R for visualisation

# R for visualisation
## - the ggplot2 way -
### Athanasia Monika Mowinckel
### 12.04.2021

---

.pull-left[
<img src="https://www.sv.uio.no/psi/personer/vit/athanasm/athanasia.mowinckel.2.small.png" width="auto" height="600px" />
]

- Staff scientist  
- PhD in cognitive psychology  
- Software Carpentry Instructor  
- Currently doing quite some R-package development & other in-house research software development

**Find me**

- Twitter: [DrMowinckels](https://twitter.com/DrMowinckels)    
- GitHub: [Athanasiamo](https://github.com/Athanasiamo)  
- Website/Blog: [DrMowinckels.io](https://drmowinckels.io/)

]

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background-image: url(https://www.lifebrain.uio.no/vrtx/decorating/resources/images/logo.png), url(https://www.lifebrain.uio.no/web-banner_rev.jpg), url(https://www.lifebrain.uio.no/vrtx/decorating/resources/images/eu-flag.jpg)
background-position: 50% 10%, 60% 100%, 90% 10% 
background-size: 50%, 100%, 10%

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---
## Graphics systems in R

- ### base R
- ### [plotly](https://plotly.com/r/)
- ### [r2d3](https://rstudio.github.io/r2d3/)
- ### [lattice](http://lattice.r-forge.r-project.org/Vignettes/src/lattice-intro/lattice-intro.pdf)

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class: dark, bottom, center
background-image: url(img/ggplot2.png)
background-size: 30%
background-position: 50% 40%
name: ggplot

# Grammar of graphics

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background-image: url(img/ggplot2.png), url(https://www.bna.org.uk/media/resources/images/BNA2021_online_website_sm.png)
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## Overview

- `ggplot()`  - initiate a plot, call once  
- `geom_x()`  - add "geometry", call several times  
- `scale_x()` - scale aesthetics, call several times  
- `coord_x()` - alter coordinate system or "zoom" in/out, call once  
- `theme_x()` - alter general plot aesthetics, call maximum twice
- `labs()`    - alter labels (some overlap with `scale_x`), call once
- `facet_x()` - create grids of subplots, call once
]

- **Mapping** 
- Using variables from data  
- Always inside an `aes()`

- **Setting**
- Setting a single value for all data
- Never inside an `aes()`

]

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## Base-r `plot()`

.pull-left[
**Pros**
- versatile (can plot data, model outputs etc.)  
- quick  
- no extra dependencies (works out of the box)

**Cons**
- not very pretty  
- is not stored as an R 'object'  
- somewhat tricky to customise  
]

```r
plot(df_long$age.category, df_long$ffa)
```

<img src="index_files/figure-html/base-plot-1.png" width="504" />
]

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## general build-up

```r
ggplot(data = df_long)
```
]

???
These next slides I will run through really fast.
Don't worry about catching the code, we will be going through it
together shortly.
I just want to leaf through the process of constructing a complex plot,
before we start doing it step by step together. 
So don't worry that its going fast, I promise to get you on board more slowly soon.

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa))
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category,
                     y = ffa)) +
* geom_boxplot()
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa)) +
* geom_boxplot(aes(fill = age.category))
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa)) +
  geom_boxplot(aes(fill = age.category)) +
* scale_fill_brewer(palette = "Dark2")
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa)) +
  geom_boxplot(aes(fill = age.category)) +
  scale_fill_brewer(palette = "Dark2") +
* theme_light()
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa)) +
  geom_boxplot(aes(fill = age.category)) +
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
* labs(
*   title = "FFA activation across age categories",
*   subtitle = "distributions of repeated participant measurements",
*   x = "Age category",
*   y = "FFA activation",
*   fill = "Age category")
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa)) +
  geom_boxplot(aes(fill = age.category)) +
* geom_violin(aes(fill = age.category)) +
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
  labs(
    title = "FFA activation across age categories",
    subtitle = "distributions of repeated participant measurements",
    x = "Age category",
    y = "FFA activation", 
    fill = "Age category")
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa)) +
* geom_violin(aes(fill = age.category)) +
  geom_boxplot(aes(fill = age.category)) +
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
  labs(
    title = "FFA activation across age categories",
    subtitle = "distributions of repeated participant measurements",
    x = "Age category",
    y = "FFA activation", 
    fill = "Age category")
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa,
*                    fill = age.category)) +
* geom_violin(alpha = .5) +
* geom_boxplot(alpha = .5, width = .2) +
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
  labs(
    title = "FFA activation across age categories",
    subtitle = "distributions of repeated participant measurements",
    x = "Age category",
    y = "FFA activation", 
    fill = "Age category")
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa,
                     fill = age.category)) + 
* geom_jitter(alpha = .2, width = .2) +
  geom_violin(alpha = .5) + 
  geom_boxplot(alpha = .5, width = .2) + 
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
  labs(
    title = "FFA activation across age categories",
    subtitle = "distributions of repeated participant measurements",
    x = "Age category",
    y = "FFA activation", 
    fill = "Age category")
```
]

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa,
                     fill = age.category)) + 
* geom_dotplot(binaxis = "y",
*              stackdir='center',
*              dotsize = 0.5,
*              alpha = .6,
*              binwidth = .045) +
  geom_violin(alpha = .5) + 
  geom_boxplot(alpha = .5, width = .2) + 
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
  labs(
    title = "FFA activation across age categories",
    subtitle = "distributions of repeated participant measurements",
    x = "Age category",
    y = "FFA activation", 
    fill = "Age category")
```
]

---
background-image: url(img/ggplot2.png), url(https://www.bna.org.uk/media/resources/images/BNA2021_online_website_sm.png)
background-size: 8%, 15%
background-position: 95% 5%, 75% 5%

## general build-up

```r
ggplot(data = df_long,
       mapping = aes(x = age.category, 
                     y = ffa,
                     fill = age.category)) + 
  geom_dotplot(binaxis = "y",     
               stackdir='center', 
               dotsize = 0.5,     
               binwidth = .045,     
               alpha = .6) +      
  geom_violin(alpha = .5) + 
  geom_boxplot(alpha = .5, width = .2) + 
  scale_fill_brewer(palette = "Dark2") +
  theme_light() +
  labs(
    title = "FFA activation across age categories",
    subtitle = "distributions of repeated participant measurements",
    x = "Age category",
    y = "FFA activation", 
    fill = "Age category") +
* facet_wrap(~face.emotion)
```
]

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## Go to RStudio 
### live coding

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class: dark, middle, center

## Bonus stuff 
### shame-less promotion

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background-image: url(img/ggseg.png), url(https://www.bna.org.uk/media/resources/images/BNA2021_online_website_sm.png)
background-size: 8%, 15%
background-position: 95% 5%, 75% 5%

## ggseg - brain atlas plotting

```r
library(ggseg)
ggplot() + geom_brain(atlas = dk, position = position_brain(hemi ~ side))
```
<center>
<img src="index_files/figure-html/ggseg1-rend-1.png" width="504" />
<center>

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background-image: url(img/ggseg.png), url(https://www.bna.org.uk/media/resources/images/BNA2021_online_website_sm.png)
background-size: 8%, 15%
background-position: 95% 5%, 75% 5%

## ggseg - brain atlas plotting

```r
test_data <- dplyr::tribble(
  ~region, ~activation,
  "banksts", .5,
  "precentral", 1,
  "precuneus", 1.5,
  "lingual", .2
)

ggplot(test_data) + 
  geom_brain(
*   aes(fill = activation),
    atlas = dk,
    position = position_brain(hemi ~ side)
  )
```
]

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background-image: url(img/ggseg.png), url(https://www.bna.org.uk/media/resources/images/BNA2021_online_website_sm.png)
background-size: 8%, 15%
background-position: 95% 5%, 75% 5%

## ggseg - brain atlas plotting

```r
test_data <- dplyr::tribble(
  ~region, ~activation,
  "bankssts", .5,
  "precentral", 1,
  "precuneus", 1.5,
  "lingual", .2
)

ggplot(test_data) + 
  geom_brain(
*   aes(fill = activation),
    atlas = dk,
    position = position_brain(hemi ~ side)
  ) +
  scale_fill_viridis_c(na.value = "grey20") +
  theme_brain2()
```
]

---
background-image: url(img/ggseg.png), url(https://www.bna.org.uk/media/resources/images/BNA2021_online_website_sm.png)
background-size: 8%, 15%
background-position: 95% 5%, 75% 5%

## ggseg - brain atlas plotting

```r
ggseg_p <- ggplot(test_data) + 
  geom_brain(
    aes(fill = activation),
    atlas = dk,
    position = position_brain(hemi ~ side),
    show.legend = FALSE
  ) +
  theme_brain2()

bar_p <- ggplot(test_data, 
                aes(x = region, 
                    y = activation, 
                    fill = activation)) +
  geom_bar(stat = "identity") +
  theme_light()

*library(patchwork)
*ggseg_p / bar_p  &
* scale_fill_viridis_c(na.value = "grey20") &
* plot_annotation(
*   title = "Brain activation strength",
*   subtitle = "Desikan-Killiany atlas",
* )
```
]