Published
Edited
Jun 3, 2019
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InputValues = [phi0, theta0, x99, y99, phi99, theta99, xdot0, ydot0, phidot0, thetadot0]
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md `## Graph Plot Setting`
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height = 500
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width =1000
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maxLayer =d3.max(data.nodes, d => d.LayerNum)
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maxwt = d3.max(data.links, d => Math.abs(d.weight))
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maxnode = d3.max(data.nodes, d => Math.abs(d.value))
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color = {
const scale = d3.scaleOrdinal(d3.schemeCategory10);
return d => scale(d.LayerNum);
}
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drag = simulation => {
function dragstarted(d) {
if (!d3.event.active) simulation.alphaTarget(3).restart();
d.fx = d.x;
d.fy = d.y;
}
function dragged(d) {
d.fx = d3.event.x;
d.fy = d3.event.y;
}
function dragended(d) {
if (!d3.event.active) simulation.alphaTarget(0);
d.fx = null;
d.fy = null;
}
return d3.drag()
.on("start", dragstarted)
.on("drag", dragged)
.on("end", dragended);
}
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d3 = require("d3@5")
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import {number} from "@jashkenas/inputs"
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import {slider} from "@jashkenas/inputs"
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md `## Graph Generation`
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NN = d3.json("https://raw.githubusercontent.com/cse512-19s/FP-Visualizing-neural-network-architecture/master/docs/FeedforwardNN.json?token=AHF5OJCHONQA7OTERXNXTCK47VYOQ")
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function ComputeLayerValues(input){
var nodes = [];
var links = [];
for (let i=0; i<NN['weights'][0].length; i++){
var node = {'id': i, 'LayerNum': 0, 'NodeNum': i, 'value': input[i], 'valueScaled': 2*input[i]}
nodes.push(node)
}
var currentLayer = input
for (let l=0; l<NN['weights'].length; l++){
var weight = NN['weights'][l]
var bias = NN['bias'][l]
var nextLayer = bias
for (let i=0; i<weight.length; i++){
for (let j=0; j<weight[i].length; j++){
nextLayer[j] += weight[i][j]*currentLayer[i]
var link = {'source': l*100+i, 'target': (l+1)*100+j, 'weight': weight[i][j]}
links.push(link)
}
}
for (let k=0; k<nextLayer.length; k++){
var v = nextLayer[k]
if (l !== NN['weights'].length-1){
v = Math.tanh(nextLayer[k]) // apply activation function
}
var node = {'id': (l+1)*100+k, 'LayerNum': l+1, 'NodeNum': k, 'value': v, 'valueScaled': Math.tanh(nextLayer[k])}
nodes.push(node)
nextLayer[k] = v
}
currentLayer = nextLayer
}
return {"nodes": nodes, "links": links};
}
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data = ComputeLayerValues(InputValues)
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