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nested for loops in js, incremented by 2

I am currently trying to solve the xmas tree problem, with internal tree-like shape.
issue is with internal spacing, it supposed to be like: 1, 5, 7, 9. Instead it is 1, 3, 4, 5. I do not know, how to increment s loop by 2 in each loop turn.
/*
*********
**** ****
*** ***
** **
* *
*********
*/
function drawTree(h) {
let n = h + 3;
for (var i = 1; i <= 1; i++) {
var temp = "";
for (var j = 1; j <= n; j++) {
temp = temp + "*";
}
console.log(temp);
}
for (var i = 0; i < h - 2; i++) {
var tree = '';
console.log("\n");
for (var k = 3; k <= h - i; k++) {
tree += "*";
};
tree += "s";
for (var k = 1; k <= i; k++) {
for (var k = 1; k <= i; k++) {
tree += "s";
};
tree += "s";
};
for (var k = 3; k <= h - i; k++) {
tree += "*";
};
console.log(tree);
};
console.log("\n");
let g = h + 3;
for (var i = 1; i <= 1; i++) {
var temp = "";
for (var j = 1; j <= g; j++) {
temp = temp + "*";
}
console.log(temp);
}
};
drawTree(6);

function drawTree(stars, rowLength) {
for (let row = 0; row < rowLength; row++) {
if (row === 0) {
console.log("*".repeat(stars));
} else if(row === rowLength - 1) {
console.log("*".repeat(stars));
} else {
let spaces = 2 * row - 1;
if (spaces > stars) {
spaces = stars;
}
let numStarsInRow = "*".repeat((stars - spaces) / 2);
console.log(numStarsInRow + " ".repeat(spaces) + numStarsInRow);
}
}
}
drawTree(9, 5)

You can implement this by nesting loops over the height and the width of the tree, noting that the output is a * whenever:
it's the first or last row; or
the current x position is less than or equal to the halfway point minus the row number; or
the current x position is greater than or equal to the halfway point plus the row number
For all other cases the output is a space. For example:
function drawTree(height) {
// compute the width of the tree from the height
let width = height % 2 ? height + 2 : height + 3;
// find the halfway point
let half = (width - 1) / 2;
for (let i = 0; i < height; i++) {
let l = '';
for (let j = 0; j < width; j++) {
if (i == 0 || // first row
i == height - 1 || // last row
j <= (half - i) || // left side
j >= (half + i) // right side
) {
l += '*';
}
else {
l += ' ';
}
}
console.log(l);
}
}
drawTree(6);
drawTree(5);

Where is the error in InitializeGrid? It's returning wrong indices

Ok, so I'm trying to code a Rectangle with multiple triangle strips joined together. according to:
http://www.corehtml5.com/trianglestripfundamentals.php
You need to take care of the triangles wrapping around when you have more than one row. However using the suggested algorithm in my code example I'm getting incorrect indice results.
Here is my example, with outputs.
I've tried copy/pasting the suggested algorithm but it doesn't seem to be returning correct results.
// Create the Index Points for the buffer array.
var rows=2;
var cols=3;
var grid = rows*cols;
var offset;
var pos = [];
var index = 0;
var mpOffset = 1;
for (var row = 0; row <= rows; ++row)
{
offsetY = row * (mpOffset / rows);
for (var col = 0; col <= cols; ++col)
{
offsetX = col * (mpOffset / cols);
pos[index+0] = (offsetX);
pos[index+1] = (offsetY);
index+=2;
}
}
log.info("pos="+JSON.stringify(pos)); // <-- Correct working good.
log.info("pos.length="+pos.length);
function initializeGrid(cols,rows)
{
var trianglestrip = [];
var RCvertices=2*cols*(rows-1);
var TSvertices=2*cols*(rows-1)+2*(rows-2);
var numVertices=TSvertices;
var j=0;
for(var i = 1; i <= RCvertices; i += 2)
{
trianglestrip[ j ] = (1 +i)/2;
trianglestrip[ j +1 ] = (cols*2 + i + 1) / 2;
if( trianglestrip[ j +1 ] % cols == 0)
{
if( trianglestrip[ j +1 ] != cols && trianglestrip[ j +1 ] != cols*rows )
{
trianglestrip[ j +2 ] = trianglestrip[ j +1 ];
trianglestrip[ j +3 ] = (1 + i + 2) / 2;
j += 2;
}
}
j += 2;
}
return trianglestrip;
}
var triStrip = initializeGrid(cols,rows);
log.info("triStrip="+JSON.stringify(triStrip)); // <-- Bad Not working.
log.info("triStrip.length="+triStrip.length);
// Generating the actual Point strip.
var actualStrip = [];
for (var i = 0 ; i < triStrip.length; ++i)
{
actualStrip.push(pos[(triStrip[i]-1)*2+0]);
actualStrip.push(pos[(triStrip[i]-1)*2+1]);
}
log.info("actualStrip="+JSON.stringify(actualStrip));
log.info("actualStrip.length="+actualStrip.length);
Indices should be:
1, 5, 2, 6, 3, 7, 4, 8, 8, 5, 5, 9, 6, 10, 7, 11, 8, 12

I ended up re-creating the function to calculate the triangle strip indices. Have not fully tested it but it can re-create the 3x2 grid in the example from the website.
Here is the code:
// This calculates the triangle points in a rectangular triangle strip.
// Used for 3D Webgl texture mapping.
// Copyright Joshua Langley 2019.
var rows=2;
var cols=3;
var grid = rows*cols;
var offset;
var pos = [];
var index = 0;
var mpOffset = 1;
var offsetX, offsetY;
for (var row = 0; row <= rows; ++row)
{
offsetY = row * (mpOffset / rows);
for (var col = 0; col <= cols; ++col)
{
offsetX = col * (mpOffset / cols);
pos[index+0] = (offsetX);
pos[index+1] = (offsetY);
index+=2;
}
}
log.info("pos="+JSON.stringify(pos));
log.info("pos.length="+pos.length);
var rows=rows+1,cols=cols+1; // Important this counting Points not Squares.
var grid = rows*cols;
var offset;
var indices = [];
var indice = 0;
var offset;
var doublePoints = false;
var tPoint, bPoint;
for (var row = 0; row < rows; ++row)
{
for (var col = 0; col < (cols-1); ++col)
{
offset = row * rows + col;
tPoint = offset+1;
bPoint = offset+cols+1;
if (bPoint > grid)
continue;
indices.push(tPoint);
indices.push(bPoint);
if (offset > 0 && (bPoint+1) < grid && (offset+1) % cols == 0)
{
indices.push(bPoint);
indices.push(tPoint+1);
}
}
}
log.info("indices="+JSON.stringify(indices)); // Expected Result
log.info("indices.length="+indices.length);
var actualStrip = [];
for (var i = 0 ; i < indices.length; ++i)
{
actualStrip.push(pos[(indices[i]-1)*2+0]);
actualStrip.push(pos[(indices[i]-1)*2+1]);
}
log.info("actualStrip="+JSON.stringify(actualStrip));
log.info("actualStrip.length="+actualStrip.length);

javascript canvas: draw moving average line with curves

So basically, I want to draw a curved average line over a certain amount of points of a time-series line chart. Like this:
I want it to span the entire length of the chart but I can't figure out how to calculate the start and end points because the average would (I think) be a point in the middle of each section. Looking at a stock chart with moving average you can see what I want to acheive:
I calculate the averages first by splitting the data array up into chunks based on a period of time. So if I start with:
[
{ time: 1, value: 2 },
{ time: 2, value: 4 },
{ time: 3, value: 5 },
{ time: 4, value: 7 },
]
I get to:
var averages = [
{
x: 1.5,
y: 3,
},
{
x: 3.5 (the average time)
y: 6 (the average value)
},
]
This is what I've tried where I end up with an incomplete line, one that doesnt start at the beginning of the chart and doesnt stop at the end, but stars and ends inside the chart at the first average time:
ctx.moveTo((averages[0].x), averages[0].y);
for(var i = 0; i < averages.length-1; i ++)
{
var x_mid = (averages[i].x + averages[i+1].x) / 2;
var y_mid = (averages[i].y + averages[i+1].y) / 2;
var cp_x1 = (x_mid + averages[i].x) / 2;
var cp_x2 = (x_mid + averages[i+1].x) / 2;
ctx.quadraticCurveTo(cp_x1, averages[i].y ,x_mid, y_mid);
ctx.quadraticCurveTo(cp_x2, averages[i+1].y ,averages[i+1].x, averages[i+1].y);
}
ctx.stroke();
How would you do this?

To get a moving mean you need to just get the mean of n points either side of the current sample.
For example
// array of data points
const movingMean = []; // the resulting means
const data = [12,345,123,53,134,...,219]; // data with index representing x axis
const sampleSize = 5;
for(var i = sampleSize; i < data.length - sampleSize; i++){
var total = 0;
for(var j = i- sampleSize; j < i + sampleSize; j++){
total += data[j];
}
movingMean[i] = total / (sampleSize * 2);
}
This method does not pull the mean forward giving the most accurate mean for each data point.
The problem with this method is that you do not get a mean for the first n and last n samples, where n is the number of samples either side of the mean.
You can do an alternative that will pull the mean forward a little but by applying a weighted mean you can reduce the bias a little
for(var i = sampleSize; i < data.length + Math.floor(sampleSize / 4); i++){
var total = 0;
var count = 0;
for(var j = sampleSize; j > 0; j --){
var index = i - (sampleSize - j);
if(index < data.length){
total += data[index] * j; // linear weighting
count += j;
}
}
movingMean[i-Math.floor(sampleSize / 4)] = total / count;
}
This method keeps that mean closer to the current sample end.
The example show a random data set and the two types of means plotted over it. Click to get a new plot. The red line is the moving mean and the blue is the weighted mean. Note how the blue line tends to follow the data a little slow.
The green line is a weighted mean that has a sample range 4 times greater than the other two.
// helper functions
const doFor = (count, callback) => {var i = 0; while (i < count) { callback(i ++) } };
const setOf = (count, callback) => {var a = [],i = 0; while (i < count) { a.push(callback(i ++)) } return a };
const rand = (min, max = min + (min = 0)) => Math.random() * (max - min) + min;
const randG = (dis, min, max) => {var r = 0; doFor(dis,()=>r+=rand(min,max)); return r / dis};
function getMinMax(data){
var min = data[0];
var max = data[0];
doFor(data.length - 1, i => {
min = Math.min(min,data[i+1]);
max = Math.max(max,data[i+1]);
});
var range = max-min;
return {min,max,range};
}
function plotData(data,minMax){
ctx.beginPath();
for(var i = 0; i < data.length; i++){
if(data[i] !== undefined){
var y = (data[i] - minMax.min) / minMax.range;
y = y *(ctx.canvas.height - 2) + 1;
ctx.lineTo(i/2,y);
}
}
ctx.stroke();
}
function getMovingMean(data,sampleSize){
const movingMean = []; // the resulting means
for(var i = sampleSize; i < data.length - sampleSize; i++){
var total = 0;
for(var j = i- sampleSize; j < i + sampleSize; j++){
total += data[j];
}
movingMean[i] = total / (sampleSize * 2);
}
return movingMean[i];
}
function getMovingMean(data,sampleSize){
const movingMean = []; // the resulting means
for(var i = sampleSize; i < data.length - sampleSize; i++){
var total = 0;
for(var j = i- sampleSize; j < i + sampleSize; j++){
total += data[j];
}
movingMean[i] = total / (sampleSize * 2);
}
return movingMean;
}
function getWeightedMean(data,sampleSize){
const weightedMean = [];
for(var i = sampleSize; i < data.length+Math.floor(sampleSize/4); i++){
var total = 0;
var count = 0;
for(var j = sampleSize; j > 0; j --){
var index = i - (sampleSize - j);
if(index < data.length){
total += data[index] * j; // linear weighting
count += j;
}
}
weightedMean[i-Math.floor(sampleSize/4)] = total / count;
}
return weightedMean;
}
const dataSize = 1000;
const sampleSize = 50;
canvas.width = dataSize/2;
canvas.height = 200;
const ctx = canvas.getContext("2d");
function displayData(){
ctx.clearRect(0,0,ctx.canvas.width,ctx.canvas.height);
var dataPoint = 100;
var distribution = Math.floor(rand(1,8));
var movement = rand(2,20);
const data = setOf(dataSize,i => dataPoint += randG(distribution, -movement, movement));
const movingMean = getMovingMean(data, sampleSize);
const weightedMean = getWeightedMean(data, sampleSize*2);
const weightedMean1 = getWeightedMean(data, sampleSize*8);
var minMax = getMinMax(data);
ctx.strokeStyle = "#ccc";
plotData(data,minMax);
ctx.strokeStyle = "#F50";
plotData(movingMean,minMax);
ctx.strokeStyle = "#08F";
plotData(weightedMean,minMax);
ctx.strokeStyle = "#4C0";
plotData(weightedMean1,minMax);
}
displayData();
document.onclick = displayData;
body { font-family : arial; }
.red { color : #F50; }
.blue { color : #0AF; }
.green { color : #4C0; }
canvas { position : absolute; top : 0px; left :130px; }
<canvas id="canvas"></canvas>
<div class="red">Moving mean</div>
<div class="blue">Weighted mean</div>
<div class="green">Wide weighted mean</div>
<div>Click for another sample</div>

How can I check a value in a cell in an array Google Sheets?

I want to calculate how many Y's & N's appear in an array / range defined:
Cell Range: D4:D42
function myFunction() {
var count = SpreadsheetApp.getActiveSheet().getRange(5, 3, 40, 1);
var numRows = count.getNumRows();
var numCols = count.getNumColumns();
var y = 0;
var n = 0;
for (var i = 1; i <= numRows; i++) {
for (var j = 1; j <= numCols; j++) {
var currentValue = count.getCell(i, j).getValue();
if (currentValue = "y") {
y = y + 1;
} else if (currentValue = "n") {
n = n + 1;
}
}
}
Browser.msgBox("There are " + y + " paid & " + n + " not paid");
}
This returns 40 Y's and 0 N's
Not sure what I am doing wrong here but I think it's a simple fix!

The problem is in this line:
if (currentValue = "y") {
You are assigning "y" to currentValue. To actually check for equality, you should try the "===" operator. Try this and see if it solves your problem:
function myFunction() {
var count = SpreadsheetApp.getActiveSheet().getRange(5, 4, 39, 1);
var numRows = count.getNumRows();
var numCols = count.getNumColumns();
var y = 0;
var n = 0;
for (var i = 1; i <= numRows; i++) {
for (var j = 1; j <= numCols; j++) {
var currentValue = count.getCell(i, j).getValue();
if (currentValue === "y") {
y = y + 1;
} else if (currentValue === "n") {
n = n + 1;
}
}
}
Browser.msgBox("There are " + y + " paid & " + n + " not paid");
}
I also updated the getRange() parameters to match D4:D42. In your code, they matched C5:C44. See the getRange() function documentation.

Got 90% of the JavaScript code - can't figure out the rest

So I am trying to model Gram-Schmidt for any size N×N matrix, and I have officially hit a roadblock I can't get past. I know it's a matter of looping this correctly, but I can't figure out what the problem is. Remember I do not want to just pass in a 3×3 matrix, but any size N×N.
The course notes QR Decomposition with Gram-Schmidt explains exactly what I want to do. Very simple calculation by the way. In the course notes ||u|| means that it is the sum of the square of the elements, so sqrt(x12 + x22 + x32 + .... + xn2).
The multiplication symbol is actually the dot product.
The code I wrote so far is listed below. What is wrong with it?
function qrProjection(arr) {
var qProjected = [];
var tempArray = [];
var aTemp = arr;
var uTemp = new Array(arr.length);
var uSquareSqrt = new Array(arr.length);
var eTemp = [];
var sum = 0;
var sumOfSquares = 0;
var breakCondition = 0;
var secondBreakCondition = 0;
var iterationCounter = 0;
//Build uTemp Array
for (i = 0; i < arr.length; i++) {
uTemp[i] = new Array(arr[i].length);
}
for (i = 0; i < arr.length; i++) {
eTemp[i] = new Array(arr[i].length);
}
uTemp[0] = aTemp[0];
for (j = 0; j <= arr.length; j++) {
for (l = 0; l < arr[j].length; l++) {
if (breakCondition == 1) break;
sumOfSquares = Math.pow(uTemp[j][l], 2) + sumOfSquares;
}
if (breakCondition == 0) {
uSquareSqrt[j] = Math.sqrt(sumOfSquares);
sumOfSquares = 0;
}
for (i = 0; i < arr[j].length; i++) {
if (breakCondition == 1) break;
eTemp[j][i] = (1 / (uSquareSqrt[j])) * (uTemp[j][i]);
}
breakCondition = 1;
if (iterationCounter == 0) {
for (m = 0; m < arr[j].length; m++) {
matrixDotProduct = aTemp[j + 1][m] * eTemp[j][m] + matrixDotProduct;
}
}
else {
for (m = 0; m < arr[j].length; m++) {
for (s = 0; s <= iterationCounter; s++) {
matrixDotProduct = aTemp[j + 1][s] * eTemp[m][s] + matrixDotProduct;
}
for (t = 0; t < arr[j].length; t++) {
uTemp[j + 1][t] = aTemp[j + 1][t] - eTemp[j][t] * matrixDotProduct;
}
}
}
if (iterationCounter == 0) {
for (m = 0; m < arr[j].length; m++) {
uTemp[j + 1][m] = aTemp[j + 1][m] - eTemp[j][m] * matrixDotProduct;
}
}
matrixDotProduct = 0;
for (l = 0; l < arr[j].length; l++) {
sumOfSquares = Math.pow(uTemp[j + 1][l], 2) + sumOfSquares;
}
uSquareSqrt[j + 1] = Math.sqrt(sumOfSquares);
sumOfSquares = 0;
for (i = 0; i < arr[j].length; i++) {
eTemp[j + 1][i] = (1 / (uSquareSqrt[j + 1])) * (uTemp[j + 1][i]);
}
iterationCounter++;
}
qProjected = eTemp;
return qProjected;
}

I must apologize that instead of tweaking your code, I wrote my own from scratch:
/* Main function of interest */
// Each entry of a matrix object represents a column
function gramSchmidt(matrixA, n) {
var totalVectors = matrixA.length;
for (var i = 0; i < totalVectors; i++) {
var tempVector = matrixA[i];
for (var j = 0; j < i; j++) {
var dotProd = dot(matrixA[i], matrixA[j], n);
var toSubtract = multiply(dotProd, matrixA[j], n);
tempVector = subtract(tempVector, toSubtract, n);
}
var nrm = norm(tempVector, n);
matrixA[i] = multiply(1 / nrm, tempVector, n);
}
}
/*
* Example usage:
* var myMatrix = [[1,0,0],[2,3,0],[5,4,7]];
* gramSchmidt(myMatrix, 3);
* ==> myMatrix now equals [[1,0,0],[0,1,0],[0,0,1]]
* 3 here equals the number of dimensions per vector
*/
/* Simple vector arithmetic */
function subtract(vectorX, vectorY, n) {
var result = new Array(n);
for (var i = 0; i < n; i++)
result[i] = vectorX[i] - vectorY[i];
return result;
}
function multiply(scalarC, vectorX, n) {
var result = new Array(n);
for (var i = 0; i < n; i++)
result[i] = scalarC * vectorX[i];
return result;
}
function dot(vectorX, vectorY, n) {
var sum = 0;
for (var i = 0; i < n; i++)
sum += vectorX[i] * vectorY[i];
return sum;
}
function norm(vectorX, n) {
return Math.sqrt(dot(vectorX, vectorX, n));
}
Note that the algorithm above computes the Gram-Schmidt orthogonalization, which is the matrix [e1 | e2 | ... | en], not the QR factorization!