pyklip.kpp.utils package¶

Submodules¶

pyklip.kpp.utils.GPIimage module¶

pyklip.kpp.utils.GPIimage.get_IOWA(image, centroid=None)[source]¶

Get the IWA (inner working angle) of the central disk of nans and return the mask corresponding to the inner disk.

Parameters:	image – A GPI image with a disk full of nans at the center. centroid – center of the nan disk
Returns:

pyklip.kpp.utils.GPIimage.get_occ(image, centroid=None)[source]¶

Get the IWA (inner working angle) of the central disk of nans and return the mask corresponding to the inner disk.

Parameters:	image – A GPI image with a disk full of nans at the center. centroid – center of the nan disk
Returns:

pyklip.kpp.utils.mathfunc module¶

pyklip.kpp.utils.mathfunc.LSQ_model_exp(x, y, m, alpha)[source]¶

pyklip.kpp.utils.mathfunc.gauss2d(x, y, amplitude=1.0, xo=0.0, yo=0.0, sigma_x=1.0, sigma_y=1.0, theta=0, offset=0)[source]¶

pyklip.kpp.utils.mathfunc.hat(x, y, radius)[source]¶

pyklip.kpp.utils.mathfunc.model_exp(x, m, alpha)[source]¶

pyklip.kpp.utils.multiproc module¶

class pyklip.kpp.utils.multiproc.NoDaemonPool(processes=None, initializer=None, initargs=(), maxtasksperchild=None, context=None)[source]¶

Bases: multiprocessing.pool.Pool

Process¶: alias of NoDaemonProcess

class pyklip.kpp.utils.multiproc.NoDaemonProcess(group=None, target=None, name=None, args=(), kwargs={}, *, daemon=None)[source]¶

Bases: multiprocessing.context.Process

daemon¶

pyklip.kpp.utils.oi module¶

pyklip.kpp.utils.oi.get_pos_known_objects(fakeinfohdr, object_name, pix2as, center=None, MJDOBS=None, OI_list_folder=None, xy=False, pa_sep=False, ignore_fakes=False, fakes_only=False, include_speckles=False, IWA=None, OWA=None)[source]¶

Return the position of real and/or simulated planets in an image based on its headers.

Parameters:

fakeinfohdr – fits file header containing the injected planets related keywords.
object_name – Name of the star being observed.
pix2as – platescale.
center – Center of the image (not needed if pa_sep = True).
MJDOBS – Julian date of the observation. (needed when OI_list_folder is not None)
OI_list_folder – List of Object of Interest (OI) that should be masked from any standard deviation calculation. See the online documentation for instructions on how to define it.
xy – Boolean. Returns the planets coordinate with x,y coordinates in pixels
pa_sep – Boolean. Returns the planets coordinates as position angle (in arcsec), separation (in pix)
ignore_fakes – Don’t return fake planets.
fakes_only – Returns only fake planets.
include_speckles – Include speckles from the list of object of interest (OI_list_folder)
IWA – Inner working angle (in pixels).
OWA – Outer working angle (in pixels).

Return: (sep_vec,pa_vec) or (x_vec,y_vec) or (row_vec,col_vec) (default): Objects coordinates (real/fakes/others). For e.g., sep_vec,pa_vec are vectors and (sep_vec[0],pa_vec[0]) is the coordinate of the first object and so on…

pyklip.kpp.utils.oi.make_GOI_list(outputDir, GOI_list_csv, GPI_TID_csv)[source]¶

Generate the GOI files from the GOI table and the TID table (queried from the database).

outputDir: Output directory in which to save the GOI files. GOI_list_csv: Table with the list of GOIs (including separation, PA…). delimiter=’,’ GPI_TID_csv: Table giving the TID code for a given object name. delimiter=’,’ :return: One .csv file per target for which at list one GOI exists. delimiter=’;’

The filename follows: [object]_GOI.csv. For e.g. c_Eri_GOI.csv.

pyklip.kpp.utils.oi.mask_known_objects(cube, fakeinfohdr, object_name, pix2as, center, MJDOBS=None, OI_list_folder=None, ignore_fakes=False, fakes_only=False, include_speckles=False, IWA=None, OWA=None, mask_radius=7)[source]¶

Mask point sources in cube with an NaN aperture.