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Actually i have two intersecting circles as specified in the figure
i want to find the area of each part separately using Monte carlo method in Matlab .
The code doesn't draw the rectangle or the circles correctly so
i guess what is wrong is my calculation for the x and y and i am not much aware about the geometry equations for solving it so i need help about the equations.
this is my code so far :
n=1000;
%supposing that a rectangle will contain both circles so :
% the mid point of the distance between 2 circles will be (0,6)
% then by adding the radius of the left and right circles the total distance
% will be 27 , 11 from the left and 16 from the right
% width of rectangle = 24
x=27.*rand(n-1)-11;
y=24.*rand(n-1)+2;
count=0;
for i=1:n
if((x(i))^2+(y(i))^2<=25 && (x(i))^2+(y(i)-12)^2<=100)
count=count+1;
figure(2);
plot(x(i),y(i),'b+')
hold on
elseif(~(x(i))^2+(y(i))^2<=25 &&(x(i))^2+(y(i)-12)^2<=100)
figure(2);
plot(x(i),y(i),'y+')
hold on
else
figure(2);
plot(x(i),y(i),'r+')
end
end
Here are the errors I found:
x = 27*rand(n,1)-5
y = 24*rand(n,1)-12
The rectangle extents were incorrect, and if you use rand(n-1) will give you a (n-1) by (n-1) matrix.
and
first If:
(x(i))^2+(y(i))^2<=25 && (x(i)-12)^2+(y(i))^2<=100
the center of the large circle is at x=12 not y=12
Second If:
~(x(i))^2+(y(i))^2<=25 &&(x(i)-12)^2+(y(i))^2<=100
This code can be improved by using logical indexing.
For example, using R, you could do (Matlab code is left as an excercise):
n = 10000
x = 27*runif(n)-5
y = 24*runif(n)-12
plot(x,y)
r = (x^2 + y^2)<=25 & ((x-12)^2 + y^2)<=100
g = (x^2 + y^2)<=25
b = ((x-12)^2 + y^2)<=100
points(x[g],y[g],col="green")
points(x[b],y[b],col="blue")
points(x[r],y[r],col="red")
which gives:
Here is my generic solution for any two circles (without any hardcoded value):
function [ P ] = circles_intersection_area( k1, k2, N )
%CIRCLES_INTERSECTION_AREA Summary...
% Adnan A.
x1 = k1(1);
y1 = k1(2);
r1 = k1(3);
x2 = k2(1);
y2 = k2(2);
r2 = k2(3);
if sqrt((x1-x2)*(x1-x2) + (y1-y2)*(y1-y2)) >= (r1 + r2)
% no intersection
P = 0;
return
end
% Wrapper rectangle config
a_min = x1 - r1 - 2*r2;
a_max = x1 + r1 + 2*r2;
b_min = y1 - r1 - 2*r2;
b_max = y1 + r1 + 2*r2;
% Monte Carlo algorithm
n = 0;
for i = 1:N
rand_x = unifrnd(a_min, a_max);
rand_y = unifrnd(b_min, b_max);
if sqrt((rand_x - x1)^2 + (rand_y - y1)^2) < r1 && sqrt((rand_x - x2)^2 + (rand_y - y2)^2) < r2
% is a point in the both of circles
n = n + 1;
plot(rand_x,rand_y, 'go-');
hold on;
else
plot(rand_x,rand_y, 'ko-');
hold on;
end
end
P = (a_max - a_min) * (b_max - b_min) * n / N;
end
Call it like: circles_intersection_area([-0.4,0,1], [0.4,0,1], 10000) where the first param is the first circle (x,y,r) and the second param is the second circle.
Without using For loop.
n = 100000;
data = rand(2,n);
data = data*2*30 - 30;
x = data(1,:);
y = data(2,:);
plot(x,y,'ro');
inside5 = find(x.^2 + y.^2 <=25);
hold on
plot (x(inside5),y(inside5),'bo');
hold on
inside12 = find(x.^2 + (y-12).^2<=144);
plot (x(inside12),y(inside12),'g');
hold on
insidefinal1 = find(x.^2 + y.^2 <=25 & x.^2 + (y-12).^2>=144);
insidefinal2 = find(x.^2 + y.^2 >=25 & x.^2 + (y-12).^2<=144);
% plot(x(insidefinal1),y(insidefinal1),'bo');
hold on
% plot(x(insidefinal2),y(insidefinal2),'ro');
insidefinal3 = find(x.^2 + y.^2 <=25 & x.^2 + (y-12).^2<=144);
% plot(x(insidefinal3),y(insidefinal3),'ro');
area1=(60^2)*(length(insidefinal1)/n);
area3=(60^2)*(length(insidefinal2)/n);
area2= (60^2)*(length(insidefinal3)/n);
I have a non-grid-aligned set of input values associated with grid-aligned output values. Given a new input value I want to find the output:
(These are X,Y coordinates, calibrating an imprecise not-square eye-tracking input device to exact locations on screen.)
This looks like Bilinear Interpolation, but my input values are not grid-aligned. Given an input, how can I figure out a reasonable output value?
Answer: In this case where I have sets of input and output points, what is actually needed is to perform inverse bilinear interpolation to find the U,V coordinates of the input point within the quad, and then perform normal bilinear interpolation (as described in Nico's answer below) on the output quad using those U,V coordinates.
You can bilinearly interpolate in any convex tetragon. A cartesian grid is just a bit simpler because the calculation of interpolation parameters is trivial. In the general case you interpolate as follows:
parameters alpha, beta
interpolated value = (1 - alpha) * ((1 - beta) * p1 + beta * p2) + alpha * ((1 - beta) * p3 + beta * p4)
In order to calculate the parameters, you have to solve a system of equations. Put your input values in the places of p1 through p4 and solve for alpha and beta.
Then put your output values in the places of p1 through p4 and use the calculated parameters to calculate the final interpolated output value.
For a regular grid, the parameter calculation comes down to:
alpha = x / cell width
beta = y / cell height
which automatically solves the equations.
Here is a sample interpolation for alpha=0.3 and beta=0.6
Actually, the equations can be solved analytically. However, the formulae are quite ugly. Therefore, iterative methods are probably nicer. There are two solutions for the system of equations. You need to pick the solution where both parameters are in [0, 1].
First solution:
alpha = -(b e - a f + d g - c h + sqrt(-4 (c e - a g) (d f - b h) +
(b e - a f + d g - c h)^2))/(2 c e - 2 a g)
beta = (b e - a f - d g + c h + sqrt(-4 (c e - a g) (d f - b h) +
(b e - a f + d g - c h)^2))/(2 c f - 2 b g)
where
a = -p1.x + p3.x
b = -p1.x + p2.x
c = p1.x - p2.x - p3.x + p4.x
d = interpolated_point.x - p1.x
e = -p1.y + p3.y
f = -p1.y + p2.y
g = p1.y - p2.y - p3.y + p4.y
h = interpolated_point.y - p1.y
Second solution:
alpha = (-b e + a f - d g + c h + sqrt(-4 (c e - a g) (d f - b h) +
(b e - a f + d g - c h)^2))/(2 c e - 2 a g)
beta = -((-b e + a f + d g - c h + sqrt(-4 (c e - a g) (d f - b h) +
(b e - a f + d g - c h)^2))/( 2 c f - 2 b g))
Here's my own technique, along with code for deriving the resulting value. It requires three lerps of the output values (and three percentage calculations to determine the lerp percentages):
Note that this is not bilinear interpolation. It does not remap the quad of input points to the quad of output values, as some input points can result in output values outside the output quad.
Here I'm showing the non-aligned input values on a Cartesian plane (using the sample input values from the question above, multiplied by 10 for simplicity).
To calculate the 'north' point (top green dot), we calculate the percentage across the X axis as
(inputX - northwestX) / (northeastX - northwestX)
= (-4.2 - -19) / (10 - -19)
= 0.51034
We use this percentage to calculate the intercept at the Y axis by lerping between the top Y values:
(targetValue - startValue) * percent + startValue
= (northeastY - northwestY) * percent + northwestY
= (-8 - -7) * 0.51034 + -7
= -7.51034
We do the same on the 'south' edge:
(inputX - southwestX) / (southeastX - southwestX)
= (-4.2 - -11) / (9 - -11)
= 0.34
(southeastY - southwestY) * percent + southwestY
= (7 - 4) * 0.34 + 4
= 5.02
Finally, we use these two values to calculate the final percentage between the north and south edges:
(inputY - southY) / (northY - southY)
= (1 - 5.02) / (-7.51034 - 5.02)
= 0.3208
With these three percentages in hand we can calculate our final output values by lerping between the points:
nw = Vector(-150,-100)
ne = Vector( 150,-100)
sw = Vector(-150, 100)
se = Vector( 150, 100)
north = lerp( nw, ne, 0.51034) --> ( 3.10, -100.00)
south = lerp( sw, se, 0.34) --> (-48.00, 100.00)
result = lerp( south, north, 0.3208) --> (-31.61, 35.84)
Finally, here is some (Lua) code performing the above. It uses a mutable Vector object that supports the ability to copy values from another vector and lerp its values towards another vector.
-- Creates a bilinear interpolator
-- Corners should be an object with nw/ne/sw/se keys,
-- each of which holds a pair of mutable Vectors
-- { nw={inp=vector1, out=vector2}, … }
function tetragonalBilinearInterpolator(corners)
local sides = {
n={ pt=Vector(), pts={corners.nw, corners.ne} },
s={ pt=Vector(), pts={corners.sw, corners.se} }
}
for _,side in pairs(sides) do
side.minX = side.pts[1].inp.x
side.diff = side.pts[2].inp.x - side.minX
end
-- Mutates the input vector to hold the result
return function(inpVector)
for _,side in pairs(sides) do
local pctX = (inpVector.x - side.minX) / side.diff
side.pt:copyFrom(side.pts[1].inp):lerp(side.pts[2].inp,pctX)
side.inpY = side.pt.y
side.pt:copyFrom(side.pts[1].out):lerp(side.pts[2].out,pctX)
end
local pctY = (inpVector.y-sides.s.inpY)/(sides.n.y-sides.s.inpY)
return inpVector:copyFrom(sides.s.pt):lerp(sides.n.pt,pctY)
end
end
local interp = tetragonalBilinearInterpolator{
nw={ inp=Vector(-19,-7), out=Vector(-150,-100) },
ne={ inp=Vector( 10,-8), out=Vector( 150,-100) },
sw={ inp=Vector(-11, 4), out=Vector(-150, 100) },
se={ inp=Vector( 9, 7), out=Vector( 150, 100) }
}
print(interp(Vector(-4.2, 1))) --> <-31.60 35.84>
I want to find the coordinate of an unknown node which lie somewhere in the space which has its reference distance away from 3 or more nodes which all of them have known coordinate.
This problem is exactly like Trilateration as described here Trilateration.
However, I don't understand the part about "Preliminary and final computations" (refer to the wikipedia site). I don't get where I could find P1, P2 and P3 just so I can put to those equation?
Thanks
Trilateration is the process of finding the center of the area of intersection of three spheres. The center point and radius of each of the three spheres must be known.
Let's consider your three example centerpoints P1 [-1,1], P2 [1,1], and P3 [-1,-1]. The first requirement is that P1' be at the origin, so let us adjust the points accordingly by adding an offset vector V [1,-1] to all three:
P1' = P1 + V = [0, 0]
P2' = P2 + V = [2, 0]
P3' = P3 + V = [0,-2]
Note: Adjusted points are denoted by the ' (prime) annotation.
P2' must also lie on the x-axis. In this case it already does, so no adjustment is necessary.
We will assume the radius of each sphere to be 2.
Now we have 3 equations (given) and 3 unknowns (X, Y, Z of center-of-intersection point).
Solve for P4'x:
x = (r1^2 - r2^2 + d^2) / 2d //(d,0) are coords of P2'
x = (2^2 - 2^2 + 2^2) / 2*2
x = 1
Solve for P4'y:
y = (r1^2 - r3^2 + i^2 + j^2) / 2j - (i/j)x //(i,j) are coords of P3'
y = (2^2 - 2^2 + 0 + -2^2) / 2*-2 - 0
y = -1
Ignore z for 2D problems.
P4' = [1,-1]
Now we translate back to original coordinate space by subtracting the offset vector V:
P4 = P4' - V = [0,0]
The solution point, P4, lies at the origin as expected.
The second half of the article is describing a method of representing a set of points where P1 is not at the origin or P2 is not on the x-axis such that they fit those constraints. I prefer to think of it instead as a translation, but both methods will result in the same solution.
Edit: Rotating P2' to the x-axis
If P2' does not lie on the x-axis after translating P1 to the origin, we must perform a rotation on the view.
First, let's create some new vectors to use as an example:
P1 = [2,3]
P2 = [3,4]
P3 = [5,2]
Remember, we must first translate P1 to the origin. As always, the offset vector, V, is -P1. In this case, V = [-2,-3]
P1' = P1 + V = [2,3] + [-2,-3] = [0, 0]
P2' = P2 + V = [3,4] + [-2,-3] = [1, 1]
P3' = P3 + V = [5,2] + [-2,-3] = [3,-1]
To determine the angle of rotation, we must find the angle between P2' and [1,0] (the x-axis).
We can use the dot product equality:
A dot B = ||A|| ||B|| cos(theta)
When B is [1,0], this can be simplified: A dot B is always just the X component of A, and ||B|| (the magnitude of B) is always a multiplication by 1, and can therefore be ignored.
We now have Ax = ||A|| cos(theta), which we can rearrange to our final equation:
theta = acos(Ax / ||A||)
or in our case:
theta = acos(P2'x / ||P2'||)
We calculate the magnitude of P2' using ||A|| = sqrt(Ax + Ay + Az)
||P2'|| = sqrt(1 + 1 + 0) = sqrt(2)
Plugging that in we can solve for theta
theta = acos(1 / sqrt(2)) = 45 degrees
Now let's use the rotation matrix to rotate the scene by -45 degrees.
Since P2'y is positive, and the rotation matrix rotates counter-clockwise, we'll use a negative rotation to align P2 to the x-axis (if P2'y is negative, don't negate theta).
R(theta) = [cos(theta) -sin(theta)]
[sin(theta) cos(theta)]
R(-45) = [cos(-45) -sin(-45)]
[sin(-45) cos(-45)]
We'll use double prime notation, '', to denote vectors which have been both translated and rotated.
P1'' = [0,0] (no need to calculate this one)
P2'' = [1 cos(-45) - 1 sin(-45)] = [sqrt(2)] = [1.414]
[1 sin(-45) + 1 cos(-45)] = [0] = [0]
P3'' = [3 cos(-45) - (-1) sin(-45)] = [sqrt(2)] = [ 1.414]
[3 sin(-45) + (-1) cos(-45)] = [-2*sqrt(2)] = [-2.828]
Now you can use P1'', P2'', and P3'' to solve for P4''. Apply the reverse rotation to P4'' to get P4', then the reverse translation to get P4, your center point.
To undo the rotation, multiply P4'' by R(-theta), in this case R(45). To undo the translation, subtract the offset vector V, which is the same as adding P1 (assuming you used -P1 as your V originally).
This is the algorithm I use in a 3D printer firmware. It avoids rotating the coordinate system, but it may not be the best.
There are 2 solutions to the trilateration problem. To get the second one, replace "- sqrtf" by "+ sqrtf" in the quadratic equation solution.
Obviously you can use doubles instead of floats if you have enough processor power and memory.
// Primary parameters
float anchorA[3], anchorB[3], anchorC[3]; // XYZ coordinates of the anchors
// Derived parameters
float Da2, Db2, Dc2;
float Xab, Xbc, Xca;
float Yab, Ybc, Yca;
float Zab, Zbc, Zca;
float P, Q, R, P2, U, A;
...
inline float fsquare(float f) { return f * f; }
...
// Precompute the derived parameters - they don't change unless the anchor positions change.
Da2 = fsquare(anchorA[0]) + fsquare(anchorA[1]) + fsquare(anchorA[2]);
Db2 = fsquare(anchorB[0]) + fsquare(anchorB[1]) + fsquare(anchorB[2]);
Dc2 = fsquare(anchorC[0]) + fsquare(anchorC[1]) + fsquare(anchorC[2]);
Xab = anchorA[0] - anchorB[0];
Xbc = anchorB[0] - anchorC[0];
Xca = anchorC[0] - anchorA[0];
Yab = anchorA[1] - anchorB[1];
Ybc = anchorB[1] - anchorC[1];
Yca = anchorC[1] - anchorA[1];
Zab = anchorB[2] - anchorC[2];
Zbc = anchorB[2] - anchorC[2];
Zca = anchorC[2] - anchorA[2];
P = ( anchorB[0] * Yca
- anchorA[0] * anchorC[1]
+ anchorA[1] * anchorC[0]
- anchorB[1] * Xca
) * 2;
P2 = fsquare(P);
Q = ( anchorB[1] * Zca
- anchorA[1] * anchorC[2]
+ anchorA[2] * anchorC[1]
- anchorB[2] * Yca
) * 2;
R = - ( anchorB[0] * Zca
+ anchorA[0] * anchorC[2]
+ anchorA[2] * anchorC[0]
- anchorB[2] * Xca
) * 2;
U = (anchorA[2] * P2) + (anchorA[0] * Q * P) + (anchorA[1] * R * P);
A = (P2 + fsquare(Q) + fsquare(R)) * 2;
...
// Calculate Cartesian coordinates given the distances to the anchors (La, Lb and Lc)
// First calculate PQRST such that x = (Qz + S)/P, y = (Rz + T)/P.
// P, Q and R depend only on the anchor positions, so they are pre-computed
const float S = - Yab * (fsquare(Lc) - Dc2)
- Yca * (fsquare(Lb) - Db2)
- Ybc * (fsquare(La) - Da2);
const float T = - Xab * (fsquare(Lc) - Dc2)
+ Xca * (fsquare(Lb) - Db2)
+ Xbc * (fsquare(La) - Da2);
// Calculate quadratic equation coefficients
const float halfB = (S * Q) - (R * T) - U;
const float C = fsquare(S) + fsquare(T) + (anchorA[1] * T - anchorA[0] * S) * P * 2 + (Da2 - fsquare(La)) * P2;
// Solve the quadratic equation for z
float z = (- halfB - sqrtf(fsquare(halfB) - A * C))/A;
// Substitute back for X and Y
float x = (Q * z + S)/P;
float y = (R * z + T)/P;
Here are the Wikipedia calculations, presented in an OpenSCAD script, which I think helps to understand the problem in a visual wayand provides an easy way to check that the results are correct. Example output from the script
// Trilateration example
// from Wikipedia
//
// pA, pB and pC are the centres of the spheres
// If necessary the spheres must be translated
// and rotated so that:
// -- all z values are 0
// -- pA is at the origin
pA = [0,0,0];
// -- pB is on the x axis
pB = [10,0,0];
pC = [9,7,0];
// rA , rB and rC are the radii of the spheres
rA = 9;
rB = 5;
rC = 7;
if ( pA != [0,0,0]){
echo ("ERROR: pA must be at the origin");
assert(false);
}
if ( (pB[2] !=0 ) || pC[2] !=0){
echo("ERROR: all sphere centers must be in z = 0 plane");
assert(false);
}
if (pB[1] != 0){
echo("pB centre must be on the x axis");
assert(false);
}
// show the spheres
module spheres(){
translate (pA){
sphere(r= rA, $fn = rA * 10);
}
translate(pB){
sphere(r = rB, $fn = rB * 10);
}
translate(pC){
sphere (r = rC, $fn = rC * 10);
}
}
function unit_vector( v) = v / norm(v);
ex = unit_vector(pB - pA) ;
echo(ex = ex);
i = ex * ( pC - pA);
echo (i = i);
ey = unit_vector(pC - pA - i * ex);
echo (ey = ey);
d = norm(pB - pA);
echo (d = d);
j = ey * ( pC - pA);
echo (j = j);
x = (pow(rA,2) - pow(rB,2) + pow(d,2)) / (2 * d);
echo( x = x);
// size of the cube to subtract to show
// the intersection of the spheres
cube_size = [10,10,10];
if ( ((d - rA) >= rB) || ( rB >= ( d + rA)) ){
echo ("Error Y not solvable");
}else{
y = (( pow(rA,2) - pow(rC,2) + pow(i,2) + pow(j,2)) / (2 * j))
- ( i / j) * x;
echo(y = y);
zpow2 = pow(rA,2) - pow(x,2) - pow(y,2);
if ( zpow2 < 0){
echo ("z not solvable");
}else{
z = sqrt(zpow2);
echo (z = z);
// subtract a cube with one of its corners
// at the point where the sphers intersect
difference(){
spheres();
translate ([x,y - cube_size[1],z]){
cube(cube_size);
}
}
translate ([x,y - cube_size[1],z]){
%cube(cube_size);
}
}
}
For example, here is the shape of intended spiral (and each step of the iteration)
y
|
|
16 15 14 13 12
17 4 3 2 11
-- 18 5 0 1 10 --- x
19 6 7 8 9
20 21 22 23 24
|
|
Where the lines are the x and y axes.
Here would be the actual values the algorithm would "return" with each iteration (the coordinates of the points):
[0,0],
[1,0], [1,1], [0,1], [-1,1], [-1,0], [-1,-1], [0,-1], [1,-1],
[2,-1], [2,0], [2,1], [2,2], [1,2], [0,2], [-1,2], [-2,2], [-2,1], [-2,0]..
etc.
I've tried searching, but I'm not exactly sure what to search for exactly, and what searches I've tried have come up with dead ends.
I'm not even sure where to start, other than something messy and inelegant and ad-hoc, like creating/coding a new spiral for each layer.
Can anyone help me get started?
Also, is there a way that can easily switch between clockwise and counter-clockwise (the orientation), and which direction to "start" the spiral from? (the rotation)
Also, is there a way to do this recursively?
My application
I have a sparse grid filled with data points, and I want to add a new data point to the grid, and have it be "as close as possible" to a given other point.
To do that, I'll call grid.find_closest_available_point_to(point), which will iterate over the spiral given above and return the first position that is empty and available.
So first, it'll check point+[0,0] (just for completeness's sake). Then it'll check point+[1,0]. Then it'll check point+[1,1]. Then point+[0,1], etc. And return the first one for which the position in the grid is empty (or not occupied already by a data point).
There is no upper bound to grid size.
There's nothing wrong with direct, "ad-hoc" solution. It can be clean enough too.
Just notice that spiral is built from segments. And you can get next segment from current one rotating it by 90 degrees. And each two rotations, length of segment grows by 1.
edit Illustration, those segments numbered
... 11 10
7 7 7 7 6 10
8 3 3 2 6 10
8 4 . 1 6 10
8 4 5 5 5 10
8 9 9 9 9 9
// (di, dj) is a vector - direction in which we move right now
int di = 1;
int dj = 0;
// length of current segment
int segment_length = 1;
// current position (i, j) and how much of current segment we passed
int i = 0;
int j = 0;
int segment_passed = 0;
for (int k = 0; k < NUMBER_OF_POINTS; ++k) {
// make a step, add 'direction' vector (di, dj) to current position (i, j)
i += di;
j += dj;
++segment_passed;
System.out.println(i + " " + j);
if (segment_passed == segment_length) {
// done with current segment
segment_passed = 0;
// 'rotate' directions
int buffer = di;
di = -dj;
dj = buffer;
// increase segment length if necessary
if (dj == 0) {
++segment_length;
}
}
}
To change original direction, look at original values of di and dj. To switch rotation to clockwise, see how those values are modified.
Here's a stab at it in C++, a stateful iterator.
class SpiralOut{
protected:
unsigned layer;
unsigned leg;
public:
int x, y; //read these as output from next, do not modify.
SpiralOut():layer(1),leg(0),x(0),y(0){}
void goNext(){
switch(leg){
case 0: ++x; if(x == layer) ++leg; break;
case 1: ++y; if(y == layer) ++leg; break;
case 2: --x; if(-x == layer) ++leg; break;
case 3: --y; if(-y == layer){ leg = 0; ++layer; } break;
}
}
};
Should be about as efficient as it gets.
This is the javascript solution based on the answer at
Looping in a spiral
var x = 0,
y = 0,
delta = [0, -1],
// spiral width
width = 6,
// spiral height
height = 6;
for (i = Math.pow(Math.max(width, height), 2); i>0; i--) {
if ((-width/2 < x && x <= width/2)
&& (-height/2 < y && y <= height/2)) {
console.debug('POINT', x, y);
}
if (x === y
|| (x < 0 && x === -y)
|| (x > 0 && x === 1-y)){
// change direction
delta = [-delta[1], delta[0]]
}
x += delta[0];
y += delta[1];
}
fiddle: http://jsfiddle.net/N9gEC/18/
This problem is best understood by analyzing how changes coordinates of spiral corners. Consider this table of first 8 spiral corners (excluding origin):
x,y | dx,dy | k-th corner | N | Sign |
___________________________________________
1,0 | 1,0 | 1 | 1 | +
1,1 | 0,1 | 2 | 1 | +
-1,1 | -2,0 | 3 | 2 | -
-1,-1 | 0,-2 | 4 | 2 | -
2,-1 | 3,0 | 5 | 3 | +
2,2 | 0,3 | 6 | 3 | +
-2,2 | -4,0 | 7 | 4 | -
-2,-2 | 0,-4 | 8 | 4 | -
By looking at this table we can calculate X,Y of k-th corner given X,Y of (k-1) corner:
N = INT((1+k)/2)
Sign = | +1 when N is Odd
| -1 when N is Even
[dx,dy] = | [N*Sign,0] when k is Odd
| [0,N*Sign] when k is Even
[X(k),Y(k)] = [X(k-1)+dx,Y(k-1)+dy]
Now when you know coordinates of k and k+1 spiral corner you can get all data points in between k and k+1 by simply adding 1 or -1 to x or y of last point.
Thats it.
good luck.
I would solve it using some math. Here is Ruby code (with input and output):
(0..($*.pop.to_i)).each do |i|
j = Math.sqrt(i).round
k = (j ** 2 - i).abs - j
p = [k, -k].map {|l| (l + j ** 2 - i - (j % 2)) * 0.5 * (-1) ** j}.map(&:to_i)
puts "p => #{p[0]}, #{p[1]}"
end
E.g.
$ ruby spiral.rb 10
p => 0, 0
p => 1, 0
p => 1, 1
p => 0, 1
p => -1, 1
p => -1, 0
p => -1, -1
p => 0, -1
p => 1, -1
p => 2, -1
p => 2, 0
And golfed version:
p (0..$*.pop.to_i).map{|i|j=Math.sqrt(i).round;k=(j**2-i).abs-j;[k,-k].map{|l|(l+j**2-i-j%2)*0.5*(-1)**j}.map(&:to_i)}
Edit
First try to approach the problem functionally. What do you need to know, at each step, to get to the next step?
Focus on plane's first diagonal x = y. k tells you how many steps you must take before touching it: negative values mean you have to move abs(k) steps vertically, while positive mean you have to move k steps horizontally.
Now focus on the length of the segment you're currently in (spiral's vertices - when the inclination of segments change - are considered as part of the "next" segment). It's 0 the first time, then 1 for the next two segments (= 2 points), then 2 for the next two segments (= 4 points), etc. It changes every two segments and each time the number of points part of that segments increase. That's what j is used for.
Accidentally, this can be used for getting another bit of information: (-1)**j is just a shorthand to "1 if you're decreasing some coordinate to get to this step; -1 if you're increasing" (Note that only one coordinate is changed at each step). Same holds for j%2, just replace 1 with 0 and -1 with 1 in this case. This mean they swap between two values: one for segments "heading" up or right and one for those going down or left.
This is a familiar reasoning, if you're used to functional programming: the rest is just a little bit of simple math.
It can be done in a fairly straightforward way using recursion. We just need some basic 2D vector math and tools for generating and mapping over (possibly infinite) sequences:
// 2D vectors
const add = ([x0, y0]) => ([x1, y1]) => [x0 + x1, y0 + y1];
const rotate = θ => ([x, y]) => [
Math.round(x * Math.cos(θ) - y * Math.sin(θ)),
Math.round(x * Math.sin(θ) + y * Math.cos(θ))
];
// Iterables
const fromGen = g => ({ [Symbol.iterator]: g });
const range = n => [...Array(n).keys()];
const map = f => it =>
fromGen(function*() {
for (const v of it) {
yield f(v);
}
});
And now we can express a spiral recursively by generating a flat line, plus a rotated (flat line, plus a rotated (flat line, plus a rotated ...)):
const spiralOut = i => {
const n = Math.floor(i / 2) + 1;
const leg = range(n).map(x => [x, 0]);
const transform = p => add([n, 0])(rotate(Math.PI / 2)(p));
return fromGen(function*() {
yield* leg;
yield* map(transform)(spiralOut(i + 1));
});
};
Which produces an infinite list of the coordinates you're interested in. Here's a sample of the contents:
const take = n => it =>
fromGen(function*() {
for (let v of it) {
if (--n < 0) break;
yield v;
}
});
const points = [...take(5)(spiralOut(0))];
console.log(points);
// => [[0,0],[1,0],[1,1],[0,1],[-1,1]]
You can also negate the rotation angle to go in the other direction, or play around with the transform and leg length to get more complex shapes.
For example, the same technique works for inward spirals as well. It's just a slightly different transform, and a slightly different scheme for changing the length of the leg:
const empty = [];
const append = it1 => it2 =>
fromGen(function*() {
yield* it1;
yield* it2;
});
const spiralIn = ([w, h]) => {
const leg = range(w).map(x => [x, 0]);
const transform = p => add([w - 1, 1])(rotate(Math.PI / 2)(p));
return w * h === 0
? empty
: append(leg)(
fromGen(function*() {
yield* map(transform)(spiralIn([h - 1, w]));
})
);
};
Which produces (this spiral is finite, so we don't need to take some arbitrary number):
const points = [...spiralIn([3, 3])];
console.log(points);
// => [[0,0],[1,0],[2,0],[2,1],[2,2],[1,2],[0,2],[0,1],[1,1]]
Here's the whole thing together as a live snippet if you want play around with it:
// 2D vectors
const add = ([x0, y0]) => ([x1, y1]) => [x0 + x1, y0 + y1];
const rotate = θ => ([x, y]) => [
Math.round(x * Math.cos(θ) - y * Math.sin(θ)),
Math.round(x * Math.sin(θ) + y * Math.cos(θ))
];
// Iterables
const fromGen = g => ({ [Symbol.iterator]: g });
const range = n => [...Array(n).keys()];
const map = f => it =>
fromGen(function*() {
for (const v of it) {
yield f(v);
}
});
const take = n => it =>
fromGen(function*() {
for (let v of it) {
if (--n < 0) break;
yield v;
}
});
const empty = [];
const append = it1 => it2 =>
fromGen(function*() {
yield* it1;
yield* it2;
});
// Outward spiral
const spiralOut = i => {
const n = Math.floor(i / 2) + 1;
const leg = range(n).map(x => [x, 0]);
const transform = p => add([n, 0])(rotate(Math.PI / 2)(p));
return fromGen(function*() {
yield* leg;
yield* map(transform)(spiralOut(i + 1));
});
};
// Test
{
const points = [...take(5)(spiralOut(0))];
console.log(JSON.stringify(points));
}
// Inward spiral
const spiralIn = ([w, h]) => {
const leg = range(w).map(x => [x, 0]);
const transform = p => add([w - 1, 1])(rotate(Math.PI / 2)(p));
return w * h === 0
? empty
: append(leg)(
fromGen(function*() {
yield* map(transform)(spiralIn([h - 1, w]));
})
);
};
// Test
{
const points = [...spiralIn([3, 3])];
console.log(JSON.stringify(points));
}
Here is a Python implementation based on the answer by #mako.
def spiral_iterator(iteration_limit=999):
x = 0
y = 0
layer = 1
leg = 0
iteration = 0
yield 0, 0
while iteration < iteration_limit:
iteration += 1
if leg == 0:
x += 1
if (x == layer):
leg += 1
elif leg == 1:
y += 1
if (y == layer):
leg += 1
elif leg == 2:
x -= 1
if -x == layer:
leg += 1
elif leg == 3:
y -= 1
if -y == layer:
leg = 0
layer += 1
yield x, y
Running this code:
for x, y in spiral_iterator(10):
print(x, y)
Yields:
0 0
1 0
1 1
0 1
-1 1
-1 0
-1 -1
0 -1
1 -1
2 -1
2 0
Try searching for either parametric or polar equations. Both are suitable to plotting spirally things. Here's a page that has plenty of examples, with pictures (and equations). It should give you some more ideas of what to look for.
I've done pretty much the same thin as a training exercise, with some differences in the output and the spiral orientation, and with an extra requirement, that the functions spatial complexity has to be O(1).
After think for a while I came to the idea that by knowing where does the spiral start and the position I was calculating the value for, I could simplify the problem by subtracting all the complete "circles" of the spiral, and then just calculate a simpler value.
Here is my implementation of that algorithm in ruby:
def print_spiral(n)
(0...n).each do |y|
(0...n).each do |x|
printf("%02d ", get_value(x, y, n))
end
print "\n"
end
end
def distance_to_border(x, y, n)
[x, y, n - 1 - x, n - 1 - y].min
end
def get_value(x, y, n)
dist = distance_to_border(x, y, n)
initial = n * n - 1
(0...dist).each do |i|
initial -= 2 * (n - 2 * i) + 2 * (n - 2 * i - 2)
end
x -= dist
y -= dist
n -= dist * 2
if y == 0 then
initial - x # If we are in the upper row
elsif y == n - 1 then
initial - n - (n - 2) - ((n - 1) - x) # If we are in the lower row
elsif x == n - 1 then
initial - n - y + 1# If we are in the right column
else
initial - 2 * n - (n - 2) - ((n - 1) - y - 1) # If we are in the left column
end
end
print_spiral 5
This is not exactly the thing you asked for, but I believe it'll help you to think your problem
I had a similar problem, but I didn't want to loop over the entire spiral each time to find the next new coordinate. The requirement is that you know your last coordinate.
Here is what I came up with with a lot of reading up on the other solutions:
function getNextCoord(coord) {
// required info
var x = coord.x,
y = coord.y,
level = Math.max(Math.abs(x), Math.abs(y));
delta = {x:0, y:0};
// calculate current direction (start up)
if (-x === level)
delta.y = 1; // going up
else if (y === level)
delta.x = 1; // going right
else if (x === level)
delta.y = -1; // going down
else if (-y === level)
delta.x = -1; // going left
// check if we need to turn down or left
if (x > 0 && (x === y || x === -y)) {
// change direction (clockwise)
delta = {x: delta.y,
y: -delta.x};
}
// move to next coordinate
x += delta.x;
y += delta.y;
return {x: x,
y: y};
}
coord = {x: 0, y: 0}
for (i = 0; i < 40; i++) {
console.log('['+ coord.x +', ' + coord.y + ']');
coord = getNextCoord(coord);
}
Still not sure if it is the most elegant solution. Perhaps some elegant maths could remove some of the if statements. Some limitations would be needing some modification to change spiral direction, doesn't take into account non-square spirals and can't spiral around a fixed coordinate.
I have an algorithm in java that outputs a similar output to yours, except that it prioritizes the number on the right, then the number on the left.
public static String[] rationals(int amount){
String[] numberList=new String[amount];
int currentNumberLeft=0;
int newNumberLeft=0;
int currentNumberRight=0;
int newNumberRight=0;
int state=1;
numberList[0]="("+newNumberLeft+","+newNumberRight+")";
boolean direction=false;
for(int count=1;count<amount;count++){
if(direction==true&&newNumberLeft==state){direction=false;state=(state<=0?(-state)+1:-state);}
else if(direction==false&&newNumberRight==state){direction=true;}
if(direction){newNumberLeft=currentNumberLeft+sign(state);}else{newNumberRight=currentNumberRight+sign(state);}
currentNumberLeft=newNumberLeft;
currentNumberRight=newNumberRight;
numberList[count]="("+newNumberLeft+","+newNumberRight+")";
}
return numberList;
}
Here's the algorithm. It rotates clockwise, but could easily rotate anticlockwise, with a few alterations. I made it in just under an hour.
// spiral_get_value(x,y);
sx = argument0;
sy = argument1;
a = max(sqrt(sqr(sx)),sqrt(sqr(sy)));
c = -b;
d = (b*2)+1;
us = (sy==c and sx !=c);
rs = (sx==b and sy !=c);
bs = (sy==b and sx !=b);
ls = (sx==c and sy !=b);
ra = rs*((b)*2);
ba = bs*((b)*4);
la = ls*((b)*6);
ax = (us*sx)+(bs*-sx);
ay = (rs*sy)+(ls*-sy);
add = ra+ba+la+ax+ay;
value = add+sqr(d-2)+b;
return(value);`
It will handle any x / y values (infinite).
It's written in GML (Game Maker Language), but the actual logic is sound in any programming language.
The single line algorithm only has 2 variables (sx and sy) for the x and y inputs. I basically expanded brackets, a lot. It makes it easier for you to paste it into notepad and change 'sx' for your x argument / variable name and 'sy' to your y argument / variable name.
`// spiral_get_value(x,y);
sx = argument0;
sy = argument1;
value = ((((sx==max(sqrt(sqr(sx)),sqrt(sqr(sy))) and sy !=(-1*max(sqrt(sqr(sx)),sqrt(sqr(sy))))))*((max(sqrt(sqr(sx)),sqrt(sqr(sy))))*2))+(((sy==max(sqrt(sqr(sx)),sqrt(sqr(sy))) and sx !=max(sqrt(sqr(sx)),sqrt(sqr(sy)))))*((max(sqrt(sqr(sx)),sqrt(sqr(sy))))*4))+(((sx==(-1*max(sqrt(sqr(sx)),sqrt(sqr(sy)))) and sy !=max(sqrt(sqr(sx)),sqrt(sqr(sy)))))*((max(sqrt(sqr(sx)),sqrt(sqr(sy))))*6))+((((sy==(-1*max(sqrt(sqr(sx)),sqrt(sqr(sy)))) and sx !=(-1*max(sqrt(sqr(sx)),sqrt(sqr(sy))))))*sx)+(((sy==max(sqrt(sqr(sx)),sqrt(sqr(sy))) and sx !=max(sqrt(sqr(sx)),sqrt(sqr(sy)))))*-sx))+(((sx==max(sqrt(sqr(sx)),sqrt(sqr(sy))) and sy !=(-1*max(sqrt(sqr(sx)),sqrt(sqr(sy))))))*sy)+(((sx==(-1*max(sqrt(sqr(sx)),sqrt(sqr(sy)))) and sy !=max(sqrt(sqr(sx)),sqrt(sqr(sy)))))*-sy))+sqr(((max(sqrt(sqr(sx)),sqrt(sqr(sy)))*2)+1)-2)+max(sqrt(sqr(sx)),sqrt(sqr(sy)));
return(value);`
I know the reply is awfully late :D but i hope it helps future visitors.
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Here's an interesting problem to solve in minimal amounts of code. I expect the recursive solutions will be most popular.
We have a maze that's defined as a map of characters, where = is a wall, a space is a path, + is your starting point, and # is your ending point. An incredibly simple example is like so:
====
+ =
= ==
= #
====
Can you write a program to find the shortest path to solve a maze in this style, in as little code as possible?
Bonus points if it works for all maze inputs, such as those with a path that crosses over itself or with huge numbers of branches. The program should be able to work for large mazes (say, 1024x1024 - 1 MB), and how you pass the maze to the program is not important.
The "player" may move diagonally. The input maze will never have a diagonal passage, so your base set of movements will be up, down, left, right. A diagonal movement would be merely looking ahead a little to determine if a up/down and left/right could be merged.
Output must be the maze itself with the shortest path highlighted using the asterisk character (*).
Works for any (fixed-size) maze with a minimum of CPU cycles (given a big enough BFG2000). Source size is irrelevant since the compiler is incredibly efficient.
while curr.x != target.x and curr.y != target.y:
case:
target.x > curr.x : dx = 1
target.x < curr.x : dx = -1
else : dx = 0
case:
target.y > curr.y : dy = 1
target.y < curr.y : dy = -1
else : dy = 0
if cell[curr.x+dx,curr.y+dy] == wall:
destroy cell[curr.x+dx,curr.y+dy] with patented BFG2000 gun.
curr.x += dx
curr.y += dy
survey shattered landscape
F#, not very short (72 non-blank lines), but readable. I changed/honed the spec a bit; I assume the original maze is a rectangle fully surrounded by walls, I use different characters (that don't hurt my eyes), I only allow orthogonal moves (not diagonal). I only tried one sample maze. Except for a bug about flipping x and y indicies, this worked the first time, so I expect it is right (I've done nothing to validate it other than eyeball the solution on the one sample I gave it).
open System
[<Literal>]
let WALL = '#'
[<Literal>]
let OPEN = ' '
[<Literal>]
let START = '^'
[<Literal>]
let END = '$'
[<Literal>]
let WALK = '.'
let sampleMaze = #"###############
# # # #
# ^# # # ### #
# # # # # # #
# # # #
############ #
# $ #
###############"
let lines = sampleMaze.Split([|'\r';'\n'|], StringSplitOptions.RemoveEmptyEntries)
let width = lines |> Array.map (fun l -> l.Length) |> Array.max
let height = lines.Length
type BestInfo = (int * int) list * int // path to here, num steps
let bestPathToHere : BestInfo option [,] = Array2D.create width height None
let mutable startX = 0
let mutable startY = 0
for x in 0..width-1 do
for y in 0..height-1 do
if lines.[y].[x] = START then
startX <- x
startY <- y
bestPathToHere.[startX,startY] <- Some([],0)
let q = new System.Collections.Generic.Queue<_>()
q.Enqueue((startX,startY))
let StepTo newX newY (path,count) =
match lines.[newY].[newX] with
| WALL -> ()
| OPEN | START | END ->
match bestPathToHere.[newX,newY] with
| None ->
bestPathToHere.[newX,newY] <- Some((newX,newY)::path,count+1)
q.Enqueue((newX,newY))
| Some(_,oldCount) when oldCount > count+1 ->
bestPathToHere.[newX,newY] <- Some((newX,newY)::path,count+1)
q.Enqueue((newX,newY))
| _ -> ()
| c -> failwith "unexpected maze char: '%c'" c
while not(q.Count = 0) do
let x,y = q.Dequeue()
let (Some(path,count)) = bestPathToHere.[x,y]
StepTo (x+1) (y) (path,count)
StepTo (x) (y+1) (path,count)
StepTo (x-1) (y) (path,count)
StepTo (x) (y-1) (path,count)
let mutable endX = 0
let mutable endY = 0
for x in 0..width-1 do
for y in 0..height-1 do
if lines.[y].[x] = END then
endX <- x
endY <- y
printfn "Original maze:"
printfn "%s" sampleMaze
let bestPath, bestCount = bestPathToHere.[endX,endY].Value
printfn "The best path takes %d steps." bestCount
let resultMaze = Array2D.init width height (fun x y -> lines.[y].[x])
bestPath |> List.tl |> List.iter (fun (x,y) -> resultMaze.[x,y] <- WALK)
for y in 0..height-1 do
for x in 0..width-1 do
printf "%c" resultMaze.[x,y]
printfn ""
//Output:
//Original maze:
//###############
//# # # #
//# ^# # # ### #
//# # # # # # #
//# # # #
//############ #
//# $ #
//###############
//The best path takes 27 steps.
//###############
//# # #....... #
//# ^# #.# ###. #
//# .# #.# # #. #
//# .....# #. #
//############. #
//# $....... #
//###############
Python
387 Characters
Takes input from stdin.
import sys
m,n,p=sys.stdin.readlines(),[],'+'
R=lambda m:[r.replace(p,'*')for r in m]
while'#'in`m`:n+=[R(m)[:r]+[R(m)[r][:c]+p+R(m)[r][c+1:]]+R(m)[r+1:]for r,c in[(r,c)for r,c in[map(sum,zip((m.index(filter(lambda i:p in i,m)[0]),[w.find(p)for w in m if p in w][0]),P))for P in zip((-1,0,1,0),(0,1,0,-1))]if 0<=r<len(m)and 0<=c<len(m[0])and m[r][c]in'# ']];m=n.pop(0)
print''.join(R(m))
I did this sort of thing for a job interview once (it was a pre-interview programming challenge)
Managed to get it working to some degree of success and it's a fun little challenge.