This tutorial covers the basics of reducing GMOS (Gemini Multi-Object Spectrographs) data using DRAGONS.
Data reduction with DRAGONS can be done in two different ways:
- From the terminal using the command line.
- From Python using the DRAGONS classes and functions.
We show how to run the same reduction using both methods.
More examples will be added in the future.
The next two sections explain what are the required software and the data set that we use throughout the tutorial.
1.1. Software Requirements¶
Before you start, make sure you have DRAGONS properly installed and configured on your machine. You can test that by typing the following commands:
$ conda activate dragons $ python -c "import astrodata"
dragons is the name of the conda environment where DRAGONS should
be installed. If you have an error message, make sure:
- Conda is properly installed;
- A Conda Virtual Environment is properly created and is active;
- DRAGONS was successfully installed within the Conda Virtual Environment;
1.2. Downloading the tutorial datasets¶
All the data needed to run this tutorial are found in the tutorial’s data packages. We have split the data packages per example to keep the size of each package within some reasonable limit.
- Example 1: gmosim_tutorial_datapkg-starfield-v1.tar
- Example 2: gmosim_tutorial_datapkg-separateCCDs-v1.tar
Download one or several packages and unpack them somewhere convenient.
cd <somewhere convenient> tar xvf gmosimg_tutorial_datapkg-starfield-v1.tar tar xvf gmosimg_tutorial_datapkg-separateCCD-v1.tar bunzip2 gmosimg_tutorial/playdata/example*/*.bz2
The datasets are found in the subdirectory
gmosimg_tutorial/playdata/example#, and we
will work in the subdirectory named
All the raw data can also be downloaded from the Gemini Observatory Archive. Using the tutorial data package is probably more convenient but if you really want to learn how to search for and retrieve the data yourself, see the step-by-step instructions for Example 1 in the appendix, Downloading from the Gemini Observatory Archive.