HDF5 allows storing data in an arbitrary fashion, which makes reading data into memory a hassle. The methods here serve as convenience functions for reading data stored in a certain format back into a certain R object. For details regarding how data should be stored on disk, please see the h5Seurat file specification.
# S3 method for H5D as.array(x, ...) # S3 method for H5D as.data.frame(x, row.names = NULL, optional = FALSE, ...) # S3 method for H5Group as.data.frame(x, row.names = NULL, optional = FALSE, ...) # S4 method for H5Group as.factor(x) # S4 method for H5Group as.list(x, ...) # S3 method for H5D as.logical(x, ...) # S3 method for H5D as.matrix(x, transpose = FALSE, ...) # S3 method for H5Group as.matrix(x, ...) # S3 method for H5Group as.sparse(x, ...) # S3 method for H5D dimnames(x)
| x | An HDF5 dataset or group |
|---|---|
| ... | Arguments passed to other methods |
| row.names |
|
| optional | logical. If |
| transpose | Transpose the data upon reading it in, used when writing data in row-major order (eg. from C or Python) |
as.array: returns an array with the data
from the HDF5 dataset
as.data.frame: returns a data.frame with
the data from the HDF5 dataset or group
as.factor: returns a factor with the data
from the HDF5 group
as.list: returns a list with the data from
the HDF5 group
as.logical: returns a logical with the
data from the HDF5 dataset
as.matrix, H5D method: returns a
matrix with the data from the HDF5 dataset
as.sparse, as.matrix, H5Group method: returns a
sparseMatrix with the data from the HDF5 group
dimnames: returns a two-length list of character vectors for
row and column names. Row names should be in a column named index