anndata.read_h5ad#
- anndata.read_h5ad(filename, backed=None, *, as_sparse=(), as_sparse_fmt=<class 'scipy.sparse._csr.csr_matrix'>, chunk_size=6000)[source]#
Read
.h5ad
-formatted hdf5 file.- Parameters:
- filename
str
|Path
File name of data file.
- backed
Union
[Literal
['r'
,'r+'
],bool
,None
] (default:None
) If
'r'
, loadAnnData
inbacked
mode instead of fully loading it into memory (memory
mode). If you want to modify backed attributes of the AnnData object, you need to choose'r+'
.Currently,
backed
only support updates toX
. That means any changes to other slots likeobs
will not be written to disk inbacked
mode. If you would like save changes made to these slots of abacked
AnnData
, write them to a new file (seewrite()
). For an example, see [here] (https://anndata-tutorials.readthedocs.io/en/latest/getting-started.html#Partial-reading-of-large-data).- as_sparse
Sequence
[str
] (default:()
) If an array was saved as dense, passing its name here will read it as a sparse_matrix, by chunk of size
chunk_size
.- as_sparse_fmt
type
[spmatrix
] (default:<class 'scipy.sparse._csr.csr_matrix'>
) Sparse format class to read elements from
as_sparse
in as.- chunk_size
int
(default:6000
) Used only when loading sparse dataset that is stored as dense. Loading iterates through chunks of the dataset of this row size until it reads the whole dataset. Higher size means higher memory consumption and higher (to a point) loading speed.
- filename
- Return type: