IRISMapCube

class irispy.sji.IRISMapCube(data, wcs, uncertainty=None, unit=None, meta=None, mask=None, extra_coords=None, copy=False, missing_axis=None, scaled=None)[source] [edit on github]

Bases: ndcube.ndcube.NDCube

Class representing SJI Images described by a single WCS

Parameters:
  • data (numpy.ndarray) – The array holding the actual data in this object.
  • wcs (ndcube.wcs.wcs.WCS) – The WCS object containing the axes’ information
  • unit (astropy.unit.Unit or str) – Unit for the dataset. Strings that can be converted to a Unit are allowed.
  • meta (dict-like object) – Additional meta information about the dataset.
  • uncertainty (any type, optional) – Uncertainty in the dataset. Should have an attribute uncertainty_type that defines what kind of uncertainty is stored, for example “std” for standard deviation or “var” for variance. A metaclass defining such an interface is NDUncertainty - but isn’t mandatory. If the uncertainty has no such attribute the uncertainty is stored as UnknownUncertainty. Defaults to None.
  • mask (any type, optional) – Mask for the dataset. Masks should follow the numpy convention that valid data points are marked by False and invalid ones with True. Defaults to None.
  • extra_coords (iterable of `tuple`s, each with three entries) – (str, int, astropy.units.quantity or array-like) Gives the name, axis of data, and values of coordinates of a data axis not included in the WCS object.
  • copy (bool, optional) – Indicates whether to save the arguments as copy. True copies every attribute before saving it while False tries to save every parameter as reference. Note however that it is not always possible to save the input as reference. Default is False.
  • scaled (bool, optional) – Indicates if datas has been scaled.

Examples

>>> from irispy import sji
>>> from irispy.data import sample
>>> sji = read_iris_sji_level2_fits(sample.SJI_CUBE_1400)

Initialization of Slit Jaw Imager

Methods Summary

apply_dust_mask([undo]) Applies or undoes an update of the mask with the dust particles positions.
apply_exposure_time_correction([undo, force]) Applies or undoes exposure time correction to data and uncertainty and adjusts unit.

Methods Documentation

apply_dust_mask(undo=False)[source] [edit on github]

Applies or undoes an update of the mask with the dust particles positions.

Parameters:undo (bool) – If False, dust particles positions mask will be applied. If True, dust particles positions mask will be removed. Default=False
Returns:Rewrite self.mask with/without the dust positions.
Return type:result
apply_exposure_time_correction(undo=False, force=False)[source] [edit on github]

Applies or undoes exposure time correction to data and uncertainty and adjusts unit.

Correction is only applied (undone) if the object’s unit doesn’t (does) already include inverse time. This can be overridden so that correction is applied (undone) regardless of unit by setting force=True.

Parameters:
  • undo (bool) – If False, exposure time correction is applied. If True, exposure time correction is removed. Default=False
  • force (bool) – If not True, applies (undoes) exposure time correction only if unit doesn’t (does) already include inverse time. If True, correction is applied (undone) regardless of unit. Unit is still adjusted accordingly.
Returns:

result – A new IRISMapCube is returned with the correction applied (undone).

Return type:

IRISMapCube