I have written the following code the plot the height of water in a tank vs. time.
A_t = 16;
[h1, t1] = update_plot(A_t);
f = figure;
h = plot(t1, h1);
b = uicontrol('Parent',f,'Style','slider','Position',[81,54,419,23], 'value',A_t, 'min',14, 'max',17);
bgcolor = f.Color;
set(b,'Callback',#(es,ed) updateSystem(h,update_plot((es.Value))))
The function to update the h (height of water) and t (time) vectors is:
function [h1, t1] = update_plot(A_t)
t = 0:0.01:100;
h = zeros(1, length(t));
h_init = 20;
t_0 = 0;
myeps = 1e-5;
i = 1;
h(1) = h_init;
while h(i) > myeps
i = i + 1;
h(i) = (sqrt(h_init) - (0.18/A_t)*sqrt(981/2)*(t(i) - t_0))^2;
h1 = h(1:i);
t1 = t(1:i);
end
The parameter A_t is the variable for which I want to use a slider.
I cannot get the callback function to work.
I want the plot to be updated as I move the slider.
You can try this:
set(b,'Callback', #slider_callback);
function slider_callback(hObject, callbackdata)
A_t = num2str(hObject.Value);
update_plot(A_t);
end
Then you would also have to clear your figure with cla and use plot with the update values.
I got it working. The modified code and functions are:
function[f] = update_plot(A_t)
t = 0:0.01:100;
h = zeros(1, length(t));
h_init = 20;
t_0 = 0;
myeps = 1e-5;
i = 1;
h(1) = h_init;
while h(i) > myeps
i = i + 1;
h(i) = (sqrt(h_init) - (0.18/A_t)*sqrt(981/2)*(t(i) - t_0))^2;
h1 = h(1:i);
t1 = t(1:i);
end
f = plot(t1, h1);
legend('Measured', 'Tuned')
grid on
The callback function is:
function change_plot(objHandle, ~)
slider_value = get(objHandle, 'Value');
new_A_t = slider_value;
update_plot(new_A_t);
And the main function is:
A_t = 15.5;
ff = figure;
axes('Parent',ff, 'units', 'normalized',...
'position',[0.05 0.15 0.9 0.8])
update_plot(A_t);
b = uicontrol('Parent',ff,'Style','slider',...
'value',A_t, 'min',14, 'max',17,...
'units', 'normalized',...
'position', [0.33 0 0.4 0.1],...
'SliderStep', [0.001 0.1],...
'callback', #change_plot);
disp_h = uicontrol('style', 'edit',...
'units', 'normalized',...
'position', [0.15 0.05 0.15 0.05]);
bgcolor = ff.Color;
Now I want to display the value of the slider in the 'edit' box I've created, but so far have been unable to get it to work.
Related
I have been trying to plot two images side by side with two sliders using uicontrol. I am relatively new to uicontrol using matlab. Only the second subplot updates when I change the slider.
close all;
clear all;
clc;
set(0,'defaultAxesFontSize',14)
set(0,'DefaultFigureWindowStyle','docked')
data = rand(3,1024,64,20);
nslice = size(data,4);
nidx = size(data,1);
if nslice == 1
sampling = 1; % in some of my data nslice would be 1 so I would like my slider to not give me error in such a case
else
sampling = 5;
end
idx = 1;
slice = 1;
h.f = figure(1);
x_axis = linspace(0,0.5,size(data,3));
y_axis = linspace(0,70,size(data,2));
set(h.f,'doublebuffer','on')
h.data = data;
inst_data = squeeze(data(nidx,:,:,slice));
h.ax(1) = subplot(1,2,1,'Parent',h.f,'Units','Normalized');
imagesc(h.ax(1),x_axis,y_axis, inst_data)
colorbar;
colormap(h.ax(1),'gray')
caxis(h.ax(1),[min(abs(inst_data(:))),max(abs(inst_data(:)))])
xlabel('xaxis')
ylabel('yaxis')
title('figure 1')
h.ax(2) = subplot(1,2,2,'Parent',h.f,'Units','Normalized');
log_data = log(inst_data);
imagesc(h.ax(2),x_axis,y_axis, log_data)
colorbar;
colormap(h.ax(2),'jet')
caxis(h.ax(2),[-max(abs(log_data(:))),max(abs(log_data(:)))])
xlabel('xaxis')
ylabel('yaxis')
title('figure 2')
sgtitle({'Sample data ', ['Slice: ',num2str(slice),' index: ', num2str(idx)]},'FontSize',16,'FontWeight','Bold')
h.slider1=uicontrol('Parent',h.f,...
'Units','Normalized',...
'Position',[0.1 0.06 0.8 0.05],...
'Style','slider',...
'SliderStep',[1,sampling],...
'Min',1,'Max',nslice,'Value',1,...
'Callback',{#slider_Callback,data,x_axis,y_axis});
txt1 = 'Slice';
txt2 = 'Index';
annotation('textbox', [0.05 0.07 0.05 0.04], 'string', txt1);
annotation('textbox', [0.05 0.021 0.05 0.04], 'string', txt2);
h.slider2=uicontrol('Parent',h.f,...
'Units','Normalized',...
'Position',[0.1 0.02 0.8 0.05],...
'Style','slider',...
'SliderStep',[1,1],...
'Min',1,'Max',nidx,'Value',1,...
'Callback',{#slider_Callback,data,x_axis,y_axis});
guidata(h.f,h)
%%
function slider_Callback(hObject,eventdata,data,x_axis,y_axis)%#ok<INUSD>
h=guidata(hObject);%retrieve struct
slice_i = round(get(h.slider1, 'Value'));
idx_i = round(get(h.slider2,'Value'));
inst = squeeze(data(idx_i,:,slice_i));
colorbar;
colormap(h.ax(1),'gray')
caxis(h.ax(1),[min(abs(inst(:))),max(abs(inst(:)))])
h.ax(1) = imagesc(x_axis,y_axis,inst); colorbar
lg = log(inst);
colorbar;
colormap(h.ax(2),'jet')
caxis(h.ax(2),[-max(abs(lg(:))),max(abs(lg(:)))])
h.ax(2) = imagesc(x_axis,y_axis, lg ); colorbar;
sgtitle({'Sample data ', ['Slice: ',num2str(slice_i),' index: ', num2str(idx_i)]},'FontSize',16,'FontWeight','Bold')
drawnow
end
Other problems include:
The slider slides with a floating value which shouldnt be the case
When my data has only 1 slice, the slider moves to value zero which shouldn't happen. You can try the same example with data = rand(3,1024,64,1);
I want to create a relative axis in Matlab like the $\Delta I$-rulers in the following plot.
Before I start writing up a function that constructs it manually, I would like to know if there's way of creating an object with the NumericRuler-properties (like the default axes of a figure())
So I ended up using the link provided by Sardar Usama's comment as inspiration and wrote a function to create an axes-object relative to the values of a "parent"-axes:
function ax = create_value_axes(hAx, pos)
%% ax = create_value_axes(hAx, pos)
%
% Create axes at the value points of hAx.
%
% pos(1) = x-position
% pos(2) = y-position
% pos(3) = x-width
% pos(4) = y-width
%
% Get "parent" position and value limits
hAx_pos = hAx.Position;
hAx_xlm = hAx.XLim;
hAx_ylm = hAx.YLim;
% Get relative position increment pr value increment
x_step = hAx_pos(3) / (hAx_xlm(2) - hAx_xlm(1));
y_step = hAx_pos(4) / (hAx_ylm(2) - hAx_ylm(1));
% Set position
subaxes_abs_pos(1) = (pos(1)-hAx_xlm(1)) * x_step + hAx_pos(1);
subaxes_abs_pos(2) = (pos(2)-hAx_ylm(1)) * y_step + hAx_pos(2);
subaxes_abs_pos(3) = pos(3) * x_step;
subaxes_abs_pos(4) = pos(4) * y_step;
% Create axes
ax = axes('Position', subaxes_abs_pos);
% Remove background
ax.Color = 'none';
end
Sidenote: I found that I didn't need plotboxpos to get the correct positions of the "parent"-axes, using Matlab r2019b on macOS Mojave 10.14.6
Anyway, this is what I end up with:
Using the code:
% Just some random data
mockup_data_ild = [-10 -7 -4 0 4 7 10];
mockup_data_itd_45 = [-40 -20 -10 0 10 20 40];
mockup_data_itd_60 = [-30 -15 -5 0 5 15 30];
% Create figure
figure('Color', 'w')
x_axis_offset = [0 30];
hold on
% Plot 45 dB result
p1 = plot_markers(x_axis_offset(1) + mockup_data_ild, mockup_data_itd_45, ii);
% Plot 60 dB results
p2 = plot_markers(x_axis_offset(2) + mockup_data_ild, mockup_data_itd_60, ii);
p2.Color = p1.Color;
p2.HandleVisibility = 'off';
hold off
% Set axes properties
ax = gca;
ax.XAxis.TickValues = [x_axis_offset(1) x_axis_offset(2)];
ax.XAxis.TickLabels = {'45 dB' '60 dB'};
ax.XAxis.Limits = [x_axis_offset(1)-15 x_axis_offset(2)+15];
ax.XAxisLocation = 'top';
ax.YAxis.Limits = [-80 100];
ax.YAxis.Label.String = 'Interaural Time Difference, \Deltat, in samples';
ax.YGrid = 'on';
% Create 45 dB axis
ax2 = create_DeltaI_axis(ax, x_axis_offset(1));
% Create 60 dB axis
ax3 = create_DeltaI_axis(ax, x_axis_offset(2));
% Create legend
leg = legend(ax, {'P1'});
leg.Location = 'northwest';
%% Helpers
function ax = create_DeltaI_axis(hAx, x_pos)
y_pos = -70;
y_height = 170;
range = 20;
ax = create_value_axes(hAx, [x_pos-range/2 y_pos range y_height]);
ax.XAxis.TickValues = [0 .25 .5 .75 1];
ax.XAxis.TickLabels = {'-10'
'-5'
'0'
'5'
'10'};
ax.XAxis.Label.String = '\DeltaI';
ax.XGrid = 'on';
ax.XMinorGrid = 'on';
ax.YAxis.Visible = 'off';
end
function p = plot_markers(x, y, ii)
markers = {'square','^', 'v', 'o', 'd'};
p = plot(x, y);
p.LineWidth = 1.5;
p.LineStyle = 'none';
p.Marker = markers{ii};
end
I want to move a red star marker along the spiral trajectory with an equal distance of 5 units between the red star points on its circumference like in the below image.
vertspacing = 10;
horzspacing = 10;
thetamax = 10*pi;
% Calculation of (x,y) - underlying archimedean spiral.
b = vertspacing/2/pi;
theta = 0:0.01:thetamax;
x = b*theta.*cos(theta)+50;
y = b*theta.*sin(theta)+50;
% Calculation of equidistant (xi,yi) points on spiral.
smax = 0.5*b*thetamax.*thetamax;
s = 0:horzspacing:smax;
thetai = sqrt(2*s/b);
xi = b*thetai.*cos(thetai);
yi = b*thetai.*sin(thetai);
plot(x,y,'b-');
hold on
I want to get a figure that looks like the following:
This is my code for the circle trajectory:
% Initialization steps.
format long g;
format compact;
fontSize = 20;
r1 = 50;
r2 = 35;
r3= 20;
xc = 50;
yc = 50;
% Since arclength = radius * (angle in radians),
% (angle in radians) = arclength / radius = 5 / radius.
deltaAngle1 = 5 / r1;
deltaAngle2 = 5 / r2;
deltaAngle3 = 5 / r3;
theta1 = 0 : deltaAngle1 : (2 * pi);
theta2 = 0 : deltaAngle2 : (2 * pi);
theta3 = 0 : deltaAngle3 : (2 * pi);
x1 = r1*cos(theta1) + xc;
y1 = r1*sin(theta1) + yc;
x2 = r2*cos(theta2) + xc;
y2 = r2*sin(theta2) + yc;
x3 = r3*cos(theta3) + xc;
y3 = r3*sin(theta3) + yc;
plot(x1,y1,'color',[1 0.5 0])
hold on
plot(x2,y2,'color',[1 0.5 0])
hold on
plot(x3,y3,'color',[1 0.5 0])
hold on
% Connecting Line:
plot([70 100], [50 50],'color',[1 0.5 0])
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);
drawnow;
axis square;
for i = 1 : length(theta1)
plot(x1(i),y1(i),'r*')
pause(0.1)
end
for i = 1 : length(theta2)
plot(x2(i),y2(i),'r*')
pause(0.1)
end
for i = 1 : length(theta3)
plot(x3(i),y3(i),'r*')
pause(0.1)
end
I can't think of a way to compute distance along a spiral, so I'm approximating it with circles, in hopes that it will still be useful.
My solution relies on the InterX function from FEX, to find the intersection of circles with the spiral. I am providing an animation so it is easier to understand.
The code (tested on R2017a):
function [x,y,xi,yi] = q44916610(doPlot)
%% Input handling:
if nargin < 1 || isempty(doPlot)
doPlot = false;
end
%% Initialization:
origin = [50,50];
vertspacing = 10;
thetamax = 5*(2*pi);
%% Calculation of (x,y) - underlying archimedean spiral.
b = vertspacing/(2*pi);
theta = 0:0.01:thetamax;
x = b*theta.*cos(theta) + origin(1);
y = b*theta.*sin(theta) + origin(2);
%% Calculation of equidistant (xi,yi) points on spiral.
DST = 5; cRes = 360;
numPts = ceil(vertspacing*thetamax); % Preallocation
[xi,yi] = deal(NaN(numPts,1));
if doPlot && isHG2() % Plots are only enabled if the MATLAB version is new enough.
figure(); plot(x,y,'b-'); hold on; axis equal; grid on; grid minor;
hAx = gca; hAx.XLim = [-5 105]; hAx.YLim = [-5 105];
hP = plot(xi,yi,'r*');
else
hP = struct('XData',xi,'YData',yi);
end
hP.XData(1) = origin(1); hP.YData(1) = origin(2);
for ind = 2:numPts
P = InterX([x;y], makeCircle([hP.XData(ind-1),hP.YData(ind-1)],DST/2,cRes));
[~,I] = max(abs(P(1,:)-origin(1)+1i*(P(2,:)-origin(2))));
if doPlot, pause(0.1); end
hP.XData(ind) = P(1,I); hP.YData(ind) = P(2,I);
if doPlot, pause(0.1); delete(hAx.Children(1)); end
end
xi = hP.XData(~isnan(hP.XData)); yi = hP.YData(~isnan(hP.YData));
%% Nested function(s):
function [XY] = makeCircle(cnt, R, nPts)
P = (cnt(1)+1i*cnt(2))+R*exp(linspace(0,1,nPts)*pi*2i);
if doPlot, plot(P,'Color',lines(1)); end
XY = [real(P); imag(P)];
end
end
%% Local function(s):
function tf = isHG2()
try
tf = ~verLessThan('MATLAB', '8.4');
catch
tf = false;
end
end
function P = InterX(L1,varargin)
% DOCUMENTATION REMOVED. For a full version go to:
% https://www.mathworks.com/matlabcentral/fileexchange/22441-curve-intersections
narginchk(1,2);
if nargin == 1
L2 = L1; hF = #lt; %...Avoid the inclusion of common points
else
L2 = varargin{1}; hF = #le;
end
%...Preliminary stuff
x1 = L1(1,:)'; x2 = L2(1,:);
y1 = L1(2,:)'; y2 = L2(2,:);
dx1 = diff(x1); dy1 = diff(y1);
dx2 = diff(x2); dy2 = diff(y2);
%...Determine 'signed distances'
S1 = dx1.*y1(1:end-1) - dy1.*x1(1:end-1);
S2 = dx2.*y2(1:end-1) - dy2.*x2(1:end-1);
C1 = feval(hF,D(bsxfun(#times,dx1,y2)-bsxfun(#times,dy1,x2),S1),0);
C2 = feval(hF,D((bsxfun(#times,y1,dx2)-bsxfun(#times,x1,dy2))',S2'),0)';
%...Obtain the segments where an intersection is expected
[i,j] = find(C1 & C2);
if isempty(i), P = zeros(2,0); return; end
%...Transpose and prepare for output
i=i'; dx2=dx2'; dy2=dy2'; S2 = S2';
L = dy2(j).*dx1(i) - dy1(i).*dx2(j);
i = i(L~=0); j=j(L~=0); L=L(L~=0); %...Avoid divisions by 0
%...Solve system of eqs to get the common points
P = unique([dx2(j).*S1(i) - dx1(i).*S2(j), ...
dy2(j).*S1(i) - dy1(i).*S2(j)]./[L L],'rows')';
function u = D(x,y)
u = bsxfun(#minus,x(:,1:end-1),y).*bsxfun(#minus,x(:,2:end),y);
end
end
Result:
Note that in the animation above, the diameter of the circle (and hence the distance between the red points) is 10 and not 5.
I want to optimize this function:
function Y_res = GetY( Y, P )
cnt = length(P);
denom = 0;
for i = 1:cnt
Y(i) = rand;
denom = denom + P(i) / (1 - Y(i));
end
Y_res = 1 - 1 / denom;
Y
Y_res
end
This function receives Y and P. P is a constant array. I need to optimize Y array values. And I trying to do this:
Y = [0.3 0.2 0.1]; % need to be optimized
P = [0.65 0.2 0.15]; % constant array
fhnd_GetY = #(x) GetY(Y, P);
options = optimset('TolX', 1e-3);
optimal_x = fminbnd(fhnd_GetY, 0.2, 0.4, options);
But the result of optimal_x variable does not equals to Y_res, which you can see on the screen during iterations of GetY function. Why? I need to optimze Y_res between 0.2 and 0.4 for example. So as a result I need to receive Y_res between 0.2 and 0.4 (for example) and Y array with values by means of which I can receive Y_res.
Assuming that you only intend to optimize the function GetY and given the fact that you are creating Y inside it and as such don't need to externally input Y into it, see if this modified function is optimized enough for you -
function [Y_res,Y] = GetY( P )
found = false;
while ~found
Y = rand(size(P));
Y_res = 1-1./sum(P./(1-Y));
if Y_res>0.2 & Y_res<0.4
found = true;
end
end
return;
Please note that if you don't need Y as an output, you can use Yres = GetY([0.65 0.2 0.15]) instead, but most probably you would need that (my guess though).
Few sample runs -
>> [Yres,Y] = GetY([0.65 0.2 0.15])
Yres =
0.3711
Y =
0.4243 0.2703 0.1971
>> [Yres,Y] = GetY([0.65 0.2 0.15])
Yres =
0.2723
Y =
0.1897 0.4950 0.1476
>> [Yres,Y] = GetY([0.65 0.2 0.15])
Yres =
0.3437
Y =
0.3624 0.0495 0.4896
Why doesn't color filter below find green peppers?
The code:
function [ outhsv ] = ColorFilter( hsv, h, s )
%COLORFILTER Summary of this function goes here
% Detailed explanation goes here
if nargin < 2
h = [];
end
if nargin < 3
s = [];
end
if size(h,2)==1
h = padarray(h, [0 1], 1/100, 'post');
end
if size(s,2)==1
s = padarray(s, [0 1], 1/100, 'post');
end
if isempty(h)
v_of_h = ones(size(hsv,1), size(hsv,2));
else
v_of_h = WeightFunction( hsv(:,:,1), h(:,1), h(:,2));
end
if isempty(s)
v_of_s = ones(size(hsv,1), size(hsv,2));
else
v_of_s = WeightFunctionOnce( hsv(:,:,2), s(:,1), s(:,2));
end
outhsv = hsv;
outhsv(:,:,3) = hsv(:,:,3) .* v_of_h .* v_of_s;
function y = WeightFunction( x, mu, sigma )
%y = WeightFunctionOnce(x,mu,sigma) + WeightFunctionOnce(x-1,mu,sigma);
y = 1 - (1-WeightFunctionOnce(x,mu,sigma)) .* (1-WeightFunctionOnce(x-1,mu,sigma));
function y = WeightFunctionOnce( x, mu, sigma )
if nargin<2
mu=0;
elseif nargin<3
sigma=1./100.;
end
if any(size(mu) ~= size(sigma))
error('mu and sigma should be of the same size');
end
y = zeros([size(x) numel(mu)]);
for i=1:numel(mu)
y(:,:,i) = exp(-((x - mu(i)) .^ 2 ./ (2 .* sigma(i) .^ 2)));
end
%y = sum(y,3)/size(y,3);
y = 1-prod(1-y,3);
Display code:
hue = 120;
h = [hue/360 0.05];
s = [];
rgb1 = imread('huescale.png');
%rgb1 = imread('peppers.png');
hsv1 = rgb2hsv(rgb1);
hsv2 = ColorFilter(hsv1, h, s);
rgb2 = hsv2rgb(hsv2);
bitmask = hsv1(:,:,1)>(h(1)-h(2)) & hsv1(:,:,1)<(h(1)+h(2));
figure;
subplot(3,1,1); imshow(rgb1);
subplot(3,1,2); imshow(rgb2);
subplot(3,1,3); imshow(bitmask);
result on scale
(works)
result on peppers:
(does not)
Why?
If you looked closer at the H values, those green peppers are kind of yellowish, so you might want to widen the rule a bit.
I would suggest something in between 0.15 and 0.5. You can also combine with saturation channel, say only consider portions of images that are vibrant, i.e., we want to get rid of the onions. Try the following codes to get a preview.
hsv_dat = rgb2hsv(imread('peppers.png'));
imagesc(hsv_dat(:,:,1) > 0.15 & hsv_dat(:,:,1) < 0.5 & hsv_dat(:,:,2) > 0.3)
colormap(gray)
You should get