parse_visits

grizli.pipeline.auto_script.parse_visits(field_root='', RAW_PATH='../RAW', use_visit=True, combine_same_pa=True, combine_minexp=2, is_dash=False, filters=['F410M', 'F467M', 'F547M', 'F550M', 'F621M', 'F689M', 'F763M', 'F845M', 'F200LP', 'F350LP', 'F435W', 'F438W', 'F439W', 'F450W', 'F475W', 'F475X', 'F555W', 'F569W', 'F600LP', 'F606W', 'F622W', 'F625W', 'F675W', 'F702W', 'F775W', 'F791W', 'F814W', 'F850LP', 'G800L', 'F098M', 'F127M', 'F139M', 'F153M', 'F105W', 'F110W', 'F125W', 'F140W', 'F160W', 'G102', 'G141'], max_dt=1000000000.0, visit_split_shift=1.5)[source]

Organize exposures into “visits” by filter / position / PA / epoch

Parameters:
field_root : str

Rootname of the {field_root}_visits.npy file to create.

RAW_PATH : str

Path to raw exposures, relative to working directory

use_visit, max_dt, visit_split_shift : bool, float, float

See parse_flt_files.

combine_same_pa : bool

Combine exposures taken at same PA/orient + filter across visits

combine_minexp : int

Try to concatenate visits with fewer than this number of exposures

filters : list

Filters to consider

Returns:
visits : list

List of “visit” dicts with keys product, files, footprint, etc.

groups : list

Visit groups for direct / grism

info : Table

Exposure summary table