Format jsdoc comments

umcconnell · Jul 2, 2019 · 793e8d5 · 793e8d5
1 parent dcb323c
commit 793e8d5
Showing 1 changed file with 18 additions and 9 deletions.
diff --git a/lib/index.js b/lib/index.js
@@ -113,7 +113,8 @@ export class Layer {
 
     /**
      * Adds Biases object to layer
-     * @param {Biases} biases biases object from Biases constructor; belongs to ouput layer
+     * @param {Biases} biases biases object from Biases constructor; belongs to
+     * ouput layer
      * @example
      * let inputLayer = new Layer(5);
      * let outputLayer = new Layer(2);
@@ -130,7 +131,8 @@ export class Layer {
 
     /**
      * Adds Weights object to layer
-     * @param {Weights} weights weights object from Weights constructor; belongs to input layer
+     * @param {Weights} weights weights object from Weights constructor; belongs
+     * to input layer
      * @example
      * let inputLayer = new Layer(5);
      * let outputLayer = new Layer(2);
@@ -151,7 +153,8 @@ export class Layer {
 
     /**
      * Applys given function to all neurons of the layer
-     * @param {Function} func mapping function called with neuron value and index
+     * @param {Function} func mapping function called with neuron value and
+     * index
      * @example
      * outputLayer.apply(sigmoid);
      * @returns layer
@@ -180,7 +183,8 @@ export class Layer {
 
     /**
      * Populates neurons with data
-     * @param {Array} data array of data to populate layer / neurons with; must be same length as layer
+     * @param {Array} data array of data to populate layer / neurons with; must
+     * be same length as layer
      * @returns layer
      */
     populate(data) {
@@ -193,7 +197,8 @@ export class Layer {
     }
 
     /**
-     * Runs connection between two layers by applying weights to input layer's neurons and biases to resulting output layer's neurons
+     * Runs connection between two layers by applying weights to input layer's
+     * neurons and biases to resulting output layer's neurons
      * @example
      * let inputLayer = new Layer(5);
      * let outputLayer = new Layer(2);
@@ -234,14 +239,16 @@ export class Layer {
 export class Network extends Array {
     /**
      * Creates a neural network with given layers
-     * @param {Array} layers array of Layer objects or numbers representing layer length
+     * @param {Array} layers array of Layer objects or numbers representing
+     * layer length
      */
     constructor(layers) {
         super(...layers.map(el => (el instanceof Layer ? el : new Layer(el))));
     }
 
     /**
-     * Adds randomly filled bias matrix with correct dimensions to every layer by calling Biases constructor
+     * Adds randomly filled bias matrix with correct dimensions to every layer
+     * by calling Biases constructor
      * @returns {Network}
      */
     addBiases() {
@@ -254,7 +261,8 @@ export class Network extends Array {
     }
 
     /**
-     * Adds randomly filled weight matrix with correct dimensions to every layer by calling Weights constructor
+     * Adds randomly filled weight matrix with correct dimensions to every layer
+     * by calling Weights constructor
      * @returns {Network}
      */
     addWeights() {
@@ -270,7 +278,8 @@ export class Network extends Array {
 
     /**
      * Applies a function to every layer by calling layer.apply() on every layer
-     * @param {Function} func mapping function called on every layer with layer.apply()
+     * @param {Function} func mapping function called on every layer with
+     * layer.apply()
      * @returns {Network}
      */
     apply(func) {