The Goodman Spectroscopic Pipeline is designed to be simple to use, however simple does not always is the best case for everyone, thus The Goodman Pipeline is also flexible.

Getting Help.

This manual is intended to be the prefered method to get help. However the quickest option is using -h or --help

redccd --help

Will print the list of arguments along with a quick explanation and default values.

It is the same for redspec

redspec --help

Prepare Data for Reduction

If you did a good job preparing and doing the observation this should be an easy step, either way, keep in mind the following steps.

  • Remove all focus sequence.
  • Remove all target acquisition or test frames.
  • Using your observation’s log remove all unwanted files.
  • Make sure all data has the same gain (GAIN) and readout noise (RDNOISE)
  • Make sure all data has the same Region Of Interest or ROI (ROI).

The pipeline does not modify the original files unless there are problems with fits compliance, is never a bad idea to keep copies of your original data in a safe place.

Processing your 2D images

It is the first step in the reduction process, the main tasks are listed below.

  • Create master bias
  • Create master flats
  • Apply Corrections:
    • Overscan
    • Trim image
    • Detect slit and trim out non-illuminated areas
    • Bias correction
    • Normalized flat field correction
    • Cosmic ray rejection


Some older Goodman HTS data has headers that are not FITS compliant, In such cases the headers are fixed and that is the only modification done to raw data.

The 2D images are initially reduced using redccd. You can simply move to the directory where your raw data is located and do:


Though you can modify the behavior in several ways.

Running redccd will create a directory called RED where it will put your reduced data. If you want to run it again it will prevent you from accidentally removing your already reduced data unless you use --auto-clean this will tell the pipeline to delete the RED directory and start over.

redccd --auto-clean

A summary of the most important command line arguments are presented below.

  • --cosmic <method> Let you select the method to do Cosmic Ray Removal.
  • --debug Show extended messages and plots of intermediate steps.
  • --flat-normalize <method> Let you select the method to do Flat Normalization.
  • --flat-norm-order <order> Set order for the model used to do Flat Normalization. Default 15.
  • --ignore-bias Ignores the existence or lack of BIAS data.
  • --ignore-flats Ignores the existence or lack of FLAT data.
  • --raw-path <path> Set the directory where the raw data is located, can be relative.
  • --red-path <path> Set the directory where the reduced data will be stored. Default RED.
  • --saturation <saturation> Set the saturation level. Flats exceeding the saturation level will be discarded. Default 65.000 ADU.

This is intended to work with spectroscopic and imaging data, that it is why the process is split in two.

Extracting the spectra

After you are done Processing your 2D images it is time to extract the spectrum into a wavelength-calibrated 1D file.

The script is called redspec. The tasks performed are the following:

  • Classifies data and creates the match of OBJECT and COMP if it exists.
  • Identifies targets
  • Extracts targets
  • Saves extracted targets to 1D spectrum
  • Finds wavelength solution automatically
  • Linearizes data
  • Saves wavelength calibrated file

First you have to move into the RED directory, this is a precautionary method to avoid unintended deletion of your raw data. Then you can simply do:


And the pipeline should work its magic, though this might not be the desired behavior for every user or science case, we have implemented a set of command line arguments which are listed below.

  • --data-path <path> Folder were data to be processed is located. Default is current working directory.
  • --proc-path <path> Folder were processed data will be stored. Default is current working directory.
  • --search-pattern <pattern> Prefix for picking up files. Default cfzsto. See File Prefixes.
  • --extraction <method> Select the Extraction Methods. The only one implemented at the moment is fractional .
  • --reference-files <path> Folder where to find reference-lamps
  • --debug Shows extended and more messages. Also show plots of intermediate steps.
  • --max-targets <value> Maximum number of targets to detect in a single image. Default is 3.
  • --save-plots Save plots as described in Plotting & Save
  • --plot-results Show plots during execution.

The mathematical model used to define the wavelength solution is recorded in the header even though the data has been linearized for record purpose.

Description of custom keywords

The pipeline adds several keywords to keep track of the process and in general for keeping important information available. The following table gives a description of all the keywords added by The Goodman Pipeline, though not all of them are added to all the images.

General Purpose Keywords

These keywords are used for record purpose, except for GSP_FNAM which is used to keep track of the file name.

General purpose keywords, added to all images at the moment of the first read.
Keyword Purpose
GSP_VERS Pipeline version.
GSP_ONAM Original file name, first read.
GSP_PNAM Parent file name.
GSP_FNAM Current file name.
GSP_PATH Path from where the file was read.
GSP_TECH Observing technique. Imaging or Spectroscopy.
GSP_DATE Date of processing.
GSP_OVER Overscan region.
GSP_TRIM Trim section.
GSP_SLIT Slit trim section. From slit-illuminated area.
GSP_BIAS Master bias file used.
GSP_FLAT Master flat file used.
GSP_NORM Master flat normalization method.
GSP_COSM Cosmic ray rejection method.
GSP_WRMS Wavelength solution RMS Error.
GSP_WPOI Number of points used to calculate RMS Error.
GSP_WREJ Number of points rejected from RMS Error Calculation.
GSP_DCRR Reference paper for DCR software (cosmic ray rejection).

Non-linear wavelength solution

Since writing non-linear wavelength solutions to the headers using the FITS standard (reference) is extremely complex and not necessarily well documented, we came up with the solution of simply describing the mathematical model from astropy’s modeling. This allows for maintaining the data untouched while keeping a reliable description of the wavelength solution.

The current implementation will work for writting any polinomial model. Reading is implemented only for Chebyshev1D which is the model by default.

Keywords used to describe a non-linear wavelength solution.
Keyword Purpose
GSP_FUNC Name of mathematical model from astropy’s modeling
GSP_ORDR Order of the model used.
GSP_NPIX Number of pixels.
GSP_C000 Value of parameter c0.
GSP_C001 Value of parameter c1.
GSP_C002 Value of parameter c2. This goes on depending the order.

Combined Images

Every image used in a combination of images is recorded in the header of the resulting one. The order does not have importance but most likely the header of the first one will be used.

The combination is made using the combine() method with the following parameters

  • method='median'
  • sigma_clip=True
  • sigma_clip_low_thresh=1.0
  • sigma_clip_high_thresh=1.0

At this moment these parameters are not user-configurable.

Keywords that list all the images used to produce a combined image.
Keyword Purpose
GSP_IC01 First image used to create combined.
GSP_IC02 Second image used to create combined.

Detected lines

The reference lamp library maintains the lamps non-linearized and also they get a record of the pixel value and its equivalent in angstrom. In the following table a three-line lamp is shown.

Description of all the keywords used to list lines in lamps in Pixel and Angstrom.
Keyword Purpose
GSP_P001 Pixel value for the first line detected.
GSP_P002 Pixel value for the second line detected.
GSP_P003 Pixel value for the third line detected.
GSP_A001 Angstrom value for the first line detected.
GSP_A002 Angstrom value for the second line detected.
GSP_A003 Angstrom value for the third line detected.

Cosmic Ray Removal

The argument --cosmic <method> has four options but there are only two real methods.

default (default):

Different methods work different for different binning. So if <method> is set to default the pipeline will decide as follows:

dcr for binning 1x1

lacosmic for binning 2x2 and 3x3 though binning 3x3 has not being tested.


It was already said that this method work better for binning 1x1. More information can be found on Installing DCR. The disadvantages of this method is that is a program written in C and it is required to write the file to the disk, process it and read it back again. Still is faster than lacosmic.

The parameters for running dcr are written in a file called dcr.par a lookup table and a file generator have been implemented but you can parse custom parameters by placing a dcr.par file in a different directory and point it using --dcr-par-file <path>.

This is the preferred method for files with binning 2x2 and 3x3. This is the Astroscrappy’s implementation and is run with the default parameters. Future versions might include some parameter adjustment.
Skips the cosmic ray removal process.

Asymetric binnings have not been tested but the pipeline only takes in consideration the dispersion axis to decide. This does not mean that the spatial binning does not impact the performance of any of the methods, we just don’t know it yet.

Flat Normalization

There are three possible <method> (s) to do the normalization of master flats. For the method using a model the default model’s order is 15. It can be set using --flat-norm-order <order>.

Calculates the mean of the image using numpy’s mean() and divide the image by it.
simple (default):
Collapses the master flat across the spatial direction, fits a Chebyshev1D model of order 15 and divide the full image by this fitted model.
Fits a Chebyshev1D model to every line/column (dispersion axis) and divides it by the fitted model. This method takes too much to process and it has been left in the code for experimentation purposes only.

Extraction Methods

The argument --extraction <method> has two options but only fractional is implemented.

Fractional pixel extraction differs from a simple and rough extraction in how it deals with the edges of the region. pipeline.core.core.extract_fractional_pixel()
Unfortunately this method has not been implemented yet.

File Prefixes

There are several ways one can do this but we selected adding prefixes to the file name because is easier to add and also easy to filter using a terminal, for instance.

ls cfzsto*fits

or in python

import glob

file_list = glob.glob('cfzsto*fits')

So what does all those letter mean? Here is a table to explain it.

Characters and meaning of prefixes
Letter Meaning
o Overscan Correction Applied
t Trim Correction Applied
s Slit trim correction applied
z Bias correction applied
f Flat correction applied
c Cosmic rays removed
e Spectrum extracted to 1D
w 1D Spectrum wavelength calibrated

So, for an original file named file.fits:


Means the file have been overscan corrected while


Means the spectrum has been extracted to a 1D file but the file has not been flat fielded (f missing).

Ideally after running redccd the file should be named:


And after running redspec: