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This class allows the user to download all full-frame images for a given sector,
camera, and chip. It also allows the user to create their own pointing model
based on each cadence for a given combination of sector, camera, and chip.
No individual user should have to download all of the full-frame images because
stacked postcards will be available for the user to download from MAST.
Parameters
----------
sector : int, optional
camera : int, optional
chip : int, optional |
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Methods defined here:
- __init__(self, sector=None, camera=None, chip=None)
- Initialize self. See help(type(self)) for accurate signature.
- build_pointing_model(self, pos_predicted, pos_inferred, outlier_removal=False)
- Builds an affine transformation to correct the positions of stars
from a possibly incorrect WCS.
Parameters
----------
pos_predicted : tuple
Positions taken straight from the WCS; [[x,y],[x,y],...] format.
pos_inferred : tuple
Positions taken using any centroiding method; [[x,y],[x,y],...] format.
outlier_removal : bool, optional
Whether to clip 1-sigma outlier frames. Default `False`.
Returns
-------
xhat : np.ndarray
(3, 3) affine transformation matrix between WCS positions
and inferred positions.
- download_ffis(self, download_dir=None)
- Downloads entire sector of data into FFI download directory.
Parameters
----------
download_dir : str
Location where the data files will be stored.
Defaults to "~/.eleanor/sector_{}/ffis" if `None` is passed.
- pointing_model_per_cadence(self, out_dir=None, n_sources=350)
- Step through build_pointing_model for each cadence.
- sort_by_date(self)
- Sorts FITS files by start date of observation.
Data descriptors defined here:
- __dict__
- dictionary for instance variables (if defined)
- __weakref__
- list of weak references to the object (if defined)
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