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readme.txt
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readme.txt
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###############
1. Setup of Python environment.
You can do it in three ways:
1.A. Use the requirements.txt file to build/modify your own env.
1.B. Use the following one-liner to create a seperate conda environment.
conda create -n spectracular -c conda-forge -c astropy 'tqdm>=4.31' 'specutils==0.2.2' 'scipy>=1.1' 'python>=3.6' 'numpy>=1.15' 'matplotlib>=3.0.2' 'astropy>=3.1.1' 'pyyaml>=3.13'
1.C. Use the environment.yml file with conda to skip the resolving step.
conda env create -f environment.yml
###############
2. Get additional data – Coelho models – and free space.
If you wish to use Spectracular without its fitting feature, skip this step.
We require you to download and unpack a large archive of high-res models:
http://specmodels.iag.usp.br/fits_search/compress/s_coelho14_highres.tgz
Spectracular also requires another ~5 GB to process these models in its own way.
###############
3. Fill in the spectracular/config.py file.
Provide full paths (ended with '/' character) to:
* a directory containing the unpacked s_coelho14_highres/ catalog;
* a directory where Spectracular can put its processing results (another ~5 GB);
* the provided SVO filter profiles;
* additional SVO filter profiles, if you wish to use other than provided.
###############
4. Try both examples!
Or one of them, if you skipped the step no. 2.
First, run the example-XSHOOTER-V.py script, which uses Spectracular's core code stucture (without its fitting features).
Next, try example-modelling.py. The first run might take additional 5–10 minutes to complete (and take these ~5 GB of your free space mentioned above).
###############
5. Write your own scripts, provide other data.
Have fun.