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I have this problem I can't figure out and need help.
The problem is about calculating how many balloons are hit by a pellet gun. Balloons positions are described by 3D coordinates (X,Y,Z) and radius R. The gunshot is defined by 3D location of the end of the barrel "p" (Px,Py,Pz) and vector "v" (Vx, Vy, Vz) describing the direction barrel is pointing to.
I've tried to implement the solution suggested here: https://math.stackexchange.com/questions/1939423/calculate-if-vector-intersects-sphere
// C = center of sphere
// r = radius of sphere
// P = point on line
// U = unit vector in direction of line
Q = P - C;
a = U*U; // should be = 1
b = 2*U*Q
c = Q*Q - r*r;
d = b*b - 4*a*c; // discriminant of quadratic
if d < 0 then solutions are complex, so no intersections
if d >= 0 then solutions are real, so there are intersections
But the problem with this is that I get intersection with balloons that are positioned behind the gun. How can I modify this algorithm in order to produce the correct result? Or is my approach maybe wrong?
You need to actually solve the quadratic equation defined by your variables a, b and c.
Often, there are math libraries to do this, something like:
(t1,t2) = QuadraticSolve(a, b, c);
You can also do it manually for each parameter:
t1 = (-b + sqrt(b*b - 4*a*c)) / (2*a)
t2 = (-b - sqrt(b*b - 4*a*c)) / (2*a)
If t1 or t2 is positive then that intersection is in front of your gun.
im trying to find the center of a circle. the only information I have is:
Two random points in the circle and the circle bulge. So far i've manage to calculate the radius of the circle (at least i think i did). Ill post bellow the equasions ive used so far.
these are just random values and will change on user input)
PointA(x = 10, y = 15)
PointB(x = 6, y = 12)
circle_bulge = 0.41
distance = PointB - PointA
radius = (distance / 4) * (circle_bulge + (1 / circle_bulge ))
if this math is incorrect, please let me know, but keep in mind that i need to find the X and Y coordinates of the center of the circle
Here is a picture of the problem:
By definition the bulge is b = tg(Alpha/4)
From the trigonometric formula: tg(2 angle) = 2tg(angle)/(1-tg2(angle))
applied to angle = Alpha/4 and using the definition of bulge:
tg(Alpha/2) = 2 b/(1-b2)
On the other hand
tg(Alpha/2) = s/d
Then
s/d = 2 b/(1-b2) and
d = s(1-b2)/(2 b)
which allows us to calculate d because b is known and s = ||B - A||/2, where ||B - A|| denotes the norm of the vector B - A.
Now, let's calculate
(u,v) = (B - A)/||B - A||
Then ||(u,v)|| = 1, (v,-u) is orthogonal to B - A, and we have
C = (v,-u)d + (A+B)/2
UPDATE
Pseudo code to compute the center
Inputs:
A = (a1, a2), B = (b1, b2) "two points"; b "bulge"
Calculations:
"lengths"
norm := sqrt(square(b1-a1) + square(b2-a2)).
s := norm/2.
d := s * (1-square(b))/(2*b)
"direction"
u := (b1-a1)/ norm.
v := (b2-a2)/ norm.
"center"
c1 := -v*d + (a1+b1)/2.
c2 := u*d + (a2+b2)/2.
Return C := (c1, c2)
Note: There are two solutions for the Center, the other one being
c1 := v*d + (a1+b1)/2.
c2 := -u*d + (a2+b2)/2.
Return C := (c1, c2)
I believe that you have all the required math in this reference: http://autocad.wikia.com/wiki/Arc_relationships
The center of the circunference has to be in the straight line that passes trough the middle point of the segment with perpendicular vector AB. You know the angle of the triangle formed by the three points because you know the bulge so you have to solve a simple equation. Try it out, if you can not I will try to help you.
Ignacio is right pointing out that there will be two solutions.
EDIT
The middle point is given by:
M = (A + B) / 2
The AB vector is gien by:
AB = A-B
The center of the circle C with coordinates (X, Y) has to be in the line given by:
((X, Y) - M) * AB = 0 //where * is the scalar vector product
The isosceles triangle generated by the points A, B and C has an angle opposite of the AB segment:
Angle = 4 arctan(bulge)
now we can compute the distance from the center C to A that we call d1 and half the distance between A and B that we call d2 we know then that
sin (Angle/2) = d2/d1
This will give you the second equation for X and Y that is quadratic (it has two solutions).
Excuse the notation but I do not know how to insert math here :-)
Heading
I need to find the indices of the polygon nearest to a point
So in this case the ouput would be 4 and 0. Such that if the red point is added I know to where to place the vertex in the array. Does anyone know where to start?
(Sorry if the title is misleading, I wasnt sure how to phrase it properly)
In this case the ouput would be 0 and 1, rather than the closest 4.
Point P lies on the segment AB, if two simple conditions are met together:
AP x PB = 0 //cross product, vectors are collinear or anticollinear, P lies on AB line
AP . PB > 0 //scalar product, exclude anticollinear case to ensure that P is inside the segment
So you can check all sequential vertice pairs (pseudocode):
if (P.X-V[i].X)*(V[i+1].Y-P.Y)-(P.Y-V[i].Y)*(V[i+1].X-P.X)=0 then
//with some tolerance if point coordinates are float
if (P.X-V[i].X)*(V[i+1].X-P.X)+(P.Y-V[i].Y)*(V[i+1].Y-P.Y)>0
then P belongs to (i,i+1) segment
This is fast direct (brute-force) method.
Special data structures exist in computer geometry to quickly select candidate segments - for example, r-tree. But these complicated methods will gain for long (many-point) polylines and for case where the same polygon is used many times (so pre-treatment is negligible)
I'll assume that the new point is to be added to an edge. So you are given the coordinates of a point a = (x, y) and you want to find the indices of the edge on which it lies. Let's call the vertices of that edge b, c. Observe that the area of the triangle abc is zero.
So iterate over all edges and choose the one that minimizes area of triangle abc where a is your point and bc is current edge.
a = input point
min_area = +infinity
closest_edge = none
n = number of vertices in polygon
for(int i = 1; i <= n; i++)
{ b = poly[ i - 1 ];
c = poly[ i % n ];
if(area(a, b, c) < min_area)
{ min_area = area(a, b, c);
closest_edge = bc
}
}
You can calculate area using:
/* Computes area x 2 */
int area(a, b, c)
{ int ans = 0;
ans = (a.x*b.y + b.x*x.y + c.x*a.y) - (a.y*b.x + b.y*c.x + c.y*a.x);
return ABS(ans);
}
I think you would be better off trying to compare the distance from the actual point to a comparable point on the line. The closest comparable point would be the one that forms a perpendicular line like this. a is your point in question and b is the comparable point on the line line between the two vertices that you will check distance to.
However there's another method which I think might be more optimal for this case (as it seems most of your test points lie pretty close to the desired line already). Instead of find the perpendicular line point we can simply check the point on the line that has the same X value like this. b in this case is a lot easier to calculate:
X = a.X - 0.X;
Slope = (1.Y - 0.Y) / (1.X - 0.X);
b.X = 0.X + X;
b.Y = 0.Y + (X * Slope);
And the distance is simply the difference in Y values between a and b:
distance = abs(a.Y - b.Y);
One thing to keep in mind is that this method will become more inaccurate as the slope increases as well as become infinite when the slope is undefined. I would suggest flipping it when the slope > 1 and checking for a b that lies at the same y rather than x. That would look like this:
Y = a.Y - 0.Y;
Inverse_Slope = (1.X - 0.X) / (1.Y - 0.Y);
b.Y = 0.Y + Y;
b.X = 0.Y + (Y * Inverse_Slope);
distance = abs(a.X - b.X);
Note: You should also check whether b.X is between 0.X and 1.X and b.Y is between 0.Y and 1.Y in the second case. That way we are not checking against points that dont lie on the line segment.
I admit I don't know the perfect terminology when it comes to this kind of thing so it might be a little confusing, but hope this helps!
Rather than checking if the point is close to an edge with a prescribed tolerance, as MBo suggested, you can fin the edge with the shortest distance to the point. The distance must be computed with respect to the line segment, not the whole line.
How do you compute this distance ? Let P be the point and Q, R two edge endpoints.
Let t be in range [0,1], you need to minimize
D²(P, QR) = D²(P, Q + t QR) = (PQ + t QR)² = PQ² + 2 t PQ.QR + t² QR².
The minimum is achieved when the derivative cancels, i.e. t = - PQ.QR / QR². If this quantity exceeds the range [0,1], just clamp it to 0 or 1.
To summarize,
if t <= 0, D² = PQ²
if t >= 1, D² = PR²
otherwise, D² = PQ² - t² QR²
Loop through all the vertices, calculate the distance of that vertex to the point, find the minimum.
double min_dist = Double.MAX_VALUE;
int min_index=-1;
for(int i=0;i<num_vertices;++i) {
double d = dist(vertices[i],point);
if(d<min_dist) {
min_dist = d;
min_index = i;
}
}
I'm working on a project in Matlab and need to find the area between two lines inside of the square [-1,+1]x[-1,+1] intersecting in a point (xIntersection,yIntersection). So the idea is to subtract the two lines and integrate between [-1, xIntersection] and [xIntersection, +1], sum the results and if it's negative, change its sign.
For details on how I find the intersection of the two lines check this link.
I'm using Matlab's function integral(), here a snippet of my code:
xIntersection = ((x_1 * y_2 - y_1 * x_2) * (x_3 - x_4) - (x_1 - x_2) * (x_3 * y_4 - y_3 * x_4) ) / ((x_1 - x_2) * (y_3 - y_4) - (y_1 - y_2) * (x_3 - x_4));
d = #(x) g(x) - f(x);
result = integral(d, -1, xIntersection) - int( d, xIntersection, 1)
if(result < 0),
result = result * -1;
end
Note that I defined previously in the code g(x) and f(x) but haven't reported it in the snippet.
The problem is that I soon realized that the lines could intersect either inside or outside of the square, furthermore they could intersect the square on any of its sides and the number of possible combinations grows up very quickly.
I.e.:
These are just 4 cases, but considering that f(+1), f(-1), g(+1), g(-1) could be inside the interval [-1,+1], above it or under it and that the intersection could be inside or outside of the square the total number is 3*3*3*3*2 = 162.
Obviously in each case the explicit function to integrate in order to get the area between the two lines is different, but I can't possibly think of writing a switch case for each one.
Any ideas?
I think my answer to your previous question still applies, for the most part.
If you want to compute the area of the region bounded by the smaller angle of the two lines and the boundaries of the square, then you can forget about the intersection, and forget about all the different cases.
You can just use the fact that
the area of the square S is equal to 4
the value of this integral
A = quadgk(#(x) ...
abs( max(min(line1(x),+1),-1) - max(min(line2(x),+1),-1) ), -1, +1);
gives you the area between the lines (sometimes the large angle, sometimes the small angle)
the value of of min(A, S-A) is the correct answer (always the small angle).
Assuming “between the lines” means “inside the smaller angle formed by the lines”:
With the lines l and h, S := [-1,+1]x[-1,+1] and B as the border of S.
Transform l to the form l_1 + t*l_2 with l_1 and l_2 beeing vectors. Do the same for h.
If the intersection is not inside S, find the 4 intersections of l and h with B. Sort them so you get a convex quadrilateral. Calculate its area.
Else:
Find the intersection point p and find the intersection angle α between l_2 and h_2. and then check:
If α in [90°,180°] or α in [270°,360°], swap l and h.
If α > 180°, set l_2 = −l_2
Set l_1 := h_1 := p. Do once for positive t and negative t
(forwards and backwards along l_2 and h_2 from p):
Find intersections s_l and s_h of l and h with B.
If on same border of B: compute area of triangle s_l, s_h, p
If on adjacent borders of B: find the corner c of B in between the hit borders and once again sort the four points s_l, s_h, p and c so you get an convex quadrilateral and calculate it’s area.
If on opposite borders, find the matching side of B (you can do this by looking at the direction of s_l-p). Using its two corner points c_1 and c_2, you now have 5 points that form a polygon. Sort them so the polygon is convex and calculate its area.
This is still quite a few cases, but I don’t think there’s a way around that. You can simplify this somewhat by also using the polygon formula for the triangle and the quadrilateral.
How to sort the points so you get a convex polygon/quadrilateral: select any one of them as p_1 and then sort the rest of the points according to angle to p_1.
If you define an intersection function and a polygon_area that takes a list of points, sorts them and returns the area, this algorithm should be rather simple to implement.
edit: Image to help explain the comment:
Hey guys thanks for your answers, I also thought of an empirical method to find the area between the lines and wanted to share it for the sake of discussion and completeness.
If you take a large number of random points within the square [-1,+1]x[-1,+1] you can measure the area as the fraction of the points which fall in the area between the two lines.
Here's a little snippet and two images to show the different accuracy of empirical result obtained with different number of points.
minX = -1;
maxX = +1;
errors = 0;
size = 10000;
for j=1:size,
%random point in [-1,+1]
T(j,:) = minX + (maxX - minX).*rand(2,1);
%equation of the two lines is used to compute the y-value
y1 = ( ( B(2) - A(2) ) / ( B(1) - A(1) ) ) * (T(j,1) - A(1)) + A(2);
y2 = (- W(1) / W(2)) * T(j,1) -tresh / W(2);
if(T(j,2) < y1),
%point is under line one
Y1 = -1;
else
%point is above line one
Y1 = +1;
end
if(T(j,2) < y2),
%point is under line two
Y2 = -1;
else
%point is above line two
Y2 = +1;
end
if(Y1 * Y2 < 0),
errors = errors + 1;
scatter(T(j,1),T(j,2),'fill','r')
else
scatter(T(j,1),T(j,2),'fill','g')
end
end
area = (errors / size) / 4;
And here are two images, it sure takes longer than the solution posted by #Rody but as you can see you can make it accurate.
Number of points = 2000
Number of points = 10000
I have two rectangles a and b with their sides parallel to the axes of the coordinate system. I have their co-ordinates as x1,y1,x2,y2.
I'm trying to determine, not only do they overlap, but HOW MUCH do they overlap? I'm trying to figure out if they're really the same rectangle give or take a bit of wiggle room. So is their area 95% the same?
Any help in calculating the % of overlap?
Compute the area of the intersection, which is a rectangle too:
SI = Max(0, Min(XA2, XB2) - Max(XA1, XB1)) * Max(0, Min(YA2, YB2) - Max(YA1, YB1))
From there you compute the area of the union:
SU = SA + SB - SI
And you can consider the ratio
SI / SU
(100% in case of a perfect overlap, down to 0%).
While the accepted answer is correct, I think it's worth exploring this answer in a way that will make the rationale for the answer completely obvious. This is too common an algorithm to have an incomplete (or worse, controversial) answer. Furthermore, with only a passing glance at the given formula, you may miss the beauty and extensibility of the algorithm, and the implicit decisions that are being made.
We're going to build our way up to making these formulas intuitive:
intersecting_area =
max(0,
min(orange.circle.x, blue.circle.x)
- max(orange.triangle.x, blue.triangle.x)
)
* max(0,
min(orange.circle.y, blue.circle.y)
- max(orange.triangle.y, blue.triangle.y)
)
percent_coverage = intersecting_area
/ (orange_area + blue_area - intersecting_area)
First, consider one way to define a two dimensional box is with:
(x, y) for the top left point
(x, y) for the bottom right point
This might look like:
I indicate the top left with a triangle and the bottom right with a circle. This is to avoid opaque syntax like x1, x2 for this example.
Two overlapping rectangles might look like this:
Notice that to find the overlap you're looking for the place where the orange and the blue collide:
Once you recognize this, it becomes obvious that overlap is the result of finding and multiplying these two darkened lines:
The length of each line is the minimum value of the two circle points, minus the maximum value of the two triangle points.
Here, I'm using a two-toned triangle (and circle) to show that the orange and the blue points are compared with each other. The small letter 'y' after the two-toned triangle indicates that the triangles are compared along the y axis, the small 'x' means they are compared along the x axis.
For example, to find the length of the darkened blue line you can see the triangles are compared to look for the maximum value between the two. The attribute that is compared is the x attribute. The maximum x value between the triangles is 210.
Another way to say the same thing is:
The length of the new line that fits onto both the orange and blue lines is found by subtracting the furthest point on the closest side of the line from the closest point on the furthest side of the line.
Finding those lines gives complete information about the overlapping areas.
Once you have this, finding the percentage of overlap is trivial:
But wait, if the orange rectangle does not overlap with the blue one then you're going to have a problem:
With this example, you get a -850 for our overlapping area, that can't be right. Even worse, if a detection doesn't overlap with either dimension (neither on the x or y axis) then you will still get a positive number because both dimensions are negative. This is why you see the Max(0, ...) * Max(0, ...) as part of the solution; it ensures that if any of the overlaps are negative you'll get a 0 back from your function.
The final formula in keeping with our symbology:
It's worth noting that using the max(0, ...) function may not be necessary. You may want to know if something overlaps along one of its dimensions rather than all of them; if you use max then you will obliterate that information. For that reason, consider how you want to deal with non-overlapping bounding boxes. Normally, the max function is fine to use, but it's worth being aware what it's doing.
Finally, notice that since this comparison is only concerned with linear measurements it can be scaled to arbitrary dimensions or arbitrary overlapping quadrilaterals.
To summarize:
intersecting_area =
max(0,
min(orange.circle.x, blue.circle.x)
- max(orange.triangle.x, blue.triangle.x)
)
* max(0,
min(orange.circle.y, blue.circle.y)
- max(orange.triangle.y, blue.triangle.y)
)
percent_coverage = intersecting_area
/ (orange_area + blue_area - intersecting_area)
I recently ran into this problem as well and applied Yves' answer, but somehow that led to the wrong area size, so I rewrote it.
Assuming two rectangles A and B, find out how much they overlap and if so, return the area size:
IF A.right < B.left OR A.left > B.right
OR A.bottom < B.top OR A.top > B.bottom THEN RETURN 0
width := IF A.right > B.right THEN B.right - A.left ELSE A.right - B.left
height := IF A.bottom > B.bottom THEN B.bottom - A.top ELSE A.bottom - B.top
RETURN width * height
Just fixing previous answers so that the ratio is between 0 and 1 (using Python):
# (x1,y1) top-left coord, (x2,y2) bottom-right coord, (w,h) size
A = {'x1': 0, 'y1': 0, 'x2': 99, 'y2': 99, 'w': 100, 'h': 100}
B = {'x1': 0, 'y1': 0, 'x2': 49, 'y2': 49, 'w': 50, 'h': 50}
# overlap between A and B
SA = A['w']*A['h']
SB = B['w']*B['h']
SI = np.max([ 0, 1 + np.min([A['x2'],B['x2']]) - np.max([A['x1'],B['x1']]) ]) * np.max([ 0, 1 + np.min([A['y2'],B['y2']]) - np.max([A['y1'],B['y1']]) ])
SU = SA + SB - SI
overlap_AB = float(SI) / float(SU)
print 'overlap between A and B: %f' % overlap_AB
# overlap between A and A
B = A
SB = B['w']*B['h']
SI = np.max([ 0, 1 + np.min([A['x2'],B['x2']]) - np.max([A['x1'],B['x1']]) ]) * np.max([ 0, 1 + np.min([A['y2'],B['y2']]) - np.max([A['y1'],B['y1']]) ])
SU = SA + SB - SI
overlap_AA = float(SI) / float(SU)
print 'overlap between A and A: %f' % overlap_AA
The output will be:
overlap between A and B: 0.250000
overlap between A and A: 1.000000
Assuming that the rectangle must be parallel to x and y axis as that seems to be the situation from the previous comments and answers.
I cannot post comment yet, but I would like to point out that both previous answers seem to ignore the case when one side rectangle is totally within the side of the other rectangle. Please correct me if I am wrong.
Consider the case
a: (1,1), (4,4)
b: (2,2), (5,3)
In this case, we see that for the intersection, height must be bTop - bBottom because the vertical part of b is wholly contained in a.
We just need to add more cases as follows: (The code can be shorted if you treat top and bottom as the same thing as right and left, so that you do not need to duplicate the conditional chunk twice, but this should do.)
if aRight <= bLeft or bRight <= aLeft or aTop <= bBottom or bTop <= aBottom:
# There is no intersection in these cases
return 0
else:
# There is some intersection
if aRight >= bRight and aLeft <= bLeft:
# From x axis point of view, b is wholly contained in a
width = bRight - bLeft
elif bRight >= aRight and bLeft <= aLeft:
# From x axis point of view, a is wholly contained in b
width = aRight - aLeft
elif aRight >= bRight:
width = bRight - aLeft
else:
width = aRight - bLeft
if aTop >= bTop and aBottom <= bBottom:
# From y axis point of view, b is wholly contained in a
height = bTop - bBottom
elif bTop >= aTop and bBottom <= aBottom:
# From y axis point of view, a is wholly contained in b
height = aTop - aBottom
elif aTop >= bTop:
height = bTop - aBottom
else:
height = aTop - bBottom
return width * height
Here is a working Function in C#:
public double calculateOverlapPercentage(Rectangle A, Rectangle B)
{
double result = 0.0;
//trivial cases
if (!A.IntersectsWith(B)) return 0.0;
if (A.X == B.X && A.Y == B.Y && A.Width == B.Width && A.Height == B.Height) return 100.0;
//# overlap between A and B
double SA = A.Width * A.Height;
double SB = B.Width * B.Height;
double SI = Math.Max(0, Math.Min(A.Right, B.Right) - Math.Max(A.Left, B.Left)) *
Math.Max(0, Math.Min(A.Bottom, B.Bottom) - Math.Max(A.Top, B.Top));
double SU = SA + SB - SI;
result = SI / SU; //ratio
result *= 100.0; //percentage
return result;
}
[ymin_a, xmin_a, ymax_a, xmax_a] = list(bbox_a)
[ymin_b, xmin_b, ymax_b, xmax_b] = list(bbox_b)
x_intersection = min(xmax_a, xmax_b) - max(xmin_a, xmin_b) + 1
y_intersection = min(ymax_a, ymax_b) - max(ymin_a, ymin_b) + 1
if x_intersection <= 0 or y_intersection <= 0:
return 0
else:
return x_intersection * y_intersection
#User3025064 is correct and is the simplest solution, though, exclusivity must be checked first for rectangles that do not intersect e.g., for rectangles A & B (in Visual Basic):
If A.Top =< B.Bottom or A.Bottom => B.Top or A.Right =< B.Left or A.Left => B.Right then
Exit sub 'No intersection
else
width = ABS(Min(XA2, XB2) - Max(XA1, XB1))
height = ABS(Min(YA2, YB2) - Max(YA1, YB1))
Area = width * height 'Total intersection area.
End if
The answer of #user3025064 is the right answer. The accepted answer inadvertently flips the inner MAX and MIN calls.
We also don't need to check first if they intersect or not if we use the presented formula, MAX(0,x) as opposed to ABS(x). If they do not intersect, MAX(0,x) returns zero which makes the intersection area 0 (i.e. disjoint).
I suggest that #Yves Daoust fixes his answer because it is the accepted one that pops up to anyone who searches for that problem. Once again, here is the right formula for intersection:
SI = Max(0, Min(XA2, XB2) - Max(XA1, XB1)) * Max(0, Min(YA2, YB2) - Max(YA1, YB1))
The rest as usual. Union:
SU = SA + SB - SI
and ratio:
SI/SU