pcut_uwp/PCUT/DeepNestLib.Core/Simplify.cs

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2024-08-21 16:02:56 +00:00
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
namespace DeepNestLib
{
public class Simplify
{
// to suit your point format, run search/replace for '.x' and '.y';
// for 3D version, see 3d branch (configurability would draw significant performance overhead)
// square distance between 2 points
public static double getSqDist(SvgPoint p1, SvgPoint p2)
{
var dx = p1.x - p2.x;
var dy = p1.y - p2.y;
return dx * dx + dy * dy;
}
// square distance from a point to a segment
public static double getSqSegDist(SvgPoint p, SvgPoint p1, SvgPoint p2)
{
var x = p1.x;
var y = p1.y;
var dx = p2.x - x;
var dy = p2.y - y;
if (dx != 0 || dy != 0)
{
var t = ((p.x - x) * dx + (p.y - y) * dy) / (dx * dx + dy * dy);
if (t > 1)
{
x = p2.x;
y = p2.y;
}
else if (t > 0)
{
x += dx * t;
y += dy * t;
}
}
dx = p.x - x;
dy = p.y - y;
return dx * dx + dy * dy;
}
// rest of the code doesn't care about point format
// basic distance-based simplification
public static NFP simplifyRadialDist(NFP points, double? sqTolerance)
{
var prevPoint = points[0];
var newPoints = new NFP();
newPoints.AddPoint(prevPoint);
SvgPoint point = null;
int i = 1;
for (var len = points.length; i < len; i++)
{
point = points[i];
if (point.marked || getSqDist(point, prevPoint) > sqTolerance)
{
newPoints.AddPoint(point);
prevPoint = point;
}
}
if (prevPoint != point) newPoints.AddPoint(point);
return newPoints;
}
public static void simplifyDPStep(NFP points, int first, int last, double? sqTolerance, NFP simplified)
{
var maxSqDist = sqTolerance;
var index = -1;
var marked = false;
for (var i = first + 1; i < last; i++)
{
var sqDist = getSqSegDist(points[i], points[first], points[last]);
if (sqDist > maxSqDist)
{
index = i;
maxSqDist = sqDist;
}
/*if(points[i].marked && maxSqDist <= sqTolerance){
index = i;
marked = true;
}*/
}
/*if(!points[index] && maxSqDist > sqTolerance){
console.log('shit shit shit');
}*/
if (maxSqDist > sqTolerance || marked)
{
if (index - first > 1) simplifyDPStep(points, first, index, sqTolerance, simplified);
simplified.push(points[index]);
if (last - index > 1) simplifyDPStep(points, index, last, sqTolerance, simplified);
}
}
// simplification using Ramer-Douglas-Peucker algorithm
public static NFP simplifyDouglasPeucker(NFP points, double? sqTolerance)
{
var last = points.length - 1;
var simplified = new NFP();
simplified.AddPoint(points[0]);
simplifyDPStep(points, 0, last, sqTolerance, simplified);
simplified.push(points[last]);
return simplified;
}
// both algorithms combined for awesome performance
public static NFP simplify(NFP points, double? tolerance, bool highestQuality)
{
if (points.length <= 2) return points;
var sqTolerance = (tolerance != null) ? (tolerance * tolerance) : 1;
points = highestQuality ? points : simplifyRadialDist(points, sqTolerance);
points = simplifyDouglasPeucker(points, sqTolerance);
return points;
}
}
}