NDCubeOrdered¶
-
class
ndcube.
NDCubeOrdered
(data, wcs, uncertainty=None, mask=None, meta=None, unit=None, extra_coords=None, copy=False, missing_axis=None, **kwargs)[source] [edit on github]¶ Bases:
ndcube.NDCube
Class representing N dimensional cubes with oriented WCS. Extra arguments are passed on to NDData’s init. The order is TIME, SPECTRAL, SOLAR-x, SOLAR-Y and any other dimension. For example, in an x, y, t cube the order would be (t,x,y) and in a lambda, t, y cube the order will be (t, lambda, y). Extra arguments are passed on to NDData’s init.
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. The axes’ priorities are time, spectral, celestial. This means that if present, each of these axis will take precedence over the others. - 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.
- meta (dict-like object, optional) – Additional meta information about the dataset. If no meta is provided an empty collections.OrderedDict is created. Default is None.
- unit (Unit-like or str, optional) – Unit for the dataset. Strings that can be converted to a Unit are allowed. Default is None.
- 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.
- data (