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I have written two tools and uploaded fileexchange, which allows us to easily draw chord diagrams：
chord chart 弦图
download:
https://www.mathworks.com/matlabcentral/fileexchange/116550-chord-chart
demo:
dataMat=[2 0 1 2 5 1 2;
3 5 1 4 2 0 1;
4 0 5 5 2 4 3];
dataMat=dataMat+rand(3,7);
dataMat(dataMat<1)=0;
colName={'G1','G2','G3','G4','G5','G6','G7'};
rowName={'S1','S2','S3'};
CC=chordChart(dataMat,'rowName',rowName,'colName',colName);
CC=CC.draw();
CC.setFont('FontSize',17,'FontName','Cambria')
% 显示刻度和数值
% Displays scales and numeric values
CC.tickState('on')
CC.tickLabelState('on')
% 调节标签半径
% Adjustable Label radius
CC.setLabelRadius(1.4);
Digraph chord chart 有向弦图
download:
https://www.mathworks.com/matlabcentral/fileexchange/121043-digraph-chord-chart
demo:
dataMat=randi([0,8],[6,6]);
% 添加标签名称
NameList={'CHORD','CHART','MADE','BY','SLANDARER','MATLAB'};
BCC=biChordChart(dataMat,'Label',NameList,'Arrow','on');
BCC=BCC.draw();
% 添加刻度
BCC.tickState('on')
% 修改字体，字号及颜色
BCC.setFont('FontName','Cambria','FontSize',17,'Color',[.2,.2,.2])
BCC.setLabelRadius(1.3);
BCC.tickLabelState('on')
How to create a legend as follows?
Principle Explanation - Graphic Objects
Hidden Properties of Legend are laid as follows
In most cases, legends are drawn using LineLoop and Quadrilateral:
Both of these basic graphic objects are drawn in groups of four points, and the general principle is as follows:
Of course, you can arrange the points in order, or set VertexIndices whitch means the vertex order to obtain the desired quadrilateral shape:
Other objects
Compared to objects that can only be grouped into four points, we also need to introduce more flexible objects. Firstly, LineStrip, a graphical object that draws lines in groups of two points:
And TriangleStrip is a set of three points that draw objects to fill triangles, for example, complex polygons can be filled with multiple triangles:
Principle Explanation - Create and Replace
Let's talk about how to construct basic graphic objects, which are all constructed using undisclosed and very low-level functions, such as LineStrip, not through:
  • LineStrip()
It is built through:
  • matlab.graphics.primitive.world.LineStrip()
After building the object, the following properties must be set to make the hidden object visible:
  • Layer
  • ColorBinding
  • ColorData
  • VertexData
  • PickableParts
The settings of these properties can refer to the original legend to form the object, which will not be elaborated here. You can also refer to the code I wrote.
Afterwards, set the newly constructed object's parent class as the Group parent class of the original component, and then hide the original component
newBoxEdgeHdl.Parent=oriBoxEdgeHdl.Parent;
oriBoxEdgeHdl.Visible='off';
The above is the entire process of component replacement, with two example codes written:
Semi transparent legend
function SPrettyLegend(lgd)
% Semitransparent rounded rectangle legend
% Copyright (c) 2023, Zhaoxu Liu / slandarer
% -------------------------------------------------------------------------
% Zhaoxu Liu / slandarer (2023). pretty legend
% (https://www.mathworks.com/matlabcentral/fileexchange/132128-pretty-legend),
% MATLAB Central File Exchange. 检索来源 2023/7/9.
% =========================================================================
if nargin<1
ax = gca;
lgd = get(ax,'Legend');
end
pause(1e-6)
Ratio = .1;
t1 = linspace(0,pi/2,4); t1 = t1([1,2,2,3,3,4]);
t2 = linspace(pi/2,pi,4); t2 = t2([1,2,2,3,3,4]);
t3 = linspace(pi,3*pi/2,4); t3 = t3([1,2,2,3,3,4]);
t4 = linspace(3*pi/2,2*pi,4); t4 = t4([1,2,2,3,3,4]);
XX = [1,1,1-Ratio+cos(t1).*Ratio,1-Ratio,Ratio,Ratio+cos(t2).*Ratio,...
0,0,Ratio+cos(t3).*Ratio,Ratio,1-Ratio,1-Ratio+cos(t4).*Ratio];
YY = [Ratio,1-Ratio,1-Ratio+sin(t1).*Ratio,1,1,1-Ratio+sin(t2).*Ratio,...
1-Ratio,Ratio,Ratio+sin(t3).*Ratio,0,0,Ratio+sin(t4).*Ratio];
% 圆角边框(border-radius)
oriBoxEdgeHdl = lgd.BoxEdge;
newBoxEdgeHdl = matlab.graphics.primitive.world.LineStrip();
newBoxEdgeHdl.AlignVertexCenters = 'off';
newBoxEdgeHdl.Layer = 'front';
newBoxEdgeHdl.ColorBinding = 'object';
newBoxEdgeHdl.LineWidth = 1;
newBoxEdgeHdl.LineJoin = 'miter';
newBoxEdgeHdl.WideLineRenderingHint = 'software';
newBoxEdgeHdl.ColorData = uint8([38;38;38;0]);
newBoxEdgeHdl.VertexData = single([XX;YY;XX.*0]);
newBoxEdgeHdl.Parent=oriBoxEdgeHdl.Parent;
oriBoxEdgeHdl.Visible='off';
% 半透明圆角背景(Semitransparent rounded background)
oriBoxFaceHdl = lgd.BoxFace;
newBoxFaceHdl = matlab.graphics.primitive.world.TriangleStrip();
Ind = [1:(length(XX)-1);ones(1,length(XX)-1).*(length(XX)+1);2:length(XX)];
Ind = Ind(:).';
newBoxFaceHdl.PickableParts = 'all';
newBoxFaceHdl.Layer = 'back';
newBoxFaceHdl.ColorBinding = 'object';
newBoxFaceHdl.ColorType = 'truecoloralpha';
newBoxFaceHdl.ColorData = uint8(255*[1;1;1;.6]);
newBoxFaceHdl.VertexData = single([XX,.5;YY,.5;XX.*0,0]);
newBoxFaceHdl.VertexIndices = uint32(Ind);
newBoxFaceHdl.Parent = oriBoxFaceHdl.Parent;
oriBoxFaceHdl.Visible = 'off';
end
Usage examples
clc; clear; close all
rng(12)
% 生成随机点(Generate random points)
mu = [2 3; 6 7; 8 9];
S = cat(3,[1 0; 0 2],[1 0; 0 2],[1 0; 0 1]);
r1 = abs(mvnrnd(mu(1,:),S(:,:,1),100));
r2 = abs(mvnrnd(mu(2,:),S(:,:,2),100));
r3 = abs(mvnrnd(mu(3,:),S(:,:,3),100));
% 绘制散点图(Draw scatter chart)
hold on
propCell = {'LineWidth',1.2,'MarkerEdgeColor',[.3,.3,.3],'SizeData',60};
scatter(r1(:,1),r1(:,2),'filled','CData',[0.40 0.76 0.60],propCell{:});
scatter(r2(:,1),r2(:,2),'filled','CData',[0.99 0.55 0.38],propCell{:});
scatter(r3(:,1),r3(:,2),'filled','CData',[0.55 0.63 0.80],propCell{:});
% 增添图例(Draw legend)
lgd = legend('scatter1','scatter2','scatter3');
lgd.Location = 'northwest';
lgd.FontSize = 14;
% 坐标区域基础修饰(Axes basic decoration)
ax=gca; grid on
ax.FontName = 'Cambria';
ax.Color = [0.9,0.9,0.9];
ax.Box = 'off';
ax.TickDir = 'out';
ax.GridColor = [1 1 1];
ax.GridAlpha = 1;
ax.LineWidth = 1;
ax.XColor = [0.2,0.2,0.2];
ax.YColor = [0.2,0.2,0.2];
ax.TickLength = [0.015 0.025];
% 隐藏轴线(Hide XY-Ruler)
pause(1e-6)
ax.XRuler.Axle.LineStyle = 'none';
ax.YRuler.Axle.LineStyle = 'none';
SPrettyLegend(lgd)
Heart shaped legend (exclusive to pie charts)
function pie2HeartLegend(lgd)
% Heart shaped legend for pie chart
% Copyright (c) 2023, Zhaoxu Liu / slandarer
% -------------------------------------------------------------------------
% Zhaoxu Liu / slandarer (2023). pretty legend
% (https://www.mathworks.com/matlabcentral/fileexchange/132128-pretty-legend),
% MATLAB Central File Exchange. 检索来源 2023/7/9.
% =========================================================================
if nargin<1
ax = gca;
lgd = get(ax,'Legend');
end
pause(1e-6)
% 心形曲线(Heart curve)
x = -1:1/100:1;
y1 = 0.6 * abs(x) .^ 0.5 + ((1 - x .^ 2) / 2) .^ 0.5;
y2 = 0.6 * abs(x) .^ 0.5 - ((1 - x .^ 2) / 2) .^ 0.5;
XX = [x, flip(x),x(1)]./3.4+.5;
YY = ([y1, y2,y1(1)]-.2)./2+.5;
Ind = [1:(length(XX)-1);2:length(XX)];
Ind = Ind(:).';
% 获取图例图标(Get Legend Icon)
lgdEntryChild = lgd.EntryContainer.NodeChildren;
iconSet = arrayfun(@(lgdEntryChild)lgdEntryChild.Icon.Transform.Children.Children,lgdEntryChild,UniformOutput=false);
% 基础边框句柄(Base Border Handle)
newEdgeHdl = matlab.graphics.primitive.world.LineStrip();
newEdgeHdl.AlignVertexCenters = 'off';
newEdgeHdl.Layer = 'front';
newEdgeHdl.ColorBinding = 'object';
newEdgeHdl.LineWidth = .8;
newEdgeHdl.LineJoin = 'miter';
newEdgeHdl.WideLineRenderingHint = 'software';
newEdgeHdl.ColorData = uint8([38;38;38;0]);
newEdgeHdl.VertexData = single([XX;YY;XX.*0]);
newEdgeHdl.VertexIndices = uint32(Ind);
% 基础多边形面句柄(Base Patch Handle)
newFaceHdl = matlab.graphics.primitive.world.TriangleStrip();
Ind = [1:(length(XX)-1);ones(1,length(XX)-1).*(length(XX)+1);2:length(XX)];
Ind = Ind(:).';
newFaceHdl.PickableParts = 'all';
newFaceHdl.Layer = 'middle';
newFaceHdl.ColorBinding = 'object';
newFaceHdl.ColorType = 'truecoloralpha';
newFaceHdl.ColorData = uint8(255*[1;1;1;.6]);
newFaceHdl.VertexData = single([XX,.5;YY,.5;XX.*0,0]);
newFaceHdl.VertexIndices = uint32(Ind);
% 替换图例图标(Replace Legend Icon)
for i = 1:length(iconSet)
oriEdgeHdl = iconSet{i}(1);
tNewEdgeHdl = copy(newEdgeHdl);
tNewEdgeHdl.ColorData = oriEdgeHdl.ColorData;
tNewEdgeHdl.Parent = oriEdgeHdl.Parent;
oriEdgeHdl.Visible = 'off';
oriFaceHdl = iconSet{i}(2);
tNewFaceHdl = copy(newFaceHdl);
tNewFaceHdl.ColorData = oriFaceHdl.ColorData;
tNewFaceHdl.Parent = oriFaceHdl.Parent;
oriFaceHdl.Visible = 'off';
end
end
Usage examples
clc; clear; close all
% 生成随机点(Generate random points)
X = [1 3 0.5 2.5 2];
pieHdl = pie(X);
% 修饰饼状图(Decorate pie chart)
colorList=[0.4941 0.5490 0.4118
0.9059 0.6510 0.3333
0.8980 0.6157 0.4980
0.8902 0.5137 0.4667
0.4275 0.2824 0.2784];
for i = 1:2:length(pieHdl)
pieHdl(i).FaceColor=colorList((i+1)/2,:);
pieHdl(i).EdgeColor=colorList((i+1)/2,:);
pieHdl(i).LineWidth=1;
pieHdl(i).FaceAlpha=.6;
end
for i = 2:2:length(pieHdl)
pieHdl(i).FontSize=13;
pieHdl(i).FontName='Times New Roman';
end
lgd=legend('FontSize',13,'FontName','Times New Roman','TextColor',[1,1,1].*.3);
pie2HeartLegend(lgd)
Umar Khan
Umar Khan
Last activity 2024 年 2 月 22 日

Which one makes sense?

I am confused, is the matlab answer better or Julia’s?

David
David
Last activity 2024 年 7 月 15 日

Read this before posting

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Enjoy yourself and have fun! We're committed to fostering a supportive and educational environment. Dive into discussions, share your expertise, and grow your knowledge. We're excited to see what you'll contribute to the community!
Hans Scharler
Hans Scharler
Last activity 2024 年 2 月 7 日

Are these really the top MATLAB books?

I found this list on Book Authority about the top MATLAB books: https://bookauthority.org/books/best-matlab-books
My favorite book is Accelerating MATLAB Performance - 1001 tips to speed up MATLAB programs. I always pick something up from the book that helps me out.
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
Noah Prisament
Noah Prisament
Last activity 2024 年 2 月 2 日

Navigating the MATLAB Graphics Tree

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 2024 年 1 月 29 日

TIL spy

spy
We are excited to unveil the ‘Open in MATLAB Online from File Exchange’ feature, which offers MATLAB users a new way to open File Exchange content!
Previously, to experiment with File Exchange code, you were required to download the file and execute it in MATLAB. But now, there's a quicker and easier way to explore the code!
You will find the ‘Open in MATLAB Online’ button next to the ‘Download’ button (see the screenshot below). A simple click transports you directly into the MATLAB Online workflow. It's that straightforward and effortless.
We strongly encourage you to try this new feature. Please share your questions, comments, or ideas by responding to this post!
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.
Hans Scharler
Hans Scharler
Last activity 2024 年 1 月 29 日

When to use a script vs. a live script?

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!
sky
sky
Last activity 2024 年 1 月 18 日

Relative pose in 2D: problem 1

I'm having problem in its test 6 ... passing 5/6 what would be the real issue..
am wring Transformation matrix correct.. as question said SSW should be 202.5 degree...
so what is the issue..
AMIT SURYAVANSHI
AMIT SURYAVANSHI
Last activity 2024 年 1 月 13 日

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
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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.