Bump OrderedFlaot dependency to 2.0.

Author: sebpuetz

Cargo.toml

@@ -20,7 +20,7 @@ byteorder = "1"
 fnv = "1"
 itertools = "0.9"
 ndarray = "0.13"
-ordered-float = "1"
+ordered-float = "2"
 rand = "0.7"
 rand_xorshift = "0.2"
 reductive = "0.5"

src/similarity.rs

@@ -305,6 +305,7 @@ mod tests {
     use std::io::BufReader;
 
     use approx::AbsDiffEq;
+    use ordered_float::NotNan;
 
     use crate::compat::word2vec::ReadWord2Vec;
     use crate::embeddings::Embeddings;
@@ -413,25 +414,25 @@ mod tests {
     fn cosine_similarity_is_correctly_converted_to_angular_similarity() {
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 1f32.into()
+            similarity: NotNan::new(1f32).unwrap()
         })
         .angular_similarity()
         .abs_diff_eq(&1f32, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 0.70710678.into()
+            similarity: NotNan::new(0.70710678).unwrap()
         })
         .angular_similarity()
         .abs_diff_eq(&0.75, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 0f32.into()
+            similarity: NotNan::new(0f32).unwrap()
         })
         .angular_similarity()
         .abs_diff_eq(&0.5f32, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: (-1f32).into()
+            similarity: NotNan::new(-1f32).unwrap()
         })
         .angular_similarity()
         .abs_diff_eq(&0f32, 1e-5));
@@ -441,25 +442,25 @@ mod tests {
     fn cosine_similarity_is_correctly_converted_to_euclidean_distance() {
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 1f32.into()
+            similarity: NotNan::new(1f32).unwrap()
         })
         .euclidean_distance()
         .abs_diff_eq(&0f32, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 0.70710678.into()
+            similarity: NotNan::new(0.70710678).unwrap()
         })
         .euclidean_distance()
         .abs_diff_eq(&0.76537, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 0f32.into()
+            similarity: NotNan::new(0f32).unwrap()
         })
         .euclidean_distance()
         .abs_diff_eq(&2f32.sqrt(), 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: (-1f32).into()
+            similarity: NotNan::new(-1f32).unwrap()
         })
         .euclidean_distance()
         .abs_diff_eq(&2f32, 1e-5));
@@ -469,25 +470,25 @@ mod tests {
     fn cosine_similarity_is_correctly_converted_to_euclidean_similarity() {
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 1f32.into()
+            similarity: NotNan::new(1f32).unwrap()
         })
         .euclidean_similarity()
         .abs_diff_eq(&1f32, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 0.70710678.into()
+            similarity: NotNan::new(0.70710678).unwrap()
         })
         .euclidean_similarity()
         .abs_diff_eq(&0.61732, 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: 0f32.into()
+            similarity: NotNan::new(0f32).unwrap()
         })
         .euclidean_similarity()
         .abs_diff_eq(&(1f32 - 1f32 / 2f32.sqrt()), 1e-5));
         assert!((WordSimilarityResult {
             word: "test",
-            similarity: (-1f32).into()
+            similarity: NotNan::new(-1f32).unwrap(),
         })
         .euclidean_similarity()
         .abs_diff_eq(&0f32, 1e-5));
@@ -513,8 +514,6 @@ mod tests {
         let result = result.unwrap();
         assert_eq!(10, result.len());
 
-        println!("{:?}", result);
-
         for (idx, word_similarity) in result.iter().enumerate() {
             assert_eq!(SIMILARITY_ORDER[idx], word_similarity.word)
         }
@@ -548,8 +547,6 @@ mod tests {
         let result = result.unwrap();
         assert_eq!(10, result.len());
 
-        println!("{:?}", result);
-
         for (idx, word_similarity) in result.iter().enumerate() {
             assert_eq!(SIMILARITY_ORDER_STUTTGART_10[idx], word_similarity.word)
         }