I'm using a for loop to add more nodes and edges on my plot. However, when I add labels on new edges the old labels are removed. I don't know how to keep old edge-labels nor how to store the results of labeledge.
This is what I have got so far.
for r = 1: 10
for j = 1:10
H = addnode(P,nodeName{r}{j});
P = addedge(H, s{r}{j}, t{r}{j}, w{r}{j});
figure;
hold on;
h = plot(P);
labeledge(h,s{r}{j},t{r}{j},labelText{r}{j})
end
end
Every time in the new plot, I can only see the newest cluster of labels while old labels are gone. Ideally, I'd love to hold on the results of labeledge but hold on can't do this. I need to show labels in each step in the loop, thus adding another overall labeledge is not my ideal solution. Any hint would be appreciated.
Edit: All my variables are multiple cells of difference sizes in cell arrays. I use for loop to help to pick up vectors from cells because I don't know how to insert all the levels of information from such cell arrays of cells etc. into addNode function.
The main problem in your code is that you keep plotting the graph again and again. This isn't necessary. Instead, use one loop to create the graph object (G), then plot it all at once, and then use another loop for labeling the graph:
P = graph;
for r = 1: 10
for j = 1:10
P = addedge(P, s{r}{j}, t{r}{j}, w{r}{j});
end
end
h = plot(P);
for r = 1: 10
for j = 1:10
labeledge(h,s{r}{j},t{r}{j},labelText{r}{j})
end
end
If you wish to plot your graph on every iteration, you can use subgraph for that:
for k = 1:height(P.Nodes)
H = subgraph(P,1:k);
figure;
h = plot(H);
c = 1;
out = false;
for r = 1: 10
if ~out
for j = 1:10
if c < k
labeledge(h,c,labelText{r}{j})
else
out = true;
break
end
c = c+1;
end
else
break
end
end
end
Besides that, you should know that (from Matlab documentation):
For the best performance, construct graphs all at once using a single call to graph. Adding nodes or edges in a loop can be slow for large graphs.
Also, regardless of the above recommendation, for an easier manipulation of your data, you should first convert your cells to an array. If your cell array contains a different number of elements in each cell, then it is better to collapse it all to one column:
C = [s{:}]; % and the same for t and w
while any(cellfun(#iscell,C))
C = vertcat(C{:});
end
C = cellfun(#(x) x(:),C,'UniformOutput', false);
S = vertcat(C{:});
Labels = [labelText{:}]; % and the same nodeName
while any(cellfun(#iscell,Labels))
Labels = vertcat(Labels{:});
end
Try to remove the 'figure;' command out of the FOR loop and try to see if this worked.
Related
I wrote this matlab code in order to concatenate the results of the integration of all the columns of a matrix extracted form a multi matrix array.
"datimf" is a matrix composed by 100 matrices, each of 224*640, vertically concatenated.
In the first loop i select every single matrix.
In the second loop i integrate every single column of the selected matrix
obtaining a row of 640 elements.
The third loop must concatenate vertically all the lines previously calculated.
Anyway i got always a problem with the third loop. Where is the error?
singleframe = zeros(224,640);
int_frame_all = zeros(1,640);
conc = zeros(100,640);
for i=0:224:(22400-224)
for j = 1:640
for k = 1:100
singleframe(:,:) = datimf([i+1:(i+223)+1],:);
int_frame_all(:,j) = trapz(singleframe(:,j));
conc(:,k) = vertcat(int_frame_all);
end
end
end
An alternate way to do this without using any explicit loops (edited in response to rayryeng's comment below. It's also worth noting that using cellfun may not be more efficient than explicitly looping.):
nmats = 100;
nrows = 224;
ncols = 640;
datimf = rand(nmats*nrows, ncols);
% convert to an nmats x 1 cell array containing each matrix
cellOfMats = mat2cell(datimf, ones(1, nmats)*nrows, ncols);
% Apply trapz to the contents of each cell
cellOfIntegrals = cellfun(#trapz, cellOfMats, 'UniformOutput', false);
% concatenate the results
conc = cat(1, cellOfIntegrals{:});
Taking inspiration from user2305193's answer, here's an even better "loop-free" solution, based on reshaping the matrix and applying trapz along the appropriate dimension:
datReshaped = reshape(datimf, nrows, nmats, ncols);
solution = squeeze(trapz(datReshaped, 1));
% verify solutions are equivalent:
all(solution(:) == conc(:)) % ans = true
I think I understand what you want. The third loop is unnecessary as both the inner and outer loops are 100 elements long. Also the way you have it you are assigning singleframe lots more times than necessary since it does not depend on the inner loops j or k. You were also trying to add int_frame_all to conc before int_frame_all was finished being populated.
On top of that the j loop isn't required either since trapz can operate on the entire matrix at once anyway.
I think this is closer to what you intended:
datimf = rand(224*100,640);
singleframe = zeros(224,640);
int_frame_all = zeros(1,640);
conc = zeros(100,640);
for i=1:100
idx = (i-1)*224+1;
singleframe(:,:) = datimf(idx:idx+223,:);
% for j = 1:640
% int_frame_all(:,j) = trapz(singleframe(:,j));
% end
% The loop is uncessary as trapz can operate on the entire matrix at once.
int_frame_all = trapz(singleframe,1);
%I think this is what you really want...
conc(i,:) = int_frame_all;
end
It looks like you're processing frames in a video.
The most efficent approach in my experience would be to reshape datimf to be 3-dimensional. This can easily be achieved with the reshape command.
something along the line of vid=reshape(datimf,224,640,[]); should get you far in this regard, where the 3rd dimension is time. vid(:,:,1) then would display the first frame of the video.
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...
Hello again logical friends!
I’m aware this is quite an involved question so please bear with me! I think I’ve managed to get it down to two specifics:- I need two loops which I can’t seem to get working…
Firstly; The variable rollers(1).ink is a (12x1) vector containing ink values. This program shares the ink equally between rollers at each connection. I’m attempting to get rollers(1).ink to interact with rollers(2) only at specific timesteps. The ink should transfer into the system once for every full revolution i.e. nTimesSteps = each multiple of nBins_max. The ink should not transfer back to rollers(1).ink as the system rotates – it should only introduce ink to the system once per revolution and not take any back out. Currently I’ve set rollers(1).ink = ones but only for testing. I’m truly stuck here!
Secondly; The reason it needs to do this is because at the end of the sim I also wish to remove ink in the form of a printed image. The image should be a reflection of the ink on the last roller in my system and half of this value should be removed from the last roller and taken out of the system at each revolution. The ink remaining on the last roller should be recycled and ‘re-split’ in the system ready for the next rotation.
So…I think it’s around the loop beginning line86 where I need to do all this stuff. In pseudo, for the intermittent in-feed I’ve been trying something like:
For k = 1:nTimeSteps
While nTimesSteps = mod(nTimeSteps, nBins_max) == 0 % This should only output when nTimeSteps is a whole multiple of nBins_max i.e. one full revolution
‘Give me the ink on each segment at each time step in a matrix’
End
The output for averageAmountOfInk is the exact format I would like to return this data except I don’t really need the average, just the actual value at each moment in time. I keep getting errors for dimensional mismatches when I try to re-create this using something like:
For m = 1:nTimeSteps
For n = 1:N
Rollers(m,n) = rollers(n).ink’;
End
End
I’ll post the full code below if anyone is interested to see what it does currently. There’s a function at the end also which of course needs to be saved out to a separate file.
I’ve posted variations of this question a couple of times but I’m fully aware it’s quite a tricky one and I’m finding it difficult to get my intent across over the internets!
If anyone has any ideas/advice/general insults about my lack of programming skills then feel free to reply!
%% Simple roller train
% # Single forme roller
% # Ink film thickness = 1 micron
clc
clear all
clf
% # Initial state
C = [0,70; % # Roller centres (x, y)
10,70;
21,61;
11,48;
21,34;
27,16;
0,0
];
R = [5.6,4.42,9.8,6.65,10.59,8.4,23]; % # Roller radii (r)
% # Direction of rotation (clockwise = -1, anticlockwise = 1)
rotDir = [1,-1,1,-1,1,-1,1]';
N = numel(R); % # Amount of rollers
% # Find connected rollers
isconn = #(m, n)(sum(([1, -1] * C([m, n], :)).^2)...
-sum(R([m, n])).^2 < eps);
[Y, X] = meshgrid(1:N, 1:N);
conn = reshape(arrayfun(isconn, X(:), Y(:)), N, N) - eye(N);
% # Number of bins for biggest roller
nBins_max = 50;
nBins = round(nBins_max*R/max(R))';
% # Initialize roller struct
rollers = struct('position',{}','ink',{}','connections',{}',...
'rotDirection',{}');
% # Initialise matrices for roller properties
for ii = 1:N
rollers(ii).ink = zeros(1,nBins(ii));
rollers(ii).rotDirection = rotDir(ii);
rollers(ii).connections = zeros(1,nBins(ii));
rollers(ii).position = 1:nBins(ii);
end
for ii = 1:N
for jj = 1:N
if(ii~=jj)
if(conn(ii,jj) == 1)
connInd = getConnectionIndex(C,ii,jj,nBins(ii));
rollers(ii).connections(connInd) = jj;
end
end
end
end
% # Initialize averageAmountOfInk and calculate initial distribution
nTimeSteps = 1*nBins_max;
averageAmountOfInk = zeros(nTimeSteps,N);
inkPerSeg = zeros(nTimeSteps,N);
for ii = 1:N
averageAmountOfInk(1,ii) = mean(rollers(ii).ink);
end
% # Iterate through timesteps
for tt = 1:nTimeSteps
rollers(1).ink = ones(1,nBins(1));
% # Rotate all rollers
for ii = 1:N
rollers(ii).ink(:) = ...
circshift(rollers(ii).ink(:),rollers(ii).rotDirection);
end
% # Update all roller-connections
for ii = 1:N
for jj = 1:nBins(ii)
if(rollers(ii).connections(jj) ~= 0)
index1 = rollers(ii).connections(jj);
index2 = find(ii == rollers(index1).connections);
ink1 = rollers(ii).ink(jj);
ink2 = rollers(index1).ink(index2);
rollers(ii).ink(jj) = (ink1+ink2)/2;
rollers(index1).ink(index2) = (ink1+ink2)/2;
end
end
end
% # Calculate average amount of ink on each roller
for ii = 1:N
averageAmountOfInk(tt,ii) = sum(rollers(ii).ink);
end
end
image(5:20) = (rollers(7).ink(5:20))./2;
inkPerSeg1 = [rollers(1).ink]';
inkPerSeg2 = [rollers(2).ink]';
inkPerSeg3 = [rollers(3).ink]';
inkPerSeg4 = [rollers(4).ink]';
inkPerSeg5 = [rollers(5).ink]';
inkPerSeg6 = [rollers(6).ink]';
inkPerSeg7 = [rollers(7).ink]';
This is an extended comment rather than a proper answer, but the comment box is a bit too small ...
Your code overwhelms me, I can't see the wood for the trees. I suggest that you eliminate all the stuff we don't need to see to help you with your immediate problem (all those lines drawing figures for example) -- I think it will help you to debug your code yourself to put all that stuff into functions or scripts.
Your code snippet
For k = 1:nTimeSteps
While nTimesSteps = mod(nTimeSteps, nBins_max) == 0
‘Give me the ink on each segment at each time step in a matrix’
End
might be (I don't quite understand your use of the while statement, the word While is not a Matlab keyword, and as you have written it the value returned by the statement doesn't change from iteration to iteration) equivalent to
For k = 1:nBins_max:nTimeSteps
‘Give me the ink on each segment at each time step in a matrix’
End
You seem to have missed an essential feature of Matlab's colon operator ...
1:8 = [1 2 3 4 5 6 7 8]
but
1:2:8 = [1 3 5 7]
that is, the second number in the triplet is the stride between successive elements.
Your matrix conn has a 1 at the (row,col) where rollers are connected, and a 0 elsewhere. You can find the row and column indices of all the 1s like this:
[ri,ci] = find(conn==1)
You could then pick up the (row,col) locations of the 1s without the nest of loops and if statements that begins
for ii = 1:N
for jj = 1:N
if(ii~=jj)
if(conn(ii,jj) == 1)
I could go on, but won't, that's enough for one comment.
I have the following code, pasted below. I would like to change it to only average the 10 most recently filtered images and not the entire group of filtered images. The line I think I need to change is: Yout(k,p,q) = (Yout(k,p,q) + (y.^2))/2;, but how do I do it?
j=1;
K = 1:3600;
window = zeros(1,10);
Yout = zeros(10,column,row);
figure;
y = 0; %# Preallocate memory for output
%Load one image
for i = 1:length(K)
disp(i)
str = int2str(i);
str1 = strcat(str,'.mat');
load(str1);
D{i}(:,:) = A(:,:);
%Go through the columns and rows
for p = 1:column
for q = 1:row
if(mean2(D{i}(p,q))==0)
x = 0;
else
if(i == 1)
meanvalue = mean2(D{i}(p,q));
end
%Calculate the temporal mean value based on previous ones.
meanvalue = (meanvalue+D{i}(p,q))/2;
x = double(D{i}(p,q)/meanvalue);
end
%Filtering for 10 bands, based on the previous state
for k = 1:10
[y, ZState{k}] = filter(bCoeff{k},aCoeff{k},x,ZState{k});
Yout(k,p,q) = (Yout(k,p,q) + (y.^2))/2;
end
end
end
% for k = 2:10
% subplot(5,2,k)
% subimage(Yout(k)*5000, [0 100]);
% colormap jet
% end
% pause(0.01);
end
disp('Done Loading...')
The best way to do this (in my opinion) would be to use a circular-buffer to store your images. In a circular-, or ring-buffer, the oldest data element in the array is overwritten by the newest element pushed in to the array. The basics of making such a structure are described in the short Mathworks video Implementing a simple circular buffer.
For each iteration of you main loop that deals with a single image, just load a new image into the circular-buffer and then use MATLAB's built in mean function to take the average efficiently.
If you need to apply a window function to the data, then make a temporary copy of the frames multiplied by the window function and take the average of the copy at each iteration of the loop.
The line
Yout(k,p,q) = (Yout(k,p,q) + (y.^2))/2;
calculates a kind of Moving Average for each of the 10 bands over all your images.
This line calculates a moving average of meanvalue over your images:
meanvalue=(meanvalue+D{i}(p,q))/2;
For both you will want to add a buffer structure that keeps only the last 10 images.
To simplify it, you can also just keep all in memory. Here is an example for Yout:
Change this line: (Add one dimension)
Yout = zeros(3600,10,column,row);
And change this:
for q = 1:row
[...]
%filtering for 10 bands, based on the previous state
for k = 1:10
[y, ZState{k}] = filter(bCoeff{k},aCoeff{k},x,ZState{k});
Yout(i,k,p,q) = y.^2;
end
YoutAvg = zeros(10,column,row);
start = max(0, i-10+1);
for avgImg = start:i
YoutAvg(k,p,q) = (YoutAvg(k,p,q) + Yout(avgImg,k,p,q))/2;
end
end
Then to display use
subimage(Yout(k)*5000, [0 100]);
You would do sth. similar for meanvalue
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