I'm using JFreeChart to draw chart. I have XYSeries with points (0, 0), (1, 2), (2, 5) and I want to read Y value for let's say x=1.5.
Is it possible to read value for points which are not in XYSeries? I couldn't find similar topic.
This is not supported directly. It does not make sense in many cases: There simply is no data available for x=1.5. The value there could be 1000.0, or -3.141. You don't know.
However, you're most likely looking for a linear interpolation. The pragmatic approach is thus to find the interval that contains the respective x-value, and interpolate the y-values linearly.
There are some technical caveats. E.g. the XYSeries may be not sorted, or may contain duplicate x-values, in which case there is no unique y-value for a given x-value. But for now, we can assume that the data set does not have these properties.
The following is an example of how this could be implemented. Note that this is not very efficient. If you have to compute many intermediate values (that is, if you intend to call the interpolate method very often), it would be beneficial to create a tree-based data structure that allows looking up the interval in O(logn).
However, if this is not time critical (e.g. if you only intend to show the value in a tooltip or so), you may interpolate the values like this:
import java.util.List;
import org.jfree.data.xy.XYDataItem;
import org.jfree.data.xy.XYSeries;
public class XYInterpolation
{
public static void main(String[] args)
{
XYSeries s = new XYSeries("Series");
s.add(0,0);
s.add(1,2);
s.add(2,5);
double minX = -0.5;
double maxX = 3.0;
int steps = 35;
for (int i=0; i<=steps; i++)
{
double a = (double)i / steps;
double x = minX + a * (maxX - minX);
double y = interpolate(s, x);
System.out.printf("%8.3f : %8.3f\n", x, y);
}
}
private static double interpolate(XYSeries s, double x)
{
if (x <= s.getMinX())
{
return s.getY(0).doubleValue();
}
if (x >= s.getMaxX())
{
return s.getY(s.getItemCount()-1).doubleValue();
}
List<?> items = s.getItems();
for (int i=0; i<items.size()-1; i++)
{
XYDataItem i0 = (XYDataItem) items.get(i);
XYDataItem i1 = (XYDataItem) items.get(i+1);
double x0 = i0.getXValue();
double y0 = i0.getYValue();
double x1 = i1.getXValue();
double y1 = i1.getYValue();
if (x >= x0 && x <= x1)
{
double d = x - x0;
double a = d / (x1-x0);
double y = y0 + a * (y1 - y0);
return y;
}
}
// Should never happen
return 0;
}
}
(This implementation clamps at the limits. This means that for x-values that are smaller than the minimum x-value or larger than the maximum x-value, the y-value of the minimum/maximum x-value will be returned, respectively)
You can use DatasetUtils.findYValue() from package org.jfree.data.general
I am trying to detect a circular shape from an image which appears to have very good definition. I do realize that part of the circle is missing but from what I've read about the Hough transform it doesn't seem like that should cause the problem I'm experiencing.
Input:
Output:
Code:
// Read the image
Mat src = Highgui.imread("input.png");
// Convert it to gray
Mat src_gray = new Mat();
Imgproc.cvtColor(src, src_gray, Imgproc.COLOR_BGR2GRAY);
// Reduce the noise so we avoid false circle detection
//Imgproc.GaussianBlur( src_gray, src_gray, new Size(9, 9), 2, 2 );
Mat circles = new Mat();
/// Apply the Hough Transform to find the circles
Imgproc.HoughCircles(src_gray, circles, Imgproc.CV_HOUGH_GRADIENT, 1, 1, 160, 25, 0, 0);
// Draw the circles detected
for( int i = 0; i < circles.cols(); i++ ) {
double[] vCircle = circles.get(0, i);
Point center = new Point(vCircle[0], vCircle[1]);
int radius = (int) Math.round(vCircle[2]);
// circle center
Core.circle(src, center, 3, new Scalar(0, 255, 0), -1, 8, 0);
// circle outline
Core.circle(src, center, radius, new Scalar(0, 0, 255), 3, 8, 0);
}
// Save the visualized detection.
String filename = "output.png";
System.out.println(String.format("Writing %s", filename));
Highgui.imwrite(filename, src);
I have Gaussian blur commented out because (counter intuitively) it was greatly increasing the number of equally inaccurate circles found.
Is there anything wrong with my input image that would cause Hough to not work as well as I expect? Are my parameters way off?
EDIT: first answer brought up a good point about the min/max radius hint for Hough. I resisted adding those parameters as the example image in this post is just one of thousands of images all with varying radii from ~20 to almost infinity.
I've adjusted my RANSAC algorithm from this answer: Detect semi-circle in opencv
Idea:
choose randomly 3 points from your binary edge image
create a circle from those 3 points
test how "good" this circle is
if it is better than the previously best found circle in this image, remember
loop 1-4 until some number of iterations reached. then accept the best found circle.
remove that accepted circle from the image
repeat 1-6 until you have found all circles
problems:
at the moment you must know how many circles you want to find in the image
tested only for that one image.
c++ code
result:
code:
inline void getCircle(cv::Point2f& p1,cv::Point2f& p2,cv::Point2f& p3, cv::Point2f& center, float& radius)
{
float x1 = p1.x;
float x2 = p2.x;
float x3 = p3.x;
float y1 = p1.y;
float y2 = p2.y;
float y3 = p3.y;
// PLEASE CHECK FOR TYPOS IN THE FORMULA :)
center.x = (x1*x1+y1*y1)*(y2-y3) + (x2*x2+y2*y2)*(y3-y1) + (x3*x3+y3*y3)*(y1-y2);
center.x /= ( 2*(x1*(y2-y3) - y1*(x2-x3) + x2*y3 - x3*y2) );
center.y = (x1*x1 + y1*y1)*(x3-x2) + (x2*x2+y2*y2)*(x1-x3) + (x3*x3 + y3*y3)*(x2-x1);
center.y /= ( 2*(x1*(y2-y3) - y1*(x2-x3) + x2*y3 - x3*y2) );
radius = sqrt((center.x-x1)*(center.x-x1) + (center.y-y1)*(center.y-y1));
}
std::vector<cv::Point2f> getPointPositions(cv::Mat binaryImage)
{
std::vector<cv::Point2f> pointPositions;
for(unsigned int y=0; y<binaryImage.rows; ++y)
{
//unsigned char* rowPtr = binaryImage.ptr<unsigned char>(y);
for(unsigned int x=0; x<binaryImage.cols; ++x)
{
//if(rowPtr[x] > 0) pointPositions.push_back(cv::Point2i(x,y));
if(binaryImage.at<unsigned char>(y,x) > 0) pointPositions.push_back(cv::Point2f(x,y));
}
}
return pointPositions;
}
float verifyCircle(cv::Mat dt, cv::Point2f center, float radius, std::vector<cv::Point2f> & inlierSet)
{
unsigned int counter = 0;
unsigned int inlier = 0;
float minInlierDist = 2.0f;
float maxInlierDistMax = 100.0f;
float maxInlierDist = radius/25.0f;
if(maxInlierDist<minInlierDist) maxInlierDist = minInlierDist;
if(maxInlierDist>maxInlierDistMax) maxInlierDist = maxInlierDistMax;
// choose samples along the circle and count inlier percentage
for(float t =0; t<2*3.14159265359f; t+= 0.05f)
{
counter++;
float cX = radius*cos(t) + center.x;
float cY = radius*sin(t) + center.y;
if(cX < dt.cols)
if(cX >= 0)
if(cY < dt.rows)
if(cY >= 0)
if(dt.at<float>(cY,cX) < maxInlierDist)
{
inlier++;
inlierSet.push_back(cv::Point2f(cX,cY));
}
}
return (float)inlier/float(counter);
}
float evaluateCircle(cv::Mat dt, cv::Point2f center, float radius)
{
float completeDistance = 0.0f;
int counter = 0;
float maxDist = 1.0f; //TODO: this might depend on the size of the circle!
float minStep = 0.001f;
// choose samples along the circle and count inlier percentage
//HERE IS THE TRICK that no minimum/maximum circle is used, the number of generated points along the circle depends on the radius.
// if this is too slow for you (e.g. too many points created for each circle), increase the step parameter, but only by factor so that it still depends on the radius
// the parameter step depends on the circle size, otherwise small circles will create more inlier on the circle
float step = 2*3.14159265359f / (6.0f * radius);
if(step < minStep) step = minStep; // TODO: find a good value here.
//for(float t =0; t<2*3.14159265359f; t+= 0.05f) // this one which doesnt depend on the radius, is much worse!
for(float t =0; t<2*3.14159265359f; t+= step)
{
float cX = radius*cos(t) + center.x;
float cY = radius*sin(t) + center.y;
if(cX < dt.cols)
if(cX >= 0)
if(cY < dt.rows)
if(cY >= 0)
if(dt.at<float>(cY,cX) <= maxDist)
{
completeDistance += dt.at<float>(cY,cX);
counter++;
}
}
return counter;
}
int main()
{
//RANSAC
cv::Mat color = cv::imread("HoughCirclesAccuracy.png");
// convert to grayscale
cv::Mat gray;
cv::cvtColor(color, gray, CV_RGB2GRAY);
// get binary image
cv::Mat mask = gray > 0;
unsigned int numberOfCirclesToDetect = 2; // TODO: if unknown, you'll have to find some nice criteria to stop finding more (semi-) circles
for(unsigned int j=0; j<numberOfCirclesToDetect; ++j)
{
std::vector<cv::Point2f> edgePositions;
edgePositions = getPointPositions(mask);
std::cout << "number of edge positions: " << edgePositions.size() << std::endl;
// create distance transform to efficiently evaluate distance to nearest edge
cv::Mat dt;
cv::distanceTransform(255-mask, dt,CV_DIST_L1, 3);
unsigned int nIterations = 0;
cv::Point2f bestCircleCenter;
float bestCircleRadius;
//float bestCVal = FLT_MAX;
float bestCVal = -1;
//float minCircleRadius = 20.0f; // TODO: if you have some knowledge about your image you might be able to adjust the minimum circle radius parameter.
float minCircleRadius = 0.0f;
//TODO: implement some more intelligent ransac without fixed number of iterations
for(unsigned int i=0; i<2000; ++i)
{
//RANSAC: randomly choose 3 point and create a circle:
//TODO: choose randomly but more intelligent,
//so that it is more likely to choose three points of a circle.
//For example if there are many small circles, it is unlikely to randomly choose 3 points of the same circle.
unsigned int idx1 = rand()%edgePositions.size();
unsigned int idx2 = rand()%edgePositions.size();
unsigned int idx3 = rand()%edgePositions.size();
// we need 3 different samples:
if(idx1 == idx2) continue;
if(idx1 == idx3) continue;
if(idx3 == idx2) continue;
// create circle from 3 points:
cv::Point2f center; float radius;
getCircle(edgePositions[idx1],edgePositions[idx2],edgePositions[idx3],center,radius);
if(radius < minCircleRadius)continue;
//verify or falsify the circle by inlier counting:
//float cPerc = verifyCircle(dt,center,radius, inlierSet);
float cVal = evaluateCircle(dt,center,radius);
if(cVal > bestCVal)
{
bestCVal = cVal;
bestCircleRadius = radius;
bestCircleCenter = center;
}
++nIterations;
}
std::cout << "current best circle: " << bestCircleCenter << " with radius: " << bestCircleRadius << " and nInlier " << bestCVal << std::endl;
cv::circle(color,bestCircleCenter,bestCircleRadius,cv::Scalar(0,0,255));
//TODO: hold and save the detected circle.
//TODO: instead of overwriting the mask with a drawn circle it might be better to hold and ignore detected circles and dont count new circles which are too close to the old one.
// in this current version the chosen radius to overwrite the mask is fixed and might remove parts of other circles too!
// update mask: remove the detected circle!
cv::circle(mask,bestCircleCenter, bestCircleRadius, 0, 10); // here the radius is fixed which isnt so nice.
}
cv::namedWindow("edges"); cv::imshow("edges", mask);
cv::namedWindow("color"); cv::imshow("color", color);
cv::imwrite("detectedCircles.png", color);
cv::waitKey(-1);
return 0;
}
If you'd set minRadius and maxRadius paramaeters properly, it'd give you good results.
For your image, I tried following parameters.
method - CV_HOUGH_GRADIENT
minDist - 100
dp - 1
param1 - 80
param2 - 10
minRadius - 250
maxRadius - 300
I got the following output
Note: I tried this in C++.
I was recently using the Java Area class to wrap up a Rectangle2D.Double type. So that I can do manipulations like intersect, add, etc. However, when it comes to the calculation of the area of the shape, I was getting a quite weird result. Below is the code I'm using to calculate the area of a shape:
private static double polyArea(ArrayList<Point2D.Double> pointList) {
double area = 0;
for (int loopi = 1; loopi < pointList.size(); loopi++) {
Point2D.Double p1 = pointList.get(loopi - 1);
Point2D.Double p2 = pointList.get(loopi);
area += (p1.x * p2.y - p2.x * p1.y) / 2.0;
}
return area;
}
public static double coverageArea(Shape s) {
ArrayList<Point2D.Double> pointList = new ArrayList<Point2D.Double>();
double[] coords = new double[6];
int type;
double totalArea = 0;
PathIterator it = s.getPathIterator(null);
while (!it.isDone()) {
type = it.currentSegment(coords);
if (type == it.SEG_MOVETO) {
pointList.clear();
pointList.add(new Point2D.Double(coords[0], coords[1]));
} else if (type == it.SEG_LINETO) {
pointList.add(new Point2D.Double(coords[0], coords[1]));
} else if (type == it.SEG_CLOSE) {
totalArea += polyArea(pointList);
pointList.clear();
} else {
System.out.println("calculateShapeArea: Cannot calculate area for shapes with segment type other than SEG_MOVETO, SEG_LINETO, or SEG_CLOSE. Ignoring segment type=" + type);
}
it.next();
}
if (totalArea < 0) {
totalArea = -totalArea;
}
return totalArea;
}
If I have a Rectangle2D r(1.0, 1.0, 6.0, 6.0), using the above code I will get the area correctly 36. However if I do a = new Area(r), then the result of coverageArea(a) is 39. Sometimes it could be tens of times larger than the correct answer.
Anyone knows why this is happening? Is there any problem with the area calculation? Any advice would be appreciated!
According to this Wiki, your code is not implementing the method correctly. Your polyArea() method forget to close the polygon (it does not consider the line from the last to the first vertex).
Also your version of the formula seems to have exchanged p1 and p2, although I'm not sure if thats a problem, I don't personally understand how this method really works.
Solved, used this code:
if ( !isClockwise(TempVectArray) ) { Collections.reverse(TempVectArray); }
...
private boolean isClockwise(ArrayList<Vec2> arl){
Iterator<Vec2> it = arl.iterator();
Vec2 pt1 = (Vec2)it.next();
Vec2 firstPt = pt1;
Vec2 lastPt = null;
double area = 0.0;
while(it.hasNext()){
Vec2 pt2 = (Vec2) it.next();
area += (((pt2.x - pt1.x) * (pt2.y + pt1.y)) / 2);
pt1 = pt2;
lastPt = pt1;
}
area += (((firstPt.x - lastPt.x) * (firstPt.y + lastPt.y)) / 2);
return area < 0;
}
Suppose I get a vertex array from the user tapping on the screen, but need it to be clockwise.
Maybe you know of some standard methods to check if it is clockwise and if it's not, then make it clockwise?
Thanks!
One way to do it is to first calculate the average point, and then sort everything around it by angle. Should be something like this:
public static void sortPointsClockwise(ArrayList<PointF> points) {
float averageX = 0;
float averageY = 0;
for (PointF point : points) {
averageX += point.x;
averageY += point.y;
}
final float finalAverageX = averageX / points.size();
final float finalAverageY = averageY / points.size();
Comparator<PointF> comparator = new Comparator<PointF>() {
public int compare(PointF lhs, PointF rhs) {
double lhsAngle = Math.atan2(lhs.y - finalAverageY, lhs.x - finalAverageX);
double rhsAngle = Math.atan2(rhs.y - finalAverageY, rhs.x - finalAverageX);
// Depending on the coordinate system, you might need to reverse these two conditions
if (lhsAngle < rhsAngle) return -1;
if (lhsAngle > rhsAngle) return 1;
return 0;
}
};
Collections.sort(points, comparator);
}
public static void sortPointsCounterClockwise(ArrayList<PointF> points) {
sortPointsClockwise(points);
Collections.reverse(points);
}
You have the sequence numbers and positions of the nodes. Get the movements which hold x and y changes in the move. All left to do is define a control structure such as:
if(movement_before is "up")
movement should-be "up" or "up-right"
if(movement_before is "up-left")
movement should-be "up" or "up-left" or "up-right"
etc..
I have a program where an entity moves around in two-dimensional space. To move one step, the entity picks its next point, and then sets it as his current point.
Sometimes, however, the entity's next point lies in an Area (java.awt.geom.Area) that is forbidden (the "forbidden area" is actually a velocity obstacle).
How can the entity pick the point outside the Area which is closest to the entity's preferred point?
The Area is composed of different shapes (sometimes, the shapes are not touching).
My initial plan was to simply draw a line to the preferred point. Wherever the line intersected the Area first, this would be the next-best point. However, finding the intersection between a line and an Area turns out to be quite complex.
EDIT: This wouldn't necessarily find the closest point. This would just find the closet point on the same trajectory. I'm looking for the closest possible point.
Perhaps Area isn't the best class to use. All I require is something that can add multiple shapes, even when the shapes aren't touching.
I've solved the problem:
First, find all the line segments that constrain the Area. I've written code to do that on a different answer.
Then, it's just a matter of iterating through each line segment, and recording the point on the segment that's closest to the entity's desired point. Store these in the data structure of your choice (e.g., an ArrayList).
See: Shortest distance between a point and a line segment
Lastly, determine which of the points is closest to the desired point. Voilà!
Here's a demonstration:
import java.awt.Color;
import java.awt.Dimension;
import java.awt.Graphics;
import java.awt.Graphics2D;
import java.awt.geom.Area;
import java.awt.geom.Ellipse2D;
import java.awt.geom.Line2D;
import java.awt.geom.Path2D;
import java.awt.geom.PathIterator;
import java.awt.geom.Point2D;
import java.util.ArrayList;
import java.util.Random;
import javax.swing.JFrame;
public class AreaTest extends JFrame{
private static final long serialVersionUID = -2221432546854106311L;
Area area = new Area();
ArrayList<Line2D.Double> areaSegments = new ArrayList<Line2D.Double>();
Point2D.Double insidePoint = new Point2D.Double(225, 225);
Point2D.Double closestPoint = new Point2D.Double(-1, -1);
Point2D.Double bestPoint = new Point2D.Double(-1, -1);
ArrayList<Point2D.Double> closestPointList = new ArrayList<Point2D.Double>();
AreaTest() {
Path2D.Double triangle = new Path2D.Double();
Random random = new Random();
// Draw three random triangles
for (int i = 0; i < 3; i++) {
triangle.moveTo(random.nextInt(400) + 50, random.nextInt(400) + 50);
triangle.lineTo(random.nextInt(400) + 50, random.nextInt(400) + 50);
triangle.lineTo(random.nextInt(400) + 50, random.nextInt(400) + 50);
triangle.closePath();
area.add(new Area(triangle));
triangle.reset();
}
// Place a point inside the area
if (!area.contains(insidePoint)); {
while (!area.contains(insidePoint)) {
insidePoint.setLocation(random.nextInt(400) + 50, random.nextInt(400) + 50);
}
}
// Note: we're storing double[] and not Point2D.Double
ArrayList<double[]> areaPoints = new ArrayList<double[]>();
double[] coords = new double[6];
for (PathIterator pi = area.getPathIterator(null); !pi.isDone(); pi.next()) {
// Because the Area is composed of straight lines
int type = pi.currentSegment(coords);
// We record a double array of {segment type, x coord, y coord}
double[] pathIteratorCoords = {type, coords[0], coords[1]};
areaPoints.add(pathIteratorCoords);
}
double[] start = new double[3]; // To record where each polygon starts
for (int i = 0; i < areaPoints.size(); i++) {
// If we're not on the last point, return a line from this point to the next
double[] currentElement = areaPoints.get(i);
// We need a default value in case we've reached the end of the ArrayList
double[] nextElement = {-1, -1, -1};
if (i < areaPoints.size() - 1) {
nextElement = areaPoints.get(i + 1);
}
// Make the lines
if (currentElement[0] == PathIterator.SEG_MOVETO) {
start = currentElement; // Record where the polygon started to close it later
}
if (nextElement[0] == PathIterator.SEG_LINETO) {
areaSegments.add(
new Line2D.Double(
currentElement[1], currentElement[2],
nextElement[1], nextElement[2]
)
);
} else if (nextElement[0] == PathIterator.SEG_CLOSE) {
areaSegments.add(
new Line2D.Double(
currentElement[1], currentElement[2],
start[1], start[2]
)
);
}
}
// Calculate the nearest point on the edge
for (Line2D.Double line : areaSegments) {
// From: https://stackoverflow.com/questions/6176227
double u =
((insidePoint.getX() - line.x1) * (line.x2 - line.x1) + (insidePoint.getY() - line.y1) * (line.y2 - line.y1))
/ ((line.x2 - line.x1) * (line.x2 - line.x1) + (line.y2 - line.y1) * (line.y2 - line.y1));
double xu = line.x1 + u * (line.x2 - line.x1);
double yu = line.y1 + u * (line.y2 - line.y1);
if (u < 0) {
closestPoint.setLocation(line.getP1());
} else if (u > 1) {
closestPoint.setLocation(line.getP2());
} else {
closestPoint.setLocation(xu, yu);
}
closestPointList.add((Point2D.Double) closestPoint.clone());
if (closestPoint.distance(insidePoint) < bestPoint.distance(insidePoint)) {
bestPoint.setLocation(closestPoint);
}
}
setSize(new Dimension(500, 500));
setLocationRelativeTo(null); // To center the JFrame on screen
setDefaultCloseOperation(EXIT_ON_CLOSE);
setResizable(false);
setVisible(true);
}
public void paint(Graphics g) {
// Fill the area
Graphics2D g2d = (Graphics2D) g;
g.setColor(Color.lightGray);
g2d.fill(area);
// Draw the border line by line
g.setColor(Color.black);
for (Line2D.Double line : areaSegments) {
g2d.draw(line);
}
// Draw the inside point
g.setColor(Color.red);
g2d.fill(
new Ellipse2D.Double(
insidePoint.getX() - 3,
insidePoint.getY() - 3,
6,
6
)
);
// Draw the other close points
for (Point2D.Double point : closestPointList) {
g.setColor(Color.black);
g2d.fill(
new Ellipse2D.Double(
point.getX() - 3,
point.getY() - 3,
6,
6
)
);
}
// Draw the outside point
g.setColor(Color.green);
g2d.fill(
new Ellipse2D.Double(
bestPoint.getX() - 3,
bestPoint.getY() - 3,
6,
6
)
);
}
public static void main(String[] args) {
new AreaTest();
}
}
Here's the result:
And again:
View my answer on this post
You can get the closest point outside of a polygon with a simple and lightweight approach:
Simply find the closest line segment, and find the perpendicular angle to that segment that intercepts the input point.
Example Code:
Vector2 is 2 doubles, x and y (Like Unity)
public class PolyCollisions {
// Call this function...
public static Vector2 doCollisions (Vector2[] polygon, Vector2 point) {
if(!pointIsInPoly(polygon, point)) {
// The point is not colliding with the polygon, so it does not need to change location
return point;
}
// Get the closest point off the polygon
return closestPointOutsidePolygon(polygon, point);
}
// Check if the given point is within the given polygon (Vertexes)
//
// If so, call on collision if required, and move the point to the
// closest point outside of the polygon
public static boolean pointIsInPoly(Vector2[] verts, Vector2 p) {
int nvert = verts.length;
double[] vertx = new double[nvert];
double[] verty = new double[nvert];
for(int i = 0; i < nvert; i++) {
Vector2 vert = verts[i];
vertx[i] = vert.x;
verty[i] = vert.y;
}
double testx = p.x;
double testy = p.y;
int i, j;
boolean c = false;
for (i = 0, j = nvert-1; i < nvert; j = i++) {
if ( ((verty[i]>testy) != (verty[j]>testy)) &&
(testx < (vertx[j]-vertx[i]) * (testy-verty[i]) / (verty[j]-verty[i]) + vertx[i]) )
c = !c;
}
return c;
}
// Gets the closed point that isn't inside the polygon...
public static Vector2 closestPointOutsidePolygon (Vector2[] poly, Vector2 point) {
return getClosestPointInSegment(closestSegment(poly, point), point);
}
public static Vector2 getClosestPointInSegment (Vector2[] segment, Vector2 point) {
return newPointFromCollision(segment[0], segment[1], point);
}
public static Vector2 newPointFromCollision (Vector2 aLine, Vector2 bLine, Vector2 p) {
return nearestPointOnLine(aLine.x, aLine.y, bLine.x, bLine.y, p.x, p.y);
}
public static Vector2 nearestPointOnLine(double ax, double ay, double bx, double by, double px, double py) {
// https://stackoverflow.com/questions/1459368/snap-point-to-a-line-java
double apx = px - ax;
double apy = py - ay;
double abx = bx - ax;
double aby = by - ay;
double ab2 = abx * abx + aby * aby;
double ap_ab = apx * abx + apy * aby;
double t = ap_ab / ab2;
if (t < 0) {
t = 0;
} else if (t > 1) {
t = 1;
}
return new Vector2(ax + abx * t, ay + aby * t);
}
public static Vector2[] closestSegment (Vector2[] points, Vector2 point) {
Vector2[] returns = new Vector2[2];
int index = closestPointIndex(points, point);
returns[0] = points[index];
Vector2[] neighbors = new Vector2[] {
points[(index+1+points.length)%points.length],
points[(index-1+points.length)%points.length]
};
double[] neighborAngles = new double[] {
getAngle(new Vector2[] {point, returns[0], neighbors[0]}),
getAngle(new Vector2[] {point, returns[0], neighbors[1]})
};
if(neighborAngles[0] < neighborAngles[1]) {
returns[1] = neighbors[0];
} else {
returns[1] = neighbors[0];
}
return returns;
}
public static double getAngle (Vector2[] abc) {
// https://stackoverflow.com/questions/1211212/how-to-calculate-an-angle-from-three-points
// atan2(P2.y - P1.y, P2.x - P1.x) - atan2(P3.y - P1.y, P3.x - P1.x)
return Math.atan2(abc[2].y - abc[0].y, abc[2].x - abc[0].x) - Math.atan2(abc[1].y - abc[0].y, abc[1].x - abc[0].x);
}
//public static Vector2 lerp (Vector2 a, Vector2 b, double c) {
//
// return new Vector2(c*(a.x-b.x)+b.x, c*(a.y-b.y)+b.y);
//
//}
/*public static Vector2 closestPoint (Vector2[] points, Vector2 point) {
int leastDistanceIndex = 0;
double leastDistance = Double.MAX_VALUE;
for(int i = 0; i < points.length; i++) {
double dist = distance(points[i], point);
if(dist < leastDistance) {
leastDistanceIndex = i;
leastDistance = dist;
}
}
return points[leastDistanceIndex];
}*/
public static int closestPointIndex (Vector2[] points, Vector2 point) {
int leastDistanceIndex = 0;
double leastDistance = Double.MAX_VALUE;
for(int i = 0; i < points.length; i++) {
double dist = distance(points[i], point);
if(dist < leastDistance) {
leastDistanceIndex = i;
leastDistance = dist;
}
}
return leastDistanceIndex;
}
public static double distance (Vector2 a, Vector2 b) {
return Math.sqrt(Math.pow(Math.abs(a.x-b.x), 2)+Math.pow(Math.abs(a.y-b.y), 2));
}
}
Useful Links / Answers
Snap Point to Line
How to calculate an angle from 3 points
The most easy (and most inefficient) approach would be a brute force.
You have a preferred point inside an area. to find the closest point to it: hold two variables, one for minimal distance and one for current closest point. now simply step over every other point in your two dimensional space: if that point is not inside the forbidden area (or any forbidden area if there are many), then calculate the distance between it and the preferred point. If that distance is less than the current minimal distance, then make it become the current minimal distance and make the point become the current closest point.
when you finish, you will have the closest point outside the area and if none was found, you stay on your original point.
I am not specialist in geometry algorithms, but if the two dimensional space is very big and the calculation is not finishing fast enough, maybe you can try to improve it with the following: the Area class has a contains method that "tests if the interior of the Shape entirely contains the specified rectangular area". therefore, start creating rectangles(or squares) around the preferred point. you start with the minimal rectangle surrounding the point and on every loop you increase it by one point in each direction. for every rectangle that you create, check if it is contained in the area. you stop calculating rectangles when you hit the first rectangle that is not entirely contained in the area. then, you use the above algorithm (the brute force) but only on points contained in this rectangle and that are not inside the area.
The formula for distance between two points is (javascript):
var xDiff = ( point1x - point2x ),
yDiff = ( point1y - point2y ),
distance = Math.sqrt( ( xDiff * xDiff ) + ( yDiff * yDiff ) );
Loop around your "proposed new point", starting at one x-1, y-1 to x+1, y+1. At each point check to see that it's not a forbidden point, not the point you just came from, and not off the boundaries of the map. If it meets all those criteria, use the above formula to measure the distance and add it to an array. At the end of your "1-point out" loop, check if there are any distances in that array. If so, take the smallest one and you're done. If there aren't any, move onto x-2, y-2 to x+2, y+2 (2 points out).
This will be extremely fast for the small area you are referring to.
Demo: http://jsfiddle.net/ThinkingStiff/V7Bqm/
var X = 0,
Y = 1,
currentPoint = [5,5],
proposedPoint = [5,6],
forbiddenPoints = [[5,6],[6,6],[4,7],[5,7],[6,7],[4,8],[5,8]],
map = { left:1, top:1, right:10, bottom:10 };
function closestSafePoint( point ) {
var x = point[X], y = point[Y], safePoints = [];
for( var left = x - 1, top = y - 1, right = x + 1, bottom = y + 1;
left <= map.left || top <= map.top || right <= map.right || bottom <= map.bottom;
left--, top--, right++, bottom++) {
checkHorizontalPoints( safePoints, point, left, right, top );
checkHorizontalPoints( safePoints, point, left, right, bottom );
checkVerticalPoints( safePoints, point, top + 1, bottom - 1, left );
checkVerticalPoints( safePoints, point, top + 1, bottom - 1, right );
safePoints.sort( function( a, b ){ return a[1] - b[1] } );
return safePoints.length ? safePoints[0] : point;
};
};
function checkHorizontalPoints( points, fromPoint, startX, endX, y ) {
for( var x = startX; x <= endX ; x++ ) {
var toPoint = [x, y];
if( !isForbidden( toPoint ) && !isCurrent( toPoint) && onMap( toPoint ) ) {
points.push( [toPoint, distance( fromPoint, toPoint )] );
};
};
};
function checkVerticalPoints( points, fromPoint, startY, endY, x ) {
for( var y = startY; y <= endY ; y++ ) {
var toPoint = [x, y];
if( !isForbidden( toPoint ) && !isCurrent( toPoint) && onMap( toPoint ) ) {
points.push( [toPoint, distance( fromPoint, toPoint )] );
};
};
};
function isForbidden( point ) {
for( var index = 0; index < forbiddenPoints.length; index++ ) {
if( forbiddenPoints[index].toString() == point.toString() ) return true;
};
};
function isCurrent( point ) {
return currentPoint.toString() == point.toString() ? true : false;
};
function onMap( point ) {
var x = point[X], y = point[Y];
return x >= map.left && y >= map.top && x <= map.right && y <= map.bottom;
};
function distance( pointA, pointB ) {
var xDiff = ( pointA[X] - pointB[X] ),
yDiff = ( pointA[Y] - pointB[Y] );
return Math.sqrt( ( xDiff * xDiff ) + ( yDiff * yDiff ) );
};
console.log(
'current: ' + currentPoint + ', '
+ 'proposed: ' + proposedPoint + ', '
+ 'closest: ' + closestSafePoint( proposedPoint )[0]
);
One optimization you could make to this, if you're fairly sure most of your safe spots will be one or two points away is to break out as soon as you get to a point thats distance is the same as the level you're on. So if you're on loop one, and you get a point that is distance = 1, stop, since you'll never get closer than that.
UPDATE: I noticed you added "same trajectory" to your question. But in one of the comments, you also say it can't jump over the forbidden area. Those statements seem to conflict.
Same trajectory is a little more tricky and requires some trig. Check out my demo of circular divs at http://jsfiddle.net/ThinkingStiff/uLu7v/. There is a "point on ray" function halfway down at:
$this.siblings( ".circle" ).each( function()
This calculates the distance to move the surrounding circles on a ray away from the selected circle. This could be used to calculate a point on your trajectory. But, I think my original function is actually what you're looking for and you didn't mean same trajectory.