I have a code as follows:
function DetailFacture2() {
var ss = SpreadsheetApp.getActive();
var DetailDEVIS = SpreadsheetApp.setActiveSheet(ss.getSheetByName('DetailDEVIS'));
var FACTUREDevis = SpreadsheetApp.setActiveSheet(ss.getSheetByName('FACTUREDevis'));
var DetailFactureDevis = SpreadsheetApp.setActiveSheet(ss.getSheetByName('DetailFactureDevis'));
var lastrowpaste = FACTUREDevis.getLastRow();
var numrow = FACTUREDevis.getRange(lastrowpaste,13).getValue()
var lastrowpaste2 = DetailFactureDevis.getLastRow() - numrow +2;
var data = DetailDEVIS.getDataRange().getValues();
var DetailD = FACTUREDevis.getRange(lastrowpaste,2).getValue();
for(var i = 0; i<data.length;i++){
if(data[i][1] == DetailD){ //[1] because column B
var firstrowcopy = i+1;
Logger.log(firstrowcopy)
return (firstrowcopy)
}
}
};
It does return the correct value, but how do you use "firstrowcopy" as a fixed var?
I would like to use as follows:
function DetailFacture2() {
var ss = SpreadsheetApp.getActive();
var DetailDEVIS = SpreadsheetApp.setActiveSheet(ss.getSheetByName('DetailDEVIS'));
var FACTUREDevis = SpreadsheetApp.setActiveSheet(ss.getSheetByName('FACTUREDevis'));
var DetailFactureDevis = SpreadsheetApp.setActiveSheet(ss.getSheetByName('DetailFactureDevis'));
var lastrowpaste = FACTUREDevis.getLastRow();
var numrow = FACTUREDevis.getRange(lastrowpaste,13).getValue()
var lastrowpaste2 = DetailFactureDevis.getLastRow() - numrow +2;
var data = DetailDEVIS.getDataRange().getValues();
var DetailD = FACTUREDevis.getRange(lastrowpaste,2).getValue();
for(var i = 0; i<data.length;i++){
if(data[i][1] == DetailD){ //[1] because column B
var firstrowcopy = i+1;
var source = DetailDEVIS.getRange(firstrowcopy,1,numrow-1);
var destination = DetailFactureDevis.getRange(lastrowpaste2,3);
source.copyTo(destination);
}
}
};
But, as one would expect, it cannot work as it loops...
Not sure if I understand your question too. The code doesn't look well. Here is just my guess. Try to change the last lines this way:
// ...
var firstrowcopy = 0;
for (var i = 0; i < data.length; i++){
if(data[i][1] == DetailD){ //[1] because column B
firstrowcopy = i+1;
break;
}
}
var source = DetailDEVIS.getRange(firstrowcopy,1,numrow-1);
var destination = DetailFactureDevis.getRange(lastrowpaste2,3);
source.copyTo(destination);
}
var dbRefObjectHis = firebase.database().ref('Box1').child('history');
dbRefObjectHis.on('value',gotData, errData);
function gotData(data) {
var ref = d3.selectAll('.His');
for (var i = 0; i < ref.length; i++){
ref[i].remove();
}
var history = data.val();
var keys = Object.keys(history);
for (i = 0; i < keys.length; i++) {
var k = keys[i];
var humidity = history[k].humidity;
var temperature = history[k].temperature;
$('.His').append('Humidity:' + humidity + 'Temperature:' + temperature );
}
This happens when the element you are trying to remove is not a removable Node.
try replacing
for (var i = 0; i < ref.length; i++){
ref[i].remove();
}
with
ref.forEach(function(e) {
e.remove();
});
function writeData () {
var sss= SpreadsheetApp.getActiveSpreadsheet();
//var inSheet2 = sss.getSheetByName('Copy of 01-Raw Data 2');
var inSheet2 = sss.getSheets()[4];
var input2 = inSheet2.getRange(2, 1, inSheet2.getLastRow(),42);
var outSheet1 = sss.getSheets()[0];
var outStartRow2 = outSheet1.getLastRow() + 2;
var outStartRow3 = outSheet1.getLastRow() + 2;
input2.copyFormatToRange(outSheet1, 2, 42, outStartRow3, outStartRow2);
var ss = SpreadsheetApp.getActiveSpreadsheet();
var inSheet = sss.getSheets()[0];
var input = inSheet.getRange(2, 18, inSheet.getLastRow(), 42).getValues();
var outSheet2 = sss.getSheets()[4];
var outStartRow = outSheet2.getLastRow() + 1;
for (var col = 0; col < input.length; col++) {
for (var row = 0; row < input[col].length; row++) {
outSheet2.getRange(outStartRow + row, col + 5)
.setValue(input[col][row]);
}
}
}
function onOpen() {
var ss = SpreadsheetApp.getActiveSpreadsheet();
var menuEntries = [];
menuEntries.push({name: "Write data", functionName: "writeData"});
ss.addMenu("Custom functions", menuEntries);
}
I am using google-apps-script in Google spreadsheets.
What i have:
What I want to achieve:
Please, let me know if you got a way to make this correctly.
The Code:
function myFunction() {
var ss=SpreadsheetApp.getActive();
var sh0=ss.getSheetByName('INPUT');
var sh1=ss.getSheetByName('OUTPUT');
var rg0=sh0.getDataRange();
var vA=rg0.getValues();
var oA=[];
for(var i=0;i<vA.length;i++)
{
for(var j=0;j<vA[0].length;j++)
{
if(vA[j][i])
{
oA.push([vA[j][i]]);
}
else
{
for(var k=0;k<j;k++)
{
oA.pop();
}
break;
}
}
}
sh1.getRange(1,1,oA.length,oA[0].length).setValues(oA);
}
Data Sheet:
Output Sheet:
I've tried to rewrite neural network found here to javascript. My javascript code looks like this.
function NeuralFactor(weight) {
var self = this;
this.weight = weight;
this.delta = 0;
}
function Sigmoid(value) {
return 1 / (1 + Math.exp(-value));
}
function Neuron(isInput) {
var self = this;
this.pulse = function() {
self.output = 0;
self.input.forEach(function(item) {
self.output += item.signal.output * item.factor.weight;
});
self.output += self.bias.weight;
self.output = Sigmoid(self.output);
};
this.bias = new NeuralFactor(isInput ? 0 : Math.random());
this.error = 0;
this.input = [];
this.output = 0;
this.findInput = function(signal) {
var input = self.input.filter(function(input) {
return signal == input.signal;
})[0];
return input;
};
}
function NeuralLayer() {
var self = this;
this.pulse = function() {
self.neurons.forEach(function(neuron) {
neuron.pulse();
});
};
this.neurons = [];
this.train = function(learningRate) {
self.neurons.forEach(function(neuron) {
neuron.bias.weight += neuron.bias.delta * learningRate;
neuron.bias.delta = 0;
neuron.input.forEach(function(input) {
input.factor.weight += input.factor.delta * learningRate;
input.factor.delta = 0;
})
})
}
}
function NeuralNet(inputCount, hiddenCount, outputCount) {
var self = this;
this.inputLayer = new NeuralLayer();
this.hiddenLayer = new NeuralLayer();
this.outputLayer = new NeuralLayer();
this.learningRate = 0.5;
for(var i = 0; i < inputCount; i++)
self.inputLayer.neurons.push(new Neuron(true));
for(var i = 0; i < hiddenCount; i++)
self.hiddenLayer.neurons.push(new Neuron());
for(var i = 0; i < outputCount; i++)
self.outputLayer.neurons.push(new Neuron());
for (var i = 0; i < hiddenCount; i++)
for (var j = 0; j < inputCount; j++)
self.hiddenLayer.neurons[i].input.push({
signal: self.inputLayer.neurons[j],
factor: new NeuralFactor(Math.random())
});
for (var i = 0; i < outputCount; i++)
for (var j = 0; j < hiddenCount; j++)
self.outputLayer.neurons[i].input.push({
signal: self.hiddenLayer.neurons[j],
factor: new NeuralFactor(Math.random())
});
this.pulse = function() {
self.hiddenLayer.pulse();
self.outputLayer.pulse();
};
this.backPropagation = function(desiredResults) {
for(var i = 0; i < self.outputLayer.neurons.length; i++) {
var outputNeuron = self.outputLayer.neurons[i];
var output = outputNeuron.output;
outputNeuron.error = (desiredResults[i] - output) * output * (1.0 - output);
}
for(var i = 0; i < self.hiddenLayer.neurons.length; i++) {
var hiddenNeuron = self.hiddenLayer.neurons[i];
var error = 0;
for(var j = 0; j < self.outputLayer.neurons.length; j++) {
var outputNeuron = self.outputLayer.neurons[j];
error += outputNeuron.error * outputNeuron.findInput(hiddenNeuron).factor.weight * hiddenNeuron.output * (1.0 - hiddenNeuron.output);
}
hiddenNeuron.error = error;
}
for(var j = 0; j < self.outputLayer.neurons.length; j++) {
var outputNeuron = self.outputLayer.neurons[j];
for(var i = 0; i < self.hiddenLayer.neurons.length; i++) {
var hiddenNeuron = self.hiddenLayer.neurons[i];
outputNeuron.findInput(hiddenNeuron).factor.delta += outputNeuron.error * hiddenNeuron.output;
}
outputNeuron.bias.delta += outputNeuron.error * outputNeuron.bias.weight;
}
for(var j = 0; j < self.hiddenLayer.neurons.length; j++) {
var hiddenNeuron = self.hiddenLayer.neurons[j];
for(var i = 0; i < self.inputLayer.neurons.length; i++) {
var inputNeuron = self.inputLayer.neurons[i];
hiddenNeuron.findInput(inputNeuron).factor.delta += hiddenNeuron.error * inputNeuron.output;
}
hiddenNeuron.bias.delta += hiddenNeuron.error * hiddenNeuron.bias.weight;
}
};
this.train = function(input, desiredResults) {
for(var i = 0; i < self.inputLayer.neurons.length; i++) {
var neuron = self.inputLayer.neurons[i];
neuron.output = input[i];
}
self.pulse();
self.backPropagation(desiredResults);
self.hiddenLayer.train(self.learningRate);
self.outputLayer.train(self.learningRate);
};
}
Now I'm trying to learn it how to resolve XOR problem. I'm teaching it like this:
var net = new NeuralNet(2,2,1);
var testInputs = [[0,0], [0,1], [1,0], [1,1]];
var testOutputs = [[1],[0],[0],[1]];
for (var i = 0; i < 1000; i++)
for(var j = 0; j < 4; j++)
net.train(testInputs[j], testOutputs[j]);
function UseNet(a, b) {
net.inputLayer.neurons[0].output = a;
net.inputLayer.neurons[1].output = b;
net.pulse();
return net.outputLayer.neurons[0].output;
}
The problem is that all results that I get is close to 0.5 and pretty random, no matter what arguments I use. For example:
UseNet(0,0) => 0.5107701166677714
UseNet(0,1) => 0.4801498747476413
UseNet(1,0) => 0.5142463167153447
UseNet(1,1) => 0.4881829364416052
What can be wrong with my code?
This network is big enough for the XOR problem and I can't see any obvious mistakes, so I suspect it's getting stuck in a local minimum.
Try going through the training set 10,000 times instead of 1000; this gives it a better chance of breaking out of any minima and converging. You can also increase convergence a lot by upping the number of hidden neurons, tweaking η (the learning rate) or adding momentum. To implement the latter, try using this as your training function:
this.train = function(learningRate) {
var momentum = 0 /* Some value, probably fairly small. */;
self.neurons.forEach(function(neuron) {
neuron.bias.weight += neuron.bias.delta * learningRate;
neuron.bias.delta = 0;
neuron.input.forEach(function(input) {
input.factor.weight += (input.factor.delta * learningRate) + (input.factor.weight * momentum);
input.factor.delta = 0;
})
})
}
I've had good results changing the learning rate to 1.5 (which is pretty high) and momentum to 0.000001 (which is pretty small).
(Incidentally, have you tried running the .NET implementation with a few different seeds? It can take quite a while to converge too!)
This system uses fuzzy logic. As it says in the article don't use integers instead use "close" real numbers as the article suggests -- try
UseNet(0.1,0.1) =>
UseNet(0.1,0.9) =>
UseNet(0.9,0.1) =>
UseNet(0.9,0.9) =>
For the results anything above 0.5 is a 1 and below is 0
Hmmmm
Try instead of:
var testInputs = [[0,0], [0,1], [1,0], [1,1]];
var testOutputs = [[1],[0],[0],[1]];
This:
var testInputs = [[0.05,0.05], [0.05,0.95], [0.95,0.05], [0.95,0.95]];
var testOutputs = [[1],[0],[0],[1]];
or
var testInputs = [[0,0], [0,1], [1,0], [1,1]];
var testOutputs = [[0.95],[0.05],[0.05],[0.95]];
I'd like to be able to reverse the results of a table returned from a PHP database with javascript, but can't seem to figure out how to get the reverse(); method to work. I'd appreciate any help you could give me.
This is my Javascript:
function title()
{
var sortedOn = 0;
var display = document.getElementById("table");
var list = new Array();
var tableLength = display.rows.length;
for(var i = 1; i < tableLength; i++){
var row = display.rows[i];
var info = row.cells[0].textContent;
list.push([info,row]);
}
list.sort();
var listLength = list.length;
for(var i = 0; i < listLength; i++) {
display.appendChild(list[i][1]);
}
This is in my html table:
<th>Title</th>
function reverse(){
var display = document.getElementById("table");
var length = display.rows.length;
for(var i = 0; i < length; i++)
{
display.appendChild(
display.removeChild(display.rows[length - i - 1])
);
}
}
Here's the fiddle