LINQ: Combining vectors - linq

I have two vectors of type float (to simplify here, I have used vector's length of 3 items):
float[] a = new float[] { 10.0f, 20.0f, 30.0f };
float[] b = new float[] { 5.0f, 10.0f, 20.0f };
I need to substract b from a in a pair wise way and keep two vectors (Result and remaining quantity). The result corresponds to a-b and the remaining quantity corresponds to that quantity that cannot be substracted from a (see example 2):
Example 1:
a | b | Result | Remaining quantity (quantity that cannot be substracted from a)
(b remainder)
------------------------------------------------
10.0f 5.0f 5.0f 0f
20.0f 10.0f 10.0f 0f
30.0f 20.0f 10.0f 0f
In above example, remaining quantities are always 0 because b's quantities are always less or equal to a's quantities, but, if any quantity in b is greater than that in a, only the quantity of a can be substracted at most and then the remaining quantity should be b remainder that has not been possible to substract from a, for example, imagine following scenario:
Example 2:
float[] a = new float[] { 10.0f, 5.0f, 30.0f };
float[] b = new float[] { 5.0f, 10.0f, 20.0f };
a | b | Result | Remaining (quantity that cannot be substracted from a)
(b remainder)
--------------------------------
10.0f 5.0f 5.0f 0f
5.0f 10.0f 0.0f 5f
30.0f 20.0f 10.0f 0f
After operation I need to obtain in two vectors the Result and Remaining. How could it be done efficiently using LINQ and some function like Zip or something?
Thanks in advance!
EDIT:
I am trying to do the following:
float[] remainder = new float[<same lenght of a or b>];
Result= a
.Zip(b, (x, y) =>
{
remainder[i] = 0;
if (y > x)
{
remainder[i] = y - x;
return 0;
}
else
{
return x- y;
}
}).ToArray();
My problem now is to know how to get the index of the current iteration, in my case this 'i' is used but how to achieve this?

This is how you could do it.
Result = a.Zip(b, (x, y) => new { x, y }).Select((a,i) =>
{
remainder[i] = 0;
if (a.y > a.x)
{
remainder[i] = a.y - a.x;
return 0;
}
else
{
return a.x- a.y;
}
}).ToArray();
It uses the indexed overload of IEnumerable.Select.

Related

Drawing ellipse with Bresenham's algorithm

Hello,
I'm trying to draw an ellipse, which is parallel to the orthogonal system, using Bresenham's algorithm. I want to draw the top-left (W,SW,S) quarter of the ellipse, and then deduce others.
To do this, i'm using an incremental algorithm with the second-order logic. I did it from another algorithm that draw the top-right quarter first, but what i'm doing isn't working.
The problem appears when the 2nd region is drawing, and I don't know where it comes from.
You can see what I have (black), and what I expect (green):
(center of the ellipse (xc, yc) and the upper right button (x2,y2) that is ~(xc+30,yc+20) in this example)
(a is abs(x2-xc), and b is abs(y2-yc))
The first parameter is the middle of the ellipse (xc, yc), the second is the upper right point established the x and y radius. You can see the ellipse goes too far (2 points on the left and on the right). You can see an other example
(center of the ellipse (xc, yc) and the upper right button (x2,y2) that is ~(xc+15,yc+18) in this example)
The algorithm is deduced from the incremental algorithm with the second-order logic.
Here is my code, (a is abs(x2-xc), and b is abs(y2-yc))
ellipse(int a, int b, int xc, int yc) {
int a2 = a*a, b2 = b*b;
int x = 0, y = b; //Starting point
int incSW = b2*2 + a2*2;
int deltaW = b2*(-2*x + 3); //deduced from incremental algorithm with the second-order logic
int deltaS = a2*(-2*y + 3);
int deltaSW = deltaW + deltaS;
int d1 = b2 - a2*b + a2/4; //dp starting value in the first region
int d2 = b2*(x - 0.5)*(x - 0.5) + a2*(y - 1)*(y - 1) - a2*b2; //dp starting value in the second region
//First region
while(a2*(y-0.5) >= b2*(-x-1)) {
DrawPixel(g,-x+xc, -y+yc); // 1st case
DrawPixel(g,-x+xc, y+yc); // 2nd case
DrawPixel(g,x+xc, y+yc); // 3rd case
DrawPixel(g,x+xc, -y+yc); // 4th case
if(d1>0) {
d1+=deltaSW;
deltaW+=b2*2;
deltaSW+=incSW;
y--;
}
else {
d1+=deltaW;
deltaW+=2*b2;
deltaSW+=2*b2;
}
x--;
}
deltaSW = b2*(2 - 2*x) + a2*(-2*y + 3);
//Second region
while(y>=0) {
DrawPixel(g,-x+xc, -y+yc); // 1st case
DrawPixel(g,-x+xc, y+yc); // 2nd case
DrawPixel(g,x+xc, y+yc); // 3rd case
DrawPixel(g,x+xc, -y+yc); // 4th case
if(d2>0) {
d2+=deltaS;
deltaS+=a2*2;
deltaSW+=a2*2;
}
else {
d2+=deltaSW;
deltaSW+=incSW;
deltaS+=a2*2;
x--;
}
y--;
}
}
I hope you can help me, thanks.
Using the error term e = a x^2 + b y^2 - r^2, it's pretty easy to show that a step from (x,y) to (x,y+1) changes the error by 2by + b, a step to (x+1,y+1) by 2ax + a + 2by + b, and a step to (x+1,y) by 2ax + a.
Starting from a point (-x0, 0), choose the least absolute error step from these three. The first two cases are the norm for the "first region" as you call it.
The first time a step right, (x,y) to (x+1,y), produces least error, you know you're in the second region. At this point the first case is no longer needed. The quarter ellipse can be finished using only the second two cases.
Note this check avoids the floating point operations you've used. The whole point of Bresenham-ish algorithms is to avoid floating point.
The last bit to notice is that you don't want to compute 2ax or 2by each iteration. The multiplications can be avoided by maintaining variables, say dx=2ax and dy=2by, and updating them. A step from x to x+1 increments dx by 2a, a constant. Similarly a step from y to y+1 increments dy by 2b.
Putting all this together, you get the (rough) code below.
Note that you can check the incremental error computation by verifying it against the original error term. If (x0,0) is the initial point, then you know x0^2 = r^2. So the actual error in every iteration is a * x^2 + b * y^2 - x0^2. This ought to equal e in the code below, and it does.
import static java.lang.Math.abs;
import java.util.Arrays;
import java.util.function.BiConsumer;
public class EllipseTracer {
static char [] [] raster = new char[51][101];
static void trace(int x, int y, int a, int b, BiConsumer<Integer, Integer> emitter) {
emitter.accept(x, y);
int e = 0;
int dx = 2 * a * x;
int dy = 2 * b * y;
// First region: stepping north and northeast.
while (x < 0) {
int dxa = dx + a;
int dyb = dy + b;
int eUp = e + dyb;
int eRt = e + dxa;
int eDg = e + dxa + dyb;
if (abs(eUp) < abs(eDg)) {
emitter.accept(x, ++y);
e = eUp;
dy += 2 * b;
} else {
if (abs(eRt) < abs(eDg)) {
// Step east is least error. Found second region.
emitter.accept(++x, y);
e = eRt;
dx += 2 * a;
break;
}
emitter.accept(++x, ++y);
e = eDg;
dy += 2 * b;
dx += 2 * a;
}
}
// Second region: step northeast and east.
while (x < 0) {
int dxa = dx + a;
int dyb = dy + b;
int eRt = e + dxa;
int eDg = e + dxa + dyb;
if (abs(eRt) < abs(eDg)) {
emitter.accept(++x, y);
e = eRt;
dx += 2 * a;
} else {
emitter.accept(++x, ++y);
e = eDg;
dy += 2 * b;
dx += 2 * a;
}
}
}
static void emit(int x, int y) {
raster[y][x + 100] = '*';
}
public static void main(String [] args) {
for (int i = 0; i < raster.length; ++i) {
Arrays.fill(raster[i], ' ');
}
trace(-100, 0, 1, 4, EllipseTracer::emit);
for (int i = 0; i < raster.length; ++i) {
System.out.println(raster[i]);
}
}
}
You can add more tricks to avoid the absolute values, but I'll let you look for those.

Pixel by pixel Bézier Curve

The quadratic/cubic bézier curve code I find via google mostly works by subdividing the line into a series of points and connects them with straight lines. The rasterization happens in the line algorithm, not in the bézier one. Algorithms like Bresenham's work pixel-by-pixel to rasterize a line, and can be optimized (see Po-Han Lin's solution).
What is a quadratic bézier curve algorithm that works pixel-by-pixel like line algorithms instead of by plotting a series of points?
A variation of Bresenham's Algorithm works with quadratic functions like circles, ellipses, and parabolas, so it should work with quadratic Bezier curves too.
I was going to attempt an implementation, but then I found one on the web: http://members.chello.at/~easyfilter/bresenham.html.
If you want more detail or additional examples, the page mentioned above has a link to a 100 page PDF elaborating on the method: http://members.chello.at/~easyfilter/Bresenham.pdf.
Here's the code from Alois Zingl's site for plotting any quadratic Bezier curve. The first routine subdivides the curve at horizontal and vertical gradient changes:
void plotQuadBezier(int x0, int y0, int x1, int y1, int x2, int y2)
{ /* plot any quadratic Bezier curve */
int x = x0-x1, y = y0-y1;
double t = x0-2*x1+x2, r;
if ((long)x*(x2-x1) > 0) { /* horizontal cut at P4? */
if ((long)y*(y2-y1) > 0) /* vertical cut at P6 too? */
if (fabs((y0-2*y1+y2)/t*x) > abs(y)) { /* which first? */
x0 = x2; x2 = x+x1; y0 = y2; y2 = y+y1; /* swap points */
} /* now horizontal cut at P4 comes first */
t = (x0-x1)/t;
r = (1-t)*((1-t)*y0+2.0*t*y1)+t*t*y2; /* By(t=P4) */
t = (x0*x2-x1*x1)*t/(x0-x1); /* gradient dP4/dx=0 */
x = floor(t+0.5); y = floor(r+0.5);
r = (y1-y0)*(t-x0)/(x1-x0)+y0; /* intersect P3 | P0 P1 */
plotQuadBezierSeg(x0,y0, x,floor(r+0.5), x,y);
r = (y1-y2)*(t-x2)/(x1-x2)+y2; /* intersect P4 | P1 P2 */
x0 = x1 = x; y0 = y; y1 = floor(r+0.5); /* P0 = P4, P1 = P8 */
}
if ((long)(y0-y1)*(y2-y1) > 0) { /* vertical cut at P6? */
t = y0-2*y1+y2; t = (y0-y1)/t;
r = (1-t)*((1-t)*x0+2.0*t*x1)+t*t*x2; /* Bx(t=P6) */
t = (y0*y2-y1*y1)*t/(y0-y1); /* gradient dP6/dy=0 */
x = floor(r+0.5); y = floor(t+0.5);
r = (x1-x0)*(t-y0)/(y1-y0)+x0; /* intersect P6 | P0 P1 */
plotQuadBezierSeg(x0,y0, floor(r+0.5),y, x,y);
r = (x1-x2)*(t-y2)/(y1-y2)+x2; /* intersect P7 | P1 P2 */
x0 = x; x1 = floor(r+0.5); y0 = y1 = y; /* P0 = P6, P1 = P7 */
}
plotQuadBezierSeg(x0,y0, x1,y1, x2,y2); /* remaining part */
}
The second routine actually plots a Bezier curve segment (one without gradient changes):
void plotQuadBezierSeg(int x0, int y0, int x1, int y1, int x2, int y2)
{ /* plot a limited quadratic Bezier segment */
int sx = x2-x1, sy = y2-y1;
long xx = x0-x1, yy = y0-y1, xy; /* relative values for checks */
double dx, dy, err, cur = xx*sy-yy*sx; /* curvature */
assert(xx*sx <= 0 && yy*sy <= 0); /* sign of gradient must not change */
if (sx*(long)sx+sy*(long)sy > xx*xx+yy*yy) { /* begin with longer part */
x2 = x0; x0 = sx+x1; y2 = y0; y0 = sy+y1; cur = -cur; /* swap P0 P2 */
}
if (cur != 0) { /* no straight line */
xx += sx; xx *= sx = x0 < x2 ? 1 : -1; /* x step direction */
yy += sy; yy *= sy = y0 < y2 ? 1 : -1; /* y step direction */
xy = 2*xx*yy; xx *= xx; yy *= yy; /* differences 2nd degree */
if (cur*sx*sy < 0) { /* negated curvature? */
xx = -xx; yy = -yy; xy = -xy; cur = -cur;
}
dx = 4.0*sy*cur*(x1-x0)+xx-xy; /* differences 1st degree */
dy = 4.0*sx*cur*(y0-y1)+yy-xy;
xx += xx; yy += yy; err = dx+dy+xy; /* error 1st step */
do {
setPixel(x0,y0); /* plot curve */
if (x0 == x2 && y0 == y2) return; /* last pixel -> curve finished */
y1 = 2*err < dx; /* save value for test of y step */
if (2*err > dy) { x0 += sx; dx -= xy; err += dy += yy; } /* x step */
if ( y1 ) { y0 += sy; dy -= xy; err += dx += xx; } /* y step */
} while (dy < 0 && dx > 0); /* gradient negates -> algorithm fails */
}
plotLine(x0,y0, x2,y2); /* plot remaining part to end */
}
Code for antialiasing is also available on the site.
The corresponding functions from Zingl's site for cubic Bezier curves are
void plotCubicBezier(int x0, int y0, int x1, int y1,
int x2, int y2, int x3, int y3)
{ /* plot any cubic Bezier curve */
int n = 0, i = 0;
long xc = x0+x1-x2-x3, xa = xc-4*(x1-x2);
long xb = x0-x1-x2+x3, xd = xb+4*(x1+x2);
long yc = y0+y1-y2-y3, ya = yc-4*(y1-y2);
long yb = y0-y1-y2+y3, yd = yb+4*(y1+y2);
float fx0 = x0, fx1, fx2, fx3, fy0 = y0, fy1, fy2, fy3;
double t1 = xb*xb-xa*xc, t2, t[5];
/* sub-divide curve at gradient sign changes */
if (xa == 0) { /* horizontal */
if (abs(xc) < 2*abs(xb)) t[n++] = xc/(2.0*xb); /* one change */
} else if (t1 > 0.0) { /* two changes */
t2 = sqrt(t1);
t1 = (xb-t2)/xa; if (fabs(t1) < 1.0) t[n++] = t1;
t1 = (xb+t2)/xa; if (fabs(t1) < 1.0) t[n++] = t1;
}
t1 = yb*yb-ya*yc;
if (ya == 0) { /* vertical */
if (abs(yc) < 2*abs(yb)) t[n++] = yc/(2.0*yb); /* one change */
} else if (t1 > 0.0) { /* two changes */
t2 = sqrt(t1);
t1 = (yb-t2)/ya; if (fabs(t1) < 1.0) t[n++] = t1;
t1 = (yb+t2)/ya; if (fabs(t1) < 1.0) t[n++] = t1;
}
for (i = 1; i < n; i++) /* bubble sort of 4 points */
if ((t1 = t[i-1]) > t[i]) { t[i-1] = t[i]; t[i] = t1; i = 0; }
t1 = -1.0; t[n] = 1.0; /* begin / end point */
for (i = 0; i <= n; i++) { /* plot each segment separately */
t2 = t[i]; /* sub-divide at t[i-1], t[i] */
fx1 = (t1*(t1*xb-2*xc)-t2*(t1*(t1*xa-2*xb)+xc)+xd)/8-fx0;
fy1 = (t1*(t1*yb-2*yc)-t2*(t1*(t1*ya-2*yb)+yc)+yd)/8-fy0;
fx2 = (t2*(t2*xb-2*xc)-t1*(t2*(t2*xa-2*xb)+xc)+xd)/8-fx0;
fy2 = (t2*(t2*yb-2*yc)-t1*(t2*(t2*ya-2*yb)+yc)+yd)/8-fy0;
fx0 -= fx3 = (t2*(t2*(3*xb-t2*xa)-3*xc)+xd)/8;
fy0 -= fy3 = (t2*(t2*(3*yb-t2*ya)-3*yc)+yd)/8;
x3 = floor(fx3+0.5); y3 = floor(fy3+0.5); /* scale bounds to int */
if (fx0 != 0.0) { fx1 *= fx0 = (x0-x3)/fx0; fx2 *= fx0; }
if (fy0 != 0.0) { fy1 *= fy0 = (y0-y3)/fy0; fy2 *= fy0; }
if (x0 != x3 || y0 != y3) /* segment t1 - t2 */
plotCubicBezierSeg(x0,y0, x0+fx1,y0+fy1, x0+fx2,y0+fy2, x3,y3);
x0 = x3; y0 = y3; fx0 = fx3; fy0 = fy3; t1 = t2;
}
}
and
void plotCubicBezierSeg(int x0, int y0, float x1, float y1,
float x2, float y2, int x3, int y3)
{ /* plot limited cubic Bezier segment */
int f, fx, fy, leg = 1;
int sx = x0 < x3 ? 1 : -1, sy = y0 < y3 ? 1 : -1; /* step direction */
float xc = -fabs(x0+x1-x2-x3), xa = xc-4*sx*(x1-x2), xb = sx*(x0-x1-x2+x3);
float yc = -fabs(y0+y1-y2-y3), ya = yc-4*sy*(y1-y2), yb = sy*(y0-y1-y2+y3);
double ab, ac, bc, cb, xx, xy, yy, dx, dy, ex, *pxy, EP = 0.01;
/* check for curve restrains */
/* slope P0-P1 == P2-P3 and (P0-P3 == P1-P2 or no slope change) */
assert((x1-x0)*(x2-x3) < EP && ((x3-x0)*(x1-x2) < EP || xb*xb < xa*xc+EP));
assert((y1-y0)*(y2-y3) < EP && ((y3-y0)*(y1-y2) < EP || yb*yb < ya*yc+EP));
if (xa == 0 && ya == 0) { /* quadratic Bezier */
sx = floor((3*x1-x0+1)/2); sy = floor((3*y1-y0+1)/2); /* new midpoint */
return plotQuadBezierSeg(x0,y0, sx,sy, x3,y3);
}
x1 = (x1-x0)*(x1-x0)+(y1-y0)*(y1-y0)+1; /* line lengths */
x2 = (x2-x3)*(x2-x3)+(y2-y3)*(y2-y3)+1;
do { /* loop over both ends */
ab = xa*yb-xb*ya; ac = xa*yc-xc*ya; bc = xb*yc-xc*yb;
ex = ab*(ab+ac-3*bc)+ac*ac; /* P0 part of self-intersection loop? */
f = ex > 0 ? 1 : sqrt(1+1024/x1); /* calculate resolution */
ab *= f; ac *= f; bc *= f; ex *= f*f; /* increase resolution */
xy = 9*(ab+ac+bc)/8; cb = 8*(xa-ya);/* init differences of 1st degree */
dx = 27*(8*ab*(yb*yb-ya*yc)+ex*(ya+2*yb+yc))/64-ya*ya*(xy-ya);
dy = 27*(8*ab*(xb*xb-xa*xc)-ex*(xa+2*xb+xc))/64-xa*xa*(xy+xa);
/* init differences of 2nd degree */
xx = 3*(3*ab*(3*yb*yb-ya*ya-2*ya*yc)-ya*(3*ac*(ya+yb)+ya*cb))/4;
yy = 3*(3*ab*(3*xb*xb-xa*xa-2*xa*xc)-xa*(3*ac*(xa+xb)+xa*cb))/4;
xy = xa*ya*(6*ab+6*ac-3*bc+cb); ac = ya*ya; cb = xa*xa;
xy = 3*(xy+9*f*(cb*yb*yc-xb*xc*ac)-18*xb*yb*ab)/8;
if (ex < 0) { /* negate values if inside self-intersection loop */
dx = -dx; dy = -dy; xx = -xx; yy = -yy; xy = -xy; ac = -ac; cb = -cb;
} /* init differences of 3rd degree */
ab = 6*ya*ac; ac = -6*xa*ac; bc = 6*ya*cb; cb = -6*xa*cb;
dx += xy; ex = dx+dy; dy += xy; /* error of 1st step */
for (pxy = &xy, fx = fy = f; x0 != x3 && y0 != y3; ) {
setPixel(x0,y0); /* plot curve */
do { /* move sub-steps of one pixel */
if (dx > *pxy || dy < *pxy) goto exit; /* confusing values */
y1 = 2*ex-dy; /* save value for test of y step */
if (2*ex >= dx) { /* x sub-step */
fx--; ex += dx += xx; dy += xy += ac; yy += bc; xx += ab;
}
if (y1 <= 0) { /* y sub-step */
fy--; ex += dy += yy; dx += xy += bc; xx += ac; yy += cb;
}
} while (fx > 0 && fy > 0); /* pixel complete? */
if (2*fx <= f) { x0 += sx; fx += f; } /* x step */
if (2*fy <= f) { y0 += sy; fy += f; } /* y step */
if (pxy == &xy && dx < 0 && dy > 0) pxy = &EP;/* pixel ahead valid */
}
exit: xx = x0; x0 = x3; x3 = xx; sx = -sx; xb = -xb; /* swap legs */
yy = y0; y0 = y3; y3 = yy; sy = -sy; yb = -yb; x1 = x2;
} while (leg--); /* try other end */
plotLine(x0,y0, x3,y3); /* remaining part in case of cusp or crunode */
}
As Mike 'Pomax' Kamermans has noted, the solution for cubic Bezier curves on the site is not complete; in particular, there are issues with antialiasing cubic Bezier curves, and the discussion of rational cubic Bezier curves is incomplete.
You can use De Casteljau's algorithm to subdivide a curve into enough pieces that each subsection is a pixel.
This is the equation for finding the [x,y] point on a Quadratic Curve at interval T:
// Given 3 control points defining the Quadratic curve
// and given T which is an interval between 0.00 and 1.00 along the curve.
// Note:
// At the curve's starting control point T==0.00.
// At the curve's ending control point T==1.00.
var x = Math.pow(1-T,2)*startPt.x + 2 * (1-T) * T * controlPt.x + Math.pow(T,2) * endPt.x;
var y = Math.pow(1-T,2)*startPt.y + 2 * (1-T) * T * controlPt.y + Math.pow(T,2) * endPt.y;
To make practical use of this equation, you can input about 1000 T values between 0.00 and 1.00. This results in a set of 1000 points guaranteed to be along the Quadratic Curve.
Calculating 1000 points along the curve is probably over-sampling (some calculated points will be at the same pixel coordinate) so you will want to de-duplicate the 1000 points until the set represents unique pixel coordinates along the curve.
There is a similar equation for Cubic Bezier curves.
Here's example code that plots a Quadratic Curve as a set of calculated pixels:
var canvas=document.getElementById("canvas");
var ctx=canvas.getContext("2d");
var points=[];
var lastX=-100;
var lastY=-100;
var startPt={x:50,y:200};
var controlPt={x:150,y:25};
var endPt={x:250,y:100};
for(var t=0;t<1000;t++){
var xyAtT=getQuadraticBezierXYatT(startPt,controlPt,endPt,t/1000);
var x=parseInt(xyAtT.x);
var y=parseInt(xyAtT.y);
if(!(x==lastX && y==lastY)){
points.push(xyAtT);
lastX=x;
lastY=y;
}
}
$('#curve').text('Quadratic Curve made up of '+points.length+' individual points');
ctx.fillStyle='red';
for(var i=0;i<points.length;i++){
var x=points[i].x;
var y=points[i].y;
ctx.fillRect(x,y,1,1);
}
function getQuadraticBezierXYatT(startPt,controlPt,endPt,T) {
var x = Math.pow(1-T,2) * startPt.x + 2 * (1-T) * T * controlPt.x + Math.pow(T,2) * endPt.x;
var y = Math.pow(1-T,2) * startPt.y + 2 * (1-T) * T * controlPt.y + Math.pow(T,2) * endPt.y;
return( {x:x,y:y} );
}
body{ background-color: ivory; }
#canvas{border:1px solid red; margin:0 auto; }
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.9.1/jquery.min.js"></script>
<h4 id='curve'>Q</h4>
<canvas id="canvas" width=350 height=300></canvas>
The thing to realise here is that "line segments", when created small enough, are equivalent to pixels. Bezier curves are not linearly traversible curves, so we can't easily "skip ahead to the next pixel" in a single step, like we can for lines or circular arcs.
You could, of course, take the tangent at any point for a t you already have, and then guess which next value t' will lie a pixel further. However, what typically happens is that you guess, and guess wrong because the curve does not behave linearly, then you check to see how "off" your guess was, correct your guess, and then check again. Repeat until you've converged on the next pixel: this is far, far slower than just flattening the curve to a high number of line segments instead, which is a fast operation.
If you pick the number of segments such that they're appropriate to the curve's length, given the display it's rendered to, no one will be able to tell you flattened the curve.
There are ways to reparameterize Bezier curves, but they're expensive, and different canonical curves require different reparameterization, so that's really not faster either. What tends to be the most useful for discrete displays is to build a LUT (lookup table) for your curve, with a length that works for the size the curve is on the display, and then using that LUT as your base data for drawing, intersection detection, etc. etc.
First of all, I'd like to say that the fastest and the most reliable way to render bezier curves is to approximate them by polyline via adaptive subdivision, then render the polyline. Approach by #markE with drawing many points sampled on the curve is rather fast, but it can skip pixels. Here I describe another approach, which is closest to line rasterization (though it is slow and hard to implement robustly).
I'll treat usually curve parameter as time. Here is the pseudocode:
Put your cursor at the first control point, find the surrounding pixel.
For each side of the pixel (four total), check when your bezier curves intersects its line by solving quadratic equations.
Among all the calculated side intersection times, choose the one which will happen strictly in future, but as early as possible.
Move to neighboring pixel depending on which side was best.
Set current time to time of that best side intersection.
Repeat from step 2.
This algorithm works until time parameter exceeds one. Also note that it has severe issues with curves exactly touching a side of a pixel. I suppose it is solvable with a special check.
Here is the main code:
double WhenEquals(double p0, double p1, double p2, double val, double minp) {
//p0 * (1-t)^2 + p1 * 2t(1 - t) + p2 * t^2 = val
double qa = p0 + p2 - 2 * p1;
double qb = p1 - p0;
double qc = p0 - val;
assert(fabs(qa) > EPS); //singular case must be handled separately
double qd = qb * qb - qa * qc;
if (qd < -EPS)
return INF;
qd = sqrt(max(qd, 0.0));
double t1 = (-qb - qd) / qa;
double t2 = (-qb + qd) / qa;
if (t2 < t1) swap(t1, t2);
if (t1 > minp + EPS)
return t1;
else if (t2 > minp + EPS)
return t2;
return INF;
}
void DrawCurve(const Bezier &curve) {
int cell[2];
for (int c = 0; c < 2; c++)
cell[c] = int(floor(curve.pts[0].a[c]));
DrawPixel(cell[0], cell[1]);
double param = 0.0;
while (1) {
int bc = -1, bs = -1;
double bestTime = 1.0;
for (int c = 0; c < 2; c++)
for (int s = 0; s < 2; s++) {
double crit = WhenEquals(
curve.pts[0].a[c],
curve.pts[1].a[c],
curve.pts[2].a[c],
cell[c] + s, param
);
if (crit < bestTime) {
bestTime = crit;
bc = c, bs = s;
}
}
if (bc < 0)
break;
param = bestTime;
cell[bc] += (2*bs - 1);
DrawPixel(cell[0], cell[1]);
}
}
Full code is available here.
It uses loadbmp.h, here it is.

How to find average of two numbers that wrap around?

I have an int that represents numbers in the range [0, 8[ that wraps around:
2
1 3
0 4
7 5
6
Now I need to find the average of two numbers like this, so that for example the average of 7 and 0 would be 7.5, the average of 7 and 2 would be 0.5, the average of 0 and 4 would be 2 or 6, etc.
I found this ("How do you calculate the average of a set of angles?") related question, but it's about angles and I don't see how it could help here. There's also "How to subtract two unsigned ints with wrap around or overflow" but it's about subtracting, and not about finding an average. Any pointers?
I also have a wrap function, if that can be utilized here somehow:
template <class type>
inline type Wrap(type Value, type Minimum, type Maximum)
{
Value = ((Value - Minimum) % (Maximum + 1 - Minimum));
return (Value >= 0 ? Minimum : Maximum + 1) + Value;
}
Edit: Trying to define the rules more formally:
If abs(a - b) <= 4 then avg = (a + b) / 2..
Otherwise, avg = (a + b) / 2. + 4; if (avg >= 8) avg -= 8;.
Another solution is to use the answer you cited by converting your numbers to angles first:
Convert your numbers to angles.
angle_a = a * pi / 4
angle_b = b * pi / 4
Compute unit vectors for each angle
unit_a
unit_b
Compute unit vectors average
unit_average = (unit_a + unit_b) / 2
Compute angle of unit_average
angle_average
Convert angle_average to number
number_average = angle_average * 4 / pi
then number_average is our answer
I think the first return expression is what you're after:
def av(a,b):
mi = min(a,b)
ma = max(a,b)
if ma - mi > 4:
return (((mi + 8) + ma) / 2.) % 8
else:
return (mi+ma)/2.
mi is the minimum of the two; ma is the max.
float wAvg(int m, int n)
{
int minimum = min(m, n);
int maximum = max(m, n);
int d1 = minimum + 8 - maximum; // difference between m and n
// when wrapped around
int d2 = max - min; // normal difference
float avg = 0.0f;
if (d1 < d2) // if wrapped around distance is shorter than normal distance
{
avg = d1 / 2.0f + maximum;
if (avg >= 8.0f)
avg -= 8.0f;
}
else
{
avg = (m + n) / 2.0f;
}
return avg;
}
I think this might work
Crude but effective:
float foo(int a, int b)
{
int c;
if(a>b)
{
c=a;
a=b;
b=c;
}
if( b-a > 3)
{
c=a+8;
a=b;
b=c;
}
float f = 0.5*(a+b);
if(f>7.6)
f-=8.0;
return(f);
}
After seeing #Beta's "crude" answer, just for fun :) :
float wAvg(int m, int n)
{
static float results[8][8] =
{
{0.0f, 0.5f, 1.0f, 1.5f, 2.0f, 6.5f, 7.0f, 7.5f},
{0.5f, 1.0f, 1.5f, 2.0f, 2.5f, 3.0f, 7.5f, 0.0f},
{1.0f, 1.5f, 2.0f, 2.5f, 3.0f, 3.5f, 4.0f, 0.5f},
{1.5f, 2.0f, 2.5f, 3.0f, 3.5f, 4.0f, 4.5f, 5.0f},
{2.0f, 2.5f, 3.0f, 3.5f, 4.0f, 4.5f, 5.0f, 5.5f},
{6.5f, 3.0f, 3.5f, 4.0f, 4.5f, 5.0f, 5.5f, 6.0f},
{7.0f, 7.5f, 4.0f, 4.5f, 5.0f, 5.5f, 6.0f, 6.5f},
{7.5f, 0.0f, 0.5f, 5.0f, 5.5f, 6.0f, 6.5f, 7.0f}
};
return results[m % 8][n % 8];
}
Presumably the following would work (in the same way it does for angles):
function meanWrappingValue(values: Array<number>, range: number): number {
return meanAngle(values.map(value => value * (Math.PI * 2) / range)) / (Math.PI * 2) * range;
}
function meanAngle(angles: Array<number>): number {
let sinSum = angles.reduce((sum, cur) => sum + Math.sin(cur), 0);
let cosSum = angles.reduce((sum, cur) => sum + Math.cos(cur), 0);
return normalizeAngle(Math.atan2(sinSum / angles.length, cosSum / angles.length));
}
function normalizeAngle(angle: number): number {
let range = Math.PI * 2;
return ((angle % range) + range) % range;
}
In your case it would be:
let result = meanWrappingValue([7, 2], 8);
console.log(result); // => 0.5

Polygon splitted by 4 parts

I have an arbitrary convex polygon. And it is splitted by 2 perpendicular lines (vectors of them are (0,1) and (1,0)). Is there any algorithm that can calculate area by smaller figures (S1, S2, S3, S4). All I can do is to calculate points where lines cross the polygon and then calculate areas, but is there something better optimized?
I store all vertexes in array double **v;
And then I calculate all points, where my polygon crosses X and Y axises:
void cross() { //calculates buf (crossing with Y)
act = 0;
for (int i = 0; i < n; ++i) {
buf[act][0]=v[i][0];
buf[act][1]=v[i][1];
act++;
if (v[i][0]*v[(i+1)%n][0] < 0) {
buf[act][0] = 0;
buf[act][1] = v[i][1] + std::abs(v[i][0])*(v[(i+1)%n][1]-v[i][1])/(std::abs(v[i][0])+std::abs(v[(i+1)%n][0]));
act++;
}
}
}
void vert() { /calculates buf2 (crossing with X)
act2 =0;
for (int i = 0; i < act; ++i) {
buf2[act2][0]=buf[i][0];
buf2[act2][1]=buf[i][1];
act2++;
if (buf[i][1]*buf[(i+1)%act][1] < 0) {
buf2[act2][1] = 0;
buf2[act2][0] = buf[i][0] + std::abs(buf[i][1])*(buf[(i+1)%act][0] - buf[i][0])/ (std::abs(buf[i][1])+std::abs(buf[(i+1)%act][1]));
act2++;
}
}
}
After calling cross(); vert(); I get an array buf2 and number of elements there is act2;
After this I'am triangilating polygon and detect in what squad does traingle lay.
double s_trian (double a, double b, double c, double d) {
//area of triangle
double s =0;
s=0.5*std::abs((a)*(d)-(c)*(b));
return s;
}
void triang() { //calculate areas of s1,s2,s3,s4 by
//triangulating
bool rotation;
double temror;
s1=0, s2 =0, s3 =0, s4 =0;
int a,b;
for (int i =0; i < act2; ++i) {
a=i%act2;
b=(i+1)%act2;
temror = s_trian(buf2[a][0], buf2[a][1], buf2[b][0], buf2[b][1]);
if ((buf2[a][0]+buf2[b][0]) > 0) {
if((buf2[a][1]+buf2[b][1] > 0))
s1+=temror;
else
s4+=temror;
} else {
if ((buf2[a][1]+buf2[b][1] > 0))
s2+=temror;
else
s3+=temror;
}
}
}
Can I optimize something here?
Given that your polygon is convex, just select an arbitrary point P inside the polygon and split it up in triangles with one corner in P.
Then calculate the area of each triangle: http://www.mathopenref.com/heronsformula.html and sum them up.
You can do slightly better.
Ignore X to begin with.
Project horizontally every vertex on Y. This way, you define trapezoids. The sum of the algebraic areas of these trapezoids gives the total surface. Add the positive and negative areas in separate accumulators, this will give you the areas on both sides of Y. But some trapezoids will cross Y and be skewed: compute the areas of the two triangles and accumulate where appropriate.
Now to deal with the horizontal axis, similarly you will add the contributions to a positive/negative accumulator, or to both.
In total there will be four accumulators, for all sign combinations, giving you the four requested areas.
This procedure will cost you a little more than one accumulation per side, instead of four. It can be done in a single loop, avoiding the need to compute and store the four subpolygons.
[Following up on my comment yesterday; has much in common with Dan Bystrom's answer.]
Loop over all sides, and compute the area of the triangle made of the side and the origin. Add to the appropriate quad area. Where a side crosses the axis, compute the intercept and split the triangle. Compute both triangle areas parts and add each to the appropriate quad.
Using the origin as a point for a triangle vertex makes the cross product based formula for a triangle area very fast and simple. You don't even need the call to fabs() if you take care to pass the parameters in the right order.
This code has not handled the problem where a vertex lies on an axis or cases where no point lies in a given quadrant.
struct Point
{
double x;
double y;
};
double areaOfTriangle(double ax, double ay, double bx, double by)
{
return fabs(by*ax - bx *ay)/2;
}
unsigned getQuad(double x, double y)
{
int xPos = (x > 0) ? 0 : 1;
int yPos = (y > 0) ? 0 : 1 ;
int quad = xPos + yPos;
if (!xPos && yPos)
quad = 3;
return quad;
}
Point getIntercept(const Point& a, const Point& b)
{
Point intercept;
if ( (a.x * b.x) < 0)
{
// Crosses y axis.
intercept.x = 0;
intercept.y = a.y - (b.y - a.y) / (b.x - a.x)*a.x;
}
else
{
// Crosses x axis.
intercept.y = 0;
intercept.x = a.x - (b.x - a.x) / (b.y - a.y)*a.y;
}
return intercept;
}
void getAreaOfQuads(double* retQuadArea, const Point* points, unsigned numPts)
{
for (unsigned i = 0; i != 4; ++i)
retQuadArea[i] = 0;
const Point* a = &points[numPts - 1];
unsigned quadA = getQuad(a->x, a->y);
for (unsigned i = 0; i != numPts; ++i)
{
const Point* b = &points[i];
unsigned quadB = getQuad(b->x, b->y);
if (quadA == quadB)
{
retQuadArea[quadA] += areaOfTriangle(a->x, a->y, b->x, b->y);
}
else
{
// The side a->b crosses an axis.
// First, find out where.
Point c = getIntercept(*a, *b);
retQuadArea[quadA] += areaOfTriangle(a->x, a->y, c.x, c.y);
retQuadArea[quadB] += areaOfTriangle(c.x, c.y, b->x, b->y);
}
a = b;
quadA = quadB;
}
}
void test(Point* polygon, unsigned n)
{
double areas[4] = {};
getAreaOfQuads(areas, polygon, n);
for (unsigned i = 0; i != 4; ++i)
std::cout << areas[i] << ", ";
std::cout << std::endl;
}
Point polygon[]
{
{0.6, 0.2},
{ 0.2, 0.8 },
{ -0.2, 0.7 },
{ -0.6, 0.6 },
{ -1.0, 0.1 },
{ -0.6, -0.5 },
{ 0.1, -0.5 },
{ 0.9, -0.1 }
};
Point square[]
{
{1, 1},
{ -1, 1 },
{ -1, -1 },
{ 1, -1 }
};
int main()
{
test(square, 4);
test(polygon, 8);
return 0;
}

Optimizing / simplifying a path

Say I have a path with 150 nodes / verticies. How could I simplify if so that for example a straight line with 3 verticies, would remove the middle one since it does nothing to add to the path. Also how could I avoid destroying sharp corners? And how could I remove tiny variations and have smooth curves remaining.
Thanks
For every 3 vertices, pick the middle one and calculate its distance to the line segment between the other two. If the distance is less than the tolerance you're willing to accept, remove it.
If the middle vertex is very close to one of the endpoints, you should tighten the tolerance to avoid removing rounded corners for instance.
The simpler approach. Take 3 verticies a, b and c and calculate the angle/inclination between verticies.
std::vector<VERTEX> path;
//fill path
std::vector<int> removeList;
//Assure that the value is in the same unit as the return of angleOf function.
double maxTinyVariation = SOMETHING;
for (int i = 0; i < quantity-2; ++i) {
double a = path[i], b = path[i + 1] , c = path[i + 2]
double abAngle = angleOf(a, b);
double bcAngle = angleOf(b, c);
if (abs(ab - bc) <= maxTinyVariation) {
//a, b and c are colinear
//remove b later
removeList.push_back(i+1);
}
}
//Remove vertecies from path using removeList.
How could I simplify if so that for example a straight line with 3 verticies, would remove the middle one since it does nothing to add to the path.
For each set of three consecutive vertices, test whether they are all in a straight line. If they are, remove the middle vertex.
Also how could I avoid destroying sharp corners?
If you're only removing vertices that fall on a straight line between two others, then you won't have a problem with this.
Use Douglas-Peucker method to simplify a Path.
epsilon parameter defines level of "simplicity":
private List<Point> douglasPeucker (List<Point> points, float epsilon){
int count = points.size();
if(count < 3) {
return points;
}
//Find the point with the maximum distance
float dmax = 0;
int index = 0;
for(int i = 1; i < count - 1; i++) {
Point point = points.get(i);
Point lineA = points.get(0);
Point lineB = points.get(count-1);
float d = perpendicularDistance(point, lineA, lineB);
if(d > dmax) {
index = i;
dmax = d;
}
}
//If max distance is greater than epsilon, recursively simplify
List<Point> resultList;
if(dmax > epsilon) {
List<Point> recResults1 = douglasPeucker(points.subList(0,index+1), epsilon);
List<Point> recResults2 = douglasPeucker(points.subList(index, count), epsilon);
List<Point> tmpList = new ArrayList<Point>();
tmpList.addAll(recResults1);
tmpList.remove(tmpList.size()-1);
tmpList.addAll(recResults2);
resultList = tmpList;
} else {
resultList = new ArrayList<Point>();
resultList.add(points.get(0));
resultList.add(points.get(count-1));
}
return resultList;
}
private float perpendicularDistance(Point point, Point lineA, Point lineB){
Point v1 = new Point(lineB.x - lineA.x, lineB.y - lineA.y);
Point v2 = new Point(point.x - lineA.x, point.y - lineA.y);
float lenV1 = (float)Math.sqrt(v1.x * v1.x + v1.y * v1.y);
float lenV2 = (float)Math.sqrt(v2.x * v2.x + v2.y * v2.y);
float angle = (float)Math.acos((v1.x * v2.x + v1.y * v2.y) / (lenV1 * lenV2));
return (float)(Math.sin(angle) * lenV2);
}
Let A, B, C be some points.
The easiest way to check they lie on the same line is to count crossproduct of vectors
B-A, C-A.
If it equals zero, they lie on the same line:
// X_ab, Y_ab - coordinates of vector B-A.
float X_ab = B.x - A.x
float Y_ab = B.y - A.y
// X_ac, Y_ac - coordinates of vector C-A.
float X_ac = C.x - A.x
float Y_ac = C.y - A.y
float crossproduct = Y_ab * X_ac - X_ab * Y_ac
if (crossproduct < EPS) // if crossprudct == 0
{
// on the same line.
} else {
// not on the same line.
}
After you know that A, B, C lie on the same line it is easy to know whether B lies between A and C throw innerproduct of vectors B-A and C-A. If B lies between A and C, then (B-A) has the same direction as (C-A), and innerproduct > 0, otherwise < 0:
float innerproduct = X_ab * X_ac + Y_ab * Y_ac;
if (innerproduct > 0) {
// B is between A and C.
} else {
// B is not between A and C.
}

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