API#

Opening Measurement Sets#

The standard xarray.open_datatree() method should be used to open a DataTree interface to the underlying Measurement Set data.

>>> datatree = xarray.open_datatree("/data/data.ms", partition_schema=["FIELD_ID"])

These methods defer to the relevant methods on the Entrypoint Class. Consult the method signatures for information on extra arguments that can be passed.

Entrypoint Class#

Entrypoint class for the MSv2 backend.

class xarray_ms.backend.msv2.entrypoint.MSv2EntryPoint#
open_dataset(filename_or_obj: str | os.PathLike[Any] | BufferedIOBase | AbstractDataStore, *, drop_variables: str | Iterable[str] | None = None, partition_schema: List[str] | None = None, partition_key: PartitionKeyT | None = None, preferred_chunks: Dict[str, int] | None = None, auto_corrs: bool = False, ninstances: int = 8, epoch: str | None = None, structure_factory: MSv2StructureFactory | None = None) → Dataset#

Create a Dataset presenting an MSv4 view over a partition of a MSv2 CASA Measurement Set

Parameters:

  • filename_or_obj – The path to the MSv2 CASA Measurement Set file.

  • drop_variables – Variables to drop from the dataset.

  • partition_schema – The columns to use for partitioning the Measurement set. Defaults to ['OBSERVATION_ID', 'PROCESSOR_ID', 'DATA_DESC_ID', 'OBS_MODE']. See Partitioning Guide for more further information.

  • partition_key – A key corresponding to an individual partition. For example (('DATA_DESC_ID', 0), ('FIELD_ID', 0)). If None, the first partition will be opened.

  • preferred_chunks – The preferred chunks for each partition.

  • auto_corrs – Include/Exclude auto-correlations.

  • ninstances – The number of Measurement Set instances to open for parallel I/O.

  • epoch – A unique string identifying the creation of this Dataset. This should not normally need to be set by the user

  • structure_factory – A factory for creating MSv2Structure objects. This should not normally need to be set by the user

Returns:

A Dataset referring to the unique partition specified by partition_schema and partition_key.

open_datatree(filename_or_obj: str | os.PathLike[Any] | BufferedIOBase | AbstractDataStore, *, preferred_chunks: Dict[str, Any] | None = None, drop_variables: str | Iterable[str] | None = None, partition_schema: List[str] | None = None, auto_corrs: bool = False, ninstances: int = 8, epoch: str | None = None, **kwargs) → DataTree#

Create a DataTree presenting an MSv4 view over multiple partitions of a MSv2 CASA Measurement Set.

Parameters:

  • filename_or_obj – The path to the MSv2 CASA Measurement Set file.

  • preferred_chunks –

    Chunk sizes along each dimension, e.g. {"time": 10, "frequency": 16}. Individual partitions can be chunked differently by partially (or fully) specifying a partition key: e.g.

    {  # Applies to all partitions with the relevant DATA_DESC_ID
  (("DATA_DESC_ID", 0),): {"time": 10, "frequency": 16},
  (("DATA_DESC_ID", 1),): {"time": 20, "frequency": 32},
}
{  # Applies to all partitions with the relevant DATA_DESC_ID and FIELD_ID
  (("DATA_DESC_ID", 0), ('FIELD_ID', 1)): {"time": 10, "frequency": 16},
  (("DATA_DESC_ID", 1), ('FIELD_ID', 0)): {"time": 20, "frequency": 32},
}
{  # String variants
  "DATA_DESC_ID=0,FIELD_ID=0": {"time": 10, "frequency": 16},
  "D=0,F=1": {"time": 20, "frequency": 32},
}

    Note

    xarray’s reserved chunks argument must be specified in order to enable this functionality and enable fine-grained chunking in Datasets and DataTrees. See xarray’s backend documentation on Preferred chunk sizes for more information.

  • drop_variables – Variables to drop from the dataset.

  • partition_schema – The columns to use for partitioning the Measurement set. Defaults to ['OBSERVATION_ID', 'PROCESSOR_ID', 'DATA_DESC_ID', 'OBS_MODE']. See Partitioning Guide for more further information.

  • auto_corrs – Include/Exclude auto-correlations.

  • ninstances – The number of Measurement Set instances to open for parallel I/O.

  • epoch – A string uniquely identifying this Dataset. This should not normally be set by the user

Returns:

An xarray DataTree