Conditionals, errors, tests, debugging Steve Bagley - - PowerPoint PPT Presentation

Conditionals, errors, tests, debugging

Steve Bagley

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Conditional execution

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Writing a function to compute the sign of a number

• Let’s write a function to compute the sign of a number:
• Return -1 if the number is < 0.
• Return 0 if the number is 0.
• Return 1 if the number is > 0.

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if, simple version

• if is a basic control flow construct in R. It is not the same as ifelse.
• Simple version: if(x == 0) 0
• The simple version takes a test, x == 0, and an expression, 0.
• If the test is true, the value of the expression is returned.
• If the test is false, NULL is returned.

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compute_sign version 1

compute_sign1 <- function(x) { if(x < 0) -1 }

• What is the result of compute_sign1(-2)?
• What is the result of compute_sign1(2)?

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compute_sign version 2

compute_sign2 <- function(x) { if(x < 0) -1 if(x == 0) 0 }

• What is the result of compute_sign2(-2)?

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if, complex version

if(x < 0) {

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} else { 1 }

• If x < 0, this returns -1.
• Else (because x >= 0), this returns 1.
• if ... then ... else is a very common programming idiom.
• Important: put the } and else on the same line.

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Braces { }

{ print(1) x <- 2 x + 1 } [1] 1 [1] 3

• Braces { } can contain one or more R expressions, one per line.
• The value of the last expression will be returned, unless you have done

something that alters control flow.

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compute_sign version 3

compute_sign3 <- function(x) { if(x < 0) {

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} else { 0 } }

• What is the result of compute_sign3(-2)?
• What is the result of compute_sign3(2)?

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compute_sign version 4

compute_sign4 <- function(x) { if(x < 0) {

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} else { if(x == 0) { } else { 1 } } } compute_sign4(-2) [1] -1 compute_sign4(0) [1] 0 compute_sign4(2) [1] 1

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What about values that are not numbers?

compute_sign4("abc") [1] 1

• If the user supplies an argument that is not a number, we’d like to get an error,

not an incorrect result.

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Errors, warnings

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stop

• The stop function raises an error. This interrupts the regular flow of
• computation. It takes an argument, the error message that you want printed.

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compute_sign version 5

compute_sign5 <- function(x) { if(!is.numeric(x)) { stop("Hey, x is not a number.") } if(x < 0) {

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} else { if(x == 0) { } else { 1 } } } compute_sign5(-2) [1] -1 compute_sign5("abc") Error in compute_sign5("abc"): Hey, x is not a number.

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warning

• warning prints a message, but the computation continues without interruption.

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compute_sign version 6

compute_sign6 <- function(x) { if(!is.numeric(x)) { warning("Hey, x is not a number.") } if(x < 0) {

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} else { if(x == 0) { } else { 1 } } } compute_sign6(-2) [1] -1 compute_sign6("abc") Warning in compute_sign6("abc"): Hey, x is not a number. [1] 1

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Assertions

• Assertions are conditions that you expect to be true at a certain point in the code.
• You can put if statements with stop to make sure that a condition is true, and

cause an error if it is not true.

• There are several R packages for writing assertions that make this kind of

checking slightly easier.

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package assertthat

library(assertthat) x <- 2 assert_that(x > 0) [1] TRUE assert_that(x < 0) Error: x not less than 0

• assert_that takes an expression, a test.
• If it is TRUE then the function does nothing.
• If it is FALSE then the function causes an error with a readable error message.
• You can put assertions throughout your functions and scripts.

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compute_sign version 7

compute_sign7 <- function(x) { assert_that(is.numeric(x)) if(x < 0) {

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} else { if(x == 0) { } else { 1 } } } compute_sign7(-2) [1] -1 compute_sign7("abc") Error: x is not a numeric or integer vector

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Debugging

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Programs have bugs

• All long, and many short, programs have bugs in them.
• Nearly always an error is detected at some point after the initial mistake.

Working backwards from the error message to the ultimate site of the error is an acquired skill.

• Defensive programming uses assertions to make sure that data have the proper

structure and values. (Eg, weight should be > 0.)

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Using print for debugging in R

• The simplest way to debug is to put print statements in your code, showing

intermediate values.

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Using print in a pipe

iris %>% as_tibble() %>% print() %>% filter(Petal.Length > 1.5) %>% print()

• print does the printing, but also returns its argument as the result.

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Super fancy way using View

library(magrittr) iris %>% ## note use of Tee pipe: %T>% as_tibble() %T>% View() %>% filter(Petal.Length > 1.5) %T>% View()

• View does not return its argument as the result, so you need to work around that

using the %T>% operator from the package magrittr. This does the function on the right, but then returns the value on the left.

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Debugging in RStudio

• RStudio has some powerful and easy to use debugging features.
• Download https://somgen223.stanford.edu/files/debug_demo.r
• Then open that file in the script window.
• (live demo in RStudio)

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How to set a breakpoint

• Click in the left margin at the line where you want to pause execution.
• Click again in the same place to remove the breakpoint.

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Commands inside a breakpoint

Command Action c continue running code Q quit running variable name print value of variable

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Reading

• Read: 19 Functions | R for Data Science (section 19.4 conditional execution)
• Read: 19 Functions | R for Data Science (section 19.5.2 checking values)
• Optional/advanced: Chapter 8 Testing and Error Handling | The Tidynomicon

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