lenskit.data.matrix.SparseIndexType

class lenskit.data.matrix.SparseIndexType(dimension)

Bases: ExtensionType

Data type for the index field of a sparse row. Indexes are just stored as ``int32``s; the extension type attaches the row’s dimensionality to the index field (making it easier to pass it to/from Rust, since we often pass arrays and not entire fields).

Stability: Internal

This API is at the internal or experimental stability level: it may change at any time, and breaking changes will not necessarily be described in the release notes. See Stability Levels for details.

Parameters:

dimension (int)

__init__(dimension)

Initialize an extension type instance.

This should be called at the end of the subclass’ __init__ method.

Parameters:

dimension (int)

Methods

__init__(dimension)	Initialize an extension type instance.
check_dimension(expected)	Check that this index type has the expected dimension.
equals(self, other, *[, check_metadata])	Return true if type is equivalent to passed value.
field(self, i)
to_pandas_dtype(self)	Return the equivalent NumPy / Pandas dtype.
wrap_array(self, storage)	Wrap the given storage array as an extension array.

Attributes

bit_width	The bit width of the extension type.
byte_width	The byte width of the extension type.
extension_name	The extension type name.
has_variadic_buffers	If True, the number of expected buffers is only lower-bounded by num_buffers.
id
num_buffers	Number of data buffers required to construct Array type excluding children.
num_fields	The number of child fields.
storage_type	The underlying storage type.
dimension

check_dimension(expected)

Check that this index type has the expected dimension.

Returns:

The dimension of the index type.

Raises:

ValueError – If the type’s dimension does not match the expected dimension.

Parameters:

expected (int | None)

Return type:

int