eumap.gapfiller.time_first_space_later

time_first_space_later(fn_files=None, data=None, time_strategy=<class 'eumap.gapfiller.TMWM'>, time_args={}, space_strategy=<class 'eumap.gapfiller.InPainting'>, space_args={}, space_flag_val=100)[source]

Helper function to gapfill all the missing pixels using first a temporal strategy (TMWM, TLI, SSA) and later a spatial strategy (InPainting).

Parameters

  • fn_files (Optional[List]) – Raster file paths to be read and gapfilled.

  • data (Optional[array]) – 3D array where the last dimension is the time.

  • time_strategy (ImageGapfill) – One of the implemented temporal gapfilling approaches.

  • time_args (set) – A set of parameters for the temporal gapfilling strategy

  • space_strategy (ImageGapfill) – One of the implemented spatial gapfilling approaches.

  • space_args (set) – A set of parameters for the spatial gapfilling strategy.

  • space_flag_val – The flag value used to indicate which pixels were gapfilled by the spatial gapfilling strategy.

Examples

>>> from eumap import gapfiller
>>>
>>> # For a 4-season time series
>>> tfsl = gapfiller.time_first_space_later(
>>>  fn_files = fn_rasters,
>>>  time_strategy = gapfiller.TMWM,
>>>  time_args = { 'season_size': 4 },
>>>  space_strategy = gapfiller.InPainting,
>>>  space_args = { 'space_win': 10 }
>>> )
>>>
>>> fn_rasters_tfsl  = tfsl.save_rasters('./gapfilled_tmwm_inpaint', dtype='uint8', fn_files=fn_rasters)