INSTRUCTOR NOTE: Code examples should generally build up by modifying the existing code example rather than by retyping the full example.

Conditionals

• Usage:
  • Generate "logical":
    • TRUE if the condition is satisfied
    • FALSE if the condition is not satisfied
• Operators:
  • ==, !=
  • <, >
  • <=, >=

10 > 5
"aang" == "aang"
3 != 3

• Combine:
  • and, &
  • or, |

5 > 2 & 6 >=10
5 > 2 | 6 >=10

• Appearances:
  • subset()
  • dplyr::filter()
  • if(), else, while()

Do Choice Operators.

Discuss floating point with students.

• Did you notice anything weird while you were doing the exercise?
• Take a closer look at item 4.

Floating point

> x <- 1.3
> y <- 2.8
>  x * 2 + 0.2 == y
[1] FALSE
> 1.3 * 2 + 0.2
[1] 2.8

• What’s going on?
  • Unexpected result from computer arithmetic
  • Numbers combine to include very small trailing digit
    • See this more easily in Python

>>> 1.3 * 2 + 0.2 == 2.8
False
>>> 1.3 * 2 + 0.2
2.8000000000000003

• Avoid floating point problems.
  • round(x * 2 + 0.2, 1) == y
  • all.equal(x * 2 + 0.2, y)

if statements

• Conditional statements generate "logical" to filter inputs.
• if statements use conditional statements to control flow of program processing.

• if (the conditional statement is TRUE ) { do something }

• Different mass calculations for different vegetation types

veg_type <- "tree"
volume <- 16.08
if (veg_type == "tree") {
  mass <- 2.65 * volume^0.9
  }
print(mass)

veg_type <- "shrub"

• } else { do something else }

if (veg_type == "tree") {
  mass <- 2.65 * volume^0.9
} else {
  print("I don't know how to convert volume to mass for that vegetation type")
  mass <- NA
}
print(mass)

• } else if ( a different conditional statement is TRUE ) {
  • do something else

if (veg_type == "tree") {
  mass <- 2.65 * volume^0.9
} else if (veg_type == "grass") {
  mass <- 0.65 * volume^1.2
} else {
  print("I don't know how to convert volume to mass for that vegetation type")
  mass <- NA
}
print(mass)

veg_type = "liana"

Do Simple If Statement.

Convert to function

est_mass <- function(volume, veg_type){
  if (veg_type == "tree") {
	mass <- 2.65 * volume^0.9
  } else if (veg_type == "grass") {
	mass <- 0.65 * volume^1.2
  } else {
	print("I don't know how to convert volume to mass for that vegetation type")
	mass <- NA
  }
  return(mass)
}

est_mass(1.6, "tree")
est_mass(1.6, "grass")
est_mass(1.6, "shrub")

Do Complete the Code.

• Can use more complex conditions

est_mass <- function(volume, veg_type, age){
  if (veg_type == "tree") {
    if (age < 5) {
	  mass <- 1.6 * volume^0.8
	} else {
	  mass <- 2.65 * volume^0.9
	}
  } else if (veg_type == "grass" | veg_type == "shrub") {
	mass <- 0.65 * volume^1.2
  } else {
	print("I don't know how to convert volume to mass for that vegetation type")
	mass <- NA
  }
  return(mass)
}

est_mass(1.6, "tree", age = 2)
est_mass(1.6, "shrub", age = 5)

• First checks if the vegetation type is “tree”
• If it is checks to see if it is < 5 years old
• If so does one calculation, if not does another
• But nesting can be difficult to follow so try to minimize it

Do Choices with Functions.