Implement realnum::rand (#251)

Co-authored-by: Luis Moreno <morenol@users.noreply.github.com>
Co-authored-by: Lorenzo <tunedconsulting@gmail.com>

* Implement rand. Use the new derive [#default]
* Use custom range
* Use range seed
* Bump version
* Add array length checks for

src/linear/logistic_regression.rs

@@ -71,19 +71,14 @@ use crate::optimization::line_search::Backtracking;
 use crate::optimization::FunctionOrder;
 
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
-#[derive(Debug, Clone, Eq, PartialEq)]
+#[derive(Debug, Clone, Eq, PartialEq, Default)]
 /// Solver options for Logistic regression. Right now only LBFGS solver is supported.
 pub enum LogisticRegressionSolverName {
     /// Limited-memory Broyden–Fletcher–Goldfarb–Shanno method, see [LBFGS paper](http://users.iems.northwestern.edu/~nocedal/lbfgsb.html)
+    #[default]
     LBFGS,
 }
 
-impl Default for LogisticRegressionSolverName {
-    fn default() -> Self {
-        LogisticRegressionSolverName::LBFGS
-    }
-}
-
 /// Logistic Regression parameters
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, Clone)]

src/linear/ridge_regression.rs

@@ -71,21 +71,16 @@ use crate::numbers::basenum::Number;
 use crate::numbers::realnum::RealNumber;
 
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
-#[derive(Debug, Clone, Eq, PartialEq)]
+#[derive(Debug, Clone, Eq, PartialEq, Default)]
 /// Approach to use for estimation of regression coefficients. Cholesky is more efficient but SVD is more stable.
 pub enum RidgeRegressionSolverName {
     /// Cholesky decomposition, see [Cholesky](../../linalg/cholesky/index.html)
+    #[default]
     Cholesky,
     /// SVD decomposition, see [SVD](../../linalg/svd/index.html)
     SVD,
 }
 
-impl Default for RidgeRegressionSolverName {
-    fn default() -> Self {
-        RidgeRegressionSolverName::Cholesky
-    }
-}
-
 /// Ridge Regression parameters
 #[cfg_attr(feature = "serde", derive(Serialize, Deserialize))]
 #[derive(Debug, Clone)]