Add Interquartile Range

DIRECTORY.md

@@ -183,6 +183,7 @@
  * [Huber Loss](https://github.com/TheAlgorithms/Rust/blob/master/src/math/huber_loss.rs)
  * [Interest](https://github.com/TheAlgorithms/Rust/blob/master/src/math/interest.rs)
  * [Interpolation](https://github.com/TheAlgorithms/Rust/blob/master/src/math/interpolation.rs)
+ * [Interquartile Range](https://github.com/TheAlgorithms/Rust/blob/master/src/math/interquartile_range.rs)
  * [Karatsuba Multiplication](https://github.com/TheAlgorithms/Rust/blob/master/src/math/karatsuba_multiplication.rs)
  * [Lcm Of N Numbers](https://github.com/TheAlgorithms/Rust/blob/master/src/math/lcm_of_n_numbers.rs)
  * [Leaky Relu](https://github.com/TheAlgorithms/Rust/blob/master/src/math/leaky_relu.rs)

src/math/interquartile_range.rs

@@ -0,0 +1,85 @@
+// Author : cyrixninja
+// Interquartile Range : An implementation of interquartile range (IQR) which is a measure of statistical
+// dispersion, which is the spread of the data.
+// Wikipedia Reference : https://en.wikipedia.org/wiki/Interquartile_range
+
+use std::cmp::Ordering;
+
+pub fn find_median(numbers: &[f64]) -> f64 {
+ let mut numbers = numbers.to_vec();
+ numbers.sort_by(|a, b| a.partial_cmp(b).unwrap_or(Ordering::Equal));
+
+ let length = numbers.len();
+ let mid = length / 2;
+
+ if length % 2 == 0 {
+ (numbers[mid - 1] + numbers[mid]) / 2.0
+ } else {
+ numbers[mid]
+ }
+}
+
+pub fn interquartile_range(numbers: &[f64]) -> f64 {
+ if numbers.is_empty() {
+ panic!("Error: The list is empty. Please provide a non-empty list.");
+ }
+
+ let mut numbers = numbers.to_vec();
+ numbers.sort_by(|a, b| a.partial_cmp(b).unwrap_or(Ordering::Equal));
+
+ let length = numbers.len();
+ let mid = length / 2;
+ let (q1, q3) = if length % 2 == 0 {
+ let first_half = &numbers[0..mid];
+ let second_half = &numbers[mid..length];
+ (find_median(first_half), find_median(second_half))
+ } else {
+ let first_half = &numbers[0..mid];
+ let second_half = &numbers[mid + 1..length];
+ (find_median(first_half), find_median(second_half))
+ };
+
+ q3 - q1
+}
+
+#[cfg(test)]
+mod tests {
+ use super::*;
+
+ #[test]
+ fn test_find_median() {
+ let numbers1 = vec![1.0, 2.0, 2.0, 3.0, 4.0];
+ assert_eq!(find_median(&numbers1), 2.0);
+
+ let numbers2 = vec![1.0, 2.0, 2.0, 3.0, 4.0, 4.0];
+ assert_eq!(find_median(&numbers2), 2.5);
+
+ let numbers3 = vec![-1.0, 2.0, 0.0, 3.0, 4.0, -4.0];
+ assert_eq!(find_median(&numbers3), 1.0);
+
+ let numbers4 = vec![1.1, 2.2, 2.0, 3.3, 4.4, 4.0];
+ assert_eq!(find_median(&numbers4), 2.75);
+ }
+
+ #[test]
+ fn test_interquartile_range() {
+ let numbers1 = vec![4.0, 1.0, 2.0, 3.0, 2.0];
+ assert_eq!(interquartile_range(&numbers1), 2.0);
+
+ let numbers2 = vec![-2.0, -7.0, -10.0, 9.0, 8.0, 4.0, -67.0, 45.0];
+ assert_eq!(interquartile_range(&numbers2), 17.0);
+
+ let numbers3 = vec![-2.1, -7.1, -10.1, 9.1, 8.1, 4.1, -67.1, 45.1];
+ assert_eq!(interquartile_range(&numbers3), 17.2);
+
+ let numbers4 = vec![0.0, 0.0, 0.0, 0.0, 0.0];
+ assert_eq!(interquartile_range(&numbers4), 0.0);
+ }
+
+ #[test]
+ #[should_panic(expected = "Error: The list is empty. Please provide a non-empty list.")]
+ fn test_interquartile_range_empty_list() {
+ let numbers: Vec<f64> = vec![];
+ interquartile_range(&numbers);
+ }
+}

src/math/mod.rs

@@ -33,6 +33,7 @@ mod greatest_common_divisor;
 mod huber_loss;
 mod interest;
 mod interpolation;
+mod interquartile_range;
 mod karatsuba_multiplication;
 mod lcm_of_n_numbers;
 mod leaky_relu;
@@ -112,6 +113,7 @@ pub use self::greatest_common_divisor::{
 pub use self::huber_loss::huber_loss;
 pub use self::interest::{compound_interest, simple_interest};
 pub use self::interpolation::{lagrange_polynomial_interpolation, linear_interpolation};
+pub use self::interquartile_range::interquartile_range;
 pub use self::karatsuba_multiplication::multiply;
 pub use self::lcm_of_n_numbers::lcm;
 pub use self::leaky_relu::leaky_relu;