better code

src/ml/f32/matrix.rs

@@ -1,4 +1,6 @@
 
+#[derive(Clone, Debug)] 
+
 pub struct MatrixStruct {
     pub rows: usize,
     pub columns: usize,
@@ -100,18 +102,9 @@ impl MatrixStruct {
         matrix
     }
 
-    pub fn clone(m: &MatrixStruct) -> MatrixStruct {
-        let mut cp_matrix = MatrixStruct::from(&m.rows, &m.columns);
-        for i in 0..m.rows  {
-            for j in 0..m.columns  {
-                cp_matrix.matrix[i][j] = m.matrix[i][j];
-            }
-        }
-        cp_matrix
-    }
     //sometimes the rust is not in the mood
     pub fn scale(num: &f32, m1: &MatrixStruct) -> MatrixStruct {
-        let mut m = MatrixStruct::clone(m1);
+        let mut m = m1.clone();
         for i in 0..m.rows {
             for j in 0..m.columns  {
                 m.matrix[i][j] *= num;

src/ml/f32/nn.rs

@@ -5,6 +5,8 @@ use crate::ml::f32::img::Img;
 use crate::ml::f32::matrix::MatrixStruct;
 
 // use crate::ml::f32::img::Img;
+#[derive(Debug, Clone)]
+
 pub struct NeuralNetwork {
     pub parameters: Box<[usize]>, //the first index will be the input layer (parameters[0]) , the last index will be the output layer (parameters[parameters.len()-1]) and lastly the rest of the vaues will be the hidden_layer (parameters[1..parameters.len()-2])
     pub learning_rate: f32,
@@ -14,15 +16,6 @@ pub struct NeuralNetwork {
 
 impl NeuralNetwork {
 
-    pub fn clone(nn: &NeuralNetwork) -> NeuralNetwork{
-        NeuralNetwork{
-           parameters: Box::clone(&nn.parameters),
-           learning_rate: nn.learning_rate.clone(),
-           hidden_weights: MatrixStruct::clone(&nn.hidden_weights),
-           output_weights: MatrixStruct::clone(&nn.output_weights)
-        }
-    }
-
     pub fn from(parameters_: &Box<[usize]>, learning_rate_: &f32) -> NeuralNetwork {
         NeuralNetwork {
             parameters: Box::clone(parameters_),

src/ml/f32/save.rs

@@ -5,6 +5,7 @@ use crate::ml::f32::matrix::MatrixStruct;
 use std::process::Command;
 
 #[allow(dead_code)]
+#[derive(Clone, Debug)]
 struct Save {
     path: String,
     nn: NeuralNetwork,
@@ -21,14 +22,15 @@ impl Save {
                     panic!("where is the path big brother?, didnt ask for a null string :< ");
                 }
             },
-            nn: NeuralNetwork::clone(&nn_),
+            nn: nn_.clone(),
         }
     }
     #[allow(dead_code)]
     pub fn mkdirs(&self) {
-        let cmd = Command::new("sh")
+        let cmd = Command::new("/bin/sh")
+            .arg("-c")
             .arg(format!(
-                "-c mkdir -v -p {} {} {}",
+                "mkdir -v -p {} {} {}",
                 (self.path.clone() + &"/NeuralNetwork/output"),
                 (self.path.clone() + &"/NeuralNetwork/hidden"),
                 (self.path.clone() + &"/NeuralNetwork/input")
@@ -40,7 +42,7 @@ impl Save {
 
     #[allow(dead_code)]
     pub fn touch_files(&self){
-        let mut cmd = Command::new("touch");
+        let mut cmd = Command::new("/usr/bin/touch");
         let len = self.nn.parameters.len();
         for i in 0..len{
             match i{

src/ml/f64/matrix.rs

@@ -1,5 +1,5 @@
 
-#[derive(Debug)]
+#[derive(Debug, Clone)]
 pub struct MatrixStruct {
     pub rows: usize,
     pub columns: usize,
@@ -106,18 +106,9 @@ impl MatrixStruct {
         }
         matrix
     }
-    pub fn clone(m: &MatrixStruct) -> MatrixStruct {
-        let mut cp_matrix = MatrixStruct::from(&m.rows, &m.columns);
-        for i in 0..m.rows {
-            for j in 0..m.columns {
-                cp_matrix.matrix[i][j] = m.matrix[i][j];
-            }
-        }
-        cp_matrix
-    }
     //sometimes the rust is not in the mood
     pub fn scale(num: &f64, m1: &MatrixStruct) -> MatrixStruct {
-        let mut m = MatrixStruct::clone(m1);
+        let mut m = m1.clone();
         for i in 0..m.rows {
             for j in 0..m.columns {
                 m.matrix[i][j] *= num;

src/ml/f64/nn.rs

@@ -3,6 +3,7 @@ use crate::ml::f64::activation;
 use crate::ml::f64::img::Img;
 use crate::ml::f64::matrix::MatrixStruct;
 
+#[derive(Clone, Debug)]
 pub struct NeuralNetwork {
     pub parameters: Box<[usize]>, //the first index will be the input layer (parameters[0]) , the last index will be the output layer (parameters[parameters.len()-1]) and lastly the rest of the vaues will be the hidden_layer (parameters[1..parameters.len()-2])
     pub learning_rate: f64,
@@ -12,14 +13,6 @@ pub struct NeuralNetwork {
 
 impl NeuralNetwork {
 
-    pub fn clone(nn: &NeuralNetwork) -> NeuralNetwork{
-        NeuralNetwork{
-           parameters: Box::clone(&nn.parameters),
-           learning_rate: nn.learning_rate.clone(),
-           hidden_weights: MatrixStruct::clone(&nn.hidden_weights),
-           output_weights: MatrixStruct::clone(&nn.output_weights)
-        }
-    }
 
     pub fn from(parameters_: &Box<[usize]>, learning_rate_: &f64) -> NeuralNetwork {
         NeuralNetwork {

src/ml/f64/save.rs

@@ -4,6 +4,7 @@ use std::io::prelude::*;
 use crate::ml::f64::matrix::MatrixStruct;
 use std::process::Command;
 
+#[derive(Clone, Debug)]
 #[allow(dead_code)]
 struct Save {
     path: String,
@@ -21,14 +22,15 @@ impl Save {
                     panic!("where is the path big brother?, didnt ask for a null string :< ");
                 }
             },
-            nn: NeuralNetwork::clone(&nn_),
+            nn: nn_.clone(),
         }
     }
     #[allow(dead_code)]
     pub fn mkdirs(&self) {
-        let cmd = Command::new("sh")
+        let cmd =  Command::new("/bin/sh")
+            .arg("-c")
             .arg(format!(
-                "-c mkdir -v -p {} {} {}",
+                "mkdir -v -p {} {} {}",
                 (self.path.clone() + &"/NeuralNetwork/output"),
                 (self.path.clone() + &"/NeuralNetwork/hidden"),
                 (self.path.clone() + &"/NeuralNetwork/input")
@@ -40,7 +42,7 @@ impl Save {
 
     #[allow(dead_code)]
     pub fn touch_files(&self){
-        let mut cmd = Command::new("touch");
+        let mut cmd = Command::new("/usr/bin/touch");
         let len = self.nn.parameters.len();
         for i in 0..len{
             match i{