Automated sorting of Keck/NIRES frames by instrument configuration

Version History

Version

Author

Date

PypeIt

1.0

Debora Pelliccia

11 Nov 2022

1.11.1dev

1.1

Debora Pelliccia

24 Mar 2023

1.12.2dev

Basics

To prepare for the data reduction, PypeIt automatically associates fits files to specific Frame Types (see Automated typing of NIRES frames) and collects groups of frames in unique instrument configurations. This is performed by the pypeit_setup script, which sorts the frames and write a PypeIt Reduction File for each unique configuration. See Setup.

NIRES configuration identification

The instrument configurations are determined by pypeit.metadata.PypeItMetaData.unique_configurations(), using a combination of header keys. However, since NIRES has a fixed configuration, the only header key used to identify the desired configuration is INSTR, which corresponds to the PypeIt fitstbl key dispname. INSTR can be equal to spec when NIRES is used in spectroscopy mode, or imag if it is used in imaging mode. Therefore, for our purpose of spectroscopic reduction, only one configuration is available.

NIRES calibration groups

PypeIt uses the concept of a “calibration group” to define a complete set of calibration frames (e.g., arcs, flats) and the science frames to which these calibration frames should be applied.

By default, pypeit_setup uses the setup identifier (e.g., A,B,C,D…) to assign frames to a single calibration group. Since NIRES has only one configuration, i.e., ony one setup identifier, all the frames would have the same PypeIt keyword calib. However, since it is likely, during an observing night, to observe different targets, PypeIt automatically assigns different calib values to the NIRES science frames of different targets. This is done because PypeIt currently only uses OH sky lines in the science frames to perform the wavelength calibration (instead of using the actual arc frames), therefore having different calib values for different targets will allow each target to have its own wavelength calibration. The standard frames, on the contrary, by default will not be used as arc/tilt frames since they are generally taken with short exposures (i.e., the sky line may not be bright enough), therefore PypeIt will assign to them the calib value of the closest science frames, i.e., they will share the wavelength calibration with the science frame. Finally, since usually only one set of flat observations are taken for the different targets, PypeIt automatically sets calib = all for the flat frames, so that it can use them for the calibration of all the different targets. See Calibration Groups. The user can always edit the PypeIt Reduction File to assign specific calibration frames to specific science frames using the data in the calib column of the Data Block.

NIRES combination and background groups

PypeIt is able to reduce data taken with a nodding pattern, by grouping the science frames into combination and background groups. Science frames that should be combined together are assigned the same combination ID (comb_id), while a background ID (bkg_id) identifies frames that are used as background images. Frames with the same value of bkg_id will be combined together. The values of comb_id and bkg_id are provided in the PypeIt Reduction File as two columns in the Data Block, so that users can modify them according to their preferred reduction. See more detail in A-B image differencing.

For NIRES, PypeIt attempts to automatically assign comb_id and bkg_id to the science frames, by using the information on the nodding pattern available in the files headers. Specifically, the keywords used are:

fitstbl key

Header Key

dithoff

YOFFSET

dithpat

no Key

dithpos

DPATIPOS

The header key that provides information on the dither positions is DPATIPOS, which defines those as positions 1, 2, 3, or 4 of a given dither pattern (DPATNAME). PypeIt, using the information from both DPATNAME and DPATIPOS, expresses the dither positions (dithpat) as A, B, or C frames. dithoff, dithpat, and dithpos are provided in the Data Block.

The dither patterns parsed by PypeIt are: “ABAB”, “ABBA”, “ABBAprime”, “ABpat”, “ABC” see examples below. comb_id and bkg_id will not be assigned if:

  • dithoff is zero for every frames of a dither sequence;

  • dithpat is NONE or MANUAL, or is none of the above patterns.

In these cases, the user should manually input the comb_id and bkg_id values.

If the observations were taken with a “ABpat” dithpat the Data Block will look like:

            filename |        frametype | ... | dithpat | dithpos | dithoff | frameno | calib | comb_id | bkg_id
s181127_0076.fits.gz | arc,science,tilt | ... |   ABpat |       A |     2.5 |      76 |     1 |      57 |     58
s181127_0077.fits.gz | arc,science,tilt | ... |   ABpat |       B |    -2.5 |      77 |     1 |      58 |     57

where the science frames have different comb_id (i.e., no frames will be combined), while the bkg_id for the A frame is equal to the comb_id of the B frame and vice versa. This combination of comb_id and bkg_id will create two reduced frames:

s181127_0076.fits.gz - s181127_0077.fits.gz (A-B)
s181127_0077.fits.gz - s181127_0076.fits.gz (B-A)

If the observations were taken with an “ABAB”, “ABBA”, or “ABBAprime” dithpat, the frames in the same dither sequence will be combined. Here is an example for “ABBA”:

            filename |        frametype | ... | dithpat | dithpos | dithoff | frameno | calib | comb_id | bkg_id
s181127_0020.fits.gz | arc,science,tilt | ... |    ABBA |       A |     2.5 |      20 |     1 |       5 |      6
s181127_0021.fits.gz | arc,science,tilt | ... |    ABBA |       B |    -2.5 |      21 |     1 |       6 |      5
s181127_0022.fits.gz | arc,science,tilt | ... |    ABBA |       B |    -2.5 |      22 |     1 |       6 |      5
s181127_0023.fits.gz | arc,science,tilt | ... |    ABBA |       A |     2.5 |      23 |     1 |       5 |      6

This combination of comb_id and bkg_id will create two reduced frames:

s181127_0020.fits.gz+s181127_0023.fits.gz - s181127_0021.fits.gz+s181127_0022.fits.gz (AA-BB)
s181127_0021.fits.gz+s181127_0022.fits.gz - s181127_0020.fits.gz+s181127_0023.fits.gz (BB-AA)

Lastly, if observations were taken with an “ABC” dithpat, where the A frame is taken at the center of the slit (dithoff = 0) while the B and C frames are taken at a +/- offset, the B frames will be used as background image for the frame taken at the center. Here is an example:

              filename |        frametype | ... | dithpat | dithpos | dithoff | frameno | calib | comb_id | bkg_id
NR.20181126.38930.fits | arc,science,tilt | ... |     ABC |       A |     0.0 |      31 |     1 |       1 |      2
NR.20181126.39604.fits | arc,science,tilt | ... |     ABC |       B |     5.0 |      32 |     1 |       2 |      3
NR.20181126.40277.fits | arc,science,tilt | ... |     ABC |       C |    -5.0 |      33 |     1 |       3 |      2

This combination of comb_id and bkg_id will create three reduced frames:

NR.20181126.38930.fits - NR.20181126.39604.fits (A-B)
NR.20181126.39604.fits - NR.20181126.40277.fits (B-C)
NR.20181126.40277.fits - NR.20181126.39604.fits (C-B)

Testing

  • Requirement PN-15 states: “As a user, I expect the pipeline to recognize dither positions from the header.”

  • Requirement PM-16 states: “As a user, I expect the pipeline to associate a pair of observations for sky subtraction and also allow for a manual selection and association. ABBA should associate A-B and B-A.”

PypeIt meets these requirements in the majority of use cases.

The test used to demonstrate that PN-14 is satisfied (Automated typing of NIRES frames) is also relevant here since it shows that PypeIt correctly identifies NIRES data frame types and associates them with a single configuration, all written to a single pypeit file.

To test that PypeIt can successfully assign comb_id and bkg_id to science frames following the information on the dither pattern, we have added the test_setup_keck_nires_comb test to ${PYPEIT_DEV}/unit_tests/test_setups.py.

To run this test:

cd ${PYPEIT_DEV}/unit_tests
pytest test_setups.py::test_setup_keck_nires_comb -W ignore

The test requires that you have downloaded the PypeIt PypeIt Development Suite and defined the PYPEIT_DEV environmental variable that points to the relevant directory.

The algorithm for this test is run on three datasets, ‘ABpat_wstandard’, ‘ABC_nostandard’, ‘ABBA_nostandard’, and is as follows:

  1. Collect the names of all files from the following directory:

${PYPEIT_DEV}/RAW_DATA/keck_nires/{dataset}

  1. Use PypeItSetup to automatically identify the configurations for these files.

  2. Check that the code found one setup.

  3. Read in a pre-generated .pypeit file with the correct calibration, combination, and background ids.

5. Check that the calib, comb_id, and bkg_id values for science frames in the automatically identified files are the same as the ones in the pre-generated .pypeit file.

The dither sequences used here are: “ABBA”, “ABC”, “ABpat”. Because this test is now included in the PypeIt Unit Tests (GitHub CI), these configuration checks are performed by the developers for every new version of the code.