Lab 8 24Nov23

# Name - AYUSH ANAND
# USN - 1MS21CI008

# Load necessary libraries
library(MASS)

# Function to take user input for matrix
get_matrix_input <- function() {
  nrow <- as.integer(readline(prompt = "Enter the number of rows for the matrix: "))
  ncol <- as.integer(readline(prompt = "Enter the number of columns for the matrix: "))
  
  matrix_elements <- matrix(NA, nrow = nrow, ncol = ncol)
  
  cat("Enter matrix elements row-wise:\n")
  for (i in 1:nrow) {
    for (j in 1:ncol) {
      prompt <- paste("Element for row", i, "and column", j, ": ")
      matrix_elements[i, j] <- as.numeric(readline(prompt = prompt))
    }
  }
  
  return(matrix_elements)
}

# Task i: Create two matrices of the same dimension (A & B)
cat("Enter details for Matrix A:\n")
matrix_A <- get_matrix_input()

cat("\nEnter details for Matrix B:\n")
matrix_B <- get_matrix_input()

# Task ii: Add the two matrices and display the result
result_addition <- matrix_A + matrix_B
cat("\nMatrix Addition Result:\n", result_addition, "\n\n")

# Task iii: Scale a matrix by multiplying with a scalar and display result
scalar <- as.numeric(readline(prompt = "Enter a scalar for matrix multiplication: "))
scaled_matrix <- scalar * matrix_A
cat("\nScalar Multiplication Result:\n", scaled_matrix, "\n\n")

# Task iv: Find transpose of the matrix and display
transpose_matrix_A <- t(matrix_A)
cat("Transpose of Matrix A:\n", transpose_matrix_A, "\n\n")

# Task v: Hadamard product(Element-wise product) of the two matrices
hadamard_product <- matrix_A * matrix_B
cat("\nHadamard Product Result:\n", hadamard_product, "\n\n")

# Task vi: Matrix multiplication
matrix_multiply <- matrix_A %*% matrix_B
cat("\nMatrix Multiplication Result:\n", matrix_multiply, "\n\n")

# Task vii: Generate statistics - Sum, mean, and standard deviation of elements of A
sum_A <- sum(matrix_A)
mean_A <- mean(matrix_A)
sd_A <- sd(matrix_A)
cat("Statistics for Matrix A:\n")
cat("Sum:", sum_A, "\nMean:", mean_A, "\nStandard Deviation:", sd_A, "\n\n")

# Task viii: Plot a heatmap of the matrix A with modified color gradient
heatmap(matrix_A, col = rev(heat.colors(10)), main = "Heatmap of Matrix A", xlab = "Columns", ylab = "Rows")

# Task ix: Plot the bar plot to compare sums of the rows of a matrix A
barplot(rowSums(matrix_A), main = "Bar Plot of Row Sums for Matrix A", xlab = "Rows", ylab = "Sum")

# Modifications:

# Modification 1: Modify the color gradient of the heatmap
heatmap(matrix_A, col = rev(rainbow(10)), main = "Modified Heatmap of Matrix A", xlab = "Columns", ylab = "Rows")

# Modification 2: Generate a barplot of column sums of matrix B with appropriate labels
barplot(colSums(matrix_B), main = "Bar Plot of Column Sums for Matrix B", xlab = "Columns", ylab = "Sum")