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

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

library(ggseg)
devtools::load_all(".")
subject_dir <- here::here("tests/testthat/data/")

stats_file <- paste0(subject_dir, "bert/stats/lh.aparc.stats")
```


FreeSurfer already have files that are compatible with `ggseg` in some extent.
There are naming conventions and file-formats that are different, and as such it can at times be a little tricky to get data directly from FreeSurfer into R, and subsequently plotting in ggseg.

# Raw stats files
## Read in single raw stats file
If `recon-all` from FreeSurfer has been run, each participant should have a `stats` folder, with various parcellation data and summary statistics for those parcellations and measures. 
These have many header lines before the data actually start, and can have some formatting difficult to handle in R.

The function `read_freesurfer_stats` is made to easily read in raw stats tables from each individual, without needing to go through FreeSurfer's internal converters.
When using this file, remembering which hemisphere is read in is important, as this information must be added to the `label` column for `ggseg` to recognize the region labels.

```{r, eval=FALSE}
library(ggseg)
library(ggplot2)

subjects_dir <- "/Applications/freesurfer/subjects/"
```

```{r, echo = FALSE}
library(ggseg)
library(ggplot2)

subjects_dir <- here::here("tests/testthat/data")
```

```{r}
stats_file <- file.path(subjects_dir, "bert/stats/lh.aparc.stats")
data <- read_freesurfer_stats(stats_file)
data
```

This data should be well-suited for use with ggseg. 

```{r}
library(dplyr)
data %>% 
  mutate(label = paste0("lh_", label)) %>% 
  ggseg(atlas = dk, mapping = aes(fill = ThickAvg))
```


## Read in raw stats files for an atlas for all subjects

A convenience function also exists for those wanting to circumvent the `aparcstats2table` and `asegstats2table` from freesurfer for creating larger datasets of all subjects for a specific parcellation and metric. 
Using the function `read_freesurfer_stats`, `read_atlas_files` uses regular expression for the atlas you want to extract data from, and grabs this data from all available subjects. 
Be careful with your pattern matching to be sure you get exactly the atlas you want. 
For instance, there are several atlases with with string `aparc` in them. 
So in order to get only the default aparc stats, we need to specify `aparc.stats$`, which will only read those files ending with that particular string. 
This function _can_ throw warnings, which is most cases can be ignored.

```{r}
dat <- read_atlas_files(subject_dir, "aparc.stats$")
dat
```

Since all files are read in, the hemisphere in the label is already fixed, so it is easy to plot.

```{r}
ggseg(dat, mapping = aes(fill = ThickStd))
```


With this data, we can even have a look at all the metrics at once.

```{r out.width="100%", fig.width=10}
library(dplyr)
library(tidyr)

dat %>% 
  gather(stat, val, -subject, -label) %>% 
  group_by(stat) %>% 
  ggseg(mapping = aes(fill = val)) +
  facet_wrap(~stat)
```

# FreeSurfer stats tables
FreeSurfer has internal functions to convert their raw stats files into tables, gather subject into a single data file with particular metric.
It is quite common to use these files, but again the formatting is not something R is very happy with.
The function `read_freesurfer_table()` is for easier import of these files, particularly for further plotting with ggseg. 

```{r}
# Path to our particular file, yours will be wherever you have saved it
table_path <- here::here("tests/testthat/data/aparc.volume.table")
table_path
```

```{r}
read_freesurfer_table(table_path)
```

The file is read and has three columns only. The subject column, the label column, and a column with the values of the metric.
Since the stats tables can contain different measures, and these are handled somewhat differently, we for convenience leave the default reading of the table this way.
To work with ggseg, though, the labels usually (but not always) need a little cleaning. 
In this case we read in a `volume` table, and as such all labels end with "_volume". 
ggseg will _not_ recognize this matching the atlas, and will therefore not plot. 

Easiest way to clean, is by using the `measure` argument for the function.

```{r}
dat <- read_freesurfer_table(table_path, measure = "volume")
dat
```

This will do two things: 1) remove the label suffix, and 2) rename the `value` column to the measure supplied.
Alternatively, you will need to do string manipulation on the label column your self, we recommend the [stringr](https://stringr.tidyverse.org/index.html) package in that case.

```{r, eval = FALSE}
dat %>% 
  ggseg(mapping = aes(fill = volume))
```

An error will be thrown because the FreeSurfer tables also include measures of total volume/region/thickness, estimated intracranial volume etc, which will not merge into the atlas, and the internal ggseg atlas-merging function throws a warning. 
To avoid this, you can remove those labels before plotting.

```{r}
dat %>% 
  filter(grepl("lh|rh", label)) %>% 
  ggseg(mapping = aes(fill = volume))
```

