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結果:
Imagine you are developing a new toolbox for MATLAB. You have a folder full of a few .m files defining a bunch of functions and you are thinking 'This would be useful for others, I'm going to make it available to the world'
What process would you go through? What's the first thing you'd do?
I have my own opinions but don't want to pollute the start of the conversation :)
I am glad to inform and share with you all my new text book titled "Inverters and AC Drives
Control, Modeling, and Simulation Using Simulink", Springer, 2024. This text book has nine chapters and three appendices. A separate "Instructor Manual" is rpovided with solutions to selected model projects. The salent features of this book are given below:
- Provides Simulink models for various PWM techniques used for inverters
- Presents vector and direct torque control of inverter-fed AC drives and fuzzy logic control of converter-fed AC drives
- Includes examples, case studies, source codes of models, and model projects from all the chapters
The Springer link for this text book is given below:
This book is also in the Mathworks book program:
Inverters and AC Drives: Control, Modeling, and Simulation Using Simulink
Successful development of power electronic converters and converter-fed electric drives involves system modeling, analyzing the output voltage, current, electromagnetic torque, and machine speed, and making necessary design changes before hardware implementation. Inverters and AC Drives: Control, Modeling, and Simulation Using Simulink offers readers Simulink models for single, multi-triangle carrier, selective harmonic elimination, and space vector PWM techniques for three-phase two-level, multi-level (including modular multi-level), Z-source, Quasi Z-source, switched inductor, switched capacitor and diode assisted extended boost inverters, six-step inverter-fed permanent magnet synchronous motor (PMSM), brushless DC motor (BLDCM) and induction motor (IM) drives, vector-controlled PMSM, IM drives, direct torque-controlled inverter-fed IM drives, and fuzzy logic controlled converter-fed AC drives with several examples and case studies.
It is time to support the cameraIntrinsics function to accept a 3-by-3 intrinsic matrix K as an input parameter for constructing the object. Currently, the built-in cameraIntrinsics function can only be constructed by explicitly specifying focalLength, principalPoint, and imageSize. This approach has drawbacks, as it is not very intuitive. In most application scenarios, using the intrinsic matrix
K=[fx,0,cx;
0,fy,cy;
0,0,1]
is much more straightforward and effective!
intrinsics = cameraIntrinsics(K)
tiledlayout(4,1);
% Plot "L" (y = 1/(x+1), for x > -1)
x = linspace(-0.9, 2, 100); % Avoid x = -1 (undefined)
y =1 ./ (x+1) ;
nexttile;
plot(x, y, 'r', 'LineWidth', 2);
xlim([-10,10])
% Plot "O" (x^2 + y^2 = 9)
theta = linspace(0, 2*pi, 100);
x = 3 * cos(theta);
y = 3 * sin(theta);
nexttile;
plot(x, y, 'r', 'LineWidth', 2);
axis equal;
% Plot "V" (y = -2|x|)
x = linspace(-1, 1, 100);
y = 2 * abs(x);
nexttile;
plot(x, y, 'r', 'LineWidth', 2);
axis equal;
% Plot "E" (x = -3 |sin(y)|)
y = linspace(-pi, pi, 100);
x = -3 * abs(sin(y));
nexttile;
plot(x, y, 'r', 'LineWidth', 2);
axis equal;
I've been trying this problem a lot of time and i don't understand why my solution doesnt't work.
In 4 tests i get the error Assertion failed but when i run the code myself i get the diag and antidiag correctly.
function [diag_elements, antidg_elements] = your_fcn_name(x)
[m, n] = size(x);
% Inicializar los vectores de la diagonal y la anti-diagonal
diag_elements = zeros(1, min(m, n));
antidg_elements = zeros(1, min(m, n));
% Extraer los elementos de la diagonal
for i = 1:min(m, n)
diag_elements(i) = x(i, i);
end
% Extraer los elementos de la anti-diagonal
for i = 1:min(m, n)
antidg_elements(i) = x(m-i+1, i);
end
end
I love it all
45%
Love the first snowfall only
15%
Hate it
17.5%
It doesn't snow where I live
22.5%
40 票
For Valentine's day this year I tried to do something a little more than just the usual 'Here's some MATLAB code that draws a picture of a heart' and focus on how to share MATLAB code. TL;DR, here's my advice
- Put the code on GitHub. (Allows people to access and collaborate on your code)
- Set up 'Open in MATLAB Online' in your GitHub repo (Allows people to easily run it)
I used code by @Zhaoxu Liu / slandarer and others to demonstrate. I think that those two steps are the most impactful in that they get you from zero to one but If I were to offer some more advice for research code it would be
3. Connect the GitHub repo to File Exchange (Allows MATLAB users to easily find it in-product).
4. Get a Digitial Object Identifier (DOI) using something like Zenodo. (Allows people to more easily cite your code)
There is still a lot more you can do of course but if everyone did this for any MATLAB code relating to a research paper, we'd be in a better place I think.
Here's the article: On love and research software: Sharing code with your Valentine » The MATLAB Blog - MATLAB & Simulink
What do you think?
Have you ever wanted to search for a community member but didn't know where to start? Or perhaps you knew where to search but couldn't find enough information from the results? You're not alone. Many community users have shared this frustration with us. That's why the community team is excited to introduce the new ‘People’ page to address this need.
What Does the ‘People’ Page Offer?
- Comprehensive User Search: Search for users across different applications seamlessly.
- Detailed User Information: View a list of community members along with additional details such as their join date, rankings, and total contributions.
- Sorting Options: Use the ‘sort by’ filter located below the search bar to organize the list according to your preferences.
- Easy Navigation: Access the Answers, File Exchange, and Cody Leaderboard by clicking the ‘Leaderboards’ button in the upper right corner.
In summary, the ‘People’ page provides a gateway to search for individuals and gain deeper insights into the community.
How Can You Access It?
Navigate to the global menu, click on the ‘More’ link, and you’ll find the ‘People’ option.
Now you know where to go if you want to search for a user. We encourage you to give it a try and share your feedback with us.
Los invito a conocer el libro "Sistemas dinámicos en contexto: Modelación matemática, simulación, estimación y control con MATLAB", el cual estará disponible pronto en formato digital.
El libro integra diversos temas de los sistemas dinámicos desde un punto de vista práctico utilizando programas de MATLAB y simulaciones en Simulink y utilizando métodos numéricos (ver enlace). Existe mucho material en el blog del libro con posibilidades para comentarios, propuestas y correcciones. Resalto los casos de estudio
Creo que el libro les puede dar un buen panorama del área con la posibilidad de experimentar de manera interactiva con todo el material de MATLAB disponible en formato Live Script. Lo mejor es que se pueden formular preguntas en el blog y hacer propuestas al autor de ejercicios resueltos.
Son bienvenidos los comentarios, sugerencias y correcciones al texto.
I got thoroughly nerd-sniped by this xkcd, leading me to wonder if you can use MATLAB to figure out the dice roll for any given (rational) probability. Well, obviously you can. The question is how. Answer: lots of permutation calculations and convolutions.
In the original xkcd, the situation described by the player has a probability of 2/9. Looking up the plot, row 2 column 9, shows that you need 16 or greater on (from the legend) 1d4+3d6, just as claimed.
If you missed the bit about convolutions, this is a super-neat trick
[v,c] = dicedist([4 6 6 6]);
bar(v,c)
% Probability distribution of dice given by d
function [vals,counts] = dicedist(d)
% d is a vector of number of sides
n = numel(d); % number of dice
% Use convolution to count the number of ways to get each roll value
counts = 1;
for k = 1:n
counts = conv(counts,ones(1,d(k)));
end
% Possible values range from n to sum(d)
maxtot = sum(d);
vals = n:maxtot;
end
MATLAB FEX(MATLAB File Exchange) should support Markdown syntax for writing. In recent years, many open-source community documentation platforms, such as GitHub, have generally supported Markdown. MATLAB is also gradually improving its support for Markdown syntax. However, when directly uploading files to the MATLAB FEX community and preparing to write an overview, the outdated document format buttons are still present. Even when directly uploading a Markdown document, it cannot be rendered. We hope the community can support Markdown syntax!
BTW，I know that open-source Markdown writing on GitHub and linking to MATLAB FEX is feasible, but this is a workaround. It would be even better if direct native support were available.
I am very pleased to share my book, with coauthors Professor Richard Davis and Associate Professor Sam Toan, titled "Chemical Engineering Analysis and Optimization Using MATLAB" published by Wiley: https://www.wiley.com/en-us/Chemical+Engineering+Analysis+and+Optimization+Using+MATLAB-p-9781394205363
Also in The MathWorks Book Program:
Chemical Engineering Analysis and Optimization Using MATLAB® introduces cutting-edge, highly in-demand skills in computer-aided design and optimization. With a focus on chemical engineering analysis, the book uses the MATLAB platform to develop reader skills in programming, modeling, and more. It provides an overview of some of the most essential tools in modern engineering design.
Chemical Engineering Analysis and Optimization Using MATLAB® readers will also find:
- Case studies for developing specific skills in MATLAB and beyond
- Examples of code both within the text and on a companion website
- End-of-chapter problems with an accompanying solutions manual for instructors
This textbook is ideal for advanced undergraduate and graduate students in chemical engineering and related disciplines, as well as professionals with backgrounds in engineering design.
MathWorks
Accelerating the pace of engineering and science.
My following code works running Matlab 2024b for all test cases. However, 3 of 7 tests fail (#1, #4, & #5) the QWERTY Shift Encoder problem. Any ideas what I am missing?
Thanks in advance.
keyboardMap1 = {'qwertyuiop[;'; 'asdfghjkl;'; 'zxcvbnm,'};
keyboardMap2 = {'QWERTYUIOP{'; 'ASDFGHJKL:'; 'ZXCVBNM<'};
if length(s) == 0
se = s;
end
for i = 1:length(s)
if double(s(i)) >= 65 && s(i) <= 90
row = 1;
col = 1;
while ~strcmp(s(i), keyboardMap2{row}(col))
if col < length(keyboardMap2{row})
col = col + 1;
else
row = row + 1;
col = 1;
end
end
se(i) = keyboardMap2{row}(col + 1);
elseif double(s(i)) >= 97 && s(i) <= 122
row = 1;
col = 1;
while ~strcmp(s(i), keyboardMap1{row}(col))
if col < length(keyboardMap1{row})
col = col + 1;
else
row = row + 1;
col = 1;
end
end
se(i) = keyboardMap1{row}(col + 1);
else
se(i) = s(i);
end
% if ~(s(i) = 65 && s(i) <= 90) && ~(s(i) >= 97 && s(i) <= 122)
% se(i) = s(i);
% end
end
Too small
22%
Just right
38%
Too large
40%
2648 票
In one of my MATLAB projects, I want to add a button to an existing axes toolbar. The function for doing this is axtoolbarbtn:
axtoolbarbtn(tb,style,Name=Value)
However, I have found that the existing interfaces and behavior make it quite awkward to accomplish this task.
Here are my observations.
Adding a Button to the Default Axes Toolbar Is Unsupported
plot(1:10)
ax = gca;
tb = ax.Toolbar
Calling axtoolbarbtn on ax results in an error:
>> axtoolbarbtn(tb,"state")
Error using axtoolbarbtn (line 77)
Modifying the default axes toolbar is not supported.
Default Axes Toolbar Can't Be Distinguished from an Empty Toolbar
The Children property of the default axes toolbar is empty. Thus, it appears programmatically to have no buttons, just like an empty toolbar created by axtoolbar.
cla
plot(1:10)
ax = gca;
tb = ax.Toolbar;
tb.Children
ans = 0x0 empty GraphicsPlaceholder array.
tb2 = axtoolbar(ax);
tb2.Children
ans = 0x0 empty GraphicsPlaceholder array.
A Workaround
An empty axes toolbar seems to have no use except to initalize a toolbar before immediately adding buttons to it. Therefore, it seems reasonable to assume that an axes toolbar that appears to be empty is really the default toolbar. While we can't add buttons to the default axes toolbar, we can create a new toolbar that has all the same buttons as the default one, using axtoolbar("default"). And then we can add buttons to the new toolbar.
That observation leads to this workaround:
tb = ax.Toolbar;
if isempty(tb.Children)
% Assume tb is the default axes toolbar. Recreate
% it with the default buttons so that we can add a new
% button.
tb = axtoolbar(ax,"default");
end
btn = axtoolbarbtn(tb);
% Then set up the button as desired (icon, callback,
% etc.) by setting its properties.
As workarounds go, it's not horrible. It just seems a shame to have to delete and then recreate a toolbar just to be able to add a button to it.
The worst part about the workaround is that it is so not obvious. It took me a long time of experimentation to figure it out, including briefly giving it up as seemingly impossible.
The documentation for axtoolbarbtn avoids the issue. The most obvious example to write for axtoolbarbtn would be the first thing every user of it will try: add a toolbar button to the toolbar that gets created automatically in every call to plot. The doc page doesn't include that example, of course, because it wouldn't work.
My Request
I like the axes toolbar concept and the axes interactivity that it promotes, and I think the programming interface design is mostly effective. My request to MathWorks is to modify this interface to smooth out the behavior discontinuity of the default axes toolbar, with an eye towards satisfying (and documenting) the general use case that I've described here.
One possible function design solution is to make the default axes toolbar look and behave like the toolbar created by axtoolbar("default"), so that it has Children and so it is modifiable.
I am curious as to how my goal can be accomplished in Matlab.
The present APP called "Matching Network Designer" works quite well, but it is limited to a single section of a "PI", a "TEE", or an "L" topology circuit.
This limits the bandwidth capability of the APP when the intended use is to create an amplifier design intended for wider bandwidth projects.
I am requesting that a "Broadband Matching Network Designer" APP be developed by you, the MathWorks support team.
One suggestion from me is to be able to cascade a second section (or "pole") to the first.
Then the resulting topology would be capable of achieving that wider bandwidth of the microwave amplifier project where it would be later used with the transistor output and input matching networks.
Instead of limiting the APP to a single frequency, the entire s parameter file would be used as an input.
The APP would convert the polar s parameters to rectangular scaler complex impedances that you already use.
At that point, having started out with the first initial center frequency, the other frequencies both greater than and less than the center would come into use by an optimization of the circuit elements.
I'm hoping that you will be able to take on this project.
I can include an attachment of such a Matching Network Designer APP that you presently have if you like.
That network is centered at 10 GHz.
Kimberly Renee Alvarez.
310-367-5768
私の場合、前の会社が音楽認識アプリの会社で、アルゴリズム開発でFFTが使われていたことがきっかけでした。でも、MATLABのすごさが分かったのは、機械学習のオンライン講座で、Andrew Ngが、線型代数を使うと、数式と非常に近い構文のコードで問題が処理できることを学んだ時でした。
Overview
Authors:
- Narayanaswamy P.R. Iyer
- Provides Simulink models for various PWM techniques used for inverters
- Presents vector and direct torque control of inverter-fed AC drives and fuzzy logic control of converter-fed AC drives
- Includes examples, case studies, source codes of models, and model projects from all the chapters.
About this book
Successful development of power electronic converters and converter-fed electric drives involves system modeling, analyzing the output voltage, current, electromagnetic torque, and machine speed, and making necessary design changes before hardware implementation. Inverters and AC Drives: Control, Modeling, and Simulation Using Simulink offers readers Simulink models for single, multi-triangle carrier, selective harmonic elimination, and space vector PWM techniques for three-phase two-level, multi-level (including modular multi-level), Z-source, Quasi Z-source, switched inductor, switched capacitor and diode assisted extended boost inverters, six-step inverter-fed permanent magnet synchronous motor (PMSM), brushless DC motor (BLDCM) and induction motor (IM) drives, vector-controlled PMSM, IM drives, direct torque-controlled inverter-fed IM drives, and fuzzy logic controlled converter-fed AC drives with several examples and case studies. Appendices in the book include source codes for all relevant models, model projects, and answers to selected model projects from all chapters.
This textbook will be a valuable resource for upper-level undergraduate and graduate students in electrical and electronics engineering, power electronics, and AC drives. It is also a hands-on reference for practicing engineers and researchers in these areas.
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