Dataset Type#
- class datacube.model.DatasetType(metadata_type, definition, id_=None)[source]#
Product definition
- Parameters
metadata_type (MetadataType) –
definition (dict) –
Methods:
canonical_measurement(measurement)resolve measurement alias into canonical name
Returns dictionary with keys compatible with
dc.load(..)named arguments:lookup_measurements([measurements])Find measurements by name
to_dict()Convert to a dictionary representation of the available fields
validate_extra_dims(definition)Validate 3D metadata in the product definition.
Attributes:
product definition document
List of dimension labels for data in this product
Dictionary of metadata for the third dimension.
Grid specification for this product
Dictionary of measurements in this product
- canonical_measurement(measurement)[source]#
resolve measurement alias into canonical name
- Return type
- definition#
product definition document
- property extra_dimensions: datacube.model.ExtraDimensions#
Dictionary of metadata for the third dimension.
- Return type
ExtraDimensions
- grid_spec#
Grid specification for this product
- load_hints()[source]#
Returns dictionary with keys compatible with
dc.load(..)named arguments:output_crs - CRS resolution - Tuple[float, float] align - Tuple[float, float] (if defined)
Returns {} if load hints are not defined on this product, or defined with errors.
- property measurements: Mapping[str, datacube.model.Measurement]#
Dictionary of measurements in this product
- Return type
- static validate_extra_dims(definition)[source]#
Validate 3D metadata in the product definition.
- Perform some basic checks for validity of the 3D dataset product definition:
Checks extra_dimensions section exists
For each 3D measurement, check if the required dimension is defined
If the 3D spectral_definition is defined: - Check there’s one entry per coordinate. - Check that wavelength and response are the same length.