io module

Module to manage general information like path to data

class darclight.io.DataCollection(path=None, reduced_path=None, ignore=None, filelist=None)

Bases: object

Class that organizes all files in a given directory.

add_file(fname, reduced=False, row=None)

adds a row to an existing table

Parameters:

• fname (str | Path) – filename to add

• reduced (bool, optional) – if it should be added to the raw or reduced table, defaults to False

• row (tuple | None, optional) – row informations, depends on raw or reduced what it should contain. If None the file will be read and the values are derived automatically, defaults to None

bias(data=True, header=False, fname=False, **filter_kwds)

Generator to get the data and/or header of the files in the raw bias frames.

Parameters:

• data (bool, optional) – whether or not the data of the file should be returned, defaults to True

• header (bool, optional) – whether or not the header should be returned, defaults to False

• fname (bool, optional) – whether or not the filename should be returned, defaults to False

Raises:

ValueError – if both (data and header) are set to False. If you want only the filenames address the attribute directly.

Yield:

tuple of the desired outputs in the order (data, header, filename)

Return type:

Tuple

property bias_files

property dark_exposures: list[int]

List of exposure times where a dark frame is directly available.

Returns:

list of exposure times

Return type:

list[int]

property dark_files

darks(exposure, data=True, header=False, fname=False, **filter_kwds)

Generator to get the data and/or header of the files of the raw dark frames

for a specific exposure.

Parameters:

• exposure (int) – the exposure time of the dark frame

• data (bool, optional) – whether or not the data of the file should be returned, defaults to True

• header (bool, optional) – whether or not the header should be returned, defaults to False

• fname (bool, optional) – whether or not the filename should be returned, defaults to False

Raises:

• ValueError – This error is raised if there is no dark frame with the given exposure registered. Try ‘update_raw()’ if you think there should be one

• ValueError – if both (data and header) are set to False. If you want only the filenames address the attribute directly.

Yield:

tuple of the desired outputs in the order (data, header, filename)

Return type:

Tuple

static file_data(filelist, data=True, header=False, fname=False, return_kwds=None, **filter_kwds)

generator to get the data and/or header of the files in the provided list.

Parameters:

• filelist (list) – list of files to iterate over

• data (bool, optional) – whether or not the data of the file should be returned, defaults to True

• header (bool, optional) – whether or not the header should be returned, defaults to False

• fname (bool, optional) – whether or not the filename should be returned, defaults to False

• return_kwds (list[str] | None) – additional keywords that should be returned alongside the data/header, defaults to None

• filter_kwds – additional keywords the returned data should be filtered for from the header

Raises:

ValueError – if both (data and header) are set to False. If you want only the filenames address the attribute directly.

Yield:

tuple of the desired outputs in the order (data, header, filename, return_kwd 1,…)

Return type:

Tuple

property flat_exposures: dict[str | None, set]

exposure times for each filter

Returns:

dictionary of the form {filter:exposure, …}

Return type:

dict[str|None,set]

property flat_files

flats(used_filter, data=True, header=False, fname=False, return_kwds=None, **filter_kwds)

Generator to get the data and/or header of the files of the raw flat frames

for a specific filter.

Parameters:

• used_filter (str | None) – the exposure time of the flat frame

• data (bool, optional) – whether or not the data of the file should be returned, defaults to True

• header (bool, optional) – whether or not the header should be returned, defaults to False

• fname (bool, optional) – whether or not the filename should be returned, defaults to False

Raises:

• ValueError – This error is raised if there is no flat frame with the given filter registered. Try ‘update_raw()’ if you think there should be one

• ValueError – if both (data and header) are set to False. If you want only the filenames address the attribute directly.

Yield:

tuple of the desired outputs in the order (data, header, filename)

Return type:

Tuple

get_files(reduced=False, **filters)

returns the filenames of the files specified

Parameters:

reduced (bool, optional) – whether the desired files should be reduced or not, defaults to False

Returns:

filenames satisfy the filters

Return type:

np.ndarray

get_master(imagetype, specifier=None, header=True)

looks for a specific stacked master frame

Parameters:

• imagetype (str) – type of the image to check, use ‘bias’, ‘dark’, ‘flat’ or ‘light’

• specifier (int | str | None, optional) – exposure time to look for, if imagetype=’dark’ or filter to look for if imagetype=’flat’ or target if imagetype=’light, defaults to None

Returns:

data of the required file, None if it does not exist

Return type:

np.ndarray | None

static hdu_from_file(file)

gives access to the data and header of a given file

Parameters:

file (str) – name of the file

Returns:

the data and header from that file

Return type:

Tuple[np.ndarray,astropy.io.fits.header.Header]

property light_meta: dict[str, set[Tuple[str, int]]]

Metadata for the light frames

Returns:

dictionary of the form {target:[(filter,exposure),…],…}, for every target there is a set of tuples that each contain the filter and the corresponding exposure time.

Return type:

dict[str,set[Tuple[str, int]]]

lights(target, data=True, header=False, fname=False, return_kwds=None, reduced=False, **filter_kwds)

Generator to get the data and/or header of the files of the raw light frames

for a specific target.

Parameters:

• target (str) – the target of the light frame

• data (bool, optional) – whether or not the data of the file should be returned, defaults to True

• header (bool, optional) – whether or not the header should be returned, defaults to False

• fname (bool, optional) – whether or not the filename should be returned, defaults to False

Raises:

• ValueError – This error is raised if there is no light frame with the given target registered. Try ‘update_raw()’ if you think there should be one

• ValueError – if both (data and header) are set to False. If you want only the filenames address the attribute directly.

Yield:

tuple of the desired outputs in the order (data, header, filename)

Return type:

Tuple

static save_file(filename, data, header=None)

Saves the given data and header with the given filename in the reduced data directory.

Parameters:

• filename (str) – Desired name for the file

• data (np.ndarray) – data that should be stored in the file

• header (astropy.io.fits.header.Header, optional) – header for the file, defaults to None

Return type:

None

scan(raw=True, reduced=True)

scans the directories from scractch

Parameters:

• raw (bool, optional) – whether or not the raw directory should be scaned, defaults to True

• reduced (bool, optional) – whether or not the reduced directory should be scanned, defaults to True

property targets: list[str]

List of targets captured.

Returns:

list of targets

Return type:

list[str]

property used_filters: list[str]

List of used filters where a flat frame is available.

Returns:

list of filters

Return type:

list[str]