
```{r, echo=FALSE, message=FALSE, include=FALSE}
if (!requireNamespace("pacman")) install.packages("pacman")
packages_cran <- c("here")
pacman::p_load(char = packages_cran)
if (basename(here::here()) == "highspeed"){
  path_root = here::here("highspeed-decoding")
} else {
  path_root = here::here()
}
```

## Multivariate decoding

### Overview

#### Data availability

The data is freely available from https://github.com/lnnrtwttkhn/highspeed-decoding and https://gin.g-node.org/lnnrtwttkhn/highspeed-decoding.

#### License

The dataset is licensed under Creative Commons Attribution-ShareAlike 4.0.
Please see https://creativecommons.org/licenses/by-sa/4.0/ for details.

### Main decoding pipeline

Here, we show the Python code used to run the decoding pipeline:

```{python, echo=TRUE, code=readLines(file.path(path_root, "code", "decoding", "highspeed_decoding.py")), eval=FALSE, python.reticulate=FALSE}
```

### Parallelization on HPC

The decoding pipeline was parallelized on the local high performance cluster of the Max Planck Institute for Human Development, Berlin, Germany, using the following code:

```{bash, echo=TRUE, code=readLines(file.path(path_root, "code", "decoding", "highspeed-decoding-cluster.sh")), eval=FALSE}
```

### Software: Required packages

The `requirements.txt` file lists the required packages which can be installed e.g., using `pip install -r requirements.txt`

```{bash, echo=TRUE, code=readLines(file.path(path_root, "code", "decoding", "requirements.txt")), eval=FALSE}
```
