def quicklook_IQ(wfo, logAmp=False, show=True):
I = np.real(wfo.wfarr)
Q = np.imag(wfo.wfarr)
print(np.sum(I), np.sum(Q))
I = proper.prop_shift_center(I)
Q = proper.prop_shift_center(Q)
fig = plt.figure(figsize=(14, 10))
ax1 = plt.subplot2grid((3, 2), (0, 0), rowspan=2)
ax2 = plt.subplot2grid((3, 2), (0, 1), rowspan=2)
ax3 = plt.subplot2grid((3, 2), (2, 0))
ax4 = plt.subplot2grid((3, 2), (2, 1))
if logAmp:
ax1.imshow(I, origin='lower', cmap="YlGnBu_r", norm=LogNorm())
else:
ax1.imshow(I, origin='lower', cmap="YlGnBu_r")
ax2.imshow(Q, origin='lower', cmap="YlGnBu_r") # , vmin=-0.5, vmax=0.5)
ax3.plot(I[int(tp.grid_size / 2)])
ax3.plot(np.sum(np.eye(tp.grid_size) * I, axis=1))
# plt.plot(np.sum(after_dm,axis=1)/after_dm[128,128])
ax4.plot(Q[int(tp.grid_size / 2)])
# ax4.plot(np.sum(np.eye(tp.grid_size)*phase_afterdm,axis=1))
plt.xlim([0, proper.prop_get_gridsize(wfo)])
fig.set_tight_layout(True)
if show == True:
plt.show()
def rotate_atmos(wf, atmos_map):
time = float(atmos_map[-19:-11])
rotate_angle = tp.rot_rate * time
# print rotate_angle, 'rotate'
# quicklook_wf(wf)
wf.wfarr = proper.prop_shift_center(wf.wfarr)
wf.wfarr = proper.prop_rotate(wf.wfarr, rotate_angle)
wf.wfarr = proper.prop_shift_center(wf.wfarr)
def circular_apodization(wf, radius, t_in, t_out, xc = 0.0, yc = 0.0, **kwargs):
if ("NORM" in kwargs and kwargs["NORM"]):
norm = True
else:
norm = False
if (t_in > t_out):
apodizer = proper.prop_shift_center(proper.prop_ellipse(wf, radius, radius, xc, yc, NORM = norm))*(t_in-t_out)+t_out
else:
apodizer = proper.prop_shift_center(proper.prop_ellipse(wf, radius, radius, xc, yc, NORM = norm))*(t_out-t_in)+t_in
return apodizer
def build_phase_map(wf, phase_error):
"""Add a phase error map or value to the current wavefront array.
The phase error array is assumed to be at the same sampling as the current
wavefront. Note that this is wavefront, not surface error.
Parameters
----------
wf : object
WaveFront class object
phase_error : numpy ndarray
A scalar or 2D image containing the phase error in meters
Returns
-------
None
"""
i = complex(0., 1.)
if type(phase_error) != np.ndarray and type(phase_error) != list:
phase_error = float(phase_error)
phase_map = np.exp(2 * np.pi * i / wf.lamda * phase_error)
else:
phase_error = np.asarray(phase_error)
phase_map = np.exp(2 * np.pi * i / wf.lamda *
proper.prop_shift_center(phase_error))
return phase_map
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 piston_refbeam(wf, iter, w):
beam_ratio = 0.7 * tp.band[0] / w * 1e-9
wf_ref = proper.prop_begin(tp.diam, w, tp.grid_size, beam_ratio)
proper.prop_define_entrance(wf_ref)
phase_mod = iter % 4 * w / 4 #np.pi/2
obj_map = np.ones((tp.grid_size, tp.grid_size)) * phase_mod
proper.prop_add_phase(wf_ref, obj_map)
wf_ref.wfarr = wf.wfarr + wf_ref.wfarr
Imap = proper.prop_shift_center(np.abs(wf_ref.wfarr)**2)
return Imap
def apodize_pupil(wf):
phase_map = proper.prop_get_phase(wf)
amp_map = proper.prop_get_amplitude(wf)
h, w = wf.wfarr.shape[:2]
wavelength = wf.lamda
scale = ap.wvl_range[0] / wavelength
inds = circular_mask(h, w, radius=scale * 0.95 * h * sp.beam_ratio / 2) #TO DO remove hardcoded sizing, especially if use is default
mask = np.zeros_like(phase_map)
mask[inds] = 1
smooth_mask = gaussian_filter(mask, 1.5, mode='nearest') #TO DO remove hardcoded sizing, especially if use is default
smoothed = phase_map * smooth_mask
wf.wfarr = proper.prop_shift_center(amp_map * np.cos(smoothed) + 1j * amp_map * np.sin(smoothed))
def save_pix_IQ(wf, plot=False):
with open(iop.IQpixel, 'a') as the_file:
complex_map = proper.prop_shift_center(wf.wfarr)
pix0 = complex_map[64, 64]
pix1 = complex_map[100, 100]
the_file.write('%f, %f, %f, %f\n' % (np.real(pix0), np.imag(pix0), np.real(pix1), np.imag(pix1)))
if plot:
quicklook_im(np.real(complex_map))
quicklook_wf(wf, show=True)
quicklook_IQ(wf, show=True)
def circularise(prim_map):
x = np.linspace(-1, 1, 128) * np.ones((128, 128))
y = np.transpose(np.linspace(-1, 1, 128) * np.ones((128, 128)))
circ_map = np.zeros((2, 128, 128))
circ_map[0] = x * np.sqrt(1 - (y**2 / 2.))
circ_map[1] = y * np.sqrt(1 - (x**2 / 2.))
circ_map *= 64
new_prim = np.zeros((128, 128))
for x in range(128):
for y in range(128):
ix = circ_map[0][x, y]
iy = circ_map[1][x, y]
new_prim[ix, iy] = prim_map[x, y]
new_prim = proper.prop_shift_center(new_prim)
new_prim = np.transpose(new_prim)
# quicklook_im(new_prim, logAmp=False, colormap="jet")
return new_prim
def build_prop_rectangular_obscuration(wf, width, height, xc = 0.0, yc = 0.0, **kwargs):
"""Multiply the current wavefront by a rectangular obscuration.
Parameters
----------
wf : obj
WaveFront class object
width, height : float
X and Y widths of the obscuration in meters (unless the norm switch is
specified, in which case these are normalized to the beam diameter)
xc, yc : float
Center of obscuration relative to the center of the beam in meters
(unless norm is specified, in which case they are normalized relative
to the beam radius; the default is (0,0)
Returns
-------
None
Multiplies the wavefront array in "wf" object by a dark rectangular mask.
Other Parameters
----------------
NORM : bool
Indicates that obscuration halfwidths and center are specified relative
to the beam radius.
ROTATION : float
Degrees counter-clockwise to rotate obscuration about its center.
"""
if ("NORM" in kwargs and kwargs["NORM"]):
norm = True
else:
norm = False
if "ROTATION" in kwargs:
rotation = kwargs["ROTATION"]
else:
rotation = 0.0
return proper.prop_shift_center(proper.prop_rectangle(wf, width, height, xc, yc, NORM = norm, ROTATION = rotation, DARK = True))
def build_prop_circular_aperture(wf, radius, xc=0.0, yc=0.0, **kwargs):
"""Multiply the wavefront by a circular clear aperture.
Parameters
----------
wf : obj
WaveFront class object
radius : float
Radius of aperture in meters, unless norm is specified
xc : float
X-center of aperture relative to center of wavefront. Default is 0.0
yc : float
Y-center of aperture relative to center of wavefront. Default is 0.0
Returns
-------
numpy ndarray:
Multiplies current wavefront in wf object by a circular aperture.
Other Parameters
-----------------
NORM : bool
If set to True, the specified radius and xc, yc aperure centers are
assumed to be normalized to the current beam radius (e.g. radius is 1.0
means the aperture is the same size as the current beam). xc, yc = 0,0
is the center of the wavefront. Default is False.
"""
if ("NORM" in kwargs and kwargs["NORM"]):
norm = True
else:
norm = False
return proper.prop_shift_center(
proper.prop_ellipse(wf, radius, radius, xc, yc, NORM=norm))
def hardmask_pupil(wf):
"""
hard-edged circular mask of the pupil plane.
Masks out the WFS map outside of the beam since the DM modeled by proper can only be a square nxn grid of actuators,
and thus the influence function surrounding each DM actuator could be affecting on-beam pixels, even if the
actuator is acting on off-beam signal. In other words, even if a cornerDM actuator doesn't actuate on the beam,
if there was non-zero signal in the WFS map, it will try to act on it, and it could 'influence' nearby DM actuators
that are acting on the beam.
This hard-edged mask is different from prop_circular_aperture in that it does not anti-alias the edges of the mask
based on the 'fill factor' of the edge pixels. Instead, it has a boolean mask to zero everything > a fixed radius,
in this case determined by the grid size and beam ratio of each wavefront passed into it.
:param wf: a single wavefront
:return: nothing is returned but the wf passed into it has been masked
"""
phase_map = proper.prop_get_phase(wf)
amp_map = proper.prop_get_amplitude(wf)
# Sizing the Mask
h, w = wf.wfarr.shape[:2]
center = (int(w / 2), int(h / 2))
radius = np.floor(
sp.grid_size * wf.beam_ratio /
2) # Should scale with wavelength if sp.focused_system=False,
# np.ceil used to oversize map so don't clip the beam
# 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 Complex Array
mask = np.zeros_like(phase_map)
mask[inds] = 1
masked = phase_map * mask
wf.wfarr = proper.prop_shift_center(amp_map * np.cos(masked) +
1j * amp_map * np.sin(masked))
def readmap(wf, dmap, xshift=0, yshift=0, **kwargs):
"""Read in a surface, wavefront, or amplitude error map, scaling if necessary.
Parameters
----------
wf : obj
WaveFront class object
dmap : 2D numpy array
the DM map in units of surface deformation
xshift, yshift : float
Amount to shift map in meters in X and Y directions
Returns
-------
dmap : numpy ndarray
Returns the error map in a 2D numpy array
Other Parameters
----------------
XC_MAP, YC_MAP : float
Specifies center pixel of map (default is n/2)
SAMPLING : float
Specifies sampling of map in meters (will override any sampling
specified in the file header; must be specified if header does not
specify sampling using the PIXSIZE value)
Raises
------
ValueError:
if pixsize keyword does not exist in FITS image header
Notes
-----
(a) The sampling is not returned in this variable
(b) if the header value RADPIX is specified (the radius of the beam in the
map in pixels), then this will override any other sampling specifiers,
either in the header or using SAMPLING.
(c) Intended for internal use by PROP routines. Users should call either
prop_errormap or prop_psd_errormap.
"""
# if the radius of the beam (in pixels) in the map is specified in the
# header, this will override any other sampling specifications, either from
# the header (PIXSIZE value) or procedure call (SAMPLING keyword)
pixsize = kwargs["SAMPLING"]
if not "XC_MAP" in kwargs:
s = dmap.shape
xc = s[0] // 2
yc = s[1] // 2
else:
xc = kwargs["XC_MAP"]
yc = kwargs["YC_MAP"]
# resample map to current wavefront grid spacing
dmap = proper.prop_resamplemap(wf, dmap, pixsize, xc, yc, xshift, yshift)
dmap = proper.prop_shift_center(dmap)
return dmap
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 occulter(self, wf):
n = int(proper.prop_get_gridsize(wf))
ofst = 0 # no offset
ramp_sign = 1 # sign of charge is positive
ramp_oversamp = 11. # vortex is oversampled for a better discretization
# f_lens = tp.f_lens #conf['F_LENS']
# diam = tp.diam#conf['DIAM']
charge = 2 #conf['CHARGE']
pixelsize = 5 #conf['PIXEL_SCALE']
Debug_print = False #conf['DEBUG_PRINT']
coron_temp = os.path.join(iop.testdir, 'coron_maps/')
if not os.path.exists(coron_temp):
os.mkdir(coron_temp)
if charge != 0:
wavelength = proper.prop_get_wavelength(wf)
gridsize = proper.prop_get_gridsize(wf)
beam_ratio = pixelsize * 4.85e-9 / (wavelength / tp.entrance_d)
# dprint((wavelength,gridsize,beam_ratio))
calib = str(charge) + str('_') + str(int(
beam_ratio * 100)) + str('_') + str(gridsize)
my_file = str(coron_temp + 'zz_perf_' + calib + '_r.fits')
if (os.path.isfile(my_file) == True):
if (Debug_print == True):
print("Charge ", charge)
vvc = self.readfield(
coron_temp,
'zz_vvc_' + calib) # read the theoretical vortex field
vvc = proper.prop_shift_center(vvc)
scale_psf = wf._wfarr[0, 0]
psf_num = self.readfield(coron_temp, 'zz_psf_' +
calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = self.readfield(
coron_temp,
'zz_perf_' + calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wf._wfarr = (
wf._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
else: # CAL==1: # create the vortex for a perfectly circular pupil
if (Debug_print == True):
dprint(f"Vortex Charge= {charge}")
f_lens = 200.0 * tp.entrance_d
wf1 = proper.prop_begin(tp.entrance_d, wavelength, gridsize,
beam_ratio)
proper.prop_circular_aperture(wf1, tp.entrance_d / 2)
proper.prop_define_entrance(wf1)
proper.prop_propagate(wf1, f_lens,
'inizio') # propagate wavefront
proper.prop_lens(
wf1, f_lens,
'focusing lens vortex') # propagate through a lens
proper.prop_propagate(wf1, f_lens, 'VC') # propagate wavefront
self.writefield(coron_temp, 'zz_psf_' + calib,
wf1.wfarr) # write the pre-vortex field
nramp = int(n * ramp_oversamp) # oversamp
# create the vortex by creating a matrix (theta) representing the ramp (created by atan 2 gradually varying matrix, x and y)
y1 = np.ones((nramp, ), dtype=np.int)
y2 = np.arange(0, nramp,
1.) - (nramp / 2) - int(ramp_oversamp) / 2
y = np.outer(y2, y1)
x = np.transpose(y)
theta = np.arctan2(y, x)
x = 0
y = 0
vvc_tmp = np.exp(1j * (ofst + ramp_sign * charge * theta))
theta = 0
vvc_real_resampled = cv2.resize(
vvc_tmp.real, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc_imag_resampled = cv2.resize(
vvc_tmp.imag, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc = np.array(vvc_real_resampled, dtype=complex)
vvc.imag = vvc_imag_resampled
vvcphase = np.arctan2(vvc.imag,
vvc.real) # create the vortex phase
vvc_complex = np.array(np.zeros((n, n)), dtype=complex)
vvc_complex.imag = vvcphase
vvc = np.exp(vvc_complex)
vvc_tmp = 0.
self.writefield(coron_temp, 'zz_vvc_' + calib,
vvc) # write the theoretical vortex field
proper.prop_multiply(wf1, vvc)
proper.prop_propagate(wf1, f_lens, 'OAP2')
proper.prop_lens(wf1, f_lens)
proper.prop_propagate(wf1, f_lens, 'forward to Lyot Stop')
proper.prop_circular_obscuration(
wf1, 1.,
NORM=True) # null the amplitude iside the Lyot Stop
proper.prop_propagate(wf1, -f_lens) # back-propagation
proper.prop_lens(wf1, -f_lens)
proper.prop_propagate(wf1, -f_lens)
self.writefield(
coron_temp, 'zz_perf_' + calib,
wf1.wfarr) # write the perfect-result vortex field
vvc = self.readfield(coron_temp, 'zz_vvc_' + calib)
vvc = proper.prop_shift_center(vvc)
scale_psf = wf._wfarr[0, 0]
psf_num = self.readfield(coron_temp, 'zz_psf_' +
calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = self.readfield(
coron_temp,
'zz_perf_' + calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wf._wfarr = (
wf._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
return wf
def fp_mask(wf, mode='RAVC', focal=660, verbose=False, **conf):
# case 1: vortex coronagraphs
if mode in ['CVC', 'RAVC']:
if verbose is True:
print('Apply Vortex phase mask')
# update conf
conf.update(focal=focal)
# load vortex calibration files:
# conf['psf_num'], conf['vvc'], conf['perf_num']
conf = vortex_init(verbose=verbose, **conf)
# propagate to vortex
lens(wf, focal)
# apply vortex
scale_psf = wf._wfarr[0,0]/conf['psf_num'][0,0]
wf_corr = (conf['psf_num']*conf['vvc'] - conf['perf_num'])*scale_psf
wf._wfarr = wf._wfarr*conf['vvc'] - wf_corr
# propagate to lyot stop
lens(wf, focal)
# TODO: cleanup CLC
# case 2: classical Lyot
elif mode in ['CLC']:
if verbose is True:
print('Apply Classical Lyot mask\n')
f_lens = conf['focal']
beam_ratio = conf['beam_ratio']
CLC_diam = conf['CLC_diam'] # classical lyot diam in lam/D (default to 4)
gridsize = conf['gridsize']
tmp_dir = conf['temp_dir']
# propagate to lyot mask
lens(wf, conf['focal'])
# create or load the classical Lyot mask
calib = str(CLC_diam)+str('_')+str(int(beam_ratio*100))+str('_')+str(gridsize)
my_file = os.path.join(tmp_dir, 'clc_'+calib+'.fits')
if not os.path.isfile(my_file):
# calculate exact size of Lyot mask diameter, in pixels
Dmask = CLC_diam/beam_ratio
# oversample the Lyot mask (round up)
samp = 100
ndisk = int(samp*np.ceil(Dmask))
ndisk = ndisk + 1 if not ndisk % 2 else ndisk # must be odd
# find center
cdisk = int((ndisk - 1)/2)
# calculate the distances to center
xy = range(-cdisk, cdisk + 1)
x,y = np.meshgrid(xy, xy)
dist = np.sqrt(x**2 + y**2)
# create the Lyot mask
mask = np.zeros((ndisk, ndisk))
mask[np.where(dist > samp*Dmask/2)] = 1
# resize to Lyot mask real size, and pad with ones
mask = resize_img(mask, int(ndisk/samp))
mask = pad_img(mask, gridsize, 1)
# write mask
fits.writeto(my_file, mask)
else:
mask = fits.getdata(my_file)
# apply lyot mask
mask = proper.prop_shift_center(mask)
wf._wfarr.real *= mask
# propagate to lyot stop
lens(wf, conf['focal'])
return wf
def convert_to_wfo(image, wfo):
wf_temp = copy(wfo)
wf_temp.wfarr = proper.prop_shift_center(image + 0j)
return wf_temp
def apodizer(wf,
mode='RAVC',
ravc_t=0.8,
ravc_r=0.6,
ravc_misalign=None,
ngrid=1024,
npupil=285,
file_ravc_amp='',
file_ravc_phase='',
margin=50,
get_amp=False,
get_phase=False,
verbose=False,
**conf):
''' Create a wavefront object at the entrance pupil plane.
The pupil is either loaded from a fits file, or created using
pupil parameters.
Can also select only one petal and mask the others.
wf: WaveFront
PROPER wavefront object
mode: str
HCI mode
ravc_t: float
RA transmittance
ravc_r: float
RA radius
ravc_misalign: list of float
RA misalignment
ngrid: int
number of pixels of the wavefront array
npupil: int
number of pixels of the pupil
file_ravc_amp: str
file_ravc_phase: str
ring apodizer files (optional)
'''
if mode in ['RAVC']:
# load apodizer from files if provided
if os.path.isfile(file_ravc_amp) and os.path.isfile(file_ravc_phase):
if verbose is True:
print('Load ring apodizer from files\n')
# get amplitude and phase data
RAVC_amp = fits.getdata(file_ravc_amp)
RAVC_phase = fits.getdata(file_ravc_phase)
# resize to npupil
RAVC_amp = impro.resize_img(RAVC_amp, npupil)
RAVC_phase = impro.resize_img(RAVC_phase, npupil)
# pad with zeros to match PROPER gridsize
RAVC_amp = impro.pad_img(RAVC_amp, ngrid)
RAVC_phase = impro.pad_img(RAVC_phase, ngrid)
# build complex apodizer
apo = RAVC_amp * np.exp(1j * RAVC_phase)
# or else, define the apodizer as a ring (with % misalignments)
else:
# RAVC misalignments
ravc_misalign = [
0, 0, 0, 0, 0, 0
] if ravc_misalign is None else list(ravc_misalign)
dx_amp, dy_amp, dz_amp = ravc_misalign[0:3]
dx_phase, dy_phase, dz_phase = ravc_misalign[3:6]
# create apodizer
apo = circular_apodization(wf, ravc_r, 1., ravc_t, xc=dx_amp, \
yc=dy_amp, NORM=True)
apo = proper.prop_shift_center(apo)
if verbose is True:
print('Create ring apodizer')
print(' ravc_t=%3.4f, ravc_r=%3.4f'\
%(ravc_t, ravc_r))
print(' ravc_misalign=%s' % ravc_misalign)
print('')
# multiply the loaded apodizer
proper.prop_multiply(wf, apo)
# get the apodizer amplitude and phase for output
apo_amp = impro.crop_img(proper.prop_get_amplitude(wf), npupil,\
margin) if get_amp is True else None
apo_phase = impro.crop_img(proper.prop_get_phase(wf), npupil,\
margin) if get_phase is True else None
return wf, apo_amp, apo_phase
else: # no ring apodizer
return wf, None, None
def simple_telescope(wavelength, gridsize):
# Define entrance aperture diameter and other quantities
d_objective = 5.0 # objective diameter in meters
fl_objective = 20.0 * d_objective # objective focal length in meters
fl_eyepiece = 0.021 # eyepiece focal length
fl_eye = 0.022 # human eye focal length
beam_ratio = 0.3 # initial beam width/grid width
# Define the wavefront
wfo = proper.prop_begin(d_objective, wavelength, gridsize, beam_ratio)
# print d_objective, wavelength, gridsize, beam_ratio
# Define a circular aperture
proper.prop_circular_aperture(wfo, d_objective / 2)
# proper.prop_propagate(wfo, fl_objective)
# proper.prop_propagate(wfo, fl_objective)
# proper.prop_propagate(wfo, fl_objective)
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Define entrance
proper.prop_define_entrance(wfo)
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# proper.prop_propagate(wfo, fl_objective+fl_eyepiece, "eyepiece")
# # plt.imshow(proper.prop_get_amplitude(wfo))
# # plt.show()
#
# proper.prop_propagate(wfo, fl_objective+fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
#
# proper.prop_propagate(wfo, fl_objective+fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Define a lens
proper.prop_lens(wfo, fl_objective, "objective")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Propagate the wavefront
proper.prop_propagate(wfo, fl_objective + fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
# Define another lens
proper.prop_lens(wfo, fl_eyepiece, "eyepiece")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
exit_pupil_distance = fl_eyepiece / (1 - fl_eyepiece /
(fl_objective + fl_eyepiece))
proper.prop_propagate(wfo, exit_pupil_distance, "exit pupil at eye lens")
# quicklook_wf(wfo)
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
proper.prop_lens(wfo, fl_eye, "eye")
proper.prop_propagate(wfo, fl_eye, "retina")
# plt.imshow(proper.prop_get_amplitude(wfo))
# plt.show()
quicklook_wf(wfo)
phase_map = proper.prop_get_phase(wfo)
amp_map = proper.prop_get_amplitude(wfo)
# quicklook_im(phase_map)
amp_map[80:100, 80:100] = 0
quicklook_im(amp_map, logAmp=True)
import numpy as np
wfo.wfarr = proper.prop_shift_center(amp_map * np.cos(phase_map) +
1j * amp_map * np.sin(phase_map))
# quicklook_wf(wf_array[iw,0])
proper.prop_propagate(wfo, fl_eye, "retina")
proper.prop_lens(wfo, fl_eye, "eye")
quicklook_wf(wfo)
# End
(wfo, sampling) = proper.prop_end(wfo)
return (wfo, sampling)
def lyotmask_init(lyotmask_calib='',
dir_temp='',
clc_diam=80,
pscale=5.47,
magnification=100,
ngrid=1024,
beam_ratio=0.26,
verbose=False,
**conf):
'''
Creates/writes classical lyot masks, or loads them if files
already exist.
The following parameters will be added to conf:
lyotmask_calib, lyotmask
Returns: conf (updated and sorted)
'''
# update conf with local variables (remove unnecessary)
conf.update(locals())
[conf.pop(key) for key in ['conf', 'verbose'] if key in conf]
# check if lyot mask already loaded for this calib
calib = 'lyotmask_%s_%s_%3.4f' % (clc_diam, ngrid, beam_ratio)
if lyotmask_calib == calib:
return conf
else:
# check for existing file
filename = os.path.join(dir_temp, '%s.fits' % calib)
if os.path.isfile(filename):
if verbose is True:
print(' loading lyot mask')
lyotmask = fits.getdata(os.path.join(dir_temp, filename))
# create file
else:
if verbose is True:
print(" writing lyot mask")
# calculate the size (in pixels) of the lyot mask,
# rounded up to an odd value
nmask = int(np.ceil(clc_diam / pscale))
nmask += 1 - nmask % 2
# create a magnified lyot mask
rmask = clc_diam / pscale / nmask
r, t = polar_coord(nmask * magnification)
lyotmask = np.zeros(np.shape(r))
lyotmask[r > rmask] = 1
# resize and pad with ones to amtch ngrid
lyotmask = pad_img(resize_img(lyotmask, nmask), ngrid, 1)
# save as fits file
fits.writeto(os.path.join(dir_temp, filename),
np.float32(lyotmask),
overwrite=True)
# shift the lyotmask amplitude
lyotmask = proper.prop_shift_center(lyotmask)
# add lyotmask amplitude at the end of conf
conf = {k: v for k, v in sorted(conf.items())}
conf.update(lyotmask_calib=calib, lyotmask=lyotmask)
if verbose is True:
print(' clc_diam=%s, ngrid=%s, beam_ratio=%3.4f'%\
(clc_diam, ngrid, beam_ratio))
return conf
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 vortex(wfo, CAL, charge, f_lens, path, Debug_print):
n = int(proper.prop_get_gridsize(wfo))
ofst = 0 # no offset
ramp_sign = 1 #sign of charge is positive
#sampling = n
ramp_oversamp = 11. # vortex is oversampled for a better discretization
if charge != 0:
if CAL == 1: # create the vortex for a perfectly circular pupil
if (Debug_print == True):
print("CAL:1, charge ", charge)
writefield(path, 'zz_psf', wfo.wfarr) # write the pre-vortex field
nramp = int(n * ramp_oversamp) #oversamp
# create the vortex by creating a matrix (theta) representing the ramp (created by atan 2 gradually varying matrix, x and y)
y1 = np.ones((nramp, ), dtype=np.int)
y2 = np.arange(0, nramp, 1.) - (nramp / 2) - int(ramp_oversamp) / 2
y = np.outer(y2, y1)
x = np.transpose(y)
theta = np.arctan2(y, x)
x = 0
y = 0
#vvc_tmp_complex = np.array(np.zeros((nramp,nramp)), dtype=complex)
#vvc_tmp_complex.imag = ofst + ramp_sign*charge*theta
#vvc_tmp = np.exp(vvc_tmp_complex)
vvc_tmp = np.exp(1j * (ofst + ramp_sign * charge * theta))
theta = 0
vvc_real_resampled = cv2.resize(
vvc_tmp.real, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc_imag_resampled = cv2.resize(
vvc_tmp.imag, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc = np.array(vvc_real_resampled, dtype=complex)
vvc.imag = vvc_imag_resampled
vvcphase = np.arctan2(vvc.imag,
vvc.real) # create the vortex phase
vvc_complex = np.array(np.zeros((n, n)), dtype=complex)
vvc_complex.imag = vvcphase
vvc = np.exp(vvc_complex)
vvc_tmp = 0.
writefield(path, 'zz_vvc',
vvc) # write the theoretical vortex field
wfo0 = wfo
proper.prop_multiply(wfo, vvc)
proper.prop_propagate(wfo, f_lens, 'OAP2')
proper.prop_lens(wfo, f_lens)
proper.prop_propagate(wfo, f_lens, 'forward to Lyot Stop')
proper.prop_circular_obscuration(
wfo, 1., NORM=True) # null the amplitude iside the Lyot Stop
proper.prop_propagate(wfo, -f_lens) # back-propagation
proper.prop_lens(wfo, -f_lens)
proper.prop_propagate(wfo, -f_lens)
writefield(path, 'zz_perf',
wfo.wfarr) # write the perfect-result vortex field
wfo = wfo0
else:
if (Debug_print == True):
print("CAL:0, charge ", charge)
vvc = readfield(path,
'zz_vvc') # read the theoretical vortex field
vvc = proper.prop_shift_center(vvc)
scale_psf = wfo._wfarr[0, 0]
psf_num = readfield(path, 'zz_psf') # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = readfield(
path, 'zz_perf') # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wfo._wfarr = (
wfo._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
return
def vortex_init(vortex_calib='',
dir_temp='',
diam_ext=37,
lam=3.8,
ngrid=1024,
beam_ratio=0.26,
focal=660,
vc_charge=2,
verbose=False,
**conf):
'''
Creates/writes vortex back-propagation fitsfiles, or loads them if files
already exist.
The following parameters will be added to conf:
vortex_calib, psf_num, perf_num, vvc
Returns: conf (updated and sorted)
'''
# update conf with local variables (remove unnecessary)
conf.update(locals())
[conf.pop(key) for key in ['conf', 'verbose'] if key in conf]
# check if back-propagation params already loaded for this calib
calib = 'vortex_%s_%s_%3.4f' % (vc_charge, ngrid, beam_ratio)
if vortex_calib == calib:
return conf
else:
# check for existing file
filename = os.path.join(dir_temp, '%s.fits' % calib)
if os.path.isfile(filename):
if verbose is True:
print(' loading vortex back-propagation params')
data = fits.getdata(os.path.join(dir_temp, filename))
# read the pre-vortex field
psf_num = data[0] + 1j * data[1]
# read the theoretical vortex field
vvc = data[2] + 1j * data[3]
# read the perfect-result vortex field
perf_num = data[4] + 1j * data[5]
# create files
else:
if verbose is True:
print(" writing vortex back-propagation params")
# create circular pupil
wf_tmp = proper.prop_begin(diam_ext, lam, ngrid, beam_ratio)
proper.prop_circular_aperture(wf_tmp, 1, NORM=True)
# propagate to vortex
lens(wf_tmp, focal)
# pre-vortex field
psf_num = deepcopy(wf_tmp.wfarr)
# vortex phase ramp is oversampled for a better discretization
ramp_oversamp = 11.
nramp = int(ngrid * ramp_oversamp)
start = -nramp / 2 - int(ramp_oversamp) / 2 + 0.5
end = nramp / 2 - int(ramp_oversamp) / 2 + 0.5
Vp = np.arange(start, end, 1.)
# Pancharatnam Phase = arg<Vref,Vp> (horizontal input polarization)
Vref = np.ones(Vp.shape)
prod = np.outer(Vref, Vp)
phiPan = np.angle(prod + 1j * prod.T)
# vortex phase ramp exp(ilphi)
ofst = 0
ramp_sign = 1
vvc_tmp = np.exp(1j * (ramp_sign * vc_charge * phiPan + ofst))
vvc = np.array(impro.resize_img(vvc_tmp.real, ngrid),
dtype=complex)
vvc.imag = impro.resize_img(vvc_tmp.imag, ngrid)
phase_ramp = np.angle(vvc)
# theoretical vortex field
vvc_complex = np.array(np.zeros((ngrid, ngrid)), dtype=complex)
vvc_complex.imag = phase_ramp
vvc = np.exp(vvc_complex)
# apply vortex
proper.prop_multiply(wf_tmp, vvc)
# null the amplitude inside the Lyot Stop, and back propagate
lens(wf_tmp, focal)
proper.prop_circular_obscuration(wf_tmp, 1., NORM=True)
lens(wf_tmp, -focal)
# perfect-result vortex field
perf_num = deepcopy(wf_tmp.wfarr)
# write all fields
data = np.dstack((psf_num.real.T, psf_num.imag.T, vvc.real.T, vvc.imag.T,\
perf_num.real.T, perf_num.imag.T)).T
fits.writeto(os.path.join(dir_temp, filename),
np.float32(data),
overwrite=True)
# shift the phase ramp
vvc = proper.prop_shift_center(vvc)
# add vortex back-propagation parameters at the end of conf
conf = {k: v for k, v in sorted(conf.items())}
conf.update(vortex_calib=calib,
psf_num=psf_num,
vvc=vvc,
perf_num=perf_num)
if verbose is True:
print(' vc_charge=%s, ngrid=%s, beam_ratio=%3.4f'%\
(vc_charge, ngrid, beam_ratio))
return conf
def rotate_atmos(wf, it):
time = it * ap.sample_time
rotate_angle = tp.rot_rate * time
wf.wfarr = proper.prop_shift_center(wf.wfarr)
wf.wfarr = proper.prop_rotate(wf.wfarr, rotate_angle)
wf.wfarr = proper.prop_shift_center(wf.wfarr)
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 apodization(wf, r_obstr, npupil, RAVC, phase_apodizer_file,
amplitude_apodizer_file, apodizer_misalignment, Debug_print,
Debug):
n = int(proper.prop_get_gridsize(wf))
if (RAVC == True):
t1_opt = 1. - 1. / 4 * (
r_obstr**2 + r_obstr * (math.sqrt(r_obstr**2 + 8.))
) # define the apodizer transmission [Mawet2013]
R1_opt = (r_obstr / math.sqrt(1. - t1_opt)
) # define the apodizer radius [Mawet2013]
if (Debug_print == True):
print("r1_opt: ", R1_opt)
print("t1_opt: ", t1_opt)
apodizer = circular_apodization(wf,
R1_opt,
1.,
t1_opt,
xc=apodizer_misalignment[0],
yc=apodizer_misalignment[1],
NORM=True) # define the apodizer
apodizer = proper.prop_shift_center(apodizer)
if (isinstance(phase_apodizer_file, (list, tuple, np.ndarray)) == True):
xc_pixels = int(apodizer_misalignment[3] * npupil)
yc_pixels = int(apodizer_misalignment[4] * npupil)
apodizer_pixels = (phase_apodizer_file.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
apodizer_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(
phase_apodizer_file.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
apodizer_large[
int(n / 2) + 1 - int(npupil / 2) - 1 + xc_pixels:int(n / 2) + 1 +
int(npupil / 2) + xc_pixels,
int(n / 2) + 1 - int(npupil / 2) - 1 + yc_pixels:int(n / 2) + 1 +
int(npupil / 2) +
yc_pixels] = apodizer_scale # insert the scaled pupil into the 0s grid
apodizer = np.exp(1j * apodizer_large)
if (isinstance(amplitude_apodizer_file,
(list, tuple, np.ndarray)) == True):
xc_pixels = int(apodizer_misalignment[0] * npupil)
yc_pixels = int(apodizer_misalignment[1] * npupil)
apodizer_pixels = (amplitude_apodizer_file.shape)[0] ## fits file size
scaling_factor = float(npupil) / float(
apodizer_pixels
) ## scaling factor between the fits file size and the pupil size of the simulation
if (Debug_print == True):
print("scaling_factor: ", scaling_factor)
apodizer_scale = cv2.resize(
amplitude_apodizer_file.astype(np.float32), (0, 0),
fx=scaling_factor,
fy=scaling_factor,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
if (Debug_print == True):
print("apodizer_resample", apodizer_scale.shape)
apodizer_large = np.zeros(
(n, n)) # define an array of n-0s, where to insert the pupuil
if (Debug_print == True):
print("n: ", n)
print("npupil: ", npupil)
apodizer_large[
int(n / 2) + 1 - int(npupil / 2) - 1 + xc_pixels:int(n / 2) + 1 +
int(npupil / 2) + xc_pixels,
int(n / 2) + 1 - int(npupil / 2) - 1 + yc_pixels:int(n / 2) + 1 +
int(npupil / 2) +
yc_pixels] = apodizer_scale # insert the scaled pupil into the 0s grid
apodizer = apodizer_large
proper.prop_multiply(wf, apodizer)
return
def vortex(wfo, charge, f_lens, diam, pixelsize, Debug_print=False):
n = int(proper.prop_get_gridsize(wfo))
ofst = 0 # no offset
ramp_sign = 1 #sign of charge is positive
ramp_oversamp = 11. # vortex is oversampled for a better discretization
if charge != 0:
wavelength = proper.prop_get_wavelength(wfo)
gridsize = proper.prop_get_gridsize(wfo)
beam_ratio = pixelsize * 4.85e-9 / (wavelength / diam)
calib = str(charge) + str('_') + str(int(
beam_ratio * 100)) + str('_') + str(gridsize)
my_file = str(tmp_dir + 'zz_perf_' + calib + '_r.fits')
proper.prop_propagate(wfo, f_lens, 'inizio') # propagate wavefront
proper.prop_lens(wfo, f_lens,
'focusing lens vortex') # propagate through a lens
proper.prop_propagate(wfo, f_lens, 'VC') # propagate wavefront
if (os.path.isfile(my_file) == True):
if (Debug_print == True):
print("Charge ", charge)
vvc = readfield(tmp_dir, 'zz_vvc_' +
calib) # read the theoretical vortex field
vvc = proper.prop_shift_center(vvc)
scale_psf = wfo._wfarr[0, 0]
psf_num = readfield(tmp_dir,
'zz_psf_' + calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = readfield(tmp_dir, 'zz_perf_' +
calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wfo._wfarr = (
wfo._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
else: # CAL==1: # create the vortex for a perfectly circular pupil
if (Debug_print == True):
print("Charge ", charge)
wfo1 = proper.prop_begin(diam, wavelength, gridsize, beam_ratio)
proper.prop_circular_aperture(wfo1, diam / 2)
proper.prop_define_entrance(wfo1)
proper.prop_propagate(wfo1, f_lens,
'inizio') # propagate wavefront
proper.prop_lens(
wfo1, f_lens,
'focusing lens vortex') # propagate through a lens
proper.prop_propagate(wfo1, f_lens, 'VC') # propagate wavefront
writefield(tmp_dir, 'zz_psf_' + calib,
wfo1.wfarr) # write the pre-vortex field
nramp = int(n * ramp_oversamp) #oversamp
# create the vortex by creating a matrix (theta) representing the ramp (created by atan 2 gradually varying matrix, x and y)
y1 = np.ones((nramp, ), dtype=np.int)
y2 = np.arange(0, nramp, 1.) - (nramp / 2) - int(ramp_oversamp) / 2
y = np.outer(y2, y1)
x = np.transpose(y)
theta = np.arctan2(y, x)
x = 0
y = 0
vvc_tmp = np.exp(1j * (ofst + ramp_sign * charge * theta))
theta = 0
vvc_real_resampled = cv2.resize(
vvc_tmp.real, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc_imag_resampled = cv2.resize(
vvc_tmp.imag, (0, 0),
fx=1 / ramp_oversamp,
fy=1 / ramp_oversamp,
interpolation=cv2.INTER_LINEAR
) # scale the pupil to the pupil size of the simualtions
vvc = np.array(vvc_real_resampled, dtype=complex)
vvc.imag = vvc_imag_resampled
vvcphase = np.arctan2(vvc.imag,
vvc.real) # create the vortex phase
vvc_complex = np.array(np.zeros((n, n)), dtype=complex)
vvc_complex.imag = vvcphase
vvc = np.exp(vvc_complex)
vvc_tmp = 0.
writefield(tmp_dir, 'zz_vvc_' + calib,
vvc) # write the theoretical vortex field
proper.prop_multiply(wfo1, vvc)
proper.prop_propagate(wfo1, f_lens, 'OAP2')
proper.prop_lens(wfo1, f_lens)
proper.prop_propagate(wfo1, f_lens, 'forward to Lyot Stop')
proper.prop_circular_obscuration(
wfo1, 1., NORM=True) # null the amplitude iside the Lyot Stop
proper.prop_propagate(wfo1, -f_lens) # back-propagation
proper.prop_lens(wfo1, -f_lens)
proper.prop_propagate(wfo1, -f_lens)
writefield(tmp_dir, 'zz_perf_' + calib,
wfo1.wfarr) # write the perfect-result vortex field
vvc = readfield(tmp_dir, 'zz_vvc_' + calib)
vvc = proper.prop_shift_center(vvc)
scale_psf = wfo._wfarr[0, 0]
psf_num = readfield(tmp_dir,
'zz_psf_' + calib) # read the pre-vortex field
psf0 = psf_num[0, 0]
psf_num = psf_num / psf0 * scale_psf
perf_num = readfield(tmp_dir, 'zz_perf_' +
calib) # read the perfect-result vortex field
perf_num = perf_num / psf0 * scale_psf
wfo._wfarr = (
wfo._wfarr - psf_num
) * vvc + perf_num # the wavefront takes into account the real pupil with the perfect-result vortex field
proper.prop_propagate(wfo, f_lens, "propagate to pupil reimaging lens")
proper.prop_lens(wfo, f_lens, "apply pupil reimaging lens")
proper.prop_propagate(wfo, f_lens, "lyot stop")
return wfo
def get_intensity(wf_array,
sp,
logAmp=True,
show=False,
save=True,
phase=False):
if show == True:
wfo = wf_array[0, 0]
after_dm = proper.prop_get_amplitude(wfo)
phase_afterdm = proper.prop_get_phase(wfo)
fig = plt.figure(figsize=(14, 10))
ax1 = plt.subplot2grid((3, 2), (0, 0), rowspan=2)
ax2 = plt.subplot2grid((3, 2), (0, 1), rowspan=2)
ax3 = plt.subplot2grid((3, 2), (2, 0))
ax4 = plt.subplot2grid((3, 2), (2, 1))
if logAmp:
ax1.imshow(after_dm,
origin='lower',
cmap="YlGnBu_r",
norm=LogNorm())
else:
ax1.imshow(after_dm, origin='lower', cmap="YlGnBu_r")
ax2.imshow(phase_afterdm, origin='lower',
cmap="YlGnBu_r") #, vmin=-0.5, vmax=0.5)
ax3.plot(after_dm[int(tp.grid_size / 2)])
ax3.plot(np.sum(np.eye(tp.grid_size) * after_dm, axis=1))
# plt.plot(np.sum(after_dm,axis=1)/after_dm[128,128])
ax4.plot(phase_afterdm[int(tp.grid_size / 2)])
# ax4.plot(np.sum(np.eye(tp.grid_size)*phase_afterdm,axis=1))
plt.xlim([0, proper.prop_get_gridsize(wfo)])
fig.set_tight_layout(True)
plt.show()
if save:
shape = wf_array.shape
ws = sp.get_ints['w']
cs = sp.get_ints['c']
int_maps = np.empty((0, tp.grid_size, tp.grid_size))
for iw in ws:
for iwf in cs:
# int_maps.append(proper.prop_shift_center(np.abs(wf_array[iw, iwf].wfarr) ** 2))
if phase:
int_map = proper.prop_get_phase(wf_array[iw, iwf])
# int_map = proper.prop_shift_center(np.abs(wf_array[iw, iwf].wfarr) ** 2)
else:
int_map = proper.prop_shift_center(
np.abs(wf_array[iw, iwf].wfarr)**2)
int_maps = np.vstack((int_maps, [int_map]))
# quicklook_im(int_map)#, logAmp=True)
# int_maps = np.array(int_maps)
# view_datacube(int_maps)
import pickle, os
if os.path.exists(iop.int_maps):
# "with" statements are very handy for opening files.
with open(iop.int_maps, 'rb') as rfp:
# dprint(np.array(pickle.load(rfp)).shape)
int_maps = np.vstack((int_maps, pickle.load(rfp)))
with open(iop.int_maps, 'wb') as wfp:
pickle.dump(int_maps, wfp, protocol=pickle.HIGHEST_PROTOCOL)
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 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
