"""
Module for the SOAR/Goodman instrument
.. include:: ../include/links.rst
"""
import numpy as np
from astropy.time import Time
from pypeit import msgs
from pypeit import telescopes
from pypeit import io
from pypeit.core import framematch
from pypeit.spectrographs import spectrograph
from pypeit.core import parse
from pypeit.images import detector_container
[docs]class SOARGoodmanSpectrograph(spectrograph.Spectrograph):
"""
Child to handle Goodman specific code for each camera
"""
ndet = 1
telescope = telescopes.SOARTelescopePar()
url = 'https://noirlab.edu/science/programs/ctio/instruments/goodman-high-throughput-spectrograph'
allowed_extensions = [".fz"]
[docs] def configuration_keys(self):
"""
Return the metadata keys that define a unique instrument
configuration.
This list is used by :class:`~pypeit.metadata.PypeItMetaData` to
identify the unique configurations among the list of frames read
for a given reduction.
Returns:
:obj:`list`: List of keywords of data pulled from file headers
and used to constuct the :class:`~pypeit.metadata.PypeItMetaData`
object.
"""
return ['dispname', 'decker', 'binning', 'dispangle']
# def pypeit_file_keys(self):
# """
# Define the list of keys to be output into a standard PypeIt file.
#
# Returns:
# :obj:`list`: The list of keywords in the relevant
# :class:`~pypeit.metadata.PypeItMetaData` instance to print to the
# :ref:`pypeit_file`.
# """
# return super().pypeit_file_keys() + ['slitwid']
[docs] def lamps(self, fitstbl, status):
"""
Check the lamp status.
Args:
fitstbl (`astropy.table.Table`_):
The table with the fits header meta data.
status (:obj:`str`):
The status to check. Can be ``'off'``, ``'arcs'``, or
``'dome'``.
Returns:
`numpy.ndarray`_: A boolean array selecting fits files that meet
the selected lamp status.
Raises:
ValueError:
Raised if the status is not one of the valid options.
"""
if status == 'off':
# Check if all are off
return np.all(np.array([ (np.char.lower(fitstbl[k]) == 'false') | (np.char.lower(fitstbl[k]) == 'none')
for k in fitstbl.keys() if 'lampstat' in k]), axis=0)
if status == 'arc':
# Check if any arc lamps are on
arc_lamp_stat = [ 'lampstat{0:02d}'.format(i) for i in range(1,5) ]
return np.any(np.array([ np.char.lower(fitstbl[k]) == 'true' for k in fitstbl.keys()
if k in arc_lamp_stat]), axis=0)
if status == 'dome':
# Check if any dome lamps are on
dome_lamp_stat = [ 'lampstat{0:02d}'.format(i) for i in [6, 8] ]
return np.any(np.array([ np.char.lower(fitstbl[k]) == 'true' for k in fitstbl.keys()
if k in dome_lamp_stat]), axis=0)
raise ValueError('No implementation for status = {0}'.format(status))
[docs] def check_frame_type(self, ftype, fitstbl, exprng=None):
"""
Check for frames of the provided type.
Args:
ftype (:obj:`str`):
Type of frame to check. Must be a valid frame type; see
frame-type :ref:`frame_type_defs`.
fitstbl (`astropy.table.Table`_):
The table with the metadata for one or more frames to check.
exprng (:obj:`list`, optional):
Range in the allowed exposure time for a frame of type
``ftype``. See
:func:`pypeit.core.framematch.check_frame_exptime`.
Returns:
`numpy.ndarray`_: Boolean array with the flags selecting the
exposures in ``fitstbl`` that are ``ftype`` type frames.
"""
good_exp = framematch.check_frame_exptime(fitstbl['exptime'], exprng)
if ftype in ['science']:
return good_exp & (fitstbl['idname'] == 'SPECTRUM') & self.lamps(fitstbl, 'off')
if ftype in ['standard']:
# Don't type pinhole or dark frames
return np.zeros(len(fitstbl), dtype=bool) & self.lamps(fitstbl, 'off')
if ftype == 'bias':
# Don't type bias
return np.zeros(len(fitstbl), dtype=bool)
if ftype in ['pixelflat', 'trace', 'illumflat']:
return good_exp & self.lamps(fitstbl, 'dome')
if ftype in ['pinhole', 'dark']:
# Don't type pinhole or dark frames
return np.zeros(len(fitstbl), dtype=bool)
if ftype in ['arc', 'tilt']:
return good_exp & self.lamps(fitstbl, 'arc')
msgs.warn('Cannot determine if frames are of type {0}.'.format(ftype))
return np.zeros(len(fitstbl), dtype=bool)
[docs]class SOARGoodmanRedSpectrograph(SOARGoodmanSpectrograph):
name = 'soar_goodman_red'
camera = 'red'
comment = 'Supported gratings: 400_SYZY at M1 and M2 tilts'
supported = True
[docs] def get_detector_par(self, det, hdu=None):
"""
Return metadata for the selected detector.
.. warning::
Many of the necessary detector parameters are read from the file
header, meaning the ``hdu`` argument is effectively **required** for
SOAR/Goodman-Red. The optional use of ``hdu`` is only viable for
automatically generated documentation.
Args:
det (:obj:`int`):
1-indexed detector number.
hdu (`astropy.io.fits.HDUList`_, optional):
The open fits file with the raw image of interest. If not
provided, frame-dependent parameters are set to a default.
Returns:
:class:`~pypeit.images.detector_container.DetectorContainer`:
Object with the detector metadata.
"""
if hdu is None:
binning = '2,2'
gain = None
ronoise = None
datasec = None
oscansec = None
else:
# TODO: Could this be detector dependent??
binning = self.get_meta_value(self.get_headarr(hdu), 'binning')
gain = np.atleast_1d(hdu[1].header['GAIN'])
ronoise = np.atleast_1d(hdu[1].header['RDNOISE'])
datasec = None
oscansec = None
# Detector 1
detector_dict = dict(
binning = binning,
det = 1,
dataext = 1,
specaxis = 1,
specflip = False,
spatflip = False,
platescale = 0.15,
darkcurr = 0.0, # e-/pixel/hour
saturation = 65535.,
nonlinear = 1.0,
mincounts = -1e10,
numamplifiers = 1,
gain = gain,
ronoise = ronoise,
datasec = datasec,
oscansec = oscansec
)
if hdu is None:
return detector_container.DetectorContainer(**detector_dict)
# Only tested for 2x2
if binning == '2,2':
# parse TRIMSEC
col0 = int(hdu[1].header['TRIMSEC'][1:].split(':')[0])
dsec = f"[:,{col0*2}:]" # rows, columns on the raw frame
detector_dict['datasec'] = np.atleast_1d(dsec)
# Overscan
osec = f"[:,1:{int(col0*2)-2}:]"
detector_dict['oscansec'] = np.atleast_1d(osec)
else:
msgs.error("Ask the developers to add your binning. Or add it yourself.")
# Return
return detector_container.DetectorContainer(**detector_dict)
[docs] @classmethod
def default_pypeit_par(cls):
"""
Return the default parameters to use for this instrument.
Returns:
:class:`~pypeit.par.pypeitpar.PypeItPar`: Parameters required by
all of PypeIt methods.
"""
par = super().default_pypeit_par()
# Turn off bias and turn on overscan
turn_off_on = dict(use_biasimage=False, use_darkimage=False, use_overscan=True)
par.reset_all_processimages_par(**turn_off_on)
# Ignore PCA
par['calibrations']['slitedges']['bound_detector'] = True
par['calibrations']['slitedges']['sync_predict'] = 'nearest'
# Always correct for flexure, starting with default parameters
par['flexure']['spec_method'] = 'boxcar'
# Set pixel flat combination method
#par['calibrations']['pixelflatframe']['process']['combine'] = 'median'
# Change the wavelength calibration method
par['calibrations']['wavelengths']['method'] = 'holy-grail'
#par['calibrations']['wavelengths']['method'] = 'reidentify'
par['calibrations']['wavelengths']['lamps'] = ['NeI', 'ArI', 'HgI']
# Wavelengths
# 1D wavelength solution
par['calibrations']['wavelengths']['rms_thresh_frac_fwhm'] = 0.17
par['calibrations']['wavelengths']['sigdetect'] = 5.
par['calibrations']['wavelengths']['fwhm']= 5.0
par['calibrations']['flatfield']['slit_illum_finecorr'] = False
#par['calibrations']['wavelengths']['n_first'] = 3
#par['calibrations']['wavelengths']['n_final'] = 5
#par['calibrations']['wavelengths']['sigdetect'] = 10.0
#par['calibrations']['wavelengths']['wv_cen'] = 4859.0
#par['calibrations']['wavelengths']['disp'] = 0.2
# Set the default exposure time ranges for the frame typing
#par['calibrations']['biasframe']['exprng'] = [None, 0.001]
#par['calibrations']['darkframe']['exprng'] = [999999, None] # No dark frames
#par['calibrations']['pinholeframe']['exprng'] = [999999, None] # No pinhole frames
par['calibrations']['arcframe']['exprng'] = [None, 30]
par['calibrations']['standardframe']['exprng'] = [None, 120]
par['scienceframe']['exprng'] = [90, None]
#par['sensfunc']['algorithm'] = 'IR'
par['sensfunc']['IR']['telgridfile'] = 'TellPCA_3000_26000_R15000.fits'
# TODO: Temporary fix for failure mode. Remove once Ryan provides a
# fix.
par['calibrations']['flatfield']['slit_illum_finecorr'] = False
return par
[docs] def config_specific_par(self, scifile, inp_par=None):
"""
Modify the PypeIt parameters to hard-wired values used for
specific instrument configurations.
Args:
scifile (:obj:`str`):
File to use when determining the configuration and how
to adjust the input parameters.
inp_par (:class:`~pypeit.par.parset.ParSet`, optional):
Parameter set used for the full run of PypeIt. If None,
use :func:`default_pypeit_par`.
Returns:
:class:`~pypeit.par.parset.ParSet`: The PypeIt parameter set
adjusted for configuration specific parameter values.
"""
# Start with instrument wide
par = super().config_specific_par(scifile, inp_par=inp_par)
# Wavelength calibrations
# Here is a useful website with an arc atlas
# http://soartelescope.org/soar/content/goodman-comparison-lamps
if self.get_meta_value(scifile, 'dispname') == '400_SYZY':
par['calibrations']['wavelengths']['reid_arxiv'] = 'soar_goodman_red_400_SYZY.fits'
par['calibrations']['wavelengths']['method'] = 'full_template'
elif self.get_meta_value(scifile, 'dispname') == '600_SYZY_OLD':
par['calibrations']['wavelengths']['lamps'] = ['NeI', 'ArI', 'HgI']
par['calibrations']['wavelengths']['reid_arxiv'] = 'soar_goodman_red_600_SYZY_OLD.fits'
par['calibrations']['wavelengths']['method'] = 'full_template'
# Return
return par
[docs] def bpm(self, filename, det, shape=None, msbias=None):
"""
Generate a default bad-pixel mask.
Even though they are both optional, either the precise shape for
the image (``shape``) or an example file that can be read to get
the shape (``filename`` using :func:`get_image_shape`) *must* be
provided.
Args:
filename (:obj:`str` or None):
An example file to use to get the image shape.
det (:obj:`int`):
1-indexed detector number to use when getting the image
shape from the example file.
shape (tuple, optional):
Processed image shape
Required if filename is None
Ignored if filename is not None
msbias (`numpy.ndarray`_, optional):
Processed bias frame used to identify bad pixels
Returns:
`numpy.ndarray`_: An integer array with a masked value set
to 1 and an unmasked value set to 0. All values are set to
0.
"""
# Call the base-class method to generate the empty bpm
bpm_img = super().bpm(filename, det, shape=shape, msbias=msbias)
msgs.info("Using hard-coded BPM for SOAR/Goodman")
bpm_img[:, 0] = 1
return bpm_img
[docs]class SOARGoodmanBlueSpectrograph(SOARGoodmanSpectrograph):
name = 'soar_goodman_blue'
camera = 'blue'
comment = 'Supported gratings: 400_SYZY at M1 tilt'
supported = True
[docs] def get_detector_par(self, det, hdu=None):
"""
Return metadata for the selected detector.
.. warning::
Many of the necessary detector parameters are read from the file
header, meaning the ``hdu`` argument is effectively **required** for
SOAR/Goodman-Blue. The optional use of ``hdu`` is only viable for
automatically generated documentation.
Args:
det (:obj:`int`):
1-indexed detector number.
hdu (`astropy.io.fits.HDUList`_, optional):
The open fits file with the raw image of interest. If not
provided, frame-dependent parameters are set to a default.
Returns:
:class:`~pypeit.images.detector_container.DetectorContainer`:
Object with the detector metadata.
"""
if hdu is None:
binning = '2,2'
gain = None
ronoise = None
datasec = None
oscansec = None
else:
# TODO: Could this be detector dependent??
binning = self.get_meta_value(self.get_headarr(hdu), 'binning')
gain = np.atleast_1d(hdu[1].header['GAIN'])
ronoise = np.atleast_1d(hdu[1].header['RDNOISE'])
datasec = None
oscansec = None
# Detector 1
detector_dict = dict(
binning=binning,
det=1,
dataext=1,
specaxis=1,
specflip=False,
spatflip=False,
platescale=0.15,
darkcurr=0.0, # e-/pixel/hour
saturation=65535.,
nonlinear=1.0,
mincounts=-1e10,
numamplifiers=1,
gain=gain,
ronoise=ronoise,
datasec=np.asarray(['[:,20:4112]']),
oscansec=np.asarray(['[:,2:16]'])
)
if hdu is None:
return detector_container.DetectorContainer(**detector_dict)
# Return
return detector_container.DetectorContainer(**detector_dict)
[docs] @classmethod
def default_pypeit_par(cls):
"""
Return the default parameters to use for this instrument.
Returns:
:class:`~pypeit.par.pypeitpar.PypeItPar`: Parameters required by
all of PypeIt methods.
"""
par = super().default_pypeit_par()
# Turn off bias and turn on overscan
turn_off_on = dict(use_biasimage=False, use_darkimage=False, use_overscan=True)
par.reset_all_processimages_par(**turn_off_on)
# Ignore PCA
par['calibrations']['slitedges']['bound_detector'] = True
par['calibrations']['slitedges']['sync_predict'] = 'nearest'
# Always correct for flexure, starting with default parameters
par['flexure']['spec_method'] = 'boxcar'
# Set pixel flat combination method
# par['calibrations']['pixelflatframe']['process']['combine'] = 'median'
# Change the wavelength calibration method
par['calibrations']['wavelengths']['method'] = 'holy-grail'
# par['calibrations']['wavelengths']['method'] = 'reidentify'
par['calibrations']['wavelengths']['lamps'] = ['NeI', 'ArI', 'HgI']
# Wavelengths
# 1D wavelength solution
par['calibrations']['wavelengths']['rms_thresh_frac_fwhm'] = 0.17
par['calibrations']['wavelengths']['sigdetect'] = 5.
par['calibrations']['wavelengths']['fwhm'] = 5.0
# par['calibrations']['wavelengths']['n_first'] = 3
# par['calibrations']['wavelengths']['n_final'] = 5
# par['calibrations']['wavelengths']['sigdetect'] = 10.0
# par['calibrations']['wavelengths']['wv_cen'] = 4859.0
# par['calibrations']['wavelengths']['disp'] = 0.2
# Set the default exposure time ranges for the frame typing
# par['calibrations']['biasframe']['exprng'] = [None, 0.001]
# par['calibrations']['darkframe']['exprng'] = [999999, None] # No dark frames
# par['calibrations']['pinholeframe']['exprng'] = [999999, None] # No pinhole frames
par['calibrations']['arcframe']['exprng'] = [None, 30]
par['calibrations']['standardframe']['exprng'] = [None, 120]
par['scienceframe']['exprng'] = [90, None]
# par['sensfunc']['algorithm'] = 'IR'
par['sensfunc']['IR']['telgridfile'] = 'TellPCA_3000_26000_R15000.fits'
return par
[docs] def config_specific_par(self, scifile, inp_par=None):
"""
Modify the PypeIt parameters to hard-wired values used for
specific instrument configurations.
Args:
scifile (:obj:`str`):
File to use when determining the configuration and how
to adjust the input parameters.
inp_par (:class:`~pypeit.par.parset.ParSet`, optional):
Parameter set used for the full run of PypeIt. If None,
use :func:`default_pypeit_par`.
Returns:
:class:`~pypeit.par.parset.ParSet`: The PypeIt parameter set
adjusted for configuration specific parameter values.
"""
# Start with instrument wide
par = super().config_specific_par(scifile, inp_par=inp_par)
# Wavelength calibrations
# Here is a useful website with an arc atlas
# http://soartelescope.org/soar/content/goodman-comparison-lamps
if self.get_meta_value(scifile, 'dispname') == '400_SYZY':
par['calibrations']['wavelengths']['reid_arxiv'] = 'soar_goodman_blue_400_SYZY.fits'
par['calibrations']['wavelengths']['method'] = 'full_template'
par['calibrations']['flatfield']['slit_illum_finecorr'] = False # Turn this off due to junk in the unilluminated part of the detector
# Return
return par
[docs] def bpm(self, filename, det, shape=None, msbias=None):
"""
Generate a default bad-pixel mask.
Even though they are both optional, either the precise shape for
the image (``shape``) or an example file that can be read to get
the shape (``filename`` using :func:`get_image_shape`) *must* be
provided.
Args:
filename (:obj:`str` or None):
An example file to use to get the image shape.
det (:obj:`int`):
1-indexed detector number to use when getting the image
shape from the example file.
shape (tuple, optional):
Processed image shape
Required if filename is None
Ignored if filename is not None
msbias (`numpy.ndarray`_, optional):
Processed calibration frame used to identify bad pixels
Returns:
`numpy.ndarray`_: An integer array with a masked value set
to 1 and an unmasked value set to 0. All values are set to
0.
"""
# Call the base-class method to generate the empty bpm
bpm_img = super().bpm(filename, det, shape=shape, msbias=msbias)
msgs.info("Using hard-coded BPM for SOAR/Goodman")
bpm_img[:, 0] = 1
return bpm_img