Spatial Ecology Lab 8: Control Structures

Transcription

1 Spatial Ecology Lab 8: Control Structures Damian Maddalena Spring Introduction This week in lab, we will look at methods to direct the flow of operations in your code. There are several methods available in R, some of which we have looked at. We will review those to as a means of being thorough. 2 Packages Used in this Lab You will not need any packages other than the base R for this week. 3 Workspace Setup You do not need to set up a workspace this week. All output will be printed to the screen. 4 Data You will not be downloading any data this this week. We will be generating random data for the exercises in this lab. 5 Control Structures In programming, there are several ways to control the flow of code you are writing, to make decisions about how things progress (or don t progress) based on conditions that are evaluated as the code 1

2 executes. So far, we have looked at for loops, which enable you to write code that iterates a repeated block over a set number of elements. 5.1 Logical Operators and Evaluating TRUE/FALSE if statements, and their related components, evalute TRUE/FALSE. Alone just typing the syntax without the if/else business will return a condition, TRUE or FALSE. Logical operators are used to construct this code. Table 1: Logical Operators in R Operator Description < less than <= less than or equal to > greater than >= greater than or equal to == exactly equal to!= not equal to x y x OR y x & y x AND y For example: #create a string variable s <- "What time is are we eating?" #check the class class(s) #now test to see if it is a string (yes, you already now it is) class(s) == "character" #now test to see if it is a number (yes, you already know it is not) class(v) == "numeric" #create a numeric variable n <- 43 #print its class class(n) #now test to see if that is a numeric variable class(sv) == "character" #to belabor the point, let s test to see if either is egg salad class(s) == "egg salad" class(n) == "egg salad" #you can also use R s built in "is" functions to test variable class is.numeric(n) is.character(n) #try the! to say NOT (the condition is NOT TRUE)!is.character(n) 2

3 #define a vector as Nanna s meatball recipe v <- c("beef","pork","parsley","cheese","breadcrumbs","eggs","salt","pepper") #test is is.vector(v) The and & operators allow you to evaluate more than one condition at the same time. For example: #define some variables #numbers n1 <- 42 n2 < #strings s1 <- "meatballs" s2 <- "braciole" #vectors nv <- c(1,2,3) sv <- c("a","b","c") #data frame df <- data.frame(nv,sv) #set name of columns on data frame names(df) <- c("numbers","letters") #test to see if sv is a vector is.vector(sv) #test to see if nv is a character is.character(sv) #test to see if sv is a number is.numeric(sv) #test to see if it is a vector OR a number is.vector(sv) is.numeric(sv) #test to see if it is a vector AND a character is.vector(sv) & is.character(sv) #test if df is a data frame is.data.frame(df) We can also test the numeric properties of variables. #is our variable less than 3? n1 < 3 #is it NOT less than three?! n1 < 3 #does adding n1 and n2 together sum to more than 30? n1 + n2 > 30 #is our first string more than 5 characters long? nchar(s1) > 5 #test to see if the number of records in our data frame is less than 10 nrow(df) < 10 #etc... You see now that you can evaluate the properties (or conditions) of variables. We will use this to construct if/else statements as well as while loops. 3

4 5.2 if/then Statements Let s look at the basic syntax: if(...) {... else {... Let s look at a simple example using some of the variables we defined above: #evalute if n1 is greater than 5, and if so, print "YES!" if (n1 > 5){print("YES!") #here is the same command on multiple lines for clarity if (n1 > 5){ print("yes!") A very simple and powerful concept. Let s look at how we can use it to make decisions about what to do with variables. In the next example, let s build a random vector of numbers between 1 and 100 with a length of 20. We will then iterate through those numbers evaluating wheter they are even or odd. We are using the R command %% here. This operator performs modulus calculations. x %% 2 will help us determine if we have an even number #generate a random set of numbers between 0 and 100 with a length of 20. Round all of them to zero decimal places. v <- round(runif(20, min=0, max=100),0) #check v print(v) #iterate through the list for (i in v){ print(paste("evaluting",i,"...", sep=" ")) #check if a number is even using the modular operator %% if (i %% 2 == 0){ s <- paste(i,"is an even number.",sep=" ") else{ s <- paste(i,"is an odd number.", sep=" ") print(s) 5.3 while Loops We have already looked at for loops. for loops allow you to iterate over a set. For example, we iterated over all elements of a string vector. Sometimes, one needs to repeat a process or calculation until some condition has been met. For example, until a certain time has passed or a certain value is calculated. To do that you use while loops. 4

5 Here is the basic structure. while (cond) {...do some stuff... The biggest issue with while loops is updating the condition (or evaluating something that is updating, like time) so that the loop eventually ends. If the condition is not updated, it will never be TRUE/FALSE and your loop will go on into infinity. Let s look at a a simple example of a while loop. threshold <- 100 n = 0 s = 0 while (s <= threshold) { n = n + 1 print(n) s = s + n print(s) print(c(n, s)) Notice we update the variables n and s within the loop. The while loop checks the condition s <= threshold at each pass and stops when it is TRUE. 5.4 Functions Many programming languages provide for ways to develop your own functions. In the case of R, this is the way the libraries you installed are developed. Libraries are packaged functions that the developer shares with the R community. Let s look at the basic structure: myfunction <- function(arg1, arg2,... ){...do some stuff... return(object) In the code above, arg1 and arg2 (and any number of arguments) are the parameters that go into the code. These are the bits you put in the () when you call the function....do some stuff... could be any R code that you write. A block of code that can be used over and over, inside or outside the current code you are writing. (We will only treat functions defined in the code they will be used in for this lab.) The return() element is what the function will return as an object. It s the output of the operation. It s the value you would set your variable to when you. Let s look at a simple example. #define a function that evaluates the number of characters in a string and outputs a sentence describing it. checklength <- function(s){ characters <- nchar(s) ostr <- paste("this string has",characters,"characters in it.",sep=" ") return(ostr) 5

6 #now call the function and set its output as the value of a new variable b <- checklength("brown off the meatballs in the skillet and then add them to the sauce.") #now print the output print(b) In the above example, you defined the function, called the function, the printed the output. 5.5 Accessing Vector Information Using the Index Numbers The final thing we will look at in this lab is using index values to access items from a vector while looping. You can do this any time, and with most objects, but we are looking at vectors here specifically. Remember, items in a list are indexed by their position in the vector. It starts at one with first item and increases by one as you move through the list. Let s look: #define your list v <- c("tomatoes","garlic","salt","pepper") #print the list print(v) #print the first item print(v[1]) #print the thrid item print(v[3]) Easy, now let s look again at a while loop and see how we can use the index number and a counter to access the items in a list as we iterate through a loop. #iintiate a list v <- round(runif(20, min=0, max=100),0) #initiate an index (or counter) variable i = 1 #now roll through a while loop that evaluates the condition of the index value as a condition while (i < 4){ #print a string print("brown the garlic cloves in the oil, then remove them.") #print a number from our vector using its index value print(v[i]) #update our index variable, IF WE DON T DO THIS THE WHILE LOOP WILL NEVER END i = i + 1 That s all well and good, but let s look now at an example of using an index variable in a while loop that depends on the condition of another variable by building on the example from above. threshold <- 100 v <- round(runif(75, min=0, max=100),0) n <- 0 s <- 0 6

7 i <- 1 while (s <= threshold){ n = n + 1 print(n) s = s + n print(s) print(v[i]) i <- i + 1 print(c(n, s, i)) 6 Putting it all Together You are to write a function that generates a list of random integers between 2 and 100, and a length of x (hint: the length of the list should be your input parameters for your function). The function should then iterate through the list you have generated, and for each value (v), it should calculate the area (a) of a square whose side is of length v. It should then check to see if the area is an even number, and if it is, it should add it to a running sum of the total areas calculated, stopping when the sum of a reaches 200. As your code runs, you are to print updates to the screen. Please include the following where appropriate in order to keep the user informed of the code s progress: 1. The creation and contents of your random number list 2. The initial value of your area sum variable 3. The value of each random integer as you work through the list 4. The value of your area sum as you work though each integer in the list 5. Whether or not an area value was added to the area sum 6. The final value of your area total 7. A printed separator (such as ) between each value in the vector list as it is evaluated. Text/submit your code with x <- 20 for the length of the list. Call your function at the bottom of your script. ######################### #file name: # #author: # #description: # #notes: # ########################## 7

8 Your file should be executable at the command prompt using the source command. (See R help for details.) 7 Submission Submit your.r script file via Blackboard. Only submit the.r file. 8