LightCurve Refactor Proposal

A Proposal to Refactor LightCurve

Abstract:

We all knew this day was coming, LightCurve cannot escape the spotlight any longer. LightCurve moves away from conditional dispatch to a Factory based creation system so that it behaves like Map.

Reasoning:

This proposal makes an API change, which will move LightCurve to follow the API of the Map submodule. This will provide end users a consistent interface submodules and allow for cleaner and easier to read code for developers, much like the map refactor did for the map submodule.

Relevant PR’s:

PR #729 The update to the base factory class, currently used for Map.

Implementation:

A factory instance (as proposed in #729) called LightCurve will be available in the top level of the sunpy.lightcurve which will allow creation of all registered LightCurve subclasses with the following API:

def LightCurve(filename=None, source=None, dates=None, *kwargs):
    """
    Parameters
    ----------------
    filename: string or File
        A file to read.
    source: string or iterable of strings
        A string identifier for a registered subclass, matched by that subclasses `_is_source_for` method.
    dates: DateTime instance or iterable of.
        The time range to create the lightcurve in between.
    
    All other keywords are passed to subclass
    """

Examples:

• my_lc = LightCurve(source=’goes’, dates=[datemin,datemax])
• my_lc = LIghtCurve(source=’goes’, dates=datetime)#Downloads a standard amount of time?
• my_lc = LightCurve(source=’goes’, filename.csv)
• my_lc = LightCurve(filename.fits)
• my_lc = LightCurve(url) # autodetect
• my_lc = LightCurve(source=’goes’, url)
• my_lc = LightCurve(source=’lyra’, dates=[min,max], events=[x,y,z])
• my_goes, my_lyra = LightCurve(source=[‘goes’,’lyra’], dates=[min,max])

LightCurve parsing order:

1. URL -> resolve to file
   1. Filename:
      1. Attempt to read with sunpy.io: (Like Map())
         1. Parse metadata to _is_source_for and find relevant subclass
         2. Create that LightCurve.
      2. Match ‘source’ flag to subclass and get subclass to read file:
         1. return data, meta pair, create instance.
      3. fail.
2. Daterange:
   1. Match ‘source’ flag to subclass and get URI
   2. Download data (support multiple files)
   3. Attempt read with sunpy.io, parse (data, meta) to subclass __init__.
   4. Attempt to read with subclass.
   5. fail
3. Other kwargs are processed and passed to subclass class method for returning (data, meta).

Required class methods:

1. parse specific data files that cannot be read by the sunpy.io module, i.e. CSV or ASCII files.
2. Parse input to the LightCurve factory such as date range and return a file download URI.
3. Provide a _is_source_for which if possible auto detects the data type from a (data, meta) pair, and also matches string names for the subclass i.e. 'goes' or 'lyra', which will be passed into the factory to specify type for download etc.

Backwards Compatibility:

None, due to the current implementation of LightCurve it will be very hard to maintain backwards compatibility. It may be possible to implement a .create() method that calls the Factory, however I would not recommend it.

#Notes:

• Make a check that the index column of the LightCurve is actually a time.
• Since there is no standard for storing time-series data (FITS files have a standard) then we can expect that each instrument subclass will be highly tailored to however the data is stored.
• Do we still want to use pandas time-series to store the data?