---
title: "Reading FreeSurfer stats files"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Reading FreeSurfer stats files}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

FreeSurfer's `recon-all` produces stats files with region-level measures --
cortical thickness, surface area, volume. ggseg includes readers that pull
these files directly into data frames shaped for plotting.

All three functions below come from the `ggseg.formats` package, which ggseg
re-exports.

```{r}
#| label: load-packages
library(ggseg)
library(ggplot2)
library(dplyr)
```

## Reading a single stats file

After `recon-all` finishes, each subject has a `stats/` folder with
parcellation data. `read_freesurfer_stats()` reads one file at a time:

```{r}
#| label: read-single-stats
subjects_dir <- Sys.getenv("SUBJECTS_DIR")
stats_file <- file.path(subjects_dir, "bert/stats/lh.aparc.stats")

data <- read_freesurfer_stats(stats_file)
data
```

The hemisphere is encoded in the filename (`lh.` or `rh.`). To match the
atlas, prepend it to the label column:

```{r}
#| label: fig-single-stats
#| fig-cap: "Brain plot of average cortical thickness from a single stats file."
ggplot() +
  geom_brain(
    atlas = dk(),
    data = data |> mutate(label = paste0("lh_", label)),
    mapping = aes(fill = ThickAvg)
  )
```

## Reading stats files across subjects

`read_atlas_files()` reads all matching stats files from a subjects
directory. Pass a regular expression to select the right files:

```{r}
#| label: read-atlas-files
dat <- read_atlas_files(subjects_dir, "aparc.stats$")
dat
```

The trailing `$` matters -- it ensures you get `aparc.stats` but not
`aparc.a2009s.stats`.

The function adds hemisphere prefixes automatically, so the data is ready
for plotting:

```{r}
#| label: fig-atlas-files
#| fig-cap: "Brain plot of cortical thickness variability across subjects."
ggplot() +
  geom_brain(atlas = dk(), data = dat, mapping = aes(fill = ThickStd))
```

To show all metrics at once, pivot and facet:

```{r}
#| label: fig-all-metrics
#| fig-cap: "All FreeSurfer metrics shown in faceted brain plots."
#| fig-width: 10
library(tidyr)

long <- dat |>
  pivot_longer(-c(subject, label), names_to = "stat", values_to = "val")

ggplot() +
  geom_brain(
    atlas = dk(),
    data = group_by(long, stat),
    mapping = aes(fill = val)
  ) +
  facet_wrap(~stat)
```

## Reading FreeSurfer stats tables

FreeSurfer's `aparcstats2table` and `asegstats2table` commands create
summary tables across subjects. Read these with `read_freesurfer_table()`:

```{r}
#| label: read-fs-table
table_path <- "path/to/aparc.volume.table"

read_freesurfer_table(table_path)
```

The output has three columns: subject, label, and value.

## Cleaning label suffixes

Stats tables append the measure name to each label
(e.g. `lh_bankssts_volume`). The `measure` argument strips that suffix and
renames the value column:

```{r}
#| label: read-fs-table-measure
dat <- read_freesurfer_table(table_path, measure = "volume")
dat
```

## Filtering non-region rows

FreeSurfer tables include summary measures (total volume, ICV) that don't
correspond to atlas regions. Filter them before plotting:

```{r}
#| label: fig-filtered-table
#| fig-cap: "Brain plot of volume data after filtering non-region rows."
ggplot() +
  geom_brain(
    atlas = dk(),
    data = dat |> filter(grepl("lh|rh", label)),
    mapping = aes(fill = volume)
  )
```

The `grepl("lh|rh", label)` pattern keeps only hemisphere-specific rows.
