bdQR_hdf5

HDF5_ALGEBRA

1 Description

Computes the QR decomposition of a matrix stored in an HDF5 file, factoring it into a product A = QR where Q is an orthogonal matrix and R is an upper triangular matrix. Results are stored back in the HDF5 file.

2 Usage

bdQR_hdf5(filename, group, dataset, outgroup = NULL, outdataset = NULL, thin = NULL, block_size = NULL, overwrite = NULL, threads = NULL)

3 Arguments

Parameter	Description
`filename`	Character string. Path to the HDF5 file containing the input matrix.
`group`	Character string. Path to the group containing the input dataset.
`dataset`	Character string. Name of the input dataset to decompose.
`outgroup`	Character string. Optional output group path where results will be stored. If not provided, results are stored in `<input_group>/QRDec`.
`outdataset`	Character string. Optional base name for output datasets. Results will be stored as `Q.'outdataset'` and `R.'outdataset'`.
`thin`	Logical. If TRUE, computes the reduced (thin) QR decomposition. If FALSE (default), computes the full decomposition.
`block_size`	Integer. Optional block size for blocked computation.
`overwrite`	Logical. If TRUE, allows overwriting existing datasets. Default is FALSE.
`threads`	Integer. Optional number of threads for parallel computation. If NULL, uses all available threads.

4 Value

List with components. If an error occurs, all string values are returned as empty strings (““):

fn: Character string with the HDF5 filename
ds_Q: Character string with the full dataset path to the Q matrix (orthogonal matrix). Results are written to the HDF5 file as “Q.’outdataset’” within the specified group
ds_R: Character string with the full dataset path to the R matrix (upper triangular matrix). Results are written to the HDF5 file as “R.’outdataset’” within the specified group

5 Details

This function performs QR decomposition on large matrices stored in HDF5 format, which is particularly useful for matrices too large to fit in memory. Features include: - Support for both thin and full QR decomposition - Blocked computation for improved performance - Parallel processing capabilities - Flexible output location specification - Optional overwriting of existing datasets

6 Examples

Code

# Create a sample HDF5 file with a matrix
library(rhdf5)
A <- matrix(rnorm(1000), 100, 10)
h5createFile("example.h5")
h5write(A, "example.h5", "mygroup/mymatrix")

# Compute QR decomposition
bdQR_hdf5("example.h5", "mygroup", "mymatrix",
          outgroup = "mygroup/results",
          outdataset = "qr_result",
          thin = TRUE)

7 See Also

bdQR for QR decomposition of in-memory matrices

--- title: "bdQR_hdf5" subtitle: "bdQR_hdf5" --- <span class="category-badge hdf5_algebra">HDF5_ALGEBRA</span> ## Description Computes the QR decomposition of a matrix stored in an HDF5 file, factoring it into a product A = QR where Q is an orthogonal matrix and R is an upper triangular matrix. Results are stored back in the HDF5 file. ## Usage ```r bdQR_hdf5(filename, group, dataset, outgroup = NULL, outdataset = NULL, thin = NULL, block_size = NULL, overwrite = NULL, threads = NULL) ``` ## Arguments ::: {.param-table} | Parameter | Description | |-----------|-------------| | `filename` | Character string. Path to the HDF5 file containing the input matrix. | | `group` | Character string. Path to the group containing the input dataset. | | `dataset` | Character string. Name of the input dataset to decompose. | | `outgroup` | Character string. Optional output group path where results will be stored. If not provided, results are stored in `<input_group>/QRDec`. | | `outdataset` | Character string. Optional base name for output datasets. Results will be stored as `Q.'outdataset'` and `R.'outdataset'`. | | `thin` | Logical. If TRUE, computes the reduced (thin) QR decomposition. If FALSE (default), computes the full decomposition. | | `block_size` | Integer. Optional block size for blocked computation. | | `overwrite` | Logical. If TRUE, allows overwriting existing datasets. Default is FALSE. | | `threads` | Integer. Optional number of threads for parallel computation. If NULL, uses all available threads. | ::: ## Value ::: {.return-value} List with components. If an error occurs, all string values are returned as empty strings (""): - **`fn`**: Character string with the HDF5 filename - **`ds_Q`**: Character string with the full dataset path to the Q matrix (orthogonal matrix). Results are written to the HDF5 file as "Q.'outdataset'" within the specified group - **`ds_R`**: Character string with the full dataset path to the R matrix (upper triangular matrix). Results are written to the HDF5 file as "R.'outdataset'" within the specified group ::: ## Details This function performs QR decomposition on large matrices stored in HDF5 format, which is particularly useful for matrices too large to fit in memory. Features include: - Support for both thin and full QR decomposition - Blocked computation for improved performance - Parallel processing capabilities - Flexible output location specification - Optional overwriting of existing datasets ## Examples ```{r} #| eval: false #| code-fold: show # Create a sample HDF5 file with a matrix library(rhdf5) A <- matrix(rnorm(1000), 100, 10) h5createFile("example.h5") h5write(A, "example.h5", "mygroup/mymatrix") # Compute QR decomposition bdQR_hdf5("example.h5", "mygroup", "mymatrix", outgroup = "mygroup/results", outdataset = "qr_result", thin = TRUE) ``` ## See Also ::: {.see-also} [bdQR](../linear_algebra/bdQR.html) for QR decomposition of in-memory matrices :::