## Read the data files into R data frames.

subject_test <- read.table("subject_test.txt")

X_test <- read.table("X_test.txt")

y_test <- read.table("y_test.txt")

subject_train <- read.table("subject_train.txt")

X_train <- read.table("X_train.txt")

y_train <- read.table("y_train.txt")

## Convert the numeric activity descriptors to names.

act_labels <- read.table("activity_labels.txt", as.is=TRUE)

for(i in 1:nrow(y_test)) {

actNum <- y_test[i,1]

actName <- act_labels[actNum,2]

y_test[i,1] <- actName

}

for(i in 1:nrow(y_train)) {

actNum <- y_train[i,1]

actName <- act_labels[actNum,2]

y_train[i,1] <- actName

}

## Bind the six data frames into one data frame.

## Column bind the test data.

test_data <- cbind(subject_test,y_test,X_test)

## Column bind the train data.

train_data <- cbind(subject_train,y_train,X_train)

## Row bind the text and train data.

all_data <- rbind(test_data,train_data)

## Read the features text file in for later use in assigning

## description variable names. Use as.is=TRUE to prevent the strings

## from being read in as factors.

features <- read.table("features.txt", as.is=TRUE)

## Convert the features object to a character vector.

featuresChar <- features[,2]

## Assign descriptive variable names to the data frame columns.

colnames(all_data) <- c("Subject","Activity",featuresChar)

## Extract only measurements on the mean and standard deviation

## for each measurement.

DCols <- colnames(all_data)

M_SD <- grep("Subject|Activity|[Mm]ean\\(|[Ss]td\\(",DCols)

all_data <- subset(all_data,select=M_SD)

## Make the variable names from features syntactically valid.

colnames(all_data) <- make.names(colnames(all_data))

## Create a second, independent tidy dataset with an average of each

## variable for each activity and each subject.

melt_data <- melt(all_data,id=c("Subject","Activity"))

tidy_data <- dcast(melt_data, Subject + Activity ~ variable, mean)

## Output the data frame to a text file.

write.table(all_data,"all_data.txt", row.names=FALSE)

# Output the tidy data frame to a text file.

write.table(tidy_data, "tidy_data.txt", row.names=FALSE)

}