.. index:: spec1d
A primary data product for PypeIt are 1D, calibrated spectra for extracted sources. The most fundamental spectrum may be described by two arrays: flux, wavelength. These together with an error array are the minimal output for even the Quick reduction mode. There are, however, several methods of extraction, calibration, etc. which yield various data products.
To allow the inclusion of multiple combinations of arrays, the standard format in PypeIt for spec1D output per object is a binary FITS table. The types of spectral arrays that may be outputted are:
| Type | Default Unit | Description | Comments |
|---|---|---|---|
| WAVE | Angstrom | Calibrated wavelenth of each pixel | Vacuum, heliocentric corrected |
| COUNTS/FLUX | \rm e^- \, or \, f_\lambda | Integrated across the spatial profile | Not normalized by exposure time |
| VAR/FVAR | (\rm e^-)^2 \, or \, (f_\lambda)^2 | Variance in the counts | 0 or negative values indicate masked pixels |
| MASK | -- | Bit-wise mask values | See :doc:`ref </mask>` for a description |
| SKY | \rm e^-/pixel \, or \, \mu | Sky model spectrum | |
| TRACE | pixel | Best centroid of the object along the detector |
Because there are several modes of extraction in PypeIt, there may be multiple outputs of the spectral arrays. These are then prefixed by the extraction mode.
| Extraction Mode | Description |
|---|---|
| BOXCAR | Top-hat extraction around the trace. The precise window used is defined by the BOXCAR_APERTURE, in pixels. |
| OPTIMAL | Standard Horne algorithm for extraction using the fitted spatial profile. An estimate of this profile is given by OBJ_FWHM |
Therefore, the integrated counts for a boxcar extraction are given by the BOXCAR_COUNTS array with variance BOXCAR_VAR.
In addition to the spectral arrays, a number of measurements are included in the binary FITS tables. This includes identifiers for the object, which may locate the object on the detector. A complete listing is now given:
| Keyword | Type | Description |
|---|---|---|
| DET_ID | int | Detector Identifier |
| SLIT_ID | int | Slit Identifier; given in fractional units of the detector |
| OBJ_ID | int | Object Identifier; given in fractional units of the slit |
| RAW_FILE | str | Name of the raw data file |
PypeIt will generate a single HDF5 file for each science exposure. The HDF5 file contains the groups: header, meta, boxcar and optimal. Each group has its respective datasets:
| Group | Description |
|---|---|
| Meta | Meta is an astropy Table of N rows, corresponding to the N objects/spectra extracted from the exposure. The table contains the RA, DEC, object ID, slit ID, detector number, science index, FWHM (spatial resolution in arcseconds), resolution (spatial resolution in lambda/Dlambda), and xslit. |
| Header | Header contains the original header information as saved on the telescope. |
| Boxcar | Boxcar contains N datasets, corresponding to the N objects/ spectra extracted via boxcar extraction. |
| Optimal | Optimal contains N datasets, correspodning to the N objects/ spectra extracted via optimal extraction. If one of the N objects were not extracted optimally, its dataset will still exist, but be empty. |
If one uses the default :ref:`outputs-compactness-compact` mode for outputs, a single multi-extension FITS file will be generated that contains the binary FITS tables for each extracted source. To ease access to the individual tables, the FITS header contains the following cards:
| Header Card | Type | Example | Description |
|---|---|---|---|
| NOBJ | int | 2 | Number of extracted sources |
| ID_#### | int | 02334223 | ID for the source (DET_ID, SLID_ID, OBJ_ID) |
| S2N_#### | float | 3.23 | Median S/N of of the spectrum |
In addition, a reproduction of nearly the entire Header from the raw FITS file is provided, modulo the header cards that describe the data type and size (e.g. NAXIS).