anndata2ri

Converter between Python’s AnnData and R’s SingleCellExperiment.

SingleCellExperiment		AnnData
assay(d, 'X')	⇄	d.X
assay(d, 'counts')	⇄	d.layers['counts']
colData(d)	⇄	d.obs
rowData(d)	⇄	d.var
metadata(d)	⇄	d.uns
reducedDim(d, 'PCA')	⇄	d.obsm['X_pca']
reducedDim(d, 'DM')	⇄	d.obsm['X_diffmap']

anndata2ri.activate()

Activate conversion for AnnData objects as well as Array objects and pandas.DataFrames via rpy2.robjects.numpy2ri and rpy2.robjects.pandas2ri.

Does nothing if this is the active converter.

anndata2ri.deactivate()

Deactivate the conversion described above if it is active.

anndata2ri.py2rpy(obj)

Convert Python objects to R interface objects. Supports: :rtype: Sexp

• AnnData → SingleCellExperiment

anndata2ri.rpy2py(obj)

Convert R interface objects to Python objects. Supports: :rtype: Sexp

• SingleCellExperiment → AnnData

• S4Vectors::DataFrame → pandas.DataFrame

anndata2ri.scipy2ri

Convert scipy.sparse matrices between Python and R.

For a detailed comparison between the two languages’ sparse matrix environment, see issue #8.

Here’s an overview over the matching classes

R	Python
dgCMatrix	csc_matrix(dtype=float64)
lgCMatrix/ngCMatrix	csc_matrix(dtype=bool)
dgRMatrix	csr_matrix(dtype=float64)
lgRMatrix/ngRMatrix	csr_matrix(dtype=bool)
dgTMatrix	coo_matrix(dtype=float64)
lgTMatrix/ngTMatrix	coo_matrix(dtype=bool)
ddiMatrix	dia_matrix(dtype=float64)
ldiMatrix	dia_matrix(dtype=bool)

anndata2ri.scipy2ri.activate()

Activate conversion between sparse matrices from Scipy and R’s Matrix package.

Does nothing if this is the active conversion.

anndata2ri.scipy2ri.deactivate()

Deactivate the conversion described above if it is active.

anndata2ri.scipy2ri.py2rpy(obj)

Convert scipy sparse matrices objects to R sparse matrices. Supports:

Return type

Sexp

csc_matrix (dtype in {float32, float64, bool}) →

dgCMatrix or lgCMatrix

csr_matrix (dtype in {float32, float64, bool}) →

dgRMatrix or lgRMatrix

coo_matrix (dtype in {float32, float64, bool}) →

dgTMatrix or lgTMatrix

dia_matrix (dtype in {float32, float64, bool}) →

ddiMatrix or ldiMatrix

anndata2ri.scipy2ri.rpy2py(obj)

Convert R sparse matrices to scipy sparse matrices. Supports:

Return type

Sexp

dgCMatrix, lgCMatrix, or ngCMatrix →

csc_matrix (dtype float64 or bool)

dgRMatrix, lgRMatrix, or ngRMatrix →

csr_matrix (dtype float64 or bool)

dgTMatrix, lgTMatrix, or ngTMatrix →

coo_matrix (dtype float64 or bool)

ddiMatrix or ldiMatrix →

dia_matrix (dtype float64 or bool)

anndata2ri.scipy2ri.supported_r_matrix_types = frozenset({'d', 'l', 'n'})

The Matrix data types supported by this module; Double, Logical, and patterN.

anndata2ri.scipy2ri.supported_r_matrix_storage = frozenset({'C', 'R', 'T', 'di'})

The Matrix storage types supported by this module; Column-sparse, Row-Sparse, Triplets, and DIagonal.

anndata2ri.scipy2ri.supported_r_matrix_classes(types=frozenset({'d', 'l', 'n'}), storage=frozenset({'C', 'R', 'T', 'di'}))

Get supported classes, possibly limiting data types or storage types.

Parameters

types : Union[Iterable[str], str] (default: frozenset({'n', 'd', 'l'}))

Data type character(s) from supported_r_matrix_types

storage : Union[Iterable[str], str] (default: frozenset({'di', 'T', 'C', 'R'}))

Storage mode(s) from supported_r_matrix_storage

Return type

FrozenSet[str]

Returns

All supported classes with those characters