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The Cody Contest 2025 is underway, and it includes a super creative problem group which many of us have found fascinating. The theme, expertly curated by @Matt Tearle, is humorously centered around the whims of the capricious dictator Lord Ned, as he goes out of his way to complicate the lives of his subjects and visitors alike. We cannot judge whether there's any truth or not to the rumors behind all the inside jokes, but it's obvious the team had a lot of fun creating these; and we had even more fun solving them.
Today I want to showcase a way to graphically solve and visualize one of those problems which I found very elegant, The Bridges of Nedsburg.
To briefly reiterate the problem, the number of islands and the arrangement of bridges of the city of Nedsburg are constantly changing. Lord Ned has decided to take advantage of this fact by charging visitors with an increasingly expensive n-bridge pass which allows them to cross up to n bridges in one journey. Provided the Connectivity Matrix C, we are tasked with calculating the minimum n needed so that there is a path from every island to every other island in n steps or fewer.
Matt kindly provided us with some useleful bit of math in the description detailing how to calculate the way to get from one island to another in an number of m steps. However, he has also hidden an alternative path to the solution in plain sight, in one of the graphs he provided. This involves the extremely useful and versatile object digraph, representing directed graphs, which have directional edges connecting the nodes. Some further useful documentation on the topic for those who are interested in learning more about it:
Directed and Undirected Graphs - MATLAB & Simulink
Graph and Digraph Classes - MATLAB
Let's start using this object to explore a graphical solution to Lord Ned's conundrum. We will use the unit tests included in the problem to visualize the solution. We can retrieve the connectivity matrix for each case using the following function:
function C = getConnectivityMatrix(unit_test)
% Number or islands and arrangement
switch unit_test
case 1
m = 3; idx = [3;4;8];
case 2
m = 3; idx = [3;4;7;8];
case 3
m = 4; idx = [2;7;8;10;13];
case 4
m = 4; idx = [4;5;7;8;9;14];
case 5
m = 5; idx = [5;8;11;12;14;18;22;23];
case 6
m = 5; idx = [2;5;8;14;20;21;24];
case 7
m = 6; idx = [3;4;7;11;18;23;24;26;30;32];
case 8
m = 6; idx = [3;11;12;13;18;19;28;32];
case 9
m = 7; idx = [3;4;6;8;13;14;20;21;23;31;36;47];
case 10
m = 7; idx = [4;11;13;14;19;22;23;26;28;30;34;35;37;38;45];
case 11
m = 8; idx = [2;4;5;6;8;12;13;17;27;39;44;48;54;58;60;62];
case 12
m = 8; idx = [3;9;12;20;24;29;30;31;33;44;48;50;53;54;58];
case 13
m = 9; idx = [8;9;10;14;15;22;25;26;29;33;36;42;44;47;48;50;53;54;55;67;80];
case 14
m = 9; idx = [8;10;22;32;37;40;43;45;47;53;56;57;62;64;69;70;73;77;79];
case 15
m = 10; idx = [2;5;8;13;16;20;24;27;28;36;43;49;53;62;71;75;77;83;86;87;95];
case 16
m = 10; idx = [4;9;14;21;22;35;37;38;44;47;50;51;53;55;59;61;63;66;69;76;77;84;85;86;90;97];
end
C = zeros(m);
C(idx) = 1;
end
The case in the example refets to unit test case 2.
unit_test = 2;
C = getConnectivityMatrix(unit_test);
disp(C)
0 1 1 0 0 1 1 0 0
We now calculate the digraph object D, and visualize it using its corresponding plot method:
D = digraph(C);
figure
p = plot(D,'LineWidth',1.5,'ArrowSize',10);
This is the same as the graph provided in the example. Another very useful method of digraph is shortestpath. This allows you to calculate the path and distance from one single node to another. For example:
% Path and distance from node 1 to node 2
[path12,dist12] = shortestpath(D,1,2);
fprintf('The shortest path from island %d to island %d is: %s. The minimum number of steps is: n = %d\n', 1, 2, join(string(path12), ' -> '),dist12)
The shortest path from island 1 to island 2 is: 1 -> 2. The minimum number of steps is: n = 1
% Path and distance from node 2 to node 1
[path21,dist21] = shortestpath(D,2,1);
fprintf('The shortest path from island %d to island %d is: %s. The minimum number of steps is: n = %d\n', 2, 1, join(string(path21), ' -> '),dist21)
The shortest path from island 2 to island 1 is: 2 -> 3 -> 1. The minimum number of steps is: n = 2
We can visualize these using the highlight method of the graph plot:
figure
p = plot(D,'LineWidth',1.5,'ArrowSize',10);
highlight(p,path12,'EdgeColor','r','NodeColor','r','LineWidth',2)
highlight(p,path21,'EdgeColor',[0 0.8 0],'LineWidth',2)
But that's not all! digraph can also provide us with a matrix of the distances D, i.e. the steps needed to travel from island i to island j, where i and j are the rows and columns of D respectively. This is accomplished by using its method distances. The distance matrix can be vizualized as:
d = distances(D);
figure
% Using pcolor w/ appending matrix workaround for convenience
pcolor([d,d(:,end);d(end,:),d(end,end)]);
% Alternatively you can use imagesc(d), but you'll have to recreate the grid manually
axis square
set(gca,'YDir','reverse');
set(gca,{'XTick','YTick'},{[],[]});
[X,Y] = meshgrid(1:height(d));
text(X(:)+0.5,Y(:)+0.5,string(d(:)),'FontSize',11)
colormap(interp1(linspace(0,1,4), [1 1 1; 0.7 0.9 1; 0.6 0.7 1; 1 0.3 0.3], linspace(0,1,8)))
clim([-0.5 7+0.5])
This confirms what we saw before, i.e. you need 1 step to go from island 1 to island 2, but 2 steps for vice versa. It also confirms that the minimum number of steps n that you need to buy the pass for is 2 (which also occurs for traveling from island 3 to island 2). As it's not the point of the post to give the full solution to the problem but rather present the graphical way of visualizing it I will not include the code of how to calculate this, but I'm sure that by now it's reduced to a trivial problem which you have already figured out how to solve.
That being said, now that we have the distance matrix, let's continue with the visualizations. First, let's plot the corresponding routes that each of these combinations:
figure
tiledlayout(size(C,1),size(C,2),'TileSpacing','tight','Padding','tight');
for i = 1:size(C,1)
for j = 1:size(C,2)
nexttile
hold on
box on
set(gca,{'XTick','YTick'},{[],[]});
p = plot(D,'ArrowSize',10);
highlight(p,shortestpath(D,i,j),'EdgeColor','r','NodeColor','r','LineWidth',2);
lims = axis;
text(lims(1)+diff(lims(1:2))*0.05,lims(3)+diff(lims(3:4))*0.9,sprintf('n = %d',d(i,j))) % Or use from shortest path
end
end
This allows us to go from the distance matrix to vizualizing the routes and number of steps for each corresponding case. Things are rather simple for the this 3-island example case, but evil Lord Ned is just getting started. Let's now try to solve to problem for all provided unit test cases:
% Cell array of connectivity matrices
C = arrayfun(@getConnectivityMatrix,1:16,'UniformOutput',false);
% Cell array of corresponding digraph objects
D = cellfun(@digraph,C,'UniformOutput',false);
% Cell array of corresponding distance matrices
d = cellfun(@distances,D,'UniformOutput',false);
% id of solutions: Provided as is to avoid handing out the code to the full solution
id = [2, 2, 9, 3, 4, 6, 16, 4, 44, 43, 33, 34, 7, 18, 39, 2];
First, let's plot the distance matrix for each case:
figure
tiledlayout('flow','TileSpacing','compact','Padding','compact');
% Vary this to plot different combinations of cases
plot_cases = 1:numel(C);
for i = plot_cases
nexttile
hold on
box on
axis tight square
pcolor([d{i},d{i}(:,end);d{i}(end,:),d{i}(end,end)]);
set(gca,'YDir','reverse');
set(gca,{'XTick','YTick'},{[],[]});
title(sprintf('Case %d',i),'FontWeight','normal','FontSize',8)
end
c = colorbar('Ticks',0:7,'TickLength',0,'Limits',[-0.5 7+0.5],'FontSize',8);
c.Layout.Tile = 'East';
c.Label.String = 'Number of Steps';
c.Label.FontSize = 8;
colormap(interp1(linspace(0,1,4), [1 1 1; 0.7 0.9 1; 0.6 0.7 1; 1 0.3 0.3], linspace(0,1,8)))
clim(findobj(gcf,'type','axes'),[-0.5 7+0.5])
We immediately notice some inconsistencies, perhaps to be expected of the eccentric and cunning dictator. Things are pretty simple for the configurations with a small number of islands, but the minimum number of steps n can increase sharply and disproportionally to the additional number of islands. Cases 8 and 9 in particular have a relatively large n (proportional to their grid dimensions), and case 14 has the largest n, almost double that of case 16 despite the fact that the latter has one extra island.
To visualize how this is possible, let's plot the route corresponding to the largest n for each case (though note that there might be multiple possible routes for each case):
figure
tiledlayout('flow','TileSpacing','tight','Padding','tight');
for i = plot_cases
nexttile
hold on
box on
set(gca,{'XTick','YTick'},{[],[]});
% Changing the layout to circular so we can better visualize the paths
p = plot(D{i},'ArrowSize',10,'Layout','Circle');
% Alternatively we could use the XData and YData properties if the positions of the islands were provided
axis([-1.5 1.5 -1.5 1.75])
[row,col] = ind2sub(size(d{i}),id(i));
highlight(p,shortestpath(D{i},row,col),'EdgeColor','r','NodeColor','r','LineWidth',2);
lims = axis;
text(lims(1)+diff(lims(1:2))*0.05,lims(3)+diff(lims(3:4))*0.9,sprintf('n = %d',d{i}(row,col)),'HorizontalAlignment','Left')
end
And busted! Lord Ned has been exposed to be taking advantages of the tectonic forces and has clearly instructed his corrupted civil engineer lackeys to design the bridges to purposely have the visitors go around in circles in order to drain them of their precious savings. In particular, for cases 8 and 9, he would have them go through each single island just to get from a single island to another, whereas for case 14 they would have to visit 8 of the 9 islands just to get to their destination. If that's not diabolical then I don't know what is!
Ned jokes aside, I hope you enjoyed this contest just as much as I did, and that you found this article useful. I look forward to seeing more creative problems and solutions in the future.
Adam Danz
Adam Danz
Last activity about 8 hours ago

Sparklines and interactive data exploration

It’s exciting to dive into a new dataset full of unfamiliar variables but it can also be overwhelming if you’re not sure where to start. Recently, I discovered some new interactive features in MATLAB live scripts that make it much easier to get an overview of your data. With just a few clicks, you can display sparklines and summary statistics using table variables, sort and filter variables, and even have MATLAB generate the corresponding code for reproducibility.
The Graphics and App Building blog published an article that walks through these features showing how to explore, clean, and analyze data—all without writing any code.
If you’re interested in streamlining your exploratory data analysis or want to see what’s new in live scripts, you might find it helpful:
Exploratory Data Analysis using Sparklines and Summary Statistics in Live Scripts
If you’ve tried these features or have your own tips for quick data exploration in MATLAB, I’d love to hear your thoughts!
idris
idris
Last activity about 6 hours ago

Awards vs Background

In the FAQs, I saw the procedure to download the "mobile background", is the the same thing as an award? If yes, good, else how can we get an award and what are the available ones?
iaabdulhameed@knu.ac.kr
idris
idris
Last activity about 16 hours ago

Appreciation

Glad to have watched the session, especially the part when the speaker, Arthur gave an answer to my question on "speech recognition use case" in Avionics.
What a fantastic start to Cody Contest 2025! In just 2 days, over 300 players joined the fun, and we already have our first contest group finishers. A big shoutout to the first finisher from each team:
  • Team Creative Coders: @Mehdi Dehghan
  • Team Cool Coders: @Pawel
  • Team Relentless Coders: @David Hill
  • 🏆 First finisher overall: Mehdi Dehghan
Other group finishers: @Bin Jiang (Relentless), @Mazhar (Creative), @Vasilis Bellos (Creative), @Stefan Abendroth (Creative), @Armando Longobardi (Cool), @Cephas (Cool)
Kudos to all group finishers! 🎉
Reminder to finishers: The goal of Cody Contest is learning together. Share hints (not full solutions) to help your teammates complete the problem group. The winning team will be the one with the most group finishers — teamwork matters!
To all players: Don’t be shy about asking for help! When you do, show your work — include your code, error messages, and any details needed for others to reproduce your results.
Keep solving, keep sharing, and most importantly — have fun!
The main round of Cody Contest 2025 kicks off today! Whether you’re a beginner or a seasoned solver, now’s your time to shine.
Here’s how to join the fun:
  • Pick your team — choose one that matches your coding personality.
  • Solve Cody problems — gain points and climb the leaderboard.
  • Finish the Contest Problem Group — help your team win and unlock chances for weekly prizes by finishing the Cody Contest 2025 problem group.
  • Share Tips & Tricks — post your insights to win a coveted MathWorks Yeti Bottle.
  • Bonus Round — 2 players from each team will be invited to a fun live code-along event!
  • Watch Party – join the big watch event to see how top players tackle Cody problems
Contest Timeline:
  • Main Round: Nov 10 – Dec 7, 2025
  • Bonus Round: Dec 8 – Dec 19, 2025
Big prizes await — MathWorks swag, Amazon gift cards, and shiny virtual badges!
We look forward to seeing you in the contest — learn, compete, and have fun!
Hi everyone!
I’m Kishen Mahadevan, Senior Product Manager at MathWorks, where I focus on controls and deep learning. I’m excited to be speaking at MATLAB EXPO this year!
In one of my sessions, I’ll share how AI-based reduced order models (ROMs) are transforming engineering workflows—using battery fast charging as an example—making it easier to reuse high-fidelity models for real-time control and deployment.
I’d love to have you join the conversation at the EXPO and right here in the community!
Feel free to drop any questions or thoughts ahead of the event.
Check out my sessions.
Jack and Cleve had famously noted in the "A Preview of PC-MATLAB" in 1985: For those of you that have not experienced MATLAB, we would like to try to show you what everybody is excited about ... The best way to appreciate PC-MATLAB is, of course, to try it yourself.
Try out the end-to-end workflow of developing touchless applications with both MathWorks' tools and STM Dev Cloud from last year!
https://github.com/Brenda-MW/WaveYourWay_Workshop
You can check out the exercises and the manual.
You can also register this year's EXPO. Join the Hands-On workshops to learn the latest features that make the design and deployment workflow even easier!
Show Results
Hey Creative Coders! 😎
Let’s get to know each other. Drop a quick intro below and meet your teammates! This is your chance to meet teammates, find coding buddies, and build connections that make the contest more fun and rewarding!
You can share:
  • Your name or nickname
  • Where you’re from
  • Your favorite coding topic or language
  • What you’re most excited about in the contest
Let’s make Team Creative Coders an awesome community—jump in and say hi! 🚀
Welcome to the Cody Contest 2025 and the Creative Coders team channel! 🎉
You think outside the box. Where others see limitations, you see opportunities for innovation. This is your space to connect with like-minded coders, share insights, and help your team win. To make sure everyone has a great experience, please keep these tips in mind:
  1. Follow the Community Guidelines: Take a moment to review our community standards. Posts that don’t follow these guidelines may be flagged by moderators or community members.
  2. Ask Questions About Cody Problems: When asking for help, show your work! Include your code, error messages, and any details needed to reproduce your results. This helps others provide useful, targeted answers.
  3. Share Tips & Tricks: Knowledge sharing is key to success. When posting tips or solutions, explain how and why your approach works so others can learn your problem-solving methods.
  4. Provide Feedback: We value your feedback! Use this channel to report issues or share creative ideas to make the contest even better.
Have fun and enjoy the challenge! We hope you’ll learn new MATLAB skills, make great connections, and win amazing prizes! 🚀
Get ready to roll up your sleeves at MATLAB EXPO 2025 – our global online event is back, and this year we’re offering 10 hands-on workshops designed to spark innovation and deepen your skills with MATLAB Online and Simulink Online.
Whether you're exploring AI, modeling batteries, or building carbon trackers, these live workshops are your chance to:
  • Work directly in MATLAB and Simulink Online
  • Solve real-world challenges with guidance from MathWorks experts
  • Connect with peers across industries
  • Ask questions and get live feedback
Join the Experience to learn more about each workshop below!
Which workshop are you most excited to attend?!
Day 1:
  • Beyond the Labels: Leveraging AI Techniques for Enlightened Product Choices
  • A Hands-On Introduction to Reinforcement Learning with MATLAB and Simulink
  • Curriculum Development with MATLAB Copilot and Generative AI
  • Simscape Battery Workshop
  • Generating Tests for your MATLAB code
Day 2:
  • Hands-On AI for Smart Appliances: From Sensor Data to Embedded Code
  • A Hands-On Introduction to Reduced Order Modeling with MATLAB and Simulink
  • Introduction to Research Software and Development with Simulink
  • Hack Your Carbon Impact: Build and Publish an Emissions Tracker with MATLAB
  • How to Simulate Scalable Cellular and Connectivity Networks: A Hands-On Session
We look forward to Accelerating the Pace of Engineering and Science together!
Mary Ann Freeman
Mary Ann Freeman
Last activity on 27 Oct 2025 at 2:33

AI Is Transforming Engineering Workflows

It’s an honor to deliver the keynote at MATLAB EXPO 2025. I'll explore how AI changes the game in engineered systems, bringing intelligence to every step of the process from design to deployment. This short video captures a glimpse of what I’ll share:
https://www.youtube.com/watch?v=90JOxCheurk
What excites or challenges you about this shift? Drop a comment or start a thread!
David
David
Last activity on 20 Oct 2025 at 21:26

Shortcut to MATLAB Online - matlab.new

I just learned you can access MATLAB Online from the following shortcut in your web browser: https://matlab.new
Thanks @Yann Debray
From his recent blog post: pip & uv in MATLAB Online » Artificial Intelligence - MATLAB & Simulink
Arkadiy Turevskiy
Arkadiy Turevskiy
Last activity on 15 Oct 2025 at 16:08

AI for Control Design

Please share with us how you are using AI in your control design workflows and what you want to hear most in our upcoming talk, 4 Ways to Improve Control Design Workflows with AI.
Arkadiy
Hello Everyone, I’m Vikram Kumar Singh, and I’m excited to be part of this amazing MATLAB community!
I’m deeply interested in learning more from all of you and contributing wherever I can. Recently, I completed a project on modeling and simulation of a Li-ion battery with a Battery Management System (BMS) for fault detection and management.
I’d love to share my learnings and also explore new ideas together with this group. Looking forward to connecting and growing with the community!