.. _example: Examples ======== On-the-fly run -------------- Example data are stored in ./gsf/examples/ .. code-block:: bash python run_gsf.py test.input If you need a new config file (\*.input), execute .. code-block:: bash python get_configfile.py Execution flag ~~~~~~~~~~~~~~ - 0: Generating templates at z=0 (takes a while if MILES). Start from here if parameter in config file is changed. Then go to 1. (From ver1.6, multiprocessing can be used to generate z=0 templates. See below.) - 1: Redshift template to z=ZGAL, and prepare mock photometry that matches to the input filters and spectra, using pre-existing z=0 templates (from step0). Then go to 2. - 2: Fitting part, using pre-existing z=z_input templates (from Step1). If ZVIS==1, gsf will ask you if the initial redshift fit is reasonable. Then go to 3. - 3: Only plot SFH and SED using existing result files. - 6: Plot physical parameters and SED (optional). Appendicies ----------- A. Specify target id ~~~~~~~~~~~~~~~~~~~~ You can speficy the target id from the command line. This way, you would not need to make a bunch of config files for each target. .. code-block:: bash python run_gsf.py test.input --id Then gsf will look into the broadband catalog (``BB_CAT``; :doc:`parameters`) and identify object with the same id. Redshift has to be either specified in the config file (``ZGAL``; :doc:`parameters`) or included in the same broadband catalog (column named ``redshift``). B. Multi-processing to generate z=0 templates ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Since step0 can take time to complete, multiprocessing may help. .. code-block:: bash python get_templates_mp.py test.input --z This does not complete the following steps (1, 2, 3, 6). Other examples -------------- Also see: - `NIRISS fitting notebook `__.