tiledbsoma.SparseNDArrayRead

class tiledbsoma.SparseNDArrayRead(array: SparseNDArray, coords: Sequence[None | int | Slice[int] | Sequence[int] | ndarray[Any, dtype[integer]] | IntegerArray | ChunkedArray], result_order: ResultOrder, platform_config: Dict[str, Mapping[str, Any]] | object | None)

SparseNDArrayRead is an intermediate type which supports multiple eventual result formats

when reading a sparse array.

Results returned by coos and tables iterate over COO coordinates in the user-specified result order, but with breaks between iterator steps at arbitrary coordinates (i.e., any given result may split a row or column across two separate steps of the iterator). See blockwise for iterators that will always yield complete “blocks” for any given user-specified dimension, eg., all coordinates in a given row in one iteration step. NB: blockwise iterators may utilize additional disk or network IO.

See also

somacore.data.SparseRead

Lifecycle

Maturing.

__init__(array: SparseNDArray, coords: Sequence[None | int | Slice[int] | Sequence[int] | ndarray[Any, dtype[integer]] | IntegerArray | ChunkedArray], result_order: ResultOrder, platform_config: Dict[str, Mapping[str, Any]] | object | None)

Lifecycle

Maturing.

Methods

__init__(array, coords, result_order, ...)	Lifecycle
blockwise(axis, *[, size, ...])	Returns an intermediate type to choose a blockwise iterator of a specific format.
coos([shape])	Returns an iterator of Arrow SparseCOOTensor.
dense_tensors()
record_batches()
tables()	Returns an iterator of Arrow Table.