tiledbsoma.ExperimentAxisQuery¶

class tiledbsoma.ExperimentAxisQuery(experiment: ~somacore.query.query._Exp, measurement_name: str, *, obs_query: ~somacore.query.axis.AxisQuery = AxisQuery(value_filter=None, coords=()), var_query: ~somacore.query.axis.AxisQuery = AxisQuery(value_filter=None, coords=()), index_factory: ~typing.Callable[[~numpy.ndarray[~typing.Any, ~numpy.dtype[~numpy.int64]]], IndexLike] = <class 'pandas.core.indexes.base.Index'>)¶

Axis-based query against a SOMA Experiment.

ExperimentAxisQuery allows easy selection and extraction of data from a single Measurement in an Experiment, by obs/var (axis) coordinates and/or value filter.

The primary use for this class is slicing Experiment X layers by obs or var value and/or coordinates. Slicing on SparseNDArray X matrices is supported; DenseNDArray is not supported at this time.

IMPORTANT: this class is not thread-safe.

IMPORTANT: this query class assumes it can store the full result of both axis dataframe queries in memory, and only provides incremental access to the underlying X NDArray. API features such as n_obs and n_vars codify this in the API.

IMPORTANT: you must call close() on any instance of this class to release underlying resources. The ExperimentAxisQuery is a context manager, and it is recommended that you use the following pattern to make this easy and safe:

with ExperimentAxisQuery(...) as query:
    ...

This base query implementation is designed to work against any SOMA implementation that fulfills the basic APIs. A SOMA implementation may include a custom query implementation optimized for its own use.

Lifecycle: maturing

__init__(experiment: ~somacore.query.query._Exp, measurement_name: str, *, obs_query: ~somacore.query.axis.AxisQuery = AxisQuery(value_filter=None, coords=()), var_query: ~somacore.query.axis.AxisQuery = AxisQuery(value_filter=None, coords=()), index_factory: ~typing.Callable[[~numpy.ndarray[~typing.Any, ~numpy.dtype[~numpy.int64]]], IndexLike] = <class 'pandas.core.indexes.base.Index'>)¶

Methods

`X`(layer_name, *[, batch_size, partitions, ...])	Returns an `X` layer as a sparse read.
`__init__`(experiment, measurement_name, *[, ...])
`close`()	Releases resources associated with this query.
`obs`(*[, column_names, batch_size, ...])	Returns `obs` as an Arrow table iterator.
`obs_joinids`()	Returns `obs` `soma_joinids` as an Arrow array.
`obsm`(layer)	Returns an `obsm` layer as a sparse read.
`obsp`(layer)	Returns an `obsp` layer as a sparse read.
`to_anndata`(X_name, *[, column_names, ...])	Executes the query and return result as an `AnnData` in-memory object.
`var`(*[, column_names, batch_size, ...])	Returns `var` as an Arrow table iterator.
`var_joinids`()	Returns `var` `soma_joinids` as an Arrow array.
`varm`(layer)	Returns a `varm` layer as a sparse read.
`varp`(layer)	Returns a `varp` layer as a sparse read.

Attributes

`indexer`	A `soma_joinid` indexer for both `obs` and `var` axes.
`n_obs`	The number of `obs` axis query results.
`n_vars`	The number of `var` axis query results.