---
title: Saving and reloading DelayedArray objects
author:
- name: Aaron Lun
  email: infinite.monkeys.with.keyboards@gmail.com
date: "Revised: 2021-05-02"
package: chihaya 
output:
  BiocStyle::html_document
vignette: >
  %\VignetteIndexEntry{User guide}
  %\VignetteEngine{knitr::rmarkdown}
  %VignetteEncoding{UTF-8}  
---

```{r, echo=FALSE}
library(BiocStyle)
knitr::opts_chunk$set(error=FALSE, warning=FALSE, message=FALSE)
```

# Motivation

The `r Biocpkg("chihaya")` package saves `DelayedArray` objects for efficient, portable and stable reproduction of delayed operations in a new R session or other programming frameworks.

- **Portability**.
  We provide a file specification in a standard format (HDF5) that enables other languages to easily interpret and reproduce the delayed operations.
- **Stability**.
  By converting `r Biocpkg("DelayedArray")` operations into our specification, we provide a layer of protection against changes in the S4 class structure that would invalidate serialized RDS objects.
- **Efficiency**. 
  We avoid any realization of the delayed operations, enabling quick saving and avoiding loss of data structure in the seed (e.g., sparsity).

Check out the [specification](https://ltla.github.io/chihaya) for more details.

# Quick start

Make a `DelayedArray` object with some operations:

```{r}
library(DelayedArray)
x <- DelayedArray(matrix(runif(1000), ncol=10))
x <- x[11:15,] / runif(5) 
x <- log2(x + 1)
x
showtree(x)
```

Save it into a HDF5 file with `saveDelayed()`:

```{r}
library(chihaya)
tmp <- tempfile(fileext=".h5")
saveDelayed(x, tmp)
rhdf5::h5ls(tmp)
```

And then load it back in later:

```{r}
y <- loadDelayed(tmp)
y
```

Of course, this is not a particularly interesting case as we end up saving the original array inside our HDF5 file anyway.
The real fun begins when you have some more interesting seeds.

# More interesting seeds

We can use the delayed nature of the operations to avoid breaking sparsity.
For example:

```{r}
library(Matrix)
x <- rsparsematrix(1000, 1000, density=0.01)
x <- DelayedArray(x) + runif(1000)

tmp <- tempfile(fileext=".h5")
saveDelayed(x, tmp)
rhdf5::h5ls(tmp)
file.info(tmp)[["size"]]

# Compared to a dense array.
tmp2 <- tempfile(fileext=".h5")
out <- HDF5Array::writeHDF5Array(x, tmp2, "data")
file.info(tmp2)[["size"]]

# Loading it back in.
y <- loadDelayed(tmp)
showtree(y)
```

We can also store references to external files, thus avoiding data duplication:

```{r}
library(HDF5Array)
test <- HDF5Array(tmp2, "data")
stuff <- log2(test + 1)
stuff

tmp <- tempfile(fileext=".h5")
saveDelayed(stuff, tmp)
rhdf5::h5ls(tmp)
file.info(tmp)[["size"]] # size of the delayed operations + pointer to the actual file

y <- loadDelayed(tmp)
y
```

# Session information {-}

```{r}
sessionInfo()
```
