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I’ve installed Claude-code, MATLAB MCP Core Server, and now Puppeteer on my MacBook Pro. Puppeteer can navigate and operate web pages like Perplexity Comet or the new Claude Chrome Extension. The new wrinkle is MATLAB in the loop.
Claude-code and MATLAB MCP installation are described at Experiments with Claude code and MATLAB MPC Core Server . To install and configure Puppeteer, I used Claude App and its ability to use my MATLAB’s access to system files. The installation includes a Google Chrome for testing browser that is independent of (and does not interfere with) my normal Chrome browser. Puppeteer installation took just minutes of my approving various steps, and quitting and relaunchinbg Claude App. A minor hiccough was overwriting a special fetch connector configuration but that was readily fixed. The resulting linkage is Claude (cloud) ↔ Claude Desktop App ↔ MCP Server (local) ↔ Puppeteer ↔ Chrome for Testing (local) as well as the link to MATLAB on my laptop.
As a very first test, I selected Wikipedia from the Claude App suggestions. We navigated to a page Lorenz system in the Chrome for testing browser where Claude dismissed a prompt for donations to Wikipedia. ( I was like “What is Anthropic’s valuation and why didn’t you donate?” but said nothing.) and extracted content and summarized, many of the equations beautifully formated. I issued the following prompt: “Take a look at the differential equations there and at the example solutions and their parameter values. Then create a MATLAB script in my folder MATLAB/ClaudePuppeteer to reproduce the illustrations and run the script.” After clicking to approve various steps, presto.
The screen shot below shows 1) Claude App (upper left) after the process completed, 2) a MacOS Finder window showing the Lorentz Attractor.m in a folder ClaudePuppeteer that Claude had previously created for me to test Puppeteer functionality, 3) the Lorentz system wiki page in the Google Chrome for testing browser (lower right), 4) the LorentzAttractor script open in MATLAB (upper right), and 5) various figures created by the MATLAB Script.
Um, wow!
Introduction
MPC is an open protocol that can link Claude and other AI Apps to MATLAB using MATLAB MCP Core Server (released in Nov 2025). For an introduction, see Exploring the MATLAB Model Context Protocol (MCP) Core Server with Claude Desktop. Here, I describe my experience with installation and testing Claude-Code and MATLAB, a security concern, and in particular how I "taught" Claude to handle various MATLAB file formats.
Setup
A basic installation requires you download for your operating system claude-code, matlab-mcp-core-server, and node.js. One configuration is a terminal-launched claude connected to MATLAB. To connect Claude App to MATLAB requires an alternate configuration step and I recommend it for interative use. The configuration defines the default node/folder and MATLAB APP location.
I recommend using Claude itself to guide you through the installation and configuration steps for your operating system by providing terminal commands. I append Claude’s general description of installation for my APPLE Silicon laptop. Once set up, just ask in Claude App to do something in MATLAB and MATLAB App will be launched.
Security warning: Explore the following at your own risk.
When working with Claude App, Claude code, and MATLAB, you are granting Claude AI access to read and write files. By default, you must approve (one time or forever) any action so you hopefully don’t clobber files etc. Claude App believes it can not directly access file outside the top node defined in the setup. For this reason, I set the top node to be a folder ..../Documents/MATLAB. However, Claude inherits MATLAB App's command line privileges, typically your full system privileges. Claude can describe for you some work-arounds like a Docker container which might still be license validation compatible. I have not explored such options. During my setup, Claude just provided me terminal commands to copy and run. After setup, I've demonstrated it can run system level commands via matlab:evaluate_matlab_code and the MCP server. Be careful out there!
My first test
Claude can write a text-based .m script, execute it, collect text standard output from it, and open files it makes (or any file). It cannot access figures that you might see in MATLAB App unless they are saved as files or embedded in files. As we will see, the figures generated by a Live Script are saved in an Claude-accessible format when the Live Script is saved so the code need not itself export them.
In the screen shot below, the window at left is the Claude App after a successful connection. The MATLAB App window shows a script in the MATLAB editor that simulates a ballistics experiment, the script created successfully with a terminal-interfaced Claude and a simple prompt on the first try.
I deliberately but trivially broke this script using MATLAB App interactively by commenting out a needed variable g (acceleration of gravity) and saving the script to the edit was accessible to Claude. Using Claude App after its connection, I fixed the script with a simple prompt and ran it successfully to make the figure you see. The visible MATLAB didn’t know the code had been altered and fixed by Claude until I reloaded the file. Claude recommends plots be saved in PNG or JPEG, not PDF. It can describe in detail a plot in a PNG and thusly judge if the code is functioning correctly.
Live Scripts with Claude
What about Live Scripts (.mlx) and the (2025a) .m live? A .mlx file is a zipped package of files mixing code and images wtih XML markup. You can peek inside one and edit it directly without unzipping and rezipping it using a tool like BBEdit on a Mac, as shown below. This short test script has two interactive slider controls. You can in v2025+ now save a .mlx in a transportable .m Live text file format. The .mlx and .m Live formats have special markup for formatted text, interactive features like sliders, and figures.
Claude can convert a vanilla .m file to .mlx using matlab.internal.liveeditor.openAndSave(source.m, dest.mlx) and the reverse matlab.internal.liveeditor.openAndConvert('myfile.mlx', 'myfile.m’).
These functions do not support .m Live yet apparently. It would be great if they did.
Vanilla Claude doesn’t know all the details of the .mlx and .m formats yet. To teach Claude these formats, I created a simple .mlx with interactive features (sliders), saved it, and exported it to .m Live. I then sketched for Claude these structures. Claude digested these files and was then able to create such formats from scratch immediately. Wow! In the figure below, you see Claude on the left after creating a .mlx with sliders from scratch. The successfully executed Live Script appears in the MATLAB App.
Once Claude knows the .mlx format, it can peek inside a saved .mlx, process a PNG figure saved there, and describe it, as illustrated below. Here you see Claude describing a plot it found in the .mlx shown in the MATLAB window.
Wrap up
This summarizes my first look at using claude-code. The generation of simple MATLAB codes with the latest models is increasingly trivial with Claude, Perplexity, Open.ai GPT and other apps and the direct method of code and other file transfer between a native MATLAB and Claude seems to beat a copy-paste workflow. New methods to connect MATLAB Online with commercial AI's like Comet and Anthropic's Chrome extension seem to me more fluid and intuitive in that the user and the AI are co-working the same interface without copy-paste steps, but seem slower.
Appendix
Here are installation and setup instructions for Mac from Claude for reference.
Setting Up Claude Code + MATLAB MCP Server on Mac
Part 1: Claude Code
Install via npm:
bash
npm install -g @anthropic-ai/claude-code
Or via Homebrew:
bash
brew install claude-code
Run it:
bash
cd /path/to/your/project
claude
You'll need to authenticate with your Anthropic account on first run. Claude Code works in your terminal and can read/write files, run commands, and do agentic coding tasks.
Part 2: MATLAB MCP Server
Step 1: Download the server binary
Go to the MathWorks GitHub or File Exchange and download matlab-mcp-core-server for macOS (Apple Silicon or Intel depending on your Mac).
Step 2: Make it executable
bash
chmod +x ~/Downloads/matlab-mcp-core-server
Step 3: Create/edit Claude Desktop config
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
json
{
"mcpServers": {
"matlab": {
"command": "/Users/YOURUSERNAME/Downloads/matlab-mcp-core-server",
"args": ["--matlab-root", "/Applications/MATLAB_R2025a.app"]
},
"filesystem": {
"command": "npx",
"args": [
"@modelcontextprotocol/server-filesystem",
"/Users/YOURUSERNAME/Documents/MATLAB"
]
}
}
}
Replace YOURUSERNAME with your actual username, and adjust the MATLAB version if needed.
Step 4: Install Node.js (if not already)
bash
brew install node
Step 5: Restart Claude Desktop
Quit fully (Cmd+Q) and reopen. You should see a hammer/tools icon indicating MCP servers are connected.
Part 3: Verify Connection
In Claude Desktop, ask me to run MATLAB code. I should be able to execute:
matlab
disp('Hello from MATLAB!')
Troubleshooting
Check logs:
bash
cat ~/Library/Logs/Claude/mcp-server-matlab.log
cat ~/Library/Logs/Claude/mcp.log
Common issues:
- Missing --matlab-root argument → "no valid MATLAB environments found"
Connecting Claude App to MATLAB via MCP Server
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
json
{
"mcpServers": {
"filesystem": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-filesystem",
"/Users/YOURUSERNAME/Documents/MATLAB"
]
},
"matlab": {
"command": "/Users/YOURUSERNAME/Downloads/matlab-mcp-core-server",
"args": [
"--matlab-root", "/Applications/MATLAB_R2025a.app"
]
}
}
}
Then fully quit Claude Desktop (Cmd+Q) and reopen.
Comet browser can figure out and operate a user interface on the web including MATLAB Online. The screen shot shows MATLAB online to the left of the Comet AI. You see a test Live Script with sliders thjat Comet created in a folder (that it created). Comet is summarizing suggested improvements it requested of MATLAB Online's Copilot. Comet can plow into the arcane NASA astrophysical database interface SIMBAD, figure out how to grab information about, say, a star orbiting the black hole in the center of our galaxy and structure that information into a MATLAB data structure in a MATLAB script and run the script in MATLAB Online and display the results in the structure - it succeeded on the first try. It can do a Google Scholar citation tree search and park the results in MATLAB (success first try) or presumably in say MS Word in Office online. Presumably it can switch to a JuypterHub tab to then run a notebook or what you will. It can make mistakes, explore and discover GUI options, and recover e.g. use undo paste in MATLAB, operate in the command window, get help via the GUI if needed. Not at light speed but this seems enabling. Just released, Claude Chrome Extension Beta has similar capabilities.
Inspired in part by Christmas Trees, I'm curious about people's experience using AI to generate Matlab code.
1. Do you use AI to generate production code or just for experimentation/fun code?
2. Do you use the AI for a complete solution? Or is it more that the AI gets you most of the way there and you have to apply the finishing touches manually?
3. What level of quality would you consider the generated code? Does it follow "standard" Matlab coding practices? Is it well commented? Factored into modular functions? Argument checking? Memory efficient? Fast execution? Etc.?
4. Does the AI ever come up with a good or clever solution of which you wouldn't have thought or maybe of which you weren't even aware?
5. Is it easy/hard to express your requirements in a manner that the AI tool effectively translates into something useful?
6. Any other thoughts you'd care to share?
I thought it would be fun to vibe code Christmas trees.
Model: Claude Sonnet4.5
Prompt: Write a MATLAB script that draws a Christmas tree. There should be decorations and presents too.
Result:
christmasTree()
function christmasTree()
% Christmas Tree with Decorations and Presents
% Creates a festive scene with a decorated tree and gift boxes
figure('Color', 'w', 'Position', [100, 100, 800, 900]);
hold on;
axis equal;
axis off;
xlim([-3, 3]);
ylim([0, 10]);
% Draw the tree (three layered triangular sections)
drawTreeSection(0, 2, 2.5, 2.5, [0.1, 0.5, 0.1]);
drawTreeSection(0, 3.5, 2, 2, [0.15, 0.55, 0.15]);
drawTreeSection(0, 4.8, 1.5, 1.8, [0.2, 0.6, 0.2]);
% Tree trunk
rectangle('Position', [-0.3, 0, 0.6, 2], 'FaceColor', [0.4, 0.2, 0.1], ...
'EdgeColor', 'none');
% Add decorations
addOrnaments();
addTinsel();
% Star on top
drawStar(0, 7.2, 0.4, [1, 0.84, 0]);
% Add presents under the tree
drawPresent(-1.8, 0, 0.6, 0.5, [0.8, 0.1, 0.1], [1, 0.84, 0]);
drawPresent(-0.8, 0, 0.5, 0.6, [0.1, 0.3, 0.8], [0.9, 0.9, 0.9]);
drawPresent(1.2, 0, 0.7, 0.4, [0.7, 0.5, 0.9], [0.2, 0.8, 0.2]);
drawPresent(0.2, 0, 0.4, 0.5, [1, 0.7, 0.1], [0.8, 0.1, 0.1]);
% Add some snow on the ground
scatter(randn(1, 100)*2.5, rand(1, 100)*0.3, 20, 'w', 'filled', ...
'MarkerEdgeColor', [0.8, 0.8, 0.8]);
title('Merry Christmas!', 'FontSize', 24, 'Color', [0.8, 0.1, 0.1], ...
'FontWeight', 'bold');
hold off;
end
function drawTreeSection(x, y, width, height, color)
% Draw a triangular section of the tree
xPoints = [x - width, x + width, x];
yPoints = [y, y, y + height];
fill(xPoints, yPoints, color, 'EdgeColor', [0.05, 0.3, 0.05], ...
'LineWidth', 1.5);
end
function addOrnaments()
% Add colorful baubles to the tree
ornamentColors = [
1, 0, 0; % Red
0, 0, 1; % Blue
1, 0.84, 0; % Gold
0.9, 0.1, 0.5;% Pink
0.5, 0, 0.5 % Purple
];
% Ornament positions (x, y coordinates)
positions = [
-1.5, 2.5; 1.5, 2.5; 0, 3.2;
-1.2, 3.8; 1.2, 3.8; -0.6, 4.2; 0.6, 4.2;
-0.8, 5.2; 0.8, 5.2; 0, 5.8; -0.4, 6.3; 0.4, 6.3
];
for i = 1:size(positions, 1)
colorIdx = mod(i-1, size(ornamentColors, 1)) + 1;
x = positions(i, 1);
y = positions(i, 2);
% Draw bauble
theta = linspace(0, 2*pi, 50);
radius = 0.15;
xCirc = x + radius * cos(theta);
yCirc = y + radius * sin(theta);
fill(xCirc, yCirc, ornamentColors(colorIdx, :), ...
'EdgeColor', ornamentColors(colorIdx, :)*0.7, 'LineWidth', 1.5);
% Add highlight for shine
highlightX = x - radius*0.4 + radius*0.3*cos(theta(1:15));
highlightY = y + radius*0.4 + radius*0.3*sin(theta(1:15));
fill(highlightX, highlightY, [1, 1, 1], 'EdgeColor', 'none', ...
'FaceAlpha', 0.6);
end
end
function addTinsel()
% Add sparkly tinsel effect
tinselX = [-1.8, -1.2, -0.5, 0.2, 0.9, 1.6];
tinselY = [2.8, 3.5, 4.0, 4.5, 5.0, 5.5];
for i = 1:length(tinselX)
plot(tinselX(i) + randn(1, 5)*0.1, tinselY(i) + rand(1, 5)*0.2, ...
'*', 'Color', [1, 0.84, 0], 'MarkerSize', 8, 'LineWidth', 1.5);
end
end
function drawStar(x, y, size, color)
% Draw a 5-pointed star on top of the tree
angles = linspace(0, 2*pi, 11);
radii = repmat([size, size*0.4], 1, 5);
radii = [radii, radii(1)];
xStar = x + radii .* cos(angles - pi/2);
yStar = y + radii .* sin(angles - pi/2);
fill(xStar, yStar, color, 'EdgeColor', [0.8, 0.6, 0], 'LineWidth', 2);
% Add sparkle
plot(x, y, '*', 'Color', [1, 1, 1], 'MarkerSize', 15, 'LineWidth', 2);
end
function drawPresent(x, y, width, height, boxColor, ribbonColor)
% Draw a gift box with ribbon and bow
% Box
rectangle('Position', [x, y, width, height], 'FaceColor', boxColor, ...
'EdgeColor', boxColor*0.7, 'LineWidth', 2);
% Vertical ribbon
ribbonWidth = width * 0.15;
rectangle('Position', [x + width/2 - ribbonWidth/2, y, ribbonWidth, height], ...
'FaceColor', ribbonColor, 'EdgeColor', 'none');
% Horizontal ribbon
ribbonHeight = height * 0.15;
rectangle('Position', [x, y + height/2 - ribbonHeight/2, width, ribbonHeight], ...
'FaceColor', ribbonColor, 'EdgeColor', 'none');
% Bow on top
bowX = x + width/2;
bowY = y + height;
bowSize = width * 0.2;
% Left loop
theta = linspace(0, pi, 30);
fill(bowX - bowSize*0.3 + bowSize*0.5*cos(theta), ...
bowY + bowSize*0.5*sin(theta), ribbonColor, 'EdgeColor', 'none');
% Right loop
fill(bowX + bowSize*0.3 + bowSize*0.5*cos(theta), ...
bowY + bowSize*0.5*sin(theta), ribbonColor, 'EdgeColor', 'none');
% Center knot
theta = linspace(0, 2*pi, 30);
fill(bowX + bowSize*0.25*cos(theta), bowY + bowSize*0.25*sin(theta), ...
ribbonColor*0.8, 'EdgeColor', 'none');
end
I like this quote, what do you think?
"If the part of programming you enjoy most is the physical act of writing code, then agents will feel beside the point. You’re already where you want to be, even just with some Copilot or Cursor-style intelligent code auto completion, which makes you faster while still leaving you fully in the driver’s seat about the code that gets written.
But if the part you care about is the decision-making around the code, agents feel like they clear space. They take care of the mechanical expression and leave you with judgment, tradeoffs, and intent. Because truly, for someone at my experience level, that is my core value offering anyway. When I spend time actually typing code these days with my own fingers, it feels like a waste of my time."
— Obie Fernandez, What happens when the coding becomes the least interesting part of the work
I can't believe someone put time into this ;-)
Our exportgraphics and copygraphics functions now offer direct and intuitive control over the size, padding, and aspect ratio of your exported figures.
- Specify Output Size: Use the new Width, Height, and Units name-value pairs
- Control Padding: Easily adjust the space around your axes using the Padding argument, or set it to to match the onscreen appearance.
- Preserve Aspect Ratio: Use PreserveAspectRatio='on' to maintain the original plot proportions when specifying a fixed size.
- SVG Export: The exportgraphics function now supports exporting to the SVG file format.
Check out the full article on the Graphics and App Building blog for examples and details: Advanced Control of Size and Layout of Exported Graphics
No, staying home (or where I'm now)
25%
Yes, 1 night
0%
Yes, 2 nights
12.5%
Yes, 3 nights
12.5%
Yes, 4-7 nights
25%
Yes, 8 nights or more
25%
8 votes
In a recent blog post, @Guy Rouleau writes about the new Simulink Copilot Beta. Sign ups are on the Copilot Beta page below. Let him know what you think.
Guy's Blog Post - https://blogs.mathworks.com/simulink/2025/12/01/a-copilot-for-simulink/
Simulink Copilot Beta - https://www.mathworks.com/products/simulink-copilot.html
The formula comes from @yuruyurau. (https://x.com/yuruyurau)
digital life 1
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 2, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 0:2e4;
x = mod(i, 100);
y = floor(i./100);
k = x./4 - 12.5;
e = y./9 + 5;
o = vecnorm([k; e])./9;
while true
t = t + pi/90;
q = x + 99 + tan(1./k) + o.*k.*(cos(e.*9)./4 + cos(y./2)).*sin(o.*4 - t);
c = o.*e./30 - t./8;
SHdl.XData = (q.*0.7.*sin(c)) + 9.*cos(y./19 + t) + 200;
SHdl.YData = 200 + (q./2.*cos(c));
drawnow
end
digital life 2
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 2, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 0:1e4;
x = i;
y = i./235;
e = y./8 - 13;
while true
t = t + pi/240;
k = (4 + sin(y.*2 - t).*3).*cos(x./29);
d = vecnorm([k; e]);
q = 3.*sin(k.*2) + 0.3./k + sin(y./25).*k.*(9 + 4.*sin(e.*9 - d.*3 + t.*2));
SHdl.XData = q + 30.*cos(d - t) + 200;
SHdl.YData = 620 - q.*sin(d - t) - d.*39;
drawnow
end
digital life 3
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 1, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 0:1e4;
x = mod(i, 200);
y = i./43;
k = 5.*cos(x./14).*cos(y./30);
e = y./8 - 13;
d = (k.^2 + e.^2)./59 + 4;
a = atan2(k, e);
while true
t = t + pi/20;
q = 60 - 3.*sin(a.*e) + k.*(3 + 4./d.*sin(d.^2 - t.*2));
c = d./2 + e./99 - t./18;
SHdl.XData = q.*sin(c) + 200;
SHdl.YData = (q + d.*9).*cos(c) + 200;
drawnow; pause(1e-2)
end
digital life 4
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 1, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 0:4e4;
x = mod(i, 200);
y = i./200;
k = x./8 - 12.5;
e = y./8 - 12.5;
o = (k.^2 + e.^2)./169;
d = .5 + 5.*cos(o);
while true
t = t + pi/120;
SHdl.XData = x + d.*k.*sin(d.*2 + o + t) + e.*cos(e + t) + 100;
SHdl.YData = y./4 - o.*135 + d.*6.*cos(d.*3 + o.*9 + t) + 275;
SHdl.CData = ((d.*sin(k).*sin(t.*4 + e)).^2).'.*[1,1,1];
drawnow;
end
digital life 5
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 1, 'filled','o','w',...
'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 0:1e4;
x = mod(i, 200);
y = i./55;
k = 9.*cos(x./8);
e = y./8 - 12.5;
while true
t = t + pi/120;
d = (k.^2 + e.^2)./99 + sin(t)./6 + .5;
q = 99 - e.*sin(atan2(k, e).*7)./d + k.*(3 + cos(d.^2 - t).*2);
c = d./2 + e./69 - t./16;
SHdl.XData = q.*sin(c) + 200;
SHdl.YData = (q + 19.*d).*cos(c) + 200;
drawnow;
end
digital life 6
clc; clear
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 2, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 1:1e4;
y = i./790;
k = y; idx = y < 5;
k(idx) = 6 + sin(bitxor(floor(y(idx)), 1)).*6;
k(~idx) = 4 + cos(y(~idx));
while true
t = t + pi/90;
d = sqrt((k.*cos(i + t./4)).^2 + (y/3-13).^2);
q = y.*k.*cos(i + t./4)./5.*(2 + sin(d.*2 + y - t.*4));
c = d./3 - t./2 + mod(i, 2);
SHdl.XData = q + 90.*cos(c) + 200;
SHdl.YData = 400 - (q.*sin(c) + d.*29 - 170);
drawnow; pause(1e-2)
end
digital life 7
clc; clear
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl = scatter([], [], 2, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.4);
t = 0;
i = 1:1e4;
y = i./345;
x = y; idx = y < 11;
x(idx) = 6 + sin(bitxor(floor(x(idx)), 8))*6;
x(~idx) = x(~idx)./5 + cos(x(~idx)./2);
e = y./7 - 13;
while true
t = t + pi/120;
k = x.*cos(i - t./4);
d = sqrt(k.^2 + e.^2) + sin(e./4 + t)./2;
q = y.*k./d.*(3 + sin(d.*2 + y./2 - t.*4));
c = d./2 + 1 - t./2;
SHdl.XData = q + 60.*cos(c) + 200;
SHdl.YData = 400 - (q.*sin(c) + d.*29 - 170);
drawnow; pause(5e-3)
end
digital life 8
clc; clear
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl{6} = [];
for j = 1:6
SHdl{j} = scatter([], [], 2, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.3);
end
t = 0;
i = 1:2e4;
k = mod(i, 25) - 12;
e = i./800; m = 200;
theta = pi/3;
R = [cos(theta) -sin(theta); sin(theta) cos(theta)];
while true
t = t + pi/240;
d = 7.*cos(sqrt(k.^2 + e.^2)./3 + t./2);
XY = [k.*4 + d.*k.*sin(d + e./9 + t);
e.*2 - d.*9 - d.*9.*cos(d + t)];
for j = 1:6
XY = R*XY;
SHdl{j}.XData = XY(1,:) + m;
SHdl{j}.YData = XY(2,:) + m;
end
drawnow;
end
digital life 9
clc; clear
figure('Position',[300,50,900,900], 'Color','k');
axes(gcf, 'NextPlot','add', 'Position',[0,0,1,1], 'Color','k');
axis([0, 400, 0, 400])
SHdl{14} = [];
for j = 1:14
SHdl{j} = scatter([], [], 2, 'filled','o','w', 'MarkerEdgeColor','none', 'MarkerFaceAlpha',.1);
end
t = 0;
i = 1:2e4;
k = mod(i, 50) - 25;
e = i./1100; m = 200;
theta = pi/7;
R = [cos(theta) -sin(theta); sin(theta) cos(theta)];
while true
t = t + pi/240;
d = 5.*cos(sqrt(k.^2 + e.^2) - t + mod(i, 2));
XY = [k + k.*d./6.*sin(d + e./3 + t);
90 + e.*d - e./d.*2.*cos(d + t)];
for j = 1:14
XY = R*XY;
SHdl{j}.XData = XY(1,:) + m;
SHdl{j}.YData = XY(2,:) + m;
end
drawnow;
end
Hello everyone,
My name is heavnely, studying Aerospace Enginerring in IIT Kharagpur. I'm trying to meet people that can help to explore about things in control systems, drones, UAV, Reseearch. I have started wrting papers an year ago and hopefully it is going fine. I hope someone would reply to reply to this messege.
Thank you so much for anyone who read my messege.
% Recreation of Saturn photo
figure('Color', 'k', 'Position', [100, 100, 800, 800]);
ax = axes('Color', 'k', 'XColor', 'none', 'YColor', 'none', 'ZColor', 'none');
hold on;
% Create the planet sphere
[x, y, z] = sphere(150);
% Saturn colors - pale yellow/cream gradient
saturn_radius = 1;
% Create color data based on latitude for gradient effect
lat = asin(z);
color_data = rescale(lat, 0.3, 0.9);
% Plot Saturn with smooth shading
planet = surf(x*saturn_radius, y*saturn_radius, z*saturn_radius, ...
color_data, ...
'EdgeColor', 'none', ...
'FaceColor', 'interp', ...
'FaceLighting', 'gouraud', ...
'AmbientStrength', 0.3, ...
'DiffuseStrength', 0.6, ...
'SpecularStrength', 0.1);
% Use a cream/pale yellow colormap for Saturn
cream_map = [linspace(0.4, 0.95, 256)', ...
linspace(0.35, 0.9, 256)', ...
linspace(0.2, 0.7, 256)'];
colormap(cream_map);
% Create the ring system
n_points = 300;
theta = linspace(0, 2*pi, n_points);
% Define ring structure (inner radius, outer radius, brightness)
rings = [
1.2, 1.4, 0.7; % Inner ring
1.45, 1.65, 0.8; % A ring
1.7, 1.85, 0.5; % Cassini division (darker)
1.9, 2.3, 0.9; % B ring (brightest)
2.35, 2.5, 0.6; % C ring
2.55, 2.8, 0.4; % Outer rings (fainter)
];
% Create rings as patches
for i = 1:size(rings, 1)
r_inner = rings(i, 1);
r_outer = rings(i, 2);
brightness = rings(i, 3);
% Create ring coordinates
x_inner = r_inner * cos(theta);
y_inner = r_inner * sin(theta);
x_outer = r_outer * cos(theta);
y_outer = r_outer * sin(theta);
% Front side of rings
ring_x = [x_inner, fliplr(x_outer)];
ring_y = [y_inner, fliplr(y_outer)];
ring_z = zeros(size(ring_x));
% Color based on brightness
ring_color = brightness * [0.9, 0.85, 0.7];
fill3(ring_x, ring_y, ring_z, ring_color, ...
'EdgeColor', 'none', ...
'FaceAlpha', 0.7, ...
'FaceLighting', 'gouraud', ...
'AmbientStrength', 0.5);
end
% Add some texture/gaps in the rings using scatter
n_particles = 3000;
r_particles = 1.2 + rand(1, n_particles) * 1.6;
theta_particles = rand(1, n_particles) * 2 * pi;
x_particles = r_particles .* cos(theta_particles);
y_particles = r_particles .* sin(theta_particles);
z_particles = (rand(1, n_particles) - 0.5) * 0.02;
% Vary particle brightness
particle_colors = repmat([0.8, 0.75, 0.6], n_particles, 1) .* ...
(0.5 + 0.5*rand(n_particles, 1));
scatter3(x_particles, y_particles, z_particles, 1, particle_colors, ...
'filled', 'MarkerFaceAlpha', 0.3);
% Add dramatic outer halo effect - multiple layers extending far out
n_glow = 20;
for i = 1:n_glow
glow_radius = 1 + i*0.35; % Extend much farther
alpha_val = 0.08 / sqrt(i); % More visible, slower falloff
% Color gradient from cream to blue/purple at outer edges
if i <= 8
glow_color = [0.9, 0.85, 0.7]; % Warm cream/yellow
else
% Gradually shift to cooler colors
mix = (i - 8) / (n_glow - 8);
glow_color = (1-mix)*[0.9, 0.85, 0.7] + mix*[0.6, 0.65, 0.85];
end
surf(x*glow_radius, y*glow_radius, z*glow_radius, ...
ones(size(x)), ...
'EdgeColor', 'none', ...
'FaceColor', glow_color, ...
'FaceAlpha', alpha_val, ...
'FaceLighting', 'none');
end
% Add extensive glow to rings - make it much more dramatic
n_ring_glow = 12;
for i = 1:n_ring_glow
glow_scale = 1 + i*0.15; % Extend farther
alpha_ring = 0.12 / sqrt(i); % More visible
for j = 1:size(rings, 1)
r_inner = rings(j, 1) * glow_scale;
r_outer = rings(j, 2) * glow_scale;
brightness = rings(j, 3) * 0.5 / sqrt(i);
x_inner = r_inner * cos(theta);
y_inner = r_inner * sin(theta);
x_outer = r_outer * cos(theta);
y_outer = r_outer * sin(theta);
ring_x = [x_inner, fliplr(x_outer)];
ring_y = [y_inner, fliplr(y_outer)];
ring_z = zeros(size(ring_x));
% Color gradient for ring glow
if i <= 6
ring_color = brightness * [0.9, 0.85, 0.7];
else
mix = (i - 6) / (n_ring_glow - 6);
ring_color = brightness * ((1-mix)*[0.9, 0.85, 0.7] + mix*[0.65, 0.7, 0.9]);
end
fill3(ring_x, ring_y, ring_z, ring_color, ...
'EdgeColor', 'none', ...
'FaceAlpha', alpha_ring, ...
'FaceLighting', 'none');
end
end
% Add diffuse glow particles for atmospheric effect
n_glow_particles = 8000;
glow_radius_particles = 1.5 + rand(1, n_glow_particles) * 5;
theta_glow = rand(1, n_glow_particles) * 2 * pi;
phi_glow = acos(2*rand(1, n_glow_particles) - 1);
x_glow = glow_radius_particles .* sin(phi_glow) .* cos(theta_glow);
y_glow = glow_radius_particles .* sin(phi_glow) .* sin(theta_glow);
z_glow = glow_radius_particles .* cos(phi_glow);
% Color particles based on distance - cooler colors farther out
particle_glow_colors = zeros(n_glow_particles, 3);
for i = 1:n_glow_particles
dist = glow_radius_particles(i);
if dist < 3
particle_glow_colors(i,:) = [0.9, 0.85, 0.7];
else
mix = (dist - 3) / 4;
particle_glow_colors(i,:) = (1-mix)*[0.9, 0.85, 0.7] + mix*[0.5, 0.6, 0.9];
end
end
scatter3(x_glow, y_glow, z_glow, rand(1, n_glow_particles)*2+0.5, ...
particle_glow_colors, 'filled', 'MarkerFaceAlpha', 0.05);
% Lighting setup
light('Position', [-3, -2, 4], 'Style', 'infinite', ...
'Color', [1, 1, 0.95]);
light('Position', [2, 3, 2], 'Style', 'infinite', ...
'Color', [0.3, 0.3, 0.4]);
% Camera and view settings
axis equal off;
view([-35, 25]); % Angle to match saturn_photo.jpg - more dramatic tilt
camva(10); % Field of view - slightly wider to show full halo
xlim([-8, 8]); % Expanded to show outer halo
ylim([-8, 8]);
zlim([-8, 8]);
% Material properties
material dull;
title('Saturn - Left click: Rotate | Right click: Pan | Scroll: Zoom', 'Color', 'w', 'FontSize', 12);
% Enable interactive camera controls
cameratoolbar('Show');
cameratoolbar('SetMode', 'orbit'); % Start in rotation mode
% Custom mouse controls
set(gcf, 'WindowButtonDownFcn', @mouseDown);
function mouseDown(src, ~)
selType = get(src, 'SelectionType');
switch selType
case 'normal' % Left click - rotate
cameratoolbar('SetMode', 'orbit');
rotate3d on;
case 'alt' % Right click - pan
cameratoolbar('SetMode', 'pan');
pan on;
end
end
Developing an application in MATLAB often feels like a natural choice: it offers a unified environment, powerful visualization tools, accessible syntax, and a robust technical ecosystem. But when the goal is to build a compilable, distributable app, the path becomes unexpectedly difficult if your workflow depends on symbolic functions like sym, zeta, or lambertw.
This isn’t a minor technical inconvenience—it’s a structural contradiction. MATLAB encourages the creation of graphical interfaces, input validation, and dynamic visualization. It even provides an Application Compiler to package your code. But the moment you invoke sym, the compiler fails. No clear warning. No workaround. Just: you cannot compile. The same applies to zeta and lambertw, which rely on the symbolic toolbox.
So we’re left asking: how can a platform designed for scientific and technical applications block compilation of functions that are central to those very disciplines?
What Are the Alternatives?
- Rewrite everything numerically, avoiding symbolic logic—often impractical for advanced mathematical workflows.
- Use partial workarounds like matlabFunction, which may work but rarely preserve the original logic or flexibility.
- Switch platforms (e.g., Python with SymPy, Julia), which means rebuilding the architecture and leaving behind MATLAB’s ecosystem.
So, Is MATLAB Still Worth It?
That’s the real question. MATLAB remains a powerful tool for prototyping, teaching, analysis, and visualization. But when it comes to building compilable apps that rely on symbolic computation, the platform imposes limits that contradict its promise.
Is it worth investing time in a MATLAB app if you can’t compile it due to essential mathematical functions? Should MathWorks address this contradiction? Or is it time to rethink our tools?
I’d love to hear your thoughts. Is MATLAB still worth it for serious application development?
Experimenting with Agentic AI
44%
I am an AI skeptic
0%
AI is banned at work
11%
I am happy with Conversational AI
44%
9 votes
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:
If you’ve tried these features or have your own tips for quick data exploration in MATLAB, I’d love to hear your thoughts!
Pure Matlab
82%
Simulink
18%
11 votes
Title: Looking for Internship Guidance as a Beginner MATLAB/Simulink Learner
Hello everyone,
I’m a Computer Science undergraduate currently building a strong foundation in MATLAB and Simulink. I’m still at a beginner level, but I’m actively learning every day and can work confidently once I understand the concepts. Right now I’m focusing on MATLAB modeling, physics simulation, and basic control systems so that I can contribute effectively to my current project.
I’m part of an Autonomous Underwater Vehicle (AUV) team preparing for the Singapore AUV Challenge (SAUVC). My role is in physics simulation, controls, and navigation, and MATLAB/Simulink plays a major role in that pipeline. I enjoy physics and mathematics deeply, which makes learning modeling and simulation very exciting for me.
On the coding side, I practice competitive programming regularly—
• Codeforces rating: ~1200
• LeetCode rating: ~1500
So I'm comfortable with logic-building and problem solving. What I’m looking for:
I want to know how a beginner like me can start applying for internships related to MATLAB, Simulink, modeling, simulation, or any engineering team where MATLAB is widely used (including companies outside MathWorks).
I would really appreciate advice from the community on:
- What skills should I strengthen first?
- Which MATLAB/Simulink toolboxes are most important for beginners aiming toward simulation/control roles?
- What small projects or portfolio examples should I build to improve my profile?
- What is the best roadmap to eventually become a good candidate for internships in this area?
Any guidance, resources, or suggestions would be extremely helpful for me.
Thank you in advance to everyone who shares their experience!
Jorge Bernal-AlvizJorge Bernal-Alviz shared the following code that requires R2025a or later:
Test()
function Test()
duration = 10;
numFrames = 800;
frameInterval = duration / numFrames;
w = 400;
t = 0;
i_vals = 1:10000;
x_vals = i_vals;
y_vals = i_vals / 235;
r = linspace(0, 1, 300)';
g = linspace(0, 0.1, 300)';
b = linspace(1, 0, 300)';
r = r * 0.8 + 0.1;
g = g * 0.6 + 0.1;
b = b * 0.9 + 0.1;
customColormap = [r, g, b];
figure('Position', [100, 100, w, w], 'Color', [0, 0, 0]);
axis equal;
axis off;
xlim([0, w]);
ylim([0, w]);
hold on;
colormap default;
colormap(customColormap);
plothandle = scatter([], [], 1, 'filled', 'MarkerFaceAlpha', 0.12);
for i = 1:numFrames
t = t + pi/240;
k = (4 + 3 * sin(y_vals * 2 - t)) .* cos(x_vals / 29);
e = y_vals / 8 - 13;
d = sqrt(k.^2 + e.^2);
c = d - t;
q = 3 * sin(2 * k) + 0.3 ./ (k + 1e-10) + ...
sin(y_vals / 25) .* k .* (9 + 4 * sin(9 * e - 3 * d + 2 * t));
points_x = q + 30 * cos(c) + 200;
points_y = q .* sin(c) + 39 * d - 220;
points_y = w - points_y;
CData = (1 + sin(0.1 * (d - t))) / 3;
CData = max(0, min(1, CData));
set(plothandle, 'XData', points_x, 'YData', points_y, 'CData', CData);
brightness = 0.5 + 0.3 * sin(t * 0.2);
set(plothandle, 'MarkerFaceAlpha', brightness);
drawnow;
pause(frameInterval);
end
end
Parallel Computing Onramp is here! This free, one-hour self-paced course teaches the basics of running MATLAB code in parallel using multiple CPU cores, helping users speed up their code and write code that handles information efficiently.
Remember, Onramps are free for everyone - give the new course a try if you're curious. Let us know what you think of it by replying below.
