NDDataArray#

class astropy.nddata.NDDataArray(data, *args, flags=None, **kwargs)[source]#

Bases: NDArithmeticMixin, NDSlicingMixin, NDIOMixin, NDData

An NDData object with arithmetic. This class is functionally equivalent to NDData in astropy versions prior to 1.0.

The key distinction from raw numpy arrays is the presence of additional metadata such as uncertainties, a mask, units, flags, and/or a coordinate system.

Parameters:

datandarray or NDData: The actual data contained in this NDData object. Not that this will always be copies by reference , so you should make copy the data before passing it in if that’s the desired behavior.
uncertaintyNDUncertainty, optional: Uncertainties on the data.
maskarray_like, optional: Mask for the data, given as a boolean Numpy array or any object that can be converted to a boolean Numpy array with a shape matching that of the data. The values must be False where the data is valid and True when it is not (like Numpy masked arrays). If data is a numpy masked array, providing mask here will causes the mask from the masked array to be ignored.
flagsarray_like or FlagCollection, optional: Flags giving information about each pixel. These can be specified either as a Numpy array of any type (or an object which can be converted to a Numpy array) with a shape matching that of the data, or as a FlagCollection instance which has a shape matching that of the data.
wcsNone, optional: WCS-object containing the world coordinate system for the data.

Warning

This is not yet defined because the discussion of how best to represent this class’s WCS system generically is still under consideration. For now just leave it as None
metadictastropy:-like object, optional: Metadata for this object. “Metadata” here means all information that is included with this object but not part of any other attribute of this particular object. e.g., creation date, unique identifier, simulation parameters, exposure time, telescope name, etc.
unitUnitBase instance or str, optional: The units of the data.

Raises:

ValueError: If the uncertainty or mask inputs cannot be broadcast (e.g., match shape) onto data.

Attributes Summary

`dtype`	`numpy.dtype` of this object's data.
`flags`
`mask`	any type : Mask for the dataset, if any.
`ndim`	integer dimensions of this object's data.
`shape`	shape tuple of this object's data.
`size`	integer size of this object's data.
`uncertainty`	any type : Uncertainty in the dataset, if any.
`unit`	`Unit` : Unit for the dataset, if any.

Methods Summary

convert_unit_to(unit[, equivalencies])

Returns a new NDData object whose values have been converted to a new unit.

Attributes Documentation

dtype#: numpy.dtype of this object’s data.

flags#

mask#

ndim#: integer dimensions of this object’s data.

shape#: shape tuple of this object’s data.

size#: integer size of this object’s data.

uncertainty#

unit#

Methods Documentation

convert_unit_to(unit, equivalencies=[])[source]#

Returns a new NDData object whose values have been converted to a new unit.

Parameters:

unitastropy.units.UnitBase instance or str: The unit to convert to.
equivalencieslist of tuple: A list of equivalence pairs to try if the units are not directly convertible. See Equivalencies.

Returns:

resultNDData: The resulting dataset

Raises:

UnitsError: If units are inconsistent.