FitsManager

class prose.FitsManager

Object to parse and retrieve FITS files from folder and sub-folders

This object scans files in a folder and stores the data in a mysql database for conveniance (but all products can be accessed without knowledge of the SQL language)

Parameters:

• folder (str) – path of the folder to parse (or list of folders as of prose 2.0.1)

• depth (int, optional) – maxiumum depth of the sub-folders to explore, by default 0

• hdu (int, optional) – by default 0

• extension (str, optional) – by default “.f*ts*”

• file (_type_, optional) – _description_, by default None

• batch_size (bool or int, optional) –

  • if False: update database after all FITS files are parsed

  • if int: update database every time batch_size FITS files are parsed

  by default False

• telescope (Telescope`) – telescope to use while parsing files, by default None

Methods

__init__([folders, files, depth, hdu, ...])
bias(i[, show])
calibrations(**kwargs)	return a pandas DataFrame of calibrations observations given some metadata constraints in the form of wildcards
darks(i[, show])
files([id, path, exposure, tolerance])	Return a pandas DataFrame of files given some metadata constraints in the form of wildcards
flats(i[, show])
get_files(folders, extension[, scan, depth])	Return path of files with specific extension in the specified folder(s)
images(i[, show])
label(i)
observation_files(i[, past, future, ...])
observations([hide_exposure])	return a pandas DataFrame of observations given some metadata constraints in the form of wildcards
paths(**kwargs)	Get the paths of all files matching the kwargs query (see prose.FitsImage.files)
scan_files(files[, batch_size, verbose, ...])	Scan files and add data to database
to_pandas(query)

Attributes

all_bias	fits paths of the observation bias images
all_darks	fits paths of the observation dark images
all_flats	fits paths of the observation flats images
all_images	fits paths of the observation science images
obs_name	Observation name ({telescope}_{date}_{target}_{filter}) if a single observation is present
reduced	fits paths of the observation calibrated images if present
stack	fits paths of the observation stack image if present
unique_obs	Return whether the object contains a unique observation (observation is defined as a unique combinaison of date, telescope, target and filter).