R_functions_and_loops.Rmd

---
title: 'R: Loops and Functions'
author: "Murray Cadzow"
date: "9 November 2015"
output: html_document
---

https://github.com/murraycadzow/R_tutorials/

# Lesson 7:

This lesson will cover the following:

- Functions
- Control Statements
- Loops

## Functions

As you have been using R you will have noticed that many tasks have a particular function already available for you to use, such as mean or sd. In this section we are going to learn how to make our own functions


We can define our own functions using the *function()* function

Inside the parenthesis we define what variables are going to be passed to our function and curly braces contain the body of the function. If we want to return a value from our function we end it with  *return()*

We can assign this new function to a variable

To call our new function we now use the variable name and pass any required arguments

```{r, eval = TRUE, echo = TRUE}
double <- function( num ){
  num <- num * 2
  return( num )
}

double(2)
```
We can also have multiple arguments

```{r, eval = TRUE, echo = TRUE}
calcBMI <- function(height, weight){
  return( weight / height ^2)
}



calcBMI( height = 1.68, weight = 73)

h = c(1.68, 1.74, 1.55)
w = c(73, 85, 65)

calcBMI(height = h, weight = w)
```

**NB:** Variables declared only inside a function don't exist outside of the function

## Control Statements

Control statements allow us to use conditions to execute particular pieces of code based on the input

We use the statements **if** or **else** to control what happens, else is only used after an if


```{r}
bmi <- 21

if(bmi > 30){
  print("obese")
} else if (bmi > 25){
  print("overweight")
} else if (bmi > 20){
  print("healthy")
} else {
  print("underweight")
}


```

There is also the *ifelse()* function that can be used

it takes the format ifelse( condition, if true, if false)

## Loops

Loops enable us to do the same operation many times until the termination condition is met

The most common loop is the **for** loop

Each iteration of the loop the continuation condition is evaluated 

```{r, eval = TRUE, echo = TRUE}
for( num in 1:5){
  print( num )
}

```


### For loop using indices

```{r, echo = TRUE, eval = TRUE}
myNumbers <- c(11,12,13,14,15)

for( i in 1:length(myNumbers) ){
  print(paste("number =", myNumbers[i], "index =", i))
}

```


### While loop
```{r, echo = TRUE, eval = TRUE}
i = 5
while( i > 0){
  print(i)
  i <- i - 1
}
```

NB: **always make sure your condition will eventually be FALSE before running**

### Things can get quite fancy

```{r, echo = TRUE, eval = TRUE, message = FALSE}
mydata = read.delim(file = "Tanya_Data.txt", header = TRUE, sep = "\t", stringsAsFactors=FALSE)

ethgroup <- levels(as.factor(mydata$ETHCLASS))
ethgroup
model_coef <-data.frame()
model_confint <- list()

for( eth in ethgroup){
  
  model = glm(formula = GOUTAFFSTAT ~ BMI + AGE + SNP, data = mydata, subset = ETHCLASS == eth)

  #insert coefficients into dataframe
  model_coef <- rbind(model_coef, exp(coef(model) ))
  #make row name be eth for this iteration
  rownames(model_coef)[which(ethgroup == eth)] <- eth
  #make names of the coefficients be names of columns
  names(model_coef) <- names(exp(coef(model)))
  
  #put confidence intervals into a list labelled by eth
  model_confint[[eth]] <- exp(confint(model) ) 
}

model_coef
model_confint
```


### Look for where you repeat yourself and ask: 

## **Can I replace this with a function/loop?**