H5SparseMatrixSeed-class: H5SparseMatrixSeed objects
In Bioconductor/HDF5Array: HDF5 datasets as array-like objects in R

H5SparseMatrixSeed-class

R Documentation

H5SparseMatrixSeed objects

Description

H5SparseMatrixSeed is a low-level helper class for representing a pointer to a sparse matrix stored in an HDF5 file and compressed using the CSC or CSR layout.

It is a virtual class with two concrete subclasses: CSC_H5SparseMatrixSeed for the Compressed Sparse Column layout, and CSR_H5SparseMatrixSeed for the Compressed Sparse Row layout. The former is used by 10x Genomics (e.g. "1.3 Million Brain Cell Dataset"). h5ad files can use one or the other layout to store a sparse matrix.

Note that an H5SparseMatrixSeed derivative is not intended to be used directly. Most end users will typically create and manipulate a higher-level H5SparseMatrix object instead. See ?H5SparseMatrix for more information.

Usage

## --- Constructor function ---

H5SparseMatrixSeed(filepath, group, subdata=NULL,
                   dim=NULL, sparse.layout=NULL)

## --- Accessors --------------

## S4 method for signature 'H5SparseMatrixSeed'
path(object)

## S4 method for signature 'H5SparseMatrixSeed'
dim(x)

## S4 method for signature 'H5SparseMatrixSeed'
dimnames(x)

## S4 method for signature 'CSC_H5SparseMatrixSeed'
chunkdim(x)
## S4 method for signature 'CSR_H5SparseMatrixSeed'
chunkdim(x)

## --- Data extraction --------

## S4 method for signature 'H5SparseMatrixSeed'
extract_array(x, index)

## S4 method for signature 'CSC_H5SparseMatrixSeed'
extract_sparse_array(x, index)
## S4 method for signature 'CSR_H5SparseMatrixSeed'
extract_sparse_array(x, index)

## S4 method for signature 'CSC_H5SparseMatrixSeed'
extractNonzeroDataByCol(x, j)
## S4 method for signature 'CSR_H5SparseMatrixSeed'
extractNonzeroDataByRow(x, i)

## --- Other methods ----------

## S4 method for signature 'H5SparseMatrixSeed'
is_sparse(x)

## S4 method for signature 'H5SparseMatrixSeed'
nzcount(x)

Arguments

`filepath`, `group`	See `?H5SparseMatrix` for a description of these arguments.
`subdata`	Experimental. Don't use!
`dim`, `sparse.layout`	The `H5SparseMatrixSeed()` constructor should be able to automatically detect the dimensions and layout of the sparse matrix stored in the HDF5 file, so the user shouldn't need to specify these arguments. See Details section below for some rare situations where the user might need to specify them.
`object`, `x`	An H5SparseMatrixSeed derivative.
`index`	See `?extract_array` in the S4Arrays package.
`j`	An integer vector containing valid column indices.
`i`	An integer vector containing valid row indices.

Details

*** Layout in R vs physical layout ***

The implementation of CSC_H5SparseMatrixSeed and CSR_H5SparseMatrixSeed objects follows the usual convention of transposing the matrix stored in the HDF5 file when loading it into R. This means that a CSC_H5SparseMatrixSeed object represents a sparse matrix stored physically in the CSR layout (Compressed Sparse Row) at the HDF5 level, and a CSR_H5SparseMatrixSeed object represents a sparse matrix stored physically in the CSC layout (Compressed Sparse Column) at the HDF5 level.

*** Automatic detection of the dimensions and layout ***

The H5SparseMatrixSeed() constructor should be able to automatically detect the dimensions and layout of the sparse matrix stored in the HDF5 file. However, in some rare situations, the user might want to bypass the detection mechanism, or they might be dealing with a sparse matrix stored in an HDF5 group that doesn't provide this information (e.g. the group only contains the data, indices, and indptr components). In which case, they can supply the dim and sparse.layout arguments:

dim must be an integer vector of length 2.
sparse.layout must be "CSC" or "CSR".

Note that both values must describe the dimensions and layout of the R object that will be returned, that is, after transposition from the physical layout used at the HDF5 level. Also be aware that the supplied values will take precedence over whatever the HDF5 file says, which means that bad things will happen if they don't reflect the actual dimensions and layout of the sparse matrix. Use these arguments only if you know what you are doing!

*** H5SparseMatrixSeed object vs H5SparseMatrix object ***

Note that H5SparseMatrixSeed derivatives support a very limited set of methods:

path(): Returns the path to the HDF5 file where the sparse matrix is located.
dim(), dimnames().
extract_array(), is_sparse(), extract_sparse_array(), chunkdim(): These generics are defined and documented in other packages e.g. in S4Arrays for extract_array() and is_sparse(), in SparseArray for extract_sparse_array(), and in DelayedArray for chunkdim().
nzcount(): Returns the number of nonzero values in the object.
extractNonzeroDataByCol(): Works on CSC_H5SparseMatrixSeed objects only. Returns a NumericList or IntegerList object parallel to j, that is, with one list element per column index in j. The row indices of the values are not returned. Furthermore, the values within a given list element can be returned in **any order**. In particular, do NOT assume that they are ordered by ascending row index.
extractNonzeroDataByRow(): Works on CSR_H5SparseMatrixSeed objects only. Returns a NumericList or IntegerList object parallel to i, that is, with one list element per row index in i. The column indices of the values are not returned. Furthermore, the values within a given list element can be returned in **any order**. In particular, do NOT assume that they are ordered by ascending column index.

In order to have access to the full set of operations that are available for DelayedMatrix objects, an H5SparseMatrixSeed derivative would first need to be wrapped in a DelayedMatrix object, typically by calling the DelayedArray() constructor on it.