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

ATTR_SKIP

OPTIONAL_KEYS

REQUIRED_KEYS