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Hi,

I created a cross section by using kmeans function from two different data (indicated by X and * in image),

My aim is to determine the distance difference of two data from center (o) of cross section,

Briefly i try to find the;

Distance between O and X (d1)

Than i need to find the nearest * to X,

Than calculate the distance between O and * (which is nearest X) (d2)

And lastly i need to calculate the difference between (d1) and (d2)

And i want to do this calculations for all X to * in cross-section.

Thank you...

My current code is given below: my points are represented by m,n and o in code...

clc;clear;

x=xlsread('king1.xlsx', 'A:A');

y=xlsread('king1.xlsx', 'B:B');

z=xlsread('king1.xlsx', 'C:C');

a=xlsread('king2.xlsx', 'A:A');

b=xlsread('king2.xlsx', 'B:B');

c=xlsread('king2.xlsx', 'C:C');

xyz=[x y z];

abc=[a b c];

rng(1);

[idx1,C1] = kmeans(xyz,100,'distance','sqEuclidean','MaxIter',500, 'Replicates', 10);

[idx2,C2] = kmeans(abc,100,'distance','sqEuclidean','MaxIter',500, 'Replicates', 10);

[dist,idx3] = pdist2(xyz, C1, 'euclidean', 'Smallest',1);

newVar = xyz(idx3 ,:);

plot3(newVar(:,1), newVar(:,2), newVar(:,3), 'bx');

hold on;

xlabel ('x - axis', 'fontsize', 12);

ylabel ('y - axis', 'fontsize', 12);

zlabel ('z - axis', 'fontsize', 12);

grid

[dist2,idx4] = pdist2(abc, C2, 'euclidean', 'Smallest',1);

newVar2 = abc(idx4 ,:);

plot3(newVar2(:,1), newVar2(:,2), newVar2(:,3), 'r*')

newVar3 = mean (newVar)

newVar4 = mean (newVar2)

newVar5 = (newVar3 + newVar4)/ 2

plot3(newVar5(:,1), newVar5(:,2), newVar5(:,3), 'go');

m=[newVar(:,1) newVar(:,2) newVar(:,3)];

n=[newVar2(:,1) newVar2(:,2) newVar2(:,3)];

o=[newVar5(:,1) newVar5(:,2) newVar5(:,3)];

darova
on 28 May 2019

I did this

xyz0 = (mean(xyz)+mean(abc))/2; % O point

XYZ0 = repmat(xyz0,size(xyz,1),1); % duplicate rows

d1 = XYZ0 - xyz; % Distance(s) between O and X (d1)

% find the nearest * to X

D = pdist2(xyz,abc); % every possible combinations

D(D==0) = max(D(:)); % fill zeros with max ( (:) - convert matrix to column vector )

[~,ind] = min(D(:)); % find index of min element

% Found index of min element in vector. Find correspoding indices of points

[i,j] = ind2sub(size(D),ind); % extract row and column (i - index of xyz, j - index of abc)

% calculate the distance between O and * (which is nearest X) (d2)

d2 = xyz0 - abc(j,:); % difference between O point and * (nearest X)

D2 = repmat(d2,size(d2,1),1); % duplicate rows

d = D2 - d1; % distance(s) between d2 and d1

e_oksum
on 29 May 2019

hi mehmet, here is an example code performing what you explained,

example uses random positions, you can adopt by yours..and also simplify it for more compact without plotting etc..

X=rand(1,10)*10 ;% your x position of X

Y=rand(1,10)*10 ;% your y position of X

xs=rand(1,10)*10 ;% your x position of *

ys=rand(1,10)*10 ;% your y position of *

xo=5 ;% center x

yo=5 ;% center y

plot(X,Y,'ro','markerfacecolor','r');

hold on

plot(xs,ys,'k+');

plot(xo,yo,'go','markerfacecolor','g');

for i=1:numel(X)

d1(i)=sqrt((X(i)-xo).^2+(Y(i)-yo).^2);% distance d1 of X(i) Y(i) to center

%find position of nearest xs,ys to X,Y

L=sqrt((xs-X(i)).^2 + (ys-Y(i)).^2);

idx=find(L==min(L));

xp(i)=xs(idx); %(xp yp are the nearest nearest X)

yp(i)=ys(idx);

d2(i)=sqrt((xp(i)-xo).^2 + (yp(i)-yo).^2); % distance d2 of nearest xp yp to X(i),Y(i)

diffd1d2(i)=(d1(i)-d2(i)); % diffrence between d1 d2

% check by plot

l1=plot([X(i) xo],[Y(i) yo],'-r'); % line d1

l2=plot([xp(i) xo],[yp(i) yo],'-k'); % line d2

pause(1)

delete(l1)

delete(l2)

end

list=[X' Y' xp' yp' d1' d2' diffd1d2']

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