feat: BernoulliNB (#31)

* feat: BernoulliNB

* Move preprocessing to a trait in linalg/stats.rs

Author: morenol

src/linalg/mod.rs

@@ -63,7 +63,7 @@ use evd::EVDDecomposableMatrix;
 use high_order::HighOrderOperations;
 use lu::LUDecomposableMatrix;
 use qr::QRDecomposableMatrix;
-use stats::MatrixStats;
+use stats::{MatrixPreprocessing, MatrixStats};
 use svd::SVDDecomposableMatrix;
 
 /// Column or row vector
@@ -619,6 +619,7 @@ pub trait Matrix<T: RealNumber>:
     + LUDecomposableMatrix<T>
     + CholeskyDecomposableMatrix<T>
     + MatrixStats<T>
+    + MatrixPreprocessing<T>
     + HighOrderOperations<T>
     + PartialEq
     + Display

src/linalg/naive/dense_matrix.rs

@@ -12,7 +12,7 @@ use crate::linalg::evd::EVDDecomposableMatrix;
 use crate::linalg::high_order::HighOrderOperations;
 use crate::linalg::lu::LUDecomposableMatrix;
 use crate::linalg::qr::QRDecomposableMatrix;
-use crate::linalg::stats::MatrixStats;
+use crate::linalg::stats::{MatrixPreprocessing, MatrixStats};
 use crate::linalg::svd::SVDDecomposableMatrix;
 use crate::linalg::Matrix;
 pub use crate::linalg::{BaseMatrix, BaseVector};
@@ -478,6 +478,7 @@ impl<T: RealNumber> HighOrderOperations<T> for DenseMatrix<T> {
 }
 
 impl<T: RealNumber> MatrixStats<T> for DenseMatrix<T> {}
+impl<T: RealNumber> MatrixPreprocessing<T> for DenseMatrix<T> {}
 
 impl<T: RealNumber> Matrix<T> for DenseMatrix<T> {}
 

src/linalg/nalgebra_bindings.rs

@@ -47,7 +47,7 @@ use crate::linalg::evd::EVDDecomposableMatrix;
 use crate::linalg::high_order::HighOrderOperations;
 use crate::linalg::lu::LUDecomposableMatrix;
 use crate::linalg::qr::QRDecomposableMatrix;
-use crate::linalg::stats::MatrixStats;
+use crate::linalg::stats::{MatrixPreprocessing, MatrixStats};
 use crate::linalg::svd::SVDDecomposableMatrix;
 use crate::linalg::Matrix as SmartCoreMatrix;
 use crate::linalg::{BaseMatrix, BaseVector};
@@ -554,6 +554,11 @@ impl<T: RealNumber + Scalar + AddAssign + SubAssign + MulAssign + DivAssign + Su
 {
 }
 
+impl<T: RealNumber + Scalar + AddAssign + SubAssign + MulAssign + DivAssign + Sum + 'static>
+    MatrixPreprocessing<T> for Matrix<T, Dynamic, Dynamic, VecStorage<T, Dynamic, Dynamic>>
+{
+}
+
 impl<T: RealNumber + Scalar + AddAssign + SubAssign + MulAssign + DivAssign + Sum + 'static>
     HighOrderOperations<T> for Matrix<T, Dynamic, Dynamic, VecStorage<T, Dynamic, Dynamic>>
 {

src/linalg/ndarray_bindings.rs

@@ -54,7 +54,7 @@ use crate::linalg::evd::EVDDecomposableMatrix;
 use crate::linalg::high_order::HighOrderOperations;
 use crate::linalg::lu::LUDecomposableMatrix;
 use crate::linalg::qr::QRDecomposableMatrix;
-use crate::linalg::stats::MatrixStats;
+use crate::linalg::stats::{MatrixPreprocessing, MatrixStats};
 use crate::linalg::svd::SVDDecomposableMatrix;
 use crate::linalg::Matrix;
 use crate::linalg::{BaseMatrix, BaseVector};
@@ -503,6 +503,11 @@ impl<T: RealNumber + ScalarOperand + AddAssign + SubAssign + MulAssign + DivAssi
 {
 }
 
+impl<T: RealNumber + ScalarOperand + AddAssign + SubAssign + MulAssign + DivAssign + Sum>
+    MatrixPreprocessing<T> for ArrayBase<OwnedRepr<T>, Ix2>
+{
+}
+
 impl<T: RealNumber + ScalarOperand + AddAssign + SubAssign + MulAssign + DivAssign + Sum>
     HighOrderOperations<T> for ArrayBase<OwnedRepr<T>, Ix2>
 {

src/linalg/stats.rs

@@ -104,6 +104,47 @@ pub trait MatrixStats<T: RealNumber>: BaseMatrix<T> {
     }
 }
 
+/// Defines baseline implementations for various matrix processing functions
+pub trait MatrixPreprocessing<T: RealNumber>: BaseMatrix<T> {
+    /// Each element of the matrix greater than the threshold becomes 1, while values less than or equal to the threshold become 0
+    /// ```
+    /// use smartcore::linalg::naive::dense_matrix::*;
+    /// use crate::smartcore::linalg::stats::MatrixPreprocessing;
+    /// let mut a = DenseMatrix::from_array(2, 3, &[0., 2., 3., -5., -6., -7.]);
+    /// let expected = DenseMatrix::from_array(2, 3, &[0., 1., 1., 0., 0., 0.]);
+    /// a.binarize_mut(0.);
+    ///
+    /// assert_eq!(a, expected);
+    /// ```
+
+    fn binarize_mut(&mut self, threshold: T) {
+        let (nrows, ncols) = self.shape();
+        for row in 0..nrows {
+            for col in 0..ncols {
+                if self.get(row, col) > threshold {
+                    self.set(row, col, T::one());
+                } else {
+                    self.set(row, col, T::zero());
+                }
+            }
+        }
+    }
+    /// Returns new matrix where elements are binarized according to a given threshold.
+    /// ```
+    /// use smartcore::linalg::naive::dense_matrix::*;
+    /// use crate::smartcore::linalg::stats::MatrixPreprocessing;
+    /// let a = DenseMatrix::from_array(2, 3, &[0., 2., 3., -5., -6., -7.]);
+    /// let expected = DenseMatrix::from_array(2, 3, &[0., 1., 1., 0., 0., 0.]);
+    ///
+    /// assert_eq!(a.binarize(0.), expected);
+    /// ```
+    fn binarize(&self, threshold: T) -> Self {
+        let mut m = self.clone();
+        m.binarize_mut(threshold);
+        m
+    }
+}
+
 #[cfg(test)]
 mod tests {
     use super::*;