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Can someone please please please remove the display part of this function?

It would be appreciated so so much!

clear;

close all;

clc;

xy = [

3 12

10 8

11 14

13 16

9 19

1 15

2 4

6 1

11 3

16 5

14 17

19 18

]

xy = xy'

yeet = convexhull(xy,0);

function k=convexhull(xy,display) ;

%CONVEXHULL Calculate convex hull

% CMP Vision Algorithms http://visionbook.felk.cvut.cz

%

% Find the convex hull of a set of N points in 2D

% : we implement

% Graham's classic scan algorithm

% which

% has optimal (N log N) complexity. The main data structure of

% Graham's scan is a stack, which can be emulated with reasonable

% efficiency in Matlab

% using arrays.

% Melkman's algorithm uses a double

% ended queue (deque) which is more difficult to implement

% efficiently.

%

% Convex hull construction is one of the fundamental computational geometry

% algorithms and we present it here for pedagogical reasons. The

% function convhull will work just as well.

%

% Usage: k = convexhull(xy,display)

% Inputs:

% xy [2 x N] Array with x,y coordinates of the N input

% points. Each column corresponds to one point.

% display (default 0) If set to 1, each iteration of the algorithm is

% illustrated graphically.

% Outputs:

% k [N x 1] A vector of indices to xy of the points

% on the convex hull.

% The first point is the point with the smallest x coordinate and we

% proceed clockwise. The last point is equal to the first point.

%

% We choose to keep collinear points on the resulting convex hull

% boundary, since it permits a slightly simpler implementation. Changes

% required to do otherwise are minor.

%

if nargin<2

display = 0;

end

% We find a pivot point first with the minimum x coordinate

% which is guaranteed

% to be part of the convex hull. (Note that this is only true if collinear

% points are included.)

[m,n] = size(xy);

if m~=2

error('convexhull: xy must have 2 columns');

end

[xmin,first] = min( xy(1,:) );

% We take the remaining points and sort them according to the direction (azimuth)

% from the pivot, creating an index array ind. This takes

% (Nlog N) time. We use function

% atan2 for convenience to calculate the angles. All angles are

% between -/2 and /2, so phase

% wraparound is not a problem. We add the pivot as

% the last point.

ind = [1:(first-1) (first+1):n];

angle = atan2( xy(1,ind)-xy(1,first), xy(2,ind)-xy(2,first) );

[junk,order] = sort(angle);

ind = [ind(order) first];

% A stack is emulated using an array stack and an index

% stacktop of the top stack element. Since we know the maximum

% stack size to be N, we initialize the stack array to avoid

% time consuming reallocations.

%

% The stack will contain indices of points that so far are considered to

% be part of the convex hull. The initial stack contains the pivot.

stack = zeros( n, 1, 'uint32' );

stack(1) = first;

stacktop = 1;

% Here is the main while-loop of the algorithm. The current

% point from the input set xy is indexed by ind(i).

% The loop terminates when all points have been considered.

%

% A current point p2=xy(:,ind(i)) is pushed to the stack if it

% contains less than two points, or if the point p2 lies on or to the right of the

% line connecting the two top points of the stack (p0, p1).

% This is determined by calculating the vector product of (p1-p0)

% x (p2-p0).

% Otherwise, the top

% point from the stack is discarded, because it cannot belong to the

% convex hull. In other words, the

% hull boundary must go straight or turn right, it may never turn to the left.

i = 1;

while i<=n

if display==1,

figure(1) ;

plot(xy(first,1),xy(first,2),'rx',[xy(first,1) ; xy(ind,1)],[xy(first,2) ...

; xy(ind,2)],'o--',xy(stack(1:stacktop),1),xy(stack(1:stacktop),2),'g-',xy(ind(i),1),xy(ind(i),2),'md','LineWidth',2,'MarkerSize',7) ;

disp([ 'Stack = ' num2str(stack(1:stacktop)') ]) ;

disp('Press any key') ;

pause

end ;

if stacktop<2

stacktop = stacktop+1;

stack(stacktop) = ind(i);

i = i+1;

else

p0 = xy(:,stack(stacktop));

p1 = xy(:,stack(stacktop-1));

p2 = xy(:,ind(i));

if (p1(1)-p0(1))*(p2(2)-p0(2))-(p2(1)-p0(1))*(p1(2)-p0(2)) >= 0

if display==1,

disp('push') ;

end ;

stacktop = stacktop+1;

stack(stacktop) = ind(i);

i = i+1;

else

if display==1,

disp('pop') ;

end ;

% pop

stacktop = stacktop-1;

end

end

end % while loop

if display,

figure(1) ;

plot([xy(1,first) xy(1,ind)],[xy(2,first) xy(2,ind)],'bo-',...

xy(1,first), xy(2,first),'ro','LineWidth',2,'MarkerSize',7) ;

if display>1,

exportfig(gcf,'output_images/convexhull_fan.eps') ;

end ;

figure(2) ;

plot(xy(1,:),xy(2,:),'bo',xy(1,stack(1:stacktop)),xy(2,stack(1:stacktop)),...

'g-',xy(1,first), xy(2,first),'ro','LineWidth',2,'MarkerSize',7) ;

if display>1,

exportfig(gcf,'output_images/convexhull_small.eps') ;

else

disp('Algorithm has converged.') ; disp('Press any key') ;

pause

end ;

end ;

% The stack now contains the completed convex hull. Because each input point

% is pushed to the stack and discarded at most once, the computational

% complexity of the while-loop is linear.

k = stack(1:stacktop);

end

JESUS DAVID ARIZA ROYETH
on 4 Dec 2019

clear;

close all;

clc;

xy = [

3 12

10 8

11 14

13 16

9 19

1 15

2 4

6 1

11 3

16 5

14 17

19 18

];

xy = xy';

yeet = convexhull(xy)

function k=convexhull(xy)

%CONVEXHULL Calculate convex hull

% CMP Vision Algorithms http://visionbook.felk.cvut.cz

%

% Find the convex hull of a set of N points in 2D

% : we implement

% Graham's classic scan algorithm

% which

% has optimal (N log N) complexity. The main data structure of

% Graham's scan is a stack, which can be emulated with reasonable

% efficiency in Matlab

% using arrays.

% Melkman's algorithm uses a double

% ended queue (deque) which is more difficult to implement

% efficiently.

%

% Convex hull construction is one of the fundamental computational geometry

% algorithms and we present it here for pedagogical reasons. The

% function convhull will work just as well.

%

% Usage: k = convexhull(xy,display)

% Inputs:

% xy [2 x N] Array with x,y coordinates of the N input

% points. Each column corresponds to one point.

% display (default 0) If set to 1, each iteration of the algorithm is

% illustrated graphically.

% Outputs:

% k [N x 1] A vector of indices to xy of the points

% on the convex hull.

% The first point is the point with the smallest x coordinate and we

% proceed clockwise. The last point is equal to the first point.

%

% We choose to keep collinear points on the resulting convex hull

% boundary, since it permits a slightly simpler implementation. Changes

% required to do otherwise are minor.

%

% We find a pivot point first with the minimum x coordinate

% which is guaranteed

% to be part of the convex hull. (Note that this is only true if collinear

% points are included.)

[m,n] = size(xy);

if m~=2

error('convexhull: xy must have 2 columns');

end

[xmin,first] = min( xy(1,:) );

% We take the remaining points and sort them according to the direction (azimuth)

% from the pivot, creating an index array ind. This takes

% (Nlog N) time. We use function

% atan2 for convenience to calculate the angles. All angles are

% between -/2 and /2, so phase

% wraparound is not a problem. We add the pivot as

% the last point.

ind = [1:(first-1) (first+1):n];

angle = atan2( xy(1,ind)-xy(1,first), xy(2,ind)-xy(2,first) );

[junk,order] = sort(angle);

ind = [ind(order) first];

% A stack is emulated using an array stack and an index

% stacktop of the top stack element. Since we know the maximum

% stack size to be N, we initialize the stack array to avoid

% time consuming reallocations.

%

% The stack will contain indices of points that so far are considered to

% be part of the convex hull. The initial stack contains the pivot.

stack = zeros( n, 1, 'uint32' );

stack(1) = first;

stacktop = 1;

% Here is the main while-loop of the algorithm. The current

% point from the input set xy is indexed by ind(i).

% The loop terminates when all points have been considered.

%

% A current point p2=xy(:,ind(i)) is pushed to the stack if it

% contains less than two points, or if the point p2 lies on or to the right of the

% line connecting the two top points of the stack (p0, p1).

% This is determined by calculating the vector product of (p1-p0)

% x (p2-p0).

% Otherwise, the top

% point from the stack is discarded, because it cannot belong to the

% convex hull. In other words, the

% hull boundary must go straight or turn right, it may never turn to the left.

i = 1;

while i<=n

if stacktop<2

stacktop = stacktop+1;

stack(stacktop) = ind(i);

i = i+1;

else

p0 = xy(:,stack(stacktop));

p1 = xy(:,stack(stacktop-1));

p2 = xy(:,ind(i));

if (p1(1)-p0(1))*(p2(2)-p0(2))-(p2(1)-p0(1))*(p1(2)-p0(2)) >= 0

stacktop = stacktop+1;

stack(stacktop) = ind(i);

i = i+1;

else

% pop

stacktop = stacktop-1;

end

end

end % while loop

% The stack now contains the completed convex hull. Because each input point

% is pushed to the stack and discarded at most once, the computational

% complexity of the while-loop is linear.

k = stack(1:stacktop);

end

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