/*
*
* This file is part of the iText (R) project.
Copyright (c) 1998-2017 iText Group NV
* Authors: Bruno Lowagie, Paulo Soares, et al.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License version 3
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* following permission added to Section 15 as permitted in Section 7(a):
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*
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*
* You can be released from the requirements of the license by purchasing
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* develop commercial activities involving the iText software without
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package com.itextpdf.text.pdf.parser;
import com.itextpdf.awt.geom.Point2D;
import java.util.ArrayList;
import java.util.List;
/**
* Represents a Bezier curve.
*
* @since 5.5.6
*/
public class BezierCurve implements Shape {
/**
* If the distance between a point and a line is less than
* this constant, then we consider the point lies on the line.
*/
public static double curveCollinearityEpsilon = 1.0e-30;
/**
* In the case when neither the line ((x1, y1), (x4, y4)) passes
* through both (x2, y2) and (x3, y3) nor (x1, y1) = (x4, y4) we
* use the square of the sum of the distances mentioned below in
* compare to this field as the criterion of good approximation.
* 1. The distance between the line and (x2, y2)
* 2. The distance between the line and (x3, y3)
*/
public static double distanceToleranceSquare = 0.025D;
/**
* The Manhattan distance is used in the case when either the line
* ((x1, y1), (x4, y4)) passes through both (x2, y2) and (x3, y3)
* or (x1, y1) = (x4, y4). The essential observation is that when
* the curve is a uniform speed straight line from end to end, the
* control points are evenly spaced from beginning to end. Our measure
* of how far we deviate from that ideal uses distance of the middle
* controls: point 2 should be halfway between points 1 and 3; point 3
* should be halfway between points 2 and 4.
*/
public static double distanceToleranceManhattan = 0.4D;
private final List<Point2D> controlPoints;
/**
* Constructs new bezier curve.
* @param controlPoints Curve's control points.
*/
public BezierCurve(List<Point2D> controlPoints) {
this.controlPoints = new ArrayList<Point2D>(controlPoints);
}
/**
* {@inheritDoc}
*/
public List<Point2D> getBasePoints() {
return controlPoints;
}
/**
* You can adjust precision of the approximation by varying the following
* parameters: {@link #curveCollinearityEpsilon}, {@link #distanceToleranceSquare},
* {@link #distanceToleranceManhattan}
*
* @return {@link java.util.List} containing points of piecewise linear approximation
* for this bezier curve.
* @since 5.5.6
*/
public List<Point2D> getPiecewiseLinearApproximation() {
List<Point2D> points = new ArrayList<Point2D>();
points.add(controlPoints.get(0));
recursiveApproximation(controlPoints.get(0).getX(), controlPoints.get(0).getY(),
controlPoints.get(1).getX(), controlPoints.get(1).getY(),
controlPoints.get(2).getX(), controlPoints.get(2).getY(),
controlPoints.get(3).getX(), controlPoints.get(3).getY(), points);
points.add(controlPoints.get(controlPoints.size() - 1));
return points;
}
// Based on the De Casteljau's algorithm
private void recursiveApproximation(double x1, double y1, double x2, double y2,
double x3, double y3, double x4, double y4, List<Point2D> points) {
// Subdivision using the De Casteljau's algorithm (t = 0.5)
double x12 = (x1 + x2) / 2;
double y12 = (y1 + y2) / 2;
double x23 = (x2 + x3) / 2;
double y23 = (y2 + y3) / 2;
double x34 = (x3 + x4) / 2;
double y34 = (y3 + y4) / 2;
double x123 = (x12 + x23) / 2;
double y123 = (y12 + y23) / 2;
double x234 = (x23 + x34) / 2;
double y234 = (y23 + y34) / 2;
double x1234 = (x123 + x234) / 2;
double y1234 = (y123 + y234) / 2;
double dx = x4 - x1;
double dy = y4 - y1;
// Constructs the line passing through (x1, y1) and (x4, y4)
// |Ax2 + By2 + C|, where Ax+By+C is the equation for the line mentioned above
double d2 = Math.abs(((x2 - x4) * dy - (y2 - y4) * dx));
// |Ax3 + Bx3 + C|
double d3 = Math.abs(((x3 - x4) * dy - (y3 - y4) * dx));
// True if neither the line passes through both (x2, y2) and (x3, y3)
// nor (x1, y1) = (x4, y4)
if (d2 > curveCollinearityEpsilon || d3 > curveCollinearityEpsilon) {
// True if the square of the distance between (x2, y2) and the line plus
// the distance between (x3, y3) and the line is lower than the tolerance square
if ((d2 + d3) * (d2 + d3) <= distanceToleranceSquare * (dx * dx + dy * dy)) {
points.add(new Point2D.Double(x1234, y1234));
return;
}
} else {
if ((Math.abs(x1 + x3 - x2 - x2) + Math.abs(y1 + y3 - y2 - y2) +
Math.abs(x2 + x4 - x3 - x3) + Math.abs(y2 + y4 - y3 - y3)) <= distanceToleranceManhattan) {
points.add(new Point2D.Double(x1234, y1234));
return;
}
}
recursiveApproximation(x1, y1, x12, y12, x123, y123, x1234, y1234, points);
recursiveApproximation(x1234, y1234, x234, y234, x34, y34, x4, y4, points);
}
}