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Have you ever used Live Tasks in MATLAB? MathWorks development team would like to get some feedback on your experience – what did you like and not like. Especially, if you know about it but don’t use it frequently, we would like to understand why?
Please tell us what you think by submitting your response to this form https://forms.office.com/r/ui1EGqAFDx
A key aspect to masting MATLAB Graphics is getting a hang of the MATLAB Graphics Object Hierarchy which is essentially the structure of MATLAB figures that is used in the rendering pipeline. The base object is the Graphics Root (see groot) which contains the Figure. The Figure contains Axes or other containers such as a Tiled Chart Layout (see tiledlayout). Then these Axes can contain graphics primatives (the objects that contain data and get rendered) such as Lines or Patches.
Every graphics object has two important properties, the "Parent" and "Children" properties which can be used to access other objects in the tree. This can be very useful when trying to customize a pre-built chart (such as adding grid lines to both axes in an eye diagram chart) or when trying to access the axes of a non-current figure via a primative (so "gca" doesn't help out).
One last Tip and Trick with this is that you can declare graphics primatives without putting them on or creating an Axes by setting the first input argument to "gobjects(0)" which is an empty array of placeholder graphics objects. Then, when you have an Axes to plot the primitive on and are ready to render it, you can set the "Parent" of the object to your new Axes.
For Example:
l = line(gobjects(0), 1:10, 1:10);
...
...
...
l.Parent = gca;
Practicing navigating and exploring this tree will help propel your understanding of plotting in MATLAB.
MathWorks just released three new courses on Coursera liseted below. If you work with image or video data and are wanting to incorporate deep learning techniques into your workflow, this is a great opporutnity. The course creators monitor the discussion forums, so you can ask questions and get feedback on your work. Below are links to the three courses and a quick description of a project you'll complete in each.
  1. Introduction to Computer Vision for Deep Learning. You'll train a classifier to classify images of people signing the American Sign Language alphabet.
  2. Deep Learning for Object Detection. Move from just classification to finding object locations. You'll train a model to find different types of parking available on the MathWorks campus.
  3. Advanced Deep Learning Techniques for Computer Vision. You'll train anomaly detection models for medical images and use AI-assisted labeling auto label images.
I just now discovered Discussions.
Can anyone provide insight into the intended difference between Discussions and Answers and what should be posted where?
Just scrolling through Discussions, I saw postst that seem more suitable Answers?
What exactly does Discussions bring to the table that wasn't already brought by Answers?
Maybe this question is more suitable for a Discussion ....
Hans Scharler
Hans Scharler
Last activity on 29 Jan 2024

TIL spy

spy
Hello Community!
We are working on a new translation experience for the MathWorks website and products. The goal is to make it easy for people to see content in the best language for them.
Step 1 is learning from those of you who use another language instead of, or in addition to English. If this sounds like you, we'd love your response to a brief survey.
MathWorks Language and Translation Survey
Feel free to comment here as well. Thanks in advance!
We've released an open-source implementation of STIPA (Speech Transmission Index for Public Address) on GitHub!
GitHub Repository: https://github.com/zawi01/stipa
What is STIPA?
Speech Transmission Index is a metric designed to assess the quality of speech transmission through a communication channel. It quantifies the intelligibility of speech signals based on amplitude modulations, providing a standardized measure crucial for evaluating public address systems and communication equipment. STIPA is a version of STI using a simplified measurement method and only one test signal.
Quality Representation:
STI values range from 0 to 1, categorizing speech transmission quality from bad to excellent. The raw STI score can be transformed into the likelihood of intelligibility of syllables, words, and sentences being comprehended.
Verification Tests:
To ensure reliability, we've conducted verification tests according to the IEC 60286-16 standard. Download the test signals and run the stipaVerificationTests.m script from our GitHub repository.
Control Measurements:
We've performed comparative measurements in a university auditorium, showcasing the validity of our implementation.
License:
Our STIPA implementation is distributed under the GNU General Public License 3, reflecting our commitment to open-source collaboration.
I recently wrote about the new ODE solution framework in MATLAB over the The MATLAB Blog The new solution framework for Ordinary Differential Equations (ODEs) in MATLAB R2023b » The MATLAB Blog - MATLAB & Simulink (mathworks.com)
This was a very popular post at the time - many thousands of views. Clearly everyone cares about ODEs in MATLAB.
This made me wonder. If you could wave a magic wand, what ODE functionality would you have next and why?
Over at Reddit, a MATLAB user asked about when to use a script vs. a live script. How would you answer this?
Starting with MATLAB can be daunting, but the right resources make all the difference. In my experience, the combination of MATLAB Onramp and Cody offers an engaging start.
MATLAB Onramp introduces you to MATLAB's basic features and workflows. Then practice your coding skill on Cody. Challenge yourself to solve 1 basic problem every day for a month! This consistent practice can significantly enhance your proficiency.
What other resources have helped you on your MATLAB journey? Share your recommendations and let's create a comprehensive learning path for beginners!
AMIT SURYAVANSHI
AMIT SURYAVANSHI
Last activity on 13 Jan 2024

Software defined ration

i am just thinking to make a project on software defined ratio SDR using matlab and its toolboxes but I am UG student in ECE don't know how to start can we have discussion here and want the guidance from the best or good persons in the field of wireless communication
I would tell myself to understand vectorization. MATLAB is designed for operating on whole arrays and matrices at once. This is often more efficient than using loops.
Matt J
Matt J
Last activity on 29 Jan 2024

3D polyshapes

Is there a reason for TMW not to invest in 3D polyshapes? Is the mathematical complexity of having all the same operations in 3D (union, intersection, subtract,...) prohibitive?
I noticed a couple new replies show up on the recent poll a day or so ago, but since then, the page can't be loaded anymore in any browser I've tried.
https://www.mathworks.com/matlabcentral/discussions/highlights/838494
cui,xingxing
cui,xingxing
Last activity on 4 Jan 2024

Matlab full support for python?

Is MathWorks going to spend 5 years starting in 2024 making Python the #1 supported language?
https://programmerhumor.io/programming-memes/the-pain-and-suffering-caused-by-matlab-will-finally-end-soon/
I'm not sure it's authentic information, and am looking forward to a high level of integration with python.
Reference:
https://www.mathworks.com/content/dam/mathworks/fact-sheet/using-matlab-with-python-cheat-sheet.pdf?source=15572&s_eid=psm_15572
Quick answer: Add set(hS,'Color',[0 0.4470 0.7410]) to code line 329 (R2023b).
Explanation: Function corrplot uses functions plotmatrix and lsline. In lsline get(hh(k),'Color') is called in for cycle for each line and scatter object in axes. Inside the corrplot it is also called for all axes, which is slow. However, when you first set the color to any given value, internal optimization makes it much faster. I chose [0 0.4470 0.7410], because it is a default color for plotmatrix and corrplot and this setting doesn't change a behavior of corrplot.
Suggestion for a better solution: Add the line of code set(hS,'Color',[0 0.4470 0.7410]) to the function plotmatrix. This will make not only corrplot faster, but also any other possible combinations of plotmatrix and get functions called like this:
h = plotmatrix(A);
% set(h,'Color',[0 0.4470 0.7410])
for k = 1:length(h(:))
get(h(k),'Color');
end
We are thrilled to announce the grand prize winners of our MATLAB Flipbook contest! This year, we invited the MATLAB Graphics Infrastructure team, renowned for their expertise in exporting and animation workflows, to be our judges. After careful consideration, they have selected the top three winners:
1st place - Rolling fog / Tim
Judge comments: Creative and realistic rendering with well-written code
2nd place - Christmas Tree / Zhaoxu Liu
Judge comments: Festive and advanced animation that is appropriate to the current holiday season.
3rd place - Energy / Nikolay Velkov
Judge comments: Nice translation of existing shader logic to MATLAB that produces an advanced and appealing visual effect.
In addition, after validating the votes, we are pleased to announce the top 10 participants on the leaderboard:
Congratulations to all! Your creativity and skills have inspired many of us to explore and learn new skills, and make this contest a big success!
The MATLAB Flipbook Mini Hack contest has concluded! During the 4 weeks, over 600 creative animations have been created. We had a lot of fun and a great learning experience! Thank you, everyone!
Now it’s the time to announce week 4 winners. Note that grand prize winners will be announced shortly after we validate votes on winning entries.
Realism:
Tim / Moonrun
Daniel Pereira / Earth with labels!
O / Skywheel
Vasilis Bellos / Isle of Storms
Holiday & Season:
Zhaoxu Liu / slandarer / The Fierce Ghost of Halloween
Shanshan / Snowman
Jr / timeless 80s
Abstract:
VMM / Diffusion/Reaction
Adrien Leygue / a walk in 13D
Jan Studnicka / River
Nikolay Velkov / Energy
leon t / Stable Manifold of Lorenz System
Cartoon:
Sarah / rock hammer
Congratulations, weekly winners!We will reach out to you shortly for your prizes.