fix: Fix new clippy warnings

src/lib.rs

@@ -1,7 +1,8 @@
 #![allow(
     clippy::type_complexity,
     clippy::too_many_arguments,
-    clippy::many_single_char_names
+    clippy::many_single_char_names,
+    clippy::unnecessary_wraps
 )]
 #![warn(missing_docs)]
 #![warn(missing_doc_code_examples)]

src/linalg/mod.rs

@@ -1,3 +1,4 @@
+#![allow(clippy::wrong_self_convention)]
 //! # Linear Algebra and Matrix Decomposition
 //!
 //! Most machine learning algorithms in SmartCore depend on linear algebra and matrix decomposition methods from this module.
@@ -265,7 +266,7 @@ pub trait BaseVector<T: RealNumber>: Clone + Debug {
             sum += xi * xi;
         }
         mu /= div;
-        sum / div - mu * mu
+        sum / div - mu.powi(2)
     }
     /// Computes the standard deviation.
     fn std(&self) -> T {

src/linalg/stats.rs

@@ -61,7 +61,7 @@ pub trait MatrixStats<T: RealNumber>: BaseMatrix<T> {
                 sum += a * a;
             }
             mu /= div;
-            *x_i = sum / div - mu * mu;
+            *x_i = sum / div - mu.powi(2);
         }
 
         x

src/linear/lasso_optimizer.rs

@@ -138,7 +138,7 @@ impl<T: RealNumber, M: Matrix<T>> InteriorPointOptimizer<T, M> {
 
             for i in 0..p {
                 self.prb[i] = T::two() + self.d1[i];
-                self.prs[i] = self.prb[i] * self.d1[i] - self.d2[i] * self.d2[i];
+                self.prs[i] = self.prb[i] * self.d1[i] - self.d2[i].powi(2);
             }
 
             let normg = grad.norm2();

src/optimization/first_order/lbfgs.rs

@@ -1,3 +1,4 @@
+#![allow(clippy::suspicious_operation_groupings)]
 use std::default::Default;
 use std::fmt::Debug;