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:
  • ==, !=
  • <, >
  • <=, >=
  • %in%

10 > 5
"aang" == "aang"
3 != 3
"dog" %in% c("cat", "dog", "rabbit")

• Combine:
  • and, &
  • or, |

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

• Vectors of values compared to a single value return one logical per value

c(1, 1, 2, 3, 1) == 1

• Checks each value to see if equal to 1
• This is what subsetting approaches use to subset
• They keep the values where the condition is TRUE

site = c('a', 'b', 'c', 'd')
state = c('FL', 'FL', 'GA', 'AL')
state == 'FL'
site[state == 'FL']
site[c(TRUE, TRUE, FALSE, FALSE)]

• Used in dplyr::filter() and other methods for subsetting data

Do Tasks 1-4 in Choice Operators.

if statements

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

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

• Example

x = 6
if (x > 5){
  x = x^2
}
x

• x > 5 is TRUE, so the code in the if runs
• x is now 6^2 or 36
• Change x to 4

x = 4
if (x > 5){
  x = x^2
}
x

• x > 5 is FALSE, so the code in the if doesn’t run
• x is still 4

• This is not a function, so everything that happens in the if statement influences the global environment

• Different mass calculations for different vegetation types

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

Do Task 1 in Basic If Statements.

• Often want to chose one of several options
• Can add more conditions and associated actions with else if

veg_type <- "grass"
volume <- 16.08
if (veg_type == "tree") {
  mass <- 2.65 * volume^0.9
} else if (veg_type == "grass") {
  mass <- 0.65 * volume^1.2
}
mass

• Checks the first condition
• If TRUE runs that condition’s code and skips the rest

• If not it checks the next one until it runs out of conditions

• Can specify what to do if none of the conditions is TRUE using else on its own

veg_type <- "shrub"
volume <- 16.08
if (veg_type == "tree") {
  mass <- 2.65 * volume^0.9
} else if (veg_type == "grass") {
  mass <- 0.65 * volume^1.2
} else {
  mass <- NA
}
mass

Do Tasks 2-3 in Basic If Statements.

Multiple ifs vs else if

• Multiple ifs check each conditional separately
• Executes code of all conditions that are TRUE

x <- 5
if (x > 2){
  x * 2
}
if (x > 4){
  x * 4
}

• else if checks each condition sequentially
• Executes code for the first condition that is TRUE

x <- 5
if (x > 2){
  x * 2
} else if (x > 4){
  x * 4
}

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 Size Estimates by Name.

Automatically extracting functions

• Can pull code out into functions
• Highlight the code
• Code -> Extract Function
• Provide a name for the function

Nested conditionals

• Sometimes decisions are more complicated
• Can “nest” conditionals inside of one another

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

Assign the rest of the exercises.