Tilts

Overview

This file describes the data model for the Tilts.

The images are written to disk as a multi-extension FITS file prefixed by Tilts in the Calibrations/ folder. See Calibration Frame Naming for the naming convention.

Inspecting

To examine the quality of this step the user can run the pypeit_chk_tilts script, or inspect the PNG files generated by the code. PypeIt QA describes how to access them.

pypeit_chk_tilts

There are currently 2 options for viewing the traced and 2D fitted tilts on the image used to construct them. Each uses the pypeit_chk_tilts script.

ginga

This is the default mode when executing, e.g.:

pypeit_chk_tilts Calibrations/Tilts_A_0_DET01.fits

The Tiltimg image is shown in ginga with the traced and 2D fitted tilts over-plotted.

Here is a zoom-in screen shot for the shane_kast_red spectrograph.

You want to check that the traced and 2D fitted tilts overlay well on the arc/OH lines.

matplotlib

To avoid ginga, use the –mpl flag:

pypeit_chk_tilts Calibrations/Tilts_A_0_DET01.fits --mpl

QA PNG files

There are 3 PNG files generated per slit:

2D Arc Tilts

This QA shows the spectral vs. spatial positions of all the lines traced by the code. Here is an example from shane_kast_red:

Here is what you hope to see in this QA:

RMS < 0.1

Very few red points

The red points are mainly at the very edges of the black lines

The black points span across the full detector

On the last point, if only a smaller portion of the detector is covered, the code is extrapolating. Indeed, the example above only shows outputs down to ~480 Spectral Pixel, which is not ideal. Of course, this will be the case for spectrographs that have data which does not span the full detector.

Spat Tilts

This QA examines the residuals of (tilt position - model) as a function of spatial offset along the slit. Here is an example from shane_kast_red:

One hopes to see small residuals without any substantial spatial dependence. But, it is common for there to be significant residuals at the edges of the slit (as in this example).

Spec Tilts

This QA examines the residuals of (tilt position - model) as a function of spetral offset along the slit. Here is an example from shane_kast_red:

One hopes to see:

The black points scattering about 0

The orange and green points not too far above 0

Troubleshooting

If one or more of your image appears to be in err, here are the things to consider:

Insufficient Lines

Todo

Explain how to add more

Current WaveTilts Data Model

Internally, the image is held in pypeit.wavetilts.WaveTilts which subclasses from pypeit.datamodel.DataContainer.

The datamodel written to disk is:

Version 1.2.0

HDU Name	HDU Type	Data Type	Description
`PRIMARY`	astropy.io.fits.PrimaryHDU	…	Empty data HDU. Contains basic header information.
`TILTS`	astropy.io.fits.BinTableHDU	…	Tilts data; see `WaveTilts`.

TILTS content is:

Version: 1.2.0

Attribute	Type	Array Type	Description
`PYP_SPEC`	str		PypeIt spectrograph name
`bpmtilts`	numpy.ndarray	numpy.integer	Bad pixel mask for tilt solutions. Keys are taken from SlitTraceSetBitmask
`coeffs`	numpy.ndarray	numpy.floating	2D coefficents for the fit on the initial slits. One set per slit/order (3D array).
`func2d`	str		Function used for the 2D fit
`nslit`	int		Total number of slits. This can include masked slits
`slits_filename`	str		Path to SlitTraceSet file. This helps to find the Slits calibration file when running pypeit_chk_tilts()
`spat_flexure`	float		Flexure shift from the input TiltImage
`spat_id`	numpy.ndarray	numpy.integer	Slit spat_id
`spat_order`	numpy.ndarray	numpy.integer	Order for spatial fit (nslit)
`spec_order`	numpy.ndarray	numpy.integer	Order for spectral fit (nslit)
`tilt_traces`	astropy.table.table.Table		Table with the positions of the traced and fitted tilts for all the slits. see `make_tbl_tilt_traces()` for more details.
`tiltimg_filename`	str		Path to Tiltimg file. This helps to find Tiltimg file when running pypeit_chk_tilts()