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Updated week2 slides
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@robjhyndman
robjhyndman committed Feb 29, 2024
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Expand Up @@ -29,79 +29,66 @@ source(here::here("course_info.R"))
\vspace*{0.4cm}
\tableofcontents

# Control flow
# Subsetting

## Quiz
## Exercises

1. What is the difference between `if` and `ifelse()`?
1. What is the result of subsetting a vector with positive integers, negative integers, a logical vector, or a character vector?
2. What's the difference between `[`, `[[`, and `$` when applied to a list?
3. When should you use `drop = FALSE`?

2. In the following code, what will the value of `y` be if `x` is `TRUE`? What if `x` is `FALSE`? What if `x` is `NA`?
## Exercises
\fontsize{13}{14}\sf

```{r, eval = FALSE}
y <- if (x) 3
```
4. Fix each of the following common data frame subsetting errors:

3. What does `switch("x", x = , y = 2, z = 3)` return?
```{r, eval = FALSE}
mtcars[mtcars$cyl = 4, ]
mtcars[-1:4, ]
mtcars[mtcars$cyl <= 5]
mtcars[mtcars$cyl == 4 | 6, ]
```

## Quiz
\fontsize{13}{14}\sf
5. Extract the residual degrees of freedom from `mod`

```{r}
#| eval: false
mod <- lm(mpg ~ wt, data = mtcars)
```

6. Extract the R squared from the model summary (`summary(mod)`)

## Exercises

7. How would you randomly permute the columns of a data frame?
8. Can you simultaneously permute the rows and columns in one step?
9. How would you select a random sample of m rows from a data frame? What if the sample had to be contiguous (i.e., with an initial row, a final row, and every row in between)?
10. How could you put the columns in a data frame in alphabetical order?

# Control flow
## Exercises

11. What is the difference between `if` and `ifelse()` and `dplyr::if_else()`?

4. What type of vector does each of the following calls to `ifelse()`
return?
12. What type of vector does each of the following calls to `ifelse()` return?

```{r, eval = FALSE}
ifelse(TRUE, 1, "no")
ifelse(FALSE, 1, "no")
ifelse(NA, 1, "no")
```
5. Why does the following code work?\fontsize{10}{10}\sf
## Exercises
13. Why does the following code work?\fontsize{10}{10}\sf
```{r}
x <- 1:10
if (length(x)) "not empty" else "empty"
x <- numeric()
if (length(x)) "not empty" else "empty"
```
## Don't allocate memory in a for loop
:::: {.columns}
::: {.column width="50%"}
```{r}
# Allocating memory within the loop
system.time(
{
x <- NULL
for(i in seq(1e5)) {
x <- c(x, i)
}
}
)
```

:::

::: {.column width="50%"}

```{r}
# Allocating memory before the loop
system.time(
{
x <- numeric(1e5)
for(i in seq(1e5)) {
x[i] <- i
}
}
)
```

:::
::::

# Functions
## Function fundamentals
Expand Down Expand Up @@ -143,24 +130,12 @@ args <- list(1:10, na.rm = TRUE)
do.call(mean, args)
```

## Quiz

6. Given a name, like `"mean"`, `match.fun()` lets you find a function.
Given a function, can you find its name? Why doesn't that make sense in R?

7. Which base function has the most arguments? Hint: Start by making a list of all functions in the base package.

```{r}
objs <- mget(ls("package:base", all = TRUE), inherits = TRUE)
funs <- Filter(is.function, objs)
```
## Function composition {#function-composition}
\fontsize{13}{15}\sf

```{r}
square <- function(x) x^2
deviation <- function(x) x - mean(x)
square <- function(x) { x^2 }
deviation <- function(x) { x - mean(x) }
x <- runif(100)
```

Expand Down Expand Up @@ -257,16 +232,16 @@ g04()
\fontsize{10}{10}\sf

```{r}
g07 <- function(x) x + 1
g07 <- function(x) { x + 1 }
g08 <- function() {
g07 <- function(x) x + 100
g07 <- function(x) { x + 100 }
g07(10)
}
g08()
```

```{r}
g09 <- function(x) x + 100
g09 <- function(x) { x + 100 }
g10 <- function() {
g09 <- 10
g09(g09)
Expand Down Expand Up @@ -305,7 +280,7 @@ g11()
\fontsize{10}{10}\sf

```{r}
g12 <- function() x + 1
g12 <- function() { x + 1 }
x <- 15
g12()
Expand Down Expand Up @@ -392,51 +367,9 @@ h04()

\pause\alert{Not recommended!}

## Missing arguments: `sample()`
\fontsize{9}{9}\sf

```{r}
sample
```

## A better approach
\fontsize{9}{9}\sf
## Exercises


```{r}
sample <- function(x, size = NULL, replace = FALSE, prob = NULL) {
if (is.null(size)) {
size <- length(x)
}
x[sample.int(length(x), size, replace = replace, prob = prob)]
}
```

\vspace*{1cm}
\alert{Even simpler}

```{r}
sample <- function(x, size = NULL, replace = FALSE, prob = NULL) {
size <- size %||% length(x)
x[sample.int(length(x), size, replace = replace, prob = prob)]
}
```

## Quiz

8. What does this function return? Why? Which principle does it illustrate?

```{r, results = "hide"}
f2 <- function(x = z) {
z <- 100
x
}
f2()
```
## Quiz
9. In `hist()`, the default value of `xlim` is `range(breaks)`, the default
14. In `hist()`, the default value of `xlim` is `range(breaks)`, the default
value for `breaks` is `"Sturges"`, and

```{r}
Expand All @@ -445,9 +378,9 @@ sample <- function(x, size = NULL, replace = FALSE, prob = NULL) {
Explain how `hist()` works to get a correct `xlim` value.
## Quiz
## Exercises
10. Explain why this function works. Why is it confusing?
15. Explain why this function works. Why is it confusing?
```{r}
show_time <- function(x = stop("Error!")) {
Expand Down Expand Up @@ -489,10 +422,7 @@ str(i04(a = 1, b = 2))
## `...` (dot-dot-dot)
\fontsize{13}{14}\sf

* If your function takes a function as an argument, you want some way to
pass additional arguments to that function.
* If your function is an S3 generic, you need some way to allow methods to
take arbitrary extra arguments.
* Allows you to pass arguments to a function called within your function, without having to list them all explicitly.

\pause\alert{Two downsides:}

Expand All @@ -507,9 +437,9 @@ str(i04(a = 1, b = 2))
sum(1, 2, NA, na_rm = TRUE)
```

## Quiz
## Exercises

11. Explain the following results: \fontsize{10}{10}\sf
16. Explain the following results: \fontsize{10}{10}\sf

```{r}
sum(1, 2, 3)
Expand Down Expand Up @@ -568,14 +498,14 @@ j02(15)
Most functions return visibly: calling the function in an interactive context prints the result.

```{r}
j03 <- function() 1
j03 <- function() { 1 }
j03()
```

However, you can prevent automatic printing by applying `invisible()` to the last value:

```{r}
j04 <- function() invisible(1)
j04 <- function() { invisible(1) }
j04()
```

Expand Down Expand Up @@ -719,6 +649,16 @@ You can specify arguments in three ways:
* By name, like `help(topic = mean)`.
* Using partial matching, like `help(top = mean)`.

## Exercises

17. Clarify the following list of odd function calls:

```{r, eval = FALSE}
x <- sample(replace = TRUE, 20, x = c(1:10, NA))
y <- runif(min = 0, max = 1, 20)
cor(m = "k", y = y, u = "p", x = x)
```
## Infix functions
Functions with 2 arguments, and the function name comes between the arguments:
Expand Down Expand Up @@ -771,26 +711,6 @@ When you write `modify(x, 1) <- 10`, behind the scenes R turns it into:
x <- `modify<-`(x, 1, 10)
```

## Quiz

12. Clarify the following list of odd function calls:

```{r, eval = FALSE}
x <- sample(replace = TRUE, 20, x = c(1:10, NA))
y <- runif(min = 0, max = 1, 20)
cor(m = "k", y = y, u = "p", x = x)
```
13. Write your own version of `+` that pastes its inputs together if they are character vectors but behaves as usual otherwise. In other words, make this code work:
```{r, eval = FALSE}
1 + 2
#> [1] 3
"a" + "b"
#> [1] "ab"
```
# Environments

## Environment basics
Expand Down Expand Up @@ -1025,27 +945,9 @@ f3 <- function(x) {
f3("x")
```

## Quiz

14. Does the following code throw an error when executed? Why or why not?

```{r, eval = FALSE}
f2 <- function(a, b) {
a * 10
}
f2(10, stop("This is an error!"))
```
## Quiz
15. What's the difference between these two commands?
```{r, eval = FALSE}
catch_cnd(stop("An error"))
catch_cnd(abort("An error"))
```
## Exercises

16. Explain the results of running this code:
18. Explain the results of running this code:

```{r}
withCallingHandlers(
Expand All @@ -1054,9 +956,9 @@ f3("x")
)
```
## Quiz
## Exercises
17. Predict the results of evaluating the following code
19. Predict the results of evaluating the following code
```{r, eval = FALSE}
show_condition <- function(code) {
Expand Down

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