I'm doing some simulations that end up taking quite a bit of memory. The numbers themselves are ok for my machine though. But when I try to plot them, I run out of memory. I guess matlab's plots are a special format that makes use of all the data available. However, I'd like to skip that step, and just generate a .jpg or .png directly. I don't even need/want the plot to pop up on the screen, I'd rather just save it directly to file, and bring it up later when I want.
Is such a thing possible in matlab?
Try creating the figure as invisible:
figure('visible','off')
plot(x, y); %// Insert your plot commands here
print filename.png -dpng %// print figure to file
Related
I have a plot in which there are a few noise components. I am planning to select data from that plot preferably above a threshold in my case I am planning to keep it at 2.009 on the Y axis. And plot the lines going only above it. And if anything is below that i would want to plot it as 0.
as we can see in the figure
t1=t(1:length(t)/5);
t2=t(length(t)/5+1:2*length(t)/5);
t3=t(2*length(t)/5+1:3*length(t)/5);
t4=t(3*length(t)/5+1:4*length(t)/5);
t5=t(4*length(t)/5+1:end);
X=(length(prcdata(:,4))/5);
a = U(1 : X);
b = U(X+1: 2*X);
c = U(2*X+1 : 3*X);
d = U(3*X+1 : 4*X);
e = U(4*X+1 : 5*X);
figure;
subplot (3,2,2)
plot(t1,a);
subplot (3,2,3)
plot(t2,b);
subplot(3,2,4)
plot(t3,c);
subplot(3,2,5)
plot(t4,d);
subplot(3,2,6)
plot(t5,e);
subplot(3,2,1)
plot(t,prcdata(:,5));
figure;
A=a(a>2.009,:);
plot (t1,A);
This code splits the data (in the image into 5 every 2.8 seconds, I am planning to use the thresholding in first 2.8 seconds. Also I had another code but I am just not sure if it works as it took a long time to be analysed
figure;
A=a(a>2.009,:);
plot (t1,A);
for k=1:length(a)
if a(k)>2.009
plot(t1,a(k)), hold on
else
plot(t1,0), hold on
end
end
hold off
The problem is that you are trying to plot potentially several thousand times and adding thousands of points onto a plot which causes severe memory and graphical issues on your computer. One thing you can do is pre process all of the information and then plot it all at once which will take significantly less time.
figure
threshold = 2.009;
A=a>threshold; %Finds all locations where the vector is above your threshold
plot_vals = a.*A; %multiplies by logical vector, this sets invalid values to 0 and leaves valid values untouched
plot(t1,plot_vals)
Because MATLAB is a highly vectorized language, this format will not only be faster to compute due to a lack of for loops, it is also much less intensive on your computer as the graphics engine does not need to process thousands of points individually.
The way MATLAB handles plots is with handles to each line. When you plot a vector, MATLAB is able to simply store the vector in one address and call it once when plotting. However, when each point is called individually, MATLAB has to store each point in a separate location in memory and call all of them individually and graphically handle each point completely separately.
Per request here is the edit
plot(t1(A),plot_vals(A))
Inside a while loop, I have some function that creates all the neccesary y-values for the plot I want to make. After all the y-values are done I want my program to plot the dat(while still inside the loop), but the plot can't be made because the data won't come out until the end of the loop.
Is there anyway to do this?
Basically my code is(and I'm just going to for the first case here)
while c~=3
c=menu('a','b','c')
switch c
case 1
for
%function that creates y-values
end
plot(x,y)
end
end
As I said; I get out all the data at the end of the loop, which is stored in the workspace. Meaning that when I run it a second time, it works fine.
But I want to know how to make it work the first time.
for Continuous line plot you can use drawnow and here it is explained how to do this (remember to use pause(.) if you want to visualize the changes "real-time".
for retain current plot when adding new plots use hold on as it is explained here
if you want to open different windows for every different plot you can use something like:
ii=1;
while ...
...
figure(ii)
plot(x,y)
ii=ii+1;
...
end
but be careful with the last one: if you have a big number of plots you can have some problem
So I have a sample dataset which I need to plot using Matlab.
The columns look like this:
Obviously due to this data set the plot looks exceptionally condensed.
Now I am totally new to plotting and statistical data processing.
What can be done to make the data plot more visually comparable/perusal-able (plotting at larger intervals?)?
Here's the code I wrote:
fid=fopen('me.dat', 'r');
s=textscan(fid,'%s %s %f %f', 'headerlines', 1);
fclose(fid);
a=s{1};
b=s{2};
c=s{3};
d=s{4};
plot(c,d)
Thanks.
When I have this kind of problem, I usually use the following methods:
1) Plot only every certain point. If you have 1D arrays a and b and you want to plot, say, every 5th point, use plot(a(1:5:end),b(1:5:end)), instead of plot(a,b). This works, because a(1:5:end) returns a(1), a(6), a(11), ..., so that you will plot roughly 1/5 of your data points. Here you simply omit most of your data points, so I prefer the second method.
2) If you have Image Processing toolbox, use imresize. Before plotting, resize your data aplot=imresize(a,0.2); If you want to decrease the size of your array by a factor of N, the second argument of the imresize should be 1/N. This generally works better, since you have an idea what's going on in your full dataset.
Is it somehow possible to get signal data from figure, to save the vector or matrix of the data to the Workspace?
We happend to make a lots of measurements on a real system in school, but ve saved only figures of the measutrement and now we need to use some of the signals from the figure and use them in another figure for comparison.
You can load the figure in Matlab and go to View->Properties, to pull the data out of the plot's properties e.g. for a line graph plot:
You can get at the XData and YData properties and copy/paste the values of out it e.g.
Alternatively, as I had to do once when this method failed, you can save the figure as EPS/postscript and try to pull the data out of the postscript file in a text editor (!)
I have a huge sparse matrix (1,000 x 1,000,000) that I cannot load on matlab (not enough RAM).
I want to visualize this matrix to have an idea of its sparsity and of the differences of the values.
Because of the memory constraints, I want to proceed as follows:
1- Divide the matrix into 4 matrices
2- Load each matrix on matlab and visualize it so that the colors give an idea of the values (and of the zeros particularly)
3- "Stick" the 4 images I will get in order to have a global idea for the original matrix
(i) Is it possible to load "part of a matrix" in matlab?
(ii) For the visualization tool, I read about spy (and daspect). However, this function only enables to visualize the non-zero values indifferently of their scales. Is there a way to add a color code?
(iii) How can I "stick" plots in order to make one?
If your matrix is sparse, then it seems that the currently method of storing it (as a full matrix in a text file) is very inefficient, and certainly makes loading it into MATLAB very hard. However, I suspect that as long as it is sparse enough, it can still be leaded into MATLAB as a sparse matrix.
The traditional way of doing this would be to load it all in at once, then convert to sparse representation. In your case, however, it would make sense to read in the text file, one line at a time, and convert to a MATLAB sparse matrix on-the-fly.
You can find out if this is possible by estimating the sparsity of your matrix, and using this to see if the whole thing could be loaded into MATLAB's memory as a sparse matrix.
Try something like: (untested code!)
% initialise sparse matrix
sparse_matrix = sparse(num_rows, num_cols);
row_num = 1;
fid = fopen(filename);
% read each line of text file in turn
while ~feof(fid)
this_line = fscanf(fid, '%f');
% add row to sparse matrix (note transpose, which I think is required)
sparse_matrix(row_num, :) = this_line';
row_num = row_num + 1;
end
fclose(fid)
% visualise using spy
spy(sparse_matrix)
Visualisation
With regards to visualisation: visualising a sparse matrix like this via a tool like imagesc is possible, but I believe it may internally create the full matrix – maybe someone can confirm if this is true or not. If it does, then it's going to cause you memory problems.
All spy is really doing is plotting in 2D the locations of the non-zero elements. You can fairly easily write your own spy function, which can have different coloured or sized points depending on the values at each location. See this answer for some examples.
Saving sparse matrices
As I say above, the method your matrix is saved as is pretty inefficient – for a matrix with 10% sparsity, around 95% of your text file will be a zero or a space. I don't know where this data has come from, but if you have any control over its creation (e.g. it comes from another program you have written) it would make much more sense to save only the non-zero elements in the format row_idx, col_idx, value.
You can then use spconvert to import the sparse matrix directly.
One of the simplest methods (if you can actually store the full sparse matrix in RAM) is to use gnuplot to visualize the sparisty pattern.
I was able to spy matrices of size 10-20GB using gnuplot without problems. But make sure you use png or jpeg formats to output the image. Note that you don't need the value of the non-zero entry only the integers (row, col). And plot them "plot "row_col.dat" using 1:2 with points".
This chooses your row as x axis and cols as your y axis and start plotting the non-zero entries. It is very easy to do this. This is the most scalable solution I know. Gnuplot works at decent speed even for very large datasets (>10GB of [row, cols]), but Matlab just hangs (with due respect)
I use imagesc() to visualise arrays. It scales the values in array to values between 0 and 1, then plots the array like a greyscale bitmap image (of course you can change the colormap to make it easier to see detail).