I have to plot graphics and compare them but it's misleading because of different y-axis upper bounds for each of them (they are all positive values).
Anyway I'm doing a cycle like this:
%% check for data files
for i=1:length(files)
load
plot(x,y)
end
I need to change my code if I want to save the maximum upper bound on y.
%% check for data files
for i=1:length(files)
load
%% compare upper bounds and get the maximum
end
%% plot cycle
But then how can I use this value to plot comparable but separated graphics.
I can't plot them in only one figure because they are many. Also tell me If you think of a possible optimization for my task.
ylim is what you are looking for, but if i understood you right you might also want to look at linkaxes.
You can use ylim. Check out these questions: 1, 2 or 3.
ylim([ymin ymax]) % or something like: set(gca,'Ylim',yLimits)
sets the axis limits in the current axes to the specified values
Related
Is it possible to make multiple vertical histograms plot in Matlab into one? Much like the excel sheet enclosed ( https://drive.google.com/file/d/1H_mbyrIoln3XrnK1hLajnVNBKn13y_np/view?usp=sharing )
I want to make a plot of many vertical histogram plots into one figure, by importing excel-files, where on the y axis it has the elevation, the x axis the distance between the histogram vertical lines and the length of the histogram bars is the values in the excel sheet. The vertical height of each bar is 5.
Is this even possible? I have to put in a number of conditions for Matlab to know where to plot, but could some one show me the basic methodology?
Help would be very much appreciated!
The problem is that the parent of a Baseline object is the Axis, which prevents us from doing something like
barh(bins1,counts1,'Basevalue',baseline1); hold on;
barh(bins2,counts2,'Basevalue',baseline2); hold off;
because the plots will automatically share the second baseline value set. There might be a workaround for this that I do not know of, so I invite anybody who knows it to show me how its done.
For now, I was able to sort-of replicate the plot you posted a picture of in a much less elegant way. I will post code below, but before I do, I would like to argue against the use of a plot like this. Why? Because I think it is confusing, as the x-axis both relates to the plot number as well as the bin count numbers. You are in fact trying to display a 3-D data set, the three dimensions being bins, bin counts, and 'histogram number'. A plethora of methods exist for displaying 3-D data, and a series of 2-D histograms may not be the best way to go.
That being said, here is a code that more-or-less creates the picture above, as promised. Any changes you may want to make will be more cumbersome than usual :-)
testData = randn(10000,1); % Generate some data
[counts,bins] = hist(testData); % Bin the data
% First histogram
baseline1 = 0;
p1=subplot(1,3,1); barh(bins,counts,'BaseValue',baseline1);
xticks(baseline1); xticklabels({0}); % Graph number on x axis at baseline (0)
box off; % Remove box on right side of plot
ylabel('Property');
% Second histogram
baseline2 = max(counts)*1.2;
sepdist = baseline2-baseline1; % Distance that separates two baselines
counts2 = baseline2 + counts;
p2=subplot(1,3,2); barh(bins,counts2,'BaseValue',baseline2)
xticks(baseline2); xticklabels({1}); % Graph number on x axis at baseline
box off;
Y=gca; Y.YAxis.Visible='off';
p1p=p1.Position; p2p=p2.Position;
p2p(1)=p1p(1)+p1p(3); p2.Position=p2p; % Move subplot so they touch
% Third histogram
baseline3 = baseline2 + sepdist;
counts3 = baseline3+counts;
p3=subplot(1,3,3); barh(bins,counts3,'BaseValue',baseline3)
xticks(baseline3); xticklabels({2});
Y=gca; Y.YAxis.Visible='off';
box off
p3p=p3.Position;
p3p(1)=p2p(1)+p2p(3); p3.Position=p3p;
% Add x-label when you are done:
xl=xlabel('Test xlabel'); xl.Units='normalized';
% Fiddle around with xl.Position(1) until you find a good centering:
xl.Position(1) = -0.49;
Result:
I am trying to write a MATLAB script to give me a contour map. The contour map must be created from inputs that I generated from 100 images.
The story is like this:
I have 100 images on which I ran an image processing algorithm for optimization. Now, I got their energy curves. So, I have 100 energy curves. I want to create a contour map that will show me where the points are denser on the plot. (the energy curves are plotted as energy vs. iteration with fixed number of iterations)
The following is my variable:
energy(iteration,numImages)
Hope I explained it well.
Thanks in advance.
I interpret your question to boil down to how can I create a surface plot with colors according to the energy found in energy. I would solve this by using the contour function with a grid generated using meshgrid. If each image is described in 1000 data points with 100 files the plot can be generated as follows:
% using stuff as random junk instead of energy
numPoints = 1000;
numFiles = 100;
stuff = rand(1000,100); % replace with actual information
[X, Y] = meshgrid(1:numFiles, 1:numPoints);
contour(X,Y,stuff);
You can also create a 3D surface plot using surf and the same logic.
From what i see of you graph (and using the comments also), one possible way is to use plot3 to plot a line in 3D for every plot.
For doing so, you can use something like this code:
x=(0:0.01:1)';
aexp=zeros(100,numel(x));
hold on
for ii=1:100;
% aexp(ii,:)=exp((-x+ii/10)); %exponential
aexp(ii,:)=exp(-(x-ii/100).^2); %~gaussian
% aexp(ii,:)= x*ii; %linear increase
plot3(x,aexp(ii,:),ii*ones(1,numel(x)));
end
% set(gca,'yscale','log'); % uncomment if you need logscale.
giving
I have a few options of plot. It always plot from the XY view. I changed by hand, but you can use the view command. Notice that i used a simple counter to make the spacing in the z direction.
In a similar manner, you can plot using the contour. For my code, after the data have been generated in the for loop, remove/comment the plot3 and add:
contour(aexp) %outside the for loop,
giving
Notice that i have not really take care what i'm plotting. You can find more info on contour in the Matlab page .
You commented that the x-axis should be number of iterations, y-axis should be energy and z-axis should be the information containing how many lines are passing through from some areas. For this, make a qq variable, being it qq=number_of_lines(number of iterations,energy) . Make a discrete grid for the energy if you don't have one. Number of iterations is probably discrete anyway. The function is you who need to devise, but i would go for something which checks the number of lines for every energy and every iteration. In this case you will have the z-function that depends on y and x, that is the case to use contour or surface.
My function above make a line for every ii point, to have a 3d function. An edition for another extra loop is not hard. Just remember to have the same regular grid for every point, otherwise you will have trouble.
I need to plot two plots on same figure in MATLAB.
The maximum and minimum values in both the data samples have large variation, which I am unable to plot by taking same y-axis limits.
I do not wish to use two scales as explained in other Overlaying two axes in a Matlab plot but need to use a single y-axis and get the solution.
I tried the code:
x_axis_X = 1:length(S);
y_axis_Y = 1:length(N);
ylim([-1204200 -1841.6])
set(gcf,'color','w');
plot(x_axis_X, S,'o-', y_axis_Y, N, 'x-');
The result is as shown in the plot where one data sample is plotted without proper y-axis range.
The y limits for first data sample is -1204200 to -1841.6 and for the second it is -489429345.5 to -10408189.43.
How should be the ylim defined to fit both plots in the same figure?
I appreciate your inputs. Thank you.
In older versions of MATLAB use the function plotyy. In more recent versions of MATLAB use yyaxis. The following is the example from the documentation:
x = linspace(0,10);
y = sin(3*x);
yyaxis left
plot(x,y)
z = sin(3*x).*exp(0.5*x);
yyaxis right
plot(x,z)
ylim([-150 150])
I tried the idea of scaling one dataset so that it has a similar magnitude as the other data set. Here, I multiplied one dataset by 100 (or any suitable scaling parameter), and then it will be similar in size to the other data set. In order to clearly mention which data has been scaled in the graph I used the legend.
plot(x,data1,x,100*data2)
legend('data1','100*data2','location','southeast')
Thank you.
Scaling is not the best option, as you may need to work with the data later. Also does not work if for instance, you need a log scale.
Matlab has a few ways to deal it with. I particularly like to use a new axes in the figure, as i have done in the example below.
Just in case, you also found this answer in a simple google search!
Code:
a=1:10;
b=(10:-1:1)*100;
x=1:10;
hold on
plot(x,a,'b')
pax1=get(gca,'Position'); %get axis position
ax2 = axes('Position',pax1); %create a new axis
plot(ax2,x,b,'r') %plot new data
set(ax2, 'Yaxislocation','right',...
'color','none') % set it transparent and to the right
I am trying to plot a figure that changes with time (think of it as plotting the shape of a pole as the wind passes through it, so I want to plot the shape at every second).
To avoid the x axis limit changing frequently I want to fix it to the limits (max and min that I calculate before plotting). Here is a sample of my code:
for i=1:1:numberofrows
momentvaluesatinstant = momentvalues(i,:);
figure(1)
plot(momentvaluesatinstant,momentheader)
drawnow
title(sprintf('Moment profile along pile at time 0.2%f',time(i)'))
xlabel('Moment (kN.m)')
xlim([momentvalues(rowminmoment) momentvalues(rowmaxmoment)])
ylabel('Length of pile (m)')
delay(1);
end
Although I am specifying the limits of the x axis to be fixed to the values I specify, the plot keeps changing the limits depending on the data being plotted? Is there something I am missing?
Figured it, need to add xlim manual
I'm not sure why you needed xlim manual, but here is a more compact and correct way to animate your data:
% use 'figure', `plot` and all the constant parts of the figure only once, before the loop.
figure(1)
m = plot(momentvalues(1,:),momentheader); % plotting only step 1
xlim([momentvalues(rowminmoment) momentvalues(rowmaxmoment)])
xlabel('Moment (kN.m)')
ylabel('Length of pile (m)')
% loop from step 2 ahead
for k = 2:length(momentvalues)
pause(1); % use pause to set the delay between shots
% use 'set' to change the x values
set(m,'Xdata',momentvalues(k,:));
drawnow
title(sprintf('Moment profile along pile at time 0.2%f',k))
end
I'm trying to save a figure with a no-default dimension, but I always obtain the default size plot.
figure
for i=1:6
for j=1:4
subplot(6,4,j+(i-1)*4)
[...]
end
end
w=600; h=800;
set(gcf,'Position',[30 60 w h]);
set(gcf, 'PaperUnits', 'centimeters');
set(gcf,'PaperPositionMode','manual')
print('test','-depsc');
It is mainly a 6-by-4 subplot. I looked for a solution on internet, I found many comments about Position, PaperUnits, PaperPositionMode, but none has worked so far. The only solution that works is when I export as .fig.
What I actually realized, is that after the set(gcf,'Position',[30 60 w h]) the window dimension of the plot is correct, but the subplot are squeezed like when the dimension is the default. If I just insert a pause and manually resize the window (even by almost nothing), the subplots expand nicely within the larger window. But still, with the print command the result is not the desired one.
I tried also with saveas and I got the same result.
Ah, if I manually save the figure, it works perfectly, but, of course, I need to automatize the process!
Thanks for your help!
Although i can't reproduce this behaviour as MATLAB 2014b automatically handles axes resizing, i'll still post an answer, that may need some adjustments.
Basically, what you need to do is :
% Get a handle to your figure object
Myfig=gcf;
% Get all of your figure Children - Warning : if you have a global
% legend in your figure, it will belong to your figure Children and you
% ll have to ignore it
AllChildren=get(Myfig,'Children');
MyAxes=findobj(AllChildren,'type','axes');
% Now you have your axes objects, whose Position attributes should be in
% normalized units. What you need to do now is to store these positions
% before changing the size of your figure, to reapply them after
% resizing (the beauty of normalized positions).
Positions=zeros(size(MyAxes,1),4);
for ii=1:size(MyAxes,1)
Positions(ii,:)=get(MyAxes(ii),'Position');
end
% Resize your figure
w=600;
h=800;
set(gcf,'Position',[30 60 w h]);
% Reuse the positions you stored to resize your subplots
for ii=1:size(MyAxes,1)
set(MyAxes(ii),'Position',Positions(ii,:));
end
This should do the trick.