# read the file with delimiter as `,` and column headers
data <- read.csv("test.csv", sep = ",", header = TRUE)

# populating the variables with data
# only TeacherID and ResourceID are used
# as.vector is used to vectorize rather than factor
# mainly to populate the mat matrix

SysID <- as.vector(data$SystemID)
TeacherID <- as.vector(data$TeacherKey)
ResourceID <- as.vector(data$ResourceID)

# mat matrix keeps track of the TeacherID with ResourceID
# More efficient way (RFC) : If each row can be called with
# some index then the creation of mat can be avoided.

mat = matrix(, nrow = length(TeacherID), ncol = 2)
mat[,1] <- TeacherID
mat[,2] <- ResourceID

# The idea is to construct the binary matrix.
# We keep a track of unique TeacherID (UTeacherID)
# and unique Resource ID (UResourceID). Compare these with
# the mat matrix to fill the BM (Binary Matrix).
# (RFC) Can binary construction be done more simpler ??
# The current implementation is too rudimentary as it runs
# over 3 loops. (WIP : More efficiency)

# Taking Resource ID as column heads and Teacher ID as row starters.

UTeacherID <- sort(unique(TeacherID), decreasing = FALSE)
UResourceID <- sort(unique(ResourceID), decreasing = FALSE)
BM <- matrix(, nrow = length(UTeacherID), ncol = length(UResourceID))
for (i in 1:length(UTeacherID)){
    for (j in 1:length(mat[,1])){
        if (mat[j, 1] == UTeacherID[i]){
            for (k in 1:length(UResourceID)){
                if (mat[j, 2] == UResourceID[k]){
                    BM[i, k] <- 1
                }
            }
        }
    }
}

# NA filled elements have to be made zero
# WIP : This can be achieved with the above loops
# RFC : for - else kind in R ??

for (i in 1:length(UTeacherID)){
    for (j in 1:length(UResourceID)){
        if (is.na(BM[i, j])){
            BM[i, j] <- 0
        }
    }
}
# BM matrix construction complete.