The README should describe how to run PySE:
- From the command line -
hatch run pyse [--options] - in combination with a config.toml, so some example config.toml will need to be provided in order to see how command line overrides config.toml settings.
- From an iPython shell. It should include the on-the-fly creation of Conf object, which should again override
config.toml. The use of the beam 3-tuple should also be demonstrated.
- For vectorized source processing, i.e. with
conf.image.vectorized==True and conf.image.deblend_nthresh==0 show PySE's speed (using %timeit), e.g. on an artificial 4K *4K image with over 100,000 sources, from an iPython shell. Show that a Pandas df is returned and the descriptions of its columns - not just the column headers - can be shown using describe_dataframe_columns.
The README should describe how to run PySE:
hatch run pyse [--options]- in combination with aconfig.toml, so some exampleconfig.tomlwill need to be provided in order to see how command line overridesconfig.tomlsettings.config.toml. The use of thebeam3-tuple should also be demonstrated.conf.image.vectorized==Trueandconf.image.deblend_nthresh==0show PySE's speed (using %timeit), e.g. on an artificial 4K *4K image with over 100,000 sources, from an iPython shell. Show that a Pandas df is returned and the descriptions of its columns - not just the column headers - can be shown usingdescribe_dataframe_columns.