---
title: "Getting started"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Getting started}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

The API of anndata for R is very similar to its Python counterpart. 
Check out `?anndata` for a full list of the functions provided by this package.

```{r check_on_cran, message=FALSE, warning=FALSE, echo=FALSE}
on_cran <- !identical(Sys.getenv("NOT_CRAN"), "true")

if (on_cran) {
  knitr::opts_chunk$set(eval = FALSE)
  knitr::asis_output(paste0(
    "<span style=\"color: red;\">**WARNING:** The outputs of this vignette are not rendered on CRAN due to package size limitations. ",
    "Please check the [Getting started](https://anndata.dynverse.org/articles/getting_started.html) ",
    "vignette in the package documentation. </span>"
  ))
}
```

## Creating an AnnData object

`AnnData()` stores a data matrix `X` together with annotations
of observations `obs` (`obsm`, `obsp`), variables `var` (`varm`, `varp`),
and unstructured annotations `uns`. 

Here is an example of how to create an AnnData object with 2 observations and 3 variables.

```{r}
library(anndata)

ad <- AnnData(
  X = matrix(1:6, nrow = 2),
  obs = data.frame(group = c("a", "b"), row.names = c("s1", "s2")),
  var = data.frame(type = c(1L, 2L, 3L), row.names = c("var1", "var2", "var3")),
  layers = list(
    spliced = matrix(4:9, nrow = 2),
    unspliced = matrix(8:13, nrow = 2)
  ),
  obsm = list(
    ones = matrix(rep(1L, 10), nrow = 2),
    rand = matrix(rnorm(6), nrow = 2),
    zeros = matrix(rep(0L, 10), nrow = 2)
  ),
  varm = list(
    ones = matrix(rep(1L, 12), nrow = 3),
    rand = matrix(rnorm(6), nrow = 3),
    zeros = matrix(rep(0L, 12), nrow = 3)
  ),
  uns = list(
    a = 1,
    b = data.frame(i = 1:3, j = 4:6, value = runif(3)),
    c = list(c.a = 3, c.b = 4)
  )
)

ad
```

You can read the information back out using the `$` notation.
```{r}
ad$X
ad$obs
ad$obsm[["ones"]]
ad$layers[["spliced"]]
ad$uns[["b"]]
```


### Reading / writing AnnData objects

Read from h5ad format:
```{r, eval = FALSE}
read_h5ad("pbmc_1k_protein_v3_processed.h5ad")
```

### Creating a view

You can use any of the regular R indexing methods to subset the `AnnData` object.
This will result in a 'View' of the underlying data without needing to store 
the same data twice.
```{r}
view <- ad[, 2]
view
view$is_view

ad[, c("var1", "var2")]
ad[-1, ]
```

### AnnData as a matrix

The `X` attribute can be used as an R matrix:
```{r}
ad$X[, c("var1", "var2")]
ad$X[-1, , drop = FALSE]
ad$X[, 2] <- 10
```

You can access a different layer matrix as follows:
```{r}
ad$layers["unspliced"]
ad$layers["unspliced"][, c("var2", "var3")]
```

### Note on state
If you assign an AnnData object to another variable and
modify either, both will be modified:
```{r}
ad2 <- ad

ad$X[, 2] <- 10

list(ad = ad$X, ad2 = ad2$X)
```

This is standard Python behaviour but not R. In order to 
have two separate copies of an AnnData object, use the `$copy()` function:
```{r}
ad3 <- ad$copy()

ad$X[, 2] <- c(3, 4)

list(ad = ad$X, ad3 = ad3$X)
```
