"""
Module for Gemini FLAMINGOS.
.. include:: ../include/links.rst
"""
from pathlib import Path
import numpy as np
from astropy.io import fits
from astropy.table import Table
from pypeit import log
from pypeit import telescopes
from pypeit.core import framematch
from pypeit.images import detector_container
from pypeit.par import parset
from pypeit.spectrographs import spectrograph
[docs]
class GeminiFLAMINGOSSpectrograph(spectrograph.Spectrograph):
"""
Base class for the Gemini FLAMINGOS spectrograph.
"""
ndet = 1
telescope = telescopes.GeminiSTelescopePar()
url = 'https://www.gemini.edu/instrumentation/flamingos-2'
[docs]
class GeminiFLAMINGOS2Spectrograph(GeminiFLAMINGOSSpectrograph):
"""
Gemini/Flamingos2 Echelle spectrograph methods.
"""
name = 'gemini_flamingos2'
camera = 'FLAMINGOS'
supported = True
comment = 'Flamingos-2 NIR spectrograph'
header_name = 'F2'
[docs]
def get_detector_par(self, det, hdu=None):
"""
Return metadata for the selected detector.
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.
"""
# Detector 1
detector_dict = dict(
binning = '1,1',
det = 1,
dataext = 1,
specaxis = 0,
specflip = True,
spatflip = False,
platescale = 0.1787,
darkcurr = 1800.0, # e-/pixel/hour (=0.5 e-/pixel/s)
saturation = 700000., #155400.,
nonlinear = 1.0,
mincounts = -1e10,
numamplifiers = 1,
gain = np.atleast_1d(4.44),
ronoise = np.atleast_1d(5.0), #8 CDS read
datasec = np.atleast_1d('[:,:]'),
oscansec = None,
)
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()
# Image processing steps
turn_off = dict(use_illumflat=False, use_biasimage=False, use_overscan=False,
use_darkimage=False)
par.reset_all_processimages_par(**turn_off)
# Wavelengths
# 1D wavelength solution with arc lines
par['calibrations']['wavelengths']['rms_thresh_frac_fwhm'] = 0.1
par['calibrations']['wavelengths']['sigdetect']=5
par['calibrations']['wavelengths']['fwhm'] = 5.
par['calibrations']['wavelengths']['n_first']=2
par['calibrations']['wavelengths']['n_final']=4
par['calibrations']['wavelengths']['lamps'] = ['OH_NIRES']
par['calibrations']['wavelengths']['match_toler']=5.0
# Set slits and tilts parameters
par['calibrations']['tilts']['tracethresh'] = 5
par['calibrations']['tilts']['spat_order'] = 4
par['calibrations']['slitedges']['trace_thresh'] = 10.
par['calibrations']['slitedges']['edge_thresh'] = 200.
par['calibrations']['slitedges']['fit_min_spec_length'] = 0.4
par['calibrations']['slitedges']['sync_predict'] = 'nearest'
# Set the default exposure time ranges for the frame typing
par['calibrations']['standardframe']['exprng'] = [None, 30]
par['calibrations']['tiltframe']['exprng'] = [50, None]
par['calibrations']['arcframe']['exprng'] = [50, None]
par['calibrations']['darkframe']['exprng'] = [20, None]
par['scienceframe']['exprng'] = [20, None]
# Scienceimage parameters
par['reduce']['findobj']['snr_thresh'] = 5.0
par['reduce']['skysub']['sky_sigrej'] = 5.0
par['reduce']['findobj']['find_trim_edge'] = [10,10]
# Do not correct for flexure
par['flexure']['spec_method'] = 'skip'
# Sensitivity function parameters
par['sensfunc']['algorithm'] = 'IR'
par['sensfunc']['polyorder'] = 8
# TODO: replace the telluric grid file for Gemini-S site.
par['sensfunc']['IR']['telgridfile'] = 'TellPCA_3000_26000_R10000.fits'
return par
[docs]
def config_specific_par(
self,
inp:str|list|Path|fits.Header|Table,
inp_par:parset.ParSet|None=None
) -> parset.ParSet:
"""
Modify the PypeIt parameters to hard-wired values used for
specific instrument configurations.
Args:
inp (:obj:`str`, :obj:`list`, `Path`_, `astropy.io.fits.Header`_, `astropy.table.Table`_):
Input filename, an `astropy.io.fits.Header`_ object, or a list
of `astropy.io.fits.Header`_ objects. Or a row from the
metadata table.
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 parameters
par = super().config_specific_par(inp, inp_par=inp_par)
# Adjust parameters based on disperser used
grating = self.get_meta_value(inp, 'dispname')
# TODO: Should we allow the user to override these?
match grating:
case 'JH_G5801':
par['calibrations']['wavelengths']['method'] = 'full_template'
par['calibrations']['wavelengths']['reid_arxiv'] = 'Flamingos2_JH_JH.fits'
case 'HK_G5802':
par['calibrations']['wavelengths']['method'] = 'full_template'
par['calibrations']['wavelengths']['reid_arxiv'] = 'Flamingos2_HK_HK.fits'
return par
[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 ['pinhole', 'bias']:
# No pinhole or bias frames
return np.zeros(len(fitstbl), dtype=bool)
if ftype in ['pixelflat', 'trace']:
return good_exp & (fitstbl['idname'] == 'FLAT')
if ftype == 'standard':
return good_exp & (fitstbl['idname'] == 'OBJECT')
if ftype == 'science':
return good_exp & (fitstbl['idname'] == 'OBJECT')
if ftype in ['arc', 'tilt']:
return good_exp & (fitstbl['idname'] == 'OBJECT')
log.debug('Cannot determine if frames are of type {0}.'.format(ftype))
return np.zeros(len(fitstbl), dtype=bool)
[docs]
class GeminiFLAMINGOS1Spectrograph(GeminiFLAMINGOSSpectrograph):
"""
Gemini/Flamingos1 Echelle spectrograph methods.
.. todo::
This is a placeholder class that is not yet supported.
"""
name = 'gemini_flamingos1'
camera = 'FLAMINGOS'
header_name = 'F1'
[docs]
def get_detector_par(self, det, hdu=None):
"""
Return metadata for the selected detector.
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.
"""
# Detector 1
detector_dict = dict(
binning='1,1',
det = 1,
dataext = 1,
specaxis = 0,
specflip = False,
spatflip = False,
platescale = 0.15,
darkcurr = 1080.0, # e-/hour/pixel (=0.3 e-/pixel/s)
saturation = 320000., #155400.,
nonlinear = 0.875,
mincounts = -1e10,
numamplifiers = 1,
gain = np.atleast_1d(3.8),
ronoise = np.atleast_1d(6.0), # SUTR readout
datasec= np.atleast_1d('[5:2044, 900:1250]'),
oscansec= np.atleast_1d('[:5, 900:1250]'),
)
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()
# Image processing steps
turn_off = dict(use_illumflat=False, use_biasimage=False, use_overscan=False,
use_darkimage=False)
par.reset_all_processimages_par(**turn_off)
# Wavelengths
# 1D wavelength solution with arc lines
par['calibrations']['wavelengths']['rms_thresh_frac_fwhm'] = 0.05 # this needs to be updated
par['calibrations']['wavelengths']['sigdetect']=3
par['calibrations']['wavelengths']['fwhm'] = 20 # we don't know this value, no dataset in the repo
par['calibrations']['wavelengths']['n_first']=2
par['calibrations']['wavelengths']['n_final']=4
par['calibrations']['wavelengths']['lamps'] = ['ArI', 'ArII', 'ThAr', 'NeI']
par['calibrations']['wavelengths']['method'] = 'full_template'
par['calibrations']['wavelengths']['reid_arxiv'] = 'magellan_fire_long.fits'
par['calibrations']['wavelengths']['match_toler']=5.0
# Set slits and tilts parameters
par['calibrations']['tilts']['tracethresh'] = 5
par['calibrations']['slitedges']['trace_thresh'] = 5.
par['calibrations']['slitedges']['sync_predict'] = 'nearest'
# Scienceimage parameters
par['reduce']['findobj']['snr_thresh'] = 5.0
# TODO: I think this parameter was removed
par['reduce']['findobj']['find_trim_edge'] = [50,50]
# Do not correct for flexure
par['flexure']['spec_method'] = 'skip'
# Set the default exposure time ranges for the frame typing
par['calibrations']['standardframe']['exprng'] = [None, 60]
par['calibrations']['arcframe']['exprng'] = [1, 50]
par['calibrations']['darkframe']['exprng'] = [20, None]
par['scienceframe']['exprng'] = [20, None]
return par
[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 ['pinhole', 'bias']:
# No pinhole or bias frames
return np.zeros(len(fitstbl), dtype=bool)
if ftype in ['pixelflat', 'trace']:
return good_exp & (fitstbl['idname'] == 'PixFlat')
if ftype == 'standard':
return good_exp & (fitstbl['idname'] == 'Telluric')
if ftype == 'science':
return good_exp & (fitstbl['idname'] == 'Science')
if ftype in ['arc', 'tilt']:
return good_exp & (fitstbl['idname'] == 'Arc')
log.debug('Cannot determine if frames are of type {0}.'.format(ftype))
return np.zeros(len(fitstbl), dtype=bool)