I am creating a graph iteratively from various data sets, and I try to add legend to it, but it fails.
colors = {'g','b','m','k','c'};
subplot(2,3,iii);
hold all;
for jjj=1:length(aggregation_methods),
aggregate = all_aggregate{jjj};
std_agg = all_std_agg{jjj};
plot(coverages, aggregate, colors{jjj});
h1 = errorbar(coverages,aggregate,std_agg,colors{jjj});
set(h1,'linestyle','none')
end
plot(coverages, regular, 'r');
h1 = errorbar(coverages,regular,std_reg,'r');
set(h1,'linestyle','none')
title(datasets{iii});
xlabel('coverage');
ylabel('MSE');
legend('enhanced with clustering(k=4)','enhanced random split', 'regular we');
The graph seems to be generated just fine, it's just the legend that is failing.
I expect the colors of the legend to be (top-down): green, blue, red.
P.S. I also tried (and it didn't work):
legend({'enhanced with clustering(k=4)','enhanced random split', 'regular we'});
EDIT:
Inspired by this thread, I changed the code to use the 'DisplayName' property for each plot:
colors = {'g','b','m','k','c'};
names = {'enhanced with clustering(k=4)','enhanced random split', 'regular we'};
subplot(2,3,iii);
hold all;
for jjj=1:length(aggregation_methods),
aggregate = all_aggregate{jjj};
std_agg = all_std_agg{jjj};
plot(coverages, aggregate, colors{jjj}, 'DisplayName', names{jjj});
h1 = errorbar(coverages,aggregate,std_agg,colors{jjj});
set(h1,'linestyle','none')
end
%plot(coverages,aggregate,'g',coverages ,regular,'r');
%h1 = errorbar(coverages,aggregate,std_agg,'g');
%set(h1,'linestyle','none')
plot(coverages, regular, 'r', 'DisplayName', names{length(aggregation_methods) + 1});
h1 = errorbar(coverages,regular,std_reg,'r');
set(h1,'linestyle','none')
%axis([0 1 0 max(mean(rc{iii}))]);
title(datasets{iii});
xlabel('coverage');
ylabel('MSE');
legend('show');
However, it yields the following legend, but I'd like to get rid of these 'dataX' strings.
a=[
1 2 3
4 5 6
7 8 9
];
clist={'g','b','m'};
for i=1:3
pt(i)=plot(a(i,:),'Color',clist{i});
hold on;
end
b=[5 6 7];
pt(4)=plot(b,'Color','r');
legend([pt(1:2) pt(4)],{'line1','line2','line4'});
Related
I have this data of which I want to make a principal component analysis.
In particular for each data point I want to associate a color.
This is my code:
for ii=1:size(SBF_ens,1)
SBF(ii) = SBF_ens(ii, max(find(SBF_ens(ii,:)~=0)) ); %value at the moment of the measurement
end
%matrix of data
toPCA =[
wind_trend_72h_ens-nanmean(wind_trend_72h_ens);
wind_trend_24h_ens-nanmean(wind_trend_24h_ens);
wind_trend_12to18h_ens-nanmean(wind_trend_12to18h_ens);
wind_trend_0to12h_ens-nanmean(wind_trend_0to12h_ens);
wind_trend_last6h_ens-nanmean(wind_trend_last6h_ens);
Mwind12h_ens-nanmean(Mwind12h_ens);
Mwind24h_ens-nanmean(Mwind24h_ens);
SBF-nanmean(SBF)]';
variables = { 'wt72h','wt24h','wt12to18h','wt0to12h','wtLast6h','Mw12h', 'Mw24h', 'SBF'}; %labels
%PCA algorithm
C = corr(toPCA,toPCA);
w = 1./var(toPCA);
[wcoeff,score,latent,tsquared,explained] = pca(toPCA,'VariableWeights',w);
coefforth = diag(sqrt(w))*wcoeff;
metric=decstd_ens; %metric for colorbar
hbi=biplot(coefforth(:,1:2),'scores',score(:,1:2),'varlabels',...
variables,'ObsLabels', num2str([1:length(toPCA)]'),...
'markersize', 15);
%plotting
cm = autumn;
colormap(cm);
for ii = length(hbi)-length(toPCA):length(hbi)
userdata = get(hbi(ii), 'UserData');
if ~isempty(userdata)
indCol = ceil( size(cm,1) * abs(metric(userdata))/max(abs(metric)) );%maps decstd between 0 and 1 and find the colormap index
if indCol==0 %just avoid 0
indCol=1;
end
col = cm(indCol,:); %color corresponding to the index
set(hbi(ii), 'Color', col); %modify the dot's color
end
end
for ii = 1:length(hbi)-length(toPCA)-1 %dots corresponding to the original dimensions are in black
set(hbi(ii), 'Color', 'k');
end
c=colorbar;
ylabel(c,'decstd') %is this true?
xlabel(['1^{st} PCA component ', num2str(explained(1)), ' of variance explained'])
ylabel(['2^{nd} PCA component ', num2str(explained(2)), ' of variance explained'])
The resulting figure is the following:
Everything is fine except for the colorbar range. In fact decstd has values between 0 and 2. Actually I do not understand at all what the values on the colorbar are.
Does anyone understand it?
Is it possible to rethrive the data in the colorbar? So to understand what they are?
size(autumn)
shows you that the default length of the autumn colourmap (actually of all the colourmaps) is 64. When you call colorbar, by default it will use tick labels from 1 to n where n is the length of your colourmap, in this case 64.
If you want the mapping of the colourbar ticklabels to match the mapping that you used to get your data to fit between 1 and 64 (i.e. this line of yours indCol = ceil( size(cm,1) * abs(metric(userdata))/max(abs(metric)) );), then you will need to set that yourself like this
numTicks = 6;
cAxisTicks = linspace(min(metric), max(metric), numTicks); % or whatever the correct limits are for your data
caxis([min(metric), max(metric)]);
set(c,'YTick', cAxisTicks );
I have a three groups such as
Group 1={x1,x2}
x1=[1,2,2,3,5,3]
x2=[2,5,4,5,8,6]
Group 2={x3,x4}
x3=[2,8,9,2,1,6]
x4=[5,4,3,22,11,6]
Group 2={x5,x6}
x5=[10,12,22,4]
x6=[12,15,4,25]
I want to draw them into char by boxplot function by group. I found the way to resolve it. But it cannot draw. Could you help me please?
x1=[1,2,2,3,5,3];
x2=[2,5,4,5,8,6];
g1={x1,x2};
%group2
x3=[2,8,9,2,1,6];
x4=[5,4,3,22,11,6];
g2={x3,x4};
%group3
x5=[10,12,22,4];
x6=[12,15,4,25];
g3={x5,x6};
G=cat(1,g1,g2,g3);
class={1,2,3}
positions = [1 1.25 2 2.25 3 3.25];
boxplot(G,class, 'positions', positions);
set(gca,'xtick',[mean(positions(1:2)) mean(positions(3:4)) mean(positions(5:6)) ])
set(gca,'xticklabel',{'Group1','Group2','Group3'})
color = ['c', 'y', 'c', 'y'];
h = findobj(gca,'Tag','Box');
for j=1:length(h)
patch(get(h(j),'XData'),get(h(j),'YData'),color(j),'FaceAlpha',.5);
end
c = get(gca, 'Children');
hleg1 = legend(c(1:2), 'Feature1', 'Feature2' );
Your problem is that the grouping variables were constructed in the wrong way. Use this sample:
x1=[1,2,2,3,5,3];
x2=[2,5,4,5,8,6];
g1=[x1,x2];
v1=[repmat('A',1,numel(x1)),repmat('B',1,numel(x2))];
%group2
x3=[2,8,9,2,1,6];
x4=[5,4,3,22,11,6];
g2=[x3,x4];
v2=[repmat('A',1,numel(x3)),repmat('B',1,numel(x4))];
%group3
x5=[10,12,22,4];
x6=[12,15,4,25];
g3=[x5,x6];
v3=[repmat('A',1,numel(x5)),repmat('B',1,numel(x6))];
%%
G=[g1,g2,g3]
vg1 = [repmat('1',1,numel(v1)),repmat('2',1,numel(v2)),repmat('3',1,numel(v3))];
vg2=[v1,v2,v3] ;
%%
clc
boxplot(G', {vg1';vg2'}, 'factorseparator',1 , 'factorgap',30,...
'colorgroup',vg2','labelverbosity','majorminor');
I have 3 vectors: Y=rand(1000,1), X=Y-rand(1000,1) and ACTid=randi(6,1000,1).
I'd like to create boxplots by groups of Y and X corresponding to their group value 1:6 (from ACTid).
This is rather ad-hoc and looks nasty
for ii=
dummyY(ii)={Y(ACTid==ii)};
dummyX(ii)={X(ACTid==ii)}
end
Now I have the data in a cell but can't work out how to group it in a boxplot. Any thoughts?
I've found aboxplot function that looks like this but I don't want that, I'd like the builtin boxplot function because i'm converting it to matlab2tikz and this one doesn't do it well.
EDIT
Thanks to Oleg: we now have a grouped boxplot... but the labels are all skew-whiff.
xylabel = repmat({'Bleh','Blah'},1000,1); % need a legend instead, but doesn't appear possible
boxplot([Y(:,end); cfu], {repmat(ACTid,2,1), xylabel(:)} ,'factorgap',10,'color','rk')
set(gca,'xtick',1.5:3.2:50)
set(gca,'xticklabel',{'Direct care','Housekeeping','Mealtimes','Medication','Miscellaneous','Personal care'})
>> ylabel('Raw CFU counts (Y)')
How to add a legend?
I had the same problem with grouping data in a box plot. A further constraint of mine was that different groups have different amounts of data points. Based on a tutorial I found, this seems to be a nice solution I wanted to share with you:
x = [1,2,3,4,5,1,2,3,4,6];
group = [1,1,2,2,2,3,3,3,4,4];
positions = [1 1.25 2 2.25];
boxplot(x,group, 'positions', positions);
set(gca,'xtick',[mean(positions(1:2)) mean(positions(3:4)) ])
set(gca,'xticklabel',{'Direct care','Housekeeping'})
color = ['c', 'y', 'c', 'y'];
h = findobj(gca,'Tag','Box');
for j=1:length(h)
patch(get(h(j),'XData'),get(h(j),'YData'),color(j),'FaceAlpha',.5);
end
c = get(gca, 'Children');
hleg1 = legend(c(1:2), 'Feature1', 'Feature2' );
Here is a link to the tutorial.
A two-line approach (although if you want to retain two-line xlables and center those in the first line, it's gonna be hackish):
Y = rand(1000,1);
X = Y-rand(1000,1);
ACTid = randi(6,1000,1);
xylabel = repmat('xy',1000,1);
boxplot([X; Y], {repmat(ACTid,2,1), xylabel(:)} ,'factorgap',10)
The result:
EDIT
To center labels...
% Retrieve handles to text labels
h = allchild(findall(gca,'type','hggroup'));
% Delete x, y labels
throw = findobj(h,'string','x','-or','string','y');
h = setdiff(h,throw);
delete(throw);
% Center labels
mylbl = {'this','is','a','pain','in...','guess!'};
hlbl = findall(h,'type','text');
pos = cell2mat(get(hlbl,'pos'));
% New centered position for first intra-group label
newPos = num2cell([mean(reshape(pos(:,1),2,[]))' pos(1:2:end,2:end)],2);
set(hlbl(1:2:end),{'pos'},newPos,{'string'},mylbl')
% delete second intra-group label
delete(hlbl(2:2:end))
Exporting as .png will cause problems...
Is there a way to pass in N datasets and plot them in a line graph using for loop?
I did it by passing fixed number of parameter ( eg M1, M2, M3, M4), and repeat plotting manually like below. But I wonder if there are way to code the function dynamically? Let say I can pass in 4 datasets, or 40 datasets, and plot them in one graph via looping.
function plot_four_cdf(M1,M2,M3,M4)
[ycdf1,xcdf1] = cdfcalc(M1);
ycdf1 = ycdf1(2:length(ycdf1));
plot(xcdf1, ycdf1, '-+k', 'LineWidth', 1);
hold on;
[ycdf2,xcdf2] = cdfcalc(M2);
ycdf2 = ycdf2(2:length(ycdf2));
plot(xcdf2, ycdf2, '-ok', 'LineWidth', 1);
hold off;
hold on;
[ycdf3,xcdf3] = cdfcalc(M3);
ycdf3 = ycdf3(2:length(ycdf3));
plot(xcdf3, ycdf3, '-*k', 'LineWidth', 1);
hold off;
hold on;
[ycdf4,xcdf4] = cdfcalc(M4);
ycdf4 = ycdf4(2:length(ycdf4));
plot(xcdf4, ycdf4, '-sk', 'LineWidth', 1);
legend('M100','M80','M50','M20',...
'Location','SE')
xlabel('Relative Error');
ylabel('CDF');
end
You can group all your data in a cell-array and pass that to the function:
function plot_cdfs(M)
figure, hold on
linestyles = {...
'-+k', '-ok', '-*k', '-sk', ...
'-+r', '-or', '-*r', '-sr');
legendentries = cell(size(M));
for ii = 1:numel(M)
[ycdf, xcdf] = cdfcalc(M{ii});
plot(xcdf, ycdf(2:end), linestyles{ii}, 'LineWidth', 1);
legendentries{ii} = ['M' num2str(ii)];
end
legend(legendentries{:}, 'Location','SE')
xlabel('Relative Error');
ylabel('CDF');
end
Note that M is constructed something like
M = {M1, M2, M3, ...}
possibly also in a loop of its own. Note also that the legendentries are now kind of hard to define. You can pass them as a separate argument to the function (better option), or stuff them in the same cell array M next to the data they describe (not very portable).
Note also that you'd have to do some error checking (now, only 8 different plots can be made. An error will result if you do more).
I want to show the p value that was used to generate each curve next to each of the curves plotted. Note that since there is a plot of E and -E, the same p value should be next to both. I've been attempting this for a while and I have not come across anything super useful.
t = -3.1;%coupling
a = 1;%distance between r1 and r3
n = 5;%latice vector span in a1 direction
m = 1;%latice vector span in a2 direction
i = -7;%unique axial vector t_hat direction
j = 11;%unique axial vector c_hat direction
max_p = abs((n*(i+j/2)-j*(m+n/2)));%# of unique p values
La = sqrt(3)*sqrt(m^2+n*m+n^2)*a/gcd(2*n+m,2*m+n);%unit cell length
C = sqrt(n^2+n*m+m^2);%circumference of the nanotube
hold on;
for p=0:1:max_p
kt = -pi/La:.05:pi/La;
kc = 2*pi*p/C;
ka1 = kc*a*.5*(2*n+m)/C + kt*a*sqrt(3)*.5*m/C;
ka2 = kc*a*.5*(n+2*m)/C - kt*a*sqrt(3)*.5*n/C;
E = abs(t+t*exp(1i*ka2)+t*exp(1i*ka1));
title_ = sprintf('(%d,%d) Carbon Nanotube Dispersion Diagram',n,m);
title(title_);
xlabel('k_{t}a');
ylabel('Energy (eV)');
plot(kt,E);
plot(kt,-E);
end
There is a command named text that writes comments into the figures,
http://www.mathworks.se/help/techdoc/ref/text.html
with if you can't solve it with that and the to string operation i misunderstood the question
First, do you need to plot both E and -E? Since these are the same except for their sign you don't really add any information to the plot by having -E there as well. However, if you do need both lines, then just construct an array of strings for the legend, during the loop, which has each string included twice (once for E and once for -E).
... Initial calculations ...
hold on;
for p=0:1:max_p
kt = -pi/La:.05:pi/La;
kc = 2*pi*p/C;
ka1 = kc*a*.5*(2*n+m)/C + kt*a*sqrt(3)*.5*m/C;
ka2 = kc*a*.5*(n+2*m)/C - kt*a*sqrt(3)*.5*n/C;
E = abs(t+t*exp(1i*ka2)+t*exp(1i*ka1));
plot(kt,E);
plot(kt,-E);
% Construct array containing legend text
legend_text{2*(p+1)-1} = strcat('p=', num2str(p));
legend_text{2*(p+1)} = strcat('p=', num2str(p));
end
title_ = sprintf('(%d,%d) Carbon Nanotube Dispersion Diagram',n,m);
title(title_);
xlabel('k_{t}a');
ylabel('Energy (eV)');
legend(legend_text)
I am sure there is a more elegant way of constructing the legend text, but the above code works. Also, notice that I moved the calls to xlabel, ylabel and title to outside of the loop. This way they are only called once and not for each iteration of the loop.
Finally, you need to take care to ensure that each iteration of the loop plots with a different line colour or line style (see edit below). You could colour/style each pair of E and -E lines the same for a given iteration of the loop and just display the legend for E (or -E), which would obviously halve the number of legend entries. To do this you will need to hide one of line's handle visibility - this prevents it from getting an item in the legend. To do this use the following in your loop:
plot(kt, E);
plot(kt,-E, 'HandleVisibility', 'off');
% Construct array containing legend text
legend_text{p+1} = strcat('p=', num2str(p));
Finally, it is best to include clear all at the top of your Matlab scripts.
Edit: To have each plotted line use a different colour for each iteration of your loop use something like the following
... initial calculations ...
cmap = hsv(max_p); % Create a max_p-by-3 set of colors from the HSV colormap
hold on;
for p = 0:1:max_p
plot(kt, E, 'Color', cmap(p,:)); % Plot each pair of lines with a different color
plot(kt, -E, 'Color', cmap(p,:));
end