From 5b095ed6f38bd54aa9d49403232bffa9918f82c1 Mon Sep 17 00:00:00 2001
From: sharkdp <davidpeter@web.de>
Date: Fri, 9 Oct 2020 22:54:45 +0200
Subject: Fix line endings

---
 tests/syntax-tests/highlighted/R/test.r | 292 ++++++++++++++++----------------
 1 file changed, 146 insertions(+), 146 deletions(-)

(limited to 'tests')

diff --git a/tests/syntax-tests/highlighted/R/test.r b/tests/syntax-tests/highlighted/R/test.r
index 16209b47..2196edef 100644
--- a/tests/syntax-tests/highlighted/R/test.r
+++ b/tests/syntax-tests/highlighted/R/test.r
@@ -1,170 +1,170 @@
 # take input from the user
-num = as.integer(readline(prompt="Enter a number: "))
-factorial = 1
+num = as.integer(readline(prompt="Enter a number: "))
+factorial = 1
 # check is the number is negative, positive or zero
-if(num < 0) {
-print("Sorry, factorial does not exist for negative numbers")
-} else if(num == 0) {
-print("The factorial of 0 is 1")
-} else {
-for(i in 1:num) {
+if(num < 0) {
+print("Sorry, factorial does not exist for negative numbers")
+} else if(num == 0) {
+print("The factorial of 0 is 1")
+} else {
+for(i in 1:num) {
 factorial = factorial * i
-}
-print(paste("The factorial of", num ,"is",factorial))
-}
-
-x <- 0
-if (x < 0) {
-print("Negative number")
-} else if (x > 0) {
-print("Positive number")
-} else
-print("Zero")
-
-x <- 1:5
-for (val in x) {
-if (val == 3){
-next
-}
-print(val)
-}
-
-x <- 1
-repeat {
-print(x)
-x = x+1
-if (x == 6){
-break
-}
-}
-
-`%divisible%` <- function(x,y)
-{
-if (x%%y ==0) return (TRUE)
-else          return (FALSE)
-}
-
-switch("length", "color" = "red", "shape" = "square", "length" = 5)
-[1] 5
-
-recursive.factorial <- function(x) {
-if (x == 0)    return (1)
-else           return (x * recursive.factorial(x-1))
-}
-
-pow <- function(x, y) {
+}
+print(paste("The factorial of", num ,"is",factorial))
+}
+
+x <- 0
+if (x < 0) {
+print("Negative number")
+} else if (x > 0) {
+print("Positive number")
+} else
+print("Zero")
+
+x <- 1:5
+for (val in x) {
+if (val == 3){
+next
+}
+print(val)
+}
+
+x <- 1
+repeat {
+print(x)
+x = x+1
+if (x == 6){
+break
+}
+}
+
+`%divisible%` <- function(x,y)
+{
+if (x%%y ==0) return (TRUE)
+else          return (FALSE)
+}
+
+switch("length", "color" = "red", "shape" = "square", "length" = 5)
+[1] 5
+
+recursive.factorial <- function(x) {
+if (x == 0)    return (1)
+else           return (x * recursive.factorial(x-1))
+}
+
+pow <- function(x, y) {
 # function to print x raised to the power y
 result <- x^y
-print(paste(x,"raised to the power", y, "is", result))
-}
-
-A <- read.table("x.data", sep=",",
-                col.names=c("year", "my1", "my2"))
+print(paste(x,"raised to the power", y, "is", result))
+}
+
+A <- read.table("x.data", sep=",",
+                col.names=c("year", "my1", "my2"))
 nrow(A)                                 # Count the rows in A
-
+
 summary(A$year)                        
-
+
 A$newcol <- A$my1 + A$my2               # Makes a new
 newvar <- A$my1 - A$my2                 # Makes a 
 A$my1 <- NULL                           # Removes 
-str(A)
-summary(A)
+str(A)
+summary(A)
 library(Hmisc)          
-contents(A)
-describe(A)
-
+contents(A)
+describe(A)
+
 set.seed(102)                           # This yields a good illustration.
-x <- sample(1:3, 15, replace=TRUE)
-education <- factor(x, labels=c("None", "School", "College"))
-x <- sample(1:2, 15, replace=TRUE)
-gender <- factor(x, labels=c("Male", "Female"))
-age <- runif(15, min=20,max=60)
-
-D <- data.frame(age, gender, education)
-rm(x,age,gender,education)
-print(D)
-
+x <- sample(1:3, 15, replace=TRUE)
+education <- factor(x, labels=c("None", "School", "College"))
+x <- sample(1:2, 15, replace=TRUE)
+gender <- factor(x, labels=c("Male", "Female"))
+age <- runif(15, min=20,max=60)
+
+D <- data.frame(age, gender, education)
+rm(x,age,gender,education)
+print(D)
+
 # Table about education
-table(D$education)
-
+table(D$education)
+
 # Table about education and gender --
-table(D$gender, D$education)
+table(D$gender, D$education)
 # Joint distribution of education and gender --
-table(D$gender, D$education)/nrow(D)
-
+table(D$gender, D$education)/nrow(D)
+
 # Add in the marginal distributions also
-addmargins(table(D$gender, D$education))
-addmargins(table(D$gender, D$education))/nrow(D)
-
+addmargins(table(D$gender, D$education))
+addmargins(table(D$gender, D$education))/nrow(D)
+
 # Generate a good LaTeX table out of it --
-library(xtable)
-xtable(addmargins(table(D$gender, D$education))/nrow(D),
+library(xtable)
+xtable(addmargins(table(D$gender, D$education))/nrow(D),
        digits=c(0,2,2,2,2))  
-
-by(D$age, D$gender, mean)
-by(D$age, D$gender, sd)
-by(D$age, D$gender, summary)
-
-a <- matrix(by(D$age, list(D$gender, D$education), mean), nrow=2)
-rownames(a) <- levels(D$gender)
-colnames(a) <- levels(D$education)
-print(a)
-print(xtable(a))
-
-dat <- read.csv(file = "files/dataset-2013-01.csv", header = TRUE)
-interim_object <- data.frame(rep(1:100, 10),
-                             rep(101:200, 10),
-                             rep(201:300, 10))
+
+by(D$age, D$gender, mean)
+by(D$age, D$gender, sd)
+by(D$age, D$gender, summary)
+
+a <- matrix(by(D$age, list(D$gender, D$education), mean), nrow=2)
+rownames(a) <- levels(D$gender)
+colnames(a) <- levels(D$education)
+print(a)
+print(xtable(a))
+
+dat <- read.csv(file = "files/dataset-2013-01.csv", header = TRUE)
+interim_object <- data.frame(rep(1:100, 10),
+                             rep(101:200, 10),
+                             rep(201:300, 10))
 object.size(interim_object) 
 rm("interim_object") 
 ls() 
-rm(list = ls())
-
-vector1 <- c(5,9,3)
-vector2 <- c(10,11,12,13,14,15)
-array1 <- array(c(vector1,vector2),dim = c(3,3,2))
-vector3 <- c(9,1,0)
-vector4 <- c(6,0,11,3,14,1,2,6,9)
-array2 <- array(c(vector1,vector2),dim = c(3,3,2))
-matrix1 <- array1[,,2]
-matrix2 <- array2[,,2]
+rm(list = ls())
+
+vector1 <- c(5,9,3)
+vector2 <- c(10,11,12,13,14,15)
+array1 <- array(c(vector1,vector2),dim = c(3,3,2))
+vector3 <- c(9,1,0)
+vector4 <- c(6,0,11,3,14,1,2,6,9)
+array2 <- array(c(vector1,vector2),dim = c(3,3,2))
+matrix1 <- array1[,,2]
+matrix2 <- array2[,,2]
 result <- matrix1+matrix2
-print(result)
-
-column.names <- c("COL1","COL2","COL3")
-row.names <- c("ROW1","ROW2","ROW3")
-matrix.names <- c("Matrix1","Matrix2")
-result <- array(c(vector1,vector2),dim = c(3,3,2),dimnames = list(row.names,
-   column.names, matrix.names))
-print(result[3,,2])
-print(result[1,3,1])
-print(result[,,2])
-
+print(result)
+
+column.names <- c("COL1","COL2","COL3")
+row.names <- c("ROW1","ROW2","ROW3")
+matrix.names <- c("Matrix1","Matrix2")
+result <- array(c(vector1,vector2),dim = c(3,3,2),dimnames = list(row.names,
+   column.names, matrix.names))
+print(result[3,,2])
+print(result[1,3,1])
+print(result[,,2])
+
 # Load the package required to read JSON files.
-library("rjson")
-result <- fromJSON(file = "input.json")
-print(result)
-
-x <- c(151, 174, 138, 186, 128, 136, 179, 163, 152, 131)
-y <- c(63, 81, 56, 91, 47, 57, 76, 72, 62, 48)
-relation <- lm(y~x)
-print(relation)
-
-relation <- lm(y~x)
-png(file = "linearregression.png")
-plot(y,x,col = "blue",main = "Height & Weight Regression",
-abline(lm(x~y)),cex = 1.3,pch = 16,xlab = "Weight in Kg",ylab = "Height in cm")
-dev.off()
-
-data <- c("East","West","East","North","North"[38;2;248;248;24