How can I solve the error 'Too many output arguments' when creating... (2024)

classdef histogram < matlab.apps.AppBase

% Properties that correspond to app components

properties (Access = public)

UIFigure matlab.ui.Figure

OrientationhistogramofphiButton matlab.ui.control.Button

OrientationhistogramofthetaButton matlab.ui.control.Button

DcollagenorientationofphiButton matlab.ui.control.Button

DcollagenorientationofthetaButton matlab.ui.control.Button

LoaddataButton matlab.ui.control.Button

UIAxes matlab.ui.control.UIAxes

end

methods (Access = private)

function meanc(app)

shgim = mean(double(shgim));3;

calcfibangspeed(app,shgim,armd,filton)= [aS];

% find size of image

sz=size(shgim,1);

sz2=size(shgim,2);

% filters the data using a Gaussian kernel

cdata=(shgim)/max(max(shgim));

if filton

hf = fspecial('gaussian',[9 9],1.2);

im=imfilter((double(cdata)+.0000001),hf);

else

im=cdata;

end

% create coordinates of window

[xk yk]=meshgrid(1:armd*2+1,1:armd*2+1);

% determine angle of each coordinate relative to center pixels xk and yk

xk=xk-armd-1;

yk=yk-armd-1;

[ang,radd] = cart2pol(xk,-1*yk);

% put all angular data between 0 and pi

ang=ang+pi*(ang<0);

% weighting factor 1/radius

wei=1./((radd));

wei=wei.*(wei>0);

% initialize variables

C=zeros(sz,sz2);

S=zeros(sz,sz2);

% This set of loops is where vector summation occurs. For each iteration a

% single directional vector is added to a running total.

for i=-armd:-1

for j=-armd:0

% creates 3 copies of the image: the original and two copies shifted

% in opposite directions by i and j

fim = circshift(im,[i j]);

bim = circshift(im,[-i -j]);

tim(:,:,1)=fim;

tim(:,:,2)=im;

tim(:,:,3)=bim;

% the standard deviation of tim is computed in the 3rd dimension,

% which means we're measuring how intensity varies between each

% pixel and its neighbors at relative shifts of i,j and -i,-j.

% We weight the orientation vector by the max possible standard

% deviation and the measured standard deviation

dc=sqrt(1/3)-(std(tim,0,3));

if ((i~=0)|(j~=0))

% we sum the x and y components of each vector and mulitply it

% by our weighting factors dc and wei

% note that because these are axial data (0deg=180deg), we

% multiply the angle by 2 (later we divide by 2)

C=C+(cos(2*ang(armd+1+i,armd+1+j)).*dc.*wei(armd+1+i,armd+1+j));

S=S+(sin(2*ang(armd+1+i,armd+1+j)).*dc.*wei(armd+1+i,armd+1+j));

end

end

end

for i=-armd:0

for j=1:armd

% creates 3 copies of the image: the original and two copies shifted

% in opposite directions by i and j

fim = circshift(im,[i j]);

bim = circshift(im,[-i -j]);

tim(:,:,1)=fim;

tim(:,:,2)=im;

tim(:,:,3)=bim;

% the standard deviation of tim is computed in the 3rd dimension,

% which means we're measuring how intensity varies between each

% pixel and its neighbors at relative shifts of i,j and -i,-j.

% We weight the orientation vector by the max possible standard

% deviation and the measured standard deviation

dc=sqrt(1/3)-(std(tim,0,3));

if ((i~=0)|(j~=0))

% we sum the x and y components of each vector and mulitply it

% by our weighting factors dc and wei

% note that because these are axial data (0deg=180deg), we

% multiply the angle by 2 (later we divide by 2)

C=C+(cos(2*ang(armd+1+i,armd+1+j)).*dc.*wei(armd+1+i,armd+1+j));

S=S+(sin(2*ang(armd+1+i,armd+1+j)).*dc.*wei(armd+1+i,armd+1+j));

end

end

end

meanc = atan2(S,C)/2;

meanc=(meanc).*(meanc>=0)+(meanc+pi).*(meanc<0);

aS=meanc;

end

function calcfibang3D(app)

function [aSDE,pSDER]=calcfibang3D(app, shgim,armdx,armdz,filton,para)

% This function calculates the voxel-wise orientation. The output and input

% indices are explained in the main program

im = shgim;

im = double(im);

sz = size(im,1);

sz2 = size(im,2);

sz3 = size(im,3);

% Here starts the determination of theta

terimc = zeros(sz,sz2,3*sz3);

terimc(:,:,1:sz3) = im;

terimc(:,:,(sz3+1):(2*sz3)) = im;

terimc(:,:,(2*sz3+1):(3*sz3)) = im;

imc = zeros(sz,sz2,sz3);

for i = 1:sz3

imc(:,:,i) = mean(terimc(:,:,(sz3+i-armdz):(sz3+i+armdz)),3);

end

clear terimc

meanc = zeros(sz,sz2,sz3);

h = waitbar(0,'Please Wait');

ij = 0;

nij = sz3;

for i = 1:sz3

ij = ij+1;

waitbar(ij/nij)

meanc(:,:,i) = calcfibangspeed(app,imc(:,:,i),armdx,filton);

end

close(h)

clear imc

% Here starts the determination of beta

terimj = zeros(3*sz,sz2,sz3);

terimj(1:sz,:,:) = im;

terimj((sz+1):(2*sz),:,:) = im;

terimj((2*sz+1):(3*sz),:,:) = im;

imj = zeros(sz,sz2,sz3);

for i = 1:sz

imj(i,:,:) = mean(terimj((sz+i-armdz):(sz+i+armdz),:,:),1);

end

clear terimj

% To calculate the orientation in 2D manner

meanj = zeros(sz,sz2,sz3);

h = waitbar(0,'Please Wait')

ij = 0;

nij = sz;

for i = 1:sz

ij = ij+1;

waitbar(ij/nij)

meanj(i,:,:) = calcfibangspeed(squeeze(imj(i,:,:)),armdx,filton);

end

close(h)

clear imj

meanj = (pi/2-meanj).*(meanj<=pi/2)+(3*pi/2-meanj).*(meanj>pi/2);

% Here starts the determination of gamma

terimg = zeros(sz,3*sz2,sz3);

terimg(:,1:sz2,:) = im;

terimg(:,(sz2+1):(2*sz2),:) = im;

terimg(:,(2*sz2+1):(3*sz2),:) = im;

img = zeros(sz,sz2,sz3);

for i = 1:sz

img(:,i,:) = mean(terimg(:,(sz2+i-armdz):(sz2+i+armdz),:),2);

end

clear terimg

% To calculate the orientation in 2D manner

meang = zeros(sz,sz2,sz3);

h = waitbar(0,'Please Wait')

ij = 0;

nij = sz2;

for i = 1:sz2

ij = ij+1;

waitbar(ij/nij)

meang(:,i,:) = calcfibangspeed(app,squeeze(img(:,i,:)),armdx,filton);

end

close(h)

clear img

meang = (pi/2+meang).*(meang<=pi/2)+(meang-(pi/2)).*(meang>pi/2);

% Here to acquire the orientation of phi

meanp = atan(sqrt(1./(tan(meanj).^2)+1./(tan(meang).^2)));

meanplim = meanp;

for i = 1:sz

for j = 1:sz2

for k = 1:sz3

if meanj(i,j,k) <= pi/2

meanp(i,j,k) = meanp(i,j,k);

else

meanp(i,j,k) = pi-meanp(i,j,k);

end

end

end

end

% Here to acquire the real phi orientation regardless of Z resolution

meanpreal = (pi/2)-(atan(para*tan((pi/2)-meanplim)));

for i = 1:sz

for j = 1:sz2

for k = 1:sz3

if meanj(i,j,k) <= pi/2

meanpreal(i,j,k) = meanpreal(i,j,k);

else

meanpreal(i,j,k) = pi-meanpreal(i,j,k);

end

end

end

end

% Here prepares the final output

aSDE = meanc*180/pi;

pSDER = meanpreal*180/pi;

end

end

end

% Callbacks that handle component events

methods (Access = private)

% Button pushed function: LoaddataButton

function LoaddataButtonPushed(app, event)

sz = 512 ;

sz2 = 512 ;

sz3 = 30 ; % 46; % modify 1, define sz, sz2, and sz3 according to the size of the 3D image

shgstack = zeros(sz,sz2,sz3);

for i = 1:sz3

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%7 modify

% shgstack(:,:,i) = imread(['C:\Users\myy15\Desktop\human500um1um\humanskin250umz1um\noshift2\',num2str(i),'.tif']); % modify 2

shgstack(:,:,i) = imread(['/Users/kaitlynn/Desktop/Matlab/imaging/',num2str(i),'.tif']); % modify 2

% shgstack(:,:,i) = imread(['C:\Users\myy15\Desktop\human500um1um\stack2\',num2str(i),'.tif']); % modify 2

% 'shgstack' is the 3D image used for directional variance analysis.

% Define the path of the folder where the images are saved

end

end

% Button pushed function: DcollagenorientationofthetaButton

function DcollagenorientationofthetaButtonPushed(app, event)

end

% Button pushed function: OrientationhistogramofthetaButton

function OrientationhistogramofthetaButtonPushed(app, event)

aSDE = meanc(app)*180/pi;

histogram(app.UIAxes,aSDE, sz,sz2, sz3) ;

end

end

% Component initialization

methods (Access = private)

% Create UIFigure and components

function createComponents(app)

% Create UIFigure and hide until all components are created

app.UIFigure = uifigure('Visible', 'off');

app.UIFigure.Position = [100 100 640 480];

app.UIFigure.Name = 'MATLAB App';

% Create UIAxes

app.UIAxes = uiaxes(app.UIFigure);

title(app.UIAxes, 'Title')

xlabel(app.UIAxes, 'X')

ylabel(app.UIAxes, 'Y')

zlabel(app.UIAxes, 'Z')

app.UIAxes.Position = [297 240 300 185];

% Create LoaddataButton

app.LoaddataButton = uibutton(app.UIFigure, 'push');

app.LoaddataButton.ButtonPushedFcn = createCallbackFcn(app, @LoaddataButtonPushed, true);

app.LoaddataButton.Position = [52 424 100 22];

app.LoaddataButton.Text = 'Load data';

% Create DcollagenorientationofthetaButton

app.DcollagenorientationofthetaButton = uibutton(app.UIFigure, 'push');

app.DcollagenorientationofthetaButton.ButtonPushedFcn = createCallbackFcn(app, @DcollagenorientationofthetaButtonPushed, true);

app.DcollagenorientationofthetaButton.Position = [10 364 184 22];

app.DcollagenorientationofthetaButton.Text = '2D collagen orientation of theta';

% Create DcollagenorientationofphiButton

app.DcollagenorientationofphiButton = uibutton(app.UIFigure, 'push');

app.DcollagenorientationofphiButton.Position = [16 314 173 22];

app.DcollagenorientationofphiButton.Text = '2D collagen orientation of phi';

% Create OrientationhistogramofthetaButton

app.OrientationhistogramofthetaButton = uibutton(app.UIFigure, 'push');

app.OrientationhistogramofthetaButton.ButtonPushedFcn = createCallbackFcn(app, @OrientationhistogramofthetaButtonPushed, true);

app.OrientationhistogramofthetaButton.Position = [13 190 176 22];

app.OrientationhistogramofthetaButton.Text = 'Orientation histogram of theta';

% Create OrientationhistogramofphiButton

app.OrientationhistogramofphiButton = uibutton(app.UIFigure, 'push');

app.OrientationhistogramofphiButton.Position = [19 130 165 22];

app.OrientationhistogramofphiButton.Text = 'Orientation histogram of phi';

% Show the figure after all components are created

app.UIFigure.Visible = 'on';

end

end

% App creation and deletion

methods (Access = public)

% Construct app

function app = histogram

% Create UIFigure and components

createComponents(app)

% Register the app with App Designer

registerApp(app, app.UIFigure)

if nargout == 0

clear app

end

end

% Code that executes before app deletion

function delete(app)

% Delete UIFigure when app is deleted

delete(app.UIFigure)

end

end

end