Assume that I have a vector with 6 distance elements as
D = [10.5 44.8 30.01 37.2 23.4 49.1].
I'm trying to create random pair positions of a given distances, inside a 200 meters circle. Note that the distance D created by using (b - a).*rand(6,1) + a, with a = 10 and b = 50 in Matlab. I do not know how to generate the random pairs with given the distances.
Could anybody help me in generating this kind of scenario?
This is an improvement to Alessiox's answer. It follows same logic, first generate a set of points ([X1 Y1]) that have at least distance D from the main circle border, then generate the second set of points ([X2 Y2]) that have exact distance D from the first set.
cx = 50; cy = -50; cr = 200;
D = [10.5 44.8 30.01 37.2 23.4 49.1]';
n = numel(D);
R1 = rand(n, 1) .* (cr - D);
T1 = rand(n, 1) * 2 * pi;
X1 = cx+R1.*cos(T1);
Y1 = cy+R1.*sin(T1);
T2 = rand(n, 1) * 2 * pi;
X2 = X1+D.*cos(T2);
Y2 = Y1+D.*sin(T2);
You can tackle the problem using a two-steps approach. You can
randomly generate the first point and then you can consider the circle whose center is that point and whose radius is the distance in D
once you did draw the circle, every point lying on that circle will have distance D from the first point previously created and by random selection of one of these candidates you'll have the second point
Let's see with an example: let's say you main circle has radius 200 and its center is (0,0) so we start by declaring some main variables.
MAINCENTER_x=0;
MAINCENTER_y=0;
MAINRADIUS=200;
Let's now consider the first distance, D(1)=10.5 and we now generate the first random point which (along with its paired point - I reckon you don't want one point inside and the other outside of the main circle) must lie inside the main circle
r=D(1); % let's concentrate on the first distance
while true
x=((MAINRADIUS-2*r) - (-MAINRADIUS+2*r))*rand(1,1) + (-MAINRADIUS+2*r);
y=((MAINRADIUS-2*r) - (-MAINRADIUS+2*r))*rand(1,1) + (-MAINRADIUS+2*r);
if x^2+y^2<=(MAINRADIUS-2*r)^2
break;
end
end
and at the end of this loop x and y will be our first point coordinates.
Now we shall generate all its neighbours, thus several candidates to be the second point in the pair. As said before, these candidates will be the points that lie on the circle whose center is (x,y) and whose radius is D(1)=10.5. We can create these candidates as follows:
% declare angular spacing
ang=0:0.01:2*pi;
% build neighbour points
xp=r*cos(ang)+x;
yp=r*sin(ang)+y;
Now xp and yp are two vectors that contain, respectively, the x-coordinates and y-coordinates of our candidates, thus we shall now randomly select one of these
% second point
idx=randsample(1:length(xp),1);
secondPoint_x=xp(idx);
secondPoint_y=yp(idx);
Finally, the pair (x,y) is the first point and the pair (secondPoint_x, secondPoint_y) is our second point. The following plot helps summarizing these steps:
The red circle is the main area (center in (0,0) and radius 200), the red asterisk is the first point (x,y) the blue little circle has center (x,y) and radius 10.5 and finally the black asterisk is the second point of the pair (secondPoint_x, secondPoint_y), randomly extracted amongst the candidates lying on the blue little circle.
You must certainly can repeat the same process for all elements in D or rely on the following code, which does the very same thing without iterating through all the elements in D.
MAINCENTER_x=0;
MAINCENTER_y=0;
MAINRADIUS=200;
D = [10.5 44.8 30.01 37.2 23.4 49.1];
% generate random point coordinates
while true
x=((MAINRADIUS-2*D) - (-MAINRADIUS+2*D)).*rand(1,6) + (-MAINRADIUS+2*D);
y=((MAINRADIUS-2*D) - (-MAINRADIUS+2*D)).*rand(1,6) + (-MAINRADIUS+2*D);
if all(x.^2+y.^2<=(MAINRADIUS-2*D).^2)
break;
end
end
% declare angular spacing
ang=0:0.01:2*pi;
% build neighbour points
xp=bsxfun(#plus, (D'*cos(ang)),x');
yp=bsxfun(#plus, (D'*sin(ang)),y');
% second points
idx=randsample(1:size(xp,2),length(D));
secondPoint_x=diag(xp(1:length(D),idx));
secondPoint_y=diag(yp(1:length(D),idx));
%plot
figure(1);
plot(MAINRADIUS*cos(ang)+MAINCENTER_x,MAINRADIUS*sin(ang)+MAINCENTER_y,'r'); %main circle
hold on; plot(xp',yp'); % neighbours circles
hold on; plot(x,y,'r*'); % first points (red asterisks)
hold on; plot(secondPoint_x,secondPoint_y,'k*'); %second points (black asterisks)
axis equal;
Now x and y (and secondPoint_x and secondPoint_y by extension) will be vector of length 6 (because 6 are the distances) in which the i-th element is the i-th x (or y) component for the first (or second) point.
Related
I want N points on a circle, set apart by a Euclidean distance (straight line, not around the circumference) of 50. The radius is determined by the number of points and the distance between consecutive points.
However, when I choose one of the points as a reference and calculate the distances to other points, I do not get any distance values equal to 50.
Below is my code:
N = 100; % number of points
eclddst = 50; % euclidean distance between adjacent points
r = eclddst/(2*sin(pi/N)); % radius of the circle
cord = r*exp((0:1/(N-1):1)*pi*2*1i)'; % coordinates
XCor = real(cord);
YCor = imag(cord);
N_COORD = [XCor YCor];
% taking location 3 as the reference point to check the distance between the points
DSTNT = sqrt( (N_COORD(3,1)-N_COORD(:,1)).^2 + ( N_COORD(3,2)- N_COORD(:,2)).^2)';
The distance values around the third point which I obtain are:
100.959
50.505
0.000
50.505
100.959
151.311
The points adjacent to point 3 should have 50 as their distance value and not 50.505.
Why do I get this error?
Thanks in advance.
Your issue is in the number of points which your formula generates, because of a misleading statement at the link you were following. Note that it was stated:
r = A*exp((0:1/300:1)*pi*2j); % 300 point circle, radius A
However, this will give 301 points not 300. If you plotted this though, you would see only 300 points (much easier to see if you use, say, 4 points). The first and last points are identical since
exp(0*pi*2j) = exp(1*pi*2j) = 1
To get around this, the simplest options are to change 0:1/300:1 to not reach 1, or simply create and remove an extra point as shown here:
N = 100; % number of points
d = 50; % Euclidean distance between adjacent points
% Euclidean distance around circle is essentially side length of N-sided polygon.
% Triangular sector angle within polygon (rads): 2*pi/N
% By bisecting the triangle to get a right-triangle, we can deduce that
% sin((2*pi/N)/2) = (d/2)/r => r = (d/2)/sin(pi/N)
r = (d/2)/sin(pi/N);
% Use linspace as it's clearer than colon array, create N+1 points
% Note that point 1 and point N+1 will be identical!
complexcoords = r*exp(linspace(0,1,N+1)*pi*2*1i).';
% Remove the last point as you put it in an array
coords = [real(complexcoords(1:N)) imag(complexcoords(1:N))];
As a check:
% Euclidean distances from point 3
dists = sqrt((coords(3,1)-coords(:,1)).^2 + (coords(3,2)-coords(:,2)).^2);
dists(1:5)
>> 99.951
50 % Neighbouring points are distance 50!
0
50 % Ditto
99.951
Note that you should be careful using '. This is the complex conjugate transpose, meaning that x + yi becomes x - yi. You won't notice this on a circle centred around 0 and an even number of points, but when you want to transpose something in MATLAB always use .', otherwise you may get some hard to diagnose issues! I have corrected this in my above code.
Doc links: ctranspose/', transpose/.'.
I'm trying to fill the intersecting area between two circles in Matlab. I've quite literally copied and pasted this piece of code from this article on Matlab Central.
t = linspace(0, 2*pi, 100);
cir = #(r,ctr) [r*cos(t)+ctr(1); r*sin(t)+ctr(2)]; % Circle Function
c1 = cir(1.0, [0; 0]);
c2 = cir(1.5, [1; 1]);
in1 = find(inpolygon(c1(1,:), c1(2,:), c2(1,:), c2(2,:))); % Circle #1 Points Inside Circle #2
in2 = find(inpolygon(c2(1,:), c2(2,:), c1(1,:), c1(2,:))); % Circle #2 Points Inside Circle #1
[fillx,ix] = sort([c1(1,in1) c2(1,in2)]); % Sort Points
filly = [c1(2,in1) (c2(2,in2))];
filly = filly(ix);
figure(1)
plot(c1(1,:), c1(2,:))
hold on
plot(c2(1,:), c2(2,:))
fill([fillx fliplr(fillx)], [filly fliplr(filly)], 'g', 'EdgeColor','none')
hold off
axis square
What I end up with is the following image:
However, it should appear as this image:
Why is the area not being filled as it is in the example article?
If you have Mapping Toolbox you can use polybool to find the intersection between to polygones, and than patch (which dosen't require Mapping Toolbox, and is better than fill) to draw it. The folowing code works even without the first 2 lines that use poly2cw, but it issues some warnings. This can be solved with the poly2cw trasfomation:
[c1(1,:), c1(2,:)] = poly2cw(c1(1,:), c1(2,:)); % clock-wise transform
[c2(1,:), c2(2,:)] = poly2cw(c2(1,:), c2(2,:)); % clock-wise transform
[xb, yb] = polybool('intersection',c1(1,:),c1(2,:),c2(1,:), c2(2,:));
plot(c1(1,:), c1(2,:))
hold on
plot(c2(1,:), c2(2,:))
patch(xb, yb, 1, 'FaceColor', 'g','EdgeColor','none')
axis equal
The code in the question does not work because it has some mistake in the order of the points in fillx and filly. We can see that if we set the 'EdgeColor' to be visible, and follow the peripheral line of the patch (see below, here reduced to 20 points, for the illustration). We can clearly see that the point of the polygon to be filled are ordered in a 'zig-zag' between the circles, so it has no area at all. I have numbered the vertices of the polygon taken from each circle to demonstrate in what order the fill function read them.
In order to fill with color all the intersection between the circles, we need to define the 'polygon' by the points on the circles that intersect (in1 and in2) in the right order. This means we want them to make a closed shape if an imaginary pencil is drawing a line between them in the same order they are given. Like this:
We start with 1 in one of the circles and continue until the numbers on that circle are ended, and then move to 1 on the other circle, and when we reach the end in the second circle we close the polygon by connecting the last point to the first one. As you can see in both figure above, the starting point and the end point of the circles are really close, so we get 2 numbers above each other.
How can we order the points correctly?
We start by getting in1 and in2 as described in the question. Let's take a look at in1:
in1 =
1 2 3 4 5 6 7 19 20
Those are the indices of the points from c1 to be taken, they appear to be in order, but contains a gap. This gap is because inpolygon checks the points by the order in c1, and the starting point of c1 is within the intersection region. So we get the first 7 points, then we are out of the intersection, and we go back in as we reach points 19 and 20. However, for our polygon, we need this points to start from the closest point to one of that places where the circle intersect and to go around the circle until we reach the second point of intersection.
To do that, we look for the 'gap' in the points order:
gap = find(diff(in1)>1);
and reorder them correctly:
X1 = [c1(1,in1(gap+1:end)) c1(1,in1(1:gap))];
Y1 = [c1(2,in1(gap+1:end)) c1(2,in1(1:gap))];
But, there may be no 'gap', as we see in in2:
in2 =
11 12 13 14
So we need to wrap this within an if to check if the points need to be reordered:
if ~isempty(gap)
X1 = [c1(1,in1(gap+1:end)) c1(1,in1(1:gap))];
Y1 = [c1(2,in1(gap+1:end)) c1(2,in1(1:gap))];
else
X1 = c1(1,in1);
Y1 = c1(2,in1);
end
Now all we need to do it to concatenate X1 and X2 (for circle 2), and the same for the Ys, and use patch (which is like fill, but better) to draw it:
patch([X1 X2],[Y1 Y2],'g','EdgeColor','none')
With 20 points the circle is not really a circle and the intersection is partially colored, so here is the full code and the result with 200 points:
t = linspace(0, 2*pi, 200);
cir = #(r,ctr) [r*cos(t)+ctr(1); r*sin(t)+ctr(2)]; % Circle Function
c1 = cir(1.0, [0; 0]);
c2 = cir(1.5, [1; 1]);
plot(c1(1,:), c1(2,:))
hold on
plot(c2(1,:), c2(2,:))
axis equal
in1 = find(inpolygon(c1(1,:), c1(2,:), c2(1,:), c2(2,:)));
in2 = find(inpolygon(c2(1,:), c2(2,:), c1(1,:), c1(2,:)));
gap = find(diff(in1)>1);
if ~isempty(gap)
X1 = [c1(1,in1(gap+1:end)) c1(1,in1(1:gap))];
Y1 = [c1(2,in1(gap+1:end)) c1(2,in1(1:gap))];
else
X1 = c1(1,in1);
Y1 = c1(2,in1);
end
gap = find(diff(in2)>1);
if ~isempty(gap)
X2 = [c2(1,in2(gap+1:end)) c2(1,in2(1:gap))];
Y2 = [c2(2,in2(gap+1:end)) c2(2,in2(1:gap))];
else
X2 = c2(1,in2);
Y2 = c2(2,in2);
end
patch([X1 X2],[Y1 Y2],'g','EdgeColor','none')
hold off
All mentioned above could be replace with the use of convhull on the vertices that intersect and give the same result:
x = [c1(1,in1) c2(1,in2)]; % all x's for intersecting vertices
y = [c1(2,in1) c2(2,in2)]; % all y's for intersecting vertices
k = convhull(x,y); % calculate the convex polygon
patch(x(k),y(k),'g','EdgeColor','none')
I'm trying to calculate the mean value of the pixels inside a circle. In the future this needs to be extended to 3D, but for now a 2D sollution would already help me out.
As can be seen in the image, some pixels are entirely inside the circle, but some are only partly inside the circle. The ones partly in the circle also need to contribute only partly to the mean value. The pixels are square. This will simplify the mathematics I hope.
I can calculate the distance from the pixelcorners to the central point, from this you can find the pixels enterly inside and enterly outside. The rest needs correction. But how to find this correction.
[edit] thanks to Heath Raftery the problem is solved! [/edit]
the integral of a circle with radius r
As an example: I want to know the average pixelvalue of pixels in this circle. I know it is 0.3425, since 34.25% of the circle has a value of 1 and the rest is 0.
Function to check what part of a pixel is in the circle:
function [ a ] = incirc( x,y,r )
%only handles the top right quadrant of a circle
if x<0||y<0,error('only positive x,y');end
%integral of sqrt(r^2-x^2) dx
F = #(x,r) (1/2)*(x*sqrt(r^2-x^2)+r^2*atan(x/sqrt(r^2-x^2)));
%find corner locations
x=[x-0.5,x+0.5];
y=[y-0.5,y+0.5];
d = sqrt(x.^2+y.^2); %distance to closed and furthest corner
if max(d)<r,a=1;return;end %inside circle
if min(d)>r,a=0;return;end %outside circle
%intersections with edges (r^2 = x^2+y^2)
inters = [sqrt(r^2-y(1)^2),sqrt(r^2-y(2)^2),sqrt(r^2-x(1)^2),sqrt(r^2-x(2)^2)]; %x(1) x(2) y(1) y(2)
%remove imaginary and out of range intersections
inters(imag(inters)~=0)=NaN;
inters(inters<1E-5)=NaN; %to find values that are zero
inters([~((x(1)<inters(1:2))&(inters(1:2)<x(2))),~((y(1)<inters(3:4))&(inters(3:4)<y(2)))])=NaN;
idx = find(~isnan(inters));
if numel(idx)~=2,error('need two intersections of circle with pixel');end
%check area of pixel inside circumference
if all(idx==[1,2]) %2 intersections on y-edge
a=(F(y(2),r)-F(y(1),r)) - x(1); %area
elseif all(idx==[3,4]) %2 intersections on x-edge
a=(F(x(2),r)-F(x(1),r)) - y(1); %area
elseif all(idx==[1,3]) %one intersection on y-edge one on x-edge (left&bottom)
a=(F(inters(1),r)-F(x(1),r))- (y(1)*(inters(1)-x(1)));
elseif all(idx==[2,4]) %one intersection on y-edge one on x-edge (top&right)
a=(inters(2)-x(1))+(F(x(2),r)-F(inters(2),r))-(y(1)*(x(2)-inters(2)));
else
error('geometry')
end
a=real(a);
if a<0||a>1
error('computational error');
end
end
Script to test the function
M = ones(100); %data
M(1:50,:)=0;
pos=[50.2,50];
r = 2;
%calculate what the result should be
h=50-pos(2)+0.5;
A=pi*r^2;
wedge = acos(h/r)/pi;
triangle = h*sqrt(r^2-h^2);
res=(A*wedge-triangle)/A
S=0;N=0;
for i = 1:size(M,1)
for j = 1:size(M,2)
x=abs(j-pos(1));
y=abs(i-pos(2));
n=incirc( x,y,r );
M_(i,j)=n;
S = S+M(i,j)*n;
N = N+n;
end
end
result = S/N
result = 0.3425
You can see the algorithm finds the part of the pixel in the circle.
The question is missing a question, but I'll assume that it's not how to calculate whether pixels are fully inside or outside the circle. That's a relatively simple task. That is, a pixel is fully inside if the furtherest corner of the pixel to the centre is less than a radius away from the centre, and a pixel is fully outside if the closest corner of the pixel to the centre is more than a radius away from the centre.
The question of what proportion of pixels on the circumference fall within the circumference is much trickier. There are two fundamental solutions:
Exact and hard.
Approximate and a bit easier.
In both cases, note the horizontal and vertical symmetry means only the top right quadrant need be considered.
Then, for (1), translate the circle centre to the origin (0, 0) and treat the circumference as the function y(x) = sqrt(r^2 - x^2). Then, the area of an overlapping pixel within the circle is the integral:
integral(y(x) - y0, from x0 to x1, with respect to x)
where y0 is the bottom coordinate of the pixel, x0 is the left coordinate and x1 is the right coordinate.
This integral can be solved exactly with a trigonometric identity and a trigonometric substitution.
For (2), just generate a set of random points within the pixel and count how many of them fall within the circumference. As the set gets larger, the proportion of points that fall within the circumference to the count of all point approaches the proportion of the pixel within the circumference.
You can use inpolygon, to get the indices which lie inside the circle, once you have those indices you can get your pixels and do what you want.
M = rand(100); %data
[nx,ny] = size(M) ;
[X,Y] = meshgrid(1:ny,1:nx) ;
pos=[20,20];
r = 5;
phi=linspace(0,2*pi,100);
imagesc(M);
axis image
hold on
plot(pos(1),pos(2),'rx')
xc = pos(1)+r*sin(phi) ;
yc = pos(2)+r*cos(phi) ;
plot(xc,yc,'-r');
% hold off
%% get indices which are inside the circle
idx = inpolygon(X(:),Y(:),xc,yc) ;
xi = X(idx) ; yi = Y(idx) ;
plot(xi,yi,'.r')
mypixels = M(idx) ;
You can also use rangesearch to get the points lying within the given radius of the circle. As below:
M = rand(100); %data
[nx,ny] = size(M) ;
[X,Y] = meshgrid(1:ny,1:nx) ;
pos=[20,20];
r = 5;
phi=linspace(0,2*pi,100);
imagesc(M);
axis image
hold on
plot(pos(1),pos(2),'rx')
xc = pos(1)+r*sin(phi) ;
yc = pos(2)+r*cos(phi) ;
plot(xc,yc,'-r');
% hold off
%% Use nearest neighbour search
idx = rangesearch([X(:),Y(:)],pos,r) ;
xi = X(idx{1}) ; yi = Y(idx{1}) ;
plot(xi,yi,'.r')
mypixels = M(idx{1}) ;
I have a binary image of a human. In MATLAB, boundary points and the center of the image are also defined, and they are two column matrices. Now I want to draw lines from the center to the boundary points so that I can obtain all points of intersection between these lines and the boundary of the image. How can I do that? Here is the code I have so far:
The code that is written just to get the one intersection point if anyone can help please
clear all
close all
clc
BW = im2bw(imread('C:\fyc-90_1-100.png'));
BW = imfill(BW,'holes');
[Bw m n]=preprocess(BW);
[bord sk pr_sk]=border_skeleton(BW);
boundry=bord;
L = bwlabel(BW);
s = regionprops(L, 'centroid');
centroids = cat(1, s.Centroid);
Step #1 - Generating your line
The first thing you need to do is figure out how to draw your line. To make this simple, let's assume that the centre of the human body is stored as an array of cen = [x1 y1] as you have said. Now, supposing you click anywhere in your image, you get another point linePt = [x2 y2]. Let's assume that both the x and y co-ordinates are the horizontal and vertical components respectively. We can find the slope and intercept of this line, then create points between these two points parameterized by the slope and intercept to generate your line points. One thing I will point out is that if we draw a slope with a vertical line, by definition the slope would be infinity. As such, we need to place in a check to see if we have this situation. If we do, we assume that all of the x points are the same, while y varies. Once you have your slope and intercept, simply create points in between the line. You'll have to choose how many points you want along this line yourself as I have no idea about the resolution of your image, nor how big you want the line to be. We will then store this into a variable called linePoints where the first column consists of x values and the second column consists of y values. In other words:
In other words, do this:
%// Define number of points
numPoints = 1000;
%// Recall the equation of the line: y = mx + b, m = (y2-y1)/(x2-x1)
if abs(cen(1) - linePt(1)) < 0.00001 %// If x points are close
yPts = linspace(cen(2), linePt(2), numPoints); %// y points are the ones that vary
xPts = cen(1)*ones(numPoints, 1); %//Make x points the same to make vertical line
else %// Normal case
slp = (cen(2) - linePt(2)) / cen(1) - linePt(1)); %// Solve for slope (m)
icept = cen(2) - slp*cen(1); %// Solve for intercept (b)
xPts = linspace(cen(1), linePt(1), numPoints); %// Vary the x points
yPts = slp*xPts + icept; %// Solve for the y points
end
linePoints = [xPts(:) yPts(:)]; %// Create point matrix
Step #2 - Finding points of intersection
Supposing you have a 2D array of points [x y] where x denotes the horizontal co-ordinates and y denotes the vertical co-ordinates of your line. We can simply find the distance between all of these points in your boundary with all of your points on the line. Should any of the points be under a certain threshold (like 0.0001 for example), then this indicates an intersection. Note that due to the crux of floating point data, we can't check to see if the distance is 0 due to the step size in between each discrete point in your data.
I'm also going to assume border_skeleton returns points of the same format. This method works without specifying what the centroid is. As such, I don't need to use the centroids in the method I'm proposing. Also, I'm going to assume that your line points are stored in a matrix called linePoints that is of the same type that I just talked about.
In other words, do this:
numBoundaryPoints = size(boundry, 1); %// boundary is misspelled in your code BTW
ptsIntersect = []; %// Store points of intersection here
for idx = 1 : numBoundaryPoints %// For each boundary point...
%//Obtain the i'th boundary point
pt = boundry(:,idx);
%//Get distances - This computes the Euclidean distance
%//between the i'th boundary point and all points along your line
dists = sqrt(sum(bsxfun(#minus, linePoints, pt).^2, 2));
%//Figure out which points intersect and store
ptsIntersect = [ptsIntersect; linePoints(dists < 0.0001, :)];
end
In the end, ptsIntersect will store all of the points along the boundary that intersect with this line. Take note that I have made a lot of assumptions here because you haven't (or seem reluctant to) give any more details than what you've specified in your comments.
Good luck.
If I have points in a graph in matlab that are randomly sorted and when plotted produce various closed shapes. Given a specific point on the left side of one of the closed shapes how can I get all the points of that shape in a vector form keeping in mind the convention of collecting the points is moving in a clockwise direction.
A commented example:
cla
% Random data
x = rand(15,1);
y = rand(15,1);
scatter(x,y)
% Random point to the left
hold on
p = [-0.1, rand(1)*0.2 + 0.5];
plot(p(1),p(2),'*r')
% Separate points that lie above your point
idx = y >= p(2);
% Sort x then y increasing for upper half and x then y decreasing for lower half
shape = [sortrows([x( idx) y( idx)],[1 2])
sortrows([x(~idx) y(~idx)],[-1 -2])];
Check that shape contains clockwise sorted coordinates by plotting an open line:
% Plot clockwise open line
plot(shape(1:end ,1),shape(1:end,2),'k')