Results for

This just came out. @Michelle Hirsch spoke to Jousef Murad and answer his questions about the big change in the desktop in R2025a and explained what was going on behind the scene. Enjoy!
The Big MATLAB Update: Dark Mode, Cloud & the Future of Engineering - Michelle Hirsch
https://www.youtube.com/watch?v=BpUG5EEwWos
The Graphics and App Building Blog just launched its first article on R2025a features, authored by Chris Portal, the director of engineering for the MATLAB graphics and app building teams.
Over the next few months, we'll publish a series of articles that showcase our updated graphics system, introduce new tools and features, and provide valuable references enriched by the perspectives of those involved in their development.
To stay updated, you can subscribe to the blog (look for the option in the upper left corner of the blog page). We also encourage you to join the conversation—your comments and questions under each article help shape the discussion and guide future content.
The ability to plot multiple signals on a plot and then use the plot browser to interactively control which ones are displayed has been one of the most useful features of the plotting tools and many of my scripts embed the command to open it after results analysis and plotting. It's been removed in 2025A with the comment that the Property Inspector provides the alternative. It doesn't. Having to go back into the menu to select the plot edit features to get to the Property Inspector (which doesn't provide an efficient alternative to the plot browser) has made the workflow very inefficient. Please bring it back a.s.a.p. !!!!
Walter Roberson
Walter Roberson
Last activity on 31 Jul 2025

R2025a Pre-release highlights

This topic is for discussing highlights to the current R2025a Pre-release.
So you've downloaded the R2025a pre-release, tried Dark mode and are wondering what else is new. A lot! A lot is new!
One thing I am particularly happy about is the fact that Apple Accelerate is now the default BLAS on Apple Silicon machines. Check it out by doing
>> version -blas
ans =
'Apple Accelerate BLAS (ILP64)'
If you compare this to R2024b that is using OpenBLAS you'll see some dramatic speed-ups in some areas. For example, I saw up to 3.7x speed-up for matrix-matrix multiplication on my M2 Mabook Pro and 2x faster LU factorisation.
Details regarding my experiments are in this blog post Life in the fast lane: Making MATLAB even faster on Apple Silicon with Apple Accelerate » The MATLAB Blog - MATLAB & Simulink . Back then you had to to some trickery to switch to Apple Accelerate, now its the default.
Hi everyone
The R2025a pre-release is now available to licensed users. I highly encourage you to download, give it a try and give us some feedback.
The first thing I tried was switching to Dark mode. Here's the magic
>> s = settings;
>> s.matlab.appearance.MATLABTheme.PersonalValue = "Dark";
The beautiful and elegant chord diagrams were all created using MATLAB?
Indeed, they were all generated using the chord diagram plotting toolkit that I developed myself:
You can download these toolkits from the provided links.
The reason for writing this article is that many people have started using the chord diagram plotting toolkit that I developed. However, some users are unsure about customizing certain styles. As the developer, I have a good understanding of the implementation principles of the toolkit and can apply it flexibly. This has sparked the idea of challenging myself to create various styles of chord diagrams. Currently, the existing code is quite lengthy. In the future, I may integrate some of this code into the toolkit, enabling users to achieve the effects of many lines of code with just a few lines.
Without further ado, let's see the extent to which this MATLAB toolkit can currently perform.
demo 1
rng(2)
dataMat = randi([0,5], [11,5]);
dataMat(1:6,1) = 0;
dataMat([11,7],1) = [45,25];
dataMat([1,4,5,7],2) = [20,20,30,30];
dataMat(:,3) = 0;
dataMat(6,3) = 45;
dataMat(1:5,4) = 0;
dataMat([6,7],4) = [25,25];
dataMat([5,6,9],5) = [25,25,25];
colName = {'Fly', 'Beetle', 'Leaf', 'Soil', 'Waxberry'};
rowName = {'Bartomella', 'Bradyrhizobium', 'Dysgomonas', 'Enterococcus',...
'Lactococcus', 'norank', 'others', 'Pseudomonas', 'uncultured',...
'Vibrionimonas', 'Wolbachia'};
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
CC = chordChart(dataMat, 'rowName',rowName, 'colName',colName, 'Sep',1/80);
CC = CC.draw();
% 修改上方方块颜色(Modify the color of the blocks above)
CListT = [0.7765 0.8118 0.5216; 0.4431 0.4706 0.3843; 0.5804 0.2275 0.4549;
0.4471 0.4039 0.6745; 0.0157 0 0 ];
for i = 1:size(dataMat, 2)
CC.setSquareT_N(i, 'FaceColor',CListT(i,:))
end
% 修改下方方块颜色(Modify the color of the blocks below)
CListF = [0.5843 0.6863 0.7843; 0.1098 0.1647 0.3255; 0.0902 0.1608 0.5373;
0.6314 0.7961 0.2118; 0.0392 0.2078 0.1059; 0.0157 0 0 ;
0.8549 0.9294 0.8745; 0.3882 0.3255 0.4078; 0.5020 0.7216 0.3843;
0.0902 0.1843 0.1804; 0.8196 0.2314 0.0706];
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'FaceColor',CListF(i,:))
end
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListT(j,:), 'FaceAlpha',.5)
end
end
CC.tickState('on')
CC.labelRotate('on')
CC.setFont('FontSize',17, 'FontName','Cambria')
% CC.labelRotate('off')
% textHdl = findobj(gca,'Tag','ChordLabel');
% for i = 1:length(textHdl)
% if textHdl(i).Position(2) < 0
% if abs(textHdl(i).Position(1)) > .7
% textHdl(i).Rotation = textHdl(i).Rotation + 45;
% textHdl(i).HorizontalAlignment = 'right';
% if textHdl(i).Rotation > 90
% textHdl(i).Rotation = textHdl(i).Rotation + 180;
% textHdl(i).HorizontalAlignment = 'left';
% end
% else
% textHdl(i).Rotation = textHdl(i).Rotation + 10;
% textHdl(i).HorizontalAlignment = 'right';
% end
% end
% end
demo 2
rng(3)
dataMat = randi([1,15], [7,22]);
dataMat(dataMat < 11) = 0;
dataMat(1, sum(dataMat, 1) == 0) = 15;
colName = {'A2M', 'FGA', 'FGB', 'FGG', 'F11', 'KLKB1', 'SERPINE1', 'VWF',...
'THBD', 'TFPI', 'PLAT', 'SERPINA5', 'SERPIND1', 'F2', 'PLG', 'F12',...
'SERPINC1', 'SERPINA1', 'PROS1', 'SERPINF2', 'F13A1', 'PROC'};
rowName = {'Lung', 'Spleen', 'Liver', 'Heart',...
'Renal cortex', 'Renal medulla', 'Thyroid'};
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
CC = chordChart(dataMat, 'rowName',rowName, 'colName',colName, 'Sep',1/80, 'LRadius',1.21);
CC = CC.draw();
CC.labelRotate('on')
% 单独设置每一个弦末端方块(Set individual end blocks for each chord)
% Use obj.setEachSquareF_Prop
% or obj.setEachSquareT_Prop
% F means from (blocks below)
% T means to (blocks above)
CListT = [173,70,65; 79,135,136]./255;
% Upregulated:1 | Downregulated:2
Regulated = rand([7, 22]);
Regulated = (Regulated < .8) + 1;
for i = 1:size(Regulated, 1)
for j = 1:size(Regulated, 2)
CC.setEachSquareT_Prop(i, j, 'FaceColor', CListT(Regulated(i,j),:))
end
end
% 绘制图例(Draw legend)
H1 = fill([0,1,0] + 100, [1,0,1] + 100, CListT(1,:), 'EdgeColor','none');
H2 = fill([0,1,0] + 100, [1,0,1] + 100, CListT(2,:), 'EdgeColor','none');
lgdHdl = legend([H1,H2], {'Upregulated','Downregulated'}, 'AutoUpdate','off', 'Location','best');
lgdHdl.ItemTokenSize = [12,12];
lgdHdl.Box = 'off';
lgdHdl.FontSize = 13;
% 修改下方方块颜色(Modify the color of the blocks below)
CListF = [128,108,171; 222,208,161; 180,196,229; 209,150,146; 175,201,166;
134,156,118; 175,175,173]./255;
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'FaceColor',CListF(i,:))
end
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListF(i,:), 'FaceAlpha',.45)
end
end
demo 3
dataMat = rand([15,15]);
dataMat(dataMat > .15) = 0;
CList = [ 75,146,241; 252,180, 65; 224, 64, 10; 5,100,146; 191,191,191;
26, 59,105; 255,227,130; 18,156,221; 202,107, 75; 0, 92,219;
243,210,136; 80, 99,129; 241,185,168; 224,131, 10; 120,147,190]./255;
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList);
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',[0,0,.8])
demo 4
rng(5)
dataMat = randi([1,20], [5,5]);
dataMat(1,1) = 110;
dataMat(2,2) = 40;
dataMat(3,3) = 50;
dataMat(5,5) = 50;
CList1 = [164,190,158; 216,213,153; 177,192,208; 238,238,227; 249,217,153]./255;
CList2 = [247,204,138; 128,187,185; 245,135,124; 140,199,197; 252,223,164]./255;
CList = CList2;
NameList={'CHORD','CHART','MADE','BY','SLANDARER'};
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList, 'Sep',1/30, 'Label',NameList, 'LRadius',1.33);
BCC = BCC.draw();
% 添加刻度
BCC.tickState('on')
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.7, 'EdgeColor',CList(i,:)./1.1)
end
end
end
% 修改方块颜色(Modify the color of the blocks)
for i = 1:size(dataMat, 1)
BCC.setSquareN(i, 'EdgeColor',CList(i,:)./1.7)
end
% 修改字体，字号及颜色
BCC.setFont('FontName','Cambria', 'FontSize',17)
BCC.tickLabelState('on')
BCC.setTickFont('FontName','Cambria', 'FontSize',9)
demo 5
dataMat=randi([1,20], [14,3]);
dataMat(11:14,1) = 0;
dataMat(6:10,2) = 0;
dataMat(1:5,3) = 0;
colName = compose('C%d', 1:3);
rowName = [compose('A%d', 1:7), compose('B%d', 7:-1:1)];
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
CC = chordChart(dataMat, 'rowName',rowName, 'colName',colName, 'Sep',1/80);
CC = CC.draw();
% 修改上方方块颜色(Modify the color of the blocks above)
for i = 1:size(dataMat, 2)
CC.setSquareT_N(i, 'FaceColor',[190,190,190]./255)
end
% 修改下方方块颜色(Modify the color of the blocks below)
CListF=[255,244,138; 253,220,117; 254,179, 78; 253,190, 61;
252, 78, 41; 228, 26, 26; 178, 0, 36; 4, 84,119;
1,113,137; 21,150,155; 67,176,173; 68,173,158;
123,204,163; 184,229,162]./255;
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'FaceColor',CListF(i,:))
end
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListF(i,:), 'FaceAlpha',.5)
end
end
CC.tickState('on')
CC.tickLabelState('on')
demo 6
rng(2)
dataMat = randi([0,40], [20,4]);
dataMat(rand([20,4]) < .2) = 0;
dataMat(1,3) = 500;
dataMat(20,1:4) = [140; 150; 80; 90];
colName = compose('T%d', 1:4);
rowName = compose('SL%d', 1:20);
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
CC = chordChart(dataMat, 'rowName',rowName, 'colName',colName, 'Sep',1/80, 'LRadius',1.23);
CC = CC.draw();
% 修改上方方块颜色(Modify the color of the blocks above)
CListT = [0.62,0.49,0.27; 0.28,0.57,0.76
0.25,0.53,0.30; 0.86,0.48,0.34];
for i = 1:size(dataMat, 2)
CC.setSquareT_N(i, 'FaceColor',CListT(i,:))
end
% 修改下方方块颜色(Modify the color of the blocks below)
CListF = [0.94,0.84,0.60; 0.16,0.50,0.67; 0.92,0.62,0.49;
0.48,0.44,0.60; 0.48,0.44,0.60; 0.71,0.79,0.73;
0.96,0.98,0.98; 0.51,0.82,0.95; 0.98,0.70,0.82;
0.97,0.85,0.84; 0.55,0.64,0.62; 0.94,0.93,0.60;
0.98,0.90,0.85; 0.72,0.84,0.81; 0.85,0.45,0.49;
0.76,0.76,0.84; 0.59,0.64,0.62; 0.62,0.14,0.15;
0.75,0.75,0.75; 1.00,1.00,1.00];
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'FaceColor',CListF(i,:))
end
CC.setSquareF_N(size(dataMat, 1), 'EdgeColor','k', 'LineWidth',1)
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListT(j,:), 'FaceAlpha',.46)
end
end
CC.tickState('on')
CC.labelRotate('on')
CC.setFont('FontSize',17, 'FontName','Cambria')
demo 7
dataMat = randi([10,10000], [10,10]);
dataMat(6:10,:) = 0;
dataMat(:,1:5) = 0;
NameList = {'BOC', 'ICBC', 'ABC', 'BOCM', 'CCB', ...
'yama', 'nikoto', 'saki', 'koto', 'kawa'};
CList = [0.63,0.75,0.88
0.67,0.84,0.75
0.85,0.78,0.88
1.00,0.92,0.93
0.92,0.63,0.64
0.57,0.67,0.75
1.00,0.65,0.44
0.72,0.73,0.40
0.65,0.57,0.58
0.92,0.94,0.96];
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList, 'Label',NameList);
BCC = BCC.draw();
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.85, 'EdgeColor',CList(i,:)./1.5, 'LineWidth',.8)
end
end
end
for i = 1:size(dataMat, 1)
BCC.setSquareN(i, 'EdgeColor',CList(i,:)./1.5, 'LineWidth',1)
end
% 添加刻度、修改字体
BCC.tickState('on')
BCC.setFont('FontName','Cambria', 'FontSize',17)
demo 8
dataMat = rand([11,4]);
dataMat = round(10.*dataMat.*((11:-1:1).'+1))./10;
colName = {'A','B','C','D'};
rowName = {'Acidobacteriota', 'Actinobacteriota', 'Proteobacteria', ...
'Chloroflexi', 'Bacteroidota', 'Firmicutes', 'Gemmatimonadota', ...
'Verrucomicrobiota', 'Patescibacteria', 'Planctomyetota', 'Others'};
figure('Units','normalized', 'Position',[.02,.05,.8,.85])
CC = chordChart(dataMat, 'colName',colName, 'Sep',1/80, 'SSqRatio',30/100);% -30/100
CC = CC.draw();
% 修改上方方块颜色(Modify the color of the blocks above)
CListT = [0.93,0.60,0.62
0.55,0.80,0.99
0.95,0.82,0.18
1.00,0.81,0.91];
for i = 1:size(dataMat, 2)
CC.setSquareT_N(i, 'FaceColor',CListT(i,:))
end
% 修改下方方块颜色(Modify the color of the blocks below)
CListF = [0.75,0.73,0.86
0.56,0.83,0.78
0.00,0.60,0.20
1.00,0.49,0.02
0.78,0.77,0.95
0.59,0.24,0.36
0.98,0.51,0.45
0.96,0.55,0.75
0.47,0.71,0.84
0.65,0.35,0.16
0.40,0.00,0.64];
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'FaceColor',CListF(i,:))
end
% 修改弦颜色(Modify chord color)
CListC = [0.55,0.83,0.76
0.75,0.73,0.86
0.00,0.60,0.19
1.00,0.51,0.04];
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListC(j,:), 'FaceAlpha',.4)
end
end
% 单独设置每一个弦末端方块(Set individual end blocks for each chord)
% Use obj.setEachSquareF_Prop
% or obj.setEachSquareT_Prop
% F means from (blocks below)
% T means to (blocks above)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setEachSquareT_Prop(i,j, 'FaceColor', CListF(i,:))
end
end
% 添加刻度
CC.tickState('on')
% 修改字体，字号及颜色
CC.setFont('FontName','Cambria', 'FontSize',17)
% 隐藏下方标签
textHdl = findobj(gca, 'Tag','ChordLabel');
for i = 1:length(textHdl)
if textHdl(i).Position(2) < 0
set(textHdl(i), 'Visible','off')
end
end
% 绘制图例(Draw legend)
scatterHdl = scatter(10.*ones(size(dataMat,1)),10.*ones(size(dataMat,1)), ...
55, 'filled');
for i = 1:length(scatterHdl)
scatterHdl(i).CData = CListF(i,:);
end
lgdHdl = legend(scatterHdl, rowName, 'Location','best', 'FontSize',16, 'FontName','Cambria', 'Box','off');
set(lgdHdl, 'Position',[.7482,.3577,.1658,.3254])
demo 9
dataMat = randi([0,10], [5,5]);
CList1 = [0.70,0.59,0.67
0.62,0.70,0.62
0.81,0.75,0.62
0.80,0.62,0.56
0.62,0.65,0.65];
CList2 = [0.02,0.02,0.02
0.59,0.26,0.33
0.38,0.49,0.38
0.03,0.05,0.03
0.29,0.28,0.32];
CList = CList2;
NameList={'CHORD','CHART','MADE','BY','SLANDARER'};
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList, 'Sep',1/30, 'Label',NameList, 'LRadius',1.33);
BCC = BCC.draw();
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
BCC.setChordMN(i,j, 'FaceAlpha',.5)
end
end
% 修改方块颜色(Modify the color of the blocks)
for i = 1:size(dataMat, 1)
BCC.setSquareN(i, 'EdgeColor',[0,0,0], 'LineWidth',5)
end
% 添加刻度
BCC.tickState('on')
% 修改字体，字号及颜色
BCC.setFont('FontSize',17, 'FontWeight','bold')
BCC.tickLabelState('on')
BCC.setTickFont('FontSize',9)
demo 10
rng(2)
dataMat = rand([14,5]) > .3;
colName = {'phosphorylation', 'vasculature development', 'blood vessel development', ...
'cell adhesion', 'plasma membrane'};
rowName = {'THY1', 'FGF2', 'MAP2K1', 'CDH2', 'HBEGF', 'CXCR4', 'ECSCR',...
'ACVRL1', 'RECK', 'PNPLA6', 'CDH5', 'AMOT', 'EFNB2', 'CAV1'};
figure('Units','normalized', 'Position',[.02,.05,.9,.85])
CC = chordChart(dataMat, 'colName',colName, 'rowName',rowName, 'Sep',1/80, 'LRadius',1.2);
CC = CC.draw();
% 修改上方方块颜色(Modify the color of the blocks above)
CListT1 = [0.5686 0.1961 0.2275
0.2275 0.2863 0.3765
0.8431 0.7882 0.4118
0.4275 0.4510 0.2706
0.3333 0.2706 0.2510];
CListT2 = [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];
CListT3 = [0.4745 0.5843 0.7569
0.4824 0.5490 0.5843
0.6549 0.7216 0.6510
0.9412 0.9216 0.9059
0.9804 0.7608 0.6863];
CListT = CListT3;
for i = 1:size(dataMat, 2)
CC.setSquareT_N(i, 'FaceColor',CListT(i,:), 'EdgeColor',[0,0,0])
end
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListT(j,:), 'FaceAlpha',.9, 'EdgeColor',[0,0,0])
end
end
% 修改下方方块颜色(Modify the color of the blocks below)
logFC = sort(rand(1,14))*6 - 3;
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'CData',logFC(i), 'FaceColor','flat', 'EdgeColor',[0,0,0])
end
CMap = [ 0 0 1.0000; 0.0645 0.0645 1.0000; 0.1290 0.1290 1.0000; 0.1935 0.1935 1.0000
0.2581 0.2581 1.0000; 0.3226 0.3226 1.0000; 0.3871 0.3871 1.0000; 0.4516 0.4516 1.0000
0.5161 0.5161 1.0000; 0.5806 0.5806 1.0000; 0.6452 0.6452 1.0000; 0.7097 0.7097 1.0000
0.7742 0.7742 1.0000; 0.8387 0.8387 1.0000; 0.9032 0.9032 1.0000; 0.9677 0.9677 1.0000
1.0000 0.9677 0.9677; 1.0000 0.9032 0.9032; 1.0000 0.8387 0.8387; 1.0000 0.7742 0.7742
1.0000 0.7097 0.7097; 1.0000 0.6452 0.6452; 1.0000 0.5806 0.5806; 1.0000 0.5161 0.5161
1.0000 0.4516 0.4516; 1.0000 0.3871 0.3871; 1.0000 0.3226 0.3226; 1.0000 0.2581 0.2581
1.0000 0.1935 0.1935; 1.0000 0.1290 0.1290; 1.0000 0.0645 0.0645; 1.0000 0 0];
colormap(CMap);
try clim([-3,3]),catch,end
try caxis([-3,3]),catch,end
CBHdl = colorbar();
CBHdl.Position = [0.74,0.25,0.02,0.2];
% =========================================================================
% 交换XY轴(Swap XY axis)
patchHdl = findobj(gca, 'Type','patch');
for i = 1:length(patchHdl)
tX = patchHdl(i).XData;
tY = patchHdl(i).YData;
patchHdl(i).XData = tY;
patchHdl(i).YData = - tX;
end
txtHdl = findobj(gca, 'Type','text');
for i = 1:length(txtHdl)
txtHdl(i).Position([1,2]) = [1,-1].*txtHdl(i).Position([2,1]);
if txtHdl(i).Position(1) < 0
txtHdl(i).HorizontalAlignment = 'right';
else
txtHdl(i).HorizontalAlignment = 'left';
end
end
lineHdl = findobj(gca, 'Type','line');
for i = 1:length(lineHdl)
tX = lineHdl(i).XData;
tY = lineHdl(i).YData;
lineHdl(i).XData = tY;
lineHdl(i).YData = - tX;
end
% =========================================================================
txtHdl = findobj(gca, 'Type','text');
for i = 1:length(txtHdl)
if txtHdl(i).Position(1) > 0
txtHdl(i).Visible = 'off';
end
end
text(1.25,-.15, 'LogFC', 'FontSize',16)
text(1.25,1, 'Terms', 'FontSize',16)
patchHdl = [];
for i = 1:size(dataMat, 2)
patchHdl(i) = fill([10,11,12],[10,13,13], CListT(i,:), 'EdgeColor',[0,0,0]);
end
lgdHdl = legend(patchHdl, colName, 'Location','best', 'FontSize',14, 'FontName','Cambria', 'Box','off');
lgdHdl.Position = [.735,.53,.167,.27];
lgdHdl.ItemTokenSize = [18,8];
demo 11
rng(2)
dataMat = rand([12,12]);
dataMat(dataMat < .85) = 0;
dataMat(7,:) = 1.*(rand(1,12)+.1);
dataMat(11,:) = .6.*(rand(1,12)+.1);
dataMat(12,:) = [2.*(rand(1,10)+.1), 0, 0];
CList = [repmat([49,49,49],[10,1]); 235,28,34; 19,146,241]./255;
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','off', 'CData',CList);
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)
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.78, 'EdgeColor',[0,0,0])
end
end
end
% 修改方块颜色(Modify the color of the blocks)
for i = 1:size(dataMat, 1)
BCC.setSquareN(i, 'EdgeColor',[0,0,0], 'LineWidth',2)
end
demo 12
dataMat = rand([9,9]);
dataMat(dataMat > .7) = 0;
dataMat(eye(9) == 1) = (rand([1,9])+.2).*3;
CList = [0.85,0.23,0.24
0.96,0.39,0.18
0.98,0.63,0.22
0.99,0.80,0.26
0.70,0.76,0.21
0.24,0.74,0.71
0.27,0.65,0.84
0.09,0.37,0.80
0.64,0.40,0.84];
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList);
BCC = BCC.draw();
% 添加刻度、刻度标签
BCC.tickState('on')
% 修改字体，字号及颜色
BCC.setFont('FontName','Cambria', 'FontSize',17)
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.7)
end
end
end
demo 13
rng(2)
dataMat = randi([1,40], [7,4]);
dataMat(rand([7,4]) < .1) = 0;
colName = compose('MATLAB%d', 1:4);
rowName = compose('SL%d', 1:7);
figure('Units','normalized', 'Position',[.02,.05,.7,.85])
CC = chordChart(dataMat, 'rowName',rowName, 'colName',colName, 'Sep',1/80, 'LRadius',1.32);
CC = CC.draw();
% 修改上方方块颜色(Modify the color of the blocks above)
CListT = [0.49,0.64,0.53
0.75,0.39,0.35
0.80,0.74,0.42
0.40,0.55,0.66];
for i = 1:size(dataMat, 2)
CC.setSquareT_N(i, 'FaceColor',CListT(i,:))
end
% 修改下方方块颜色(Modify the color of the blocks below)
CListF = [0.91,0.91,0.97
0.62,0.95,0.66
0.91,0.61,0.20
0.54,0.45,0.82
0.99,0.76,0.81
0.91,0.85,0.83
0.53,0.42,0.43];
for i = 1:size(dataMat, 1)
CC.setSquareF_N(i, 'FaceColor',CListF(i,:))
end
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
CC.setChordMN(i,j, 'FaceColor',CListT(j,:), 'FaceAlpha',.46)
end
end
CC.tickState('on')
CC.tickLabelState('on')
CC.setFont('FontSize',17, 'FontName','Cambria')
CC.setTickFont('FontSize',8, 'FontName','Cambria')
% 绘制图例(Draw legend)
scatterHdl = scatter(10.*ones(size(dataMat,1)),10.*ones(size(dataMat,1)), ...
55, 'filled');
for i = 1:length(scatterHdl)
scatterHdl(i).CData = CListF(i,:);
end
lgdHdl = legend(scatterHdl, rowName, 'Location','best', 'FontSize',16, 'FontName','Cambria', 'Box','off');
set(lgdHdl, 'Position',[.77,.38,.1658,.27])
demo 14
rng(6)
dataMat = randi([1,20], [8,8]);
dataMat(dataMat > 5) = 0;
dataMat(1,:) = randi([1,15], [1,8]);
dataMat(1,8) = 40;
dataMat(8,8) = 60;
dataMat = dataMat./sum(sum(dataMat));
CList = [0.33,0.53,0.86
0.94,0.50,0.42
0.92,0.58,0.30
0.59,0.47,0.45
0.37,0.76,0.82
0.82,0.68,0.29
0.75,0.62,0.87
0.43,0.69,0.57];
NameList={'CHORD', 'CHART', 'AND', 'BICHORD',...
'CHART', 'MADE', 'BY', 'SLANDARER'};
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList, 'Sep',1/12, 'Label',NameList, 'LRadius',1.33);
BCC = BCC.draw();
% 添加刻度
BCC.tickState('on')
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.7, 'EdgeColor',CList(i,:)./1.1)
end
end
end
% 修改方块颜色(Modify the color of the blocks)
for i = 1:size(dataMat, 1)
BCC.setSquareN(i, 'EdgeColor',CList(i,:)./1.7)
end
% 修改字体，字号及颜色
BCC.setFont('FontName','Cambria', 'FontSize',17)
BCC.tickLabelState('on')
BCC.setTickFont('FontName','Cambria', 'FontSize',9)
% 调整数值字符串格式
% Adjust numeric string format
BCC.setTickLabelFormat(@(x)[num2str(round(x*100)),'%'])
demo 15
CList = [0.81,0.72,0.83
0.69,0.82,0.89
0.17,0.44,0.64
0.70,0.85,0.55
0.03,0.57,0.13
0.97,0.67,0.64
0.84,0.09,0.12
1.00,0.80,0.46
0.98,0.52,0.01
];
figure('Units','normalized', 'Position',[.02,.05,.53,.85], 'Color',[1,1,1])
% =========================================================================
ax1 = axes('Parent',gcf, 'Position',[0,1/2,1/2,1/2]);
dataMat = rand([9,9]);
dataMat(dataMat > .4) = 0;
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList);
BCC = BCC.draw();
BCC.tickState('on')
BCC.setFont('Visible','off')
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.6)
end
end
end
text(-1.2,1.2, 'a', 'FontName','Times New Roman', 'FontSize',35)
% =========================================================================
ax2 = axes('Parent',gcf, 'Position',[1/2,1/2,1/2,1/2]);
dataMat = rand([9,9]);
dataMat(dataMat > .4) = 0;
dataMat = dataMat.*(1:9);
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList);
BCC = BCC.draw();
BCC.tickState('on')
BCC.setFont('Visible','off')
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.6)
end
end
end
text(-1.2,1.2, 'b', 'FontName','Times New Roman', 'FontSize',35)
% =========================================================================
ax3 = axes('Parent',gcf, 'Position',[0,0,1/2,1/2]);
dataMat = rand([9,9]);
dataMat(dataMat > .4) = 0;
dataMat = dataMat.*(1:9).';
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList);
BCC = BCC.draw();
BCC.tickState('on')
BCC.setFont('Visible','off')
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceAlpha',.6)
end
end
end
text(-1.2,1.2, 'c', 'FontName','Times New Roman', 'FontSize',35)
% =========================================================================
ax4 = axes('Parent',gcf, 'Position',[1/2,0,1/2,1/2]);
ax4.XColor = 'none'; ax4.YColor = 'none';
ax4.XLim = [-1,1]; ax4.YLim = [-1,1];
hold on
NameList = {'Food supply', 'Biodiversity', 'Water quality regulation', ...
'Air quality regulation', 'Erosion control', 'Carbon storage', ...
'Water retention', 'Recreation', 'Soil quality regulation'};
patchHdl = [];
for i = 1:size(dataMat, 2)
patchHdl(i) = fill([10,11,12],[10,13,13], CList(i,:), 'EdgeColor',[0,0,0]);
end
lgdHdl = legend(patchHdl, NameList, 'Location','best', 'FontSize',14, 'FontName','Cambria', 'Box','off');
lgdHdl.Position = [.625,.11,.255,.27];
lgdHdl.ItemTokenSize = [18,8];
demo 16
dataMat = rand([15,15]);
dataMat(dataMat > .2) = 0;
CList = [ 75,146,241; 252,180, 65; 224, 64, 10; 5,100,146; 191,191,191;
26, 59,105; 255,227,130; 18,156,221; 202,107, 75; 0, 92,219;
243,210,136; 80, 99,129; 241,185,168; 224,131, 10; 120,147,190]./255;
CListC = [54,69,92]./255;
CList = CList.*.6 + CListC.*.4;
figure('Units','normalized', 'Position',[.02,.05,.6,.85])
BCC = biChordChart(dataMat, 'Arrow','on', 'CData',CList);
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',[0,0,0])
% 修改弦颜色(Modify chord color)
for i = 1:size(dataMat, 1)
for j = 1:size(dataMat, 2)
if dataMat(i,j) > 0
BCC.setChordMN(i,j, 'FaceColor',CListC ,'FaceAlpha',.07)
end
end
end
[~, N] = max(sum(dataMat > 0, 2));
for j = 1:size(dataMat, 2)
BCC.setChordMN(N,j, 'FaceColor',CList(N,:) ,'FaceAlpha',.6)
end
You need to download following tools:
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
New in R2022b: GridSizeChangedFcn
tiledlayout() creates a TiledChartLayout object that defines a gridded layout of axes within a figure. When using the 'flow' option, the grid size becomes dynamic and updates as axes are added or as the figure size changes. These features were introduced in R2019b and if you're still stuck on using subplot, you're missing out on several other great features of tiledlayout.
Starting in MATLAB R2022b you can define a callback function that responds to changes to the grid size in flow arrangements by setting the new gridSizeChangedFcn.
Use case
I often use a global legend to represent data across all axes within a figure. When the figure is tall and narrow, I want the legend to be horizontally oriented at the bottom of the figure but when the figure is short and wide, I prefer a vertically oriented legend on the right of the figure. By using the gridSizeChangedFcn, now I can update the legend location and orientation when the grid size changes.
Demo
gridSizeChangeFcn works like all other graphics callback functions. In this demo, I've named the gridSizeChangedFcn "updateLegendLayout", assigned by an anonymous function. The first input is the TiledChartLayout object and the second input is the event object that indicates the old and new grid sizes. The legend handle is also passed into the function. Since all of the tiles contain the same groups of data, the legend is based on data in the last tile.
As long as the legend is valid, the gridSizeChangedFcn updates the location and orientation of the legend so that when the grid is tall, the legend will be horizontal at the bottom of the figure and when the grid is wide, the legend will be vertical at the right of the figure.
Since the new grid size is available as a property in the TiledChartLayout object, I chose not to use the event argument. This way I can directly call the callback function at the end to update the legend without having to create an event.
Run this example from an m-file. Then change the width or height of the figure to demonstrate the legend adjustments.
% Prepare data
data1 = sort(randn(6))*10;
data2 = sort(randn(6))*10;
labels = ["A","B","C","D","E","F"];
groupLabels = categorical(["Control", "Test"]);
% Generate figure
fig = figure;
tcl = tiledlayout(fig, "flow", TileSpacing="compact", Padding="compact");
nTiles = height(data1);
h = gobjects(1,nTiles);
for i = 1:nTiles
ax = nexttile(tcl);
groupedData = [data1(i,:); data2(i,:)];
h = bar(ax,groupLabels, groupedData, "grouped");
title(ax,"condition " + i)
end
title(tcl,"GridSizeChangedFcn Demo")
ylabel(tcl,"Score")
legh = legend(h, labels);
title(legh,"Factors")
% Define and call the GridSizeChangeFcn
tcl.GridSizeChangedFcn = @(tclObj,event)updateLegendLayout(tclObj,event,legh);
updateLegendLayout(tcl,[],legh);
% Manually resize the vertical and horizontal dimensions of the figure
function updateLegendLayout(tclObj,~,legh)
% Evoked when the TiledChartLayout grid size changes in flow arrangements.
% tclObj - TiledChartLayout object
% event - (unused in this demo) contains old and new grid size
% legh - legend handle
if isgraphics(legh,'legend')
if tclObj.GridSize(1) > tclObj.GridSize(2)
legh.Layout.Tile = "south";
legh.Orientation = "horizontal";
else
legh.Layout.Tile = "east";
legh.Orientation = "vertical";
end
end
end
Give it a shot in MATLAB R2022b
  • Replace the legend with a colorbar to update the location and orientation of the colorbar.
  • Define a GridSizeChangedFcn within the loop so that it is called every time a tile is added.
  • Create a figure with many tiles (~20) and dynamically set a color to each row of axes.
  • Assign xlabels only to the bottom row of tiles and ylabels to only the left column of tiles.
Learn about other new features
This article is attached as a live script.
Uniform spacing and the problem of round-off error
The vector [3 4 5 6 7 8 9] is uniformly spaced with a step size of 1. So is [3 2 1 0 -1 -2] but with a step size of -1.
The vector [1 2 4 8] is not uniformly spaced.
A vector v with uniform spacing has the same finite interval or step size between consecutive elements of the vector. But sometimes round-off error poses a problem in calculating uniformity.
Take, for example, the vector produced by
format shortg
v = linspace(1,9,7)
v = 1x7
1 2.3333 3.6667 5 6.3333 7.6667 9
Linspace produces linearly spaced vectors but the intervals between elements of v, computed by diff(v), are not identical.
dv = diff(v)
dv = 1x6
1.3333 1.3333 1.3333 1.3333 1.3333 1.3333
dv == dv(1)
ans = 1×6 logical array
1 0 0 1 0 1
diff(dv)
ans = 1x5
4.4409e-16 0 -4.4409e-16 8.8818e-16 -8.8818e-16
Some extra steps are therefore necessary to set a tolerance that ignores error introduced by floating point arithmetic.
New in R2022b: isuniform
Determining uniformity of a vector became a whole lot easier in MATLAB R2022b with the new isuniform function.
[tf,step] = isuniform(v)
isuniform returns a logical scalar indicating whether vector v is uniformly spaced within a round-off tolerance and returns the step size (or NaN if v is not uniform).
Let's look at the results for our vector v,
[tf,step] = isuniform(v)
tf = logical
1
step =
1.3333
How about non-uniformly spaced vector?
[tf,step] = isuniform(logspace(1,5,4))
tf = logical
0
step =
NaN
Give it a shot in MATLAB R2022b
  • What happens when all elements of v are equal?
  • Can you produce a vector with uniform spacing without using colons or linspace?
  • What additional steps would be needed to use isuniform with circular data?
References
This article is attached as a live script.

.

MATLAB R2022a provides app developers more control over user navigation through app components using the keyboard's Tab key.

Part 1. The new focus function: programmatically set keyboard focus to a UI component

Part 2. Modify focus order of components

Today we'll review Part 2. See yesterday's Community Highlight for Part 1.

-------------------------------------------------------------------------------------------------

Well-designed apps have an obvious flow through interactive fields and, as we learned yesterday, using the Tab key to move the focus to the next UI component is faster and more efficient than using a mouse. Here we'll learn how to read and set the tab order of UI components in an app.

Understanding tab and stacking order

By default, tab order in MATLAB apps is controlled by the stacking order in the Component Browser. Initially, the stacking order within the component browswer is based on the sequence in which the objects were added to the container object within the app. MATLAB R2020b gave us control to edit the stacking order by selecting a component and using either the Reorder tool from the Canvas toolstrip or by right-clicking the component and selecting Reorder from the context menu [1]. Tab order flows from bottom to top through the Component Browswer hierarchy for objects that are focusable. Sending a component backward within the stack sets its tab order to earlier relative to other components.

Setting tab focus order in R2022a

Three additional tab order features were added in MATLAB R2022a that make it easier to control app navigation with the Tab key.

1. Sort and Filter by Tab Order : Instead of using the Reorder tool which lists components in reverse tab-order and includes components that are not focusable, filter the list by focusable components and sort them by tab-order using the View dropdown menu within the Component Browser (label 1 in image below). From here, you can drag and drop components to set their tab (and stacking) order.

2. Auto Tab Order : To automatically sort focusable components within your app so that the tab order is from left-to-right and then top-to-bottom, in App Designer, from Design View, select the Canvas tab > Tab Order button > Apply Auto Tab Order (label 2 in image below). Alternatively, you can apply auto tab order to components within a container such as a uipanel or uitab by right-clicking on the container within the Component Browser and selecting Apply Auto Tab Order.

3. Visualize Tab Order : You no longer have to read and interpret the handle names in the component browser to understand the current tab order of UI components. Instead, view an animation of tab order within App Designer. From Design View, select the Canvas tab > Tab Order button > Visualize Tab Order (label 3 in image below).

.

Contextual focus control: the power of combining focus() with setting tab order

Yesterday's Community Highlight showed how to programmatically set UI component focus using the focus(c) function. This, combined with control of tab order, allows app developers to implement contextual focus control. For example, when a radio button is selected in the GIF below, the corresponding UI Tab is selected programmatically and the keyboard focus is set to the first component within the UI Tab thus allowing the user to smoothly continue keyboard navigation. This is achieved by a callback function that responds to changes in the Button Group that sets the SelectedTab property of the TabGroup and uses the new focus() function. For details, see the attached focusAndTabOrderDemo.mlapp.

-------------------------------------------------------------------------------------------------

Stay tuned

Follow Community Highlights to get notifications for new content.

Let us know what interests you in the new MATLAB R2022a release in the comment section below.

See also

Footnotes

[1] R202b release notes: change the stacking order of UI components

This Community Highlight is attached as a live script.

.

MATLAB R2022a provides app developers more control over user navigation through app components using the keyboard's Tab key.

Part 1. The new focus function: programmatically set keyboard focus to a UI component

Part 2. Modify focus order of components

Today we'll review Part 1. Come back tomorrow for Part 2.

-------------------------------------------------------------------------------------------------

Programmatically set UI component focus

Did you know that you can save ~2 seconds every time you use a keyboard shortcut rather than reaching for your mouse [1,2]?

I need you to focus here: starting in MATLAB R2022a, use the new focus function to set keyboard focus to a specific UI component.

By specifying the component handle ( c ) in focus(c),

  1. The figure containing the component is displayed
  2. A blue frame appears around the component
  3. The user can directly interact with the component.

.

Which components are focusable?

Focusable components are those that a user can interact with using the keyboard. So an object set to Enable='off' or Visible='off' cannot be in focus. See the documentation for more details.

What will you do with all of that extra time saved?

-------------------------------------------------------------------------------------------------

Stay tuned

Tomorrow we'll learn how to apply the new focus function with control of tab order to create contextual flow of UI component focus. Follow Community Highlights to get notifications.

Let us know what interests you in the new MATLAB R2022a release in the comment section below.

See also

Footnotes

[1] Lane et. al. (2005). International Journal of Human-Computer Interaction, 18(2).

[2] Michels (2018). median.com

This Community Highlight is attached as a live script.

Starting in MATLAB R2022a, use the append option in exportgraphics to create GIF files from animated axes, figures, or other visualizations.

This basic template contains just two steps:

% 1. Create the initial image file
gifFile = 'myAnimation.gif';
exportgraphics(obj, gifFile);

% 2. Within a loop, append the gif image
for i = 1:20

      %   %   %   %   %   %    % 
      % Update the figure/axes %
      %   %   %   %   %   %    % 
      exportgraphics(obj, gifFile, Append=true);
  end

Note, exportgraphics will not capture UI components such as buttons and knobs and requires constant axis limits.

To create animations of images or more elaborate graphics, learn how to use imwrite to create animated GIFs .

Share your MATLAB animated GIFs in the comments below!

See Also

This Community Highlight is attached as a live script

Adam Danz
Adam Danz
Last activity on 17 Mar 2022

New in MATLAB R2022a: Fontsize scaling

You've spent hours designing the perfect figure and now it's time to add it to a presentation or publication but the font sizes in the figure are too small to see for the people in the back of the room or too large for the figure space in the publication. You've got titles, subtitles, axis labels, legends, text objects, and other labels but their handles are inaccessible or scattered between several blocks of code. Making your figure readable no longer requires digging through your code and setting each text object's font size manually.

Starting in MATLAB R2022a, you have full control over a figure's font sizes and font units using the new fontsize function (see release notes ).

Use fontsize() to

  • Set FontSize and FontUnits properties for all text within specified graphics objects
  • Incrementally increase or decrease font sizes
  • Specify a scaling factor to maintain relative font sizes
  • Reset font sizes and font units to their default values . Note that the default font size and units may not be the same as the font sizes/units set directly with your code.

When specifying an object handle or an array of object handles, fontsize affects the font sizes and font units of text within all nested objects.

While you're at it, also check out the new fontname function that allows you to change the font name of objects in a figure!

Give the new fontsize function a test drive using the following demo figure in MATLAB R2022a or later and try the following commands:

% Increase all font sizes within the figure by a factor of 1.5
fontsize(fig, scale=1.5)

% Set all font sizes in the uipanel to 16
fontsize(uip, 16, "pixels")

% Incrementally increase the font sizes of the left two axes (x1.1)
% and incrementally decrease the font size of the legend (x0.9)
fontsize([ax1, ax2], "increase")
fontsize(leg, "decrease")

% Reset the font sizes within the entire figure to default values
fontsize(fig, "default")

% Create fake behavioral data
rng('default')
fy = @(a,x)a*exp(-(((x-8).^2)/(2*3.^2)));
x = 1 : 0.5 : 20;
y = fy(32,x);
ynoise = y+8*rand(size(y))-4;
selectedTrial = 13;

% Plot behavioral data
fig = figure('Units','normalized','Position',[0.1, 0.1, 0.4, 0.5]);
movegui(fig, 'center')
tcl = tiledlayout(fig,2,2); 
ax1 = nexttile(tcl); 
hold(ax1,'on')
h1 = plot(ax1, x, ynoise, 'bo', 'DisplayName', 'Response');
h2 = plot(ax1, x, y, 'r-', 'DisplayName', 'Expected');
grid(ax1, 'on')
title(ax1, 'Behavioral Results')
subtitle(ax1, sprintf('Trial %d', selectedTrial))
xlabel(ax1, 'Time (seconds)','Interpreter','Latex')
ylabel(ax1, 'Responds ($\frac{deg}{sec}$)','Interpreter','Latex')
leg = legend([h1,h2]);

% Plot behavioral error
ax2 = nexttile(tcl,3);
behavioralError = ynoise-y; 
stem(ax2, x, behavioralError)
yline(ax2, mean(behavioralError), 'r--', 'Mean', ...
    'LabelVerticalAlignment','bottom')
grid(ax2, 'on')
title(ax2, 'Behavioral Error')
subtitle(ax2, ax1.Subtitle.String)
xlabel(ax2, ax1.XLabel.String,'Interpreter','Latex')
ylabel(ax2, 'Response - Expected ($\frac{deg}{sec}$)','Interpreter','Latex')

% Simulate spike train data
ntrials = 25; 
nSamplesPerSecond = 3; 
nSeconds = max(x) - min(x); 
nSamples = ceil(nSeconds*nSamplesPerSecond);
xTime = linspace(min(x),max(x), nSamples);
spiketrain = round(fy(1, xTime)+(rand(ntrials,nSamples)-.5));
[trial, sample] = find(spiketrain);
time = xTime(sample);

% Spike raster plot
axTemp = nexttile(tcl, 2, [2,1]);
uip = uipanel(fig, 'Units', axTemp.Units, ...
    'Position', axTemp.Position, ...
    'Title', 'Neural activity', ...
    'BackgroundColor', 'W');
delete(axTemp)
tcl2 = tiledlayout(uip, 3, 1);
pax1 = nexttile(tcl2); 
plot(pax1, time, trial, 'b.', 'MarkerSize', 4)
yline(pax1, selectedTrial-0.5, 'r-', ...
    ['\leftarrow Trial ',num2str(selectedTrial)], ...
    'LabelHorizontalAlignment','right', ...
    'FontSize', 8); 
linkaxes([ax1, ax2, pax1], 'x')
pax1.YLimitMethod = 'tight';
title(pax1, 'Spike train')
xlabel(pax1, ax1.XLabel.String)
ylabel(pax1, 'Trial #')

% Show MRI
pax2 = nexttile(tcl2,2,[2,1]); 
[I, cmap] = imread('mri.tif');
imshow(I,cmap,'Parent',pax2)
hold(pax2, 'on')
th = 0:0.1:2*pi; 
plot(pax2, 7*sin(th)+84, 5*cos(th)+90, 'r-','LineWidth',2)
text(pax2, pax2.XLim(2), pax2.YLim(1), 'ML22a',...
    'FontWeight', 'bold', ...
    'Color','r', ...
    'VerticalAlignment', 'top', ...
    'HorizontalAlignment', 'right', ...
    'BackgroundColor',[1 0.95 0.95])
title(pax2, 'Area of activation')

% Overall figure title
title(tcl, 'Single trial responses')

This Community Highlight is attached as a live script.

R2021b is live! There are two new products, five major updates, and hundreds of other feature updates in this latest release. Download or access MATLAB Online to discover what’s new.

New Products

Major Updates

  • Lidar Toolbox - Use Lidar Viewer app to visualize, analyze, and preprocess lidar point clouds interactively
  • Simulink Code Inspector - Use Code Inspector contextual tab to check compatibility, inspect code and view results directly in the model
  • Simulink Control Design - Design Model Reference Adaptive Controllers
  • Symbolic Math Toolbox - Get guidance for symbolic workflows with next-step suggestions in MATLAB Live Editor
  • Wavelet Toolbox - Use wavelet analysis to process and extract features for signals and images for AI workflows

Check out our release highlight page for details.

Share your experience with the community

Are there any new features you find particularly useful? Are you trying the new product to solve a particular problem? Share your story with us no matter it’s big or small. We plan to publish those stories in the highlight channel so that community users can get more out of the new release. A good example is an article written by Adam Danz . If you are interested, contact me via email on my profile card.

Starting in MATLAB R2021a axis tick labels will auto-rotate to avoid overlap when the user manually specifies ticks or tick labels ( release notes ). In custom visualization functions, the tick label density or tick label lengths may be variable and unknown. The new auto-rotation feature removes the burden of detecting the need to rotate manually-set labels and eliminates the need to manually rotate them.

Many properties and combinations of properties can cause tick labels to overlap if they are not rotated.

  • Length of tick labels
  • Number of tick labels
  • Interval between tick labels
  • Font size
  • Font name
  • Figure size
  • Axes size
  • Viewing angle of the axes

Demo: varying tick density and length of tick labels

These 9 axes vary by the number of x-ticks and length of x-tick-labels. MATLAB auto-rotates the labels when needed.

Demo: Changes to axis view angle and rotation

The auto-rotation feature updates the label angles as the axes change programmatically or during user interaction.

What if I don't want auto-rotation?

Auto-rotation mode is on by default for each X|Y|Z axis. When the tick label rotation angle is manually set from the X|Y|ZTickLabelRotation property of axes or by using xtickangle | ytickangle | ztickangle , auto-rotation is turned off. Auto-rotation can also be turned off by setting the X|Y|ZTickLabelRotationMode axis property to manual but it's important to also hold the axis properties so that the rotation mode does not revert to the default value, auto. If you're looking for a broader method of reverting to older behavior you can set the default label rotation mode to manual at the start of a function that produces multiple plots and then revert to the factory default rotation mode at the end of the file (consider using onCleanup).

set(groot,'defaultAxesXTickLabelRotationMode','manual')
set(groot,'defaultAxesYTickLabelRotationMode','manual')
set(groot,'defaultAxesZTickLabelRotationMode','manual')

% Revert to factory-default
set(groot,'defaultAxesXTickLabelRotationMode','remove')
set(groot,'defaultAxesYTickLabelRotationMode','remove')
set(groot,'defaultAxesZTickLabelRotationMode','remove')

A copy of this Community Highlight is attached as a live script.

Adam Danz
Adam Danz
Last activity on 17 Oct 2023

New in R2021a: LimitsChangedFcn

New in R2021a, LimitsChangedFcn

LimitsChangedFcn is a callback function that responds to changes to axis limits ( release notes ). The function responds to axis interaction such as panning and zooming, programmatically setting the axis limits, or when axis limits are automatically adjusted by other processes.

LimitsChangedFcn is a property of ruler objects which are properties of axes and can be independently set for each axis. For example,

ax = gca(); 
ax.XAxis.LimitsChangedFcn = ... % Responds to changes to XLim
ax.YAxis.LimitsChangedFcn = ... % Responds to changes to YLim
ax.ZAxis.LimitsChangedFcn = ... % Responds to changes to ZLim

Previously, a listener could be assigned to respond to changes to axis limits. Here are some examples.

However, LimitsChangedFcn responds more reliably than a listener that responds to setting/getting axis limits. For example, after zooming or panning the axes in the demo below, the listener does not respond to the Restore View button in the axis toolbar but LimitsChangedFcn does! After restoring the view, try zooming out which does not result in changes to axis limits yet the listener will respond but the LimitsChangedFcn will not. Adding objects to axes after an axis-limit listener is set will not trigger the listener even if the added object expands the axis limits ( why not? ) but LimitsChangedFcn will!

ax = gca(); 
ax.UserData.Listener = addlistener(ax,'XLim','PostSet',@(~,~)disp('Listener')); 
ax.XAxis.LimitsChangedFcn = @(~,~)disp('LimitsChangedFcn')

How to use LimitsChangedFcn

The LimitsChangedFcn works like any other callback. For review,

The first input to the LimitsChangedFcn callback function is the handle to the axis ruler object that was changed.

The second input is a structure that contains the old and new limits. For example,

    LimitsChanged with properties:
      OldLimits: [0 1]
      NewLimits: [0.25 0.75]
         Source: [1×1 NumericRuler]
      EventName: 'LimitsChanged'

Importantly, since LimitsChangedFcn is a property of the axis rulers rather than the axis object, changes to the axes may clear the LimitsChangedFcn property if the axes aren't held using hold on. For example,

% Axes not held
ax = gca(); 
ax.XAxis.LimitsChangedFcn = @(ruler,~)title(ancestor(ruler,'axes'),'LimitsChangedFcn fired!'); 
plot(ax, 1:5, rand(1,5), 'o')
ax.XAxis.LimitsChangedFcn

ans =
    0×0 empty char array

% Axes held
ax = gca(); 
hold(ax,'on')
ax.XAxis.LimitsChangedFcn = @(ruler,~)title(ancestor(ruler,'axes'),'LimitsChangedFcn fired!'); 
plot(ax, 1:5, rand(1,5), 'o')
ax.XAxis.LimitsChangedFcn

ans =
  function_handle with value:
    @(ruler,~)title(ancestor(ruler,'axes'),'LimitsChangedFcn fired!')

Demo

In this simple app a LimitsChangedFcn callback function is assigned to the x and y axes. The function does two things:

  1. Text boxes showing the current axis limits are updated
  2. The prying eyes that are centered on the axes will move to the new axis center

This demo also uses Name=Value syntax and emoji text objects !

Create app

h.fig = uifigure(Name="LimitsChangedFcn Demo", ...
    Resize="off");
h.fig.Position(3:4) = [500,260];
movegui(h.fig)
h.ax = uiaxes(h.fig,...
    Units="pixels", ...
    Position=[200 26 250 208], ...
    Box="on");
grid(h.ax,"on")
title(h.ax,"I'm following you!")
h.eyeballs = text(h.ax, .5, .5, ...
    char([55357 56385 55357 56385]), ...
    HorizontalAlignment="center", ...
    FontSize=40);
h.label = uilabel(h.fig, ...
    Text="Axis limits", ...
    Position=[25 212 160 15], ...
    FontWeight="bold",...
    HorizontalAlignment="center");
h.xtxt = uitextarea(h.fig, ...
    position=[25 191 160 20], ...
    HorizontalAlignment="center", ...
    WordWrap="off", ...
    Editable="off",...
    FontName=get(groot, 'FixedWidthFontName'));
h.ytxt = uitextarea(h.fig, ...
    position=[25 165 160 20], ...
    HorizontalAlignment="center", ...
    WordWrap="off", ...
    Editable="off", ...
    FontName=get(groot, 'FixedWidthFontName'));
h.label = uilabel(h.fig, ...
    Text=['X',newline,newline,'Y'], ...
    Position=[10 170 15 38], ...
    FontWeight="bold");

Set LimitsChangedFcn of x and y axes

h.ax.XAxis.LimitsChangedFcn = @(hObj,data)limitsChangedCallbackFcn(hObj,data,h,'x');
h.ax.YAxis.LimitsChangedFcn = @(hObj,data)limitsChangedCallbackFcn(hObj,data,h,'y');

Update text fields

xlim(h.ax, [-100,100])
ylim(h.ax, [-100,100])

Define LimitsChangedFcn

function limitsChangedCallbackFcn(rulerHand, limChgData, handles, xy)
% limitsChangedCallbackFcn() responds to changes to x or y axis limits.
% - rulerHand: Ruler handle for x or y axis that was changed (not used in this demo)
% - limChgData: LimitsChanged data structure
% - handles: structure of App handles
% - xy: either 'x' or 'y' identifying rulerHand
switch lower(xy)
    case 'x'
        textHandle = handles.xtxt;
        positionIndex = 1; 
    case 'y'
        textHandle = handles.ytxt;
        positionIndex = 2; 
    otherwise
        error('xy is a character ''x'' or ''y''.')
end
% Update text boxes showing rounded axis limits
textHandle.Value = sprintf('[%.3f, %.3f]',limChgData.NewLimits);
% Move the eyes to the new center position
handles.eyeballs.Position(positionIndex) = limChgData.NewLimits(1)+range(limChgData.NewLimits)/2; % for linear scales only!
drawnow
end

See attached mlx file for a copy of this thread.

Highlight Icon image

Adam Danz
Adam Danz
Last activity on 17 Oct 2023

New in R2021a: Name=Value syntax

Starting in MATLAB R2021a, name-value arguments have a new optional syntax!

A property name can be paired with its value by an equal sign and the property name is not enclosed in quotes.

Compare the comma-separated name,value syntax to the new equal-sign syntax, either of which can be used in >=r2021a:

  • plot(x, y, "b-", "LineWidth", 2)
  • plot(x, y, "b-", LineWidth=2)

It comes with some limitations:

  1. It's recommended to use only one syntax in a function call but if you're feeling rebellious and want to mix the syntaxes, all of the name=value arguments must appear after the comma-separated name,value arguments.
  2. Like the comma-separated name,value arguments, the name=value arguments must appear after positional arguments.
  3. Name=value pairs must be used directly in function calls and cannot be wrapped in cell arrays or additional parentheses.

Some other notes:

  1. The property names are not case-sensitive so color='r' and Color='r' are both supported.
  2. Partial name matches are also supported. plot(1:5, LineW=4)

The new syntax is helpful in distinguishing property names from property values in long lists of name-value arguments within the same line.

For example, compare the following 2 lines:

h = uicontrol(hfig, "Style", "checkbox", "String", "Long", "Units", "Normalize", "Tag", "chkBox1")

h = uicontrol(hfig,  Style="checkbox",    String="Long",    Units="Normalize",    Tag="chkBox1")

Here's another side-by-side comparison of the two syntaxes. See the attached mlx file for the full code and all content of this Community Highlight.

tiledlayout, introduced in MATLAB R2019b, offers a flexible way to add subplots, or tiles, to a figure.

Reviewing two changes to tiledlayout in MATLAB R2021a

  1. The new TileIndexing property
  2. Changes to TileSpacing and Padding properties

1) TileIndexing

By default, axes within a tiled layout are created from left to right, top to bottom, but sometimes it's better to organize plots column-wise from top to bottom and then left to right. Starting in r2021a, the TileIndexing property of tiledlayout specifies the direction of flow when adding new tiles.

tiledlayout(__,'TileIndexing','rowmajor') creates tiles by row (default).

tiledlayout(__,'TileIndexing','columnmajor') creates tiles by column.

.

2) TileSpacing & Padding changes

Some changes have been made to the spacing properties of tiles created by tiledlayout.

TileSpacing: sets the spacing between tiles.

  • "loose" is the new default and replaces "normal" which is no longer recommended but is still accepted.
  • "tight" replaces "none" and brings the tiles closer together still leaving space for axis ticks and labels.
  • "none" results in tile borders touching, following the true meaning of none.
  • "compact" is unchanged and has slightly more space between tiles than "tight".

Padding: sets the spacing of the figure margins.

  • "loose" is the new default and replaces "normal" which is no longer recommended but is still accepted.
  • "tight" replaces "none" and reduces the figure margins. "none" is no longer recommended but is still accepted.
  • "compact" is unchanged and adds slightly more marginal space than "tight".
  • Reducing the figure margins to a true none is still not an option.

The release notes show a comparison of these properties between r2020b and r2021a.

Here's what the new TileSpacing options (left column of figures below) and Padding options (right column) look like in R2021a. Spacing properties are written in the figure names.

.

And here's a grid of all 12 combinations of the 4 TileSpacing options and 3 Padding options in R2021a.

.

Code used to generate these figures

%% Animate the RowMajor and ColumnMajor indexing with colored tiles 
fig1 = figure('position',[200 200 560 420]); 
tlo1 = tiledlayout(fig1, 3, 3, 'TileIndexing','rowmajor');
title(tlo1, 'RowMajor indexing')

fig2 = figure('position',[760 200 560 420]); 
tlo2 = tiledlayout(fig2, 3, 3, 'TileIndexing','columnmajor');
title(tlo2, 'ColumnMajor indexing')

colors = jet(9);
drawnow()

for i = 1:9
    ax = nexttile(tlo1);
    ax.Color = colors(i,:);
    text(ax, .5, .5, num2str(i), 'Horiz','Cent','Vert','Mid','Fontsize',24)

      ax = nexttile(tlo2);
      ax.Color = colors(i,:);
      text(ax, .5, .5, num2str(i), 'Horiz','Cent','Vert','Mid','Fontsize',24)
      drawnow
      pause(.3)
  end
%% Show TileSpacing options
tileSpacing = ["loose","compact","tight","none"];
figHeight = 140;  % unit: pixels
figPosY = fliplr(50 : figHeight+32 : (figHeight+30)*numel(tileSpacing)); 

for i = 1:numel(tileSpacing)
    uif = uifigure('Units','Pixels','Position', [150 figPosY(i) 580 figHeight], ...
        'Name', ['TileSpacing: ', tileSpacing{i}]);
    tlo = tiledlayout(uif,1,3,'TileSpacing',tileSpacing(i)); 
    h = arrayfun(@(i)nexttile(tlo), 1:tlo.GridSize(2));
    box(h,'on')
    drawnow()
end

%% Show Padding options
padding = ["loose","compact","tight"];
for i = 1:numel(padding)
    uif = uifigure('Units','Pixels','Position', [732 figPosY(i) 580 figHeight], ...
        'Name', ['Padding: ', padding{i}]);
    tlo = tiledlayout(uif,1,3,'Padding',padding(i)); 
    h = arrayfun(@(i)nexttile(tlo), 1:tlo.GridSize(2));
    box(h,'on')
    drawnow()
end

%% Show all combinations of TileSpacing and Padding options
tileSpacing = ["loose","compact","tight","none"];
padding = ["loose","compact","tight"];
[tsIdx, padIdx] = meshgrid(1:numel(tileSpacing), 1:numel(padding));
figSize = [320 220]; % width, height (pixels)
figPosX = 150 + (figSize(1)+2)*(0:numel(tileSpacing)-1); 
figPosY = 50 + (figSize(2)+32)*(0:numel(padding)-1);
[figX, figY] = meshgrid(figPosX, fliplr(figPosY));
for i = 1:numel(padIdx)
    uif = uifigure('Units','pixels','Position',[figX(i), figY(i), figSize], ...
        'name', ['TS: ', tileSpacing{tsIdx(i)}, ', Pad: ', padding{padIdx(i)}]);
    tlo = tiledlayout(uif,2,2,'TileSpacing',tileSpacing(tsIdx(i)),'Padding',padding(padIdx(i))); 
    h = arrayfun(@(i)nexttile(tlo), 1:prod(tlo.GridSize));
    box(h,'on')
    drawnow()
end

We've all been there. You've got some kind of output that displays perfectly in the command window and you just want to capture that display as a string so you can use it again somewhere else. Maybe it's a multidimensional array, a table, a structure, or a fit object that perfectly displays the information you need in a neat and tidy format but when you try to recreate the display in a string variable it's like reconstructing the Taj Mahal out of legos.

Enter Matlab r2021a > formattedDisplayText()

Use str=formattedDisplayText(var) the same way you use disp(var) except instead of displaying the output, it's stored as a string as it would appear in the command window.

Additional name-value pairs allow you to

  • Specify a numeric format
  • Specify loose|compact line spacing
  • Display true|false instead of 1|0 for logical values
  • Include or suppress markup formatting that may appear in the display such as the bold headers in tables.

Demo: Record the input table and results of a polynomial curve fit

load census
[fitobj, gof] = fit(cdate, pop, 'poly3', 'normalize', 'on')

Results printed to the command window:

fitobj = 
     Linear model Poly3:
     fitobj(x) = p1*x^3 + p2*x^2 + p3*x + p4
       where x is normalized by mean 1890 and std 62.05
     Coefficients (with 95% confidence bounds):
       p1 =       0.921  (-0.9743, 2.816)
       p2 =       25.18  (23.57, 26.79)
       p3 =       73.86  (70.33, 77.39)
       p4 =       61.74  (59.69, 63.8)

gof = 
  struct with fields:

             sse: 149.77
         rsquare: 0.99879
             dfe: 17
      adjrsquare: 0.99857
            rmse: 2.9682

Capture the input table, the printed fit object, and goodness-of-fit structure as strings:

rawDataStr = formattedDisplayText(table(cdate,pop),'SuppressMarkup',true)
fitStr = formattedDisplayText(fitobj)
gofStr = formattedDisplayText(gof)

Display the strings:

rawDataStr = 
    "    cdate     pop 
         _____    _____
         1790       3.9
         1800       5.3
         1810       7.2
         1820       9.6
         1830      12.9
         1840      17.1
         1850      23.1
         1860      31.4
         1870      38.6
         1880      50.2
         1890      62.9
         1900        76
         1910        92
         1920     105.7
         1930     122.8
         1940     131.7
         1950     150.7
         1960       179
         1970       205
         1980     226.5
         1990     248.7
     "

fitStr = 
    "     Linear model Poly3:
          ary(x) = p1*x^3 + p2*x^2 + p3*x + p4
            where x is normalized by mean 1890 and std 62.05
          Coefficients (with 95% confidence bounds):
            p1 =       0.921  (-0.9743, 2.816)
            p2 =       25.18  (23.57, 26.79)
            p3 =       73.86  (70.33, 77.39)
            p4 =       61.74  (59.69, 63.8)
     "

gofStr = 
    "           sse: 149.77
            rsquare: 0.99879
                dfe: 17
         adjrsquare: 0.99857
               rmse: 2.9682
     "

Combine the strings into a single string and write it to a text file in your temp directory:

txt =  strjoin([rawDataStr; fitStr; gofStr],[newline newline]);
file = fullfile(tempdir,'results.txt');
fid = fopen(file,'w+');
cleanup = onCleanup(@()fclose(fid)); 
fprintf(fid, '%s', txt);
clear cleanup

Open results.txt.

winopen(file) % for Windows platforms