‘extending ggplot2’

# ‘extending ggplot2’

---

# 0. Modify existing geoms/stats

examples base on those in https://ggplot2-book.org/programming.html

---

```r
*ggplot(mpg, aes(displ, 1 / hwy))
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_01_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
* geom_point()
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_02_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
* geom_smooth()
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_03_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
*g0
```
]
 
.panel2-existing-auto[

]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

*geom_lm <- function(formula = y ~ x,
*                   colour = alpha("steelblue", 0.5),
*                   size = 2, ...)  {
* geom_smooth(formula = formula,
*             se = FALSE, method = "lm",
*             colour = colour,
*   size = size, ...)
*} 
```
]
 
.panel2-existing-auto[

]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

geom_lm <- function(formula = y ~ x,
                    colour = alpha("steelblue", 0.5),
                    size = 2, ...)  {
  geom_smooth(formula = formula,
              se = FALSE, method = "lm",
              colour = colour,
    size = size, ...)
}

*ggplot(mpg, aes(displ, 1 / hwy))
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_06_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
* geom_point()
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_07_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
* geom_lm()
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_08_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
*g1
```
]
 
.panel2-existing-auto[

]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
g1

*ggplot(mpg, aes(displ, 1 / hwy))
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_10_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
g1

ggplot(mpg, aes(displ, 1 / hwy)) +
* geom_point()
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_11_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
g1

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
* geom_lm(formula = y ~ poly(x, 2),
*         size = 1, colour = "red")
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_12_output-1.png" width="576" />
]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
g1

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm(formula = y ~ poly(x, 2),
          size = 1, colour = "red") ->
*g2
```
]
 
.panel2-existing-auto[

]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
g1

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm(formula = y ~ poly(x, 2),
          size = 1, colour = "red") ->
g2

*library(patchwork)
```
]
 
.panel2-existing-auto[

]

---
count: false
 
### Modifying an existing geom
.panel1-existing-auto[

```r
ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_smooth() ->
g0

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm() ->
g1

ggplot(mpg, aes(displ, 1 / hwy)) +
  geom_point() +
  geom_lm(formula = y ~ poly(x, 2),
          size = 1, colour = "red") ->
g2

library(patchwork)

*g0 + g1 + g2
```
]
 
.panel2-existing-auto[
<img src="extending_ggplot2_files/figure-html/existing_auto_15_output-1.png" width="576" />
]

---

count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

```r
*ggplot(mpg, aes(class, cty))
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_01_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

```r
ggplot(mpg, aes(class, cty)) +
* stat_summary(fun = "mean", geom = "bar", fill = "grey70")
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_02_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

```r
ggplot(mpg, aes(class, cty)) +
  stat_summary(fun = "mean", geom = "bar", fill = "grey70") +
* stat_summary(fun.data = "mean_cl_normal", geom = "errorbar", width = 0.4)
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_03_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

```r
ggplot(mpg, aes(class, cty)) +
  stat_summary(fun = "mean", geom = "bar", fill = "grey70") +
  stat_summary(fun.data = "mean_cl_normal", geom = "errorbar", width = 0.4) +
* geom_point(alpha = .4)
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_04_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

```r
ggplot(mpg, aes(class, cty)) +
  stat_summary(fun = "mean", geom = "bar", fill = "grey70") +
  stat_summary(fun.data = "mean_cl_normal", geom = "errorbar", width = 0.4) +
  geom_point(alpha = .4) ->
*g0
```
]
 
.panel2-combining_layers-auto[

]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

*geom_mean <- function(alpha = .4, fill = "magenta") {
* list(
*   stat_summary(fun = "mean", geom = "bar", fill = fill, alpha = alpha),
*   stat_summary(fun.data = "mean_cl_normal", geom = "errorbar", width = 0.4),
*   geom_point(alpha = alpha)
* )
*} 
```
]
 
.panel2-combining_layers-auto[

]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

geom_mean <- function(alpha = .4, fill = "magenta") {
  list(
    stat_summary(fun = "mean", geom = "bar", fill = fill, alpha = alpha),
    stat_summary(fun.data = "mean_cl_normal", geom = "errorbar", width = 0.4),
    geom_point(alpha = alpha)
  )
}

*ggplot(mpg, aes(class, cty))
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_07_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
* geom_mean()
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_08_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
  geom_mean() ->
*g1
```
]
 
.panel2-combining_layers-auto[

]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
  geom_mean() ->
g1

*ggplot(mpg, aes(class, cty))
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_10_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
  geom_mean() ->
g1

ggplot(mpg, aes(class, cty)) +
* geom_mean(fill = "blue", alpha = .2)
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_11_output-1.png" width="576" />
]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
  geom_mean() ->
g1

ggplot(mpg, aes(class, cty)) +
  geom_mean(fill = "blue", alpha = .2) ->
*g2
```
]
 
.panel2-combining_layers-auto[

]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
  geom_mean() ->
g1

ggplot(mpg, aes(class, cty)) +
  geom_mean(fill = "blue", alpha = .2) ->
g2

*library(patchwork)
```
]
 
.panel2-combining_layers-auto[

]

---
count: false
 
### Combining existing geoms/stats into a single call
.panel1-combining_layers-auto[

ggplot(mpg, aes(class, cty)) +
  geom_mean() ->
g1

ggplot(mpg, aes(class, cty)) +
  geom_mean(fill = "blue", alpha = .2) ->
g2

library(patchwork)
*g0 + g1 + g2
```
]
 
.panel2-combining_layers-auto[
<img src="extending_ggplot2_files/figure-html/combining_layers_auto_14_output-1.png" width="576" />
]

---

# 1. Building new geoms

## a. springs

This example is https://ggplot2-book.org/spring1.html

---

```r
*tibble(
* x = sin(seq(0, 2*pi, length.out = 100)),
* y = cos(seq(0, 2*pi, length.out = 100)),
* index = 1:100,
* type = "circle"
*) 
```
]
 
.panel2-spring-auto[

```
# A tibble: 100 x 4
        x     y index type  
    <dbl> <dbl> <int> <chr> 
 1 0      1         1 circle
 2 0.0634 0.998     2 circle
 3 0.127  0.992     3 circle
 4 0.189  0.982     4 circle
 5 0.251  0.968     5 circle
 6 0.312  0.950     6 circle
 7 0.372  0.928     7 circle
 8 0.430  0.903     8 circle
 9 0.486  0.874     9 circle
10 0.541  0.841    10 circle
# … with 90 more rows
```
]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
* circle
```
]
 
.panel2-spring-auto[

]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

*spring <- circle
```
]
 
.panel2-spring-auto[

]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

*spring$x + seq(0, 1.5, length.out = 100) -> spring$x
```
]
 
.panel2-spring-auto[

]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
*spring$type <- "spring"
```
]
 
.panel2-spring-auto[

]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
spring$type <- "spring"

*rbind(circle, spring)
```
]
 
.panel2-spring-auto[

```
# A tibble: 200 x 4
        x     y index type  
    <dbl> <dbl> <int> <chr> 
 1 0      1         1 circle
 2 0.0634 0.998     2 circle
 3 0.127  0.992     3 circle
 4 0.189  0.982     4 circle
 5 0.251  0.968     5 circle
 6 0.312  0.950     6 circle
 7 0.372  0.928     7 circle
 8 0.430  0.903     8 circle
 9 0.486  0.874     9 circle
10 0.541  0.841    10 circle
# … with 190 more rows
```
]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
spring$type <- "spring"

rbind(circle, spring) %>%
* ggplot()
```
]
 
.panel2-spring-auto[
<img src="extending_ggplot2_files/figure-html/spring_auto_07_output-1.png" width="576" />
]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
spring$type <- "spring"

rbind(circle, spring) %>%
  ggplot() +
* facet_wrap(~ type, scales = "free_x")
```
]
 
.panel2-spring-auto[
<img src="extending_ggplot2_files/figure-html/spring_auto_08_output-1.png" width="576" />
]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
spring$type <- "spring"

rbind(circle, spring) %>%
  ggplot() +
  facet_wrap(~ type, scales = "free_x") +
* aes(x = x, y = y, group = type, alpha = index)
```
]
 
.panel2-spring-auto[
<img src="extending_ggplot2_files/figure-html/spring_auto_09_output-1.png" width="576" />
]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
spring$type <- "spring"

rbind(circle, spring) %>%
  ggplot() +
  facet_wrap(~ type, scales = "free_x") +
  aes(x = x, y = y, group = type, alpha = index) +
* geom_point(show.legend = FALSE)
```
]
 
.panel2-spring-auto[
<img src="extending_ggplot2_files/figure-html/spring_auto_10_output-1.png" width="576" />
]

---
count: false
 
### Thinking about springs
.panel1-spring-auto[

```r
tibble(
  x = sin(seq(0, 2*pi, length.out = 100)),
  y = cos(seq(0, 2*pi, length.out = 100)),
  index = 1:100,
  type = "circle"
) ->
  circle

spring <- circle

spring$x + seq(0, 1.5, length.out = 100) -> spring$x
spring$type <- "spring"

rbind(circle, spring) %>%
  ggplot() +
  facet_wrap(~ type, scales = "free_x") +
  aes(x = x, y = y, group = type, alpha = index) +
  geom_point(show.legend = FALSE) +
* geom_path(show.legend = FALSE)
```
]
 
.panel2-spring-auto[
<img src="extending_ggplot2_files/figure-html/spring_auto_11_output-1.png" width="576" />
]

---

count: false
 
### Writing and using a general spring function
.panel1-create_spring-auto[

```r
*create_spring <- function(x, y, xend, yend, diameter, tension, n) {
* if (tension <= 0) {
*   rlang::abort("`tension` must be larger than 0")
* }
# Calculate direct length of segment
* length <- sqrt((x - xend)^2 + (y - yend)^2)

# Figure out how many revolutions and points we need
* n_revolutions <- length / (diameter * tension)
* n_points <- n * n_revolutions

# Calculate sequence of radians and x and y offset
* radians <- seq(0, n_revolutions * 2 * pi, length.out = n_points)
* x <- seq(x, xend, length.out = n_points)
* y <- seq(y, yend, length.out = n_points)

# Create the new data
* data.frame(
*   x = cos(radians) * diameter/2 + x,
*   y = sin(radians) * diameter/2 + y
* )
*} 
```
]
 
.panel2-create_spring-auto[

]

---
count: false
 
### Writing and using a general spring function
.panel1-create_spring-auto[

```r
create_spring <- function(x, y, xend, yend, diameter, tension, n) {
  if (tension <= 0) {
    rlang::abort("`tension` must be larger than 0")
  }
# Calculate direct length of segment
  length <- sqrt((x - xend)^2 + (y - yend)^2)

# Figure out how many revolutions and points we need
  n_revolutions <- length / (diameter * tension)
  n_points <- n * n_revolutions

# Calculate sequence of radians and x and y offset
  radians <- seq(0, n_revolutions * 2 * pi, length.out = n_points)
  x <- seq(x, xend, length.out = n_points)
  y <- seq(y, yend, length.out = n_points)

# Create the new data
  data.frame(
    x = cos(radians) * diameter/2 + x,
    y = sin(radians) * diameter/2 + y
  )
}

*create_spring(
* x = 4, y = 2,
* xend = 10, yend = 6,
* diameter = 2,
* tension = 0.75, n = 20
*) 
```
]
 
.panel2-create_spring-auto[

```
           x        y
1   5.000000 2.000000
2   5.013407 2.351144
3   4.933447 2.671902
4   4.774109 2.934870
5   4.557173 3.118320
6   4.310078 3.208330
7   4.063220 3.200154
8   3.846975 3.098686
9   3.688711 2.917979
10  3.610105 2.679868
11  3.625012 2.411822
12  3.738104 2.144253
13  3.944414 1.907522
14  4.229821 1.728964
15  4.572440 1.630203
16  4.944767 1.625026
17  5.316379 1.718034
18  5.656928 1.904184
19  5.939112 2.169292
20  6.141360 2.491417
21  6.249953 2.843022
22  6.260364 3.193676
23  6.177707 3.513041
24  6.016235 3.773849
25  5.797939 3.954585
26  5.550389 4.041593
27  5.304029 4.030422
28  5.089183 3.926260
29  4.933085 3.743424
30  4.857196 3.503959
31  4.875106 3.235467
32  4.991191 2.968402
33  5.200192 2.733078
34  5.487723 2.556690
35  5.831689 2.460650
36  6.204455 2.458477
37  6.575555 2.554477
38  6.914691 2.743315
39  7.194700 3.010540
40  7.394225 3.334006
41  7.499812 3.686043
42  7.507232 4.036178
43  7.421891 4.354123
44  7.258306 4.612751
45  7.038676 4.790760
46  6.790702 4.874762
47  6.544868 4.860601
48  6.331448 4.753759
49  6.177535 4.568816
50  6.104377 4.328023
51  6.125293 4.059114
52  6.244368 3.792582
53  6.456045 3.558690
54  6.745678 3.384493
55  7.090965 3.291186
56  7.464141 3.292022
57  7.834701 3.391009
58  8.172398 3.582520
59  8.450211 3.851842
60  8.646999 4.176622
61  8.749578 4.529062
62  8.754011 4.878649
63  8.666000 5.195149
64  8.500324 5.451577
65  8.279386 5.626845
66  8.031017 5.707838
67  7.785738 5.690692
68  7.573770 5.581183
69  7.422063 5.394154
70  7.351647 5.152060
71  7.375575 4.882762
72  7.497633 4.616794
73  7.711973 4.384360
74  8.003686 4.212373
75  8.350268 4.121812
76  8.723825 4.125660
77  9.093815 4.227629
78  9.430047 4.421800
79  9.705644 4.693197
80  9.899684 5.019265
81  9.999249 5.372079
82 10.000702 5.721089
83  9.910036 6.036117
84  9.742290 6.290324
85  9.520071 6.462841
86  9.271334 6.540819
87  9.026640 6.520694
88  8.816150 6.408533
89  8.666668 6.219439
90  8.599008 5.976071
91  8.625950 5.706414
92  8.750986 5.441037
93  8.967974 5.210087
94  9.261747 5.040331
95  9.609597 4.952529
96  9.983506 4.959392
97 10.352897 5.064338
```
]

---
count: false
 
### Writing and using a general spring function
.panel1-create_spring-auto[

# Figure out how many revolutions and points we need
  n_revolutions <- length / (diameter * tension)
  n_points <- n * n_revolutions

# Create the new data
  data.frame(
    x = cos(radians) * diameter/2 + x,
    y = sin(radians) * diameter/2 + y
  )
}

create_spring(
  x = 4, y = 2,
  xend = 10, yend = 6,
  diameter = 2,
  tension = 0.75, n = 20
) %>%
* ggplot()
```
]
 
.panel2-create_spring-auto[
<img src="extending_ggplot2_files/figure-html/create_spring_auto_03_output-1.png" width="576" />
]

---
count: false
 
### Writing and using a general spring function
.panel1-create_spring-auto[

# Figure out how many revolutions and points we need
  n_revolutions <- length / (diameter * tension)
  n_points <- n * n_revolutions

# Create the new data
  data.frame(
    x = cos(radians) * diameter/2 + x,
    y = sin(radians) * diameter/2 + y
  )
}

create_spring(
  x = 4, y = 2,
  xend = 10, yend = 6,
  diameter = 2,
  tension = 0.75, n = 20
) %>%
  ggplot() +
* aes(x = x, y = y)
```
]
 
.panel2-create_spring-auto[
<img src="extending_ggplot2_files/figure-html/create_spring_auto_04_output-1.png" width="576" />
]

---
count: false
 
### Writing and using a general spring function
.panel1-create_spring-auto[

# Figure out how many revolutions and points we need
  n_revolutions <- length / (diameter * tension)
  n_points <- n * n_revolutions

# Create the new data
  data.frame(
    x = cos(radians) * diameter/2 + x,
    y = sin(radians) * diameter/2 + y
  )
}

create_spring(
  x = 4, y = 2,
  xend = 10, yend = 6,
  diameter = 2,
  tension = 0.75, n = 20
) %>%
  ggplot() +
  aes(x = x, y = y) +
* geom_point()
```
]
 
.panel2-create_spring-auto[
<img src="extending_ggplot2_files/figure-html/create_spring_auto_05_output-1.png" width="576" />
]

---
count: false
 
### Writing and using a general spring function
.panel1-create_spring-auto[

# Figure out how many revolutions and points we need
  n_revolutions <- length / (diameter * tension)
  n_points <- n * n_revolutions

# Create the new data
  data.frame(
    x = cos(radians) * diameter/2 + x,
    y = sin(radians) * diameter/2 + y
  )
}

create_spring(
  x = 4, y = 2,
  xend = 10, yend = 6,
  diameter = 2,
  tension = 0.75, n = 20
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
* geom_path()
```
]
 
.panel2-create_spring-auto[
<img src="extending_ggplot2_files/figure-html/create_spring_auto_06_output-1.png" width="576" />
]

---

```r
StatSpring <- ggproto("StatSpring", Stat, 
  setup_params = function(data, params) {
    if (is.null(params$diameter)) {
      params$diameter <- 1
    } else if (params$diameter == 0) {
      rlang::abort("Springs cannot be defined with a diameter of 0")
    }
    if (is.null(params$tension)) {
      params$tension <- 0.75
    } else if (params$tension <= 0) {
      rlang::abort("Springs must be defined with a tension greater than 0")
    }
    if (is.null(params$n)) {
      params$n <- 50
    } else if (params$n <= 0) {
      rlang::abort("Springs must be defined with `n` greater than 0")
    }
    params
  },
  setup_data = function(data, params) {
    if (anyDuplicated(data$group)) {
      data$group <- paste(data$group, seq_len(nrow(data)), sep = "-")
    }
    data
  },
  compute_panel = function(data, scales, diameter = 1, tension = 0.75, 
                           n = 50) {
    cols_to_keep <- setdiff(names(data), c("x", "y", "xend", "yend"))
    springs <- lapply(seq_len(nrow(data)), function(i) {
      spring_path <- create_spring(data$x[i], data$y[i], data$xend[i], 
                                   data$yend[i], diameter, tension, n)
      cbind(spring_path, unclass(data[i, cols_to_keep]))
    })
    do.call(rbind, springs)
  },
  required_aes = c("x", "y", "xend", "yend")
)
```

---

count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
*tibble(x = 1:2,
*      y = 4:3,
*      xend = 5:6,
*      yend = 8:7)
```
]
 
.panel2-unpack-auto[

```
# A tibble: 2 x 4
      x     y  xend  yend
  <int> <int> <int> <int>
1     1     4     5     8
2     2     3     6     7
```
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
* mutate(group = row_number())
```
]
 
.panel2-unpack-auto[

```
# A tibble: 2 x 5
      x     y  xend  yend group
  <int> <int> <int> <int> <int>
1     1     4     5     8     1
2     2     3     6     7     2
```
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
*data
```
]
 
.panel2-unpack-auto[

]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

*diameter = 1
```
]
 
.panel2-unpack-auto[

]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
*tension = 0.75
```
]
 
.panel2-unpack-auto[

]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
*n = 2
```
]
 
.panel2-unpack-auto[

]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

*setdiff(names(data), c("x", "y", "xend", "yend"))
```
]
 
.panel2-unpack-auto[

```
[1] "group"
```
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

* cols_to_keep
```
]
 
.panel2-unpack-auto[

]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

*   springs <- lapply(seq_len(nrow(data)), function(i) {

*     spring_path <- create_spring(x = data$x[i], y = data$y[i], xend =
*                                   data$xend[i], yend =
*                                  data$yend[i], diameter = diameter,
*                                   tension = tension,
*                                  n = n)
*     cbind(spring_path, unclass(data[i, cols_to_keep]))

*   })
```
]
 
.panel2-unpack-auto[

]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

springs <- lapply(seq_len(nrow(data)), function(i) {

spring_path <- create_spring(x = data$x[i], y = data$y[i], xend =
                                    data$xend[i], yend =
                                   data$yend[i], diameter = diameter,
                                    tension = tension,
                                   n = n)
      cbind(spring_path, unclass(data[i, cols_to_keep]))

})

*do.call(rbind, springs)
```
]
 
.panel2-unpack-auto[

```
           x        y group
1  1.5000000 4.000000     1
2  0.7667458 4.257772     1
3  2.0330169 4.551120     1
4  1.3007120 4.773327     1
5  2.5654012 5.102218     1
6  1.8353102 5.288915     1
7  3.0971541 5.653271     1
8  2.3705389 5.804560     1
9  3.6282777 6.204256     1
10 2.9063957 6.320283     1
11 4.1587747 6.755152     1
12 3.4428773 6.836107     1
13 4.6886488 7.305936     1
14 3.9799798 7.352055     1
15 5.2179043 7.856585     1
16 4.5176984 7.868147     1
17 2.5000000 3.000000     2
18 1.7667458 3.257772     2
19 3.0330169 3.551120     2
20 2.3007120 3.773327     2
21 3.5654012 4.102218     2
22 2.8353102 4.288915     2
23 4.0971541 4.653271     2
24 3.3705389 4.804560     2
25 4.6282777 5.204256     2
26 3.9063957 5.320283     2
27 5.1587747 5.755152     2
28 4.4428773 5.836107     2
29 5.6886488 6.305936     2
30 4.9799798 6.352055     2
31 6.2179043 6.856585     2
32 5.5176984 6.868147     2
```
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

springs <- lapply(seq_len(nrow(data)), function(i) {

})

do.call(rbind, springs) %>%
* ggplot()
```
]
 
.panel2-unpack-auto[
<img src="extending_ggplot2_files/figure-html/unpack_auto_11_output-1.png" width="576" />
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

springs <- lapply(seq_len(nrow(data)), function(i) {

})

do.call(rbind, springs) %>%
  ggplot() +
* aes(x = x, y = y, color = group)
```
]
 
.panel2-unpack-auto[
<img src="extending_ggplot2_files/figure-html/unpack_auto_12_output-1.png" width="576" />
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

springs <- lapply(seq_len(nrow(data)), function(i) {

})

do.call(rbind, springs) %>%
  ggplot() +
  aes(x = x, y = y, color = group) +
* geom_point(data = data, color = "black")
```
]
 
.panel2-unpack-auto[
<img src="extending_ggplot2_files/figure-html/unpack_auto_13_output-1.png" width="576" />
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

springs <- lapply(seq_len(nrow(data)), function(i) {

})

do.call(rbind, springs) %>%
  ggplot() +
  aes(x = x, y = y, color = group) +
  geom_point(data = data, color = "black") +
* geom_point(data = data, aes(x = xend, y = yend), color = "red")
```
]
 
.panel2-unpack-auto[
<img src="extending_ggplot2_files/figure-html/unpack_auto_14_output-1.png" width="576" />
]

---
count: false
 
### Let's unpack that data manipulation that happens with a 2-row data set.
.panel1-unpack-auto[

```r
tibble(x = 1:2,
       y = 4:3,
       xend = 5:6,
       yend = 8:7) %>%
  mutate(group = row_number())->
data

diameter = 1
tension = 0.75
n = 2

setdiff(names(data), c("x", "y", "xend", "yend")) ->

cols_to_keep

springs <- lapply(seq_len(nrow(data)), function(i) {

})

do.call(rbind, springs) %>%
  ggplot() +
  aes(x = x, y = y, color = group) +
  geom_point(data = data, color = "black") +
  geom_point(data = data, aes(x = xend, y = yend), color = "red") +
* geom_point()
```
]
 
.panel2-unpack-auto[
<img src="extending_ggplot2_files/figure-html/unpack_auto_15_output-1.png" width="576" />
]

---

```r
geom_spring <- function(mapping = NULL, data = NULL, stat = "spring", 
                        position = "identity", ..., diameter = 1, tension = 0.75, 
                        n = 50, arrow = NULL, lineend = "butt", linejoin = "round", 
                        na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) {
  layer(
    data = data, 
    mapping = mapping, 
    stat = stat, 
    geom = GeomPath, 
    position = position, 
    show.legend = show.legend, 
    inherit.aes = inherit.aes, 
    params = list(
      diameter = diameter, 
      tension = tension, 
      n = n, 
      arrow = arrow, 
      lineend = lineend, 
      linejoin = linejoin, 
      na.rm = na.rm, 
      ...
    )
  )
}
```

---

```r
*set.seed(123)
```
]
 
.panel2-use_spring-auto[

]

---
count: false

```r
set.seed(123)
*tibble(
* x = runif(5, max = 10),
* y = runif(5, max = 10),
* xend = runif(5, max = 10),
* yend = runif(5, max = 10),
* class = 1:5
*) 
```
]
 
.panel2-use_spring-auto[

```
# A tibble: 5 x 5
      x     y  xend  yend class
  <dbl> <dbl> <dbl> <dbl> <int>
1  2.88 0.456  9.57 9.00      1
2  7.88 5.28   4.53 2.46      2
3  4.09 8.92   6.78 0.421     3
4  8.83 5.51   5.73 3.28      4
5  9.40 4.57   1.03 9.55      5
```
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
* ggplot()
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_03_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
* aes(x = x, y = y)
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_04_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
* geom_point()
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_05_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
* geom_point(aes(x = xend, y = yend), color = "red")
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_06_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  geom_point(aes(x = xend, y = yend), color = "red") +
* facet_wrap(~class)
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_07_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  geom_point(aes(x = xend, y = yend), color = "red") +
  facet_wrap(~class) +
* aes(xend = xend, yend = yend)
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_08_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  geom_point(aes(x = xend, y = yend), color = "red") +
  facet_wrap(~class) +
  aes(xend = xend, yend = yend) +
* geom_spring()
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_09_output-1.png" width="576" />
]

---
count: false

```r
set.seed(123)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  xend = runif(5, max = 10),
  yend = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  geom_point(aes(x = xend, y = yend), color = "red") +
  facet_wrap(~class) +
  aes(xend = xend, yend = yend) +
  geom_spring() +
* geom_spring(tension = .9, diameter = 2,
*             color = "magenta", alpha = .7)
```
]
 
.panel2-use_spring-auto[
<img src="extending_ggplot2_files/figure-html/use_spring_auto_10_output-1.png" width="576" />
]

---

## b. circle

This one based on the idea from T. Pedersen's talk
https://rstudio.com/resources/rstudioconf-2020/extending-your-ability-to-extend-ggplot2/

He seems to get it done in a more succinct way, so something to come back to.

---

```r
*create_circle <- function(x0, y0, r = 1, n = 100){

* angels <- seq(

*   from = 0,
*   to = 2*pi,
*   length.out = n + 1

* )

* data.frame(
*   x = cos(angels) * r + x0,
*   y = sin(angels) * r + y0
* )

*} 
```
]
 
.panel2-circle-auto[

]

---
count: false

```r
create_circle <- function(x0, y0, r = 1, n = 100){

angels <- seq(

from = 0,
    to = 2*pi,
    length.out = n + 1

)

data.frame(
    x = cos(angels) * r + x0,
    y = sin(angels) * r + y0
  )

}

*create_circle(x0 = 1, y0 = 2, r = 2)
```
]
 
.panel2-circle-auto[

```
              x           y
1    3.00000000 2.000000000
2    2.99605346 2.125581039
3    2.98422940 2.250666467
4    2.96457450 2.374762629
5    2.93716632 2.497379774
6    2.90211303 2.618033989
7    2.85955297 2.736249105
8    2.80965410 2.851558583
9    2.75261336 2.963507348
10   2.68865585 3.071653590
11   2.61803399 3.175570505
12   2.54102649 3.274847979
13   2.45793725 3.369094212
14   2.36909421 3.457937255
15   2.27484798 3.541026486
16   2.17557050 3.618033989
17   2.07165359 3.688655851
18   1.96350735 3.752613360
19   1.85155858 3.809654105
20   1.73624911 3.859552972
21   1.61803399 3.902113033
22   1.49737977 3.937166322
23   1.37476263 3.964574501
24   1.25066647 3.984229403
25   1.12558104 3.996053457
26   1.00000000 4.000000000
27   0.87441896 3.996053457
28   0.74933353 3.984229403
29   0.62523737 3.964574501
30   0.50262023 3.937166322
31   0.38196601 3.902113033
32   0.26375089 3.859552972
33   0.14844142 3.809654105
34   0.03649265 3.752613360
35  -0.07165359 3.688655851
36  -0.17557050 3.618033989
37  -0.27484798 3.541026486
38  -0.36909421 3.457937255
39  -0.45793725 3.369094212
40  -0.54102649 3.274847979
41  -0.61803399 3.175570505
42  -0.68865585 3.071653590
43  -0.75261336 2.963507348
44  -0.80965410 2.851558583
45  -0.85955297 2.736249105
46  -0.90211303 2.618033989
47  -0.93716632 2.497379774
48  -0.96457450 2.374762629
49  -0.98422940 2.250666467
50  -0.99605346 2.125581039
51  -1.00000000 2.000000000
52  -0.99605346 1.874418961
53  -0.98422940 1.749333533
54  -0.96457450 1.625237371
55  -0.93716632 1.502620226
56  -0.90211303 1.381966011
57  -0.85955297 1.263750895
58  -0.80965410 1.148441417
59  -0.75261336 1.036492652
60  -0.68865585 0.928346410
61  -0.61803399 0.824429495
62  -0.54102649 0.725152021
63  -0.45793725 0.630905788
64  -0.36909421 0.542062745
65  -0.27484798 0.458973514
66  -0.17557050 0.381966011
67  -0.07165359 0.311344149
68   0.03649265 0.247386640
69   0.14844142 0.190345895
70   0.26375089 0.140447028
71   0.38196601 0.097886967
72   0.50262023 0.062833678
73   0.62523737 0.035425499
74   0.74933353 0.015770597
75   0.87441896 0.003946543
76   1.00000000 0.000000000
77   1.12558104 0.003946543
78   1.25066647 0.015770597
79   1.37476263 0.035425499
80   1.49737977 0.062833678
81   1.61803399 0.097886967
82   1.73624911 0.140447028
83   1.85155858 0.190345895
84   1.96350735 0.247386640
85   2.07165359 0.311344149
86   2.17557050 0.381966011
87   2.27484798 0.458973514
88   2.36909421 0.542062745
89   2.45793725 0.630905788
90   2.54102649 0.725152021
91   2.61803399 0.824429495
92   2.68865585 0.928346410
93   2.75261336 1.036492652
94   2.80965410 1.148441417
95   2.85955297 1.263750895
96   2.90211303 1.381966011
97   2.93716632 1.502620226
98   2.96457450 1.625237371
99   2.98422940 1.749333533
100  2.99605346 1.874418961
101  3.00000000 2.000000000
```
]

---
count: false

```r
create_circle <- function(x0, y0, r = 1, n = 100){

angels <- seq(

from = 0,
    to = 2*pi,
    length.out = n + 1

)

data.frame(
    x = cos(angels) * r + x0,
    y = sin(angels) * r + y0
  )

}

create_circle(x0 = 1, y0 = 2, r = 2) %>%
* ggplot()
```
]
 
.panel2-circle-auto[
<img src="extending_ggplot2_files/figure-html/circle_auto_03_output-1.png" width="576" />
]

---
count: false

```r
create_circle <- function(x0, y0, r = 1, n = 100){

angels <- seq(

from = 0,
    to = 2*pi,
    length.out = n + 1

)

data.frame(
    x = cos(angels) * r + x0,
    y = sin(angels) * r + y0
  )

}

create_circle(x0 = 1, y0 = 2, r = 2) %>%
  ggplot() +
* aes(x = x, y = y)
```
]
 
.panel2-circle-auto[
<img src="extending_ggplot2_files/figure-html/circle_auto_04_output-1.png" width="576" />
]

---
count: false

```r
create_circle <- function(x0, y0, r = 1, n = 100){

angels <- seq(

from = 0,
    to = 2*pi,
    length.out = n + 1

)

data.frame(
    x = cos(angels) * r + x0,
    y = sin(angels) * r + y0
  )

}

create_circle(x0 = 1, y0 = 2, r = 2) %>%
  ggplot() +
  aes(x = x, y = y) +
* geom_point()
```
]
 
.panel2-circle-auto[
<img src="extending_ggplot2_files/figure-html/circle_auto_05_output-1.png" width="576" />
]

---
count: false

```r
create_circle <- function(x0, y0, r = 1, n = 100){

angels <- seq(

from = 0,
    to = 2*pi,
    length.out = n + 1

)

data.frame(
    x = cos(angels) * r + x0,
    y = sin(angels) * r + y0
  )

}

create_circle(x0 = 1, y0 = 2, r = 2) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
* geom_point(data = data_frame(x = 1, y = 2))
```
]
 
.panel2-circle-auto[
<img src="extending_ggplot2_files/figure-html/circle_auto_06_output-1.png" width="576" />
]

---

```r
StatCircle <- ggproto("StatCircle", Stat, 
  setup_params = function(data, params) {
    if (is.null(params$r)) {
      params$r <- 1
    } else if (params$r == 0) {
      rlang::abort("Circles cannot be defined with a radius of 0")
    }
    if (is.null(params$n)) {
      params$n <- 50
    } else if (params$n <= 0) {
      rlang::abort("Circles must be defined with `n` greater than 0")
    }
    params
  },
  setup_data = function(data, params) {
    if (anyDuplicated(data$group)) {
      data$group <- paste(data$group, seq_len(nrow(data)), sep = "-")
    }
    data
  },
  compute_panel = function(data, scales, r = 1, n = 50) {
    
    cols_to_keep <- setdiff(names(data), c("x0", "y0"))
    circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], r, n)
      cbind(circles_path, unclass(data[i, cols_to_keep]))
      
    })
    do.call(rbind, circles)
  },
  required_aes = c("x0", "y0")
)
```

---

```r
*tibble(x0 = 1:2,
*      y0 = c(1,8),
*      r = 1:2)
```
]
 
.panel2-circle_unpack-auto[

```
# A tibble: 2 x 3
     x0    y0     r
  <int> <dbl> <int>
1     1     1     1
2     2     8     2
```
]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
* mutate(group = row_number())
```
]
 
.panel2-circle_unpack-auto[

```
# A tibble: 2 x 4
     x0    y0     r group
  <int> <dbl> <int> <int>
1     1     1     1     1
2     2     8     2     2
```
]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
*data
```
]
 
.panel2-circle_unpack-auto[

]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

*r = .25
```
]
 
.panel2-circle_unpack-auto[

]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
*n = 10
```
]
 
.panel2-circle_unpack-auto[

]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

*  cols_to_keep <- setdiff(names(data), c("x0", "y0"))
```
]
 
.panel2-circle_unpack-auto[

]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

cols_to_keep <- setdiff(names(data), c("x0", "y0"))

*   circles <- lapply(seq_len(nrow(data)), function(i) {
*     circles_path <- create_circle(data$x0[i], data$y0[i], data$r[i], n)
*     cbind(circles_path, unclass(data[i, cols_to_keep]))
*   })
```
]
 
.panel2-circle_unpack-auto[

]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

cols_to_keep <- setdiff(names(data), c("x0", "y0"))

circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], data$r[i], n)
      cbind(circles_path, unclass(data[i, cols_to_keep]))
    })

*do.call(rbind, circles)
```
]
 
.panel2-circle_unpack-auto[

```
          x          y r group
1  2.000000 1.00000000 1     1
2  1.809017 1.58778525 1     1
3  1.309017 1.95105652 1     1
4  0.690983 1.95105652 1     1
5  0.190983 1.58778525 1     1
6  0.000000 1.00000000 1     1
7  0.190983 0.41221475 1     1
8  0.690983 0.04894348 1     1
9  1.309017 0.04894348 1     1
10 1.809017 0.41221475 1     1
11 2.000000 1.00000000 1     1
12 4.000000 8.00000000 2     2
13 3.618034 9.17557050 2     2
14 2.618034 9.90211303 2     2
15 1.381966 9.90211303 2     2
16 0.381966 9.17557050 2     2
17 0.000000 8.00000000 2     2
18 0.381966 6.82442950 2     2
19 1.381966 6.09788697 2     2
20 2.618034 6.09788697 2     2
21 3.618034 6.82442950 2     2
22 4.000000 8.00000000 2     2
```
]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

cols_to_keep <- setdiff(names(data), c("x0", "y0"))

circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], data$r[i], n)
      cbind(circles_path, unclass(data[i, cols_to_keep]))
    })

do.call(rbind, circles) %>%
* ggplot()
```
]
 
.panel2-circle_unpack-auto[
<img src="extending_ggplot2_files/figure-html/circle_unpack_auto_09_output-1.png" width="576" />
]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

cols_to_keep <- setdiff(names(data), c("x0", "y0"))

circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], data$r[i], n)
      cbind(circles_path, unclass(data[i, cols_to_keep]))
    })

do.call(rbind, circles) %>%
  ggplot() +
* aes(x = x, y = y, col = group)
```
]
 
.panel2-circle_unpack-auto[
<img src="extending_ggplot2_files/figure-html/circle_unpack_auto_10_output-1.png" width="576" />
]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

cols_to_keep <- setdiff(names(data), c("x0", "y0"))

circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], data$r[i], n)
      cbind(circles_path, unclass(data[i, cols_to_keep]))
    })

do.call(rbind, circles) %>%
  ggplot() +
  aes(x = x, y = y, col = group) +
* geom_point()
```
]
 
.panel2-circle_unpack-auto[
<img src="extending_ggplot2_files/figure-html/circle_unpack_auto_11_output-1.png" width="576" />
]

---
count: false

```r
tibble(x0 = 1:2,
       y0 = c(1,8),
       r = 1:2) %>%
  mutate(group = row_number()) ->
data

r = .25
n = 10

cols_to_keep <- setdiff(names(data), c("x0", "y0"))

circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], data$r[i], n)
      cbind(circles_path, unclass(data[i, cols_to_keep]))
    })

do.call(rbind, circles) %>%
  ggplot() +
  aes(x = x, y = y, col = group) +
  geom_point() +
* geom_point(data = data, aes(x = x0, y = y0))
```
]
 
.panel2-circle_unpack-auto[
<img src="extending_ggplot2_files/figure-html/circle_unpack_auto_12_output-1.png" width="576" />
]

---

```r
geom_circle <- function(mapping = NULL, data = NULL, stat = "circle", 
                        position = "identity", ..., r = 1,  
                        n = 50, arrow = NULL, lineend = "butt", linejoin = "round", 
                        na.rm = FALSE, show.legend = NA, inherit.aes = TRUE) {
  layer(
    data = data, 
    mapping = mapping, 
    stat = stat, 
    geom = GeomPath, 
    position = position, 
    show.legend = show.legend, 
    inherit.aes = inherit.aes, 
    params = list(
      r = r, 
      n = n, 
      arrow = arrow, 
      lineend = lineend, 
      linejoin = linejoin, 
      na.rm = na.rm, 
      ...
    )
  )
}
```

---

```r
*set.seed(1244)
```
]
 
.panel2-use_circle-auto[

]

---
count: false

```r
set.seed(1244)
*tibble(
* x = runif(5, max = 10),
* y = runif(5, max = 10),
* r = runif(5, max = 10),
* class = 1:5
*) 
```
]
 
.panel2-use_circle-auto[

```
# A tibble: 5 x 4
      x     y     r class
  <dbl> <dbl> <dbl> <int>
1 2.56   7.65 3.81      1
2 0.779  5.64 3.58      2
3 1.25   1.51 0.121     3
4 5.05   7.52 5.42      4
5 4.06   2.79 3.32      5
```
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
* ggplot()
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_03_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
* aes(x = x, y = y)
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_04_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
* geom_point()
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_05_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
* aes(x0 = x, y0 = y)
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_06_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(x0 = x, y0 = y) +
* geom_circle(n = 6)
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_07_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(x0 = x, y0 = y) +
  geom_circle(n = 6) +
* geom_circle(n = 13)
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_08_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(x0 = x, y0 = y) +
  geom_circle(n = 6) +
  geom_circle(n = 13) +
* geom_circle(r = 2)
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_09_output-1.png" width="576" />
]

---
count: false

```r
set.seed(1244)
tibble(
  x = runif(5, max = 10),
  y = runif(5, max = 10),
  r = runif(5, max = 10),
  class = 1:5
) %>%
  ggplot() +
  aes(x = x, y = y) +
  geom_point() +
  aes(x0 = x, y0 = y) +
  geom_circle(n = 6) +
  geom_circle(n = 13) +
  geom_circle(r = 2) +
* geom_circle()
```
]
 
.panel2-use_circle-auto[
<img src="extending_ggplot2_files/figure-html/use_circle_auto_10_output-1.png" width="576" />
]

---

## c. circlemean (a collective geom)

---

### Now me... I will try to do geom_mean_circle.  This is collective geom.  Take the mean of x0 and y0 and r, then draw a circle around the mean, and r reflective of that.

---

### collective geoms

Thus far we've looked at creating individual geoms -- a mark/geom is associated with each row in the data.  But what about a geom that summarizes.  i.e. creates a mark/geom which reflects all of the rows of data or groups within the data. This is the case of x-mean (my target) and several of the other geoms that I want to create.

I think I'll try to get it done in the wrong way first - having a vertical line for each and every row at the mean.  And then come back to this.

---

```r
StatCirclemean <- ggproto("StatCirclemean", Stat, 
  setup_params = function(data, params) {
    if (is.null(params$r)) {
      params$r <- 1
    } else if (params$r == 0) {
      rlang::abort("Circles cannot be defined with a radius of 0")
    }
    if (is.null(params$n)) {
      params$n <- 50
    } else if (params$n <= 0) {
      rlang::abort("Circles must be defined with `n` greater than 0")
    }
    params
  },
  setup_data = function(data, params) {
    if (anyDuplicated(data$group)) {
      data$group <- paste(data$group, seq_len(nrow(data)), sep = "-")
    }
    data
  },
  compute_panel = function(data, scales, r = 1, n = 50) {
   data %>% 
     summarise(x0 = mean(x0),
               y0 = mean(y0),
               r = mean(r)) %>% 
     mutate(group = 1) ->
    data
    cols_to_keep <- setdiff(names(data), c("x0", "y0"))
    circles <- lapply(seq_len(nrow(data)), function(i) {
      circles_path <- create_circle(data$x0[i], data$y0[i], r, n)
      
      cbind(circles_path, unclass(data[i, cols_to_keep]))
      
    })
    do.call(rbind, circles)
  },
  required_aes = c("x0", "y0")
)
```

---

```r
*tibble(x0 = 1:2,
*      y0 = c(1,8),
*      r = 1:2)
```
]
 
.panel2-circle1_unpack-auto[

```
# A tibble: 2 x 3
     x0    y0     r
  <int> <dbl> <int>
1     1     1     1
2     2     8     2
```
]