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Conversaciones actualizadas
I rarely/never save .fig files
47%
Continue working on it later
16%
Archive for future reference
23%
Share within my organization
10%
Share outside my organization
2%
Other (please leave a comment)
2%
2097 votos
It is April 3, 2025 now. Where is the MATLAB 2025a?
I have written, tested, and prepared a function with four subsunctions on my computer for solving one of the problems in the list of Cody problems in MathWorks in three days. Today, when I wanted to upload or copy paste the codes of the function and its subfunctions to the specified place of the problem of Cody page, I do not see a place to upload it, and the ability to copy past the codes. The total of the entire codes and their documentations is about 600 lines, which means that I cannot and it is not worth it to retype all of them in the relevent Cody environment after spending a few days. I would appreciate your guidance on how to enter the prepared codes to the desired environment in Cody.
I'm getting this annoying survey (screenshot below) in the help windows of MATLAB R2024b this morning. It blocks the text I'm actually trying to read, when minimised it pops up again after a few minutes, and persists even after picking an option and completing the SurveyMonkey survey it links to. I don't even know what the OPC UA server so rest assured any of my answers to that survey aren't going to help MathWorks improve their product.
Starting in MATLAB R2022a, use the append option in exportgraphics to create GIF files from animated axes, figures, or other visualizations.
This basic template contains just two steps:
% 1. Create the initial image file gifFile = 'myAnimation.gif'; exportgraphics(obj, gifFile);
% 2. Within a loop, append the gif image for i = 1:20
% % % % % % %
% Update the figure/axes %
% % % % % % % exportgraphics(obj, gifFile, Append=true); end
Note, exportgraphics will not capture UI components such as buttons and knobs and requires constant axis limits.
To create animations of images or more elaborate graphics, learn how to use imwrite to create animated GIFs .
Share your MATLAB animated GIFs in the comments below!
See Also
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I've long used the Tensor Toolbox from Sandia in order to use tensors in Matlab, but recently found myself wanting to apply it on symbolic arguments, which don't appear supported. Some google-fu'ing resulted in (non-free) Tensorlab and some file-exchange entries of mixed quality. And of course, there's the recent tensorprod, which a) doesn't support symbolics and b) arguments aren't strictly tensors (rather "representations of tensors in a matrix type").
This all got me to thinking that it would be mighty nice to have general / native / comprehensive support for a tensor class in official Matlab - even if it were in a separate toolbox.
No
50%
Yes, but I am not interested
8%
Yes, but it is too expensive
20%
Yes, I would like to know more
18%
Yes, I am cert. MATLAB Associate
2%
Yes, I am cert. MATLAB Professional
3%
4741 votos
Let's say MathWorks decides to create a MATLAB X release, which takes a big one-time breaking change that abandons back-compatibility and creates a more modern MATLAB language, ditching the unfortunate stuff that's around for historical reasons. What would you like to see in it?
I'm thinking stuff like syntax and semantics tweaks, changes to function behavior and interfaces in the standard library and Toolboxes, and so on.
(The "X" is for major version 10, like in "OS X". Matlab is still on version 9.x even though we use "R20xxa" release names now.)
What should you post where?
Next Gen threads (#1): features that would break compatibility with previous versions, but would be nice to have
@anyone posting a new thread when the last one gets too large (about 50 answers seems a reasonable limit per thread), please update this list in all last threads. (if you don't have editing privileges, just post a comment asking someone to do the edit)
Me: If you have parallel code and you apply this trick that only requires changing one line then it might go faster.
Reddit user: I did and it made my code 3x faster
Not bad for just one line of code!
Which makes me wonder. Could it make your MATLAB program go faster too? If you have some MATLAB code that makes use of parallel constructs like parfor or parfeval then start up your parallel pool like this
parpool("Threads")
before running your program.
The worst that will happen is you get an error message and you'll send us a bug report....or maybe it doesn't speed up much at all....
....or maybe you'll be like the Reddit user and get 3x speed-up for 10 seconds work. It must be worth a try...after all, you're using parallel computing to make your code faster right? May as well go all the way.
In an artificial benchmark I tried, I got 10x speedup! More details in my recent blog post: Parallel computing in MATLAB: Have you tried ThreadPools yet? » The MATLAB Blog - MATLAB & Simulink
Give it a try and let me know how you get on.
Hello, everyone! I’m Mark Hayworth, but you might know me better in the community as Image Analyst. I've been using MATLAB since 2006 (18 years). My background spans a rich career as a former senior scientist and inventor at The Procter & Gamble Company (HQ in Cincinnati). I hold both master’s & Ph.D. degrees in optical sciences from the College of Optical Sciences at the University of Arizona, specializing in imaging, image processing, and image analysis. I have 40+ years of military, academic, and industrial experience with image analysis programming and algorithm development. I have experience designing custom light booths and other imaging systems. I also work with color and monochrome imaging, video analysis, thermal, ultraviolet, hyperspectral, CT, MRI, radiography, profilometry, microscopy, NIR, and Raman spectroscopy, etc. on a huge variety of subjects.
I'm thrilled to participate in MATLAB Central's Ask Me Anything (AMA) session, a fantastic platform for knowledge sharing and community engagement. Following Adam Danz’s insightful AMA on staff contributors in the Answers forum, I’d like to discuss topics in the area of image analysis and processing. I invite you to ask me anything related to this field, whether you're seeking recommendations on tools, looking for tips and tricks, my background, or career development advice. Additionally, I'm more than willing to share insights from my experiences in the MATLAB Answers community, File Exchange, and my role as a member of the Community Advisory Board. If you have questions related to your specific images or your custom MATLAB code though, I'll invite you to ask those in the Answers forum. It's a more appropriate forum for those kinds of questions, plus you can get the benefit of other experts offering their solutions in addition to me.
For the coming weeks, I'll be here to engage with your questions and help shed light on any topics you're curious about.
%% 清理环境
close all; clear; clc;
%% 模拟时间序列
t = linspace(0,12,200); % 时间从 0 到 12，分 200 个点
% 下面构造一些模拟的"峰状"数据，用于演示
% 你可以根据需要替换成自己的真实数据
rng(0); % 固定随机种子，方便复现
baseIntensity = -20; % 强度基线（z 轴的最低值）
numSamples = 5; % 样本数量
yOffsets = linspace(20,140,numSamples); % 不同样本在 y 轴上的偏移
colors = [ ...
0.8 0.2 0.2; % 红
0.2 0.8 0.2; % 绿
0.2 0.2 0.8; % 蓝
0.9 0.7 0.2; % 金黄
0.6 0.4 0.7]; % 紫
% 构造一些带多个峰的模拟数据
dataMatrix = zeros(numSamples, length(t));
for i = 1:numSamples
% 随机峰参数
peakPositions = randperm(length(t),3); % 三个峰位置
intensities = zeros(size(t));
for pk = 1:3
center = peakPositions(pk);
width = 10 + 10*rand; % 峰宽
height = 100 + 50*rand; % 峰高
% 高斯峰
intensities = intensities + height*exp(-((1:length(t))-center).^2/(2*width^2));
end
% 再加一些小随机扰动
intensities = intensities + 10*randn(size(t));
dataMatrix(i,:) = intensities;
end
%% 开始绘图
figure('Color','w','Position',[100 100 800 600],'Theme','light');
hold on; box on; grid on;
for i = 1:numSamples
% 构造 fill3 的多边形顶点
xPatch = [t, fliplr(t)];
yPatch = [yOffsets(i)*ones(size(t)), fliplr(yOffsets(i)*ones(size(t)))];
zPatch = [dataMatrix(i,:), baseIntensity*ones(size(t))];
% 使用 fill3 填充面积
hFill = fill3(xPatch, yPatch, zPatch, colors(i,:));
set(hFill,'FaceAlpha',0.8,'EdgeColor','none'); % 调整透明度、去除边框
% 在每条曲线尾部标注 Sample i
text(t(end)+0.3, yOffsets(i), dataMatrix(i,end), ...
['Sample ' num2str(i)], 'FontSize',10, ...
'HorizontalAlignment','left','VerticalAlignment','middle');
end
%% 坐标轴与视角设置
xlim([0 12]);
ylim([0 160]);
zlim([-20 350]);
xlabel('Time (sec)','FontWeight','bold');
ylabel('Frequency (Hz)','FontWeight','bold');
zlabel('Intensity','FontWeight','bold');
% 设置刻度（根据需要微调）
set(gca,'XTick',0:2:12, ...
'YTick',0:40:160, ...
'ZTick',-20:40:200);
% 设置视角（az = 水平旋转，el = 垂直旋转）
view([211 21]);
% 让三维坐标轴在后方
set(gca,'Projection','perspective');
% 如果想去掉默认的坐标轴线，也可以尝试
% set(gca,'BoxStyle','full','LineWidth',1.2);
%% 可选：在后方添加一个浅色网格平面 (示例)
% 这个与题图右上方的网格类似
[Xplane,Yplane] = meshgrid([0 12],[0 160]);
Zplane = baseIntensity*ones(size(Xplane)); % 在 Z = -20 处画一个竖直面的框
surf(Xplane, Yplane, Zplane, ...
'FaceColor',[0.95 0.95 0.9], ...
'EdgeColor','k','FaceAlpha',0.3);
%% 进一步美化（可根据需求调整）
title('3D Stacked Plot Example','FontSize',12);
constantplane("x",12,FaceColor=rand(1,3),FaceAlpha=0.5);
constantplane("y",0,FaceColor=rand(1,3),FaceAlpha=0.5);
constantplane("z",-19,FaceColor=rand(1,3),FaceAlpha=0.5);
hold off;
Have fun! Enjoy yourself!
Hello Community,
We're excited to announce that registration is now open for the MathWorks AUTOMOTIVE CONFERENCE 2025! This event presents a fantastic opportunity to connect with MathWorks and industry experts while exploring the latest trends in the automotive sector.
Event Details:
- Date: April 29, 2025
- Location: St. John’s Resort, Plymouth, MI
Featured Topics:
- Virtual Development
- Electrification
- Software Development
- AI in Engineering
Whether you're a professional in the automotive industry or simply interested in these cutting-edge topics, we highly encourage you to register for this conference.
We look forward to seeing you there!
This topic is for discussing highlights to the current R2025a Pre-release.
We are excited to announce another update to our Discussions area: the new Contribution Widget! The new widget simplifies the process of creating diverse types of content, whether you're praising someone who has helped you, sharing tips and tricks, or polling the community.
Previously, creating various types of content required navigating multiple links or channels. With the new Contribution Widget, everything you need is conveniently located in one place.
Give it a try and let us know how we can further enhance your user experience.
P.S. Who has been particularly helpful to you lately? Create your first praise post and let them know!
We are excited to announce the first edition of the MathWorks AI Challenge. You’re invited to submit innovative solutions to challenges in the field of artificial intelligence. Choose a project from our curated list and submit your solution for a chance to win up to $1,000 (USD). Showcase your creativity and contribute to the advancement of AI technology.
AI Challenge
Submit an innovative solution to a challenge in the field of artificial intelligence as part of the MathWorks AI Challenge and you could win up to $1,000 (USD).
I am pleased to announce the 6th Edition of my book MATLAB Recipes for Earth Sciences with Springer Nature
also in the MathWorks Book Program
It is now almost exactly 20 years since I signed the contract with Springer for the first edition of the book. Since then, the book has grown from 237 to 576 pages, with many new chapters added. I would like to thank my colleagues Norbert Marwan and Robin Gebbers, who have each contributed two sections to Chapters 5, 7 and 9.
And of course, my thanks go to the excellent team at the MathWorks Book Program and the numerous other MathWorks experts who have helped and advised me during the last 30+ years working with MATLAB. And of course, thank you Springer for 20 years of support.
This book introduces methods of data analysis in the earth sciences using MATLAB, such as basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, signal processing, spatial and directional data analysis, and image analysis.
Martin H. Trauth
MATLAB Recipes for Earth Sciences, 6th edition
MATLAB is used in a wide range of geoscientific applications, such as for image processing in remote sensing, for generating and processing digital elevation models, and for analyzing time series. This book introduces methods of data analysis in the earth sciences using MATLAB, such as basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, signal processing, spatial and directional data analysis, and image analysis.
There has been a lot of discussion here about the R2025a Prerelease that has really helped us get it ready for the prime time. Thank you for that!
A new update of the Prerelease has just dropped. So fresh it is still warm from the oven! In my latest blog post I discuss changes in the way MathWorks has been asking-for and processing feedback...and you have all been a part of that.
If you haven't tried the Prerelease in a while, I suggest you update and see how things are looking now.
If you have already submitted a bug report and it hasn't been fixed in this update, you don't need to submit another one. Everything is being tracked!
Have a play, discuss it here and thanks for again for being part of the process.
Speaking as someone with 31+ years of experience developing and using imshow, I want to advocate for retiring and replacing it.
The function imshow has behaviors and defaults that were appropriate for the MATLAB and computer monitors of the 1990s, but which are not the best choice for most image display situations in today's MATLAB. Also, the 31 years have not been kind to the imshow code base. It is a glitchy, hard-to-maintain monster.
My new File Exchange function, imview, illustrates the kind of changes that I think should be made. The function imview is a much better MATLAB graphics citizen and produces higher quality image display by default, and it dispenses with the whole fraught business of trying to resize the containing figure. Although this is an initial release that does not yet support all the useful options that imshow does, it does enough that I am prepared to stop using imshow in my own work.
The Image Processing Toolbox team has just introduced in R2024b a new image viewer called imageshow, but that image viewer is created in a special-purpose window. It does not satisfy the need for an image display function that works well with the axes and figure objects of the traditional MATLAB graphics system.
I have published a blog post today that describes all this in more detail. I'd be interested to hear what other people think.
Note: Yes, I know there is an Image Processing Toolbox function called imview. That one is a stub for an old toolbox capability that was removed something like 15+ years ago. The only thing the toolbox imview function does now is call error. I have just submitted a support request to MathWorks to remove this old stub.
I've been trying this problem a lot of time and i don't understand why my solution doesnt't work.
In 4 tests i get the error Assertion failed but when i run the code myself i get the diag and antidiag correctly.
function [diag_elements, antidg_elements] = your_fcn_name(x)
[m, n] = size(x);
% Inicializar los vectores de la diagonal y la anti-diagonal
diag_elements = zeros(1, min(m, n));
antidg_elements = zeros(1, min(m, n));
% Extraer los elementos de la diagonal
for i = 1:min(m, n)
diag_elements(i) = x(i, i);
end
% Extraer los elementos de la anti-diagonal
for i = 1:min(m, n)
antidg_elements(i) = x(m-i+1, i);
end
end
Hi! I'm Joseff and along with being a student in chemical engineering, one of my great passions is language-learning. I learnt something really cool recently about Catalan (a romance language closely related to Valencian that's spoken in Andorra, Catalonia, and parts of Spain) — and that is how speakers tell the time.
While most European languages stick to the standard minutes-past / minutes-to between hours, Catalan does something really quite special, with a focus on the quarters (quarts [ˈkwarts]). To see what I mean, take a look at this clock made by Penguin___Lover on Instructables :
If you want to tell the time in Catalan, you should refer to the following hour (the one that's still to come), and how many minutes have passed or will pass for the closest quarter (sometimes half-quarter / mig quart [ˈmit͡ʃ kwart]) — clear as mud? It's definitely one of the more difficult things to wrap your head around as a learner. But fear not, with the power of MATLAB, we'll understand in no time!
To make a tool to tell the time in Catalan, the first thing we need to do is extract the current time into its individual hours, minutes and seconds*
function catalanTime = quinahora()
% Get the current time
[hours, minutes, seconds] = hms(datetime("now"));
% Adjust hours to 12-hour format
catalanHour = mod(hours-1, 12)+1;
nextHour = mod(hours, 12)+1;
Then to defining the numbers in catalan. It's worth noting that because the hours are feminine and the minutes are masculine, the words for 1 and 2 is different too (this is not too weird as languages go, in fact for my native Welsh there's a similar pattern between 2 and 4).
% Define the numbers in Catalan
catNumbers.masc = ["un", "dos", "tres", "quatre", "cinc"];
catNumbers.fem = ["una", "dues", "tres", "quatre",...
"cinc", "sis", "set", "vuit",...
"nou", "deu", "onze", "dotze"];
Okay, now it's starting to get serious! I mentioned before that this traditional time telling system is centred around the quarters — and that is true, but you'll also hear about the mig de quart (half of a quarter) * which is why we needed that seconds' precision from earlier!
% Define 07:30 intervals around the clock from 0 to 60
timeMarks = 0:15/2:60;
timeFraction = minutes + seconds / 60; % get the current position
[~, idx] = min(abs(timeFraction - timeMarks)); % extract the closest timeMark
mins = round(timeFraction - timeMarks(idx)); % round to the minute
After getting the fraction of the hour that we'll use later to tell the time, we can look into how many minutes it differs from that set time, using menys (less than) and i (on top of). There's also a bit of an AM/PM distinction, so you can use this function and know whether it's morning or night!
% Determine the minute string (diffString logic)
diffString = '';
if mins < 0
diffString = sprintf(' menys %s', catNumbers.masc(abs(mins)));
elseif mins > 0
diffString = sprintf(' i %s', catNumbers.masc(abs(mins)));
end
% Determine the part of the day (partofDay logic)
if hours < 12
partofDay = 'del matí'; % Morning (matí)
elseif hours < 18
partofDay = 'de la tarda'; % Afternoon (tarda)
elseif hours < 21
partofDay = 'del vespre'; % Evening (vespre)
else
partofDay = 'de la nit'; % Night (nit)
end
% Determine 'en punt' (o'clock exactly) based on minutes
enPunt = '';
if mins == 0
enPunt = ' en punt';
end
Now all that's left to do is define the main part of the string, which is which mig quart we are in. Since we extracted the index idx earlier as the closest timeMark, it's just a matter of indexing into this after the strings have been defined.
% Create the time labels
labels = {sprintf('són les %s%s%s %s', catNumbers.fem(catalanHour), diffString, enPunt, partofDay), ...
sprintf('és mig quart de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('és un quart de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('és un quart i mig de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('són dos quarts de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('són dos quarts i mig de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('són tres quarts de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('són tres quarts i mig de %s%s %s', catNumbers.fem(nextHour), diffString, partofDay), ...
sprintf('són les %s%s%s %s', catNumbers.fem(nextHour), diffString, enPunt, partofDay)};
catalanTime = labels{idx};
Then we need to do some clean up — the definite article les / la and the preposition de don't play nice with un and the initial vowel in onze, so there's a little replacement lookup here.
% List of old and new substrings for replacement
oldStrings = {'les un', 'són la una', 'de una', 'de onze'};
newStrings = {'la una', 'és la una', 'd''una', 'd''onze'};
% Apply replacements using a loop
for i = 1:length(oldStrings)
catalanTime = strrep(catalanTime, oldStrings{i}, newStrings{i});
end
end
quinahora()
So, can you work out what time it was when I made this post? 🤔
And how do you tell the time in your language?
Fins després!
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