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New Cheat Sheet Alert!
Level up your data organization and access skills in MATLAB with our latest cheat sheet! Download the full cheat sheet on MATLAB GitHub for Students here.
Recently, I came across a post about the JIT compiler on this Korean blog. In the post. The writer discussed the concept of the "Compile Threshold" and how it is calculated.
"The JVM accumulates the number of calls for each method called and compiles when the number exceeds a certain number. In other words, there is a standard for checking how often it is called and then deciding, 'It is time to compile.' This standard is called the compilation threshold. But what is this and why should it be used as a standard?"
The concept of the "Compile Threshold," as used above, seems to be more commonly associated with Tracing just-in-time compilation.
The writer used the simple Java code below to calculate the threshold.
for (int i = 0; i < 500; ++i) {
long startTime = System.nanoTime();
for (int j = 0; j < 1000; ++j) {
new Object();
}
long endTime = System.nanoTime();
System.out.printf("%d\t%d\n", i, endTime - startTime);
}
Since the MATLAB execution engine uses JIT compilation, I just wanted to perform the same experiment that the writer did.
I experimented using simple codes based on the code in the blog. I iterated a function 500 time using for-loop and calculated the execution time for each iteration using tic and toc. Then I plotted the execution time for each loop as blow. First five execution times are much higher than followings (10 times!) The test is very rough so I am not sure that I can conclude "MATLAB has Compile Threshold and it is 5!" but this value is actually correct ;-)
t0 = 0;
tfinal = 10;
y0 = [20;20];
timeToRun = zeros(500,1);
for i = 1:500
tStart = tic;
[preypeaks,predatorpeaks] = solvelotka(t0, tfinal, y0);
tEnd = toc(tStart);
timeToRun(i) = tEnd;
end
VS Code Extension for MATLAB was introduced back in April and has been downloaded 75K times since. Do people here use VS Code for writing MATLAB code?
Earlier this year a bunch of MATLAB users got together to talk about their hobbies in a lightning talk format.
  • Using "UIHTML" to create app components and Lightning
  • Creating generative art with MATLAB
  • Making MATLAB run on the Steam Deck (it was a wager)
Do you use MATLAB for hobbies?
https://www.mathworks.com/videos/series/awesome-matlab-projects-lightning-talks-april-5-2023.html
Matt J
Matt J
Last activity 2023-10-15

Do Reinvent the Wheel

Are there Matlab features which intend to satisfy your needs but fail in certain critical areas, forcing you to abandon them completely in favor of your own version or a 3rd party alternative? Perhaps these features are starting to improve with new Matlab releases, but not quickly enough? Share your own frustrations in the comments below.
Here are two of mine:
1. volumeViewier
volumeViewer is 6 years old now. It is fine when you only need to view one 3D image at a time, but I never do. In my work, I am putting several images side-by-side for visual comparison. For such work, you need to be able to programmatically change axis limits and grayscale and use linkprop to reflect these changes across all the images. With 2D image comparison, all that is possible, but volumeViewer supports none of those things. So, I resort to my own 3D viewer
2.Tomographic projection commands RADON and FANBEAM
These commands are provided in the Image Processing Toolbox seemingly for no other reason than to support homework exercises for people taking introductory tomographic imaging courses. They fail in a number of ways for people who need to do serious tomographic imaging work, producing artifacts or nonlinear effects which shouldn't be there. See for example Why isn't FANBEAM linear? or Radon Transform works unexpectedly. Moreover, the toolbox still provides tomographic projectors only for 2D imaging not 3D, even though 64-bit RAM has made volumetric imaging commonplace in Matlab for at least 10 years. Luckily, there are now freely available 3rd party alternatives like TIGRE.
goc3
goc3
Last activity 2023-11-6

Don't Reinvent the Wheel

Have you ever learned that something you were doing manually in MATLAB was already possible using a built-in feature? Have you ever written a function only to later realize (or be told) that a built-in function already did what you needed?
Two such moments come to mind for me.
1. Did you realize that you can set conditional breakpoints? Neither did I, until someone showed me that feature. To do that, open or create a file in the editor, right click on a line number for any line that contains code, and select Set Conditional Breakpoint... This will bring up a dialog wherein you can type any logical condition for which execution should be paused. Before I learned about this, I would manually insert if-statements during debugging. Then, after fixing each bug, I would have to delete those statements. This built-in feature is so much better.
2. Have you ever needed to plot horizontal or vertical lines in a plot? For the longest time, I would manually code such lines. Then, I learned about xline() and yline(). Not only is less code required, these lines automatically span the entire axes while zooming, panning, or adjusting axis limits!
Share your own Aha! moments below. This will help everyone learn about MATLAB functionality that may not be obvious or front and center.
(Note: While File Exchange contains many great contributions, the intent of this thread is to focus on built-in MATLAB functionality.)
Moja
Moja
Last activity 2023-10-13

caret on macbook pro

The carot symbol on my keyboard (ˆ shift+6) doesn't work on matlab. Matlab doesn't recognize it so I can't write any equation with power symbol. I tried every possible solution on the web and it doesn't work. even in the character viewer I don't have any result when I search ''caret".
Exciting news for students! 🚀Simulink Student Challenge 2023 is live! Unleash your engineering skills and compete for exciting rewards. Submission deadline is December 12th, 2023!
https://www.mathworks.com/academia/student-challenge/simulink-student-challenge-2023.html
Adam Danz
Adam Danz
Last activity 2023-10-13

Approximating π with durations

Over the weekend I came across a pi approximation using durations of years and weeks (image below, Wolfram, eq. 89), accurate to 6 digits using the average Gregorian year (365.2425 days).
Here it is in MATLAB. I divided by 1 week at the end rather than multiplying by its reciprocal because you can’t divide a numeric by a duration in MATLAB (1/week).
weeks = @(n)n*days(7);
piApprox = ((years(13)-weeks(6))/years(13) + weeks(3)) / weeks(1)
% piApprox = 3.141593493469302
Here’s a breakdown
  • The first argument becomes 12.885 yrs / 13 yrs or 0.99115
  • Add three weeks: 0.99115 + 3 weeks = 21.991 days
  • The reduced fraction becomes 21.991 days / 7 days
Now it looks a lot closer to the more familiar approximation for pi 22/7 but with greater precision!
Adam Danz
Adam Danz
Last activity 2024-3-6

To hold or not to hold

I'm curious how the community uses the hold command when creating charts and graphics in MATLAB. In short, hold on sets up the axes to add new objects to the axes while hold off sets up the axes to reset when new objects are added.
When you use hold on do you always follow up with hold off? What's your reasoning on this decision?
Can't wait to discuss this here! I'd love to hear from newbies and experts alike!
Calling all students! New to MATLAB or need helpful resources? Check out our MATLAB GitHub for Students repository! Find MATLAB examples, videos, cheat sheets, and more!
Visit the repository here: MATLAB GitHub for Students
The way we've solved ODEs in MATLAB has been relatively unchanged at the user-level for decades. Indeed, I consider ode45 to be as iconic as backslash! There have been a few new solvers in recent years -- ode78 and ode89 for example -- and various things have gotten much faster but if you learned how to solve ODEs in MATLAB in 1997 then your knowledge is still applicable today.
In R2023b, there's a completely new framework for solving ODEs and I love it! You might argue that I'm contractually obliged to love it since I'm a MathWorker but I can assure you this is the real thing!
I wrote it up in a tutorial style on The MATLAB Blog https://blogs.mathworks.com/matlab/2023/10/03/the-new-solution-framework-for-ordinary-differential-equations-odes-in-matlab-r2023b/
The new interface makes a lot of things a much easier to do. Its also setting us up for a future where we'll be able to do some very cool algorithmic stuff behind the scenes.
Let me know what you think of the new functionality and what you think MathWorks should be doing next in the area of ODEs.
The MATLAB Answers community is an invaluable resource for all MATLAB users, providing selfless assistance and support. However, with the emergence of AI-based chatbots, like chatGPT, there may be concerns about the future relevance and utility of the MATLAB Answer community. What are your thoughts?
4 weeks of contests is fun but intense. Next, we recommend 3 things to do as warm-down exercises.
1. Complete 1-minute contest survey
To make future contests better and more appealing to you, we created a 1-minute survey to understand your experience. Your feedback is critical to us!
2. Read 2022 Mini Hack Content Analysis blog post by Dave Bulkin
Dave Bulkin is a developer on the MATLAB Graphics and Charting Team. In the Blog post, @Dave B not only examines the code behind the leading entries, but also introduces you to some new visualization techniques.
3. Solve The Cody First XI – MATLAB Problems for Cricket Fans by Matt Tearle
Matt Tearle is from MathWorks Training Services Team. @Matt Tearle created this problem group to celebrate the 10th anniversary of Cody and the 2022 T20 World Cup (which happened to occur at the same time). Note that the problems can be done without the knowledge of cricket.
Thank you in advance and hope to see you in 2023!
I've now seen linear programming questions pop up on Answers recently, with some common failure modes for linprog that people seem not to understand.
One basic failure mode is an infeasible problem. What does this mean, and can it be resolved?
The most common failure mode seems to be a unbounded problem. What does this mean? How can it be avoided/solved/fixed? Is there some direction I can move where the objective obviously grows without bounds towards +/- inf?
Finally, I also see questions where someone wants the tool to produce all possible solutions.
A truly good exposition about linear programming would probably result in a complete course on the subject, and Aswers is limited in how much I can write (plus I'll only have a finite amount of energy to keep writing.) I'll try to answer each sub-question as separate answers, but if someone else would like to offer their own take, feel free to do so as an answer, since it has been many years for me since I learned linear programming.
The 2022 community contests have concluded! During the 4 weeks, we hope you had a lot of fun and learned some MATLAB skills. Together, we've achieved amazing milestones:
  • 500+ entries and 5,000+ votes created in the Mini Hack 2022 contest.
  • 100,000+ solutions submitted in Cody 10th Anniversary contest
  • 2,000+ participants in both contests
Now, it's time to announce weekly winners and grand prize winners!
Mini Hack - Pick of the MATLAB Graphics Team
We invited the MATLAB Graphics team, the authors of the MATLAB functions used in every entry, to be our Mini Hack judges. Here are their picks in 3 categories:
  • Our Top 3:
Rising Hand by Augusto Mazzei
Object used: fill; Judge comments: Clever code, nice metaphor, kind comments
Above the clouds by Tim
Object used: patch (via VOXview); Judge comments: Very pretty, looks like it could be in a video game
Monocular rivalry by Jenny Bosten
Object used: Image; Judge comments: We spent a too much time trying to figure out what this illusion was doing to our brains
  • Clever use of Charts:
Holiday Festivities at MATropolis! by Anton Kogios
Object used: Bar3; Judge comments: Cute! Nice fireworks!
Ship by Shanshan Wang
Object used: histogram2; Judge comments: We didn't realize there was a ship in the flow data set
A fish for fun by Shanshan Wang
Object used: plot; Judge comments: Nifty and very different from other entries.
Colorful Fibonacci Spiral #3 by Basil Imoberdorf
Object used: scatter; Judge comments: Overlapping markers make for a very cool tunnel-like effect
  • Things we still loved:
Sandstone by Tim
Object used: image; Judge comments: Domain Warping FTW
Jellyfish by Tim
Object used: surface; Judge comments: Clever use of transparency
Congratulations and you should be very proud of yourself! It's a huge achievement that your entry is recognized by the MATLAB Graphics team!
Mini Hack - special category for Week 4
Our Week 4 special category is ‘Holiday’. The winner is Christmas snowman by Simon Thor
Mini Hack - grand prize winners
After an intensive (and very time-consuming) review of votes on winning entries, we have finalized the list of grand prize winners. Huge congratulations! We appreciate the time and effort you spent and the awesome entries you created. Each of you won an Amazon gift card.
Anton Kogios, Brandon Caasenbrood, KARUPPASAMYPANDIYAN M, Teodo, Jenny Bosten, MvLevi, Abdullah Caliskan, Stewart Thomas, Jonas Schlatter, and Tim Davis
Cody 10th Anniversary - surprise prize for 28-day streak winners
We are thrilled to see that 37 players have built a streak of 28 days! Coming back every day to solve problems is an incredible achievement. We decided to show our appreciation by awarding a surprise prize to those 37 players. Congratulations! Each of you will get a MathWorks T-shirt.
Christian Schröder, Stefan Abendroth, Mohammed, Victoria, Vasileios Pasialis, Gerardo Domínguez Ramírez, HH, Anton Kogios, Lizhi Zhu, Marco Fuscà, Armando Longobardi, Monica, Rithik KRT, Ayman, Teodo, Lincoln Poon, Elijah Keifert, siranjeevi gurumani, kazuyoshi kouno, Ryan Koh, Manuela Kaiser, Mehmet OZC, Dyuman Joshi, KOTHAPALLI SRI BRINDA, Gergely Patay, abyss, Takumi, Keita Abe, Petr Cerny, Shubham Shubham, Meredith, Andrew K, Atsushi Ueno, Peter Orthmann, Armando Longobardi, Chuang Tao, and David Romero
Cody 10th Anniversary winners – Week 4
The top 3 players for solving the most problems in week 4 are Christian Schröder, Gerardo Dominguez Ramirez, and Stefan Abendroth, Congratulations! Each of you won an Amazon gift card.
Week 4 lucky winners are Qingrui Liu and Basant Ale.
Cody 10th Anniversary winners – grand prize winners
We know how hard it is to be a top-10 leader in the contest leaderboard! It requires a huge time commitment and advanced MATLAB skills. Congratulations! Each of you will win an Amazon gift card.
Christian Schröder, Stefan Abendroth, Mohammed, Victoria, Vasileios Pasialis, Gerardo Domínguez Ramírez, HH, Anton Kogios, Lizhi Zhu, and Marco Fuscà
Lucky voters and participants
Thank you for your participation in our 2022 contests. You don’t need to be on the top of the leaderboards to win. As we announced, we would give out 20 MathWorks T-shirts to lucky voters and participants of the 2 contests.
Ismail Bera Altan, Robin Stolz, Michael Mellin, Kellan Smith, Neha Shaah, Siranjeevi gurumani, Paul Villain, Andrew Horchler, Meg Noah, Saurabh Chaudhary, Pakize erdogmus, Godfrey Ojerheghan, Selena Mastrodonato, Damir Rasic, Thomas Kjeldsen, Meredith, John Noah Ramiterre, Patience Oliveira, Panda, and Sujeet Kumar Choudhary
On behalf of the MATLAB Central community team, we thank you for joining our celebration of the MATLAB Central community 2022 contests. We hope you enjoyed these contests and look forward to seeing you in next year’s contests.
In Week 3, several new milestones have been achieved! Cody 10th contest has reached the 80,000-solution milestone! Mini Hack has over 400 entries. @Tim Davis’ seashell entry actually inspired a MathWorks blog post. Check it out.
During the last week of this contest, we strongly encourage you to inspire your colleagues, classmates, or friends to vote. Let the world know the beauty of Mathematics. Voters will also have the opportunity to win a MATLAB T-shirt.
MATLAB Mini Hack Winners - Week 3
In week 2, we announced the special category for week 3 is nature. Below are the 3 winners for this category.
Winners of other categories are:
Congratulations! Each of you won a T-shirt. I just heard we have 4 designs of MATLAB T-shirts. Can you collect all of them?
Cody 10th Anniversary Winners - Week 3
  • The top 3 players for solving the most problems in week 3 are Christian Schröder, Marco Fuscà, and Stefan Abendroth, Congratulations! Each of you won an Amazon gift card.
  • As long as you participate, you have the opportunity to win MathWorks T-shirts. Week 3 lucky winners are Luffy Wangand Augusto Mazzei.
What’s new in week 4?
MATLAB Mini Hack 2022:
  • Week 4’s new category is holiday! Halloween is around the corner. What holidays are you celebrating?
  • You are able to leverage Signal Processing Toolbox in your entry.
Cody 10th Anniversary:
Want a MATLAB T-shirt? We have 10 more to give out in the 10 days between now and Oct. 30th. You might win a MATLAB T-shirt by doing any of these activities:
  • Vote on entries you like from the Mini Hack contest
  • Solve Cody problems in the Cody 10th contest
  • Create or remix entries in the Mini Hack contest
The more activities you do, the higher your chance to win. Every day, we will pick a winner.
We had another wonderful week of community contests 2022. In week 2, the voting for Mini Hack started! About 1000 votes have been cast on 300+ entries. In Cody 10th Anniversary contest, we already have 85 finishers for the two special groups: Matrices and Arrays and Plotting and Visualization.
Now, it’s time to announce the weekly winners!
MATLAB Mini Hack Winners - Week 2
Amazing entries keep coming in every day. In week 2, we announced a space category to celebrate the milestone of NASA’s Dart mission. We’ve picked 4 winners for this new category.
Winners of other categories are:
Congratulations! Each of you won a MathWorks T-shirt. If this is the second time you won, you have the option to choose a MathWorks hat or a coffee mug!
Cody 10th Anniversary Winners - Week 2
  • The top 3 players for solving most problems in week 2 are Mohammed, Armando Longobardi, and Stefan Abendroth, Congratulations! Each of you won an Amazon gift card.
  • You don’t need to be an expert or spend tons of time to win! As long as you participate, you have the opportunity to win MathWorks T-shirts. Week 2 lucky winners are Dylan Baker and Takumi.
What’s new in week 3?
MATLAB Mini Hack 2022:
  • Week 3’s new category is nature! We look forward to seeing more nature-themed creative entries from you!
  • You are able to leverage up to 2 File Exchange submissions in your code.
Cody 10th Anniversary: