Merge pull request #25 from morenol/lmm/utils

Add capability to convert a slice to a BaseVector

src/linalg/mod.rs

@@ -83,6 +83,21 @@ pub trait BaseVector<T: RealNumber>: Clone + Debug {
         self.len() == 0
     }
 
+    /// Create a new vector from a &[T]
+    /// ```
+    /// use smartcore::linalg::naive::dense_matrix::*;
+    /// let a: [f64; 5] = [0., 0.5, 2., 3., 4.];
+    /// let v: Vec<f64> = BaseVector::from_array(&a);
+    /// assert_eq!(v, vec![0., 0.5, 2., 3., 4.]);
+    /// ```
+    fn from_array(f: &[T]) -> Self {
+        let mut v = Self::zeros(f.len());
+        for (i, elem) in f.iter().enumerate() {
+            v.set(i, *elem);
+        }
+        v
+    }
+
     /// Return a vector with the elements of the one-dimensional array.
     fn to_vec(&self) -> Vec<T>;
 

src/math/vector.rs

@@ -1,13 +1,14 @@
 use crate::math::num::RealNumber;
 use std::collections::HashMap;
 
+use crate::linalg::BaseVector;
 pub trait RealNumberVector<T: RealNumber> {
-    fn unique(&self) -> (Vec<T>, Vec<usize>);
+    fn unique_with_indices(&self) -> (Vec<T>, Vec<usize>);
 }
 
-impl<T: RealNumber> RealNumberVector<T> for Vec<T> {
+impl<T: RealNumber, V: BaseVector<T>> RealNumberVector<T> for V {
-    fn unique(&self) -> (Vec<T>, Vec<usize>) {
+    fn unique_with_indices(&self) -> (Vec<T>, Vec<usize>) {
-        let mut unique = self.clone();
+        let mut unique = self.to_vec();
         unique.sort_by(|a, b| a.partial_cmp(b).unwrap());
         unique.dedup();
 
@@ -17,8 +18,8 @@ impl<T: RealNumber> RealNumberVector<T> for Vec<T> {
         }
 
         let mut unique_index = Vec::with_capacity(self.len());
-        for e in self {
+        for idx in 0..self.len() {
-            unique_index.push(index[&e.to_i64().unwrap()]);
+            unique_index.push(index[&self.get(idx).to_i64().unwrap()]);
         }
 
         (unique, unique_index)
@@ -30,11 +31,11 @@ mod tests {
     use super::*;
 
     #[test]
-    fn unique() {
+    fn unique_with_indices() {
         let v1 = vec![0.0, 0.0, 1.0, 1.0, 2.0, 0.0, 4.0];
         assert_eq!(
             (vec!(0.0, 1.0, 2.0, 4.0), vec!(0, 0, 1, 1, 2, 0, 3)),
-            v1.unique()
+            v1.unique_with_indices()
         );
     }
 }

src/metrics/cluster_helpers.rs

@@ -7,8 +7,8 @@ pub fn contingency_matrix<T: RealNumber>(
     labels_true: &Vec<T>,
     labels_pred: &Vec<T>,
 ) -> Vec<Vec<usize>> {
-    let (classes, class_idx) = labels_true.unique();
+    let (classes, class_idx) = labels_true.unique_with_indices();
-    let (clusters, cluster_idx) = labels_pred.unique();
+    let (clusters, cluster_idx) = labels_pred.unique_with_indices();
 
     let mut contingency_matrix = Vec::with_capacity(classes.len());
 

src/naive_bayes/mod.rs

@@ -58,10 +58,7 @@ impl<T: RealNumber, M: Matrix<T>, D: NBDistribution<T, M>> BaseNaiveBayes<T, M,
                 *prediction
             })
             .collect::<Vec<T>>();
-        let mut y_hat = M::RowVector::zeros(rows);
+        let y_hat = M::RowVector::from_array(&predictions);
-        for (i, prediction) in predictions.iter().enumerate().take(rows) {
-            y_hat.set(i, *prediction);
-        }
         Ok(y_hat)
     }
 }