var siuColours = {	black: "#262638",
					purple: "#414258",
					purple10: "#5B5C72",
					purple20: "#74758B",
					purple30: "#8E8FA5",
					teal: "#588D97",
					teal10: "#72A7B1",
					teal20: "#8BC0CA",
					teal30: "#A5DAE4",
					green: "#315259",
					green10: "#4B6C73",
					green20: "#64858C",
					green30: "#7E9FA6",
					orange: "#F47C20",
					orange10: "#FF963A",
					orange20: "#FFAF53",
					orange30: "#FFC96D",
					greyDark: "#BDBAC0",
					greyLight: "#D1D3D4"
				};

function roundUpToNearestFive(n) {
	return 5 * ( Math.ceil(n/5) );;
};

function formatNumberWithCommas(n) {
    var numberSegment = n.toString().split(".");
    numberSegment[0] = numberSegment[0].replace(/\B(?=(\d{3})+(?!\d))/g, ",");
    return numberSegment.join(".");
}

//http://trentrichardson.com/2010/04/06/compute-linear-regressions-in-javascript/
function linearRegression(y,x){
		var lr = {};
		var n = y.length;
		var sum_x = 0;
		var sum_y = 0;
		var sum_xy = 0;
		var sum_xx = 0;
		var sum_yy = 0;

		for (var i = 0; i < y.length; i++) {

			sum_x += x[i];
			sum_y += y[i];
			sum_xy += (x[i]*y[i]);
			sum_xx += (x[i]*x[i]);
			sum_yy += (y[i]*y[i]);
		}

		lr['slope'] = (n * sum_xy - sum_x * sum_y) / (n*sum_xx - sum_x * sum_x);
		lr['intercept'] = (sum_y - lr.slope * sum_x)/n;
		lr['r2'] = Math.pow((n*sum_xy - sum_x*sum_y)/Math.sqrt((n*sum_xx-sum_x*sum_x)*(n*sum_yy-sum_y*sum_y)),2);

		return lr;
}