graphData = []
graphData
accuracy = {
var error = 275;
var accuracy = 0;
var distanceAvg = 0;
for (var i = 0; i < graphData.length; i++) {
var smallest = 9999;
for (var j = 0; j < check.length; j++) {
var distance = Math.sqrt(Math.pow((check[j][0]-graphData[i][0]),2) + Math.pow((check[j][1]-graphData[i][1]),2));
if (smallest > distance) smallest = distance;
}
distanceAvg += smallest;
}
distanceAvg /= graphData.length
if (distanceAvg < error && distanceAvg > error * .8) accuracy = 0.2;
if (distanceAvg < error * .8 && distanceAvg > error * .6) accuracy = 0.4;
if (distanceAvg < error * .6 && distanceAvg > error * .4) accuracy = 0.6;
if (distanceAvg < error * .4 && distanceAvg > error * .2) accuracy = 0.8;
if (distanceAvg < error * .2 && distanceAvg > 0) accuracy = 1;
return accuracy
}
pathCoordinates = [[0,10], [20, 50], [20, 50], [40, 50], [50, 70], [60,80], [90,100]]
l = draw.getTotalLength();
check = d3.range(l+1).map((d,i)=> [draw.getPointAtLength(d).x,draw.getPointAtLength(d).y])
x = d3.scaleLinear()
.domain(d3.extent(pathCoordinates,(d,i)=>d[0]))
.range ([margin.left, width - margin.right])
y = d3.scaleLinear()
.domain(d3.extent(pathCoordinates,(d,i)=>d[1]))
.range ([ height - margin.bottom, margin.top ])
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
