Gemini-GNIRS HOWTO
Overview
This doc goes through a full run of PypeIt on one of the Gemini/GNIRS datasets
(specifically the 32_SB_SXD dataset) in the PypeIt Development Suite,
providing an example for how to best run a NIR reduction and especially how to
set the calib IDs.
PypeIt File
Here is some advice on how to setup your PypeIt file.
To setup the pypeit file, first run pypeit_setup:
pypeit_setup -r absolute_path -s gemini_gnirs_echelle -b -c A
where -b indicates that the data uses background images and includes the
calib, comb_id, bkg_id in the pypeit file.
The resulting pypeit file looks like:
# Auto-generated PypeIt input file using PypeIt version: 1.12.2
# UTC 2023-04-05T22:42:29.971
# User-defined execution parameters
[rdx]
spectrograph = gemini_gnirs_echelle
# Setup
setup read
Setup A:
decker: 0.68arcsec_G5530
dispangle: 6.1887
dispname: 32/mmSB_G5533
setup end
# Data block
data read
path /Users/rcooke/Software/PypeIt-development-suite/RAW_DATA/gemini_gnirs_echelle/32_SB_SXD
filename | frametype | ra | dec | target | dispname | decker | binning | mjd | airmass | exptime | dispangle | dithoff | calib | comb_id | bkg_id
cN20170331S0216.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3709743134 | 1.077 | 300.0 | 6.1887 | -0.34225501721318 | 0 | 5 | -1
cN20170331S0217.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3746886267 | 1.068 | 300.0 | 6.1887 | 2.65774498278682 | 0 | 6 | -1
cN20170331S0218.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3784029399 | 1.06 | 300.0 | 6.1887 | 2.65774498278682 | 0 | 7 | -1
cN20170331S0219.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3821513967 | 1.053 | 300.0 | 6.1887 | -0.34225501721318 | 0 | 8 | -1
cN20170331S0220.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3858649384 | 1.047 | 300.0 | 6.1887 | -0.34225501721318 | 0 | 9 | -1
cN20170331S0221.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.389578673 | 1.041 | 300.0 | 6.1887 | 2.65774498278682 | 0 | 10 | -1
cN20170331S0222.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.393291443 | 1.036 | 300.0 | 6.1887 | 2.65774498278682 | 0 | 11 | -1
cN20170331S0223.fits | arc,science,tilt | 205.53380833 | 9.47733611 | pisco | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3970400927 | 1.032 | 300.0 | 6.1887 | -0.34225501721318 | 0 | 12 | -1
cN20170331S0206.fits | arc,standard,tilt | 192.84719583 | 12.37277778 | HIP62745 | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.356848156 | 1.029 | 10.0 | 6.1887 | 0.771149555867309 | 0 | 1 | -1
cN20170331S0207.fits | arc,standard,tilt | 192.84719583 | 12.37277778 | HIP62745 | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.357060926 | 1.028 | 10.0 | 6.1887 | -2.22885044413268 | 0 | 2 | -1
cN20170331S0208.fits | arc,standard,tilt | 192.84719583 | 12.37277778 | HIP62745 | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3572769754 | 1.028 | 10.0 | 6.1887 | -2.22885044413268 | 0 | 3 | -1
cN20170331S0209.fits | arc,standard,tilt | 192.84719583 | 12.37277778 | HIP62745 | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.3575292903 | 1.028 | 10.0 | 6.1887 | 0.771149555867309 | 0 | 4 | -1
cN20170331S0246.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4632337656 | 1.052 | 5.0 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0247.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4633936807 | 1.052 | 5.0 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0248.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4635534029 | 1.052 | 5.0 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0249.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4637127393 | 1.053 | 5.0 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0250.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4638740048 | 1.053 | 5.0 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0251.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.464033727 | 1.053 | 5.0 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0252.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4641730017 | 1.053 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0253.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4642846915 | 1.054 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0254.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4643977316 | 1.054 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0255.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.464510193 | 1.054 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0256.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4646238119 | 1.054 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0257.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4647383952 | 1.054 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0258.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4648516282 | 1.055 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0259.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4649642825 | 1.055 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0260.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4650775156 | 1.055 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
cN20170331S0261.fits | pixelflat,trace | 205.53380833 | 9.47733611 | GCALflat | 32/mmSB_G5533 | 0.68arcsec_G5530 | 1,1 | 57843.4651915202 | 1.055 | 0.84 | 6.1887 | 0.0 | 0 | -1 | -1
data end
Reliable image typing and sequence generation based on header cards is not yet implemented for GNIRS. Hence, several modifications to the PypeIt file need to be made before executing run_pypeit. Wavelength solutions can be robustly determined from OH sky lines, which due to flexure, is preferable to using the Ar lamp arcs. Typically the telluric star chosen is bright and will have high signal in a short amount of time resulting in weak sky lines relative to the telluric star itself. For this reason we cannot determine the tilt and and wavelength solutions from the telluric standard (t_exp = 10s), thus, arc and tilt should be removed from the telluric star’s frame types.
Instead we will set its calibration calib ID to match that of the
nearest (in time) science image, which instructs pypeit to use the tilt and
wavelength solution from that sequence for the telluric standard.
Note that even if you don’t plan to telluric correct your data, it is advantageous
to always nevertheless include the telluric star in your PypeIt file.
The reason is that PypeIt uses the telluric star as a crutch for object tracing,
and if you have faint objects this will likely produce better results than if there
is no telluric star in the PypeIt file, in which case PypeIt uses the slit/order boundaries as the
tracing crutch.
The calib ID should be set to the same number for the frames that will be
combined together to generate the calibration image in question. The best
strategy for choosing these frames and setting the associated calib IDs
depends on the exposure time, dither pattern, and the instrument in question.
The example PypeIt file block below is for an ABBA sequence with GNIRS. To
better understand how to set the calib IDs, review how to set the
comb_id and bkg_id for an ABBA sequence, as described
here.
In the edited pypeit file below, we instruct PypeIt to average two A images
together as the science (e.g., frames *216* and *219*) and subtract from
this the average of two B images (e.g., frames *217* and *218*), which
will generate one set of spec2d and spec1d outputs. We do the same thing for the
B images, i.e. combine them and subtract from them the combine of the A images.
This entire ABBA sequence has the same OH lines. If we really want a distinct
wavelength and tilt solution to be generated from the average of the As and
another one to be generated from the average of the Bs, then we would set the
calib IDs to be 0110, where the 0 and 1 are arbitrary numbers (i.e. it could
also be 4554). However, if the instrument is not expected to flex much in an
ABBA sequence, it is actually advantageous to combine the entire ABBA sequence
into one frame for wavelength calibration and tilt generation. The reason
for this is that by averaging four images, the flux from the science object gets
diluted. This is desirable for OH wavelength and tilt calibrations because the
object counts, particularly if the object is bright, is actually a contaminant.
In other words, we extract a 1d OH sky spectrum for the wavelength calibration
and trace the arc lines trajectories across the detector for the tilts.
Obviously a bright object can mess this up. (For example in the optical you
would not turn the arc lamps on and take arcs while simultaneously observing a
star through the slit). In the IR often the sky is so bright relative to the
objects and contaminates so few spatial pixels that this is not much of a worry,
but it still good practice to average away the object flux by combining the
entire ABBA sequence into set of calibration frames. For this reason, we set the
calib IDs to be, e.g., 0 for all the images in a given ABBA sequence. The
calib IDs in the next ABBA sequence is 1, etc.
The edited pypeit file (exactly the one to reduce our example Gemini/GNIRS data set in the PypeIt Development Suite) is:
# Auto-generated PypeIt file
# Tue 18 Dec 2018 17:01:48
# User-defined execution parameters
[rdx]
spectrograph = gemini_gnirs_echelle
#[calibrations]
# [[wavelengths]]
# rms_thresh_frac_fwhm = 0.4
# sigdetect = 5.,5.,6.,6.,5.,7.
# Setup
setup read
Setup A
setup end
# Read in the data
data read
path /Users/joe/python/PypeIt-development-suite/RAW_DATA/gemini_gnirs_echelle/32_SB_SXD/
| filename | date | frametype | target | exptime | dispname | decker | setup | calib | dispangle | idname | comb_id | bkg_id |
| cN20170331S0206.fits | 2017-03-31 | standard | HIP62745 | 10.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 5 | 6 |
| cN20170331S0207.fits | 2017-03-31 | standard | HIP62745 | 10.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 6 | 5 |
| cN20170331S0208.fits | 2017-03-31 | standard | HIP62745 | 10.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 6 | 5 |
| cN20170331S0209.fits | 2017-03-31 | standard | HIP62745 | 10.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 5 | 6 |
| cN20170331S0216.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 1 | 2 |
| cN20170331S0217.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 2 | 1 |
| cN20170331S0218.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 2 | 1 |
| cN20170331S0219.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 0 | 6.1887 | OBJECT | 1 | 2 |
| cN20170331S0220.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 1 | 6.1887 | OBJECT | 3 | 4 |
| cN20170331S0221.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 1 | 6.1887 | OBJECT | 4 | 3 |
| cN20170331S0222.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 1 | 6.1887 | OBJECT | 4 | 3 |
| cN20170331S0223.fits | 2017-03-31 |tilt,arc,science | pisco | 300.0 | 32/mmSB_G5533 | SCXD_G5531 | A | 1 | 6.1887 | OBJECT | 3 | 4 |
| cN20170331S0252.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0253.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0254.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0255.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0256.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0257.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0258.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0259.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0260.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
| cN20170331S0261.fits | 2017-03-31 | trace,pixelflat | GCALflat | 0.84 | 32/mmSB_G5533 | SCXD_G5531 | A | all | 6.1887 | FLAT | -1 | -1 |
data end
Note that the telluric standard has its calib IDs set to all 0s, which
corresponds to the calib ID of the nearest science ABBA sequence in time.
Try pulling the data from the PypeIt Development Suite (see Raw Data) and reducing it!