Ops.HDF5Matrix

Ops.HDF5Matrix

OTHER

1 Description

Standard R arithmetic operators applied element-wise to HDF5Matrix objects stored on disk. Both operands must be HDF5Matrix objects with identical dimensions.

2 Usage

Ops.HDF5Matrix(e1, e2)

3 Arguments

Parameter	Description
`e1`	An object (left-hand side)
`e2`	An object (right-hand side)

4 Value

A new containing the result, stored in the same HDF5 file as under a temporary dataset name.

5 Details

Supported operators:

All operations use block-wise processing and optional OpenMP parallelisation, controlled via hdf5matrix_options.

Performance settings:

Global options set via hdf5matrix_options are applied. For explicit control use the R6 methods directly: A$add(B, paral = TRUE, threads = 4).

6 Examples

\donttest{
fn <- tempfile(fileext = ".h5")
A_hdf5 <- hdf5_create_matrix(fn, "data/A", data = matrix(1:12, 3, 4))
B_hdf5 <- hdf5_create_matrix(fn, "data/B", data = matrix(2, 3, 4))

C <- A_hdf5 + B_hdf5
D <- A_hdf5 - B_hdf5
E <- A_hdf5 * B_hdf5
G <- A_hdf5 / B_hdf5

all.equal(as.matrix(C), matrix(1:12, 3, 4) + 2)

hdf5_close_all()
unlink(fn)
}

7 See Also

hdf5matrix_options for global performance settings, HDF5Matrix for R6 methods with explicit parameters

---
title: "Ops.HDF5Matrix"
subtitle: "Ops.HDF5Matrix"
---

<span class="category-badge other">OTHER</span>

## Description

Standard R arithmetic operators applied element-wise to `HDF5Matrix`
objects stored on disk. Both operands must be `HDF5Matrix` objects
with identical dimensions.

## Usage

```r
Ops.HDF5Matrix(e1, e2)
```
## Arguments

::: {.param-table}
| Parameter | Description |
|-----------|-------------|
| `e1` | An \code{HDF5Matrix} object (left-hand side) |
| `e2` | An \code{HDF5Matrix} object (right-hand side)  |
:::

## Value

::: {.return-value}
A new \code{HDF5Matrix} containing the result, stored in the same
  HDF5 file as \code{e1} under a temporary dataset name.

:::
## Details

Supported operators:
\describe{
  \item{`+`}{Element-wise addition}
  \item{`-`}{Element-wise subtraction}
  \item{`*`}{Element-wise multiplication (Hadamard product)}
  \item{`/`}{Element-wise division. Division by zero produces
    `NaN` or `Inf`, matching base R behaviour.}
}

All operations use block-wise processing and optional OpenMP parallelisation,
controlled via [hdf5matrix_options](../hdf5matrix_core/hdf5matrix_options.html).

**Performance settings:**

Global options set via [hdf5matrix_options](../hdf5matrix_core/hdf5matrix_options.html) are applied.
For explicit control use the R6 methods directly:
`A$add(B, paral = TRUE, threads = 4)`.

## Examples
```{r}
#| eval: false
#| warning: false

\donttest{
fn <- tempfile(fileext = ".h5")
A_hdf5 <- hdf5_create_matrix(fn, "data/A", data = matrix(1:12, 3, 4))
B_hdf5 <- hdf5_create_matrix(fn, "data/B", data = matrix(2, 3, 4))

C <- A_hdf5 + B_hdf5
D <- A_hdf5 - B_hdf5
E <- A_hdf5 * B_hdf5
G <- A_hdf5 / B_hdf5

all.equal(as.matrix(C), matrix(1:12, 3, 4) + 2)

hdf5_close_all()
unlink(fn)
}

```
## See Also

::: {.see-also}
[hdf5matrix_options](../hdf5matrix_core/hdf5matrix_options.html) for global performance settings,
`HDF5Matrix` for R6 methods with explicit parameters

:::