datacube.model.Measurement¶

class datacube.model.Measurement(canonical_name=None, **kwargs)[source]¶

Describes a single data variable of a Product or Dataset.

Must include, which can be used when loading and interpreting data:

name

dtype - eg: int8, int16, float32

nodata - What value represent No Data

units

Attributes can be accessed using dict [] syntax.

Can also include attributes like alternative names ‘aliases’, and spectral and bit flags definitions to aid with interpreting the data.

__init__(canonical_name=None, **kwargs)[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`([canonical_name])	Initialize self.
`clear`()
`copy`()	Required as the super class dict method returns a dict and does not preserve Measurement class
`dataarray_attrs`()	This returns attributes filtered for display in a dataarray.
`fromkeys`	Returns a new dict with keys from iterable and values equal to value.
`get`(k[,d])
`items`()
`keys`()
`pop`(k[,d])	If key is not found, d is returned if given, otherwise KeyError is raised
`popitem`()	2-tuple; but raise KeyError if D is empty.
`setdefault`(k[,d])
`update`([E, ]**F)	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
`values`()

Attributes