def __init__(self, offline=False):
"""Instantiate DarkPrep object.
Parameters
----------
offline : bool
If True, the check for the existence of the MIRAGE_DATA
directory is skipped. This is primarily for Travis testing
"""
self.offline = offline
# Locate the module files, so that we know where to look
# for config subdirectory
self.modpath = pkg_resources.resource_filename('mirage', '')
# Get the location of the MIRAGE_DATA environment
# variable, so we know where to look for darks, CR,
# PSF files, etc later
self.env_var = 'MIRAGE_DATA'
datadir = utils.expand_environment_variable(self.env_var,
offline=offline)
# Check that CRDS-related environment variables are set correctly
self.crds_datadir = crds_tools.env_variables()
def confirm_gridded_properties(filename,
instrument,
detector,
filtername,
pupilname,
wavefront_error_type,
wavefront_error_group,
file_path,
extname='PRIMARY'):
"""Examine the header of the gridded PSF model file to confirm that
the properties of the data match those expected.
Parameters
----------
filename : str
Base name of the PSF library file to be checked
instrument : str
Name of instrument the PSFs are from
detector : str
Name of the detector within ```instrument```
filtername : str
Name of filter used for PSF library creation
pupilname : str
Name of pupil wheel element used for PSF library creation
wavefront_error_type : str
Wavefront error. Can be 'predicted' or 'requirements'
wavefront_error_group : int
Wavefront error realization group. Must be an integer from 0 - 9.
file_path : str
Path pointing to the location of the PSF library
extname : str
Name of the extension within ``filename`` to check
Returns
-------
full_filename : str
Full path and filename if the file properties are as expected.
None if the properties do not match.
"""
# Determine if the PSF path is default or not
mirage_dir = expand_environment_variable('MIRAGE_DATA')
default_psf = file_path == os.path.join(
mirage_dir, '{}/gridded_psf_library'.format(instrument.lower()))
full_filename = os.path.join(file_path, filename)
with fits.open(full_filename) as hdulist:
header = hdulist[extname.upper()].header
inst = header['INSTRUME']
try:
det = header['DETECTOR']
except KeyError:
det = header['DET_NAME']
filt = header['FILTER']
try:
pupil = header['PUPIL']
except KeyError:
# If no pupil mask value is present, then assume the CLEAR is
# being used
if instrument.upper() == 'NIRCAM':
pupil = 'CLEAR'
elif instrument.upper() == 'NIRISS':
pupil = 'CLEARP'
# NIRISS has many filters in the pupil wheel. WebbPSF does
# not make a distinction, but Mirage does. Adjust the info
# to match Mirage's expectations
if inst.upper() == 'NIRISS' and filt in NIRISS_PUPIL_WHEEL_FILTERS:
save_filt = copy(filt)
if pupil == 'CLEARP':
filt = 'CLEAR'
else:
raise ValueError(('Pupil value is something other than '
'CLEARP, but the filter being used is '
'in the pupil wheel.'))
pupil = save_filt
# Same for NIRCam
if inst.upper() == 'NIRCAM' and filt in NIRCAM_PUPIL_WHEEL_FILTERS:
save_filt = copy(filt)
if pupil == 'CLEAR':
if save_filt[0:2] == 'F4':
filt = 'F444W'
elif save_filt[0:2] == 'F3':
filt = 'F322W2'
elif save_filt[0:2] == 'F1':
filt = 'F150W2'
else:
raise ValueError(('Pupil value is something other than '
'CLEAR, but the filter being used is '
'in the pupil wheel.'))
pupil = save_filt
opd_file = header['OPD_FILE']
if default_psf:
if 'predicted' in opd_file:
wfe_type = 'predicted'
elif 'requirements' in opd_file:
wfe_type = 'requirements'
realization = header['OPDSLICE']
# make the check below pass for FGS
if instrument.lower() == 'fgs':
pupil = 'N/A'
pupilname = 'N/A'
filt = 'N/A'
filtername = 'N/A'
match = inst.lower() == instrument.lower() and \
det.lower() == detector.lower() and \
filt.lower() == filtername.lower() and \
pupil.lower() == pupilname.lower()
if match and not default_psf:
return full_filename
elif match and wfe_type == wavefront_error_type.lower() and \
realization == wavefront_error_group:
return full_filename
else:
return None
def get_library_file(instrument,
detector,
filt,
pupil,
wfe,
wfe_group,
library_path,
wings=False,
segment_id=None):
"""Given an instrument and filter name along with the path of
the PSF library, find the appropriate library file to load.
Parameters
-----------
instrument : str
Name of instrument the PSFs are from
detector : str
Name of the detector within ```instrument```
filt : str
Name of filter used for PSF library creation
pupil : str
Name of pupil wheel element used for PSF library creation
wfe : str
Wavefront error. Can be 'predicted' or 'requirements'
wfe_group : int
Wavefront error realization group. Must be an integer from 0 - 9.
library_path : str
Path pointing to the location of the PSF library
wings : bool, optional
Must the library file contain PSF wings or PSF cores? Default is False.
segment_id : int or None, optional
If specified, returns a segment PSF library file and denotes the ID
of the mirror segment
Returns
--------
matches : str
Name of the PSF library file for the instrument and filter name
"""
logger = logging.getLogger('mirage.psf.psf_selection.get_library_file')
psf_files = glob(os.path.join(library_path, '*.fits'))
# Determine if the PSF path is default or not
mirage_dir = expand_environment_variable('MIRAGE_DATA')
gridded_dir = os.path.join(
mirage_dir, '{}/gridded_psf_library'.format(instrument.lower()))
if wings:
gridded_dir = os.path.join(gridded_dir, 'psf_wings')
default_psf = library_path == gridded_dir
# Create a dictionary of header information for all PSF library files
matches = []
instrument = instrument.upper()
detector = detector.upper()
filt = filt.upper()
pupil = pupil.upper()
wfe = wfe.lower()
# set default
file_wfe = ''
# handle the NIRISS NRM case
if pupil == 'NRM':
pupil = 'MASK_NRM'
# Handle the DHS for Coarse Phasing - this is a workaround for webbpsf not
# implementing this. We're going to load an ITM image in any case in this mode
# so the PSF is entirely unused, but we need to load something or else MIRAGE errors.
if pupil == 'GDHS0' or pupil == 'GDHS60':
pupil = 'CLEAR'
for filename in psf_files:
try:
header = fits.getheader(filename)
# Determine if it is an ITM file
itm_sim = header.get('ORIGIN', '') == 'ITM'
# Compare the header entries to the user input
file_inst = header['INSTRUME'].upper()
try:
file_det = header['DETECTOR'].upper()
except KeyError:
file_det = header['DET_NAME'].upper()
file_filt = header['FILTER'].upper()
try:
file_pupil = header['PUPIL'].upper()
except KeyError:
# If no pupil mask value is present, then assume the CLEAR is
# being used
if file_inst.upper() == 'NIRCAM':
file_pupil = 'CLEAR'
elif file_inst.upper() == 'NIRISS':
try:
file_pupil = header['PUPIL'].upper(
) # can be 'MASK_NRM'
except KeyError:
file_pupil = 'CLEARP'
# NIRISS has many filters in the pupil wheel. WebbPSF does
# not make a distinction, but Mirage does. Adjust the info
# to match Mirage's expectations
if file_inst.upper(
) == 'NIRISS' and file_filt in NIRISS_PUPIL_WHEEL_FILTERS:
save_filt = copy(file_filt)
if file_pupil == 'CLEARP':
file_filt = 'CLEAR'
else:
raise ValueError(('Pupil value is something other than '
'CLEARP, but the filter being used is '
'in the pupil wheel.'))
file_pupil = save_filt
# Same for NIRCam
if file_inst.upper(
) == 'NIRCAM' and file_filt in NIRCAM_PUPIL_WHEEL_FILTERS:
save_filt = copy(file_filt)
if file_pupil == 'CLEAR':
if save_filt[0:2] == 'F4':
file_filt = 'F444W'
elif save_filt[0:2] == 'F3':
file_filt = 'F322W2'
elif save_filt[0:2] == 'F1':
file_filt = 'F150W2'
else:
raise ValueError(('Pupil value is something other than '
'CLEAR, but the filter being used is '
'in the pupil wheel.'))
file_pupil = save_filt
if segment_id is None and not itm_sim:
opd = header['OPD_FILE']
if 'requirements' in opd:
file_wfe = 'requirements'
elif 'predicted' in opd:
file_wfe = 'predicted'
file_wfe_grp = header['OPDSLICE']
if segment_id is not None:
segment_id = int(segment_id)
file_segment_id = int(header['SEGID'])
if segment_id is None and itm_sim:
# If we have an ITM library, then wfe is
# meaningless, so force it to match
file_wfe = 'predicted'
wfe = 'predicted'
# allow check below to pass for FGS
if instrument.lower() == 'fgs':
file_filt = 'N/A'
filt = 'N/A'
file_pupil = 'N/A'
pupil = 'N/A'
# Evaluate if the file matches the given parameters
match = (file_inst == instrument and file_det == detector
and file_filt == filt and file_pupil == pupil
and file_wfe == wfe)
if not wings and segment_id is None and not itm_sim and default_psf:
match = match and file_wfe_grp == wfe_group
if segment_id is not None:
match = match and file_segment_id == segment_id
elif not itm_sim and default_psf:
match = match and file_wfe == wfe
# If so, add to the list of all matches
if match:
matches.append(filename)
except KeyError as e:
warnings.warn(
'While searching for PSF file, error raised when examining {}:\n{}\nContinuing.'
.format(os.path.basename(filename), e))
continue
# Find files matching the requested inputs
if len(matches) == 1:
return matches[0]
elif len(matches) == 0:
logger.info(
'Requested parameters:\ninstrument {}\ndetector {}\nfilt {}\npupil {}\nwfe {}\n'
'wfe_group {}\nlibrary_path {}\n'.format(instrument, detector,
filt, pupil, wfe,
wfe_group, library_path))
raise ValueError(
"No PSF library file found matching requested parameters.")
elif len(matches) > 1:
raise ValueError(
"More than one PSF library file matches requested parameters: {}".
format(matches))
#! /usr/bin/env python
"""Create test RA, Dec data to be used in test_ra_dec_to_x_y.py. Travis does
not have access to the reference files, so this must be done manually, and
the results placed into test_ra_dec_to_x_y.py.
"""
import asdf
import glob
import os
import numpy as np
import pysiaf
from mirage.seed_image import catalog_seed_image
from mirage.utils import siaf_interface
from mirage.utils.utils import expand_environment_variable
data_dir = expand_environment_variable('MIRAGE_DATA', offline=False)
instruments = ['nircam', 'niriss', 'fgs']
xyvals = {}
# Create list of points at which to calculate x, y
pointing_ra = 12.0
pointing_dec = 12.0
rotation = 0.0
ra_list = []
dec_list = []
delta_pix = np.array([0, 10, 20, 40, 75, 180, 500, 1000])
delta_deg = delta_pix * 0.031 / 3600.
for delta in delta_deg:
ra_entry = pointing_ra + delta
dec_entry = pointing_dec + delta
ra_list.append(ra_entry)
def get_library_file(instrument,
detector,
filt,
pupil,
wfe,
wfe_group,
library_path,
wings=False,
segment_id=None):
"""Given an instrument and filter name along with the path of
the PSF library, find the appropriate library file to load.
Parameters
-----------
instrument : str
Name of instrument the PSFs are from
detector : str
Name of the detector within ```instrument```
filt : str
Name of filter used for PSF library creation
pupil : str
Name of pupil wheel element used for PSF library creation
wfe : str
Wavefront error. Can be 'predicted' or 'requirements'
wfe_group : int
Wavefront error realization group. Must be an integer from 0 - 9.
library_path : str
Path pointing to the location of the PSF library
wings : bool, optional
Must the library file contain PSF wings or PSF cores? Default is False.
segment_id : int or None, optional
If specified, returns a segment PSF library file and denotes the ID
of the mirror segment
Returns
--------
matches : str
Name of the PSF library file for the instrument and filter name
"""
psf_files = glob(os.path.join(library_path, '*.fits'))
# Determine if the PSF path is default or not
mirage_dir = expand_environment_variable('MIRAGE_DATA')
default_psf = library_path == os.path.join(
mirage_dir, '{}/gridded_psf_library'.format(instrument.lower()))
# Create a dictionary of header information for all PSF library files
matches = []
instrument = instrument.upper()
detector = detector.upper()
filt = filt.upper()
pupil = pupil.upper()
wfe = wfe.lower()
# handle the NIRISS NRM case
if pupil == 'NRM':
pupil = 'MASK_NRM'
for filename in psf_files:
try:
header = fits.getheader(filename)
# Determine if it is an ITM file
itm_sim = header.get('ORIGIN', '') == 'ITM'
# Compare the header entries to the user input
file_inst = header['INSTRUME'].upper()
file_det = header['DETECTOR'].upper()
file_filt = header['FILTER'].upper()
try:
file_pupil = header['PUPIL_MASK'].upper()
except KeyError:
# If no pupil mask value is present, then assume the CLEAR is
# being used
if file_inst.upper() == 'NIRCAM':
file_pupil = 'CLEAR'
elif file_inst.upper() == 'NIRISS':
try:
file_pupil = header['PUPIL'].upper(
) # can be 'MASK_NRM'
except KeyError:
file_pupil = 'CLEARP'
# NIRISS has many filters in the pupil wheel. WebbPSF does
# not make a distinction, but Mirage does. Adjust the info
# to match Mirage's expectations
if file_inst.upper(
) == 'NIRISS' and file_filt in NIRISS_PUPIL_WHEEL_FILTERS:
save_filt = copy(file_filt)
if file_pupil == 'CLEARP':
file_filt = 'CLEAR'
else:
raise ValueError(('Pupil value is something other than '
'CLEARP, but the filter being used is '
'in the pupil wheel.'))
file_pupil = save_filt
if segment_id is None and not itm_sim:
opd = header['OPD_FILE']
if 'requirements' in opd:
file_wfe = 'requirements'
elif 'predicted' in opd:
file_wfe = 'predicted'
file_wfe_grp = header['OPDSLICE']
if segment_id is not None:
segment_id = int(segment_id)
file_segment_id = int(header['SEGID'])
# allow check below to pass for FGS
if instrument.lower() == 'fgs':
file_filt = 'N/A'
filt = 'N/A'
file_pupil = 'N/A'
pupil = 'N/A'
# Evaluate if the file matches the given parameters
match = (file_inst == instrument and file_det == detector
and file_filt == filt and file_pupil == pupil)
if not wings and segment_id is None and not itm_sim and default_psf:
match = match and file_wfe_grp == wfe_group
if segment_id is not None:
match = match and file_segment_id == segment_id
elif not itm_sim and default_psf:
match = match and file_wfe == wfe
# If so, add to the list of all matches
if match:
matches.append(filename)
except KeyError:
continue
# Find files matching the requested inputs
if len(matches) == 1:
return matches[0]
elif len(matches) == 0:
raise ValueError(
"No PSF library file found matching requested parameters.")
elif len(matches) > 1:
raise ValueError(
"More than one PSF library file matches requested parameters: {}".
format(matches))
