : obj
WaveFront class object
dm_z0 : str or numpy ndarray
Either a 2D numpy array containing the surface piston of each DM
actuator in meters or the name of a 2D FITS image file containing the
above
dm_xc, dm_yc : list or numpy ndarray
The location of the optical axis (center of the wavefront) on the DM in
actuator units (0 ro num_actuator-1). The center of the first actuator
is (0.0, 0.0)
spacing : float
Defines the spacing in meters between actuators; must not be used when
n_act_across_pupil is specified.
Returns
-------
dmap : numpy ndarray
Returns DM surface (not wavefront) map in meters
Other Parameters
----------------
FIT : bool
Switch that tells routine that the values in "dm_z" are the desired
surface heights rather than commanded actuator heights, and so the
routine should fit this map, accounting for actuator influence functions,
to determine the necessary actuator heights. An iterative error-minimizing
loop is used for the fit.
NO_APPLY : bool
If set, the DM pattern is not added to the wavefront. Useful if the DM
surface map is needed but should not be applied to the wavefront
N_ACT_ACROSS_PUPIL : int
Specifies the number of actuators that span the X-axis beam diameter. If
it is a whole number, the left edge of the left pixel is aligned with
the left edge of the beam, and the right edge of the right pixel with
the right edge of the beam. This determines the spacing and size of the
actuators. Should not be used when "spacing" value is specified.
XTILT, YTILT, ZTILT : float
Specify the rotation of the DM surface with respect to the wavefront plane
in degrees about the X, Y, Z axes, respectively, with the origin at the
center of the wavefront. The DM surface is interpolated and orthographically
projected onto the wavefront grid. The coordinate system assumes that
the wavefront and initial DM surface are in the X,Y plane with a lower
left origin with Z towards the observer. The rotations are left handed.
The default rotation order is X, Y, then Z unless the /ZYX switch is set.
XYZ or ZYX : bool
Specifies the rotation order if two or more of XTILT, YTILT, or ZTILT
are specified. The default is /XYZ for X, Y, then Z rotations.
inf_fn : string
specify a new influence function as a FITS file with the same header keywords as
PROPER's default influence function. Needs these values in info.PrimaryData.Keywords:
'P2PDX_M' % pixel width x (m)
'P2PDY_M' % pixel width y (m)
'C2CDX_M' % actuator pitch x (m)
'C2CDY_M' % actuator pitch y (m)
inf_sign : {+,-}
specifies the sign (+/-) of the influence function. Given as an option because
the default influence function file is positive, but positive DM actuator
commands make a negative deformation for Xinetics and BMC DMs.
Raises
------
ValueError:
User cannot specify both actuator spacing and N_ACT_ACROSS_PUPIL
ValueError:
User must specify either actuator spacing or N_ACT_ACROSS_PUPIL
"""
if "ZYX" in kwargs and "XYZ" in kwargs:
raise ValueError('PROP_DM: Error: Cannot specify both XYZ and ZYX ' +
'rotation orders. Stopping')
elif "ZYX" not in kwargs and 'XYZ' not in kwargs:
XYZ = 1 # default is rotation around X, then Y, then Z
# ZYX = 0
elif "ZYX" in kwargs:
# ZYX = 1
XYZ = 0
elif "XYZ" in kwargs:
XYZ = 1
# ZYX = 0
if "XTILT" in kwargs:
xtilt = kwargs["XTILT"]
else:
xtilt = 0.
if "YTILT" in kwargs:
ytilt = kwargs["YTILT"]
else:
ytilt = 0.
if "ZTILT" in kwargs:
ztilt = kwargs["ZTILT"]
else:
ztilt = 0.
if type(dm_z0) == str:
dm_z = proper.prop_fits_read(dm_z0) # Read DM setting from FITS file
else:
dm_z = dm_z0
if "inf_fn" in kwargs:
inf_fn = kwargs["inf_fn"]
else:
inf_fn = "influence_dm5v2.fits"
if "inf_sign" in kwargs:
if(kwargs["inf_sign"] == '+'):
sign_factor = 1.
elif(kwargs["inf_sign"] == '-'):
sign_factor = -1.
else:
sign_factor = 1.
n = proper.prop_get_gridsize(wf)
dx_surf = proper.prop_get_sampling(wf) # sampling of surface in meters
beamradius = proper.prop_get_beamradius(wf)
# Default influence function sampling is 0.1 mm, peak at (x,y)=(45,45)
# Default influence function has shape = 1x91x91. Saving it as a 2D array
# before continuing with processing
dir_path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"data")
inf = proper.prop_fits_read(os.path.join(dir_path, inf_fn))
inf = sign_factor*np.squeeze(inf)
s = inf.shape
nx_inf = s[1]
ny_inf = s[0]
xc_inf = nx_inf // 2
yc_inf = ny_inf // 2
dx_inf = 0.1e-3 # influence function spacing in meters
dx_dm_inf = 1.0e-3 # nominal spacing between DM actuators in meters
inf_mag = 10
if spacing != 0 and "N_ACT_ACROSS_PUPIL" in kwargs:
raise ValueError("PROP_DM: User cannot specify both actuator spacing" +
"and N_ACT_ACROSS_PUPIL. Stopping.")
if spacing == 0 and "N_ACT_ACROSS_PUPIL" not in kwargs:
raise ValueError("PROP_DM: User must specify either actuator spacing" +
" or N_ACT_ACROSS_PUPIL. Stopping.")
if "N_ACT_ACROSS_PUPIL" in kwargs:
dx_dm = 2. * beamradius / int(kwargs["N_ACT_ACROSS_PUPIL"])
else:
dx_dm = spacing
dx_inf = dx_inf * dx_dm / dx_dm_inf # Influence function sampling scaled
# to specified DM actuator spacing
if "FIT" in kwargs:
x = (np.arange(5, dtype=np.float64) - 2) * dx_dm
if proper.use_cubic_conv:
inf_kernel = proper.prop_cubic_conv(inf.T, x/dx_inf+xc_inf,
x/dx_inf+yc_inf, GRID=True)
else:
xygrid = np.meshgrid(x/dx_inf+xc_inf, x/dx_inf+yc_inf)
inf_kernel = map_coordinates(inf.T, xygrid, order=3,
mode="nearest")
(dm_z_commanded, dms) = proper.prop_fit_dm(dm_z, inf_kernel)
else:
dm_z_commanded = dm_z
s = dm_z.shape
nx_dm = s[1]
ny_dm = s[0]
# Create subsampled DM grid
margin = 9 * inf_mag
nx_grid = nx_dm * inf_mag + 2 * margin
ny_grid = ny_dm * inf_mag + 2 * margin
xoff_grid = margin + inf_mag/2 # pixel location of 1st actuator center in subsampled grid
yoff_grid = xoff_grid
dm_grid = np.zeros([ny_grid, nx_grid], dtype = np.float64)
x = np.arange(nx_dm, dtype=int) * int(inf_mag) + int(xoff_grid)
y = np.arange(ny_dm, dtype=int) * int(inf_mag) + int(yoff_grid)
dm_grid[np.tile(np.vstack(y), (nx_dm,)),
np.tile(x, (ny_dm, 1))] = dm_z_commanded
dm_grid = ss.fftconvolve(dm_grid, inf, mode='same')
# 3D rotate DM grid and project orthogonally onto wavefront
xdim = int(np.round(np.sqrt(2) * nx_grid * dx_inf / dx_surf)) # grid dimensions (pix) projected onto wavefront
ydim = int(np.round(np.sqrt(2) * ny_grid * dx_inf / dx_surf))
if xdim > n: xdim = n
if ydim > n: ydim = n
x = np.ones((ydim, 1), dtype=int) * ((np.arange(xdim) - xdim // 2) * dx_surf)
y = (np.ones((xdim, 1), dtype=int) * ((np.arange(ydim) - ydim // 2) * dx_surf)).T
a = xtilt * np.pi / 180
b = ytilt * np.pi / 180
g = ztilt * np.pi /180
if XYZ:
m = np.array([[cos(b)*cos(g), -cos(b)*sin(g), sin(b), 0],
[cos(a)*sin(g) + sin(a)*sin(b)*cos(g), cos(a)*cos(g)-sin(a)*sin(b)*sin(g), -sin(a)*cos(b), 0],
[sin(a)*sin(g)-cos(a)*sin(b)*cos(g), sin(a)*cos(g)+cos(a)*sin(b)*sin(g), cos(a)*cos(b), 0],
[0, 0, 0, 1] ])
else:
m = np.array([ [cos(b)*cos(g), cos(g)*sin(a)*sin(b)-cos(a)*sin(g), cos(a)*cos(g)*sin(b)+sin(a)*sin(g), 0],
[cos(b)*sin(g), cos(a)*cos(g)+sin(a)*sin(b)*sin(g), -cos(g)*sin(a)+cos(a)*sin(b)*sin(g), 0],
[-sin(b), cos(b)*sin(a), cos(a)*cos(b), 0],
[0, 0, 0, 1] ])
# Forward project a square
edge = np.array([[-1.0, -1.0, 0.0, 0.0],
[1.0, -1.0, 0.0, 0.0],
[1.0, 1.0, 0.0, 0.0],
[-1.0, 1.0, 0.0, 0.0]])
new_xyz = np.dot(edge, m)
# determine backward projection for screen-raster-to-DM-surce computation
dx_dxs = (new_xyz[0, 0] - new_xyz[1, 0]) / (edge[0, 0] - edge[1, 0])
dx_dys = (new_xyz[1, 0] - new_xyz[2, 0]) / (edge[1, 1] - edge[2, 1])
dy_dxs = (new_xyz[0, 1] - new_xyz[1, 1]) / (edge[0, 0] - edge[1, 0])
dy_dys = (new_xyz[1, 1] - new_xyz[2, 1]) / (edge[1, 1] - edge[2, 1])
xs = (x/dx_dxs - y*dx_dys/(dx_dxs*dy_dys)) / \
(1 - dy_dxs*dx_dys/(dx_dxs*dy_dys))
ys = (y/dy_dys - x*dy_dxs/(dx_dxs*dy_dys)) / \
(1 - dx_dys*dy_dxs/(dx_dxs*dy_dys))
xdm = (xs + dm_xc * dx_dm) / dx_inf + xoff_grid
ydm = (ys + dm_yc * dx_dm) / dx_inf + yoff_grid
if proper.use_cubic_conv:
grid = proper.prop_cubic_conv(dm_grid.T, xdm, ydm, GRID = False)
grid = grid.reshape([xdm.shape[1], xdm.shape[0]])
else:
grid = map_coordinates(dm_grid.T, [xdm, ydm], order=3,
mode="nearest", prefilter = True)
dmap = np.zeros([n, n], dtype=np.float64)
nx_grid, ny_grid = grid.shape
xmin, xmax = n // 2 - xdim // 2, n // 2 - xdim // 2 + nx_grid
ymin, ymax = n // 2 - ydim // 2, n // 2 - ydim // 2 + ny_grid
dmap[ymin:ymax, xmin:xmax] = grid
if "NO_APPLY" not in kwargs:
proper.prop_add_phase(wf, 2 * dmap) # convert surface to WFE
return dmap
def errormap(wf, dm_map, xshift=0., yshift=0., **kwargs):
"""Read in a surface, wavefront, or amplitude error map from a FITS file.
Map is assumed to be in meters of surface error. One (and only one) of the
MIRROR_SURFACE, WAVEFRONT, or AMPLITUDE switches must be specified in order
to properly apply the map to the wavefront. For surface or wavefront error
maps, the map values are assumed to be in meters, unless the NM or MICRONS
switches are used to specify the units. The amplitude map must range
from 0 to 1. The map will be interpolated to match the current wavefront
sampling if necessary.
Parameters
----------
wf : obj
WaveFront class object
dm_map : 2D numpy array
the DM map in units of surface deformation
xshify, yshift : float
Amount to shift map (meters) in X,Y directions
Returns
-------
DMAP : numpy ndarray
Returns map (after any necessary resampling) if set.
Other Parameters
----------------
XC_MAP, YC_MAP : float
Pixel coordinates of map center (Assumed n/2,n/2)
SAMPLING : float
Sampling of map in meters
ROTATEMAP : float
Degrees counter-clockwise to rotate map, after any resampling and
shifting
MULTIPLY : float
Multiplies the map by the specified factor
MAGNIFY : float
Spatially magnify the map by a factor of "constant" from its default
size; do not use if SAMPLING is specified
MIRROR_SURFACE : bool
Indicates file contains a mirror surface height error map; It assumes a
positive value indicates a surface point higher than the mean surface.
The map will be multiplied by -2 to convert it to a wavefront map to
account for reflection and wavefront delay (a low region on the surface
causes a positive increase in the phase relative to the mean)
WAVEFRONT : bool
Indicates file contains a wavefront error map
AMPLITUDE : bool
Indicates file contains an amplitude error map
NM or MICRONS : bool
Indicates map values are in nanometers or microns. For surface or
wavefront maps only
Raises
------
SystemExit:
If AMPLITUDE and (NM or MICRONS) parameters are input.
SystemExit:
If NM and MICRONS parameteres are input together.
ValueError:
If map type is MIRROR_SURFACE, WAVEFRONT, or AMPLITUDE.
"""
if ("AMPLITUDE" in kwargs and kwargs["AMPLITUDE"]) \
and (("NM" in kwargs and kwargs["NM"]) \
or ("MICRONS" in kwargs and kwargs["MICRONS"])):
raise SystemExit(
"ERRORMAP: Cannot specify NM or MICRON for an amplitude map")
if ("NM" in kwargs and kwargs["NM"]) and \
("MICRONS" in kwargs and kwargs["MICRONS"]):
raise SystemExit("ERRORMAP: Cannot specify both NM and MICRONS")
if not "XC_MAP" in kwargs:
s = dm_map.shape
xc = s[
0] // 2 # center of map read-in (xc should be 25 for SCExAO DM maps)
yc = s[1] // 2
else:
xc = kwargs["XC_MAP"]
yc = kwargs["YC_MAP"]
# KD edit: try to get the dm map to apply only in regions of the beam
n = proper.prop_get_gridsize(wf) #
new_sampling = proper.prop_get_sampling(
wf) #kwargs["SAMPLING"] #*dm_map.shape[0]/npix_across_beam
if new_sampling > (kwargs["SAMPLING"] + kwargs["SAMPLING"]*.1) or \
new_sampling < (kwargs["SAMPLING"] - kwargs["SAMPLING"]*.1):
dm_map = proper.prop_resamplemap(wf, dm_map, kwargs["SAMPLING"], 0, 0)
dm_map = dm_map[n // 2:n // 2 + xc * 4, n // 2:n // 2 + xc * 4]
# print(f'User-defined samping is {kwargs["SAMPLING"]:.6f} but proper wavefront has sampling of '
# f'{new_sampling:.6f}')
warnings.warn(
f'User-defined beam ratio does not produce aperture sampling consistent with SCExAO actuator '
f'spacing. Resampling Map')
# resample dm_map to size of beam in the simulation
# grid = proper.prop_resamplemap(wf, dm_map, new_sampling, xc, yc, xshift, yshift)
dmap = np.zeros((wf.wfarr.shape[0], wf.wfarr.shape[1]))
r = dmap.shape
xrc = r[0] // 2
yrc = r[1] // 2
dmap[xrc - xc * 2:xrc + xc * 2, yrc - yc * 2:yrc + yc * 2] = dm_map
# Create mask to eliminate resampling artifacts outside of beam
if ("MASKING" in kwargs and kwargs["MASKING"]):
h, w = wf.wfarr.shape[:2]
center = (int(w / 2), int(h / 2))
radius = np.ceil(h * kwargs['BR'] / 2) #
# Making the Circular Boolean Mask
Y, X = np.mgrid[:h, :w]
dist_from_center = np.sqrt((X - center[0])**2 + (Y - center[1])**2)
inds = dist_from_center <= radius
# Applying the Mask to the dm_map
mask = np.zeros_like(dmap)
mask[inds] = 1
dmap *= mask
# Shift the center of dmap to 0,0
dmap = proper.prop_shift_center(dmap)
if kwargs['PLOT']:
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm, SymLogNorm
fig, subplot = plt.subplots(nrows=1, ncols=2, figsize=(12, 5))
ax1, ax2 = subplot.flatten()
fig.suptitle(f'RTC DM Voltage Maps')
ax1.imshow(
dm_map, norm=SymLogNorm(1e-2)
) # LogNorm(vmin=np.min(dm_map),vmax=np.max(dm_map)) SymLogNorm(1e-2)
ax1.set_title('DM Map Read In')
ax2.imshow(proper.prop_shift_center(
dmap)) # , cmap='hsv' must shift the center because
# proper assumes dmap center is 0,0, so we need to shift it back to plot properly
ax2.set_title('DM Map in Center of Proper simulated beam')
if "ROTATEMAP" in kwargs or "MAGNIFY" in kwargs:
# readmap stores map with center at (0,0), so shift
# before and after rotation
dmap = proper.prop_shift_center(dmap)
if "ROTATEMAP" in kwargs:
dmap = proper.prop_rotate(dmap,
kwargs["ROTATEMAP"],
CUBIC=-0.5,
MISSING=0.0)
if "MAGNIFY" in kwargs:
dmap = proper.prop_magnify(dmap, kwargs["MAGNIFY"], dmap.shape[0])
dmap = proper.prop_shift_center(dmap)
if ("MICRONS" in kwargs and kwargs["MICRONS"]):
dmap *= 1.e-6
if ("NM" in kwargs and kwargs["NM"]):
dmap *= 1.e-9
if "MULTIPLY" in kwargs:
dmap *= kwargs["MULTIPLY"]
i = complex(0., 1.)
if ("MIRROR_SURFACE" in kwargs and kwargs["MIRROR_SURFACE"]):
wf.wfarr *= np.exp(-4 * np.pi * i / wf.lamda * dmap) # Krist version
elif "WAVEFRONT" in kwargs:
wf.wfarr *= np.exp(2 * np.pi * i / wf.lamda * dmap)
elif "AMPLITUDE" in kwargs:
wf.wfarr *= dmap
else:
raise ValueError(
"ERRORMAP: Unspecified map type: Use MIRROR_SURFACE, WAVEFRONT, or AMPLITUDE"
)
# check1 = proper.prop_get_sampling(wf)
# print(f"\n\tErrormap Sampling\n"
# f"sampling in errormap.py is {check1 * 1e3:.4f} mm\n")
return dmap
def Hubble_frontend(empty_lamda, grid_size, PASSVALUE):
"""
propagates instantaneous complex E-field tSubaru from the primary through the AO188
AO system in loop over wavelength range
this function is called a 'prescription' by proper
uses PyPROPER3 to generate the complex E-field at the source, then propagates it through atmosphere,
then telescope, to the focal plane
the AO simulator happens here
this does not include the observation of the wavefront by the detector
:returns spectral cube at instantaneous time, sampling of the wavefront at final location
"""
# print("Propagating Broadband Wavefront Through Hubble Telescope")
# Getting Parameters-import statements weren't working--RD
passpara = PASSVALUE['params']
ap.__dict__ = passpara[0].__dict__
tp.__dict__ = passpara[1].__dict__
iop.__dict__ = passpara[2].__dict__
sp.__dict__ = passpara[3].__dict__
datacube = []
# Initialize the Wavefront in Proper
wfo = opx.Wavefronts()
wfo.initialize_proper()
########################################
# Hubble Propagation
#######################################
# Defines aperture (baffle-before primary)
wfo.loop_collection(proper.prop_circular_aperture,
**{'radius':
tp.entrance_d / 2}) # clear inside, dark outside
# Obscurations
wfo.loop_collection(opx.add_obscurations,
d_primary=tp.entrance_d,
d_secondary=tp.d_secondary,
legs_frac=0.01)
wfo.loop_collection(
proper.prop_define_entrance) # normalizes the intensity
# Test Sampling
if PASSVALUE['iter'] == 1:
initial_sampling = proper.prop_get_sampling(wfo.wf_collection[0, 0])
dprint(f"initial sampling is {initial_sampling:.4f}")
# Primary
# CPA from Effective Primary
# aber.add_aber(wfo.wf_collection, tp.entrance_d, step=PASSVALUE['iter'], lens_name='primary')
# wfo.loop_collection(opx.prop_pass_lens, tp.flen_primary, tp.flen_primary)
wfo.loop_collection(opx.prop_pass_lens, tp.flen_primary,
tp.dist_pri_second)
# Secondary
# aber.add_aber(wfo.wf_collection, tp.d_secondary, step=PASSVALUE['iter'], lens_name='second')
# # Zernike Aberrations- Low Order
# wfo.loop_collection(aber.add_zern_ab, tp.zernike_orders, tp.zernike_vals)
wfo.loop_collection(opx.prop_pass_lens, tp.flen_secondary,
tp.dist_second_focus)
########################################
# Focal Plane
# #######################################
# Converting Array of Arrays (wfo) into 3D array
# wavefront array is now (number_wavelengths x number_astro_bodies x sp.grid_size x sp.grid_size)
# prop_end moves center of the wavefront from lower left corner (Fourier space) back to the center
# ^ also takes square modulus of complex values, so gives units as intensity not field
shape = wfo.wf_collection.shape
for iw in range(shape[0]):
for io in range(shape[1]):
if sp.maskd_size != sp.grid_size:
wframes = np.zeros((sp.maskd_size, sp.maskd_size))
(wframe,
sampling) = proper.prop_end(wfo.wf_collection[iw, io],
EXTRACT=np.int(sp.maskd_size))
else:
wframes = np.zeros((sp.grid_size, sp.grid_size))
(wframe, sampling) = proper.prop_end(wfo.wf_collection[
iw, io]) # Sampling returned by proper is in m
wframes += wframe # adds 2D wavefront from all astro_bodies together into single wavefront, per wavelength
# dprint(f"sampling in focal plane at wavelength={iw} is {sampling} m")
datacube.append(
wframes) # puts each wavlength's wavefront into an array
# (number_wavelengths x sp.grid_size x sp.grid_size)
datacube = np.array(datacube)
datacube = np.roll(np.roll(datacube, tp.pix_shift[0], 1), tp.pix_shift[1],
2) # cirshift array for off-axis observing
datacube = np.abs(datacube) # get intensity from datacube
# Interpolating spectral cube from ap.n_wvl_init discreet wavelengths to ap.n_wvl_final
if ap.interp_wvl and ap.n_wvl_init > 1 and ap.n_wvl_init < ap.n_wvl_final:
wave_samps = np.linspace(0, 1, ap.n_wvl_init)
f_out = interp1d(wave_samps, datacube, axis=0)
new_heights = np.linspace(0, 1, ap.n_wvl_final)
datacube = f_out(new_heights)
print('Finished datacube at single timestep')
return datacube, sampling
def propcustom_zernikes(a, zernike_num, zernike_val, eps=0., **kwargs):
"""
Add Zernike-polynomial wavefront errors to current wavefront.
Noll ordering is used and a circular system is assumed. An arbitrary number
of Zernikes normalized for an unobscured circular region can be computed,
but only the first 22 Zernikes can be computed normalized for a
centrally-obscured region.
Parameters
----------
a : object
WaveFront class object
zernike_num : numpy ndarray
Scalar or 1D array specifying which Zernike polynomials to include
zernike_val : numpy ndarray
Scalar or 1D array containing Zernike coefficients (in meters of RMS
wavefront phase error or dimensionless RMS amplitude error) for Zernike
polynomials indexed by "zernike_num".
eps : float
Central obscuration ratio (0.0-1.0); default is 0.0
Returns
-------
None
Adds wavefront errors to current wavefront array
dmap : numpy ndarray
Aberration map
Other Parameters
----------------
AMPLITUDE : bool
Optional keyword that specifies that the Zernike values in "zernike_val"
represent the wavefront RMS amplitude (rather than phase) variation.
The current wavefront will be multipled by the generated map.
NAME : str
String containing name of surface that will be printed when executed.
NO_APPLY : bool
If set, the aberration map will be generated but will not be applied to
the wavefront. This is useful if you just want to generate a map for
your own use and modification (e.g. to create an error map for a multi-
segmented system, each with its own aberration map).
RADIUS : float
Optional keyword specifying the radius to which the Zernike polynomials
are normalized. If not specified, the pilot beam radius is used.
CENTERING : str
String containing the centering of the array. "interpixel" centers the
array between pixels. Any other value gives pixel centering.
Raises
------
ValueError:
Maximum index for an obscured Zernike polynomial is 22
Notes
-----
The user specifies 1D arrays containing the Zernike polynomial coefficient
indicies, the respective coefficients, and if an obstructed circular aperture
the central obscuration ratio. A wavefront error map will be generated and
added to the current wavefront.
Zernike index and corresponding aberration for 1st 22 zernikes
1 : Piston
2 : X tilt
3 : Y tilt
4 : Focus
5 : 45 degree astigmatism
6 : 0 degree astigmatism
7 : Y coma
8 : X coma
9 : Y clover (trefoil)
10 : X clover (trefoil)
11 : 3rd order spherical
12 : 5th order 0 degree astig
13 : 5th order 45 degree astig
14 : X quadrafoil
15 : Y quadrafoil
16 : 5th order X coma
17 : 5th order Y coma
18 : 5th order X clover
19 : 5th order Y clover
20 : X pentafoil
21 : Y pentafoil
22 : 5th order spherical
Update - JEK - Fixed use of ** instead of ** in obscured Zernikes
Update - AR - Added CENTERING as keyword
"""
zernike_num = np.asarray(zernike_num)
zernike_val = np.asarray(zernike_val)
n = proper.n
if proper.print_it and not ("NO_APPLY" in kwargs and kwargs["NO_APPLY"]):
if "NAME" in kwargs:
print("Applying aberrations at %s" % kwargs["NAME"])
else:
print("Applying aberrations")
max_z = zernike_num.max()
if eps != 0. and max_z > 22:
raise ValueError("PROP_ZERNIKES: Maximum index for an obscured Zernike polynomial is 22.")
dmap = np.zeros([n, n], dtype=np.float64)
if "RADIUS" not in kwargs:
beam_radius = proper.prop_get_beamradius(a)
else:
beam_radius = kwargs["RADIUS"]
dx = proper.prop_get_sampling(a) / beam_radius
x_offset = 0.
y_offset = 0.
if("CENTERING" in kwargs):
if kwargs["CENTERING"] not in _VALID_CENTERING:
raise ValueError(_CENTERING_ERR)
# Shift by half pixel
if('interpixel' in kwargs["CENTERING"]):
x_offset = dx/2.
y_offset = dx/2.
x = (np.arange(n, dtype=np.float64) - n//2) * dx + x_offset
# x_pow_2 = x**2
if (eps == 0.):
# get list of executable equations defining Zernike polynomials
zlist, maxrp, maxtc = proper.prop_noll_zernikes(max_z, COMPACT=True,
EXTRA_VALUES=True)
for j in range(n):
ab = np.zeros(n, dtype=np.float64)
y = (j - n//2) * dx + y_offset
r = np.sqrt(x**2 + y**2)
t = np.arctan2(y, x)
# predefine r**power, cos(const*theta), sin(const*theta) vectors
for i in range(2, maxrp+1):
rps = str(i).strip()
cmd = "r_pow_" + rps + " = r**i"
exec(cmd)
for i in range(1, maxtc+1):
tcs = str(i).strip()
cmd = "cos" + tcs + "t = np.cos(i*t)"
exec(cmd)
cmd = "sin" + tcs + "t = np.sin(i*t)"
exec(cmd)
# assemble aberrations
for iz in range(zernike_num.size):
tmp = eval(zlist[zernike_num[iz]])
ab += zernike_val[iz] * tmp
dmap[j, :] += ab
else:
for j in range(n):
y = (j-n//2) * dx + y_offset
r = np.sqrt(x**2 + y**2)
r2 = r**2
r3 = r**3
r4 = r**4
r5 = r**5
t = np.arctan2(y, x)
for iz in range(len(zernike_num)):
if zernike_num[iz] == 1:
ab = 1.
elif zernike_num[iz] == 2:
ab = (2*r*np.cos(t))/np.sqrt(1 + eps**2)
elif zernike_num[iz] == 3:
ab = (2*r*np.sin(t))/np.sqrt(1 + eps**2)
elif zernike_num[iz] == 4:
ab = (np.sqrt(3)*(1 + eps**2 - 2*r2))/(-1 + eps**2)
elif zernike_num[iz] == 5:
ab = (np.sqrt(6)*r2*np.sin(2*t))/np.sqrt(1 + eps**2 + eps**4)
elif zernike_num[iz] == 6:
ab = (np.sqrt(6)*r2*np.cos(2*t))/np.sqrt(1 + eps**2 + eps**4)
elif zernike_num[iz] == 7:
ab = (2*np.sqrt(2)*r*(2 + 2*eps**4 - 3*r2 + eps**2*(2 - 3*r2))*np.sin(t))/((-1 + eps**2)*np.sqrt(1 + 5*eps**2 + 5*eps**4 + eps**6))
elif zernike_num[iz] == 8:
ab = (2*np.sqrt(2)*r*(2 + 2*eps**4 - 3*r2 + eps**2*(2 - 3*r2))*np.cos(t))/((-1 + eps**2)*np.sqrt(1 + 5*eps**2 + 5*eps**4 + eps**6))
elif zernike_num[iz] == 9:
ab = (2*np.sqrt(2)*r3*np.sin(3*t))/np.sqrt(1 + eps**2 + eps**4 + eps**6)
elif zernike_num[iz] == 10:
ab = (2*np.sqrt(2)*r3*np.cos(3*t))/np.sqrt(1 + eps**2 + eps**4 + eps**6)
elif zernike_num[iz] == 11:
ab = (np.sqrt(5)*(1 + eps**4 - 6*r2 + 6*r4 + eps**2*(4 - 6*r2)))/ (-1 + eps**2)**2
elif zernike_num[iz] == 12:
ab = (np.sqrt(10)*r2*(3 + 3*eps**6 - 4*r2 + eps**2*(3 - 4*r2) + eps**4*(3 - 4*r2))*np.cos(2*t))/ ((-1 + eps**2)*np.sqrt((1 + eps**2 + eps**4)*(1 + 4*eps**2 + 10*eps**4 + 4*eps**6 + eps**8)))
elif zernike_num[iz] == 13:
ab = (np.sqrt(10)*r2*(3 + 3*eps**6 - 4*r2 + eps**2*(3 - 4*r2) + eps**4*(3 - 4*r2))*np.sin(2*t))/ ((-1 + eps**2)*np.sqrt((1 + eps**2 + eps**4)*(1 + 4*eps**2 + 10*eps**4 + 4*eps**6 + eps**8)))
elif zernike_num[iz] == 14:
ab = (np.sqrt(10)*r4*np.cos(4*t))/np.sqrt(1 + eps**2 + eps**4 + eps**6 + eps**8)
elif zernike_num[iz] == 15:
ab = (np.sqrt(10)*r4*np.sin(4*t))/np.sqrt(1 + eps**2 + eps**4 + eps**6 + eps**8)
elif zernike_num[iz] == 16:
ab = (2*np.sqrt(3)*r*(3 + 3*eps**8 - 12*r2 + 10*r4 - 12*eps**6*(-1 + r2) + 2*eps**4*(15 - 24*r2 + 5*r4) + 4*eps**2*(3 - 12*r2 + 10*r4))*np.cos(t))/((-1 + eps**2)**2*np.sqrt((1 + 4*eps**2 + eps**4)* (1 + 9*eps**2 + 9*eps**4 + eps**6)))
elif zernike_num[iz] == 17:
ab = (2*np.sqrt(3)*r*(3 + 3*eps**8 - 12*r2 + 10*r4 - 12*eps**6*(-1 + r2) + 2*eps**4*(15 - 24*r2 + 5*r4) + 4*eps**2*(3 - 12*r2 + 10*r4))*np.sin(t))/((-1 + eps**2)**2*np.sqrt((1 + 4*eps**2 + eps**4)* (1 + 9*eps**2 + 9*eps**4 + eps**6)))
elif zernike_num[iz] == 18:
ab = (2*np.sqrt(3)*r3*(4 + 4*eps**8 - 5*r2 + eps**2*(4 - 5*r2) + eps**4*(4 - 5*r2) + eps**6*(4 - 5*r2))*np.cos(3*t))/ ((-1 + eps**2)*np.sqrt((1 + eps**2 + eps**4 + eps**6)*(1 + 4*eps**2 + 10*eps**4 + 20*eps**6 + 10*eps**8 + 4*eps**10 + eps**12)))
elif zernike_num[iz] == 19:
ab = (2*np.sqrt(3)*r3*(4 + 4*eps**8 - 5*r2 + eps**2*(4 - 5*r2) + eps**4*(4 - 5*r2) + eps**6*(4 - 5*r2))*np.sin(3*t))/ ((-1 + eps**2)*np.sqrt((1 + eps**2 + eps**4 + eps**6)*(1 + 4*eps**2 + 10*eps**4 + 20*eps**6 + 10*eps**8 + 4*eps**10 + eps**12)))
elif zernike_num[iz] == 20:
ab = (2*np.sqrt(3)*r5*np.cos(5*t))/ np.sqrt(1 + eps**2 + eps**4 + eps**6 + eps**8 + eps**10)
elif zernike_num[iz] == 21:
ab = (2*np.sqrt(3)*r5*np.sin(5*t))/ np.sqrt(1 + eps**2 + eps**4 + eps**6 + eps**8 + eps**10)
elif zernike_num[iz] == 22:
ab = (np.sqrt(7)*(1 + eps**6 - 12*r2 + 30*r4 - 20*r**6 + eps**4*(9 - 12*r2) + eps**2*(9 - 36*r2 + 30*r4)))/ (-1 + eps**2)**3
dmap[j, :] += zernike_val[iz] * ab
if not ("NO_APPLY" in kwargs and kwargs["NO_APPLY"]):
if ("AMPLITUDE" in kwargs and kwargs["AMPLITUDE"]):
a.wfarr *= proper.prop_shift_center(dmap)
else:
i = complex(0, 1)
a.wfarr *= np.exp(i*2*np.pi/a.lamda*proper.prop_shift_center(dmap))
return dmap
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 adaptive_optics(wfo, iwf, iw, f_lens, beam_ratio, iter):
# print 'Including Adaptive Optics'
# PSF = proper.prop_shift_center(np.abs(wfo.wfarr)**2)
# quicklook_im(obj_map, logAmp=False)
# code to distort measured phase map goes here....
# print 'add code to distort phase measurment'
nact = tp.ao_act #49 # number of DM actuators along one axis
nact_across_pupil = nact - 2 #/1.075#nact #47 # number of DM actuators across pupil
dm_xc = (nact / 2) - 0.5 #-1#0.5#- 0.5
dm_yc = (nact / 2) - 0.5 #-1#0.5#- 0.5
d_beam = 2 * proper.prop_get_beamradius(wfo) # beam diameter
# dprint((d_beam, d_beam/nact_across_pupil))
act_spacing = d_beam / (nact_across_pupil) # actuator spacing
map_spacing = proper.prop_get_sampling(wfo) # map sampling
# have passed through focus, so pupil has rotated 180 deg;
# need to rotate error map (also need to shift due to the way
# the rotate() function operates to recenter map)
# obj_map = np.roll(np.roll(np.rot90(obj_map, 2), 1, 0), 1, 1)
# obj_map = np.roll(obj_map, 1, -1)
# quicklook_im(obj_map[45:83,45:83], logAmp=False, show=False)
# plt.figure()
# plt.plot(range(44, 84), obj_map[64, 44:84])
# print map_spacing
# interpolate map to match number of DM actuators
# print map_spacing/act_spacing
# print 'Interpolation boundary uncertainty is likely because of beam ratio causing a non-integer'
# print '128*0.3 ~ 38 so thats what is being used for now. Needs some T.L.C.'
# true_width = tp.grid_size*beam_ratio
# width = int(np.ceil(true_width))
# # width = int(np.ceil(tp.grid_size*beam_ratio))
# if width%2 != 0:
# width += 1
# exten = width/true_width
# print exten
# mid = int(tp.grid_size/2.)
# lower = int(mid-width/2.)
# upper = int(mid+width/2.)
# print width, mid, lower, upper
# #
# # f= interpolate.interp2d(range(width+1), range(width+1), obj_map[lower:upper, lower:upper])
# # dm_map = f(np.linspace(0,width+1,nact),np.linspace(0,width+1,nact))
#
# import skimage.transform
# dm_map = skimage.transform.resize(obj_map[lower:upper, lower:upper], (nact,nact))
# print map_spacing, act_spacing, map_spacing/act_spacing
try:
with open(iop.CPA_meas, 'rb') as handle:
CPA_maps, iters = pickle.load(handle)
except EOFError:
print 'CPA file not ready?'
import time
time.sleep(10)
with open(iop.CPA_meas, 'rb') as handle:
CPA_maps, iters = pickle.load(handle)
# loop_frames(CPA_maps, logAmp=False)
if iwf[:9] == 'companion':
CPA_map = CPA_maps[1, iw]
else:
CPA_map = CPA_maps[0, iw]
# loop_frames(CPA_maps, logAmp=False)
# quicklook_im(CPA_map, logAmp=False)
# dprint((map_spacing, act_spacing, map_spacing/act_spacing))
# dm_map = proper.prop_magnify(CPA_map, map_spacing/act_spacing, nact)
dm_map = CPA_map[tp.grid_size / 2 -
(beam_ratio * tp.grid_size / 2):tp.grid_size / 2 +
(beam_ratio * tp.grid_size / 2) + 1, tp.grid_size / 2 -
(beam_ratio * tp.grid_size / 2):tp.grid_size / 2 +
(beam_ratio * tp.grid_size / 2) + 1]
f = interpolate.interp2d(range(dm_map.shape[0]), range(dm_map.shape[0]),
dm_map)
dm_map = f(np.linspace(0, dm_map.shape[0], nact),
np.linspace(0, dm_map.shape[0], nact))
# quicklook_im(dm_map, logAmp=False, show=True)
dm_map = -dm_map * proper.prop_get_wavelength(wfo) / (4 * np.pi
) #<--- here
# dm_map = -dm_map * proper.prop_get_wavelength(wfo) / (2 * np.pi)
# dm_map = np.zeros((65,65))
# quicklook_im(dm_map, logAmp=False, show=True, colormap='jet')
# if tp.piston_error:
# mean_dm_map = np.mean(np.abs(dm_map))
# var = mean_dm_map/200.#40.
# print var
# # var = 0.001#1e-11
# if var != 0.0:
# dm_map = dm_map + np.random.normal(0, var, (dm_map.shape[0], dm_map.shape[1]))
# quicklook_im(dm_map, logAmp=False, show=True, colormap='jet')
# plt.figure()
# quicklook_wf(wfo)
# plt.plot(np.linspace(44, 84, nact),dm_map[16])
# plt.figure()
# quicklook_im( obj_map[lower:upper, lower:upper], logAmp=False, show=True)
# act_spacing /= 0.625
# print act_spacing, proper.prop_get_beamradius(wfo)
# Need to put on opposite pattern; convert wavefront error to surface height
# plt.plot(range(44,84), proper.prop_get_phase(wfo)[64, 44:84])
# proper.prop_add_phase(wfo, waffle)
# quicklook_im(dm_map)
if tp.active_null:
with open(iop.NCPA_meas, 'rb') as handle:
_, null_map, _ = pickle.load(handle)
# dprint('null_map')
# quicklook_im(null_map, logAmp=False)
# dm_NCPA = -proper.prop_magnify(NCPA_map, map_spacing / act_spacing, nact)
dm_NCPA = null_map * proper.prop_get_wavelength(wfo) / (4 * np.pi)
# quicklook_im(dm_map, logAmp=False)
dm_map += dm_NCPA
# quicklook_im(dm_map, logAmp=False, show=True, colormap ='jet')
# dm_map /= 2
# if tp.speckle_kill:
# with open(iop.NCPA_meas, 'rb') as handle:
# Imaps, NCPA_map,_ = pickle.load(handle)
# quicklook_im(NCPA_map, logAmp=False)
# loop_frames(Imaps+1e-9, logAmp=True)
# with open(iop.NCPA_meas, 'rb') as handle:
# _, NCPA_map,_ = pickle.load(handle)
# quicklook_im(NCPA_map, logAmp=False)
#
# dm_NCPA = -proper.prop_magnify(NCPA_map, map_spacing / act_spacing, nact)
# dm_NCPA = dm_NCPA*proper.prop_get_wavelength(wfo)/(4*np.pi)
#
# # quicklook_im(dm_map, logAmp=False)
# dm_map = dm_NCPA
if tp.active_modulate and iter >= 8:
# import dm_functions as DM
# # speck.generate_flatmap(phase)
# s_amp = DM.amplitudemodel(0.05, 30, c=1.6)
# tp.null_ao_act = tp.ao_act
# xloc, yloc = 4, 0
# # rotate_angle = iter%30 * 360/30
# # rotate_angle = np.pi * rotate_angle / 180.
# # rot_matrix = [[np.cos(rotate_angle), -np.sin(rotate_angle)], [np.sin(rotate_angle), np.cos(rotate_angle)]]
# # xloc, yloc = np.matmul(rot_matrix, [xloc, yloc])
#
# phase = iter % 10 * 2 * np.pi / 10.
# s_amp = iter % 5 * s_amp/ 5.
# print xloc, yloc, phase
# waffle = DM.make_speckle_kxy(xloc, yloc, s_amp, phase) / 1e6
# waffle += DM.make_speckle_kxy(yloc, xloc, s_amp, -phase) / 1e6
# waffle += DM.make_speckle_kxy(0.71 * xloc, 0.71 * xloc, s_amp, -phase) / 1e6
# waffle += DM.make_speckle_kxy(0.71 * xloc, -0.71 * xloc, s_amp, -phase) / 1e6
# waffle /= 4
# # quicklook_im(waffle, logAmp=False)
# # print dm_map.shape
# # print waffle.shape
#
# dmap =proper.prop_dm(wfo, waffle, dm_xc, dm_yc, N_ACT_ACROSS_PUPIL=nact, FIT = True)
# dm_map = -dm_map * proper.prop_get_wavelength(wfo) / (4 * np.pi * 5) * (iter % 10 - 5)
print 1 / 5. * (iter % 10 - 5)
dm_map = dm_map / 5. * (iter % 10 - 5)
# dmap = proper.prop_dm(wfo, pattern, dm_xc, dm_yc,
# N_ACT_ACROSS_PUPIL=nact, FIT=True)
# quicklook_wf(wfo)
# quicklook_wf(wfo)
# dmap =proper.prop_dm(wfo, dm_map, dm_xc, dm_yc, N_ACT_ACROSS_PUPIL=nact, FIT = True) #<-- here
dmap = proper.prop_dm(wfo, dm_map, dm_xc, dm_yc, act_spacing,
FIT=True) #<-- here
# quicklook_im(dmap, logAmp=False, show=True)
# quicklook_im(CPA_map*proper.prop_get_wavelength(wfo)/(4*np.pi), logAmp=False)
# quicklook_im(CPA_map*proper.prop_get_wavelength(wfo)/(4*np.pi) + dmap, logAmp=False, show=True)
# # # There's a boundary effect that needs to be mitigated
# phase_map = proper.prop_get_phase(wfo)
# artefacts = np.abs(phase_map) > 1
# # print np.shape(artefacts), np.shape(phase_map)
# # quicklook_im(phase_map, logAmp=False)
#
# width = round(tp.grid_size*beam_ratio)
# mid = int(tp.grid_size/2.)
# lower = int(mid-width/2.)
# upper = int(mid+width/2.)
# mask = np.zeros((tp.grid_size, tp.grid_size))
# mask[upper,:] = 1
# mask[:, upper] = 1
# mask[lower,:] = 1
# mask[:,lower] = 1
# mask = mask*artefacts
#
# # print width, upper
#
# # wfo.wfarr[upper] = phase_map[tp.grid_size/2,tp.grid_size/2]
# # quicklook_im( phase_map*mask, logAmp=False)
#
# proper.prop_add_phase(wfo,-phase_map*mask*proper.prop_get_wavelength(wfo)/(2*np.pi))
# quicklook_IQ(wfo)
# I = np.real(wfo.wfarr)
# Q = np.imag(wfo.wfarr)
# I = proper.prop_shift_center(I)
# Q = proper.prop_shift_center(Q)
# Q[89] = 0
# Q[:,89] = 0
# # Q[39] = 0
# # Q[:,39] = 0
# I = proper.prop_shift_center(I)
# Q = proper.prop_shift_center(Q)
# wfo.wfarr = I+1j*Q
# quicklook_wf(wfo)
# quicklook_IQ(wfo)
# print phase_map[artefacts]
# plt.imshow(phase_map)
# # plt.figure()
# # plt.imshow(dmap)
# #
# plt.show()
# #
# proper.prop_propagate(wfo, f_lens, "coronagraph lens")
# quicklook_wf(wfo)
return
def coronagraph(wfo, f_lens, occulter_type, occult_loc, diam):
# proper.prop_lens(wfo, f_lens, "coronagraph imaging lens")
# proper.prop_propagate(wfo, f_lens, "occulter")
# quicklook_wf(wfo)
# occulter sizes are specified here in units of lambda/diameter;
# convert lambda/diam to radians then to meters
lamda = proper.prop_get_wavelength(wfo)
# print lamda
occrad = 3 # 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
# print occrad_m, occulter_type
# print 'line 22.', occulter_type
#plt.figure(figsize=(12,8))
# quicklook_wf(wfo)
if occulter_type == "Gaussian":
r = proper.prop_radius(wfo)
h = np.sqrt(-0.5 * occrad_m**2 / np.log(1 - np.sqrt(0.5))) #*0.8
gauss_spot = 1 - np.exp(-0.5 * (r / h)**2)
# print occult_loc
# gauss_spot = np.roll(gauss_spot,occult_loc,(0,1))
gauss_spot = shift(gauss_spot, shift=occult_loc, mode='wrap')
proper.prop_multiply(wfo, gauss_spot)
# quicklook_wf(wfo)
#plt.suptitle("Gaussian spot", fontsize = 18)
elif occulter_type == "Solid":
proper.prop_circular_obscuration(wfo, occrad_m * 4. / 3)
#plt.suptitle("Solid spot", fontsize = 18)
# quicklook_wf(wfo)
elif occulter_type == "8th_Order":
proper.prop_8th_order_mask(wfo, occrad * 3. / 4., CIRCULAR=True)
# quicklook_wf(wfo)
elif occulter_type == 'Vortex':
# print('lol')
# apodization(wfo, True)
vortex(wfo)
# lyotstop(wfo, True)
#plt.suptitle("8th order band limited spot", fontsize = 18)
# quicklook_wf(wfo, logAmp=False, show=True)
# 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")
# plt.show()
# quicklook_wf(wfo)
proper.prop_propagate(wfo, f_lens, "pupil reimaging lens")
# quicklook_wf(wfo)
proper.prop_lens(wfo, f_lens, "pupil reimaging lens")
# quicklook_wf(wfo)
proper.prop_propagate(wfo, 2 * f_lens, "lyot stop")
# quicklook_wf(wfo)
# from numpy.fft import fft2, ifft2
# wfo.wfarr = fft2(wfo.wfarr) #/ np.size(wfo.wfarr)
# quicklook_wf(wfo)
# 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()
# quicklook_wf(wfo,logAmp=False, show=True)
if occulter_type == "Gaussian":
# quicklook_wf(wfo)
proper.prop_circular_aperture(wfo, 0.75, NORM=True)
elif occulter_type == "Solid":
# quicklook_wf(wfo)
proper.prop_circular_aperture(wfo, 0.84, NORM=True)
elif occulter_type == "8th_Order":
# quicklook_wf(wfo)
proper.prop_circular_aperture(wfo, 0.75, NORM=True) #0.5
elif occulter_type == "Vortex":
# proper.prop_circular_aperture(wfo, 0.98, NORM = True) #0.5
lyotstop(wfo, True)
# quicklook_wf(wfo)
elif occulter_type == "None (Lyot Stop)":
proper.prop_circular_aperture(wfo, 0.8, NORM=True)
proper.prop_propagate(wfo, f_lens, "reimaging lens")
# errs = np.sqrt(proper.prop_get_amplitude(wfo))
# # plt.figure()
# # plt.imshow(errs)
# # plt.show()
# quicklook_wf(wfo)
proper.prop_lens(wfo, f_lens, "reimaging lens")
# quicklook_wf(wfo)
proper.prop_propagate(wfo, f_lens, "final focus")
# from numpy.fft import fft2, ifft2
# wfo.wfarr = fft2(wfo.wfarr) / np.size(wfo.wfarr)
# quicklook_wf(wfo)
return
