Fix typos & remove commented-out code

Author: NicklasXYZ

src/gleam_community/maths.gleam

@@ -332,20 +332,6 @@ pub fn weighted_sum(arr: List(#(Float, Float))) -> Result(Float, Nil) {
   }
 }
 
-// let weight_is_negative = list.any(arr, fn(tuple) { tuple.1 <. 0.0 })
-
-// case weight_is_negative {
-//   True -> Error(Nil)
-//   False -> {
-//     let weighted_sum =
-//       list.fold(arr, 0.0, fn(acc, a) { a.0 *. a.1 +. acc })
-//     Ok(weighted_sum)
-//   }
-// }
-//     }
-//   }
-// }
-
 /// <div style="text-align: right;">
 ///     <a href="https://github.com/gleam-community/maths/issues">
 ///         <small>Spot a typo? Open an issue!</small>
@@ -2170,7 +2156,7 @@ pub fn absolute_difference(a: Float, b: Float) -> Float {
 /// \\]
 ///
 /// The function takes two inputs \\(x\\) and \\(y\\) and returns a positive integer
-/// value which is the the absolute difference of the inputs.
+/// value which is the absolute difference of the inputs.
 ///
 /// <details>
 ///     <summary>Example:</summary>
@@ -3363,7 +3349,7 @@ pub fn norm(arr: List(Float), p: Float) -> Result(Float, Nil) {
     [] -> Ok(0.0)
     _ -> {
       case p {
-        // Handle the the special case when 'p' is equal to zero. In this case, we compute a 
+        // Handle the special case when 'p' is equal to zero. In this case, we compute a 
         // pseudo-norm, which is the number of non-zero elements in the given list 'arr'
         0.0 ->
           Ok(
@@ -3473,7 +3459,7 @@ pub fn norm_with_weights(
         False -> {
           case p {
             0.0 -> {
-              // Handle the the special case when 'p' is equal to zero. In this case, we compute 
+              // Handle the special case when 'p' is equal to zero. In this case, we compute 
               // a pseudo-norm, which is the number of non-zero elements in the given list 'arr'
               Ok(
                 list.fold(arr, 0.0, fn(acc, tuple) {
@@ -3931,7 +3917,7 @@ pub fn chebyshev_distance_with_weights(
 ///     </a>
 /// </div>
 ///
-/// Calculcate the n'th moment about the mean of a list of elements.
+/// Calculate the n'th moment about the mean of a list of elements.
 ///
 /// <details>
 ///     <summary>Example:</summary>
@@ -3968,40 +3954,6 @@ pub fn chebyshev_distance_with_weights(
 ///     </a>
 /// </div>
 ///
-// pub fn moment(arr: List(Float), n: Int) -> Result(Float, Nil) {
-//   case list.length(arr), n {
-//     0, _ -> Error(Nil)
-//     // 0th moment is always 1.0
-//     __, 0 -> Ok(1.0)
-//     // 1st moment (about the mean) is 0.0 by definition
-//     _, 1 -> Ok(0.0)
-//     _, n if n >= 0 -> {
-//       // Check if the list has enough elements for the nth moment
-//       case list.length(arr) >= n {
-//         True -> {
-//           // Usage of let assert: The function 'mean' will only return an error if the given list
-//           // is emptry. No error will occur since we already checked that the list is non-empty.
-//           let assert Ok(m1) = mean(arr)
-//           let result =
-//             list.try_fold(arr, 0.0, fn(acc, a) {
-//               case float.power(a -. m1, int.to_float(n)) {
-//                 Error(Nil) -> Error(Nil)
-//                 Ok(value) -> Ok(value +. acc)
-//               }
-//             })
-//           case result {
-//             Error(Nil) -> Error(Nil)
-//             Ok(value) -> Ok(value /. int.to_float(list.length(arr)))
-//           }
-//         }
-//         // Not enough elements for meaningful computation
-//         False -> Error(Nil)
-//       }
-//     }
-//     _, _ -> Error(Nil)
-//   }
-// }
-
 pub fn moment(arr: List(Float), n: Int) -> Result(Float, Nil) {
   case arr, n {
     // Handle empty list: no moments can be calculated
@@ -4089,7 +4041,7 @@ pub fn mean(arr: List(Float)) -> Result(Float, Nil) {
 ///     </a>
 /// </div>
 ///
-/// Calculcate the harmonic mean \\(\bar{x}\\) of the elements in a list:
+/// Calculate the harmonic mean \\(\bar{x}\\) of the elements in a list:
 ///
 /// \\[
 ///   \bar{x} = \frac{n}{\sum_{i=1}^{n}\frac{1}{x_i}}
@@ -4158,7 +4110,7 @@ pub fn harmonic_mean(arr: List(Float)) -> Result(Float, Nil) {
 ///     </a>
 /// </div>
 ///
-/// Calculcate the geometric mean \\(\bar{x}\\) of the elements in a list:
+/// Calculate the geometric mean \\(\bar{x}\\) of the elements in a list:
 ///
 /// \\[
 ///   \bar{x} = \left(\prod^{n}_{i=1} x_i\right)^{\frac{1}{n}}
@@ -4414,7 +4366,7 @@ pub fn standard_deviation(arr: List(Float), ddof: Int) -> Result(Float, Nil) {
 ///     </a>
 /// </div>
 ///
-/// Calculcate the sample kurtosis of a list of elements using the 
+/// Calculate the sample kurtosis of a list of elements using the 
 /// definition of Fisher. 
 ///
 /// <details>
@@ -4469,7 +4421,7 @@ pub fn kurtosis(arr: List(Float)) -> Result(Float, Nil) {
 ///     </a>
 /// </div>
 ///
-/// Calculcate the sample skewness of a list of elements using the 
+/// Calculate the sample skewness of a list of elements using the 
 /// Fisher-Pearson coefficient of skewness. 
 ///
 /// <details>
@@ -5296,7 +5248,7 @@ pub fn canberra_distance(arr: List(#(Float, Float))) -> Result(Float, Nil) {
 ///     import gleam_community/maths
 ///
 ///     pub fn example() {
-///       maths.canberra_distance([])
+///       maths.canberra_distance_with_weights([])
 ///       |> should.be_error()
 ///     
 ///       maths.canberra_distance_with_weights([#(1.0, -2.0, 0.5), #(2.0, -1.0, 1.0)])
@@ -5365,8 +5317,8 @@ pub fn canberra_distance_with_weights(
 ///       maths.canberra_distance([])
 ///       |> should.be_error()
 ///     
-///       maths.canberra_distance_with_weights([#(1.0, -2.0, 0.5), #(2.0, -1.0, 1.0)])
-///       |> should.equal(Ok(1.5))
+///       maths.braycurtis_distance([#(1.0, 3.0), #(2.0, 4.0)])
+///       |> should.equal(Ok(0.4))
 ///     }
 /// </details>
 ///

test/gleam_community/metrics_test.gleam

@@ -974,6 +974,7 @@ pub fn braycurtis_distance_test() {
   // Try different types of valid input
   maths.braycurtis_distance([#(0.0, 0.0), #(0.0, 0.0)])
   |> should.equal(Ok(0.0))
+
   maths.braycurtis_distance([#(1.0, -2.0), #(2.0, -1.0)])
   |> should.equal(Ok(3.0))