---
title: "Import and plot spline data from AAA"
author: "Stefano Coretta"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Import and plot spline data from AAA}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, echo=FALSE, include=FALSE}
knitr::opts_chunk$set(out.width = "300px", fig.align = "center", dpi = 300)
library(readr)
library(dplyr)
library(stringr)
library(ggplot2)
theme_set(theme_bw())
library(rticulate)
```

The package `rticulate` facilitates UTI data import and plotting with spline data exported from Articulate Assistant Advanced (AAA). To use the package, load it as usual.

```{r load, eval=FALSE}
library(rticulate)
```

# Import spline data

The function `read_aaa()` can quickly import spline data and transform it into the long format (where each observation is a point on a fan line and the coordinates values are two variables, `X` and `Y`, see `?tongue` for more details).

To correctly import AAA data, it is required that the file exported from AAA does not contain the header. This must be supplied as an argument to the `read_aaa()` function. We thus create a character vector with a concatenation of column names as strings.

```{r columns}
columns <- c(
    "speaker",
    "seconds",
    "rec_date",
    "prompt",
    "label",
    "TT_displacement",
    "TT_velocity",
    "TT_abs_velocity",
    "TD_displacement",
    "TD_velocity",
    "TD_abs_velocity"
)
```

Now we can use `read_aaa()` to import the spline data as a tibble. The function requires a string with the file path and name, and a vector with the names of the columns.

```{r read-aaa}
# system.file() is needed here because the example files reside in the package.
# You can just include the file path directly in read_aaa, like 
# read_aaa("~/Desktop/splines.tsv", columns)
file_path <- system.file("extdata", "it01.tsv", package = "rticulate")

tongue <- read_aaa(file_path, knots = 42, column_names = columns)
```

To check the head of the tibble, just do:

```{r tibble}
tongue
```

Sometimes is useful to add extra information for each prompt (like vowel, consonant place, phonation, etc.). We can do so by using functions from the `dplyr` package (`word()` is from the `stringr` package).

```{r join}
stimuli <- read_csv(system.file("extdata", "stimuli.csv", package = "rticulate"))

tongue <- mutate(tongue, word = word(prompt, 2)) %>%
    left_join(y = stimuli) %>%
    mutate_if(is.character, as.factor)
```

Let's check `tongue` again.

```{r tibble-2}
tongue
```

# Plot splines

To plot splines from a spline data frame, use `plot_tongue()`. This function is a wrapper of a `ggplot` call (from the `ggplot2` package). The coordinates must be in two variables named `X` and `Y`. `read_aaa()` creates them automatically while importing the raw data.

```{r plot-splines}
plot_tongue(tongue)
```

You can also easily filter the tibble with the `filter()` function from `dplyr`.

```{r filter-plot}
filter(tongue, label == "max_TD") %>%
    plot_tongue()
```

You can specify `geom` options and aesthetics in the usual `ggplot` way (remember to load the package with `library(ggplot2)` if you need this). `geom` options are arguments of `plot_tongue()`, while aesthetics can be called with `aes()`.

```{r plot-options}
plot_tongue(tongue, alpha = 0.5) +
    aes(group = rec_date, colour = c2_place) +
    theme(legend.position = "bottom")
```

To plot points instead of splines, use `plot_tongue(geom = "point")`.

```{r plot-geom}
plot_tongue(tongue, geom = "point", alpha = 0.5) +
    aes(group = rec_date, colour = c2_place) +
    theme(legend.position = "bottom")
```

Finally, if you want to plot the palate profile, you can do so by specifying a data frame with the coordinates for the palate spline.

```{r plot-palate}
palate <- read_aaa(system.file("extdata", "it01-palate.tsv", package = "rticulate"), knots = 42, column_names = columns)

filter(tongue, label == "max_TD") %>%
    plot_tongue(palate = palate, alpha = 0.5) + aes(group = rec_date)
```

# Import multiple files

To import multiple files with AAA data, simply use a list of paths with `read_aaa`, for example using `list.files`.

```{r read-multiple}
tongue2 <- list.files(
    path = system.file("extdata", package = "rticulate"),
    pattern = "*\\d{2}.tsv",
    full.names = TRUE
    ) %>%
    read_aaa(., knots = 42, column_names = columns)
```

We can now plot splines for both speakers.

```{r plot-speakers}
plot_tongue(tongue2, alpha = 0.5) +
    aes(group = rec_date) +
    facet_grid(. ~ speaker)
```
