diff --git a/DominantColorExtraction/getdominantcolor.py b/DominantColorExtraction/getdominantcolor.py
new file mode 100644
index 0000000..26d47ef
--- /dev/null
+++ b/DominantColorExtraction/getdominantcolor.py
@@ -0,0 +1,102 @@
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+from sklearn.cluster import KMeans
+from os import listdir
+import imageio
+
+from PIL import Image, ImageDraw
+
+def list_files(directory, extension):
+    return (f for f in listdir(directory) if f.endswith('.jpg') or f.endswith('.png'))
+
+def find_histogram(clt):
+    """
+    create a histogram with k clusters
+    :param: clt
+    :return:hist
+    """
+    numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1)
+    (hist, _) = np.histogram(clt.labels_, bins=numLabels)
+
+    hist = hist.astype("float")
+    hist /= hist.sum()
+
+    return hist
+def plot_colors2(hist, centroids):
+    bar = np.zeros((50, 300, 3), dtype="uint8")
+    startX = 0
+
+    for (percent, color) in zip(hist, centroids):
+        # plot the relative percentage of each cluster
+        endX = startX + (percent * 300)
+        cv2.rectangle(bar, (int(startX), 0), (int(endX), 50),
+                      color.astype("uint8").tolist(), -1)
+        startX = endX
+
+    # return the bar chart
+    return bar
+
+
+def generateColorImage(img_input):
+    img = cv2.imread("images/"+img_input)
+
+    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    img_old = img
+
+    height=img.shape[0]
+    width=img.shape[1]
+
+    img = img.reshape((img.shape[0] * img.shape[1],3)) #represent as row*column,channel number
+    clt = KMeans(n_clusters=3) #cluster number
+    clt.fit(img)
+
+    hist = find_histogram(clt)
+
+    #print(hist, clt.cluster_centers_)
+
+    # size of image
+    canvas = (width, height)
+
+    # scale ration
+    scale = 1
+    thumb = canvas[0]/scale, canvas[1]/scale
+
+    # rectangles (width, height, left position, top position)
+    #print(width*hist[0])
+    frames = [(0, 0, 115, height), (width*hist[0], height, width*hist[0]+width,2), (100, 205, 120,200)]
+
+    # init canvas
+    im = Image.new('RGB', canvas, (255, 255, 255))
+    draw = ImageDraw.Draw(im)
+
+    draw.rectangle([0, 0, width*hist[0], height], fill=(int(clt.cluster_centers_[0][0]), int(clt.cluster_centers_[0][1]), int(clt.cluster_centers_[0][2])))
+    draw.rectangle([width*hist[0], 0, width*hist[0]+width*hist[1], height], fill=(int(clt.cluster_centers_[1][0]),int(clt.cluster_centers_[1][1]),int(clt.cluster_centers_[1][2])))
+    draw.rectangle([width*hist[0]+width*hist[1], 0, width*hist[0]+width*hist[1]+width*hist[2], height], fill=(int(clt.cluster_centers_[2][0]),int(clt.cluster_centers_[2][1]),int(clt.cluster_centers_[2][2])))
+
+    # make thumbnail
+    im.thumbnail(thumb)
+
+    # save image
+    im.save("output/"+img_input)
+
+    # images = []
+    # images.append(imageio.imread("images/"+img_input))
+    # images.append(imageio.imread("img/"+img_input))
+    # imageio.mimsave('gifs/'+img_input+".gif", images)
+
+
+
+directory = 'images'
+files = list_files(directory, "jpg")
+for f in files:
+    print(f)
+    generateColorImage(f)
+
+
+
+#bar = plot_colors2(hist, clt.cluster_centers_)
+
+#plt.axis("off")
+#plt.imshow(bar)
+#plt.show()
diff --git a/ImageClassificationPython/predict.py b/ImageClassificationPython/predict.py
new file mode 100755
index 0000000..fc5cc79
--- /dev/null
+++ b/ImageClassificationPython/predict.py
@@ -0,0 +1,58 @@
+
+# Part 3 - Making new predictions
+import numpy as np
+from PIL import Image, ImageDraw, ImageFont
+from keras.preprocessing import image
+from keras.models import model_from_yaml
+from keras.preprocessing.image import ImageDataGenerator
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument('images', nargs="*", help="images to classify")
+args = parser.parse_args()
+
+# load YAML and create model
+yaml_file = open('model.yaml', 'r')
+loaded_model_yaml = yaml_file.read()
+yaml_file.close()
+classifier = model_from_yaml(loaded_model_yaml)
+# load weights into new model
+classifier.load_weights("model.h5")
+print("Loaded model from disk")
+
+
+for f in args.images:
+    from keras.preprocessing import image
+    test_image = image.load_img(f, target_size = (64, 64))
+    test_image = image.img_to_array(test_image)
+    test_image = np.expand_dims(test_image, axis = 0)
+    result = classifier.predict(test_image)
+    print(result)
+
+
+
+    #WHAT ARE YOUR CLASSES?
+    if result[0][0] == 1:
+        prediction = 'rect'
+    else:
+        prediction = 'circle'
+
+    print("PREDICTION: {}".format(prediction))
+
+
+    #WRITE RESULT TO IMAGE
+    image = Image.open(f)
+    width, height = image.size
+    size = (width, height+100)
+    layer = Image.new('RGB', size, (255,255,255))
+    layer.paste(image, (0,0))
+
+    draw = ImageDraw.Draw(layer)
+    font = ImageFont.truetype('Roboto-Regular.ttf', size=45)
+    (x, y) = (50, height+20)
+    message = prediction
+    color = 'rgb(0, 0, 0)' # black color
+    draw.text((x, y), message, fill=color, font=font)
+
+
+    layer.save("{}.predicted.png".format(f))
diff --git a/ImageClassificationPython/requirements.txt b/ImageClassificationPython/requirements.txt
new file mode 100644
index 0000000..9fc9fe3
--- /dev/null
+++ b/ImageClassificationPython/requirements.txt
@@ -0,0 +1,11 @@
+h5py==2.8.0
+Keras==2.2.4
+Keras-Applications==1.0.6
+Keras-Preprocessing==1.0.5
+numpy==1.15.2
+Pillow==5.3.0
+protobuf==3.6.1
+PyYAML==3.13
+scipy==1.1.0
+six==1.11.0
+tensorflow==1.0.0
diff --git a/ImageClassificationPython/train.py b/ImageClassificationPython/train.py
new file mode 100755
index 0000000..7518f24
--- /dev/null
+++ b/ImageClassificationPython/train.py
@@ -0,0 +1,78 @@
+# Convolutional Neural Network
+
+# Installing Theano
+# pip install --upgrade --no-deps git+git://github.com/Theano/Theano.git
+
+# Installing Tensorflow
+# pip install tensorflow
+
+# Installing Keras
+# pip install --upgrade keras
+
+# Part 1 - Building the CNN
+
+# Importing the Keras libraries and packages
+
+from keras.models import Sequential
+from keras.layers import Conv2D
+from keras.layers import MaxPooling2D
+from keras.layers import Flatten
+from keras.layers import Dense
+
+# Initialising the CNN
+classifier = Sequential()
+# Step 1 - Convolution
+classifier.add(Conv2D(32, (3, 3), input_shape = (64, 64, 3), activation = 'relu'))
+
+# Step 2 - Pooling
+classifier.add(MaxPooling2D(pool_size = (2, 2)))
+
+# Adding a second convolutional layer
+classifier.add(Conv2D(32, (3, 3), activation = 'relu'))
+classifier.add(MaxPooling2D(pool_size = (2, 2)))
+
+# Step 3 - Flattening
+classifier.add(Flatten())
+
+# Step 4 - Full connection
+classifier.add(Dense(units = 128, activation = 'relu'))
+classifier.add(Dense(units = 1, activation = 'sigmoid'))
+
+# Compiling the CNN
+classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
+
+# Part 2 - Fitting the CNN to the images
+
+from keras.preprocessing.image import ImageDataGenerator
+
+train_datagen = ImageDataGenerator(rescale = 1./255,
+                                   shear_range = 0.2,
+                                   zoom_range = 0.2,
+                                   horizontal_flip = True)
+
+test_datagen = ImageDataGenerator(rescale = 1./255)
+
+training_set = train_datagen.flow_from_directory('dataset/training_set',
+                                                 target_size = (64, 64),
+                                                 batch_size = 32,
+                                                 class_mode = 'binary')
+
+test_set = test_datagen.flow_from_directory('dataset/test_set',
+                                            target_size = (64, 64),
+                                            batch_size = 32,
+                                            class_mode = 'binary')
+
+classifier.fit_generator(training_set,
+                         steps_per_epoch = 500,
+                         epochs = 1,
+                         validation_data = test_set,
+                         validation_steps = 100)
+
+
+# serialize model to YAML
+model_yaml = classifier.to_yaml()
+with open("model.yaml", "w") as yaml_file:
+    yaml_file.write(model_yaml)
+# serialize weights to HDF5
+classifier.save_weights("model.h5")
+print("Saved model to disk")
diff --git a/VanillaJavascriptSimpleNN/NeuralNetwork.js b/VanillaJavascriptSimpleNN/NeuralNetwork.js
new file mode 100755
index 0000000..c8d2667
--- /dev/null
+++ b/VanillaJavascriptSimpleNN/NeuralNetwork.js
@@ -0,0 +1,162 @@
+class NeuralNetwork
+{
+    constructor(numInputs, numOutputs, numHiddenLayers, numNeuronsPerHiddenLayer)
+    {
+
+        this.numInputs = numInputs;
+        this.numOutputs = numOutputs;
+        this.numHiddenLayers = numHiddenLayers;
+        this.numNeuronsPerHiddenLayer = numNeuronsPerHiddenLayer;
+
+        this.bias = 0.0;
+        this.activationResponse = 1.0;
+        this.neuronLayers = [];
+
+        this.createNetwork();
+    }
+
+    createNetwork()
+    {
+
+		//create the layers of the network
+		if (this.numHiddenLayers > 0)
+		{
+			//create first hidden layer
+			var firstHiddenLayer = new NeuronLayer(this.numNeuronsPerHiddenLayer, this.numInputs);
+			this.neuronLayers.push(firstHiddenLayer);
+
+		    for (var i=0; i<this.numHiddenLayers-1; ++i)
+		    {
+		    	var newHiddenLayer = new NeuronLayer(this.numNeuronsPerHiddenLayer, this.numNeuronsPerHiddenLayer);
+				this.neuronLayers.push(newHiddenLayer);
+		    }
+
+		    //create output layer
+		    var outputLayer = new NeuronLayer(this.numOutputs, this.numNeuronsPerHiddenLayer);
+			this.neuronLayers.push(outputLayer);
+		}
+		else
+		{
+			//create output layer
+			var outputLayer = new NeuronLayer(this.numOutputs, this.numInputs);
+			this.neuronLayers.push(outputLayer);
+		}
+	}
+
+	update(inputs)
+	{
+
+		var outputs = [];
+
+		var cWeight = 0;
+
+		// If the number of inputs supplied is incorrect...
+		if (inputs.length!=this.numInputs)
+		{
+			return outputs; // Return empty outputs
+		}
+
+		// Loop through all layers
+		var inputLayer = true;
+		for (var i=0; i < this.numHiddenLayers + 1; ++i)
+		{
+			var neuronLayer = this.neuronLayers[i];
+
+			if (!inputLayer)
+			{
+				inputs = [];
+				inputs = inputs.concat(outputs);
+			}
+			else
+			{
+				inputLayer = false;
+			}
+
+			outputs = [];
+
+			cWeight = 0;
+
+			// For each neuron sum the (inputs * corresponding weights).
+			// Throw the total at our sigmoid function to get the output.
+			for (var j=0; j < neuronLayer.neurons.length; ++j)
+			{
+				var neuron = neuronLayer.neurons[j];
+
+				var totalInput = 0;
+
+				// For each weight...
+				for (var k=0; k < neuron.numInputs ; ++k) // -1 ???
+				{
+					// Multiply it with the input.
+					totalInput += neuron.weights[k] *
+							inputs[cWeight];
+            console.log("cweight "+cWeight);
+            console.log("neuron weight "+neuron.weights[k]);
+            console.log("input: "+inputs[cWeight]);
+            console.log("total input "+totalInput);
+
+
+					cWeight++;
+				}
+
+				// Add in the bias (final weight)
+			//	totalInput += neuron.weights[neuron.weights.length-1] * this.bias;
+
+				// We can store the outputs from each layer as we generate them.
+			    // The combined activation is first filtered through the sigmoid function
+				outputs.push(this.sigmoid(totalInput, this.activationResponse));
+
+				cWeight = 0;
+			}
+		}
+
+		return outputs;
+	}
+
+	sigmoid(totalInput, activationResponse)
+	{
+		return ( 1 / ( 1 + Math.exp(-totalInput / activationResponse)));
+	}
+
+	getWeights()
+	{
+		var weights = [];
+
+		//for each layer
+		for (var i=0; i<this.numHiddenLayers + 1; ++i)
+		{
+
+			//for each neuron
+			for (var j=0; j<this.neuronLayers[i].neurons.length; ++j)
+			{
+				//for each weight
+				for (var k=0; k<this.neuronLayers[i].neurons[j].numInputs; ++k)
+				{
+					weights.push(this.neuronLayers[i].neurons[j].weights[k]);
+				}
+			}
+		}
+
+		return weights;
+	}
+
+	setWeights(weights)
+	{
+		var cWeight = 0;
+
+		//for each layer
+		for (var i=0; i<this.numHiddenLayers + 1; ++i)
+		{
+
+			//for each neuron
+			for (var j=0; j<this.neuronLayers[i].neurons.length; ++j)
+			{
+				//for each weight
+				for (var k=0; k<this.neuronLayers[i].neurons[j].numInputs; ++k)
+				{
+					this.neuronLayers[i].neurons[j].weights[k] = weights[cWeight++];
+				}
+			}
+		}
+	}
+}
diff --git a/VanillaJavascriptSimpleNN/Neuron.js b/VanillaJavascriptSimpleNN/Neuron.js
new file mode 100755
index 0000000..bf52429
--- /dev/null
+++ b/VanillaJavascriptSimpleNN/Neuron.js
@@ -0,0 +1,15 @@
+class Neuron
+{
+	constructor(numInputs)
+	{
+    this.weights = [];
+		this.numInputs = numInputs;
+
+		for (var i=0; i<numInputs+1; ++i)
+		{
+			var newWeight = -1 + (Math.random()*2);
+			//var newWeight = 1;
+			this.weights.push(newWeight);
+		}
+	}
+}
diff --git a/VanillaJavascriptSimpleNN/NeuronLayer.js b/VanillaJavascriptSimpleNN/NeuronLayer.js
new file mode 100755
index 0000000..21bae47
--- /dev/null
+++ b/VanillaJavascriptSimpleNN/NeuronLayer.js
@@ -0,0 +1,14 @@
+class NeuronLayer
+{
+	constructor(numNeuronsPerHiddenLayer, numInputs)
+	{
+        this.neurons = [];
+
+		for (var i = 0; i < numNeuronsPerHiddenLayer; ++i)
+		{
+			var newNeuron = new Neuron(numInputs);
+			
+			this.neurons.push(newNeuron);
+		}
+	}
+}
diff --git a/VanillaJavascriptSimpleNN/index.html b/VanillaJavascriptSimpleNN/index.html
new file mode 100644
index 0000000..be51d84
--- /dev/null
+++ b/VanillaJavascriptSimpleNN/index.html
@@ -0,0 +1,225 @@
+<html>
+<head>
+<script src="NeuralNetwork.js"></script>
+<script src="Neuron.js"></script>
+<script src="NeuronLayer.js"></script>
+
+<style>
+  body{
+    padding:0;
+    margin:0;
+    overflow:hidden;
+    font-family:Helvetica;
+    font-size:10px;
+  }
+  input{
+    padding:0;
+  }
+  p{
+    padding:0;
+    margin:0;
+  }
+
+  #input{
+      position:absolute;
+      top:100px;
+      left:10px;
+  }
+  #first_layer{
+    position:absolute;
+    top: 100px;
+    left: 200px;
+  }
+  #second_layer{
+    position:absolute;
+    top: 100px;
+    left: 400px;
+  }
+  #output{
+    position:absolute;
+    top: 100px;
+    left: 600px;
+  }
+  #network_container{
+    position:absolute;
+    top: 100px;
+    left: 600px;
+    margin-left:-400px;
+    margin-top:-250px;
+  }
+
+</style>
+  </head>
+<body>
+
+  <canvas id="myCanvas" width="100%" height="100%"></canvas>
+<div id="network_container">
+<div id="input">
+
+
+  <input type="range" min="0" max="100" value="1" class="i0" id="i0">
+  <p id="i0_output"></p>
+  <input type="range" min="0" max="100" value="10" class="i1" id="i1">
+  <p id="i1_output"></p>
+</div>
+<div id = "first_layer">
+ <input type="range" min="-400" max="400" value="10" class="w0" id="w0">
+ <p id="w0_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w1" id="w1">
+ <p id="w1_output"></p><br><br>
+ <input type="range" min="-400" max="400" value="10" class="w2" id="w2">
+ <p id="w2_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w3" id="w3">
+ <p id="w3_output"></p><br><br>
+ <input type="range" min="-400" max="400" value="10" class="w4" id="w4">
+ <p id="w4_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w5" id="w5">
+ <p id="w5_output"></p>
+</div>
+<div id = "second_layer">
+ <input type="range" min="-400" max="400" value="10" class="w6" id="w6">
+ <p id="w6_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w7" id="w7">
+ <p id="w7_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w8" id="w8">
+ <p id="w8_output"></p><br><br>
+ <input type="range" min="-400" max="400" value="10" class="w9" id="w9">
+ <p id="w9_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w10" id="w10">
+ <p id="w10_output"></p>
+ <input type="range" min="-400" max="400" value="10" class="w11" id="w11">
+ <p id="w11_output"></p>
+</div>
+
+<div id="output">
+<input id="clickMe" type="button" value="update network" onclick="update();" />
+<input id="random" type="button" value="random network" onclick="random();" />
+
+<p id="network_output"></p>
+</div>
+</div>
+<script>
+
+  var numInputs = 2;
+  var numOutputs = 2;
+  var numHiddenLayers = 1;
+  var numNeuronsPerHiddenLayer = 3;
+
+  var slider = [];
+  var output = [];
+
+  var neuralNetwork = new NeuralNetwork(numInputs, numOutputs, numHiddenLayers, numNeuronsPerHiddenLayer);
+
+
+  var input0 = document.getElementById("i0")
+  var input_display0 = document.getElementById("i0_output")
+  input_display0.innerHTML = input0.value/100;
+  input0.oninput = function() {
+    input_display0.innerHTML = this.value/100;
+  }
+  var input1 = document.getElementById("i1")
+  var input_display1 = document.getElementById("i1_output")
+  input_display1.innerHTML = input1.value/100;
+  input1.oninput = function() {
+    input_display1.innerHTML = this.value/100;
+  }
+
+
+
+
+//slider
+for (var i = 0; i<12; i++){
+  slider.push(document.getElementById("w"+i));
+  output.push(document.getElementById("w"+i+"_output"));
+  output[i].innerHTML = slider[i].value/100;
+  slider[i].oninput = function() {
+    output[slider.indexOf(this)].innerHTML = this.value/100;
+
+  updateCanvas()
+
+  }
+}
+
+document.addEventListener('mousemove', function(e) {
+  console.log("move")
+  var x = e.clientX / window.innerWidth;
+  var y = e.clientY / window.innerHeight;
+input0.value=x*100;
+input1.value=y*100;
+input_display0.innerHTML = x;
+input_display1.innerHTML = y;
+update([x,y])
+})
+
+
+//CANVAS STUFF
+var c = document.getElementById("myCanvas");
+var ctx = c.getContext("2d");
+ctx.canvas.width  = window.innerWidth;
+ctx.canvas.height = window.innerHeight;
+var stepsize = 50;
+for(var x = 0; x < window.innerWidth; x = x+stepsize){
+  for(var y = 0; y < window.innerHeight; y = y+stepsize){
+    var outputs = neuralNetwork.update([x/window.innerWidth,y/window.innerHeight]);
+    ctx.fillStyle = 'hsl(' + 360 * outputs[0] + ', 50%,'+outputs[1]*100 +'%)';
+    //ctx.fillStyle= "rgb(255,20,255);"
+    console.log(outputs[1]*255)
+    ctx.fillRect(x,y,stepsize,stepsize);
+  }
+}
+
+
+function updateCanvas(){
+
+  var stepsize = 50;
+  for(var x = 0; x < window.innerWidth; x = x+stepsize){
+    for(var y = 0; y < window.innerHeight; y = y+stepsize){
+      var outputs = neuralNetwork.update([x/window.innerWidth,y/window.innerHeight]);
+      ctx.fillStyle = 'hsl(' + 360 * outputs[0] + ', 90%,'+outputs[1]*100+'%)';
+      //ctx.fillStyle= "rgb(255,20,255);"
+      console.log(outputs[1]*255)
+      ctx.fillRect(x,y,stepsize,stepsize);
+    }
+  }
+
+}
+
+
+function update(inputs){
+
+
+var weights = neuralNetwork.getWeights();
+var newWeights = [];
+for (var i=0; i < weights.length; i++) {
+    newWeights.push(slider[i].value/100);
+    //newWeights.push(1);
+}
+  neuralNetwork.setWeights(newWeights);
+
+
+//var inputs = [input0.value/100, input1.value/100];
+  var outputs = neuralNetwork.update(inputs);
+  //  console.log(neuralNetwork.getWeights());
+  var output_display = document.getElementById("network_output")
+  output_display.innerHTML = "<br> "+outputs[0] + "<br><br> "+outputs [1];
+
+document.getElementById('network_container').style.left=outputs[0]*window.innerWidth;
+document.getElementById('network_container').style.top=outputs[1]*window.innerHeight;
+
+}
+
+random()
+function random(inputs){
+
+for (var i = 0; i<slider.length; i++){
+
+  slider[i].value = Math.random()*800-400;
+output[slider.indexOf(slider[i])].innerHTML = slider[i].value/100;
+}
+updateCanvas();
+}
+
+
+</script>
+</body>
+</html>
diff --git a/VanillaJavascriptVisualisation/index.html b/VanillaJavascriptVisualisation/index.html
new file mode 100644
index 0000000..b444bda
--- /dev/null
+++ b/VanillaJavascriptVisualisation/index.html
@@ -0,0 +1,198 @@
+
+<html>
+<head>
+  <title>neural network art</title>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=320, initial-scale=1.0, maximum-scale=1.0, user-scalable=0"/>
+    <meta name="apple-mobile-web-app-capable" content="yes" />
+    <meta http-equiv="X-UA-Compatible" content="IE=edge">
+    <meta name="mobile-web-app-capable" content="yes">
+    <meta name="description" content="ōtoro.net">
+    <meta name="author" content="hardmaru">
+
+
+    <!-- extra styles -->
+    <style>
+    head {
+      margin: 0;
+      padding: 0;
+    }
+    body {
+      margin: 0;
+      padding: 0;
+    }
+    p {
+      padding: 10px;
+      font-family: Courier, "Helvetica Neue",Helvetica,Arial,sans-serif;
+      font-weight: 100;
+      font-size: 0.6em;
+    }
+    textarea {
+      padding: 5;
+      font-family: Courier, "Helvetica Neue",Helvetica,Arial,sans-serif;
+      font-weight: 100;
+      font-size: 0.5em;
+    }
+    </style>
+
+</head>
+<body>
+
+    <div id="p5Container">
+    </div>
+
+  <!-- jQuery -->
+  <script src="http://ajax.googleapis.com/ajax/libs/jquery/1.8.3/jquery.min.js"></script>
+
+  <script src="lib/p5.min.js"></script>
+
+  <script src="lib/recurrent.js"></script>
+
+  <script>
+  // neural network random art generator
+
+  // settings
+
+  // actual size of generated image
+  var sizeh  = 300;
+  var sizew = 300;
+  var sizeImage = sizeh*sizew;
+
+  var nH, nW, nImage;
+  var mask;
+
+  // settings of nnet:
+  var networkSize = 8;
+  var nHidden = 10;
+  var nOut = 3; // r, g, b layers
+
+  // support variables:
+  var img;
+  var img2;
+  var G = new R.Graph(false);
+
+  var initModel = function() {
+    "use strict";
+
+    var model = [];
+    var i;
+
+    var randomSize = 1.0;
+
+    // define the model below:
+    model.w_in = R.RandMat(networkSize, 3, 0, randomSize); // x, y, and bias
+
+  //  model['w_0'] = R.RandMat(networkSize, networkSize, 0, randomSize);
+
+    for (i = 0; i < nHidden; i++) {
+      model['w_'+i] = R.RandMat(networkSize, networkSize, 0, randomSize);
+    }
+    model.w_out = R.RandMat(nOut, networkSize, 0, randomSize); // output layer
+
+    console.log(model)
+
+    return model;
+  };
+
+
+  var forwardNetwork = function(G, model, x_, y_) {
+    // x_, y_ is a normal javascript float, will be converted to a mat object below
+    // G is a graph to amend ops to
+    var x = new R.Mat(3, 1); // input
+    var i;
+    x.set(0, 0, x_);
+    x.set(1, 0, y_);
+    x.set(2, 0, 1.0); // bias.
+    var out;
+    out = G.tanh(G.mul(model.w_in, x));
+    for (i = 0; i < nHidden; i++) {
+      out = G.tanh(G.mul(model['w_'+i], out));
+    }
+    out = G.sigmoid(G.mul(model.w_out, out));
+    console.log(out)
+    return out;
+  };
+
+  function getColorAt(model, x, y) {
+    // function that returns a color given coordintes (x, y)
+    // (x, y) are scaled to -0.5 -> 0.5 for image recognition later
+    // but it can be behond the +/- 0.5 for generation above and beyond
+    // recognition limits
+    var r, g, b;
+    var out = forwardNetwork(G, model, x, y);
+
+    r = out.w[0]*255.0;
+    g = out.w[1]*255.0;
+    b = out.w[2]*255.0;
+
+    return color(r, g, b);
+  }
+
+  function genImage(img, model) {
+    var i, j, m, n;
+    img.loadPixels();
+    for (i = 0, m=img.width; i < m; i++) {
+      for (j = 0, n=img.height; j < n; j++) {
+        img.set(i, j, getColorAt(model, i/sizeh-0.5,j/sizew-0.5));
+      }
+    }
+    img.updatePixels();
+  }
+
+  function setup() {
+
+    "use strict";
+    var myCanvas;
+
+    myCanvas = createCanvas(windowWidth,windowHeight);
+
+    myCanvas.parent('p5Container');
+
+    nW = Math.max(Math.floor(windowWidth/sizew), 1);
+    nH = Math.max(Math.floor(windowHeight/sizeh), 1);
+    nImage = nH*nW;
+    mask = R.zeros(nImage);
+
+    //img.resize(320*1.0, 320*1.0);
+    //img.save('genart.png','png');
+    //noLoop();
+    img = createImage(sizeh, sizew);
+
+    frameRate(30);
+  }
+
+  function getRandomLocation() {
+    var i, result=0, r;
+    for (i=0;i<nImage;i++) {
+      result += mask[i];
+    }
+    if (result === nImage) {
+      mask = R.zeros(nImage);
+    }
+    do {
+      r = R.randi(0, nImage);
+    } while (mask[r] !== 0);
+    mask[r] = 1;
+    return r;
+  }
+
+  function displayImage(n) {
+    var row = Math.floor(n/nW);
+    var col = n % nW;
+    image(img, col*sizew, row*sizeh);
+  }
+
+  function draw() {
+
+    model = initModel();
+    genImage(img, model);
+    displayImage(getRandomLocation());
+
+  }
+
+
+  </script>
+
+
+</body>
+</html>
diff --git a/VanillaJavascriptVisualisation/lib/p5.min.js b/VanillaJavascriptVisualisation/lib/p5.min.js
new file mode 100644
index 0000000..7a2f819
--- /dev/null
+++ b/VanillaJavascriptVisualisation/lib/p5.min.js
@@ -0,0 +1,5 @@
+/*! p5.min.js v0.3.15 December 23, 2014 */
+
+var shim=function(){window.requestDraw=function(){return window.requestAnimationFrame||window.webkitRequestAnimationFrame||window.mozRequestAnimationFrame||window.oRequestAnimationFrame||window.msRequestAnimationFrame||function(t){window.setTimeout(t,1e3/60)}}()}({}),constants=function(){var t=Math.PI;return{ARROW:"default",CROSS:"crosshair",HAND:"pointer",MOVE:"move",TEXT:"text",WAIT:"wait",HALF_PI:t/2,PI:t,QUARTER_PI:t/4,TAU:2*t,TWO_PI:2*t,DEGREES:"degrees",RADIANS:"radians",CORNER:"corner",CORNERS:"corners",RADIUS:"radius",RIGHT:"right",LEFT:"left",CENTER:"center",POINTS:"points",LINES:"lines",TRIANGLES:"triangles",TRIANGLE_FAN:"triangles_fan",TRIANGLE_STRIP:"triangles_strip",QUADS:"quads",QUAD_STRIP:"quad_strip",CLOSE:"close",OPEN:"open",CHORD:"chord",PIE:"pie",PROJECT:"square",SQUARE:"butt",ROUND:"round",BEVEL:"bevel",MITER:"miter",RGB:"rgb",HSB:"hsb",AUTO:"auto",ALT:18,BACKSPACE:8,CONTROL:17,DELETE:46,DOWN_ARROW:40,ENTER:13,ESCAPE:27,LEFT_ARROW:37,OPTION:18,RETURN:13,RIGHT_ARROW:39,SHIFT:16,TAB:9,UP_ARROW:38,BLEND:"normal",ADD:"lighter",DARKEST:"darken",LIGHTEST:"lighten",DIFFERENCE:"difference",EXCLUSION:"exclusion",MULTIPLY:"multiply",SCREEN:"screen",REPLACE:"source-over",OVERLAY:"overlay",HARD_LIGHT:"hard-light",SOFT_LIGHT:"soft-light",DODGE:"color-dodge",BURN:"color-burn",NORMAL:"normal",ITALIC:"italic",BOLD:"bold",LINEAR:"linear",QUADRATIC:"quadratic",BEZIER:"bezier",CURVE:"curve"}}({}),core=function(t,e,r){"use strict";var r=r,o=function(t,e){this._setupDone=!1,this._pixelDensity=window.devicePixelRatio||1,this._startTime=(new Date).getTime(),this._userNode=e,this._curElement=null,this._elements=[],this._preloadCount=0,this._updateInterval=0,this._isGlobal=!1,this._loop=!0,this._styles=[],this._defaultCanvasSize={width:100,height:100},this._events={mousemove:null,mousedown:null,mouseup:null,click:null,mousewheel:null,mouseover:null,mouseout:null,keydown:null,keyup:null,keypress:null,touchstart:null,touchmove:null,touchend:null,resize:null,blur:null},this._loadingScreenId="p5_loading",this._start=function(){if(this._userNode&&"string"==typeof this._userNode&&(this._userNode=document.getElementById(this._userNode)),this._loadingScreen=document.getElementById(this._loadingScreenId),!this._loadingScreen){this._loadingScreen=document.createElement("loadingDiv"),this._loadingScreen.innerHTML="loading...",this._loadingScreen.style.position="absolute";var t=this._userNode||document.body;t.appendChild(this._loadingScreen)}this.createCanvas(this._defaultCanvasSize.width,this._defaultCanvasSize.height,!0);var e=this.preload||window.preload,r=this._isGlobal?window:this;e?(this._preloadMethods.forEach(function(t){r[t]=function(e){return r._preload(t,e)}}),e(),0===this._preloadCount&&(this._setup(),this._runFrames(),this._draw())):(this._setup(),this._runFrames(),this._draw())}.bind(this),this._preload=function(t,e){var r=this._isGlobal?window:this;return r._setProperty("_preloadCount",r._preloadCount+1),o.prototype[t].call(r,e,function(){r._setProperty("_preloadCount",r._preloadCount-1),0===r._preloadCount&&(r._setup(),r._runFrames(),r._draw())})}.bind(this),this._setup=function(){var t=this._isGlobal?window:this;"function"==typeof t.preload&&this._preloadMethods.forEach(function(e){t[e]=o.prototype[e]}),"function"==typeof t.setup&&t.setup(),this.canvas.style.visibility="",this.canvas.className=this.canvas.className.replace("p5_hidden",""),this._setupDone=!0,this._loadingScreen.parentNode.removeChild(this._loadingScreen)}.bind(this),this._draw=function(){var t=this.setup||window.setup,e=(new Date).getTime();this._frameRate=1e3/(e-this._lastFrameTime),this._lastFrameTime=e;var r=this.draw||window.draw;this._loop&&(this._drawInterval&&clearInterval(this._drawInterval),this._drawInterval=setTimeout(function(){window.requestDraw(this._draw.bind(this))}.bind(this),1e3/this._targetFrameRate)),"function"==typeof r&&(this.push(),"undefined"==typeof t&&this.scale(this._pixelDensity,this._pixelDensity),this._registeredMethods.pre.forEach(function(t){t.call(this)}),r(),this._registeredMethods.post.forEach(function(t){t.call(this)}),this.pop()),this._updatePMouseCoords(),this._updatePTouchCoords()}.bind(this),this._runFrames=function(){this._updateInterval&&clearInterval(this._updateInterval),this._updateInterval=setInterval(function(){this._setProperty("frameCount",this.frameCount+1)}.bind(this),1e3/this._targetFrameRate)}.bind(this),this._setProperty=function(t,e){this[t]=e,this._isGlobal&&(window[t]=e)}.bind(this),this.remove=function(){if(this._curElement){this._loop=!1,this._drawInterval&&clearTimeout(this._drawInterval),this._updateInterval&&clearTimeout(this._updateInterval);for(var t in this._events)window.removeEventListener(t,this._events[t]);for(var e=0;e<this._elements.length;e++){var r=this._elements[e];r.elt.parentNode&&r.elt.parentNode.removeChild(r.elt);for(var n in r._events)r.elt.removeEventListener(n,r._events[n])}var i=this;if(this._registeredMethods.remove.forEach(function(t){"undefined"!=typeof t&&t.call(i)}),this._isGlobal){for(var s in o.prototype)try{delete window[s]}catch(a){window[s]=void 0}for(var h in this)if(this.hasOwnProperty(h))try{delete window[h]}catch(a){window[h]=void 0}}}}.bind(this);for(var n in r)o.prototype[n]=r[n];if(t)t(this);else{this._isGlobal=!0;for(var i in o.prototype)if("function"==typeof o.prototype[i]){var s=i.substring(2);this._events.hasOwnProperty(s)||(window[i]=o.prototype[i].bind(this))}else window[i]=o.prototype[i];for(var a in this)this.hasOwnProperty(a)&&(window[a]=this[a])}for(var h in this._events){var p=this["on"+h];if(p){var u=p.bind(this);window.addEventListener(h,u),this._events[h]=u}}var l=this;window.addEventListener("focus",function(){l._setProperty("focused",!0)}),window.addEventListener("blur",function(){l._setProperty("focused",!1)}),"complete"===document.readyState?this._start():window.addEventListener("load",this._start.bind(this),!1)};return o.prototype._preloadMethods=["loadJSON","loadImage","loadStrings","loadXML","loadShape","loadTable"],o.prototype._registeredMethods={pre:[],post:[],remove:[]},o.prototype.registerPreloadMethod=function(t){o.prototype._preloadMethods.push(t)}.bind(this),o.prototype.registerMethod=function(t,e){o.prototype._registeredMethods.hasOwnProperty(t)||(o.prototype._registeredMethods[t]=[]),o.prototype._registeredMethods[t].push(e)}.bind(this),o}({},shim,constants),p5Color=function(t,e,r){var o=e,r=r;return o.Color=function(t,e){if(e instanceof Array)this.rgba=e;else{var n=o.Color._getFormattedColor.apply(t,e);t._colorMode===r.HSB?(this.hsba=n,this.rgba=o.Color._getRGB(n)):this.rgba=n}var i=o.Color._normalizeColorArray.call(t,this.rgba);return this.colorString=o.Color._getColorString(i),this},o.Color._getFormattedColor=function(){if(arguments[0]instanceof Array)return o.Color.getNormalizedColor.apply(this,arguments[0]);var t,e,n,i;return arguments.length>=3?(t=arguments[0],e=arguments[1],n=arguments[2],i="number"==typeof arguments[3]?arguments[3]:255):(this._colorMode===r.RGB?t=e=n=arguments[0]:(t=n=arguments[0],e=0),i="number"==typeof arguments[1]?arguments[1]:255),[t,e,n,i]},o.Color._normalizeColorArray=function(t){var e=this._colorMode===r.RGB,o=e?this._maxRGB:this._maxHSB;return t[0]*=255/o[0],t[1]*=255/o[1],t[2]*=255/o[2],t[3]*=255/o[3],t},o.Color._getRGB=function(t){var e=t[0],r=t[1],o=t[2];e/=255,r/=255,o/=255;var n=[];if(0===r)n=[Math.round(255*o),Math.round(255*o),Math.round(255*o),t[3]];else{var i=6*e;6===i&&(i=0);var s,a,h,p=Math.floor(i),u=o*(1-r),l=o*(1-r*(i-p)),c=o*(1-r*(1-(i-p)));0===p?(s=o,a=c,h=u):1===p?(s=l,a=o,h=u):2===p?(s=u,a=o,h=c):3===p?(s=u,a=l,h=o):4===p?(s=c,a=u,h=o):(s=o,a=u,h=l),n=[Math.round(255*s),Math.round(255*a),Math.round(255*h),t[3]]}return n},o.Color._getHSB=function(t){var e,r,o=t[0]/255,n=t[1]/255,i=t[2]/255,s=Math.min(o,n,i),a=Math.max(o,n,i),h=a-s,p=a;if(0===h)e=0,r=0;else{r=h/a;var u=((a-o)/6+h/2)/h,l=((a-n)/6+h/2)/h,c=((a-i)/6+h/2)/h;o===a?e=c-l:n===a?e=1/3+u-c:i===a&&(e=2/3+l-u),0>e&&(e+=1),e>1&&(e-=1)}return[Math.round(255*e),Math.round(255*r),Math.round(255*p),t[3]]},o.Color._getColorString=function(t){for(var e=0;3>e;e++)t[e]=Math.floor(t[e]);var r="undefined"!=typeof t[3]?t[3]/255:1;return"rgba("+t[0]+","+t[1]+","+t[2]+","+r+")"},o.Color._getCanvasColor=function(){if(arguments[0]instanceof o.Color){if(1===arguments.length)return arguments[0].colorString;var t=arguments[0].rgba;return t[3]=arguments[1],t=o.Color._normalizeColorArray.call(this,t),o.Color._getColorString(t)}if(arguments[0]instanceof Array){if(1===arguments.length)return o.Color._getColorString(arguments[0]);var e=this._colorMode===r.RGB,n=e?this._maxRGB[3]:this._maxHSB[3];return arguments[0][3]=255*arguments[1]/n,o.Color._getColorString(arguments[0])}var i=o.Color._getFormattedColor.apply(this,arguments);return i=o.Color._normalizeColorArray.call(this,i),this._colorMode===r.HSB&&(i=o.Color._getRGB(i)),o.Color._getColorString(i)},o.Color}({},core,constants),p5Element=function(t,e){function r(t,e,r){var o=e.bind(r);r.elt.addEventListener(t,o,!1),r._events[t]=o}var o=e;return o.Element=function(t,e){this.elt=t,this._pInst=e,this._events={},this.width=this.elt.offsetWidth,this.height=this.elt.offsetHeight},o.Element.prototype.parent=function(t){return"string"==typeof t?t=document.getElementById(t):t instanceof o.Element&&(t=t.elt),t.appendChild(this.elt),this},o.Element.prototype.id=function(t){return this.elt.id=t,this},o.Element.prototype.class=function(t){return this.elt.className+=" "+t,this},o.Element.prototype.mousePressed=function(t){return r("mousedown",t,this),r("touchstart",t,this),this},o.Element.prototype.mouseWheel=function(t){return r("mousewheel",t,this),this},o.Element.prototype.mouseReleased=function(t){return r("mouseup",t,this),r("touchend",t,this),this},o.Element.prototype.mouseClicked=function(t){return r("click",t,this),this},o.Element.prototype.mouseMoved=function(t){return r("mousemove",t,this),r("touchmove",t,this),this},o.Element.prototype.mouseOver=function(t){return r("mouseover",t,this),this},o.Element.prototype.mouseOut=function(t){return r("mouseout",t,this),this},o.Element.prototype.touchStarted=function(t){return r("touchstart",t,this),r("mousedown",t,this),this},o.Element.prototype.touchMoved=function(t){return r("touchmove",t,this),r("mousemove",t,this),this},o.Element.prototype.touchEnded=function(t){return r("touchend",t,this),r("mouseup",t,this),this},o.Element.prototype._setProperty=function(t,e){this[t]=e},o.Element}({},core),p5Graphics=function(t,e,r){var o=e,r=r;return o.Graphics=function(t,e,r){o.Element.call(this,t,e),this.canvas=t,this.drawingContext=this.canvas.getContext("2d"),this._pInst=e,r?(this._isMainCanvas=!0,this._pInst._setProperty("_curElement",this),this._pInst._setProperty("canvas",this.canvas),this._pInst._setProperty("drawingContext",this.drawingContext),this._pInst._setProperty("width",this.width),this._pInst._setProperty("height",this.height)):(this.canvas.style.display="none",this._styles=[])},o.Graphics.prototype=Object.create(o.Element.prototype),o.Graphics.prototype._applyDefaults=function(){this.drawingContext.fillStyle="#FFFFFF",this.drawingContext.strokeStyle="#000000",this.drawingContext.lineCap=r.ROUND,this.drawingContext.font="normal 12px sans-serif"},o.Graphics.prototype.resize=function(t,e){this.width=t,this.height=e,this.elt.width=t*this._pInst._pixelDensity,this.elt.height=e*this._pInst._pixelDensity,this.elt.style.width=t+"px",this.elt.style.height=e+"px",this._isMainCanvas&&(this._pInst._setProperty("width",this.width),this._pInst._setProperty("height",this.height)),this.drawingContext.scale(this._pInst._pixelDensity,this._pInst._pixelDensity)},o.Graphics}({},core,constants),filters=function(){"use strict";function t(t){var e=3.5*t|0;if(e=1>e?1:248>e?e:248,o!==e){o=e,n=1+o<<1,i=new Int32Array(n),s=new Array(n);for(var r=0;n>r;r++)s[r]=new Int32Array(256);for(var a,h,p,u,l=1,c=e-1;e>l;l++){i[e+l]=i[c]=h=c*c,p=s[e+l],u=s[c--];for(var d=0;256>d;d++)p[d]=u[d]=h*d}a=i[e]=e*e,p=s[e];for(var f=0;256>f;f++)p[f]=a*f}}function e(e,a){for(var h=r._toPixels(e),p=e.width,u=e.height,l=p*u,c=new Int32Array(l),d=0;l>d;d++)c[d]=r._getARGB(h,d);var f,g,y,m,w,v,_,x,C,b,S=new Int32Array(l),R=new Int32Array(l),T=new Int32Array(l),E=new Int32Array(l),M=0;t(a);var P,A,I,D;for(A=0;u>A;A++){for(P=0;p>P;P++){if(m=y=g=w=f=0,v=P-o,0>v)b=-v,v=0;else{if(v>=p)break;b=0}for(I=b;n>I&&!(v>=p);I++){var k=c[v+M];D=s[I],w+=D[(-16777216&k)>>>24],g+=D[(16711680&k)>>16],y+=D[(65280&k)>>8],m+=D[255&k],f+=i[I],v++}_=M+P,S[_]=w/f,R[_]=g/f,T[_]=y/f,E[_]=m/f}M+=p}for(M=0,x=-o,C=x*p,A=0;u>A;A++){for(P=0;p>P;P++){if(m=y=g=w=f=0,0>x)b=_=-x,v=P;else{if(x>=u)break;b=0,_=x,v=P+C}for(I=b;n>I&&!(_>=u);I++)D=s[I],w+=D[S[v]],g+=D[R[v]],y+=D[T[v]],m+=D[E[v]],f+=i[I],_++,v+=p;c[P+M]=w/f<<24|g/f<<16|y/f<<8|m/f}M+=p,C+=p,x++}r._setPixels(h,c)}var r={};r._toPixels=function(t){return t instanceof ImageData?t.data:t.getContext("2d").getImageData(0,0,t.width,t.height).data},r._getARGB=function(t,e){var r=4*e;return t[r+3]<<24&4278190080|t[r]<<16&16711680|t[r+1]<<8&65280|255&t[r+2]},r._setPixels=function(t,e){for(var r=0,o=0,n=t.length;n>o;o++)r=4*o,t[r+0]=(16711680&e[o])>>>16,t[r+1]=(65280&e[o])>>>8,t[r+2]=255&e[o],t[r+3]=(4278190080&e[o])>>>24},r._toImageData=function(t){return t instanceof ImageData?t:t.getContext("2d").getImageData(0,0,t.width,t.height)},r._createImageData=function(t,e){return r._tmpCanvas=document.createElement("canvas"),r._tmpCtx=r._tmpCanvas.getContext("2d"),this._tmpCtx.createImageData(t,e)},r.apply=function(t,e,r){var o=t.getContext("2d"),n=o.getImageData(0,0,t.width,t.height),i=e(n,r);i instanceof ImageData?o.putImageData(i,0,0,0,0,t.width,t.height):o.putImageData(n,0,0,0,0,t.width,t.height)},r.threshold=function(t,e){var o=r._toPixels(t);void 0===e&&(e=.5);for(var n=Math.floor(255*e),i=0;i<o.length;i+=4){var s,a=o[i],h=o[i+1],p=o[i+2],u=.2126*a+.7152*h+.0722*p;s=u>=n?255:0,o[i]=o[i+1]=o[i+2]=s}},r.gray=function(t){for(var e=r._toPixels(t),o=0;o<e.length;o+=4){var n=e[o],i=e[o+1],s=e[o+2],a=.2126*n+.7152*i+.0722*s;e[o]=e[o+1]=e[o+2]=a}},r.opaque=function(t){for(var e=r._toPixels(t),o=0;o<e.length;o+=4)e[o+3]=255;return e},r.invert=function(t){for(var e=r._toPixels(t),o=0;o<e.length;o+=4)e[o]=255-e[o],e[o+1]=255-e[o+1],e[o+2]=255-e[o+2]},r.posterize=function(t,e){var o=r._toPixels(t);if(2>e||e>255)throw new Error("Level must be greater than 2 and less than 255 for posterize");for(var n=e-1,i=0;i<o.length;i+=4){var s=o[i],a=o[i+1],h=o[i+2];o[i]=255*(s*e>>8)/n,o[i+1]=255*(a*e>>8)/n,o[i+2]=255*(h*e>>8)/n}},r.dilate=function(t){for(var e,o,n,i,s,a,h,p,u,l,c,d,f,g,y,m,w,v=r._toPixels(t),_=0,x=v.length?v.length/4:0,C=new Int32Array(x);x>_;)for(e=_,o=_+t.width;o>_;)n=i=r._getARGB(v,_),h=_-1,a=_+1,p=_-t.width,u=_+t.width,e>h&&(h=_),a>=o&&(a=_),0>p&&(p=0),u>=x&&(u=_),d=r._getARGB(v,p),c=r._getARGB(v,h),f=r._getARGB(v,u),l=r._getARGB(v,a),s=77*(n>>16&255)+151*(n>>8&255)+28*(255&n),y=77*(c>>16&255)+151*(c>>8&255)+28*(255&c),g=77*(l>>16&255)+151*(l>>8&255)+28*(255&l),m=77*(d>>16&255)+151*(d>>8&255)+28*(255&d),w=77*(f>>16&255)+151*(f>>8&255)+28*(255&f),y>s&&(i=c,s=y),g>s&&(i=l,s=g),m>s&&(i=d,s=m),w>s&&(i=f,s=w),C[_++]=i;r._setPixels(v,C)},r.erode=function(t){for(var e,o,n,i,s,a,h,p,u,l,c,d,f,g,y,m,w,v=r._toPixels(t),_=0,x=v.length?v.length/4:0,C=new Int32Array(x);x>_;)for(e=_,o=_+t.width;o>_;)n=i=r._getARGB(v,_),h=_-1,a=_+1,p=_-t.width,u=_+t.width,e>h&&(h=_),a>=o&&(a=_),0>p&&(p=0),u>=x&&(u=_),d=r._getARGB(v,p),c=r._getARGB(v,h),f=r._getARGB(v,u),l=r._getARGB(v,a),s=77*(n>>16&255)+151*(n>>8&255)+28*(255&n),y=77*(c>>16&255)+151*(c>>8&255)+28*(255&c),g=77*(l>>16&255)+151*(l>>8&255)+28*(255&l),m=77*(d>>16&255)+151*(d>>8&255)+28*(255&d),w=77*(f>>16&255)+151*(f>>8&255)+28*(255&f),s>y&&(i=c,s=y),s>g&&(i=l,s=g),s>m&&(i=d,s=m),s>w&&(i=f,s=w),C[_++]=i;r._setPixels(v,C)};var o,n,i,s;return r.blur=function(t,r){e(t,r)},r}({}),p5Image=function(t,e,r){"use strict";var o=e,n=r;return o.Image=function(t,e){this.width=t,this.height=e,this.canvas=document.createElement("canvas"),this.canvas.width=this.width,this.canvas.height=this.height,this.drawingContext=this.canvas.getContext("2d"),this.pixels=[]},o.Image.prototype._setProperty=function(t,e){this[t]=e},o.Image.prototype.loadPixels=function(){o.prototype.loadPixels.call(this)},o.Image.prototype.updatePixels=function(t,e,r,n){o.prototype.updatePixels.call(this,t,e,r,n)},o.Image.prototype.get=function(t,e,r,n){return o.prototype.get.call(this,t,e,r,n)},o.Image.prototype.set=function(t,e,r){o.prototype.set.call(this,t,e,r)},o.Image.prototype.resize=function(t,e){t=t||this.canvas.width,e=e||this.canvas.height;var r=document.createElement("canvas");r.width=t,r.height=e,r.getContext("2d").drawImage(this.canvas,0,0,this.canvas.width,this.canvas.height,0,0,r.width,r.height),this.canvas.width=this.width=t,this.canvas.height=this.height=e,this.drawingContext.drawImage(r,0,0,t,e,0,0,t,e),this.pixels.length>0&&this.loadPixels()},o.Image.prototype.copy=function(){o.prototype.copy.apply(this,arguments)},o.Image.prototype.mask=function(t){void 0===t&&(t=this);var e=this.drawingContext.globalCompositeOperation,r=1;t instanceof o.Graphics&&(r=t._pInst._pixelDensity);var n=[t,0,0,r*t.width,r*t.height,0,0,this.width,this.height];this.drawingContext.globalCompositeOperation="destination-out",this.copy.apply(this,n),this.drawingContext.globalCompositeOperation=e},o.Image.prototype.filter=function(t,e){n.apply(this.canvas,n[t.toLowerCase()],e)},o.Image.prototype.blend=function(){o.prototype.blend.apply(this,arguments)},o.Image.prototype.save=function(t,e){var r;if(e)switch(e.toLowerCase()){case"png":r="image/png";break;case"jpeg":r="image/jpeg";break;case"jpg":r="image/jpeg";break;default:r="image/png"}else e="png",r="image/png";var n="image/octet-stream",i=this.canvas.toDataURL(r);i=i.replace(r,n),o.prototype.downloadFile(i,t,e)},o.Image}({},core,filters),polargeometry=function(){return{degreesToRadians:function(t){return 2*Math.PI*t/360},radiansToDegrees:function(t){return 360*t/(2*Math.PI)}}}({}),p5Vector=function(t,e,r,o){"use strict";var n=e,i=r,o=o;return n.Vector=function(){var t,e,r;arguments[0]instanceof n?(this.p5=arguments[0],t=arguments[1][0]||0,e=arguments[1][1]||0,r=arguments[1][2]||0):(t=arguments[0]||0,e=arguments[1]||0,r=arguments[2]||0),this.x=t,this.y=e,this.z=r},n.Vector.prototype.set=function(t,e,r){return t instanceof n.Vector?(this.x=t.x||0,this.y=t.y||0,this.z=t.z||0,this):t instanceof Array?(this.x=t[0]||0,this.y=t[1]||0,this.z=t[2]||0,this):(this.x=t||0,this.y=e||0,this.z=r||0,this)},n.Vector.prototype.get=function(){return this.p5?new n.Vector(this.p5,[this.x,this.y,this.z]):new n.Vector(this.x,this.y,this.z)},n.Vector.prototype.add=function(t,e,r){return t instanceof n.Vector?(this.x+=t.x||0,this.y+=t.y||0,this.z+=t.z||0,this):t instanceof Array?(this.x+=t[0]||0,this.y+=t[1]||0,this.z+=t[2]||0,this):(this.x+=t||0,this.y+=e||0,this.z+=r||0,this)},n.Vector.prototype.sub=function(t,e,r){return t instanceof n.Vector?(this.x-=t.x||0,this.y-=t.y||0,this.z-=t.z||0,this):t instanceof Array?(this.x-=t[0]||0,this.y-=t[1]||0,this.z-=t[2]||0,this):(this.x-=t||0,this.y-=e||0,this.z-=r||0,this)},n.Vector.prototype.mult=function(t){return this.x*=t||0,this.y*=t||0,this.z*=t||0,this},n.Vector.prototype.div=function(t){return this.x/=t,this.y/=t,this.z/=t,this},n.Vector.prototype.mag=function(){return Math.sqrt(this.magSq())},n.Vector.prototype.magSq=function(){var t=this.x,e=this.y,r=this.z;return t*t+e*e+r*r},n.Vector.prototype.dot=function(t,e,r){return t instanceof n.Vector?this.dot(t.x,t.y,t.z):this.x*(t||0)+this.y*(e||0)+this.z*(r||0)},n.Vector.prototype.cross=function(t){var e=this.y*t.z-this.z*t.y,r=this.z*t.x-this.x*t.z,o=this.x*t.y-this.y*t.x;return this.p5?new n.Vector(this.p5,[e,r,o]):new n.Vector(e,r,o)},n.Vector.prototype.dist=function(t){var e=t.get().sub(this);return e.mag()},n.Vector.prototype.normalize=function(){return this.div(this.mag())},n.Vector.prototype.limit=function(t){var e=this.magSq();return e>t*t&&(this.div(Math.sqrt(e)),this.mult(t)),this},n.Vector.prototype.setMag=function(t){return this.normalize().mult(t)},n.Vector.prototype.heading=function(){var t=Math.atan2(this.y,this.x);return this.p5?this.p5._angleMode===o.RADIANS?t:i.radiansToDegrees(t):t},n.Vector.prototype.rotate=function(t){this.p5&&this.p5._angleMode===o.DEGREES&&(t=i.degreesToRadians(t));var e=this.heading()+t,r=this.mag();return this.x=Math.cos(e)*r,this.y=Math.sin(e)*r,this},n.Vector.prototype.lerp=function(t,e,r,o){return t instanceof n.Vector?this.lerp(t.x,t.y,t.z,e):(this.x+=(t-this.x)*o||0,this.y+=(e-this.y)*o||0,this.z+=(r-this.z)*o||0,this)},n.Vector.prototype.array=function(){return[this.x||0,this.y||0,this.z||0]},n.Vector.fromAngle=function(t){return this.p5&&this.p5._angleMode===o.DEGREES&&(t=i.degreesToRadians(t)),this.p5?new n.Vector(this.p5,[Math.cos(t),Math.sin(t),0]):new n.Vector(Math.cos(t),Math.sin(t),0)},n.Vector.random2D=function(){var t;return t=this.p5?this.p5.random(this.p5._angleMode===o.DEGREES?360:o.TWO_PI):Math.random()*Math.PI*2,this.fromAngle(t)},n.Vector.random3D=function(){var t,e;this.p5?(t=this.p5.random(0,o.TWO_PI),e=this.p5.random(-1,1)):(t=Math.random()*Math.PI*2,e=2*Math.random()-1);var r=Math.sqrt(1-e*e)*Math.cos(t),i=Math.sqrt(1-e*e)*Math.sin(t);return this.p5?new n.Vector(this.p5,[r,i,e]):new n.Vector(r,i,e)},n.Vector.add=function(t,e){return t.get().add(e)},n.Vector.sub=function(t,e){return t.get().sub(e)},n.Vector.mult=function(t,e){return t.get().mult(e)},n.Vector.div=function(t,e){return t.get().div(e)},n.Vector.dot=function(t,e){return t.dot(e)},n.Vector.cross=function(t,e){return t.cross(e)},n.Vector.dist=function(t,e){return t.dist(e)},n.Vector.lerp=function(t,e,r){return t.get().lerp(e,r)},n.Vector.angleBetween=function(t,e){var r=Math.acos(t.dot(e)/(t.mag()*e.mag()));return this.p5&&this.p5._angleMode===o.DEGREES&&(r=i.radiansToDegrees(r)),r},n.Vector}({},core,polargeometry,constants),p5TableRow=function(t,e){"use strict";var r=e;return r.TableRow=function(t,e){var r=[],o={};t&&(e=e||",",r=t.split(e));for(var n=0;n<r.length;n++){var i=n,s=r[n];o[i]=s}this.arr=r,this.obj=o,this.table=null},r.TableRow.prototype.set=function(t,e){if("string"==typeof t){var r=this.table.columns.indexOf(t);if(!(r>=0))throw'This table has no column named "'+t+'"';this.obj[t]=e,this.arr[r]=e}else{if(!(t<this.table.columns.length))throw"Column #"+t+" is out of the range of this table";this.arr[t]=e;var o=this.table.columns[t];this.obj[o]=e}},r.TableRow.prototype.setNum=function(t,e){var r=parseFloat(e,10);this.set(t,r)},r.TableRow.prototype.setString=function(t,e){var r=e.toString();this.set(t,r)},r.TableRow.prototype.get=function(t){return"string"==typeof t?this.obj[t]:this.arr[t]},r.TableRow.prototype.getNum=function(t){var e;if(e="string"==typeof t?parseFloat(this.obj[t],10):parseFloat(this.arr[t],10),"NaN"===e.toString())throw"Error: "+this.obj[t]+" is NaN (Not a Number)";return e},r.TableRow.prototype.getString=function(t){return"string"==typeof t?this.obj[t].toString():this.arr[t].toString()},r.TableRow}({},core),p5Table=function(t,e){"use strict";var r=e;return r.Table=function(){this.columns=[],this.rows=[]},r.Table.prototype.addRow=function(t){var e=t||new r.TableRow;if("undefined"==typeof e.arr||"undefined"==typeof e.obj)throw"invalid TableRow: "+e;return e.table=this,this.rows.push(e),e},r.Table.prototype.removeRow=function(t){this.rows[t].table=null;var e=this.rows.splice(t+1,this.rows.length);this.rows.pop(),this.rows=this.rows.concat(e)},r.Table.prototype.getRow=function(t){return this.rows[t]},r.Table.prototype.getRows=function(){return this.rows},r.Table.prototype.findRow=function(t,e){if("string"==typeof e){for(var r=0;r<this.rows.length;r++)if(this.rows[r].obj[e]===t)return this.rows[r]}else for(var o=0;o<this.rows.length;o++)if(this.rows[o].arr[e]===t)return this.rows[o];return null},r.Table.prototype.findRows=function(t,e){var r=[];if("string"==typeof e)for(var o=0;o<this.rows.length;o++)this.rows[o].obj[e]===t&&r.push(this.rows[o]);else for(var n=0;n<this.rows.length;n++)this.rows[n].arr[e]===t&&r.push(this.rows[n]);return r},r.Table.prototype.matchRow=function(t,e){if("number"==typeof e){for(var r=0;r<this.rows.length;r++)if(this.rows[r].arr[e].match(t))return this.rows[r]}else for(var o=0;o<this.rows.length;o++)if(this.rows[o].obj[e].match(t))return this.rows[o];return null},r.Table.prototype.matchRows=function(t,e){var r=[];if("number"==typeof e)for(var o=0;o<this.rows.length;o++)this.rows[o].arr[e].match(t)&&r.push(this.rows[o]);else for(var n=0;n<this.rows.length;n++)this.rows[n].obj[e].match(t)&&r.push(this.rows[n]);return r},r.Table.prototype.getColumn=function(t){var e=[];if("string"==typeof t)for(var r=0;r<this.rows.length;r++)e.push(this.rows[r].obj[t]);else for(var o=0;o<this.rows.length;o++)e.push(this.rows[o].arr[t]);return e},r.Table.prototype.clearRows=function(){delete this.rows,this.rows=[]},r.Table.prototype.addColumn=function(t){var e=t||null;this.columns.push(e)},r.Table.prototype.getColumnCount=function(){return this.columns.length},r.Table.prototype.getRowCount=function(){return this.rows.length},r.Table.prototype.removeTokens=function(t,e){for(var r=function(t){return t.replace(/[-\/\\^$*+?.()|[\]{}]/g,"\\$&")},o=[],n=0;n<t.length;n++)o.push(r(t.charAt(n)));var i=new RegExp(o.join("|"),"g");if("undefined"==typeof e)for(var s=0;s<this.columns.length;s++)for(var a=0;a<this.rows.length;a++){var h=this.rows[a].arr[s];h=h.replace(i,""),this.rows[a].arr[s]=h,this.rows[a].obj[this.columns[s]]=h}else if("string"==typeof e)for(var p=0;p<this.rows.length;p++){var u=this.rows[p].obj[e];u=u.replace(i,""),this.rows[p].obj[e]=u;var l=this.columns.indexOf(e);this.rows[p].arr[l]=u}else for(var c=0;c<this.rows.length;c++){var d=this.rows[c].arr[e];d=d.replace(i,""),this.rows[c].arr[e]=d,this.rows[c].obj[this.columns[e]]=d}},r.Table.prototype.trim=function(t){var e=new RegExp(" ","g");if("undefined"==typeof t)for(var r=0;r<this.columns.length;r++)for(var o=0;o<this.rows.length;o++){var n=this.rows[o].arr[r];n=n.replace(e,""),this.rows[o].arr[r]=n,this.rows[o].obj[this.columns[r]]=n}else if("string"==typeof t)for(var i=0;i<this.rows.length;i++){var s=this.rows[i].obj[t];s=s.replace(e,""),this.rows[i].obj[t]=s;var a=this.columns.indexOf(t);this.rows[i].arr[a]=s}else for(var h=0;h<this.rows.length;h++){var p=this.rows[h].arr[t];p=p.replace(e,""),this.rows[h].arr[t]=p,this.rows[h].obj[this.columns[t]]=p}},r.Table.prototype.removeColumn=function(t){var e,r;"string"==typeof t?(e=t,r=this.columns.indexOf(t),console.log("string")):(r=t,e=this.columns[t]);var o=this.columns.splice(r+1,this.columns.length);this.columns.pop(),this.columns=this.columns.concat(o);for(var n=0;n<this.rows.length;n++){var i=this.rows[n].arr,s=i.splice(r+1,i.length);i.pop(),this.rows[n].arr=i.concat(s),delete this.rows[n].obj[e]}},r.Table}({},core),colorcreating_reading=function(t,e){"use strict";var r=e;return r.prototype.alpha=function(t){if(t instanceof r.Color)return t.rgba[3];if(t instanceof Array)return t[3];throw new Error("Needs p5.Color or pixel array as argument.")},r.prototype.blue=function(t){if(t instanceof Array)return t[2];if(t instanceof r.Color)return t.rgba[2];throw new Error("Needs p5.Color or pixel array as argument.")},r.prototype.brightness=function(t){if(!t instanceof r.Color)throw new Error("Needs p5.Color as argument.");return t.hsba||(t.hsba=r.Color.getRGB(t.rgba),t.hsba=t.hsba.concat(t.rgba[3])),t.hsba[2]},r.prototype.color=function(){return arguments[0]instanceof Array?new r.Color(this,arguments[0],!0):new r.Color(this,arguments)},r.prototype.green=function(t){if(t instanceof Array)return t[1];if(t instanceof r.Color)return t.rgba[1];throw new Error("Needs p5.Color or pixel array as argument.")},r.prototype.hue=function(t){if(!t instanceof r.Color)throw new Error("Needs p5.Color as argument.");return t.hsba||(t.hsba=r.Color.getRGB(t.rgba)),t.hsba[0]},r.prototype.lerpColor=function(t,e,o){if(t instanceof Array){for(var n=[],i=0;i<t.length;i++)n.push(r.prototype.lerp(t[i],e[i],o));return n}if(t instanceof r.Color){for(var s=[],a=0;4>a;a++)s.push(r.prototype.lerp(t.rgba[a],e.rgba[a],o));return new r.Color(this,s)}return r.prototype.lerp(t,e,o)},r.prototype.red=function(t){if(t instanceof Array)return t[0];if(t instanceof r.Color)return t.rgba[0];throw new Error("Needs p5.Color or pixel array as argument.")},r.prototype.saturation=function(t){if(!t instanceof r.Color)throw new Error("Needs p5.Color as argument.");return t.hsba||(t.hsba=r.Color.getRGB(t.rgba),t.hsba=t.hsba.concat(t.rgba[3])),t.hsba[1]},r}({},core,p5Color),colorsetting=function(t,e,r){"use strict";var o=e,r=r;return o.prototype._doStroke=!0,o.prototype._doFill=!0,o.prototype._colorMode=r.RGB,o.prototype._maxRGB=[255,255,255,255],o.prototype._maxHSB=[255,255,255,255],o.prototype.background=function(){if(arguments[0]instanceof o.Image)this.image(arguments[0],0,0,this.width,this.height);else{var t=this.drawingContext.fillStyle,e=this.drawingContext;e.fillStyle=o.Color._getCanvasColor.apply(this,arguments),e.fillRect(0,0,this.width,this.height),e.fillStyle=t}},o.prototype.clear=function(){this.drawingContext.clearRect(0,0,this.width,this.height)},o.prototype.colorMode=function(){if(arguments[0]===r.RGB||arguments[0]===r.HSB){this._colorMode=arguments[0];var t=this._colorMode===r.RGB,e=t?this._maxRGB:this._maxHSB;2===arguments.length?(e[0]=arguments[1],e[1]=arguments[1],e[2]=arguments[1]):arguments.length>2&&(e[0]=arguments[1],e[1]=arguments[2],e[2]=arguments[3]),5===arguments.length&&(e[3]=arguments[4])}},o.prototype.fill=function(){this._setProperty("_doFill",!0);var t=this.drawingContext;t.fillStyle=o.Color._getCanvasColor.apply(this,arguments)},o.prototype.noFill=function(){this._setProperty("_doFill",!1)},o.prototype.noStroke=function(){this._setProperty("_doStroke",!1)},o.prototype.stroke=function(){this._setProperty("_doStroke",!0);var t=this.drawingContext;t.strokeStyle=o.Color._getCanvasColor.apply(this,arguments)},o}({},core,constants,p5Color),dataconversion=function(t,e){"use strict";var r=e;return r.prototype.float=function(t){return parseFloat(t)},r.prototype.int=function(t,e){return"string"==typeof t?(e=e||10,parseInt(t,e)):"number"==typeof t?0|t:"boolean"==typeof t?t?1:0:t instanceof Array?t.map(r.prototype.int):void 0},r}({},core),dataarray_functions=function(t,e){"use strict";var r=e;return r.prototype.append=function(t,e){return t.push(e),t},r.prototype.arrayCopy=function(t,e,r,o,n){var i,s;"undefined"!=typeof n?(s=Math.min(n,t.length),i=o,t=t.slice(e,s+e)):("undefined"!=typeof r?(s=r,s=Math.min(s,t.length)):s=t.length,i=0,r=e,t=t.slice(0,s)),Array.prototype.splice.apply(r,[i,s].concat(t))},r.prototype.concat=function(t,e){return t.concat(e)},r.prototype.reverse=function(t){return t.reverse()},r.prototype.shorten=function(t){return t.pop(),t},r.prototype.sort=function(t,e){var r=e?t.slice(0,Math.min(e,t.length)):t,o=e?t.slice(Math.min(e,t.length)):[];return r="string"==typeof r[0]?r.sort():r.sort(function(t,e){return t-e}),r.concat(o)},r.prototype.splice=function(t,e,r){return Array.prototype.splice.apply(t,[r,0].concat(e)),t},r.prototype.subset=function(t,e,r){return"undefined"!=typeof r?t.slice(e,e+r):t.slice(e,t.length)},r}({},core),datastring_functions=function(t,e){"use strict";function r(){var t=arguments[0],e=0>t,r=e?t.toString().substring(1):t.toString(),o=r.indexOf("."),n=-1!==o?r.substring(0,o):r,i=-1!==o?r.substring(o+1):"",s=e?"-":"";if(3===arguments.length){for(var a=0;a<arguments[1]-n.length;a++)s+="0";s+=n,s+=".",s+=i;for(var h=0;h<arguments[2]-i.length;h++)s+="0";return s}for(var p=0;p<Math.max(arguments[1]-n.length,0);p++)s+="0";return s+=r}function o(){var t=arguments[0].toString(),e=t.indexOf("."),r=-1!==e?t.substring(e):"",o=-1!==e?t.substring(0,e):t;return o=o.toString().replace(/\B(?=(\d{3})+(?!\d))/g,","),0===arguments[1]&&(r=""),arguments.length>1&&(r=r.substring(0,arguments[1]+1)),o+r}function n(){return parseFloat(arguments[0])>0?"+"+arguments[0].toString():arguments[0].toString()}function i(){return parseFloat(arguments[0])>0?" "+arguments[0].toString():arguments[0].toString()
+}var s=e;return s.prototype.join=function(t,e){return t.join(e)},s.prototype.match=function(t,e){return t.match(e)},s.prototype.matchAll=function(t,e){for(var r=new RegExp(e,"g"),o=r.exec(t),n=[];null!==o;)n.push(o),o=r.exec(t);return n},s.prototype.nf=function(){if(arguments[0]instanceof Array){var t=arguments[1],e=arguments[2];return arguments[0].map(function(o){return r(o,t,e)})}return r.apply(this,arguments)},s.prototype.nfc=function(){if(arguments[0]instanceof Array){var t=arguments[1];return arguments[0].map(function(e){return o(e,t)})}return o.apply(this,arguments)},s.prototype.nfp=function(){var t=this.nf(arguments);return t instanceof Array?t.map(n):n(t)},s.prototype.nfs=function(){var t=this.nf(arguments);return t instanceof Array?t.map(i):i(t)},s.prototype.split=function(t,e){return t.split(e)},s.prototype.splitTokens=function(){var t=arguments.length>0?arguments[1]:/\s/g;return arguments[0].split(t).filter(function(t){return t})},s.prototype.trim=function(t){return t instanceof Array?t.map(this.trim):t.trim()},s}({},core),environment=function(t,e,r){"use strict";function o(t){var e=document.fullscreenEnabled||document.webkitFullscreenEnabled||document.mozFullScreenEnabled||document.msFullscreenEnabled;if(!e)throw new Error("Fullscreen not enabled in this browser.");t.requestFullscreen?t.requestFullscreen():t.mozRequestFullScreen?t.mozRequestFullScreen():t.webkitRequestFullscreen?t.webkitRequestFullscreen():t.msRequestFullscreen&&t.msRequestFullscreen()}function n(){document.exitFullscreen?document.exitFullscreen():document.mozCancelFullScreen?document.mozCancelFullScreen():document.webkitExitFullscreen&&document.webkitExitFullscreen()}var i=e,s=r,a=[s.ARROW,s.CROSS,s.HAND,s.MOVE,s.TEXT,s.WAIT];return i.prototype._frameRate=0,i.prototype._lastFrameTime=(new Date).getTime(),i.prototype._targetFrameRate=60,i.prototype.frameCount=0,i.prototype.focused=!0,i.prototype.cursor=function(t,e,r){var o="auto",n=this._curElement.elt;if(a.indexOf(t)>-1)o=t;else if("string"==typeof t){var i="";e&&r&&"number"==typeof e&&"number"==typeof r&&(i=e+" "+r),o="http://"!==t.substring(0,6)?"url("+t+") "+i+", auto":/\.(cur|jpg|jpeg|gif|png|CUR|JPG|JPEG|GIF|PNG)$/.test(t)?"url("+t+") "+i+", auto":t}n.style.cursor=o},i.prototype.frameRate=function(t){return"undefined"==typeof t?this._frameRate:(this._setProperty("_targetFrameRate",t),this._runFrames(),this)},i.prototype.getFrameRate=function(){return this.frameRate()},i.prototype.setFrameRate=function(t){return this.frameRate(t)},i.prototype.noCursor=function(){this._curElement.elt.style.cursor="none"},i.prototype.displayWidth=screen.width,i.prototype.displayHeight=screen.height,i.prototype.windowWidth=window.innerWidth,i.prototype.windowHeight=window.innerHeight,i.prototype.onresize=function(t){this._setProperty("windowWidth",window.innerWidth),this._setProperty("windowHeight",window.innerHeight);var e,r=this._isGlobal?window:this;"function"==typeof r.windowResized&&(e=r.windowResized(t),void 0===e||e||t.preventDefault())},i.prototype.width=0,i.prototype.height=0,i.prototype.fullscreen=function(t){return"undefined"==typeof t?document.fullscreenElement||document.webkitFullscreenElement||document.mozFullScreenElement||document.msFullscreenElement:void(t?o(document.documentElement):n())},i.prototype.devicePixelScaling=function(t){this._pixelDensity=t?window.devicePixelRatio||1:1,this.resizeCanvas(this.width,this.height)},i.prototype.getURL=function(){return location.href},i.prototype.getURLPath=function(){return location.pathname.split("/").filter(function(t){return""!==t})},i.prototype.getURLParams=function(){for(var t,e=/[?&]([^&=]+)(?:[&=])([^&=]+)/gim,r={};null!=(t=e.exec(location.search));)t.index===e.lastIndex&&e.lastIndex++,r[t[1]]=t[2];return r},i}({},core,constants),imageimage=function(t,e,r){"use strict";var o=e,r=r;return o.prototype._imageMode=r.CORNER,o.prototype._tint=null,o.prototype.createImage=function(t,e){return new o.Image(t,e)},o}({},core,constants),canvas=function(t,e){var e=e;return{modeAdjust:function(t,r,o,n,i){return i===e.CORNER?{x:t,y:r,w:o,h:n}:i===e.CORNERS?{x:t,y:r,w:o-t,h:n-r}:i===e.RADIUS?{x:t-o,y:r-n,w:2*o,h:2*n}:i===e.CENTER?{x:t-.5*o,y:r-.5*n,w:o,h:n}:void 0},arcModeAdjust:function(t,r,o,n,i){return i===e.CORNER?{x:t+.5*o,y:r+.5*n,w:o,h:n}:i===e.CORNERS?{x:t,y:r,w:o+t,h:n+r}:i===e.RADIUS?{x:t,y:r,w:2*o,h:2*n}:i===e.CENTER?{x:t,y:r,w:o,h:n}:void 0}}}({},constants),imageloading_displaying=function(t,e,r,o,n){"use strict";var i=e,s=r,o=o,n=n;return i.prototype.loadImage=function(t,e){var r=new Image,o=new i.Image(1,1,this);return r.onload=function(){o.width=o.canvas.width=r.width,o.height=o.canvas.height=r.height,o.canvas.getContext("2d").drawImage(r,0,0),"undefined"!=typeof e&&e(o)},0!==t.indexOf("data:image/")&&(r.crossOrigin="Anonymous"),r.src=t,o},i.prototype.image=function(t,e,r,n,i){var s=t.canvas||t.elt;e=e||0,r=r||0,n=n||t.width,i=i||t.height;var a=o.modeAdjust(e,r,n,i,this._imageMode);this._tint&&t.canvas?this.drawingContext.drawImage(this._getTintedImageCanvas(t),a.x,a.y,a.w,a.h):this.drawingContext.drawImage(s,a.x,a.y,a.w,a.h)},i.prototype.tint=function(){var t=i.Color._getFormattedColor.apply(this,arguments);t=i.Color._normalizeColorArray.call(this,t),this._tint=t},i.prototype.noTint=function(){this._tint=null},i.prototype._getTintedImageCanvas=function(t){if(!t.canvas)return t;var e=s._toPixels(t.canvas),r=document.createElement("canvas");r.width=t.canvas.width,r.height=t.canvas.height;for(var o=r.getContext("2d"),n=o.createImageData(t.canvas.width,t.canvas.height),i=n.data,a=0;a<e.length;a+=4){var h=e[a],p=e[a+1],u=e[a+2],l=e[a+3];i[a]=h*this._tint[0]/255,i[a+1]=p*this._tint[1]/255,i[a+2]=u*this._tint[2]/255,i[a+3]=l*this._tint[3]/255}return o.putImageData(n,0,0),r},i.prototype.imageMode=function(t){(t===n.CORNER||t===n.CORNERS||t===n.CENTER)&&(this._imageMode=t)},i}({},core,filters,canvas,constants),imagepixels=function(t,e,r){"use strict";var o=e,n=r;return o.prototype.pixels=[],o.prototype.blend=function(){var t=this.drawingContext.globalCompositeOperation,e=arguments[arguments.length-1],r=Array.prototype.slice.call(arguments,0,arguments.length-1);this.drawingContext.globalCompositeOperation=e,this.copy.apply(this,r),this.drawingContext.globalCompositeOperation=t},o.prototype.copy=function(){var t,e,r,o,n,i,s,a,h;if(9===arguments.length)t=arguments[0],e=arguments[1],r=arguments[2],o=arguments[3],n=arguments[4],i=arguments[5],s=arguments[6],a=arguments[7],h=arguments[8];else{if(8!==arguments.length)throw new Error("Signature not supported");e=arguments[0],r=arguments[1],o=arguments[2],n=arguments[3],i=arguments[4],s=arguments[5],a=arguments[6],h=arguments[7],t=this}var p=t.canvas.width/t.width;this.drawingContext.drawImage(t.canvas,p*e,p*r,p*o,p*n,i,s,a,h)},o.prototype.filter=function(t,e){n.apply(this.canvas,n[t.toLowerCase()],e)},o.prototype.get=function(t,e,r,n){if(void 0===t&&void 0===e&&void 0===r&&void 0===n?(t=0,e=0,r=this.width,n=this.height):void 0===r&&void 0===n&&(r=1,n=1),t>this.width||e>this.height||0>t||0>e)return[0,0,0,255];var i=this.drawingContext.getImageData(t,e,r,n),s=i.data;if(1===r&&1===n){for(var a=[],h=0;h<s.length;h+=4)a.push(s[h],s[h+1],s[h+2],s[h+3]);return a}r=Math.min(r,this.width),n=Math.min(n,this.height);var p=new o.Image(r,n);return p.canvas.getContext("2d").putImageData(i,0,0,0,0,r,n),p},o.prototype.loadPixels=function(){var t=this.width,e=this.height,r=this.drawingContext.getImageData(0,0,t,e);this._setProperty("imageData",r),this._setProperty("pixels",r.data)},o.prototype.set=function(t,e,r){if(r instanceof o.Image)this.drawingContext.drawImage(r.canvas,t,e),this.loadPixels.call(this);else{var n=4*(e*this.width+t);if(this.imageData||this.loadPixels.call(this),"number"==typeof r)n<this.pixels.length&&(this.pixels[n]=r,this.pixels[n+1]=r,this.pixels[n+2]=r,this.pixels[n+3]=255);else if(r instanceof Array){if(r.length<4)throw new Error("pixel array must be of the form [R, G, B, A]");n<this.pixels.length&&(this.pixels[n]=r[0],this.pixels[n+1]=r[1],this.pixels[n+2]=r[2],this.pixels[n+3]=r[3])}else r instanceof o.Color&&n<this.pixels.length&&(this.pixels[n]=r.rgba[0],this.pixels[n+1]=r.rgba[1],this.pixels[n+2]=r.rgba[2],this.pixels[n+3]=r.rgba[3])}},o.prototype.updatePixels=function(t,e,r,o){void 0===t&&void 0===e&&void 0===r&&void 0===o&&(t=0,e=0,r=this.width,o=this.height),this.drawingContext.putImageData(this.imageData,t,e,0,0,r,o)},o}({},core,filters,p5Color);!function(t,e,r){"undefined"!=typeof module&&module.exports?module.exports=r():"function"==typeof define&&define.amd?define("reqwest",r):e[t]=r()}("reqwest",this,function(){function handleReadyState(t,e,r){return function(){return t._aborted?r(t.request):void(t.request&&4==t.request[readyState]&&(t.request.onreadystatechange=noop,twoHundo.test(t.request.status)?e(t.request):r(t.request)))}}function setHeaders(t,e){var r,o=e.headers||{};o.Accept=o.Accept||defaultHeaders.accept[e.type]||defaultHeaders.accept["*"],e.crossOrigin||o[requestedWith]||(o[requestedWith]=defaultHeaders.requestedWith),o[contentType]||(o[contentType]=e.contentType||defaultHeaders.contentType);for(r in o)o.hasOwnProperty(r)&&"setRequestHeader"in t&&t.setRequestHeader(r,o[r])}function setCredentials(t,e){"undefined"!=typeof e.withCredentials&&"undefined"!=typeof t.withCredentials&&(t.withCredentials=!!e.withCredentials)}function generalCallback(t){lastValue=t}function urlappend(t,e){return t+(/\?/.test(t)?"&":"?")+e}function handleJsonp(t,e,r,o){var n=uniqid++,i=t.jsonpCallback||"callback",s=t.jsonpCallbackName||reqwest.getcallbackPrefix(n),a=new RegExp("((^|\\?|&)"+i+")=([^&]+)"),h=o.match(a),p=doc.createElement("script"),u=0,l=-1!==navigator.userAgent.indexOf("MSIE 10.0");return h?"?"===h[3]?o=o.replace(a,"$1="+s):s=h[3]:o=urlappend(o,i+"="+s),win[s]=generalCallback,p.type="text/javascript",p.src=o,p.async=!0,"undefined"==typeof p.onreadystatechange||l||(p.event="onclick",p.htmlFor=p.id="_reqwest_"+n),p.onload=p.onreadystatechange=function(){return p[readyState]&&"complete"!==p[readyState]&&"loaded"!==p[readyState]||u?!1:(p.onload=p.onreadystatechange=null,p.onclick&&p.onclick(),e(lastValue),lastValue=void 0,head.removeChild(p),void(u=1))},head.appendChild(p),{abort:function(){p.onload=p.onreadystatechange=null,r({},"Request is aborted: timeout",{}),lastValue=void 0,head.removeChild(p),u=1}}}function getRequest(t,e){var r,o=this.o,n=(o.method||"GET").toUpperCase(),i="string"==typeof o?o:o.url,s=o.processData!==!1&&o.data&&"string"!=typeof o.data?reqwest.toQueryString(o.data):o.data||null,a=!1;return"jsonp"!=o.type&&"GET"!=n||!s||(i=urlappend(i,s),s=null),"jsonp"==o.type?handleJsonp(o,t,e,i):(r=o.xhr&&o.xhr(o)||xhr(o),r.open(n,i,o.async===!1?!1:!0),setHeaders(r,o),setCredentials(r,o),win[xDomainRequest]&&r instanceof win[xDomainRequest]?(r.onload=t,r.onerror=e,r.onprogress=function(){},a=!0):r.onreadystatechange=handleReadyState(this,t,e),o.before&&o.before(r),a?setTimeout(function(){r.send(s)},200):r.send(s),r)}function Reqwest(t,e){this.o=t,this.fn=e,init.apply(this,arguments)}function setType(t){var e=t.match(/\.(json|jsonp|html|xml)(\?|$)/);return e?e[1]:"js"}function init(o,fn){function complete(t){for(o.timeout&&clearTimeout(self.timeout),self.timeout=null;self._completeHandlers.length>0;)self._completeHandlers.shift()(t)}function success(resp){resp="jsonp"!==type?self.request:resp;var filteredResponse=globalSetupOptions.dataFilter(resp.responseText,type),r=filteredResponse;try{resp.responseText=r}catch(e){}if(r)switch(type){case"json":try{resp=win.JSON?win.JSON.parse(r):eval("("+r+")")}catch(err){return error(resp,"Could not parse JSON in response",err)}break;case"js":resp=eval(r);break;case"html":resp=r;break;case"xml":resp=resp.responseXML&&resp.responseXML.parseError&&resp.responseXML.parseError.errorCode&&resp.responseXML.parseError.reason?null:resp.responseXML}for(self._responseArgs.resp=resp,self._fulfilled=!0,fn(resp),self._successHandler(resp);self._fulfillmentHandlers.length>0;)resp=self._fulfillmentHandlers.shift()(resp);complete(resp)}function error(t,e,r){for(t=self.request,self._responseArgs.resp=t,self._responseArgs.msg=e,self._responseArgs.t=r,self._erred=!0;self._errorHandlers.length>0;)self._errorHandlers.shift()(t,e,r);complete(t)}this.url="string"==typeof o?o:o.url,this.timeout=null,this._fulfilled=!1,this._successHandler=function(){},this._fulfillmentHandlers=[],this._errorHandlers=[],this._completeHandlers=[],this._erred=!1,this._responseArgs={};var self=this,type=o.type||setType(this.url);fn=fn||function(){},o.timeout&&(this.timeout=setTimeout(function(){self.abort()},o.timeout)),o.success&&(this._successHandler=function(){o.success.apply(o,arguments)}),o.error&&this._errorHandlers.push(function(){o.error.apply(o,arguments)}),o.complete&&this._completeHandlers.push(function(){o.complete.apply(o,arguments)}),this.request=getRequest.call(this,success,error)}function reqwest(t,e){return new Reqwest(t,e)}function normalize(t){return t?t.replace(/\r?\n/g,"\r\n"):""}function serial(t,e){var r,o,n,i,s=t.name,a=t.tagName.toLowerCase(),h=function(t){t&&!t.disabled&&e(s,normalize(t.attributes.value&&t.attributes.value.specified?t.value:t.text))};if(!t.disabled&&s)switch(a){case"input":/reset|button|image|file/i.test(t.type)||(r=/checkbox/i.test(t.type),o=/radio/i.test(t.type),n=t.value,(!(r||o)||t.checked)&&e(s,normalize(r&&""===n?"on":n)));break;case"textarea":e(s,normalize(t.value));break;case"select":if("select-one"===t.type.toLowerCase())h(t.selectedIndex>=0?t.options[t.selectedIndex]:null);else for(i=0;t.length&&i<t.length;i++)t.options[i].selected&&h(t.options[i])}}function eachFormElement(){var t,e,r=this,o=function(t,e){var o,n,i;for(o=0;o<e.length;o++)for(i=t[byTag](e[o]),n=0;n<i.length;n++)serial(i[n],r)};for(e=0;e<arguments.length;e++)t=arguments[e],/input|select|textarea/i.test(t.tagName)&&serial(t,r),o(t,["input","select","textarea"])}function serializeQueryString(){return reqwest.toQueryString(reqwest.serializeArray.apply(null,arguments))}function serializeHash(){var t={};return eachFormElement.apply(function(e,r){e in t?(t[e]&&!isArray(t[e])&&(t[e]=[t[e]]),t[e].push(r)):t[e]=r},arguments),t}function buildParams(t,e,r,o){var n,i,s,a=/\[\]$/;if(isArray(e))for(i=0;e&&i<e.length;i++)s=e[i],r||a.test(t)?o(t,s):buildParams(t+"["+("object"==typeof s?i:"")+"]",s,r,o);else if(e&&"[object Object]"===e.toString())for(n in e)buildParams(t+"["+n+"]",e[n],r,o);else o(t,e)}var win=window,doc=document,twoHundo=/^(20\d|1223)$/,byTag="getElementsByTagName",readyState="readyState",contentType="Content-Type",requestedWith="X-Requested-With",head=doc[byTag]("head")[0],uniqid=0,callbackPrefix="reqwest_"+ +new Date,lastValue,xmlHttpRequest="XMLHttpRequest",xDomainRequest="XDomainRequest",noop=function(){},isArray="function"==typeof Array.isArray?Array.isArray:function(t){return t instanceof Array},defaultHeaders={contentType:"application/x-www-form-urlencoded",requestedWith:xmlHttpRequest,accept:{"*":"text/javascript, text/html, application/xml, text/xml, */*",xml:"application/xml, text/xml",html:"text/html",text:"text/plain",json:"application/json, text/javascript",js:"application/javascript, text/javascript"}},xhr=function(t){if(t.crossOrigin===!0){var e=win[xmlHttpRequest]?new XMLHttpRequest:null;if(e&&"withCredentials"in e)return e;if(win[xDomainRequest])return new XDomainRequest;throw new Error("Browser does not support cross-origin requests")}return win[xmlHttpRequest]?new XMLHttpRequest:new ActiveXObject("Microsoft.XMLHTTP")},globalSetupOptions={dataFilter:function(t){return t}};return Reqwest.prototype={abort:function(){this._aborted=!0,this.request.abort()},retry:function(){init.call(this,this.o,this.fn)},then:function(t,e){return t=t||function(){},e=e||function(){},this._fulfilled?this._responseArgs.resp=t(this._responseArgs.resp):this._erred?e(this._responseArgs.resp,this._responseArgs.msg,this._responseArgs.t):(this._fulfillmentHandlers.push(t),this._errorHandlers.push(e)),this},always:function(t){return this._fulfilled||this._erred?t(this._responseArgs.resp):this._completeHandlers.push(t),this},fail:function(t){return this._erred?t(this._responseArgs.resp,this._responseArgs.msg,this._responseArgs.t):this._errorHandlers.push(t),this}},reqwest.serializeArray=function(){var t=[];return eachFormElement.apply(function(e,r){t.push({name:e,value:r})},arguments),t},reqwest.serialize=function(){if(0===arguments.length)return"";var t,e,r=Array.prototype.slice.call(arguments,0);return t=r.pop(),t&&t.nodeType&&r.push(t)&&(t=null),t&&(t=t.type),e="map"==t?serializeHash:"array"==t?reqwest.serializeArray:serializeQueryString,e.apply(null,r)},reqwest.toQueryString=function(t,e){var r,o,n=e||!1,i=[],s=encodeURIComponent,a=function(t,e){e="function"==typeof e?e():null==e?"":e,i[i.length]=s(t)+"="+s(e)};if(isArray(t))for(o=0;t&&o<t.length;o++)a(t[o].name,t[o].value);else for(r in t)t.hasOwnProperty(r)&&buildParams(r,t[r],n,a);return i.join("&").replace(/%20/g,"+")},reqwest.getcallbackPrefix=function(){return callbackPrefix},reqwest.compat=function(t,e){return t&&(t.type&&(t.method=t.type)&&delete t.type,t.dataType&&(t.type=t.dataType),t.jsonpCallback&&(t.jsonpCallbackName=t.jsonpCallback)&&delete t.jsonpCallback,t.jsonp&&(t.jsonpCallback=t.jsonp)),new Reqwest(t,e)},reqwest.ajaxSetup=function(t){t=t||{};for(var e in t)globalSetupOptions[e]=t[e]},reqwest});var inputfiles=function(t,e,r){"use strict";function o(t,e){var r={};if(e=e||[],"undefined"==typeof e)for(var o=0;o<t.length;o++)e[o.toString()]=o;for(var n=0;n<e.length;n++){var i=e[n],s=t[n];r[i]=s}return r}var n=e,r=r;return n.prototype.createInput=function(){throw"not yet implemented"},n.prototype.createReader=function(){throw"not yet implemented"},n.prototype.loadBytes=function(){throw"not yet implemented"},n.prototype.loadJSON=function(t,e){var o=[],n=-1===t.indexOf("http")?"json":"jsonp";return"string"==typeof arguments[2]&&("jsonp"===arguments[2]||"json"===arguments[2])&&(n=arguments[2]),r({url:t,type:n,crossOrigin:!0}).then(function(t){for(var r in t)o[r]=t[r];"undefined"!=typeof e&&e(t)}),o},n.prototype.loadStrings=function(t,e){var r=[],o=new XMLHttpRequest;return o.open("GET",t,!0),o.onreadystatechange=function(){if(4===o.readyState&&(200===o.status||0===o.status)){var t=o.responseText.match(/[^\r\n]+/g);for(var n in t)r[n]=t[n];"undefined"!=typeof e&&e(r)}},o.send(null),r},n.prototype.loadTable=function(t){for(var e=null,r=[],i=!1,s=",",a=1;a<arguments.length;a++)"function"==typeof arguments[a]?e=arguments[a]:"string"==typeof arguments[a]&&(r.push(arguments[a]),"header"===arguments[a]&&(i=!0),"csv"===arguments[a]?s=",":"tsv"===arguments[a]&&(s="	"));var h=[],p=new n.Table,u=new XMLHttpRequest;return u.open("GET",t,!0),u.onreadystatechange=function(){if(4===u.readyState&&(200===u.status||0===u.status)){var t=u.responseText.match(/[^\r\n]+/g);for(var r in t)h[r]=t[r];if("undefined"!=typeof e){var a,l;if(i)for(p.columns=new n.TableRow(h[0]).arr,a=1;a<h.length;a++)l=new n.TableRow(h[a],s),l.obj=o(l.arr,p.columns),p.addRow(l);else{for(a=0;a<h[0].split(s).length;a++)p.columns[a]=a.toString();for(a=0;a<h.length;a++)l=new n.TableRow(h[a],s),p.addRow(l)}e(p)}}},u.send(null),p},n.prototype.loadXML=function(t,e){var o=[];return r({url:t,type:"xml",crossOrigin:!0}).then(function(t){e(t)}),o},n.prototype.parseXML=function(){throw"not yet implemented"},n.prototype.selectFolder=function(){throw"not yet implemented"},n.prototype.selectInput=function(){throw"not yet implemented"},n.prototype.httpGet=function(){var t=Array.prototype.slice.call(arguments);t.push("GET"),n.prototype.httpDo.apply(this,t)},n.prototype.httpPost=function(){var t=Array.prototype.slice.call(arguments);t.push("POST"),n.prototype.httpDo.apply(this,t)},n.prototype.httpDo=function(){for(var t,e="GET",o=arguments[0],n={},i="",s=1;s<arguments.length;s++){var a=arguments[s];"string"==typeof a?"GET"===a||"POST"===a||"PUT"===a?e=a:i=a:"object"==typeof a?n=a:"function"==typeof a&&(t=a)}""===i&&(i=-1!==o.indexOf("json")?"json":-1!==o.indexOf("xml")?"xml":"text"),r({url:o,method:e,data:n,type:i,crossOrigin:!0,success:function(e){"undefined"!=typeof t&&t("text"===i?e.response:e)}})},n}({},core,reqwest),inputkeyboard=function(t,e){"use strict";var r=e,o={};return r.prototype.isKeyPressed=!1,r.prototype.keyIsPressed=!1,r.prototype.key="",r.prototype.keyCode=0,r.prototype.onkeydown=function(t){this._setProperty("isKeyPressed",!0),this._setProperty("keyIsPressed",!0),this._setProperty("keyCode",t.which),o[t.which]=!0;var e=String.fromCharCode(t.which);e||(e=t.which),this._setProperty("key",e);var r=this.keyPressed||window.keyPressed;if("function"==typeof r&&!t.charCode){var n=r(t);n===!1&&t.preventDefault()}},r.prototype.onkeyup=function(t){var e=this.keyReleased||window.keyReleased;this._setProperty("isKeyPressed",!1),this._setProperty("keyIsPressed",!1),o[t.which]=!1;var r=String.fromCharCode(t.which);if(r||(r=t.which),this._setProperty("key",r),this._setProperty("keyCode",t.which),"function"==typeof e){var n=e(t);n===!1&&t.preventDefault()}},r.prototype.onkeypress=function(t){this._setProperty("keyCode",t.which),this._setProperty("key",String.fromCharCode(t.which));var e=this.keyTyped||window.keyTyped;if("function"==typeof e){var r=e(t);r===!1&&t.preventDefault()}},r.prototype.onblur=function(){o={}},r.prototype.keyIsDown=function(t){return o[t]},r}({},core),inputmouse=function(t,e,r){"use strict";function o(t,e){var r=t.getBoundingClientRect();return{x:e.clientX-r.left,y:e.clientY-r.top}}var n=e,r=r;return n.prototype.mouseX=0,n.prototype.mouseY=0,n.prototype.pmouseX=0,n.prototype.pmouseY=0,n.prototype.winMouseX=0,n.prototype.winMouseY=0,n.prototype.pwinMouseX=0,n.prototype.pwinMouseY=0,n.prototype.mouseButton=0,n.prototype.mouseIsPressed=!1,n.prototype.isMousePressed=!1,n.prototype._updateMouseCoords=function(t){if("touchstart"===t.type||"touchmove"===t.type||"touchend"===t.type)this._setProperty("mouseX",this.touchX),this._setProperty("mouseY",this.touchY);else if(null!==this._curElement){var e=o(this._curElement.elt,t);this._setProperty("mouseX",e.x),this._setProperty("mouseY",e.y)}this._setProperty("winMouseX",t.pageX),this._setProperty("winMouseY",t.pageY)},n.prototype._updatePMouseCoords=function(){this._setProperty("pmouseX",this.mouseX),this._setProperty("pmouseY",this.mouseY),this._setProperty("pwinMouseX",this.winMouseX),this._setProperty("pwinMouseY",this.winMouseY)},n.prototype._setMouseButton=function(t){1===t.button?this._setProperty("mouseButton",r.CENTER):2===t.button?this._setProperty("mouseButton",r.RIGHT):(this._setProperty("mouseButton",r.LEFT),("touchstart"===t.type||"touchmove"===t.type)&&(this._setProperty("mouseX",this.touchX),this._setProperty("mouseY",this.touchY)))},n.prototype.onmousemove=function(t){var e,r=this._isGlobal?window:this;this._updateMouseCoords(t),this.isMousePressed?"function"==typeof r.mouseDragged?(e=r.mouseDragged(t),e===!1&&t.preventDefault()):"function"==typeof r.touchMoved&&(e=r.touchMoved(t),e===!1&&t.preventDefault(),this._updateTouchCoords(t)):"function"==typeof r.mouseMoved&&(e=r.mouseMoved(t),e===!1&&t.preventDefault())},n.prototype.onmousedown=function(t){var e,r=this._isGlobal?window:this;this._setProperty("isMousePressed",!0),this._setProperty("mouseIsPressed",!0),this._setMouseButton(t),this._updateMouseCoords(t),"function"==typeof r.mousePressed?(e=r.mousePressed(t),e===!1&&t.preventDefault()):"function"==typeof r.touchStarted&&(e=r.touchStarted(t),e===!1&&t.preventDefault(),this._updateTouchCoords(t))},n.prototype.onmouseup=function(t){var e,r=this._isGlobal?window:this;this._setProperty("isMousePressed",!1),this._setProperty("mouseIsPressed",!1),"function"==typeof r.mouseReleased?(e=r.mouseReleased(t),e===!1&&t.preventDefault()):"function"==typeof r.touchEnded&&(e=r.touchEnded(t),e===!1&&t.preventDefault(),this._updateTouchCoords(t))},n.prototype.onclick=function(t){var e=this._isGlobal?window:this;if("function"==typeof e.mouseClicked){var r=e.mouseClicked(t);r===!1&&t.preventDefault()}},n.prototype.onmousewheel=function(t){var e=this._isGlobal?window:this;if("function"==typeof e.mouseWheel){var r=e.mouseWheel(t);r===!1&&t.preventDefault()}},n}({},core,constants),inputtime_date=function(t,e){"use strict";var r=e;return r.prototype.day=function(){return(new Date).getDate()},r.prototype.hour=function(){return(new Date).getHours()},r.prototype.minute=function(){return(new Date).getMinutes()},r.prototype.millis=function(){return(new Date).getTime()-this._startTime},r.prototype.month=function(){return(new Date).getMonth()+1},r.prototype.second=function(){return(new Date).getSeconds()},r.prototype.year=function(){return(new Date).getFullYear()},r}({},core),inputtouch=function(t,e){"use strict";function r(t,e,r){r=r||0;var o=t.getBoundingClientRect();return{x:e.changedTouches[r].pageX-o.left,y:e.changedTouches[r].pageY-o.top}}var o=e;return o.prototype.touchX=0,o.prototype.touchY=0,o.prototype.ptouchX=0,o.prototype.ptouchY=0,o.prototype.touches=[],o.prototype._updateTouchCoords=function(t){if("mousedown"===t.type||"mousemove"===t.type||"mouseup"===t.type)this._setProperty("touchX",this.mouseX),this._setProperty("touchY",this.mouseY);else{var e=r(this._curElement.elt,t,0);this._setProperty("touchX",e.x),this._setProperty("touchY",e.y);for(var o=[],n=0;n<t.changedTouches.length;n++){var i=r(this._curElement.elt,t,n);o[n]={x:i.x,y:i.y}}this._setProperty("touches",o)}},o.prototype._updatePTouchCoords=function(){this._setProperty("ptouchX",this.touchX),this._setProperty("ptouchY",this.touchY)},o.prototype.ontouchstart=function(t){var e,r=this._isGlobal?window:this;this._updateTouchCoords(t),"function"==typeof r.touchStarted?(e=r.touchStarted(t),e===!1&&t.preventDefault()):"function"==typeof r.mousePressed&&(e=r.mousePressed(t),e===!1&&t.preventDefault())},o.prototype.ontouchmove=function(t){var e,r=this._isGlobal?window:this;this._updateTouchCoords(t),"function"==typeof r.touchMoved?(e=r.touchMoved(t),e===!1&&t.preventDefault()):"function"==typeof r.mouseDragged&&(e=r.mouseDragged(t),e===!1&&t.preventDefault(),this._updateMouseCoords(t))},o.prototype.ontouchend=function(t){this._updateTouchCoords(t);var e,r=this._isGlobal?window:this;"function"==typeof r.touchEnded?(e=r.touchEnded(t),e===!1&&t.preventDefault()):"function"==typeof r.mouseReleased&&(e=r.mouseReleased(t),e===!1&&t.preventDefault(),this._updateMouseCoords(t))},o}({},core),mathmath=function(t,e){"use strict";var r=e;return r.prototype.createVector=function(){return new r.Vector(this,arguments)},r}({},core),mathcalculation=function(t,e){"use strict";var r=e;return r.prototype.abs=Math.abs,r.prototype.ceil=Math.ceil,r.prototype.constrain=function(t,e,r){return Math.max(Math.min(t,r),e)},r.prototype.dist=function(t,e,r,o){return Math.sqrt((r-t)*(r-t)+(o-e)*(o-e))},r.prototype.exp=Math.exp,r.prototype.floor=Math.floor,r.prototype.lerp=function(t,e,r){return r*(e-t)+t},r.prototype.log=Math.log,r.prototype.mag=function(t,e){return Math.sqrt(t*t+e*e)},r.prototype.map=function(t,e,r,o,n){return(t-e)/(r-e)*(n-o)+o},r.prototype.max=function(){return arguments[0]instanceof Array?Math.max.apply(null,arguments[0]):Math.max.apply(null,arguments)},r.prototype.min=function(){return arguments[0]instanceof Array?Math.min.apply(null,arguments[0]):Math.min.apply(null,arguments)},r.prototype.norm=function(t,e,r){return this.map(t,e,r,0,1)},r.prototype.pow=Math.pow,r.prototype.round=Math.round,r.prototype.sq=function(t){return t*t},r.prototype.sqrt=Math.sqrt,r}({},core),mathrandom=function(t,e){"use strict";var r=e,o=!1,n=function(){var t,e,r=4294967296,o=1664525,n=1013904223;return{setSeed:function(o){e=t=o||Math.round(Math.random()*r)},getSeed:function(){return t},rand:function(){return e=(o*e+n)%r,e/r}}}();r.prototype.randomSeed=function(t){n.setSeed(t),o=!0},r.prototype.random=function(t,e){var r;if(r=o?n.rand():Math.random(),0===arguments.length)return r;if(1===arguments.length)return r*t;if(t>e){var i=t;t=e,e=i}return r*(e-t)+t};var i,s=!1;return r.prototype.randomGaussian=function(t,e){var r,o,n,a;if(s)r=i,s=!1;else{do o=this.random(2)-1,n=this.random(2)-1,a=o*o+n*n;while(a>=1);a=Math.sqrt(-2*Math.log(a)/a),r=o*a,i=n*a,s=!0}var h=t||0,p=e||1;return r*p+h},r}({},core),mathnoise=function(t,e){"use strict";for(var r=e,o=4,n=1<<o,i=8,s=1<<i,a=4095,h=4,p=.5,u=.5,l=Math.floor(360/u),c=new Array(l),d=new Array(l),f=Math.PI/180,g=0;l>g;g++)c[g]=Math.sin(g*f*u),d[g]=Math.cos(g*f*u);var y=l;y>>=1;var m;return r.prototype.noise=function(t,e,r){if(e=e||0,r=r||0,null==m){m=new Array(a+1);for(var u=0;a+1>u;u++)m[u]=Math.random()}0>t&&(t=-t),0>e&&(e=-e),0>r&&(r=-r);for(var c,f,g,w,v,_=Math.floor(t),x=Math.floor(e),C=Math.floor(r),b=t-_,S=e-x,R=r-C,T=0,E=.5,M=function(t){return.5*(1-d[Math.floor(t*y)%l])},P=0;h>P;P++){var A=_+(x<<o)+(C<<i);c=M(b),f=M(S),g=m[A&a],g+=c*(m[A+1&a]-g),w=m[A+n&a],w+=c*(m[A+n+1&a]-w),g+=f*(w-g),A+=s,w=m[A&a],w+=c*(m[A+1&a]-w),v=m[A+n&a],v+=c*(m[A+n+1&a]-v),w+=f*(v-w),g+=M(R)*(w-g),T+=g*E,E*=p,_<<=1,b*=2,x<<=1,S*=2,C<<=1,R*=2,b>=1&&(_++,b--),S>=1&&(x++,S--),R>=1&&(C++,R--)}return T},r.prototype.noiseDetail=function(t,e){t>0&&(h=t),e>0&&(p=e)},r.prototype.noiseSeed=function(t){var e=function(){var t,e,r=4294967296,o=1664525,n=1013904223;return{setSeed:function(o){e=t=o||Math.round(Math.random()*r)},getSeed:function(){return t},rand:function(){return e=(o*e+n)%r,e/r}}}();e.setSeed(t),m=new Array(a+1);for(var r=0;a+1>r;r++)m[r]=e.rand()},r}({},core),mathtrigonometry=function(t,e,r,o){"use strict";var n=e,i=r,o=o;return n.prototype._angleMode=o.RADIANS,n.prototype.acos=function(t){return this._angleMode===o.RADIANS?Math.acos(t):i.radiansToDegrees(Math.acos(t))},n.prototype.asin=function(t){return this._angleMode===o.RADIANS?Math.asin(t):i.radiansToDegrees(Math.asin(t))},n.prototype.atan=function(t){return this._angleMode===o.RADIANS?Math.atan(t):i.radiansToDegrees(Math.atan(t))},n.prototype.atan2=function(t,e){return this._angleMode===o.RADIANS?Math.atan2(t,e):i.radiansToDegrees(Math.atan2(t,e))},n.prototype.cos=function(t){return Math.cos(this._angleMode===o.RADIANS?t:this.radians(t))},n.prototype.sin=function(t){return Math.sin(this._angleMode===o.RADIANS?t:this.radians(t))},n.prototype.tan=function(t){return Math.tan(this._angleMode===o.RADIANS?t:this.radians(t))},n.prototype.degrees=function(t){return i.radiansToDegrees(t)},n.prototype.radians=function(t){return i.degreesToRadians(t)},n.prototype.angleMode=function(t){(t===o.DEGREES||t===o.RADIANS)&&(this._angleMode=t)},n}({},core,polargeometry,constants),outputfiles=function(t,e){"use strict";function r(t,e){e||(e=""),t||(t="untitled");var r="";return t&&t.indexOf(".")>-1&&(r=t.split(".").pop()),e&&r!==e&&(r=e,t=t+"."+r),[t,r]}function o(t){document.body.removeChild(t.target)}var n=e;window.URL=window.URL||window.webkitURL,n.prototype._pWriters=[],n.prototype.beginRaw=function(){throw"not yet implemented"},n.prototype.beginRecord=function(){throw"not yet implemented"},n.prototype.createOutput=function(){throw"not yet implemented"},n.prototype.createWriter=function(t,e){var r;for(var o in n.prototype._pWriters)if(n.prototype._pWriters[o].name===t)return r=new n.PrintWriter(t+window.millis(),e),n.prototype._pWriters.push(r),r;return r=new n.PrintWriter(t,e),n.prototype._pWriters.push(r),r},n.prototype.endRaw=function(){throw"not yet implemented"},n.prototype.endRecord=function(){throw"not yet implemented"},n.PrintWriter=function(t,e){var r=this;this.name=t,this.content="",this.print=function(t){this.content+=t},this.println=function(t){this.content+=t+"\n"},this.flush=function(){this.content=""},this.close=function(){var o=[];o.push(this.content),n.prototype.writeFile(o,t,e);for(var i in n.prototype._pWriters)n.prototype._pWriters[i].name===this.name&&n.prototype._pWriters.splice(i,1);r.flush(),r={}}},n.prototype.saveBytes=function(){throw"not yet implemented"},n.prototype.save=function(){var t=arguments,e=this._curElement.elt;if(0===t.length)return void n.prototype.saveCanvas(e);if(t[0]instanceof n.Graphics)return void n.prototype.saveCanvas(t[0].elt,t[1],t[2]);if("string"==typeof t[0])n.prototype.saveCanvas(e,t[0]);
+else{var o=r(t[1],t[2])[1];switch(o){case"json":n.prototype.saveJSON(t[0],t[1],t[2]);break;case"txt":n.prototype.saveStrings(t[0],t[1],t[2]);break;default:t[0]instanceof Array?n.prototype.saveStrings(t[0],t[1],t[2]):t[0]instanceof n.Table?n.prototype.saveTable(t[0],t[1],t[2],t[3]):t[0]instanceof n.Image?n.prototype.saveCanvas(t[0].canvas,t[1]):t[0]instanceof n.SoundFile?n.prototype.saveSound(t[0],t[1],t[2],t[3]):t[0]instanceof Object&&n.prototype.saveJSON(t[0],t[1],t[2])}}},n.prototype.saveJSON=function(t,e,r){var o;o=r?JSON.stringify(t):JSON.stringify(t,void 0,2),this.saveStrings(o.split("\n"),e,"json")},n.prototype.saveJSONObject=n.prototype.saveJSON,n.prototype.saveJSONArray=n.prototype.saveJSON,n.prototype.saveStream=function(){throw"not yet implemented"},n.prototype.saveStrings=function(t,e,r){var o=r||"txt",n=this.createWriter(e,o);for(var i in t)i<t.length-1?n.println(t[i]):n.print(t[i]);n.close(),n.flush()},n.prototype.saveXML=function(){throw"not yet implemented"},n.prototype.selectOutput=function(){throw"not yet implemented"},n.prototype.saveTable=function(t,e,r){var o=this.createWriter(e,r),n=t.columns,s=",";if("tsv"===r&&(s="	"),"html"!==r){if("0"!==n[0])for(var a=0;a<n.length;a++)a<n.length-1?o.print(n[a]+s):o.println(n[a]);for(var h=0;h<t.rows.length;h++){var p;for(p=0;p<t.rows[h].arr.length;p++)p<t.rows[h].arr.length-1?o.print(t.rows[h].arr[p]+s):h<t.rows.length-1?o.println(t.rows[h].arr[p]):o.print(t.rows[h].arr[p])}}else{o.println("<html>"),o.println("<head>");var u='  <meta http-equiv="content-type" content';if(u+='="text/html;charset=utf-8" />',o.println(u),o.println("</head>"),o.println("<body>"),o.println("  <table>"),"0"!==n[0]){o.println("    <tr>");for(var l=0;l<n.length;l++){var c=i(n[l]);o.println("      <td>"+c),o.println("      </td>")}o.println("    </tr>")}for(var d=0;d<t.rows.length;d++){o.println("    <tr>");for(var f=0;f<t.columns.length;f++){var g=t.rows[d].getString(f),y=i(g);o.println("      <td>"+y),o.println("      </td>")}o.println("    </tr>")}o.println("  </table>"),o.println("</body>"),o.print("</html>")}o.close(),o.flush()};var i=function(t){return t.replace(/&/g,"&amp;").replace(/</g,"&lt;").replace(/>/g,"&gt;").replace(/"/g,"&quot;").replace(/'/g,"&#039;")};return n.prototype.writeFile=function(t,e,r){var o="application/octet-stream";n.prototype._isSafari()&&(o="text/plain");var i=new Blob(t,{type:o}),s=window.URL.createObjectURL(i);n.prototype.downloadFile(s,e,r)},n.prototype.downloadFile=function(t,e,i){var s=r(e,i),a=s[0],h=s[1],p=document.createElement("a");if(p.href=t,p.download=a,p.onclick=o,p.style.display="none",document.body.appendChild(p),n.prototype._isSafari()){var u="Hello, Safari user! To download this file...\n";u+="1. Go to File --> Save As.\n",u+='2. Choose "Page Source" as the Format.\n',u+='3. Name it with this extension: ."'+h+'"',alert(u)}p.click(),t=null},n.prototype._checkFileExtension=r,n.prototype._isSafari=function(){var t=Object.prototype.toString.call(window.HTMLElement);return t.indexOf("Constructor")>0},n}({},core),outputimage=function(t,e){"use strict";var r=e,o=[];return r.prototype.saveCanvas=function(t,e,o){o||(o=r.prototype._checkFileExtension(e,o)[1],""===o&&(o="png"));var n;if(t?n=t:this._curElement&&this._curElement.elt&&(n=this._curElement.elt),r.prototype._isSafari()){var i="Hello, Safari user!\n";i+="Now capturing a screenshot...\n",i+="To save this image,\n",i+="go to File --> Save As.\n",alert(i),window.location.href=n.toDataURL()}else{var s;if("undefined"==typeof o)o="png",s="image/png";else switch(o){case"png":s="image/png";break;case"jpeg":s="image/jpeg";break;case"jpg":s="image/jpeg";break;default:s="image/png"}var a="image/octet-stream",h=n.toDataURL(s);h=h.replace(s,a),r.prototype.downloadFile(h,e,o)}},r.prototype.saveFrames=function(t,e,n,i,s){var a=n||3;a=r.prototype.constrain(a,0,15),a=1e3*a;var h=i||15;h=r.prototype.constrain(h,0,22);var p=0,u=r.prototype._makeFrame,l=this._curElement.elt,c=setInterval(function(){u(t+p,e,l),p++},1e3/h);setTimeout(function(){if(clearInterval(c),s)s(o);else for(var t=0;t<o.length;t++){var e=o[t];r.prototype.downloadFile(e.imageData,e.filename,e.ext)}o=[]},a+.01)},r.prototype._makeFrame=function(t,e,r){var n;n=this?this._curElement.elt:r;var i;if(e)switch(e.toLowerCase()){case"png":i="image/png";break;case"jpeg":i="image/jpeg";break;case"jpg":i="image/jpeg";break;default:i="image/png"}else e="png",i="image/png";var s="image/octet-stream",a=n.toDataURL(i);a=a.replace(i,s);var h={};h.imageData=a,h.filename=t,h.ext=e,o.push(h)},r}({},core),outputtext_area=function(t,e){"use strict";var r=e;return r.prototype.print=window.console&&console.log?console.log.bind(console):function(){},r.prototype.println=r.prototype.print,r}({},core),renderingrendering=function(t,e,r){var o=e,r=r;return o.prototype.createCanvas=function(t,e,r){var n;return r?(n=document.createElement("canvas"),n.id="defaultCanvas"):n=this.canvas,this._setupDone||(n.className+=" p5_hidden",n.style.visibility="hidden"),this._userNode?this._userNode.appendChild(n):document.body.appendChild(n),this._defaultGraphics||(this._defaultGraphics=new o.Graphics(n,this,!0),this._elements.push(this._defaultGraphics)),this._defaultGraphics.resize(t,e),this._defaultGraphics._applyDefaults(),this._defaultGraphics},o.prototype.resizeCanvas=function(t,e){this._defaultGraphics&&(this._defaultGraphics.resize(t,e),this._defaultGraphics._applyDefaults(),this.redraw())},o.prototype.noCanvas=function(){this.canvas&&this.canvas.parentNode.removeChild(this.canvas)},o.prototype.createGraphics=function(t,e){var r=document.createElement("canvas"),n=this._userNode||document.body;n.appendChild(r);var i=new o.Graphics(r,this,!1);this._elements.push(i);for(var s in o.prototype)i.hasOwnProperty(s)||(i[s]="function"==typeof o.prototype[s]?o.prototype[s].bind(i):o.prototype[s]);return i.resize(t,e),i._applyDefaults(),i},o.prototype.blendMode=function(t){if(t!==r.BLEND&&t!==r.DARKEST&&t!==r.LIGHTEST&&t!==r.DIFFERENCE&&t!==r.MULTIPLY&&t!==r.EXCLUSION&&t!==r.SCREEN&&t!==r.REPLACE&&t!==r.OVERLAY&&t!==r.HARD_LIGHT&&t!==r.SOFT_LIGHT&&t!==r.DODGE&&t!==r.BURN&&t!==r.ADD&&t!==r.NORMAL)throw new Error("Mode "+t+" not recognized.");this.drawingContext.globalCompositeOperation=t},o}({},core,constants),shape2d_primitives=function(t,e,r,o){"use strict";var n=e,r=r,o=o;return n.prototype.arc=function(t,e,n,i,s,a,h){if(this._doStroke||this._doFill){this._angleMode===o.DEGREES&&(s=this.radians(s),a=this.radians(a));var p=this.drawingContext,u=r.arcModeAdjust(t,e,n,i,this._ellipseMode),l=u.h>u.w?u.h/2:u.w/2,c=u.h>u.w?u.w/u.h:1,d=u.h>u.w?1:u.h/u.w;return p.save(),p.scale(c,d),p.beginPath(),p.arc(u.x,u.y,l,s,a),this._doStroke&&p.stroke(),h===o.CHORD||h===o.OPEN?p.closePath():(h===o.PIE||void 0===h)&&(p.lineTo(u.x,u.y),p.closePath()),this._doFill&&p.fill(),this._doStroke&&h!==o.OPEN&&void 0!==h&&p.stroke(),p.restore(),this}},n.prototype.ellipse=function(t,e,o,n){if(this._doStroke||this._doFill){o=Math.abs(o),n=Math.abs(n);var i=this.drawingContext,s=r.modeAdjust(t,e,o,n,this._ellipseMode);if(i.beginPath(),o===n)i.arc(s.x+s.w/2,s.y+s.w/2,s.w/2,0,2*Math.PI,!1);else{var a=.5522848,h=s.w/2*a,p=s.h/2*a,u=s.x+s.w,l=s.y+s.h,c=s.x+s.w/2,d=s.y+s.h/2;i.moveTo(s.x,d),i.bezierCurveTo(s.x,d-p,c-h,s.y,c,s.y),i.bezierCurveTo(c+h,s.y,u,d-p,u,d),i.bezierCurveTo(u,d+p,c+h,l,c,l),i.bezierCurveTo(c-h,l,s.x,d+p,s.x,d),i.closePath()}return this._doFill&&i.fill(),this._doStroke&&i.stroke(),this}},n.prototype.line=function(t,e,r,o){if(this._doStroke){var n=this.drawingContext;if("rgba(0,0,0,0)"!==n.strokeStyle)return n.beginPath(),n.moveTo(t,e),n.lineTo(r,o),n.stroke(),this}},n.prototype.point=function(t,e){if(this._doStroke){var r=this.drawingContext,n=r.strokeStyle,i=r.fillStyle;if("rgba(0,0,0,0)"!==n)return t=Math.round(t),e=Math.round(e),r.fillStyle=n,r.lineWidth>1?(r.beginPath(),r.arc(t,e,r.lineWidth/2,0,o.TWO_PI,!1),r.fill()):r.fillRect(t,e,1,1),r.fillStyle=i,this}},n.prototype.quad=function(t,e,r,o,n,i,s,a){if(this._doStroke||this._doFill){var h=this.drawingContext;return h.beginPath(),h.moveTo(t,e),h.lineTo(r,o),h.lineTo(n,i),h.lineTo(s,a),h.closePath(),this._doFill&&h.fill(),this._doStroke&&h.stroke(),this}},n.prototype.rect=function(t,e,o,n){if(this._doStroke||this._doFill){var i=r.modeAdjust(t,e,o,n,this._rectMode),s=this.drawingContext;return this._doStroke&&s.lineWidth%2===1&&s.translate(.5,.5),s.beginPath(),s.rect(i.x,i.y,i.w,i.h),this._doFill&&s.fill(),this._doStroke&&s.stroke(),this._doStroke&&s.lineWidth%2===1&&s.translate(-.5,-.5),this}},n.prototype.triangle=function(t,e,r,o,n,i){if(this._doStroke||this._doFill){var s=this.drawingContext;return s.beginPath(),s.moveTo(t,e),s.lineTo(r,o),s.lineTo(n,i),s.closePath(),this._doFill&&s.fill(),this._doStroke&&s.stroke(),this}},n}({},core,canvas,constants),shapeattributes=function(t,e,r){"use strict";var o=e,r=r;return o.prototype._rectMode=r.CORNER,o.prototype._ellipseMode=r.CENTER,o.prototype.ellipseMode=function(t){return(t===r.CORNER||t===r.CORNERS||t===r.RADIUS||t===r.CENTER)&&(this._ellipseMode=t),this},o.prototype.noSmooth=function(){return this.drawingContext.mozImageSmoothingEnabled=!1,this.drawingContext.webkitImageSmoothingEnabled=!1,this},o.prototype.rectMode=function(t){return(t===r.CORNER||t===r.CORNERS||t===r.RADIUS||t===r.CENTER)&&(this._rectMode=t),this},o.prototype.smooth=function(){return this.drawingContext.mozImageSmoothingEnabled=!0,this.drawingContext.webkitImageSmoothingEnabled=!0,this},o.prototype.strokeCap=function(t){return(t===r.ROUND||t===r.SQUARE||t===r.PROJECT)&&(this.drawingContext.lineCap=t),this},o.prototype.strokeJoin=function(t){return(t===r.ROUND||t===r.BEVEL||t===r.MITER)&&(this.drawingContext.lineJoin=t),this},o.prototype.strokeWeight=function(t){return this.drawingContext.lineWidth="undefined"==typeof t||0===t?1e-4:t,this},o}({},core,constants),shapecurves=function(t,e){"use strict";var r=e,o=20,n=20;return r.prototype._curveTightness=0,r.prototype.bezier=function(t,e,r,o,n,i,s,a){return this._doStroke?(this.beginShape(),this.vertex(t,e),this.bezierVertex(r,o,n,i,s,a),this.endShape(),this.stroke(),this):void 0},r.prototype.bezierDetail=function(t){return o=t,this},r.prototype.bezierPoint=function(t,e,r,o,n){var i=1-n;return Math.pow(i,3)*t+3*Math.pow(i,2)*n*e+3*i*Math.pow(n,2)*r+Math.pow(n,3)*o},r.prototype.bezierTangent=function(t,e,r,o,n){var i=1-n;return 3*o*Math.pow(n,2)-3*r*Math.pow(n,2)+6*r*i*n-6*e*i*n+3*e*Math.pow(i,2)-3*t*Math.pow(i,2)},r.prototype.curve=function(t,e,r,o,n,i,s,a){return this._doStroke?(this.beginShape(),this.curveVertex(t,e),this.curveVertex(r,o),this.curveVertex(n,i),this.curveVertex(s,a),this.endShape(),this.stroke(),this):void 0},r.prototype.curveDetail=function(t){return n=t,this},r.prototype.curveTightness=function(t){this._setProperty("_curveTightness",t)},r.prototype.curvePoint=function(t,e,r,o,n){var i=n*n*n,s=n*n,a=-.5*i+s-.5*n,h=1.5*i-2.5*s+1,p=-1.5*i+2*s+.5*n,u=.5*i-.5*s;return t*a+e*h+r*p+o*u},r.prototype.curveTangent=function(t,e,r,o,n){var i=n*n,s=-3*i/2+2*n-.5,a=9*i/2-5*n,h=-9*i/2+4*n+.5,p=3*i/2-n;return t*s+e*a+r*h+o*p},r.prototype.curveTightness=function(){throw"not yet implemented"},r}({},core),shapevertex=function(t,e,r){"use strict";var o=e,r=r,n=null,i=[],s=[],a=!1,h=!1,p=!1,u=!1;return o.prototype._doFillStrokeClose=function(){this._doFill&&this.drawingContext.fill(),this._doStroke&&this.drawingContext.stroke(),this.drawingContext.closePath()},o.prototype.beginContour=function(){return s=[],u=!0,this},o.prototype.beginShape=function(t){return n=t===r.POINTS||t===r.LINES||t===r.TRIANGLES||t===r.TRIANGLE_FAN||t===r.TRIANGLE_STRIP||t===r.QUADS||t===r.QUAD_STRIP?t:null,i=[],s=[],this},o.prototype.bezierVertex=function(){if(0===i.length)throw"vertex() must be used once before calling bezierVertex()";a=!0;for(var t=[],e=0;e<arguments.length;e++)t[e]=arguments[e];return t.isVert=!1,u?s.push(t):i.push(t),this},o.prototype.curveVertex=function(t,e){return h=!0,this.vertex(t,e),this},o.prototype.endContour=function(){var t=s[0].slice();t.isVert=s[0].isVert,t.moveTo=!1,s.push(t),i.push(i[0]);for(var e=0;e<s.length;e++)i.push(s[e]);return this},o.prototype.endShape=function(t){if(0===i.length)return this;if(!this._doStroke&&!this._doFill)return this;var e,o=t===r.CLOSE;o&&!u&&i.push(i[0]);var s,l,c=i.length;if(!h||n!==r.POLYGON&&null!==n)if(!a||n!==r.POLYGON&&null!==n)if(!p||n!==r.POLYGON&&null!==n)if(n===r.POINTS)for(s=0;c>s;s++)e=i[s],this._doStroke&&this.stroke(e[6]),this.point(e[0],e[1]);else if(n===r.LINES)for(s=0;c>s+1;s+=2)e=i[s],this._doStroke&&this.stroke(i[s+1][6]),this.line(e[0],e[1],i[s+1][0],i[s+1][1]);else if(n===r.TRIANGLES)for(s=0;c>s+2;s+=3)e=i[s],this.drawingContext.beginPath(),this.drawingContext.moveTo(e[0],e[1]),this.drawingContext.lineTo(i[s+1][0],i[s+1][1]),this.drawingContext.lineTo(i[s+2][0],i[s+2][1]),this.drawingContext.lineTo(e[0],e[1]),this._doFill&&(this.fill(i[s+2][5]),this.drawingContext.fill()),this._doStroke&&(this.stroke(i[s+2][6]),this.drawingContext.stroke()),this.drawingContext.closePath();else if(n===r.TRIANGLE_STRIP)for(s=0;c>s+1;s++)e=i[s],this.drawingContext.beginPath(),this.drawingContext.moveTo(i[s+1][0],i[s+1][1]),this.drawingContext.lineTo(e[0],e[1]),this._doStroke&&this.stroke(i[s+1][6]),this._doFill&&this.fill(i[s+1][5]),c>s+2&&(this.drawingContext.lineTo(i[s+2][0],i[s+2][1]),this._doStroke&&this.stroke(i[s+2][6]),this._doFill&&this.fill(i[s+2][5])),this._doFillStrokeClose();else if(n===r.TRIANGLE_FAN){if(c>2)for(this.drawingContext.beginPath(),this.drawingContext.moveTo(i[0][0],i[0][1]),this.drawingContext.lineTo(i[1][0],i[1][1]),this.drawingContext.lineTo(i[2][0],i[2][1]),this._doFill&&this.fill(i[2][5]),this._doStroke&&this.stroke(i[2][6]),this._doFillStrokeClose(),s=3;c>s;s++)e=i[s],this.drawingContext.beginPath(),this.drawingContext.moveTo(i[0][0],i[0][1]),this.drawingContext.lineTo(i[s-1][0],i[s-1][1]),this.drawingContext.lineTo(e[0],e[1]),this._doFill&&this.fill(e[5]),this._doStroke&&this.stroke(e[6]),this._doFillStrokeClose()}else if(n===r.QUADS)for(s=0;c>s+3;s+=4){for(e=i[s],this.drawingContext.beginPath(),this.drawingContext.moveTo(e[0],e[1]),l=1;4>l;l++)this.drawingContext.lineTo(i[s+l][0],i[s+l][1]);this.drawingContext.lineTo(e[0],e[1]),this._doFill&&this.fill(i[s+3][5]),this._doStroke&&this.stroke(i[s+3][6]),this._doFillStrokeClose()}else if(n===r.QUAD_STRIP){if(c>3)for(s=0;c>s+1;s+=2)e=i[s],this.drawingContext.beginPath(),c>s+3?(this.drawingContext.moveTo(i[s+2][0],i[s+2][1]),this.drawingContext.lineTo(e[0],e[1]),this.drawingContext.lineTo(i[s+1][0],i[s+1][1]),this.drawingContext.lineTo(i[s+3][0],i[s+3][1]),this._doFill&&this.fill(i[s+3][5]),this._doStroke&&this.stroke(i[s+3][6])):(this.drawingContext.moveTo(e[0],e[1]),this.drawingContext.lineTo(i[s+1][0],i[s+1][1])),this._doFillStrokeClose()}else{for(this.drawingContext.beginPath(),this.drawingContext.moveTo(i[0][0],i[0][1]),s=1;c>s;s++)e=i[s],e.isVert&&(e.moveTo?this.drawingContext.moveTo(e[0],e[1]):this.drawingContext.lineTo(e[0],e[1]));this._doFillStrokeClose()}else{for(this.drawingContext.beginPath(),s=0;c>s;s++)i[s].isVert?i[s].moveTo?this.drawingContext.moveTo([0],i[s][1]):this.drawingContext.lineTo(i[s][0],i[s][1]):this.drawingContext.quadraticCurveTo(i[s][0],i[s][1],i[s][2],i[s][3]);this._doFillStrokeClose()}else{for(this.drawingContext.beginPath(),s=0;c>s;s++)i[s].isVert?i[s].moveTo?this.drawingContext.moveTo(i[s][0],i[s][1]):this.drawingContext.lineTo(i[s][0],i[s][1]):this.drawingContext.bezierCurveTo(i[s][0],i[s][1],i[s][2],i[s][3],i[s][4],i[s][5]);this._doFillStrokeClose()}else if(c>3){var d=[],f=1-this._curveTightness;for(this.drawingContext.beginPath(),this.drawingContext.moveTo(i[1][0],i[1][1]),s=1;c>s+2;s++)e=i[s],d[0]=[e[0],e[1]],d[1]=[e[0]+(f*i[s+1][0]-f*i[s-1][0])/6,e[1]+(f*i[s+1][1]-f*i[s-1][1])/6],d[2]=[i[s+1][0]+(f*i[s][0]-f*i[s+2][0])/6,i[s+1][1]+(f*i[s][1]-f*i[s+2][1])/6],d[3]=[i[s+1][0],i[s+1][1]],this.drawingContext.bezierCurveTo(d[1][0],d[1][1],d[2][0],d[2][1],d[3][0],d[3][1]);o&&this.drawingContext.lineTo(i[s+1][0],i[s+1][1]),this._doFillStrokeClose()}return h=!1,a=!1,p=!1,u=!1,o&&i.pop(),this},o.prototype.quadraticVertex=function(t,e,o,n){if(this._contourInited){var a={};return a.x=t,a.y=e,a.x3=o,a.y3=n,a.type=r.QUADRATIC,this._contourVertices.push(a),this}if(!(i.length>0))throw"vertex() must be used once before calling quadraticVertex()";p=!0;for(var h=[],l=0;l<arguments.length;l++)h[l]=arguments[l];return h.isVert=!1,u?s.push(h):i.push(h),this},o.prototype.vertex=function(t,e,r){var o=[];return o.isVert=!0,o[0]=t,o[1]=e,o[2]=0,o[3]=0,o[4]=0,o[5]=this.drawingContext.fillStyle,o[6]=this.drawingContext.strokeStyle,r&&(o.moveTo=r),u?(0===s.length&&(o.moveTo=!0),s.push(o)):i.push(o),this},o}({},core,constants),structure=function(t,e){"use strict";var r=e;return r.prototype.exit=function(){throw"exit() not implemented, see remove()"},r.prototype.noLoop=function(){this._loop=!1,this._drawInterval&&clearInterval(this._drawInterval)},r.prototype.loop=function(){this._loop=!0,this._draw()},r.prototype.push=function(){this.drawingContext.save(),this._styles.push({doStroke:this._doStroke,doFill:this._doFill,tint:this._tint,imageMode:this._imageMode,rectMode:this._rectMode,ellipseMode:this._ellipseMode,colorMode:this._colorMode,textFont:this.textFont,textLeading:this.textLeading,textSize:this.textSize,textStyle:this.textStyle})},r.prototype.pop=function(){this.drawingContext.restore();var t=this._styles.pop();this._doStroke=t.doStroke,this._doFill=t.doFill,this._tint=t.tint,this._imageMode=t.imageMode,this._rectMode=t.rectMode,this._ellipseMode=t.ellipseMode,this._colorMode=t.colorMode,this.textFont=t.textFont,this.textLeading=t.textLeading,this.textSize=t.textSize,this.textStyle=t.textStyle},r.prototype.pushStyle=function(){throw new Error("pushStyle() not used, see push()")},r.prototype.popStyle=function(){throw new Error("popStyle() not used, see pop()")},r.prototype.redraw=function(){var t=this._isGlobal?window:this;t.draw&&t.draw()},r.prototype.size=function(){throw"size() not implemented, see createCanvas()"},r}({},core),transform=function(t,e,r){"use strict";var o=e,r=r;return o.prototype.applyMatrix=function(t,e,r,o,n,i){return this.drawingContext.transform(t,e,r,o,n,i),this},o.prototype.popMatrix=function(){throw new Error("popMatrix() not used, see pop()")},o.prototype.printMatrix=function(){throw new Error("printMatrix() not implemented")},o.prototype.pushMatrix=function(){throw new Error("pushMatrix() not used, see push()")},o.prototype.resetMatrix=function(){return this.drawingContext.setTransform(),this},o.prototype.rotate=function(t){return this._angleMode===r.DEGREES&&(t=this.radians(t)),this.drawingContext.rotate(t),this},o.prototype.rotateX=function(){throw"not yet implemented"},o.prototype.rotateY=function(){throw"not yet implemented"},o.prototype.scale=function(){var t=1,e=1;return 1===arguments.length?t=e=arguments[0]:(t=arguments[0],e=arguments[1]),this.drawingContext.scale(t,e),this},o.prototype.shearX=function(t){return this._angleMode===r.DEGREES&&(t=this.radians(t)),this.drawingContext.transform(1,0,this.tan(t),1,0,0),this},o.prototype.shearY=function(t){return this._angleMode===r.DEGREES&&(t=this.radians(t)),this.drawingContext.transform(1,this.tan(t),0,1,0,0),this},o.prototype.translate=function(t,e){return this.drawingContext.translate(t,e),this},o}({},core,constants,outputtext_area),typographyattributes=function(t,e,r){"use strict";var o=e,r=r;return o.prototype._textLeading=15,o.prototype._textFont="sans-serif",o.prototype._textSize=12,o.prototype._textStyle=r.NORMAL,o.prototype._textAscent=null,o.prototype._textDescent=null,o.prototype.textAlign=function(t){(t===r.LEFT||t===r.RIGHT||t===r.CENTER)&&(this.drawingContext.textAlign=t)},o.prototype.textLeading=function(t){this._setProperty("_textLeading",t)},o.prototype.textSize=function(t){this._setProperty("_textSize",t),this._applyTextProperties()},o.prototype.textStyle=function(t){(t===r.NORMAL||t===r.ITALIC||t===r.BOLD)&&(this._setProperty("_textStyle",t),this._applyTextProperties())},o.prototype.textWidth=function(t){return this.drawingContext.measureText(t).width},o.prototype.textAscent=function(){return null==this._textAscent&&this._updateTextMetrics(),this._textAscent},o.prototype.textDescent=function(){return null==this._textDescent&&this._updateTextMetrics(),this._textDescent},o.prototype._applyTextProperties=function(){this._setProperty("_textAscent",null),this._setProperty("_textDescent",null);var t=this._textStyle+" "+this._textSize+"px "+this._textFont;this.drawingContext.font=t},o.prototype._updateTextMetrics=function(){var t=document.createElement("span");t.style.fontFamily=this._textFont,t.style.fontSize=this._textSize+"px",t.innerHTML="ABCjgq|";var e=document.createElement("div");e.style.display="inline-block",e.style.width="1px",e.style.height="0px";var r=document.createElement("div");r.appendChild(t),r.appendChild(e),r.style.height="0px",r.style.overflow="hidden",document.body.appendChild(r),e.style.verticalAlign="baseline";var o=this._calculateOffset(e),n=this._calculateOffset(t),i=o[1]-n[1];e.style.verticalAlign="bottom",o=this._calculateOffset(e),n=this._calculateOffset(t);var s=o[1]-n[1],a=s-i;document.body.removeChild(r),this._setProperty("_textAscent",i),this._setProperty("_textDescent",a)},o.prototype._calculateOffset=function(t){var e=0,r=0;if(t.offsetParent){do e+=t.offsetLeft,r+=t.offsetTop;while(t=t.offsetParent)}else e+=t.offsetLeft,r+=t.offsetTop;return[e,r]},o}({},core,constants),typographyloading_displaying=function(t,e){"use strict";var r=e;return r.prototype.text=function(t,e,r,o,n){if("string"==typeof t){"undefined"!=typeof o&&(r+=this._textLeading,n+=r),t=t.replace(/(\t)/g,"  ");for(var i=t.split("\n"),s=0;s<i.length;s++){for(var a="",h=i[s].split(" "),p=0;p<h.length;p++)if(r+this._textLeading<=n||"undefined"==typeof n){var u=a+h[p]+" ",l=this.drawingContext.measureText(u),c=l.width;"undefined"!=typeof o&&c>o?(this._doFill&&this.drawingContext.fillText(a,e,r),this._doStroke&&this.drawingContext.strokeText(a,e,r),a=h[p]+" ",r+=this._textLeading):a=u}this._doFill&&this.drawingContext.fillText(a,e,r),this._doStroke&&this.drawingContext.strokeText(a,e,r),r+=this._textLeading}}},r.prototype.textFont=function(t){this._setProperty("_textFont",t),this._applyTextProperties()},r}({},core),src_app=function(t,e){"use strict";var r=e,o=function(){window.PHANTOMJS||(window.setup&&"function"==typeof window.setup||window.draw&&"function"==typeof window.draw)&&new r};return"complete"===document.readyState?o():window.addEventListener("load",o,!1),window.p5=r,r}({},core,p5Color,p5Element,p5Graphics,p5Image,p5Vector,p5TableRow,p5Table,colorcreating_reading,colorsetting,constants,dataconversion,dataarray_functions,datastring_functions,environment,imageimage,imageloading_displaying,imagepixels,inputfiles,inputkeyboard,inputmouse,inputtime_date,inputtouch,mathmath,mathcalculation,mathrandom,mathnoise,mathtrigonometry,outputfiles,outputimage,outputtext_area,renderingrendering,shape2d_primitives,shapeattributes,shapecurves,shapevertex,structure,transform,typographyattributes,typographyloading_displaying);
diff --git a/VanillaJavascriptVisualisation/lib/recurrent.js b/VanillaJavascriptVisualisation/lib/recurrent.js
new file mode 100644
index 0000000..d904a16
--- /dev/null
+++ b/VanillaJavascriptVisualisation/lib/recurrent.js
@@ -0,0 +1,1141 @@
+// the Recurrent library with DCT compression and CoSyNe neuroevolution
+var R = {};
+
+(function(global) {
+  "use strict";
+
+  // Utility fun
+  function assert(condition, message) {
+    // from http://stackoverflow.com/questions/15313418/javascript-assert
+    if (!condition) {
+      message = message || "Assertion failed";
+      if (typeof Error !== "undefined") {
+        throw new Error(message);
+      }
+      throw message; // Fallback
+    }
+  }
+
+  // Random numbers utils
+  var return_v = false;
+  var v_val = 0.0;
+  var gaussRandom = function() {
+    if(return_v) {
+      return_v = false;
+      return v_val;
+    }
+    var u = 2*Math.random()-1;
+    var v = 2*Math.random()-1;
+    var r = u*u + v*v;
+    if(r === 0 || r > 1) return gaussRandom();
+    var c = Math.sqrt(-2*Math.log(r)/r);
+    v_val = v*c; // cache this
+    return_v = true;
+    return u*c;
+  };
+  var randf = function(a, b) { return Math.random()*(b-a)+a; };
+  var randi = function(a, b) { return Math.floor(Math.random()*(b-a)+a); };
+  var randn = function(mu, std){ return mu+gaussRandom()*std; };
+
+  // helper function returns array of zeros of length n
+  // and uses typed arrays if available
+  var zeros = function(n) {
+    if(typeof(n)==='undefined' || isNaN(n)) { return []; }
+    if(typeof ArrayBuffer === 'undefined') {
+      // lacking browser support
+      var arr = new Array(n);
+      for(var i=0;i<n;i++) { arr[i] = 0; }
+      return arr;
+    } else {
+      return new Float64Array(n);
+    }
+  };
+
+  var shuffle = function(origArray) {
+    // returns a newArray which is a shuffled version of origArray
+    var i, randomIndex;
+    var temp;
+    var N = origArray.length;
+    var result = zeros(N);
+    for (i=0;i<N;i++) {
+      result[i] = origArray[i];
+    }
+    for (i=0;i<N;i++) {
+      // swaps i with randomIndex
+      randomIndex = randi(0, N);
+      temp = result[randomIndex];
+      result[randomIndex] = result[i];
+      result[i] = temp;
+    }
+    return result;
+  };
+
+  // Mat holds a matrix
+  var Mat = function(n,d) {
+    // n is number of rows d is number of columns
+    this.n = n;
+    this.d = d;
+    this.w = zeros(n * d);
+    this.dw = zeros(n * d);
+  };
+  Mat.prototype = {
+    get: function(row, col) {
+      // slow but careful accessor function
+      // we want row-major order
+      var ix = (this.d * row) + col;
+      assert(ix >= 0 && ix < this.w.length);
+      return this.w[ix];
+    },
+    set: function(row, col, v) {
+      // slow but careful accessor function
+      var ix = (this.d * row) + col;
+      assert(ix >= 0 && ix < this.w.length);
+      this.w[ix] = v;
+    },
+    copy: function() {
+      // return a copy of Mat
+      var result = new Mat(this.n, this.d);
+      var i, len;
+      len = this.n*this.d;
+      for (i = 0; i < len; i++) {
+        result.w[i] = this.w[i];
+        result.dw[i] = this.dw[i];
+      }
+      return result;
+    },
+    toString: function(precision_) {
+      var result_w = '[';
+      var i, j;
+      var n, d;
+      var ix;
+      var precision = 10e-4 || precision_;
+      precision = 1/precision;
+      n = this.n;
+      d = this.d;
+      for (i=0;i<n;i++) {
+        for (j=0;j<d;j++) {
+          ix = i*d+j;
+          assert(ix >= 0 && ix < this.w.length);
+          result_w+=''+Math.round(precision*this.w[ix])/precision+',\t';
+        }
+        result_w+='\n';
+      }
+      result_w+=']';
+      return result_w;
+    },
+    print: function() {
+      console.log(this.toString());
+    },
+    dct2: function() {
+      // inefficient implementation of discrete cosine transform (2d)
+      // ref: http://www.mathworks.com/help/images/ref/dct2.html
+      var n = this.n;
+      var d = this.d;
+      var B = new Mat(n, d); // resulting matrix
+      var i, j, k, l;
+      var temp;
+      for (i=0;i<n;i++) {
+        for (j=0;j<d;j++) {
+          temp=0;
+          for (k=0;k<n;k++) {
+            for (l=0;l<d;l++) {
+              temp=temp+this.w[k*d+l]*Math.cos(i*Math.PI*((2*k)+1)/(2*n))*Math.cos(j*Math.PI*((2*l)+1)/(2*d));
+            }
+          }
+          if ((i===0)&&(j!==0)) temp*=1/Math.SQRT2;
+          if ((j===0)&&(i!==0)) temp*=1/Math.SQRT2;
+          if ((j===0)&&(i===0)) temp*=0.5;
+          B.w[i*d+j]=temp*2/Math.sqrt(n*d);
+        }
+      }
+      return B;
+    },
+    idct2: function() {
+      // inefficient implementation of inverse discrete cosine transform (2d)
+      // ref: http://www.mathworks.com/help/images/ref/idct2.html
+      var n = this.n;
+      var d = this.d;
+      var A = new Mat(n, d); // resulting matrix
+      var i, j, k, l;
+      var temp;
+      for (i=0;i<n;i++) {
+        for (j=0;j<d;j++) {
+          A.w[i*d+j]=0;
+          for (k=0;k<n;k++) {
+            for (l=0;l<d;l++) {
+              temp=this.w[k*d+l]*Math.cos((((2*i)+1)*k*Math.PI)/(2*n))*Math.cos((((2*j)+1)*l*Math.PI)/(2*d));
+
+              if ((k===0)&&(l===0)) temp*=0.5;
+              if ((k!==0)&&(l===0)) temp*=1/Math.SQRT2;
+              if ((k===0)&&(l!==0)) temp*=1/Math.SQRT2;
+
+              A.w[i*d+j]+=temp*2/Math.sqrt(n*d);
+
+            }
+          }
+        }
+      }
+      return A;
+    },
+    toJSON: function() {
+      var json = {};
+      json.n = this.n;
+      json.d = this.d;
+      json.w = this.w;
+      return json;
+    },
+    fromJSON: function(json) {
+      this.n = json.n;
+      this.d = json.d;
+      this.w = zeros(this.n * this.d);
+      this.dw = zeros(this.n * this.d);
+      for(var i=0,n=this.n * this.d;i<n;i++) {
+        this.w[i] = json.w[i]; // copy over weights
+      }
+    }
+  };
+
+  // return Mat but filled with random numbers from gaussian
+  var RandMat = function(n,d,mu,std) {
+    var m = new Mat(n, d);
+    fillRandn(m,mu || 0,std || 0.08); // kind of :P
+    return m;
+  };
+
+  // Mat utils
+  // fill matrix with random gaussian numbers
+  var fillRandn = function(m, mu, std) { for(var i=0,n=m.w.length;i<n;i++) { m.w[i] = randn(mu, std); } };
+  var fillRand = function(m, lo, hi) { for(var i=0,n=m.w.length;i<n;i++) { m.w[i] = randf(lo, hi); } };
+
+  // Transformer definitions
+  var Graph = function(needs_backprop) {
+    if(typeof needs_backprop === 'undefined') { needs_backprop = true; }
+    this.needs_backprop = needs_backprop;
+
+    // this will store a list of functions that perform backprop,
+    // in their forward pass order. So in backprop we will go
+    // backwards and evoke each one
+    this.backprop = [];
+  };
+  Graph.prototype = {
+    backward: function() {
+      for(var i=this.backprop.length-1;i>=0;i--) {
+        this.backprop[i](); // tick!
+      }
+    },
+    rowPluck: function(m, ix) {
+      // pluck a row of m with index ix and return it as col vector
+      assert(ix >= 0 && ix < m.n);
+      var d = m.d;
+      var out = new Mat(d, 1);
+      for(var i=0,n=d;i<n;i++){ out.w[i] = m.w[d * ix + i]; } // copy over the data
+
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0,n=d;i<n;i++){ m.dw[d * ix + i] += out.dw[i]; }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+    tanh: function(m) {
+      // tanh nonlinearity
+      var out = new Mat(m.n, m.d);
+      var n = m.w.length;
+      for(var i=0;i<n;i++) {
+        out.w[i] = Math.tanh(m.w[i]);
+      }
+
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0;i<n;i++) {
+            // grad for z = tanh(x) is (1 - z^2)
+            var mwi = out.w[i];
+            m.dw[i] += (1.0 - mwi * mwi) * out.dw[i];
+          }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+    sigmoid: function(m) {
+      // sigmoid nonlinearity
+      var out = new Mat(m.n, m.d);
+      var n = m.w.length;
+      for(var i=0;i<n;i++) {
+        out.w[i] = sig(m.w[i]);
+      }
+
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0;i<n;i++) {
+            // grad for z = sigmoid(x) is z(1 - z)
+            var mwi = out.w[i];
+            m.dw[i] += mwi * (1.0 - mwi) * out.dw[i];
+          }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+    relu: function(m) {
+      var out = new Mat(m.n, m.d);
+      var n = m.w.length;
+      for(var i=0;i<n;i++) {
+        out.w[i] = Math.max(0, m.w[i]); // relu
+      }
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0;i<n;i++) {
+            m.dw[i] += m.w[i] > 0 ? out.dw[i] : 0.0;
+          }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+    mul: function(m1, m2) {
+      // multiply matrices m1 * m2
+      assert(m1.d === m2.n, 'matmul dimensions misaligned');
+
+      var n = m1.n;
+      var d = m2.d;
+      var out = new Mat(n,d);
+      for(var i=0;i<m1.n;i++) { // loop over rows of m1
+        for(var j=0;j<m2.d;j++) { // loop over cols of m2
+          var dot = 0.0;
+          for(var k=0;k<m1.d;k++) { // dot product loop
+            dot += m1.w[m1.d*i+k] * m2.w[m2.d*k+j];
+          }
+          out.w[d*i+j] = dot;
+        }
+      }
+
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0;i<m1.n;i++) { // loop over rows of m1
+            for(var j=0;j<m2.d;j++) { // loop over cols of m2
+              for(var k=0;k<m1.d;k++) { // dot product loop
+                var b = out.dw[d*i+j];
+                m1.dw[m1.d*i+k] += m2.w[m2.d*k+j] * b;
+                m2.dw[m2.d*k+j] += m1.w[m1.d*i+k] * b;
+              }
+            }
+          }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+    add: function(m1, m2) {
+      assert(m1.w.length === m2.w.length);
+
+      var out = new Mat(m1.n, m1.d);
+      for(var i=0,n=m1.w.length;i<n;i++) {
+        out.w[i] = m1.w[i] + m2.w[i];
+      }
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0,n=m1.w.length;i<n;i++) {
+            m1.dw[i] += out.dw[i];
+            m2.dw[i] += out.dw[i];
+          }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+    eltmul: function(m1, m2) {
+      assert(m1.w.length === m2.w.length);
+
+      var out = new Mat(m1.n, m1.d);
+      for(var i=0,n=m1.w.length;i<n;i++) {
+        out.w[i] = m1.w[i] * m2.w[i];
+      }
+      if(this.needs_backprop) {
+        var backward = function() {
+          for(var i=0,n=m1.w.length;i<n;i++) {
+            m1.dw[i] += m2.w[i] * out.dw[i];
+            m2.dw[i] += m1.w[i] * out.dw[i];
+          }
+        };
+        this.backprop.push(backward);
+      }
+      return out;
+    },
+  };
+
+  var softmax = function(m) {
+      var out = new Mat(m.n, m.d); // probability volume
+      var maxval = -999999;
+      var i, n;
+      for(i=0,n=m.w.length;i<n;i++) { if(m.w[i] > maxval) maxval = m.w[i]; }
+
+      var s = 0.0;
+      for(i=0,n=m.w.length;i<n;i++) {
+        out.w[i] = Math.exp(m.w[i] - maxval);
+        s += out.w[i];
+      }
+      for(i=0,n=m.w.length;i<n;i++) { out.w[i] /= s; }
+
+      // no backward pass here needed
+      // since we will use the computed probabilities outside
+      // to set gradients directly on m
+      return out;
+  };
+
+  var Solver = function() {
+    this.decay_rate = 0.999;
+    this.smooth_eps = 1e-8;
+    this.step_cache = {};
+  };
+  Solver.prototype = {
+    step: function(model, step_size, regc, clipval) {
+      // perform parameter update
+      var solver_stats = {};
+      var num_clipped = 0;
+      var num_tot = 0;
+      for(var k in model) {
+        if(model.hasOwnProperty(k)) {
+          var m = model[k]; // mat ref
+          if(!(k in this.step_cache)) { this.step_cache[k] = new Mat(m.n, m.d); }
+          var s = this.step_cache[k];
+          for(var i=0,n=m.w.length;i<n;i++) {
+
+            // rmsprop adaptive learning rate
+            var mdwi = m.dw[i];
+            s.w[i] = s.w[i] * this.decay_rate + (1.0 - this.decay_rate) * mdwi * mdwi;
+
+            // gradient clip
+            if(mdwi > clipval) {
+              mdwi = clipval;
+              num_clipped++;
+            }
+            if(mdwi < -clipval) {
+              mdwi = -clipval;
+              num_clipped++;
+            }
+            num_tot++;
+
+            // update (and regularize)
+            m.w[i] += - step_size * mdwi / Math.sqrt(s.w[i] + this.smooth_eps) - regc * m.w[i];
+            m.dw[i] = 0; // reset gradients for next iteration
+          }
+        }
+      }
+      solver_stats.ratio_clipped = num_clipped*1.0/num_tot;
+      return solver_stats;
+    }
+  };
+
+  var initLSTM = function(input_size, hidden_sizes, output_size) {
+    // hidden size should be a list
+
+    var model = {};
+    var hidden_size;
+    var prev_size;
+    for(var d=0;d<hidden_sizes.length;d++) { // loop over depths
+      prev_size = d === 0 ? input_size : hidden_sizes[d - 1];
+      hidden_size = hidden_sizes[d];
+
+      // gates parameters
+      model['Wix'+d] = new RandMat(hidden_size, prev_size , 0, 0.08);
+      model['Wih'+d] = new RandMat(hidden_size, hidden_size , 0, 0.08);
+      model['bi'+d] = new Mat(hidden_size, 1);
+      model['Wfx'+d] = new RandMat(hidden_size, prev_size , 0, 0.08);
+      model['Wfh'+d] = new RandMat(hidden_size, hidden_size , 0, 0.08);
+      model['bf'+d] = new Mat(hidden_size, 1);
+      model['Wox'+d] = new RandMat(hidden_size, prev_size , 0, 0.08);
+      model['Woh'+d] = new RandMat(hidden_size, hidden_size , 0, 0.08);
+      model['bo'+d] = new Mat(hidden_size, 1);
+      // cell write params
+      model['Wcx'+d] = new RandMat(hidden_size, prev_size , 0, 0.08);
+      model['Wch'+d] = new RandMat(hidden_size, hidden_size , 0, 0.08);
+      model['bc'+d] = new Mat(hidden_size, 1);
+    }
+    // decoder params
+    model.Whd = new RandMat(output_size, hidden_size, 0, 0.08);
+    model.bd = new Mat(output_size, 1);
+    return model;
+  };
+
+  var forwardLSTM = function(G, model, hidden_sizes, x, prev) {
+    // forward prop for a single tick of LSTM
+    // G is graph to append ops to
+    // model contains LSTM parameters
+    // x is 1D column vector with observation
+    // prev is a struct containing hidden and cell
+    // from previous iteration
+
+    var hidden_prevs;
+    var cell_prevs;
+    var d;
+
+    if(typeof prev.h === 'undefined') {
+      hidden_prevs = [];
+      cell_prevs = [];
+      for(d=0;d<hidden_sizes.length;d++) {
+        hidden_prevs.push(new R.Mat(hidden_sizes[d],1));
+        cell_prevs.push(new R.Mat(hidden_sizes[d],1));
+      }
+    } else {
+      hidden_prevs = prev.h;
+      cell_prevs = prev.c;
+    }
+
+    var hidden = [];
+    var cell = [];
+    for(d=0;d<hidden_sizes.length;d++) {
+
+      var input_vector = d === 0 ? x : hidden[d-1];
+      var hidden_prev = hidden_prevs[d];
+      var cell_prev = cell_prevs[d];
+
+      // input gate
+      var h0 = G.mul(model['Wix'+d], input_vector);
+      var h1 = G.mul(model['Wih'+d], hidden_prev);
+      var input_gate = G.sigmoid(G.add(G.add(h0,h1),model['bi'+d]));
+
+      // forget gate
+      var h2 = G.mul(model['Wfx'+d], input_vector);
+      var h3 = G.mul(model['Wfh'+d], hidden_prev);
+      var forget_gate = G.sigmoid(G.add(G.add(h2, h3),model['bf'+d]));
+
+      // output gate
+      var h4 = G.mul(model['Wox'+d], input_vector);
+      var h5 = G.mul(model['Woh'+d], hidden_prev);
+      var output_gate = G.sigmoid(G.add(G.add(h4, h5),model['bo'+d]));
+
+      // write operation on cells
+      var h6 = G.mul(model['Wcx'+d], input_vector);
+      var h7 = G.mul(model['Wch'+d], hidden_prev);
+      var cell_write = G.tanh(G.add(G.add(h6, h7),model['bc'+d]));
+
+      // compute new cell activation
+      var retain_cell = G.eltmul(forget_gate, cell_prev); // what do we keep from cell
+      var write_cell = G.eltmul(input_gate, cell_write); // what do we write to cell
+      var cell_d = G.add(retain_cell, write_cell); // new cell contents
+
+      // compute hidden state as gated, saturated cell activations
+      var hidden_d = G.eltmul(output_gate, G.tanh(cell_d));
+
+      hidden.push(hidden_d);
+      cell.push(cell_d);
+    }
+
+    // one decoder to outputs at end
+    var output = G.add(G.mul(model.Whd, hidden[hidden.length - 1]),model.bd);
+
+    // return cell memory, hidden representation and output
+    return {'h':hidden, 'c':cell, 'o' : output};
+  };
+
+  var initRNN = function(input_size, hidden_sizes, output_size) {
+    // hidden size should be a list
+
+    var model = {};
+    var hidden_size, prev_size;
+    for(var d=0;d<hidden_sizes.length;d++) { // loop over depths
+      prev_size = d === 0 ? input_size : hidden_sizes[d - 1];
+      hidden_size = hidden_sizes[d];
+      model['Wxh'+d] = new R.RandMat(hidden_size, prev_size , 0, 0.08);
+      model['Whh'+d] = new R.RandMat(hidden_size, hidden_size, 0, 0.08);
+      model['bhh'+d] = new R.Mat(hidden_size, 1);
+    }
+    // decoder params
+    model.Whd = new RandMat(output_size, hidden_size, 0, 0.08);
+    model.bd = new Mat(output_size, 1);
+    return model;
+  };
+
+   var forwardRNN = function(G, model, hidden_sizes, x, prev) {
+    // forward prop for a single tick of RNN
+    // G is graph to append ops to
+    // model contains RNN parameters
+    // x is 1D column vector with observation
+    // prev is a struct containing hidden activations from last step
+
+    var hidden_prevs;
+    var d;
+    if(typeof prev.h === 'undefined') {
+      hidden_prevs = [];
+      for(d=0;d<hidden_sizes.length;d++) {
+        hidden_prevs.push(new R.Mat(hidden_sizes[d],1));
+      }
+    } else {
+      hidden_prevs = prev.h;
+    }
+
+    var hidden = [];
+    for(d=0;d<hidden_sizes.length;d++) {
+
+      var input_vector = d === 0 ? x : hidden[d-1];
+      var hidden_prev = hidden_prevs[d];
+
+      var h0 = G.mul(model['Wxh'+d], input_vector);
+      var h1 = G.mul(model['Whh'+d], hidden_prev);
+      var hidden_d = G.relu(G.add(G.add(h0, h1), model['bhh'+d]));
+
+      hidden.push(hidden_d);
+    }
+
+    // one decoder to outputs at end
+    var output = G.add(G.mul(model.Whd, hidden[hidden.length - 1]),model.bd);
+
+    // return cell memory, hidden representation and output
+    return {'h':hidden, 'o' : output};
+  };
+
+  var sig = function(x) {
+    // helper function for computing sigmoid
+    return 1.0/(1+Math.exp(-x));
+  };
+
+  var maxi = function(w) {
+    // argmax of array w
+    var maxv = w[0];
+    var maxix = 0;
+    for(var i=1,n=w.length;i<n;i++) {
+      var v = w[i];
+      if(v > maxv) {
+        maxix = i;
+        maxv = v;
+      }
+    }
+    return maxix;
+  };
+
+  var samplei = function(w) {
+    // sample argmax from w, assuming w are
+    // probabilities that sum to one
+    var r = randf(0,1);
+    var x = 0.0;
+    var i = 0;
+    while(true) {
+      x += w[i];
+      if(x > r) { return i; }
+      i++;
+    }
+    return w.length - 1; // pretty sure we should never get here?
+  };
+
+  var getModelSize = function(model) {
+    // returns the size (ie, number of floats) used in a model
+    var len = 0;
+    var k;
+    var m;
+    for(k in model) {
+      if(model.hasOwnProperty(k)) {
+        m = model[k];
+        len += m.w.length;
+      }
+    }
+    return len;
+  };
+
+  // other utils
+  var flattenModel = function(model, gradient_) {
+    // returns an float array containing a dump of model's params in order
+    // if gradient_ is true, the the flatten model returns the dw's, rather whan w's.
+    var len = 0; // determine length of dump
+    var i = 0;
+    var j;
+    var k;
+    var m;
+    var gradientMode = false || gradient_;
+    len = getModelSize(model);
+    var result = R.zeros(len);
+    for(k in model) {
+      if(model.hasOwnProperty(k)) {
+        m = model[k];
+        len = m.w.length;
+        for (j = 0; j < len; j++) {
+          if (gradientMode) {
+            result[i] = m.dw[j];
+          } else {
+            result[i] = m.w[j];
+          }
+          i++;
+        }
+      }
+    }
+    return result;
+  };
+  var pushToModel = function(model, dump, gradient_) {
+    // pushes a float array containing a dump of model's params into a model
+    // if gradient_ is true, dump will be pushed to dw's, rather whan w's.
+    var len = 0; // determine length of dump
+    var i = 0;
+    var j;
+    var k;
+    var m;
+    var gradientMode = false || gradient_;
+    len = getModelSize(model);
+    assert(dump.length === len); // make sure the array dump has same len as model
+    for(k in model) {
+      if(model.hasOwnProperty(k)) {
+        m = model[k];
+        len = m.w.length;
+        for (j = 0; j < len; j++) {
+          if (gradientMode) {
+            m.dw[j] = dump[i];
+          } else {
+            m.w[j] = dump[i];
+          }
+          i++;
+        }
+      }
+    }
+  };
+  var copyModel = function(model) {
+    // returns an exact copy of a model
+    var k;
+    var m;
+    var result = [];
+    for(k in model) {
+      if(model.hasOwnProperty(k)) {
+        m = model[k];
+        result[k] = m.copy();
+      }
+    }
+    return result;
+  };
+  var compressModel = function(model, nCoef) {
+    // returns a compressed model using 2d-dct
+    // each model param will be compressed down to:
+    // min(nRow, nCoef), min(nCol, nCoef)
+    var k;
+    var m;
+    var nRow, nCol;
+    var result = [];
+    var z; // dct transformed matrix
+    var i, j;
+    for(k in model) {
+      if(model.hasOwnProperty(k)) {
+        m = model[k];
+        z = m.dct2();
+        nRow = Math.min(z.n, nCoef);
+        nCol = Math.min(z.d, nCoef);
+        result[k] = new Mat(nRow, nCol);
+        for (i=0;i<nRow;i++) {
+          for (j=0;j<nCol;j++) {
+            result[k].set(i, j, z.get(i, j));
+          }
+        }
+      }
+    }
+    return result;
+  };
+  var decompressModel = function(small, model) {
+    // decompresses small (a compressed model) into model using idct
+    var k;
+    var m, s;
+    var nRow, nCol;
+    var z; // idct transformed matrix
+    var i, j;
+    for(k in small) {
+      if(small.hasOwnProperty(k)) {
+        s = small[k];
+        m = model[k];
+        nRow = m.n;
+        nCol = m.d;
+        z = new Mat(nRow, nCol);
+        for (i=0;i<s.n;i++) {
+          for (j=0;j<s.d;j++) {
+            z.set(i, j, s.get(i, j));
+          }
+        }
+        model[k] = z.idct2();
+      }
+    }
+  };
+  var numGradient = function(f, model, avgDiff_, epsilon_) {
+    // calculates numerical gradient.  fitness f is forward pass function passed in is a function of model only.
+    // f will be run many times when the params of each indiv weight changes
+    // numerical gradient is computed off average of uptick and downtick gradient, so O(e^2) noise.
+    // returns a mat object, where .w holds percentage differences, and .dw holds numerical gradient
+    // if avgDiff_ mode is set to true, returns the average percentage diff rather than the actual gradients
+    var epsilon = 1e-10 || epsilon_;
+    var avgDiff = false || avgDiff_;
+    var base = f(model);
+    var upBase, downBase;
+    var uptick = copyModel(model); // uptick.w holds the ticked weight value
+    var downtick = copyModel(model); // opposite of uptick.w
+    var numGrad = copyModel(model); // numGrad.dw holds the numerical gradient.
+
+    var avgPercentDiff = 0.0;
+    var avgPercentDiffCounter = 0;
+
+    var i, len;
+    var m;
+    var k;
+    var result = [];
+    for(k in model) {
+      if(model.hasOwnProperty(k)) {
+        m = model[k];
+        len = m.w.length;
+        for (i = 0; i < len; i++) {
+          // change the weights by a small amount to find gradient
+          uptick[k].w[i] += epsilon;
+          downtick[k].w[i] -= epsilon;
+          upBase = f(uptick);
+          downBase = f(downtick);
+          // store numerical gradient
+          numGrad[k].dw[i] = (upBase - downBase) / (2 * epsilon);
+          numGrad[k].w[i] = ((numGrad[k].dw[i] + epsilon) / (model[k].dw[i] + epsilon) - 1);
+          avgPercentDiff += numGrad[k].w[i] * numGrad[k].w[i];
+          avgPercentDiffCounter += 1;
+          // store precentage diff in w.
+          // undo the change of weights by a small amount
+          uptick[k].w[i] -= epsilon;
+          downtick[k].w[i] += epsilon;
+
+          // set model's dw to numerical gradient (useful for debugging)
+          //model[k].dw[i] = numGrad[k].dw[i];
+        }
+      }
+    }
+
+    if (avgDiff) {
+      return Math.sqrt(avgPercentDiff / avgPercentDiffCounter);
+    }
+    return numGrad;
+  };
+
+  // neuroevolution tools
+
+  // chromosome implementation using an array of floats
+  var Gene = function(initFloatArray) {
+    var i;
+    var len = initFloatArray.length;
+    // the input array will be copied
+    this.fitness = -1e20; // default fitness value is very negative
+    this.nTrial = 0; // number of trials subjected to so far.
+    this.gene = zeros(len);
+    for (i=0;i<len;i++) {
+      this.gene[i] = initFloatArray[i];
+    }
+  };
+
+  Gene.prototype = {
+    burstMutate: function(burst_magnitude_) { // adds a normal random variable of stdev width, zero mean to each gene.
+      var burst_magnitude = burst_magnitude_ || 0.1;
+      var i, N;
+      N = this.gene.length;
+      for (i = 0; i < N; i++) {
+        this.gene[i] += randn(0.0, burst_magnitude);
+      }
+    },
+    randomize: function(burst_magnitude_) { // resets each gene to a random value with zero mean and stdev
+      var burst_magnitude = burst_magnitude_ || 0.1;
+      var i, N;
+      N = this.gene.length;
+      for (i = 0; i < N; i++) {
+        this.gene[i] = randn(0.0, burst_magnitude);
+      }
+    },
+    mutate: function(mutation_rate_, burst_magnitude_) { // adds random gaussian (0,stdev) to each gene with prob mutation_rate
+      var mutation_rate = mutation_rate_ || 0.1;
+      var burst_magnitude = burst_magnitude_ || 0.1;
+      var i, N;
+      N = this.gene.length;
+      for (i = 0; i < N; i++) {
+        if (randf(0,1) < mutation_rate) {
+          this.gene[i] += randn(0.0, burst_magnitude);
+        }
+      }
+    },
+    crossover: function(partner, kid1, kid2) {
+      // performs one-point crossover with partner to produce 2 kids
+      // assumes all chromosomes are initialised with same array size. pls make sure of this before calling
+      assert(this.gene.length === partner.gene.length);
+      assert(partner.gene.length === kid1.gene.length);
+      assert(kid1.gene.length === kid2.gene.length);
+      var i, N;
+      N = this.gene.length;
+      var l = randi(0, N); // crossover point
+      for (i = 0; i < N; i++) {
+        if (i < l) {
+          kid1.gene[i] = this.gene[i];
+          kid2.gene[i] = partner.gene[i];
+        } else {
+          kid1.gene[i] = partner.gene[i];
+          kid2.gene[i] = this.gene[i];
+        }
+      }
+    },
+    copyFrom: function(g) { // copies g's gene into itself
+      var i, N;
+      this.copyFromArray(g.gene);
+    },
+    copyFromArray: function(sourceFloatArray) {
+      // copy an array own's gene (must be same size)
+      assert(this.gene.length === sourceFloatArray.length);
+      var i, N;
+      N = this.gene.length;
+      for (i = 0; i < N; i++) {
+        this.gene[i] = sourceFloatArray[i];
+      }
+    },
+    copy: function(precision_) { // returns a rounded exact copy of itself (into new memory, doesn't return reference)
+      var precision = 10e-4 || precision_; precision = 1/precision;
+      var newFloatArray = zeros(this.gene.length);
+      var i;
+      for (i = 0; i < this.gene.length; i++) {
+        newFloatArray[i] = Math.round(precision*this.gene[i])/precision;
+      }
+      var g = new Gene(newFloatArray);
+      g.fitness = this.fitness;
+      g.nTrial = this.nTrial;
+      return g;
+    },
+    pushToModel: function(model) { // pushes this chromosome to a specified network
+      pushToModel(model, this.gene);
+    }
+  };
+
+  // randomize neural network model with random weights and biases
+  var randomizeModel = function(model, magnitude_) {
+    var modelSize = getModelSize(model);
+    var magnitude = 1.0 || magnitude_;
+    var r = new RandMat(1, modelSize, 0, magnitude);
+    var g = new Gene(r.w);
+    g.pushToModel(model);
+  };
+
+  var GATrainer = function(model, options_, init_gene_array) {
+    // implementation of CoSyNe neuroevolution framework
+    //
+    // options:
+    // population_size : positive integer
+    // hall_of_fame_size : positive integer, stores best guys in all of history and keeps them.
+    // mutation_rate : [0, 1], when mutation happens, chance of each gene getting mutated
+    // elite_percentage : [0, 0.3], only this group mates and produces offsprings
+    // mutation_size : positive floating point.  stdev of gausian noise added for mutations
+    // target_fitness : after fitness achieved is greater than this float value, learning stops
+    // init_weight_magnitude : stdev of initial random weight (default = 1.0)
+    // burst_generations : positive integer.  if best fitness doesn't improve after this number of generations
+    //                    then mutate everything!
+    // best_trial : default 1.  save best of best_trial's results for each chromosome.
+    // num_match : for use in arms race mode.  how many random matches we set for each chromosome when it is its turn.
+    //
+    // init_gene_array:  init float array to initialize the chromosomes.  can be result obtained from pretrained sessions.
+    // debug_mode: false by default.  if set to true, console.log debug output occurs.
+
+    this.model = copyModel(model); // makes a local working copy of the model. copies architecture and weights
+
+    var options = options_ || {};
+    this.hall_of_fame_size = typeof options.hall_of_fame_size !== 'undefined' ? options.hall_of_fame_size : 5;
+    this.population_size = typeof options.population_size !== 'undefined' ? options.population_size : 30;
+    this.population_size += this.hall_of_fame_size; // make room for hall of fame beyond specified population size.
+    this.population_size = Math.floor(this.population_size/2)*2; // make sure even number
+    this.length = this.population_size; // use the variable length to suit array pattern.
+    this.mutation_rate = typeof options.mutation_rate !== 'undefined' ? options.mutation_rate : 0.01;
+    this.init_weight_magnitude = typeof options.init_weight_magnitude !== 'undefined' ? options.init_weight_magnitude : 1.0;
+    this.elite_percentage = typeof options.elite_percentage !== 'undefined' ? options.elite_percentage : 0.2;
+    this.mutation_size = typeof options.mutation_size !== 'undefined' ? options.mutation_size : 0.5;
+    this.debug_mode = typeof options.debug_mode !== 'undefined' ? options.debug_mode : false;
+    this.gene_size = getModelSize(this.model); // number of floats in each gene
+
+    var initGene;
+    var i;
+    var gene;
+    if (init_gene_array) {
+      initGene = new Gene(init_gene_array);
+    }
+
+    this.genes = []; // population
+    this.hallOfFame = []; // stores the hall of fame here!
+    for (i = 0; i < this.population_size; i++) {
+      gene = new Gene(zeros(this.gene_size));
+      if (initGene) { // if initial gene supplied, burst mutate param.
+        gene.copyFrom(initGene);
+        if (i > 0) { // don't mutate the first guy.
+          gene.burstMutate(this.mutation_size);
+        }
+      } else {
+        gene.randomize(this.init_weight_magnitude);
+      }
+      this.genes.push(gene);
+    }
+    // generates first few hall of fame genes (but burst mutates some of them)
+    for (i = 0; i < this.hall_of_fame_size; i++) {
+      gene = new Gene(zeros(this.gene_size));
+      if (init_gene_array) { // if initial gene supplied, burst mutate param.
+        gene.copyFrom(initGene);
+      } else {
+        gene.randomize(this.init_weight_magnitude);
+        if (i > 0) { // don't mutate the first guy.
+          gene.burstMutate(this.mutation_size);
+        }
+      }
+      this.hallOfFame.push(gene);
+    }
+
+    pushToModel(this.model, this.genes[0].gene); // push first chromosome to neural network. (replaced *1 above)
+
+  };
+
+  GATrainer.prototype = {
+    sortByFitness: function(c) {
+      c = c.sort(function (a, b) {
+        if (a.fitness > b.fitness) { return -1; }
+        if (a.fitness < b.fitness) { return 1; }
+        return 0;
+      });
+    },
+    pushGeneToModel: function(model, i) {
+      // pushes the i th gene of the sorted population into a model
+      // this ignores hall of fame
+      var g = this.genes[i];
+      g.pushToModel(model);
+    },
+    pushBestGeneToModel: function(model) {
+      this.pushGeneToModel(model, 0);
+    },
+    pushHistToModel: function(model, i) {
+      // pushes the i th gene of the sorted population into a model from the hall-of-fame
+      // this requires hall of fame model to be used
+      var Nh = this.hall_of_fame_size;
+      assert(Nh > 0); // hall of fame must be used.
+      var g = this.hallOfFame[i];
+      g.pushToModel(model);
+    },
+    pushBestHistToModel: function(model) {
+      this.pushHistToModel(model, 0);
+    },
+    flushFitness: function() {
+      // resets all the fitness scores to very negative numbers, incl hall-of-fame
+      var i, N, Nh;
+      var c = this.genes;
+      var h = this.hallOfFame;
+      N = this.population_size;
+      Nh = this.hall_of_fame_size;
+      for (i=0;i<N;i++) {
+        c[i].fitness = -1e20;
+      }
+      for (i=0;i<Nh;i++) {
+        h[i].fitness = -1e20;
+      }
+
+    },
+    evolve: function() {
+      // this function does bare minimum simulation of one generation
+      // it assumes the code prior to calling evolve would have simulated the system
+      // it also assumes that the fitness in each chromosome of this trainer will have been assigned
+      // it just does the task of crossovers and mutations afterwards.
+
+      var i, j, N, Nh;
+      var c = this.genes;
+      var h = this.hallOfFame;
+
+      N = this.population_size;
+      Nh = this.hall_of_fame_size;
+
+      // sort the chromosomes by fitness
+      this.sortByFitness(c);
+
+      if (this.debug_mode) {
+        console.log(0+': '+Math.round(c[0].fitness*100)/100);
+        console.log((N-1)+': '+Math.round(c[N-1].fitness*100)/100);
+      }
+
+      // copies best from population to hall of fame:
+      for (i = 0; i < Nh; i++) {
+        h.push(c[i].copy());
+      }
+
+      // sorts hall of fame
+      this.sortByFitness(h);
+      // cuts off hall of fame to keep only Nh elements
+      h = h.slice(0, Nh);
+
+      if (this.debug_mode) {
+        console.log('hall of fame:');
+        for (i = 0; i < Math.min(Nh, 3); i++) {
+          console.log(i+': '+Math.round(h[i].fitness*100)/100);
+        }
+      }
+
+      // alters population:
+
+      var Nelite = Math.floor(Math.floor(this.elite_percentage*N)/2)*2; // even number
+      for (i = Nelite; i < N; i+=2) {
+        var p1 = randi(0, Nelite);
+        var p2 = randi(0, Nelite);
+        c[p1].crossover(c[p2], c[i], c[i+1]);
+      }
+
+      // leaves the last Nh slots for hall of fame guys.
+      for (i = 0; i < N-Nh; i++) {
+        c[i].mutate(this.mutation_rate, this.mutation_size);
+      }
+
+      // sneakily puts in the hall of famers back into the population at the end:
+      for (i = 0; i < Nh; i++) {
+        c[N-Nh+i] = h[i].copy();
+      }
+
+
+      // permutation step in CoSyNe
+      // we permute all weights in elite set, and don't prob-weight as in Gomez 2008.
+
+      var Nperm = Nelite; // permute the weights up to Nperm.
+      var permData = zeros(Nperm);
+      var len = c[0].gene.length; // number of elements in each gene
+      for (j=0;j<len;j++) {
+        // populate the data to be shuffled
+        for (i=0;i<Nperm;i++) {
+          permData[i] = c[i].gene[j];
+        }
+        permData = shuffle(permData); // the magic is supposed to happen here.
+        // put back the shuffled data back:
+        for (i=0;i<Nperm;i++) {
+          c[i].gene[j] = permData[i];
+        }
+      }
+
+    }
+  };
+
+  // various utils
+  global.maxi = maxi;
+  global.samplei = samplei;
+  global.randi = randi;
+  global.randf = randf;
+  global.randn = randn;
+  global.zeros = zeros;
+  global.shuffle = shuffle;
+  global.softmax = softmax;
+  global.assert = assert;
+
+  // classes
+  global.Mat = Mat;
+  global.RandMat = RandMat;
+
+  global.forwardLSTM = forwardLSTM;
+  global.initLSTM = initLSTM;
+  global.forwardRNN = forwardRNN;
+  global.initRNN = initRNN;
+
+  // optimization
+  global.Solver = Solver;
+  global.Graph = Graph;
+
+  // other utils
+  global.flattenModel = flattenModel;
+  global.getModelSize = getModelSize;
+  global.copyModel = copyModel;
+  global.numGradient = numGradient;
+  global.pushToModel = pushToModel;
+  global.randomizeModel = randomizeModel;
+
+  // model compression
+  global.compressModel = compressModel;
+  global.decompressModel = decompressModel;
+
+  // ga
+  global.GATrainer = GATrainer;
+  global.Gene = Gene;
+
+})(R);