diff --git a/README.md b/README.md
index dafc4ce..52de57e 100644
--- a/README.md
+++ b/README.md
@@ -2,12 +2,15 @@ __RLTK__
An attempt to manually port some of nltk to rust.
-Currently in it's infancy:
+Currently in it's infancy (but growing):
* rltk::lm::preprocessing::pad_both_ends(\["a","b","c"], 2) -> "\", "a", "b", "c", "\"]
* rltk::util::pad_sequence == same as above with customisation
* rltk::util::pad_sequence_left == same
* rltk::util::pad_sequence_right == same
-* rltk::util::ngrams(\["a","b","c"],2) -> \[\["a"], \["b"], \["b"], \["c"]]
+* rltk::util::ngrams(\["a","b","c"],2) -> \[\["a", "b"], \["b", "c"]]
* rltk::util::bigrams(\["a","b","c"]) == ngrams(..., 2)
* rltk::util::trigrams(\["a","b","c"]) == ngrams(..., 3)
+* rltk::util::everygrams(\["a","b","c"],2) == \[\["a"], \["a", "b"], \["b"], \["b", "c"]]
+* rltk::util::flatten(\[\["a"], \["a", "b"], \["b"], \["b", "c"]]) == \[\"a", "a", "b", "b", "b", "c"]
+* rltk::metrics::distance::edit_distance("")
diff --git a/src/metrics/distance.rs b/src/metrics/distance.rs
index 64fab4d..3f52bdb 100644
--- a/src/metrics/distance.rs
+++ b/src/metrics/distance.rs
@@ -14,8 +14,6 @@ impl Element {
}
}
-
-
// non recursive implementation requires a table
// my guess is that this is more efficient (should check)
pub(crate) fn get_edit_distance_table(word1: &str, word2: &str) -> Vec> {
diff --git a/src/metrics/mod.rs b/src/metrics/mod.rs
index 04f720c..fabd061 100644
--- a/src/metrics/mod.rs
+++ b/src/metrics/mod.rs
@@ -1,5 +1,10 @@
pub mod distance;
+/// Calculate the Levenshtein edit-distance between two strings.
+/// The edit distance is the number of characters that need to be substituted, inserted, or deleted, to transform s1 into s2.
+/// For example, transforming “rain” to “shine” requires three steps, consisting of two substitutions and one insertion:
+/// “rain” -> “sain” -> “shin” -> “shine”.
+/// These operations could have been done in other orders, but at least three steps are needed.
pub fn edit_distance(s1: &str, s2: &str) -> usize {
distance::get_edit_distance_table(s1, s2)[s1.len()][s2.len()].value
}