From 9614692a4f274795594578d6ff1bf3d460dae7bc Mon Sep 17 00:00:00 2001
From: Engine Feeder <enginefeeder101@users.noreply.github.com>
Date: Sat, 10 Mar 2018 18:56:18 +0100
Subject: [PATCH 1/3] Adding crossover function

This commit adds crossover functions to the Matrix and NeuralNetwork class. It defaults
to a uniform crossover (ratio = 0.5), but this is customizable (third parameter).

You can use it as such:
```javascript
  let mom = new NeuralNetwork(2, 4, 1);
  let dad = new NeuralNetwork(2, 4, 1);
  let child = NeuralNetwork.crossover(mom, dad);
```
---
 lib/matrix.js | 6 ++++++
 lib/nn.js     | 8 ++++++++
 2 files changed, 14 insertions(+)

diff --git a/lib/matrix.js b/lib/matrix.js
index 34b2d97..29e24a2 100644
--- a/lib/matrix.js
+++ b/lib/matrix.js
@@ -18,6 +18,12 @@ class Matrix {
     return m;
   }
 
+  static crossover(a, b, ratio = 0.5) {
+    let m = a.copy();
+    m.map((value, i, j) => Math.random() < ratio ? value : b.data[i][j])
+    return m;
+  }
+
   static fromArray(arr) {
     return new Matrix(arr.length, 1).map((e, i) => arr[i]);
   }
diff --git a/lib/nn.js b/lib/nn.js
index 0260280..8514d5d 100644
--- a/lib/nn.js
+++ b/lib/nn.js
@@ -175,6 +175,14 @@ class NeuralNetwork {
     this.bias_o.map(mutate);
   }
 
+  static crossover(a, b, ratio = 0.5) {
+    let nn = a.copy();
+    nn.weights_ih = Matrix.crossover(a.weights_ih, b.weights_ih, ratio);
+    nn.weights_ho = Matrix.crossover(a.weights_ho, b.weights_ho, ratio);
+    nn.bias_h = Matrix.crossover(a.bias_h, b.bias_h, ratio);
+    nn.bias_o = Matrix.crossover(a.bias_o, b.bias_o, ratio);
+    return nn;
+  }
 
 
 }

From 515100c07e067eafc833e51948e55ca5d72b79a2 Mon Sep 17 00:00:00 2001
From: Engine Feeder <enginefeeder101@users.noreply.github.com>
Date: Thu, 15 Mar 2018 21:06:33 +0100
Subject: [PATCH 2/3] Fixed missing semicolon

There was a semicolon missing after the `map()` function.
---
 lib/matrix.js | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/matrix.js b/lib/matrix.js
index 29e24a2..d9347fe 100644
--- a/lib/matrix.js
+++ b/lib/matrix.js
@@ -20,7 +20,7 @@ class Matrix {
 
   static crossover(a, b, ratio = 0.5) {
     let m = a.copy();
-    m.map((value, i, j) => Math.random() < ratio ? value : b.data[i][j])
+    m.map((value, i, j) => Math.random() < ratio ? value : b.data[i][j]);
     return m;
   }
 

From 3a76ec9dc982520f3c25afe20a07ce31c631c359 Mon Sep 17 00:00:00 2001
From: Engine Feeder <enginefeeder101@users.noreply.github.com>
Date: Thu, 15 Mar 2018 22:40:34 +0100
Subject: [PATCH 3/3] Add type checking and size checking to crossover
 functions

This commit adds a check to the `crossover()` functions (both Matrix and NeuralNetwork)
that does not allow to crossover between different breeds. In other words, only if two
NeuralNetwork have the same number of nodes thay can crossover. Otherwise undefined is
returned. Same for the Matrix crossover function.
---
 lib/matrix.js | 5 +++++
 lib/nn.js     | 5 +++++
 2 files changed, 10 insertions(+)

diff --git a/lib/matrix.js b/lib/matrix.js
index d9347fe..f83475e 100644
--- a/lib/matrix.js
+++ b/lib/matrix.js
@@ -19,6 +19,11 @@ class Matrix {
   }
 
   static crossover(a, b, ratio = 0.5) {
+    if (!a instanceof this || !b instanceof this || a.rows !== b.rows || a.cols !== b.cols) {
+      console.log('Columns and Rows of A must match Columns and Rows of B.');
+      return;
+    }
+
     let m = a.copy();
     m.map((value, i, j) => Math.random() < ratio ? value : b.data[i][j]);
     return m;
diff --git a/lib/nn.js b/lib/nn.js
index 8514d5d..8895f03 100644
--- a/lib/nn.js
+++ b/lib/nn.js
@@ -176,6 +176,11 @@ class NeuralNetwork {
   }
 
   static crossover(a, b, ratio = 0.5) {
+    if (!a instanceof this || !b instanceof this || a.input_nodes !== b.input_nodes || a.hidden_nodes !== b.hidden_nodes || a.output_nodes !== b.output_nodes) {
+      console.error('Only NeuralNetworks of the same breed can generate offspring.');
+      return;
+    }
+
     let nn = a.copy();
     nn.weights_ih = Matrix.crossover(a.weights_ih, b.weights_ih, ratio);
     nn.weights_ho = Matrix.crossover(a.weights_ho, b.weights_ho, ratio);