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Congratulations, @Cris LaPierre for achieving 10K reputation points.
You reached this milestone by providing valuable contribution to the community since you started answering questions in Since September 2018.
You provided 3984 answers and received 1142 votes. You are ranked #24 in the community. Thank you for your contribution to the community and please keep up the good track record!
MATLAB Central Team
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
The MATLAB AI Chat Playground is now open to the whole community! Answer questions, write first draft MATLAB code, and generate examples of common functions with natural language.
The playground features a chat panel next to a lightweight MATLAB code editor. Use the chat panel to enter natural language prompts to return explanations and code. You can keep chatting with the AI to refine the results or make changes to the output.
MATLAB AI Chat Playground
Give it a try, provide feedback on the output, and check back often as we make improvements to the model and overall experience.
What amazing animations can be created with no more than 2000 characters of MATLAB code? Check out our GALLERY from the MATLAB Flipbook Mini Hack contest.
Vote on your favorite animations before Dec. 3rd. We will give out MATLAB T-shirts to 10 lucky voters!
Tips: the more you vote, the higher your chance to win.
Emma Farnan
Emma Farnan
Last activity on 28 Nov 2023

Add alpha capability to "Line" class

I think it would be a really great feature to be able to add an Alpha property to the basic "Line" class in MATLAB plots. I know that I have previously had to resort to using Patch to be able to plot semitransparent lines, but there are also so many other functions that rely on the "Line" class.
For example, if you want to make a scatter plot from a table with things specified into groups, you can use ScatterHistogram or gscatter but since gscatter uses the Line class, you can't adjust the marker transparency. So if you don't want the histograms, you are stuck with manually separating it and using scatter with hold on.
Hi Guys
Posting this based on a thought I had, so I don't really ahve any code however I would like to know if the thought process is correct and/or relatively accurate.
Consider a simple spring mass system which only allows compression on the spring however when there is tension the mass should move without the effect of the spring distrupting it, thus the mass is just thrown vertically upwards.
The idea which I came up with for such a system is to have two sets of dfferential equations, one which represents the spring system and another which presents a mass in motion without the effects of the spring.
Please refer to the below basic outline of the code which I am proposing. I believe that this may produce relatively decent results. The code essentially checks if there is tension in the system if there is it then takes the last values from the spring mass differential equation and uses it as initial conditions for the differential equation with the mass moving wothout the effects of the spring, this process works in reverse also. The error which would exist is that the initial conditions applied to the system would include effects of the spring. Would there be a better way to code such behaviour?
function xp = statespace(t,x,f,c,k,m)
if (k*x(1)) positive #implying tension
**Use last time step as initial conditions**
**differential equation of a mass moving""
end
if x(1) negative #implying that the mass in now moving down therefore compression in spring
**Use last time step as initial conditions**
**differential equation for a spring mass system**
end
end
Seeing a colleague make this mistake (one I've had to fix multiple times in other's work too) makes me want to ask the community: would you like the awgn() function/blocks to give the option for creating a SNR at the bandwidth of the signal? Your typical flow is something like this:
  • Create a signal, usually at some nominal upsampling factor (e.g., 4) such that it's now nicely over sampled, especially if you're using a RRC or similar pulse shaping filter.
  • Potentially add a frequency offset (which might make the sample frequency even higher)
  • Add AWGN channel model for a desired SNR
  • Put this into your detector/receiver model
The problem is, when someone says, "I'm detecting XYZ at foo SNR," it should not magically improve as a function of the oversample. The problem isn't that awgn() generates white noise, that's what it's supposed to do and the typical receiver has noise across the entire band. The problem is that SNR is most properly defined as the signal power over the noise power spectral density times the signal's noise equivalent bandwidth. Now I looked and there's no handy function for computing NEBW for an input signal (there's just a function for assessing analysis windows). In practice it can get a bit tricky. The occupied bandwidth or HPBW are often close enough to the NEBW, we're usually not haggling over hundredths of a dB. So, in my not so humble opinion, the "measured" flag for awgn() should give an option for bandwidth matching or at least document the behavior better in the help page. All too often I'm seeing 3-6 (or worse) dB errors because people aren't taking the signal's bandwidth into account.
You are invited to join our 2023 community contest – MATLAB Flipbook Mini Hack! This year’s contest revolves around creating interesting animations using MATLAB.
Whether you are a seasoned MATLAB user or just getting started, this contest offers a fantastic opportunity to showcase your skills, learn from others, and engage with the vibrant MATLAB Central community.
Timeframe
This contest runs for 4 weeks from Nov. 6th to Dec. 3rd.
How to play
  • Create a new animation or remix an existing one with up to 2,000 characters of code.
  • Simply vote on the animations you love!
Prizes
You will have opportunities to win compelling prizes, including Amazon gift cards, MathWorks T-shirts, and virtual badges. We will give out both weekly prizes and grand prizes.
Check out the gallery and vote on the animations you like.
The MATLAB Central Community team
Adam Danz
Adam Danz
Last activity on 9 Dec 2023

Why do you save figure (.fig) files?

I rarely/never save .fig files
47%
Continue working on it later
16%
Archive for future reference
23%
Share within my organization
10%
Share outside my organization
2%
Other (please leave a comment)
2%
2097 votes
Julian
Julian
Last activity on 5 Feb 2024

Naming x-values in bar(x,y)

I know the latest version of MATLAB R2023b has this feature already, put it should be added to R2023a as well because of its simplicity and convenience.
Basically, I want to make a bar graph that lets me name each column in a basic bar graph:
y=[100 99 100 200 200 300 500 800 1000];
x=["0-4" "5-17" "18-29" "30-39" "40-49" "50-64" "65-74" "75-84" "85+"];
bar(x,y)
However, in R2023a, this isn't a feature. I think it should be added because it helps to present data and ideas more clearly and professionally, which is the purpose of a graph to begin with.
Matt J
Matt J
Last activity on 1 Mar 2024

Implicit expansion for CAT()

Would it be a good thing to have implicit expansion enabled for cat(), horzcat(), vertcat()? There are often situations where I would like to be able to do things like this:
x=[10;20;30;40];
y=[11;12;13;14];
z=cat(3, 0,1,2);
C=[x,y,z]
with the result,
C(:,:,1) =
10 11 0
20 12 0
30 13 0
40 14 0
C(:,:,2) =
10 11 1
20 12 1
30 13 1
40 14 1
C(:,:,3) =
10 11 2
20 12 2
30 13 2
40 14 2
In the past year, we've witnessed an exponential growth of ChatGPT and other Generative AI tools. AI has quickly become a transformative force across industries, from tech giants to small startups, and even community sites like ours. For instance, Stack Overflow announced its plan to leverage AI tools to draft a question or tag content; Quora built a ChatGPT bot to answer questions; and GitHub is piloting the AI tool for personalized content.
This trend in the community landscape makes me wonder what MATLAB Central community, especially in MATLAB Answers, can do to integrate AI and enhance the community.
Share with us your ideas in the comment session. Ideally one comment per idea, so that others can vote on a secific idea or have deeper discussions about it.
Adam and Heather will be discussing new features in R2023b and answering your questions in a few hours - visit the link below to check out the preview and sign up for notification.
https://www.youtube.com/watch?v=mImQs4PfioM
We launched the Discussions area with 6 channels, based on the existing types of content we see today in the MATLAB Central community.
I'm curious which channels you are most interested in participating, or which channels are missing.
Tell us your thoughts here!
Adam Danz just launched a new blog about MATLAB Graphics and App Building.
https://blogs.mathworks.com/graphics-and-apps/2023/10/10/welcome/
As you know, He has been a prolific contributor to MATLAB Answers and one of his answers recently won the Editor's Choice Award.
If there are any topics or questions you are interested in, please share with Adam, and I am sure he will get those into his blog.
4 months ago, the new API was published to access content on the MATLAB Central community. I shared my MATLAB code to access the API at that time, but the team just released the official SDK.
MATLAB toolbox on File Exchange: https://www.mathworks.com/matlabcentral/fileexchange/135567-matlab-central-interface-for-matlab
Node.js package on NPM: https://www.npmjs.com/package/matlabcentral
Public API Doc: https://api.mathworks.com/
Houman and Rameez will talk about how you can model wireless networks (5G, WLAN, Bluetooth, 802.11ax WLAN mesh, etc.) in MATLAB in the upcoming livestream. They will start with the basics such as nodes, links, topology and metrics. Then they will introduce a new free add-on library that lets you model such networks, and show you how to use it.
Bookmark this link:
https://www.youtube.com/watch?v=2EFpUd5aTFw
Congratulations, @Adam Danz for winning the Editor's Pick badge awarded for MATLAB Answers, in recognition of your awesome solution in overlapping images in grid layout.
Thank you for going to great lengths to help a user in this thread by suggesting alternative approach to representing stack of playing cards in MATLAB, highlighting very interesting features like hggroup.
This badge recognizes awesome answers people contribute and yours was picked for providing a very detailed and helpful answer.
Thank you so much for setting a high standard for MATLAB Answers and for your ongoing contribution to the community.
MATLAB Central Team
Congratuations, @Voss, for htting this important miletone!
You had a meteoric rise to in our community since you started answering questions in June 2020.
You provided 3218 answers and 926 votes. You are ranked #23 in the community. Thank you for your contribution to the community and please keep up the good track record!
MATLAB Central Team
MATLAB Onramp is a free online tutorial and it has been very popular with new MATLAB users to learn how to use it, and MathWorks have been adding more and more modules. The lastest one just dropped https://matlabacademy.mathworks.com/details/power-systems-simulation-onramp/orps
It shows you the basics of power system simulation by modeling a simple microgrid. You will learn how to simulate and measure three-phase circuits, and how to evaluate algorithms like droop control and maximum power point tracking.