API

Opening Measurement Sets

The standard xarray.backends.api.open_dataset() and xarray.backends.api.open_datatree() methods should be used to open either a Dataset or a DataTree.

>>> dataset = xarray.open_dataset(
                "/data/data.ms",
                partition_columns=["DATA_DESC_ID", "FIELD_ID"])
>>> datatree = xarray.backends.api.open_datatree(
                "/data/data.ms",
                partition_columns=["DATA_DESC_ID", "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.MSv2PartitionEntryPoint

open_dataset(filename_or_obj: str | os.PathLike[Any] | BufferedIOBase | AbstractDataStore, *, drop_variables: str | Iterable[str] | None = None, partition_columns: List[str] | None = None, partition_key: PartitionKeyT | None = None, auto_corrs: bool = True, 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_columns – The columns to use for partitioning the Measurement set. Defaults to ['DATA_DESC_ID', 'FIELD_ID', 'OBSERVATION_ID'].

• 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.

• 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_columns and partition_key.

open_datatree(filename_or_obj: str | os.PathLike[Any] | BufferedIOBase | AbstractDataStore, *, drop_variables: str | Iterable[str] | None = None, partition_columns: List[str] | None = None, auto_corrs: bool = True, 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.

• drop_variables – Variables to drop from the dataset.

• partition_columns – The columns to use for partitioning the Measurement set. Defaults to ['DATA_DESC_ID', 'FIELD_ID', 'OBSERVATION_ID'].

• 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

Returns:

An xarray DataTree

Reading from Zarr

Thin wrappers around xarray.Dataset.open_zarr() and xarray.DataTree.open_zarr() that encode Dataset attributes as JSON.

xarray_ms.xds_from_zarr(*args, **kwargs)

Read a Measurement Set-like Dataset from a Zarr store.

Thin wrapper around xarray.open_zarr().

xarray_ms.xdt_from_zarr(*args, **kwargs)

Read a Measurement Set-like DataTree from a Zarr store.

Thin wrapper around xarray.backends.api.open_datatree().

Writing to Zarr

Thin wrappers around xarray.Dataset.to_zarr() and xarray.DataTree.to_zarr() that encode Dataset attributes as JSON.

xarray_ms.xds_to_zarr(ds: Dataset, *args, **kwargs) → None

Write a Measurement Set-like Dataset to a Zarr store.

Thin wrapper around xarray.Dataset.to_zarr().

xarray_ms.xdt_to_zarr(dt: DataTree, *args, **kwargs) → None

Read a Measurement Set-like DataTree to a Zarr store

Thin wrapper around xarray.core.datatree.DataTree.to_zarr().