Results for
I have MATLAB R2026b, the MATLAB Agentic Toolkit, and Claude Code installed.
In the first session, I asked Claude (Opus 5.5, High effort) to review the game rules, suggest MATLAB Agentic Toolkit skills, install them inside the project folder, and create a CLAUDE.md file.
In the second session, I asked Claude to create a combat game in which the player controls a simple stick figure wielding a club; clicking makes the figure swing the club. Simple monsters approach the player and drain the player’s health on contact, while hitting a monster with the club eliminates it. The game has an old-school 2D look, with a dark blue, star-filled background and light blue characters.
That's it. You can see result here: CLUB NIGHT
My best score until now is 2060.
Let me know your best score in the comments.
I started my game for this contest, Stack OverDad, one month before the contest began. Dad tells programming jokes at the dinner table, and you have to laugh at the right moment. I was very happy with it. It had a dog, a little brother with a spoon, a window with a sun that goes down, fifty jokes, and many small animations.
Then the contest started, and I read the rules again. One line said: each entry is limited to 10,000 characters of MATLAB code.
My code had more than 70,000 characters.
So, as you can guess, the next hourse were cut, test, cut, test, cut... In this post, I will tell you what I learned on the way (from my AI friend!). Some of it surprised me.
Step 1: Cut What the Player Does Not Feel
For every part of the game, I asked: "Does the player really feel this?"
The dog: cute, but no. The brother: funny, but no. The sunset: nobody looks at the window when Dad tells a joke. Forty jokes: a game only uses ten anyway.
This was the biggest step, and the hardest, because I liked all of these things. But the game did not get worse. It got clearer. After this, my file had about 9,800 characters. I was done!
Step 2: The Surprise
The contest project has a command to check the game before you submit it:
minihackContest.validate
I ran it, and it said:
Validation failed: game.m exceeds the character limit (16145 / 10000, comments excluded).
16,145? My file had 9,800 characters. I counted again. It still had 9,800.
So I opened the validator to see how it counts. This is the line:
charCount = strlength(char(tree2str(mtree(gameFile, '-file'))));
mtree reads the code into a tree, and this removes the comments. Then tree2str writes the code again, in a clean, standard layout. The validator counts that text, not my file.
And the clean layout is not short at all. For example, this one line of mine:
if p,pr(s.T);end
comes back from tree2str like this:
if p
pr( s.T );
end
Every statement gets its own line. Every line gets indentation. Every f(a,b) becomes f( a, b ), and every [1 2 3] becomes [ 1, 2, 3 ]. My short style was not short anymore.
The good news: now I knew the real rule, so I could play by it.
Step 3: What Is Cheap and What Is Expensive
- Expensive: many statements, deep nesting, and long lists of numbers.
- Cheap: text inside a string. tree2str does not change a string at all.
So the plan was: fewer statements, less nesting, and move numbers into strings.
Example 1: Many Values in One Statement
s.st = 3;
s.t0 = t;
s.la = -1;
becomes one statement with deal:
[s.st, s.t0, s.la] = deal(3, t, -1);
Example 2: A Small if Without if
if n == 1
s.fl = "TEN?!";
end
With logical indexing, it is one line. If the condition is false, nothing changes:
s.fl(n == 1) = "TEN?!";
Example 3: Many Strings in One String
A list like ["PERFECT!", "GOOD!", "TOO LATE..."] pays for every ", ". One string with a separator is cheaper:
B = split("PERFECT!|GOOD!|TOO LATE...", "|");
All fifteen jokes are now one string too.
Example 4: Numbers Inside a String
This was the biggest trick. My scene (the table, the chairs, Dad, the family) is made of rectangles, ellipses, and polygons. That is hundreds of numbers.
So I stored each number as one character in a string. A character is really a number (its code), so I can turn it back:
v = double(char(z))/20 - 1025; % every character of z becomes one number again
I chose codes from a big block of normal, printable characters. They look like Chinese characters, but they are not words. I only use their codes. One small loop reads the string and draws all the shapes with patch. Now the whole scene costs about one character per number.
One warning from my own mistake: use double(char(z)), not double(z). If z is a string, double(z) gives NaN. My first test showed an empty table because of this.
I kept the readable list of shapes in a separate file, and it writes the packed strings for me.
I Had Help
I worked with an AI assistant the whole way. It read the validator with me, tested many small ideas fast, measured which part of the code cost the most, and rewrote code again and again without getting tired.
But the AI did not decide what the game is. It could tell me that the dog costs 1,700 characters. It could not tell me if the dog is worth it. Every "keep" or "cut" was my choice. I think this is the best way to work with AI: let it do the heavy lifting, and keep the decisions for yourself.
The Result
The validator now says 9,936 characters. The game still has Dad, THE LOOK, Mom's warnings, the family walking out, the ranks, and fifteen jokes.
My advice: run minihackContest.validate early. Do not count the characters yourself, because the validator does not count your file. It counts the clean version of your file.
I hope you have found this helpful. Thank you for reading.
Hello everyone, I am new to Matlab.
I am trying to create an app to export the 5th column into a new sheet in the imported Excel file when I click Export button.
How can I write code in ExportButtonPushed
classdef test < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
UIFigure matlab.ui.Figure
ExportButton matlab.ui.control.Button
UITable matlab.ui.control.Table
ImportButton matlab.ui.control.Button
end
% Callbacks that handle component events
methods (Access = private)
% Button pushed function: ImportButton
function ImportButtonPushed(app, event)
[file, location] = uigetfile( ...
{'*.xlsx;*.xlsm', 'Excel files'; '*.txt', 'Text files'; '*.*', 'All files'}, ...
'File Selector');
figure(app.UIFigure)
if isequal(file, 0), return, end
fullPath = fullfile(location, file);
try
[~,~,ext] = fileparts(fullPath);
if any(strcmpi(ext, {'.xlsx','.xlsm','.xls'}))
T = readtable(fullPath, 'Sheet', 1, 'VariableNamingRule', 'preserve');
else
T = readtable(fullPath, 'VariableNamingRule', 'preserve');
end
catch ME
uialert(app.UIFigure, ME.message, 'Read error');
return
end
if width(T) < 5
uialert(app.UIFigure, 'The file needs at least 5 columns.', 'Import error');
return
end
app.UITable.Data = T;
app.UITable.ColumnName = T.Properties.VariableNames;
lengthlist = T{:,5};
end
% Button pushed function: ExportButton
function ExportButtonPushed(app, event)
Recently, I encountered an issue where solve returned no solution for a system of equations, even though the system obviously has solutions. This can be easy to overlook.
For example:
syms a b c x
equs = [a*x^2+b*x+c==0;
a==1];
St = solve(equs,x)
St is returned as an empty set, suggesting that there is no solution???
However, since a is constrained by the equation a == 1, the correct way is:
S = solve(equs,[x,a])
disp(S.x)
disp(S.a)
Here, a must also be included in the list of variables to solve for. Only then will solve treat a as an unknown, apply the constraint a == 1, and substitute it into the equation during the solving process.
symvar(equs)
Based on the output of the symvar function, a is already identified as one of the symbolic variables (unknowns) in the system of equations. However, the actual behavior of solve appears to contradict this expectation. In practice, a must still be explicitly included in the variable list passed to solve; otherwise, it is treated as a symbolic parameter rather than a variable to be solved for.
Takeaway: When using solve for a system of equations, any symbol that appears in the equations and is constrained by additional equations (such as a == 1) should generally be included in the variable list. Otherwise, solve may treat it as a symbolic parameter rather than an unknown, which can lead to an empty solution set or unexpected results.
Am I missing something here? I'd love to hear your thoughts.
We use Timecontrol for statistic automations. Yesterday at 2026-10-220 10:00pm CET Time control stopped working. There is new new time in the "Run At" field, although the script should run every 5 minutes. We had the same problem in September, see https://de.mathworks.com/matlabcentral/answers/2184870-thingspeak-timecontrol-stopped-working-at-all?s_tid=srchtitle
Has anybody also prolems with Timecontrol?
For the past several days I have been experiencing a problem with data visualization on two of my ThingSpeak channels.
The data appears to be uploaded and stored correctly, and new entries are still being added to the channels. However, the visualizations are not working correctly.
The standard Field Charts show only a very small number of data points instead of the normal continuous measurements. Most of the points are compressed on the left side of the chart, while one or a few points appear far to the right and are connected by long straight lines. The time axis is also incorrect and sometimes shows repeated dates such as “01 Jan”.
The numeric widgets are affected as well and display incorrect values. Some custom visualizations also remain blank or fail to load.
The problem appeared suddenly and affects two separate channels which had previously been working correctly. I did not make any significant changes to the channels before the problem started.
This seems somewhat similar to the ThingSpeak chart/timeline issue reported in June 2026, when charts were displaying incorrect time ranges and the DAYS/RESULTS settings were not working correctly. However, my current problem also affects numeric widgets and custom visualizations, and the charts show incorrect dates and strangely positioned data points.
Could this be a regression or a similar issue with the ThingSpeak visualization system?
Has anyone else experienced the same problem recently?
Hey, this is a safe space to share your cool projects you know. I have pet ducks, I use ThingSpeak to open the door to their house each morning. I just finished an upgrade to the LED strip lights on my driveway that are controlled via ThingSpeak. And the valves for my drip irrigation system. You got it. Controlled by ThingSpeak. Let me know your last cool project you finished or the one you keep dreaming of starting. I need some more inspiration :)
The example code below shows how to write version 7.3 MAT files directly from C++ using the HDF5 library (libhdf5) and HighFive, a header-only C++ wrapper for libhdf5. Version 7.3 MAT files are HDF5-based, but contain a proprietary header in the first 512 bytes of the file.
The implementation performs three primary tasks:
First, it creates an HDF5 file with a 512-byte userblock. After data has been added into the file, the file is closed. Then a 128-byte header is written into the userblock so that the file is recognized by MATLAB as a valid version-7.3 MAT file. This is done in function “makeMatHeader”.
Second, MATLAB-specific metadata attributes are added to each dataset. Attributes such as “MATLAB_class” and “MATLAB_int_decode” inform MATLAB how each dataset should be interpreted.
Third, MATLAB-compatible complex datasets are created by overriding HighFive's default complex-number layout. HighFive uses the field names `r` and `i` by default, while MATLAB expects `real` and `imag`. A Highfive custom compound type is therefore registered for `std::complex<double>` using the MATLAB field names.
With these changes in place, C++ code can write scalar values, vectors, structs, complex arrays, and character arrays to a file that MATLAB can read as a version 7.3 MAT file.
#include <iostream>
#include <vector>
#include <complex>
#include <cstddef>
#include <fstream>
#include <string>
#include <cstdint>
#include <utility>
#include <bitset>
#include <highfive/highfive.hpp>
#include "hdf5.h"
// Modify the 512-byte userblock at the front of the HDF5 file to make it compatible with MATLAB's v7.3 MAT file format.
void makeMatHeader(std::string filename)
{
char header[512]; // MATLAB-style header for HDF5 file
memset(header, 0, sizeof(header)); // Initialize header to all zeros
// Example header content
snprintf(header, sizeof(header), "MATLAB 7.3 MAT-file, Platform: HDF5");
header[124] = 0;
header[125] = 2;
// I/M indicate little-endian format (Intel Mac/Windows)
header[126] = 'I';
header[127] = 'M';
// Write the header to the beginning of the file
std::ofstream outFile(filename, std::ios::binary | std::ios::in | std::ios::out);
outFile.seekp(0);
outFile.write(header, sizeof(header));
outFile.close();
}
// https://www.geeksforgeeks.org/dsa/inplace-m-x-n-size-matrix-transpose/
void MatrixInplaceTranspose(int *A, int rows, int cols)
{
// Moves elements in-place to achieve the transpose.
// A is a pointer to a 2D array, rows is the number of rows, and cols is the number of columns.
int size = rows*cols - 1;
int t; // holds element to be replaced, eventually becomes next element to move
int next; // location of 't' to be moved
int cycleBegin; // holds start of cycle
int i; // iterator
const int HASH_SIZE = 8192; // define a suitable hash size for the bitset. Must be at least as large as the number of elements in the matrix.
std::bitset<HASH_SIZE> b; // hash to mark moved elements. Must be large enough to cover all indices.
if (rows <= 0 || cols <= 0) {
throw std::invalid_argument("Matrix dimensions must be positive");
}
else if ((rows * cols) > HASH_SIZE)
{
throw std::invalid_argument("Matrix size exceeds hash size for in-place transpose. Increase the HASH_SIZE constant.");
}
b.reset();
b[0] = b[size] = 1;
i = 1; // Note that A[0] and A[size-1] won't move
while (i < size)
{
cycleBegin = i;
t = A[i];
do
{
// Input matrix [rows x cols]
// Output matrix [cols x rows]
// i_new = (i*rows)%(N-1)
next = (i*rows)%size;
std::swap(A[next], t);
b[i] = 1;
i = next;
}
while (i != cycleBegin);
// Get Next Move (what about querying random location?)
for (i = 1; (i < size) && b[i]; i++)
;
}
}
template <typename T>
std::vector<std::vector<T>> transpose(const std::vector<std::vector<T>>& matrix)
{
// Performs a nonconjugate transpose on a vector of vectors
// The input matrix is a vector of vectors, where each inner vector represents a row of the matrix.
// Handle empty matrix edge case
if (matrix.empty() || matrix[0].empty()) {
return {};
}
size_t rows = matrix.size();
size_t cols = matrix[0].size();
// Initialize the transposed matrix with flipped dimensions: cols x rows
std::vector<std::vector<T>> transposed(cols, std::vector<T>(rows));
for (size_t i = 0; i < rows; ++i) {
for (size_t j = 0; j < cols; ++j) {
transposed[j][i] = matrix[i][j];
}
}
return transposed;
}
// Creates a HighFive compound type for representing MATLAB-style complex numbers
// HighFive by default uses r/i but that is not compatible with MATLAB's complex number representation, which uses real/imag.
HighFive::CompoundType matlabComplexDouble () {
return {
{"real", HighFive::AtomicType<double>{}},
{"imag", HighFive::AtomicType<double>{}}
};
}
// Register the CompoundType to represent std::complex<double>
HIGHFIVE_REGISTER_TYPE(std::complex<double>, matlabComplexDouble);
int main()
{
const std::string filename = "test.mat";
// Needed for the complex number literal suffix 'i'
using namespace std::literals;
/*
* MATLAB vs C++ array layout
*
* MATLAB stores arrays in column-major order, meaning values in the same column are
* laid out next to each other in memory. Typical C++ containers such as nested std::vector and arrays
* are written in row-major order, where values in the same row are adjacent in memory.
*
* That difference matters when something such as a 2D dataset is exchanged from C++ to MATLAB. A 2x3
* matrix written from C++ in row-major order will be interpreted by MATLAB as a 3x2 matrix, transposed relative
* to the original C++ layout. The user will have to transpose the array to view the original C++ layout
* correctly.
*
* C++ developers need to be aware of the memory layout when
* exchanging multidimensional arrays with MATLAB. To maintain the structure,
* one will need to transpose the array before writing it to the mat file.
*/
// Test data
// 2x3 Array of complex double
std::vector<std::vector<std::complex<double>>> dataComplex = {{10.0 + 1.0i, 20.0 + 2.0i, 30.0 + 3.0i},
{40.0 + 4.0i, 50.0 + 5.0i, 60.0 + 6.0i}};
// 1x3 Vector of double
std::vector<double> dataDoubleVec = {1.1, 2.2, 3.3};
// 1x5 Array of integers
int dataIntArray[5] = {1, 2, 3, 4, 5};
// 2x4 Array of integers
int dataIntArray2x4[2][4] = {{1, 2, 3, 4},
{5, 6, 7, 8}};
int dataInt = 79;
double dataDouble = 3.14;
std::string dataString = "Hello, MATLAB!!!!!";
{
// Put the highfive related code into its own block so that the file gets closed when the file object is no longer in scope.
// Create a highfive file create property, get the underlying HDF5 property ID, and set a userblock size
HighFive::FileCreateProps fcp = HighFive::FileCreateProps::Empty();
hid_t fcpl_id = fcp.getId();
H5Pset_userblock(fcpl_id, 512);
HighFive::File file(filename, HighFive::File::Truncate, fcp);
// Storing a double to the file
// For something that is only a single value, must create a 1x1 dataspace
HighFive::DataSpace scalarDoubleSpace({1, 1});
// This creates a variable in the MATLAB workspace with the name "double_value"
HighFive::DataSet doubleField = file.createDataSet<double>("double_value", scalarDoubleSpace);
doubleField.write(dataDouble);
// Metadata for MATLAB compatibility
doubleField.createAttribute("MATLAB_class", std::string("double"));
// Storing an integer to the file
// For something that is only a single value, must create a 1x1 dataspace
HighFive::DataSpace scalarIntSpace({1, 1});
// This creates a variable in the MATLAB workspace with the name "int_value"
HighFive::DataSet intField = file.createDataSet<int>("int_value", scalarIntSpace);
intField.write(dataInt);
// Metadata for MATLAB compatibility
intField.createAttribute("MATLAB_class", std::string("int32"));
// Storing a C-style 1x5 array of integers to the file
// Since it is a single dimension, there is no need to move the data, just reinterpret it as a 5x1 row-major array.
// When Matlab imports it, it will perceive it as a 1x5 column-major array.
// This line casts the 1x5 array to a 5x1 array to match MATLAB's column-major order
int (*numArrayTrans5x1)[1] = reinterpret_cast<int (*)[1]>(dataIntArray);
HighFive::DataSpace intArray5x1Space({5, 1});
// This creates a variable in the MATLAB workspace with the name "int_array"
HighFive::DataSet intArrayField = file.createDataSet<int>("int_array", intArray5x1Space);
intArrayField.write(numArrayTrans5x1);
intArrayField.createAttribute("MATLAB_class", std::string("int32"));
// Storing a C-style 2x4 array of integers to the file
// For something that is a multi-dimensional array, we need to transpose the array and create a dataspace with the dimensions swapped
// so that the data is stored in column-major order.
MatrixInplaceTranspose((int*)dataIntArray2x4, 2, 4);
// After moving the values around, we need to cast the array with the new dimensions to match the new layout
// Cast the transposed 2x4 array to a 4x2 array to match MATLAB's column-major order
int (*numArrayTrans)[2] = reinterpret_cast<int (*)[2]>(dataIntArray2x4);
HighFive::DataSpace intArray2x4Space({4, 2});
// This creates a variable in the MATLAB workspace with the name "int_array_2x4"
HighFive::DataSet intArray2x4Field = file.createDataSet<int>("int_array_2x4", intArray2x4Space);
intArray2x4Field.write(numArrayTrans);
intArray2x4Field.createAttribute("MATLAB_class", std::string("int32"));
// Creating a Matlab struct (HDF5 group)
HighFive::Group my_struct = file.createGroup("my_struct");
my_struct.createAttribute("MATLAB_class", std::string("struct"));
// The only difference between storing data into a struct or as a normal variable in the MAT file is the
// the parent object you use when you do "createDataSet".
// file.createDataSet would create a normal variable, my_struct.createDataSet creates it within the "my_struct" struct.
// Storing a string to the struct so that it will be accessible as a character array in MATLAB
// For something that is a string, we create a dataspace with dimensions [string_length, 1] and save the character data accordingly
// We create a vector that has dataString.size() elements, each of which is a char vector of size 1 to store individual characters.
std::vector<std::vector<char>> text_bytes(dataString.size(), std::vector<char>(1));
// MATLAB expects character arrays to be a row vector so we reshape it accordingly since dimensions are swapped between C++ and MATLAB
for (int i = 0; i < dataString.size(); ++i) {
text_bytes[i][0] = dataString[i];
}
HighFive::DataSpace charSpace({dataString.size(), 1});
// uint16_t is required for MATLAB character arrays
HighFive::DataSet textField = my_struct.createDataSet<uint16_t>("text_value", charSpace);
textField.write(text_bytes);
// Metadata for MATLAB compatibility
textField.createAttribute("MATLAB_class", std::string("char"));
// Tell MATLAB to interpret the data as characters rather than integers
textField.createAttribute("MATLAB_int_decode", 2);
// Storing a vector to the struct
// In order to transpose the vector correctly, we first wrap it in another vector to make it a 2D array.
std::vector<std::vector<double>> transposableDoubleVec = { dataDoubleVec };
// For vectors, we let HighFive infer the dataspace from the data itself
// Transpose the vector to match MATLAB's column-major order
HighFive::DataSet doubleVectorField = my_struct.createDataSet("double_vector", transpose(transposableDoubleVec));
// Metadata for MATLAB compatibility
doubleVectorField.createAttribute("MATLAB_class", std::string("double"));
// Storing a complex (and multi-dimensional) vector to the struct
// For multi-dimensional vectors, we need to perform a noncojugate transpose on the array to match
// MATLAB's column-major order so the data layout is consistent between C++ and MATLAB.
// For vectors, we let HighFive infer the dataspace from the data itself
HighFive::DataSet complexField = my_struct.createDataSet("complex_vector", transpose(dataComplex));
// Metadata for MATLAB compatibility
complexField.createAttribute("MATLAB_class", std::string("complex"));
}
// Finalize the MATLAB-compatible HDF5 file by writing the MATLAB header into the userblock
makeMatHeader(filename);
return 0;
}
For those using Matlab and ecountering difficulty with mex and Xcode v27
Fix for Xcode 27 breaking MATLAB MEX C++ compilation:
matlab
edit(fullfile(prefdir,'mex_C++_maca64.xml'))
% Set LINKEXPORTCPP=""
% Then rebuild normally
If you're a student looking for tips, resources, or guidance for learning MATLAB, check out my new blog: Learn MATLAB – A Student’s Guide
The blog highlights a variety of student resources, including getting started guides, cheat sheets, learning materials, and other helpful tools to make learning MATLAB easier. I hope you find it useful!
Annular, sector, triangular, and cluster heatmaps can all be produced by this tool：https://www.mathworks.com/matlabcentral/fileexchange/125520-special-heatmap
Demo: Group Sep with non-square matrix
Data = rand(3, 12);
SHM = SHeatmap(Data, 'Format','sq');
SHM.RowName = {'Off-peak', 'Peak', 'Regular'};
SHM.ColName = {'Beijing', 'Shanghai', 'Guangzhou', 'Shenzhen'};
SHM.ColGroup = [1,1,1,1, 2,2,2,2, 3,3,3,3];
SHM.draw().setFrame()
Demo: Merge two triangle heatmaps
% Made up some data casually (随便捏造了点数据)
X = randn(20,15) + [(linspace(-1,2.5,20)').*ones(1, 6), (linspace(.5,-.7,20)').*ones(1, 5), (linspace(.9,-.2,20)').*ones(1, 4)];
% Get the correlation matrix (求相关系数矩阵)
Data = corr(X);
figure()
SHM_m1 = SHeatmap(Data, 'Format','sq').draw().setType('tril');
SHM_m1.setColLabel('Visible','off').setText()
SHM_m2 = SHeatmap(Data, 'Format','hex').draw().setType('triu0');
SHM_m2.setRowLabel('Visible','off').setColLabel('Visible','on') % Show the hidden Var-1 label (显示隐藏的 Var-1 标签)
Demo: Circular heatmap with Group Block and GroupSep
% Circular heatmap is currently supported only for
% SHeatmap with 'sq' Format and 'full' Type.
rng(1)
Data = randn(100, 5);
rowName = compose('row-%d', 1:100);
colName = compose('col-%d', 1:5);
rowGroup = [ones(1, 25), 2.*ones(1, 15), 3.*ones(1, 20), 4.*ones(1, 20), 5.*ones(1, 20)];
rowColor = [187,207,232; 222,236,247; 253,253,253; 251,225,216; 231,184,192]./255;
rgnames = {'Group-R1','Group-R2','Group-R3','Group-R4','Group-R5'};
% create figure (图窗创建)
fig = figure('Units','normalized', 'Position',[.1,.05,.5,.72]);
ax = axes('Parent',fig, 'Position',[.1,.1,.75,.75]);
% Draw group block (绘制分组方块)
SCB_L = SClusterBlock(ax, rowGroup, 'Orientation','left', 'ColorList',rowColor, 'Group',rowGroup, 'GroupSep',2.5);
SCB_L.draw(); SCB_L.setXYTLim('XLim',[1.65,1.95], 'YLim',[0, 1], 'TLim',[-3*pi/2, pi/3]);
% Draw circular heatmap (绘制环形热图)
SHM = SHeatmap(ax, Data, 'Format','sq', 'RowGroup',rowGroup, 'GroupSep',2.5);
SHM.TickLength = .3;
SHM.draw();
SHM.setRowName(rowName)
SHM.setColName(colName)
SHM.setRowLabelLocation('right')
SHM.setColLabelLocation('top')
% YLim(1) -> TLim(1), YLim(2) -> TLim(2)
SHM.setXYTLim('XLim',[2, 3], 'YLim',[0, 1], 'TLim',[-3*pi/2, pi/3]);
SHM.Colorbar.Position(1) = SHM.Colorbar.Position(1) + .1;
gHdl = text(ax, SCB_L.X, SCB_L.Y, rgnames, 'FontSize',14, 'FontName','Times New Roman');
setTextPerpRadial(gHdl)
colormap(slanCM(97, 32))
More than 50 examples are incorporated into this tool：
All figures presented in this Discussion were generated using MATLAB.
I developed two functions: one for plotting chord diagrams without self-loops, and the other for plotting chord diagrams with self-loops.
chordChart : basic usage
plotting chord diagrams without self-loops : https://www.mathworks.com/matlabcentral/fileexchange/116550-chordchart-chord-diagram
dataMat = [2 0 1 2 5 1 2;
3 5 1 4 2 0 1;
4 0 5 5 2 4 3];
colName = {'B1','G2','G3','G4','G5','G6','G7'};
rowName = {'S1','S2','S3'};
% Create and render chord diagram object (创建弦图对象并渲染)
CC = chordChart(dataMat, 'RowName',rowName, 'ColName',colName, 'Arrow','on');
CC.LinearMinorTick = 'on';
CC.draw();
% Set Font for labels and show ticks (调整字体并显示刻度)
CC.setFont('FontSize',17, 'FontName','Cambria')
CC.tickState('on')
CC.tickLabelState('on')
biChordChart : basic usage
plotting chord diagrams with self-loops : https://www.mathworks.com/matlabcentral/fileexchange/121043-bichordchart-bidirectional-chord-diagram
dataMat = randi([0,8], [5,5]);
nameList = {'AAA','BBB','CCC','DDD','EEE'};
% Create bichord chart object and draw (创建并绘制双向弦图对象)
BCC = biChordChart(dataMat, 'Arrow','on', 'Label',nameList);
BCC = BCC.draw();
% Show ticks and tick labels (添加刻度)
BCC.tickState('on')
BCC.tickLabelState('on')
% Set font properties (修改字体，字号及颜色)
BCC.setFont('FontName','Cambria','FontSize',17)
The two File Exchange submissions each provide more than a dozen basic examples. In addition, the GitHub repository listed below provides nearly 40 elaborate customized demonstration cases.
How does MATLAB ThingSpeak Work ?
Hallo zusammen,
Ich habe einen Frage zu meinen Programm. Dies will einfach nicht laufen und ich finde keinen Fehler mehr. Ich habe mein Programm bei Simulink geschriebenen den Code bei Maltab Function. Das Board ist ein Adruino Uni Board. Ein Ultrasonic Sensor soll die Füllstände ich Wäschekörben messen. Dabei wird unter voll oder halbvoll entschieden. Anschließend wird ein Motor angesprochen, der entweder 15 oder 30 Sekunden laufen soll. Überwacht wird der Motor von einem Thermistor (den habe ich hier PT100 genannt) und einen Vibrationsschalter. Dazu soll der Vibrationsschalter über einen Resetknopf zurückgesetzt werden. Ich hoffe ihr könnt mir weiterhelfen.
Vielen Dank:)
if true
% code
end
n= input('Escolhe um número inteiro postivo. ')
primo=true;
i=2;
while i<n
if mod(n,i)==0;
primo=false;
end
i= i+1;
end
if primo && n>1;
disp('É primo')
else
disp('Não é primo')
end
anterior= n-1;
while true
primo=true;
i=2;
while i< anterior
if mod(anterior,i)==0;
primo= false;
end
i= i+1;
end
if primo && anterior>1;
end
anterior= anterior-1;
end
disp(anterior)
seguinte= n+1;
while true;
primo= true;
i=2;
while i<seguinte;
if mod(seguinte,i)==0;
primo=false;
end
i=i+1;
end
if primo && seguinte>1;
end
seguinte= seguinte+1;
end
disp(seguinte)
Any ideas? It is in portuguese if you intend to translate it.
This is a brief introduction and recommendation of a Sankey diagram plotting tool:
Basic usage - links
links={'a1','A',1.2;'a2','A',1;'a1','B',.6;'a3','A',1; 'a3','C',0.5;
'b1','B',.4; 'b2','B',1;'b3','B',1; 'c1','C',1;
'c2','C',1; 'c3','C',1;'A','AA',2; 'A','BB',1.2;
'B','BB',1.5; 'B','AA',1.5; 'C','BB',2.3; 'C','AA',1.2};
% 创建桑基图对象(Create a Sankey diagram object)
SK=SSankey(links(:,1),links(:,2),links(:,3));
% 开始绘图(Start drawing)
SK.draw()
Basic usage - adjMat
% Define inter-layer adjacency matrices
% 定义层间邻接矩阵
A12 = [1,2,1; 1,2,3; 2,0,1];
A23 = [1,4; 2,1; 0,3];
A34 = [1,5; 2,3];
% Assemble global block matrix (main diagonal = zero, super-diagonal = A12, A23, A34)
% 组装全局分块矩阵（主对角线为零，上对角线为 A12, A23, A34）
adjMat = mergeAdjMat({A12, A23, A34});
SK = SSankey([],[],[], 'AdjMat',adjMat);
SK.draw()
Further usage examples can be found in the demos included in the compressed package：
I've been confused trying to write (or have an AI write) the .m (Live) text format from scratch for various reasons using .mlx format exported with the IDE as .m (old) and .m (LIve). Of course, one problem is the .m and .m (Live) files have the same name,causing confusion and requiring renaming, but repeatedly, after sussing out and following all conventions for headings and latex etc in .m (LIve), my .m (Live) files would not open as .mlx in the IDE. I think I've found the answer by trial and error and comparison and don't know it is documented. Add at the end
%[appendix]{"version":"1.0"} %--- %[metadata:view] % data: {"layout":"inline"} %---
This seems to trigger the IDE to recognize this is a .m (Live). Woohoo! This is a LOT easier than writing .mlx zip packages from scratch.
Have there been some changes made to the ThinkSpeak graphs? I am unable to change the number of days displayed, nor the number of data points to display. I did have them display 5 days, but now they are showing 14 days even though the setting is 5. I tried logging out and back in, but to no avail. Thanks.
Have been using Thingspeak for a few years, suddenly I get this message relating to one of my Matlab analysis scripts, which has run for years:
Error Message:
Unrecognized function or variable 'cusum'. cusum requires Signal Processing Toolbox.
What has changed to cause this error - I've done nothing!
Generate a 3D visualization of carnation flowers
with sepals and stems for celebrating Mother's Day 2026.
function carnation
% CARNATION Generate a 3D visualization of carnation flowers with sepals and stems.
% This code is authored by Zhaoxu Liu / slandarer
% for the purpose of celebrating Mother's Day 2026.
% =========================================================================
% Zhaoxu Liu / slandarer (2026). carnation for Mother's Day
% (https://www.mathworks.com/matlabcentral/fileexchange/183838-carnation-for-mother-s-day),
% MATLAB Central File Exchange. Retrieved May 9, 2026.
% Create figure and axes / 创建图窗及坐标区域
fig = figure('Units','normalized', 'Position',[.3,.1,.4,.8],'Color',[244,234,225]./255);
axes('Parent',fig, 'NextPlot','add', 'DataAspectRatio',[1,1,1],...
'View',[-64, 5.5], 'Position',[0,-.15,1,1], 'Color',[244,234,225]./255, ...
'XColor','none', 'YColor','none', 'ZColor','none');
annotation("textbox", [.05, .8, .9, .2], "String", {"Happy"; "Mother's Day"}, ...
'FontName','Segoe Script', 'FontSize',52, 'FontWeight','bold', 'EdgeColor','none', ...
'HorizontalAlignment','center', 'VerticalAlignment','middle', 'Color',[97,40,20]./255);
xx = linspace(0, 1, 100);
tt = linspace(0, 1, 1e4);
[X, P] = meshgrid(xx, tt);
T1 = P*20*pi;
C1 = 1 - (1 - mod(3.6*T1/pi, 2)).^4./2; % Petal profile / 花瓣形状
S1 = (sin(50*T1)/150 + sin(10*T1)/30).*min(1, max(0, (X - .85)/.1)); % Edge serration / 边缘褶皱和锯齿
Y1 = (- (X.*1.2 - .5).^5.*32 - 1)./15.*P; % Petal curvature / 花瓣弧度
% Petal shape and serration modeling + rotating the planar petal to tilt it
% 花瓣形状和锯齿塑造 + 转动平躺的花瓣令其倾斜
R1 = (C1 + S1).*(X.*sin(P) - Y1.*cos(P))./(P + .5);
H1 = (C1 + S1).*(X.*cos(P) + Y1.*sin(P));
% Convert radius to Cartesian coordinates / 将半径映射为X,Y坐标
X1 = R1.*cos(T1);
Y1 = R1.*sin(T1);
% Colormap for carnation petals / 康乃馨配色
CList1 = [208, 62, 23; 221,146,121; 229,201,202; 233,219,222; 237,223,225]./255;
CMat1 = zeros(1e4, 100, 3);
CMat1(:, :, 1) = repmat(interp1(linspace(0, 1, size(CList1, 1)), CList1(:, 1), linspace(0, 1, 100)), [1e4, 1]);
CMat1(:, :, 2) = repmat(interp1(linspace(0, 1, size(CList1, 1)), CList1(:, 2), linspace(0, 1, 100)), [1e4, 1]);
CMat1(:, :, 3) = repmat(interp1(linspace(0, 1, size(CList1, 1)), CList1(:, 3), linspace(0, 1, 100)), [1e4, 1]);
% Darken edges / 边缘的深色
for i = 1:1e4
tNum = randi([98, 100]);
CMat1(i, tNum:end, 1) = 212./255;
CMat1(i, tNum:end, 2) = 87./255;
CMat1(i, tNum:end, 3) = 113./255;
end
% Rotation matrices / 旋转矩阵
Rx = @(rx) [1, 0, 0; 0, cos(rx), -sin(rx); 0, sin(rx), cos(rx)];
Rz = @(yz) [cos(yz), - sin(yz), 0; sin(yz), cos(yz), 0; 0, 0, 1];
Rx1 = Rx(pi/6); Rz1 = Rz(0);
% Render flower / 绘制康乃馨
surface(X1, Y1, H1 + .3, 'CData',CMat1, 'EdgeAlpha',0.1, 'EdgeColor',[224,39,39]./255, 'FaceColor','interp')
[U1, V1, W1] = matRotate(X1, Y1, H1 + .3, Rx1);
surface(U1 + .7, V1 - .7, W1 - .6, 'CData',CMat1, 'EdgeAlpha',0.1, 'EdgeColor',[224,39,39]./255, 'FaceColor','interp')
% Following the same method as before,
% the profile is designed with four serrated cycles to simulate the four sepals.
% 还是之前的方法，不过让轮廓有4个锯齿状周期来模拟四片花萼
% Sepals generation with 4-lobed pattern / 生成四片花萼（带4个锯齿状周期）
[X, T] = meshgrid(linspace(0, 1, 100), linspace(0, 1, 100).*2*pi);
P2 = T.*0 + pi/8;
C2 = .5 + (.5 - abs(mod(T, pi/2)/pi*2 - .5))*.4;
Y2 = (- (X.*1 - .5).^7.*128 - 1)./15 - .1;
R2 = C2.*(X.*sin(P2) - Y2.*cos(P2));
H2 = C2.*(X.*cos(P2) + Y2.*sin(P2));
X2 = R2.*cos(T);
Y2 = R2.*sin(T);
% Rotate by 90 degrees around the z-axis
% and reduce the size to render the four smaller sepals.
% 绕z轴旋转90度且减小其大小，绘制四片小花萼
% Smaller sepal layer / 绘制四片小花萼（第二层）
P3 = T.*0 + pi/10;
C3 = .3 + (.5 - abs(mod(T + pi/4, pi/2)/pi*2 - .5))*.7;
Y3 = (- (X.*.7 - .5).^7.*128 - 1)./15 - .1;
R3 = C3.*(X.*sin(P3) - Y3.*cos(P3));
H3 = C3.*(X.*cos(P3) + Y3.*sin(P3));
X3 = R3.*cos(T);
Y3 = R3.*sin(T);
% Colormap for sepals / 花托配色
CList2 = [178,173,113; 151,135, 73; 117,123, 50; 86, 89, 29; 75, 65, 17]./255;
CMat2 = zeros(100, 100, 3);
CMat2(:, :, 1) = repmat(interp1(linspace(0, 1, size(CList2, 1)), CList2(:, 1), linspace(0, 1, 100)), [100, 1]);
CMat2(:, :, 2) = repmat(interp1(linspace(0, 1, size(CList2, 1)), CList2(:, 2), linspace(0, 1, 100)), [100, 1]);
CMat2(:, :, 3) = repmat(interp1(linspace(0, 1, size(CList2, 1)), CList2(:, 3), linspace(0, 1, 100)), [100, 1]);
% Render sepals / 绘制花托
surf(X2, Y2, H2.*.8 + .12, 'CData',CMat2, 'EdgeAlpha',0.1, 'EdgeColor',CList2(end,:), 'FaceColor','interp')
surf(X3.*.93, Y3.*.92, H3.*.5 + .02, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
[U2, V2, W2] = matRotate(X2, Y2, H2.*.8 + .12, Rx1);
[U3, V3, W3] = matRotate(X3.*.93, Y3.*.92, H3.*.5 + .02, Rx1);
surf(U2 + .7, V2 - .7, W2 - .6, 'CData',CMat2, 'EdgeAlpha',0.1, 'EdgeColor',CList2(end,:), 'FaceColor','interp')
surf(U3 + .7, V3 - .7, W3 - .6, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
% A pulse function with two periods is applied
% to the contour to simulate the leaves.
% 让轮廓有2个周期且是脉冲函数，来模拟叶片
P4 = T.*0 + pi/16;
C4 = - abs(mod(T, pi)/pi - .5) + .11;
C4(C4 < 0) = 0; C4 = C4.*10; C4(51:100, :) = C4(51:100, :).*.7;
Y4 = (- (X.*1.01 - .5).^7.*128 - 1)./15 - .03;
R4 = C4.*(X.*sin(P4) - Y4.*cos(P4));
H4 = C4.*(X.*cos(P4) + Y4.*sin(P4));
X4 = R4.*cos(T);
Y4 = R4.*sin(T);
surf(X4 - .1, Y4 + .05, H4 - 2.2, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
[U4, V4, W4] = matRotate(X4 - .1, Y4 - .1, H4 + .1, Rz1);
[U4, V4, W4] = matRotate(U4, V4, W4, Rx1);
surf(U4 + .7, V4 - .7 + 1, W4 - .6 - 1.2, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
P5 = T.*0 + pi/8;
C5 = - abs(mod(T + pi/6, pi)/pi - .5) + .11;
C5(C5 < 0) = 0; C5 = C5.*5;
Y5 = (- (X.*1.01 - .5).^7.*128 - 1)./15 - .1;
R5 = C5.*(X.*sin(P5) - Y5.*cos(P5));
H5 = C5.*(X.*cos(P5) + Y5.*sin(P5));
X5 = R5.*cos(T);
Y5 = R5.*sin(T);
surf(X5, Y5, H5 - .3, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
[U5, V5, W5] = matRotate(X5, Y5, H5+.1, Rx1);
surf(U5 + .7, V5 - .7 + 1/4, W5 - .6 - 1.7/4, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
% Render stems / 绘制花杆
P1_1 = [mean(X3(:).*.93), mean(Y3(:).*.92), mean(H3(:).*.5 + .02)];
P1_2 = [mean(X5(:)), mean(Y5(:)), mean(H5(:) - .3)];
P1_3 = [mean(X4(:) - .1), mean(Y4(:) + .05), mean(H4(:) - 2.2)];
P1_3 = (P1_3 - P1_2).*1.4 + P1_2;
[XX1, YY1, ZZ1] = cylinderXYZ(P1_1, P1_2, .05);
[XX2, YY2, ZZ2] = cylinderXYZ(P1_2, P1_3, .04);
surf(XX1, YY1, ZZ1, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
surf(XX2, YY2, ZZ2, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
P1_1 = [mean(U3(:) + .7), mean(V3(:) - .7), mean(W3(:) - .6)];
P1_2 = [mean(U5(:) + .7), mean(V5(:) - .7 + 1/4), mean(W5(:) - .6 - 1.7/4)];
P1_3 = [mean(U4(:) + .7), mean(V4(:) - .7 + 1), mean(W4(:) - .6 - 1.2)];
P1_3 = (P1_3 - P1_2).*2.4 + P1_2;
[XX1, YY1, ZZ1] = cylinderXYZ(P1_1, P1_2, .05);
[XX2, YY2, ZZ2] = cylinderXYZ(P1_2, P1_3, .04);
surf(XX1, YY1, ZZ1, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
surf(XX2, YY2, ZZ2, 'FaceColor',[ 84, 85, 54]./255, 'EdgeAlpha',0.1, 'EdgeColor','k')
% 在任意两点间构建圆柱
function [XX, YY, ZZ] = cylinderXYZ(P1, P2, r)
% CYLINDERXYZ Create a cylinder connecting two 3D points
% [XX, YY, ZZ] = cylinderXYZ(P1, P2, r) generates a cylinder
% of radius r between points P1 and P2.
v = P2 - P1; l = norm(v);
if l < eps, return; end
[XX, YY, ZZ] = cylinder(r, 30); ZZ = ZZ * l;
ddir = [0, 0, 1]; tdir = v / l;
if dot(ddir, tdir) > 0.9999
R = eye(3);
elseif dot(ddir, tdir) < -0.9999
R = [1, 0, 0; 0, -1, 0; 0, 0, -1];
else
av = cross(ddir, tdir); av = av / norm(av);
R = axisRotate(av, acos(dot(ddir, tdir)));
end
for ii = 1:size(XX, 1)
for jj = 1:size(XX, 2)
p = R * [XX(ii, jj); YY(ii, jj); ZZ(ii, jj)];
XX(ii, jj) = p(1) + P1(1);
YY(ii, jj) = p(2) + P1(2);
ZZ(ii, jj) = p(3) + P1(3);
end
end
end
% 通过矩阵旋转数据
function [U, V, W] = matRotate(X, Y, Z, R)
% MATROTATE Apply 3x3 rotation matrix to a set of 3D points
% [U,V,W] = matRotate(X,Y,Z,R) rotates points (X,Y,Z)
% using rotation matrix R.
U = X; V = Y; W = Z;
for ii = 1:numel(X)
v = [X(ii); Y(ii); Z(ii)];
n = R*v; U(ii) = n(1); V(ii) = n(2); W(ii) = n(3);
end
end
% 根据轴-角参数生成旋转矩阵
function R = axisRotate(axis, angle)
% AXISROTATE Compute rotation matrix from axis-angle representation
% R = axisRotate(axis, angle) returns a 3x3 rotation matrix
% for rotating by angle (radians) around the given axis vector.
% Implementation based on Rodrigues' rotation formula.
u = axis(1); v = axis(2); w = axis(3);
c = cos(angle); s = sin(angle);
R = [u^2 + (1-u^2)*c, u*v*(1-c) - w*s, u*w*(1-c) + v*s;
u*v*(1-c) + w*s, v^2 + (1-v^2)*c, v*w*(1-c) - u*s;
u*w*(1-c) - v*s, v*w*(1-c) + u*s, w^2 + (1-w^2)*c];
end
end
