octave

Currently, I use print -dpng foo.png to print a plot to file in Octave 3.0.1 on Ubuntu. Sometimes, I generate thousands of images in a loop. Whenever a new image pops up, it grabs the mouse control precluding me from multitasking. Is there anyway to print silently or quietly? It would be easier to answer your question with a little more information about what you are doing. But with a little guessing maybe this is what you need: f = figure set(f, "visible", "off") plot([1,2,3,4]) print("MyPNG.png", "-dpng") 来源： https://stackoverflow.com/questions/6289807/print-plot-in-octave-in-background

This question already has an answer here: Create a zero-filled 2D array with ones at positions indexed by a vector 4 answers Often you are given a vector of integer values representing your labels (aka classes), for example [2; 1; 3; 3; 2] and you would like to hot one encode this vector, such that each value is represented by a 1 in the column indicated by the value in each row of the labels vector, for example [0 1 0; 1 0 0; 0 0 1; 0 0 1; 0 1 0] For speed and memory savings, you can use bsxfun combined with eq to accomplish the same thing. While your eye solution may work, your memory usage

I'm using Windows 7 64 bit. Each time, I'm using plot function, plot windows will shows and draws successfully, but after that it stops responding and must shut down it. For example : x = linspace(0,1,10) y = x.^2 plot(x,y); Strangely, when plot windows freeze and I must close octave windows, they will be unresponsive too. This will not happen if I don't use plot function. I don't know why. Does it because I'm using 64 bit version? Please tell me how to fix this. The problem is likely to be the graphics toolkit which your installation of Octave is using. To check this, type graphics_toolkit in

I have a big matrix A which is 1GB of double values, when I reshape it to different dimensions, it's incredible fast. A=rand(128,1024,1024); tic;B=reshape(A,1024,128,1024);toc Elapsed time is 0.000011 seconds. How can it be that fast? Another observation, MATLAB uses less memory than it should after running that code and storing two matrices of 1GB each: Memory used by MATLAB: 1878 MB (1.969e+09 bytes) Explanation of the good performance Matlab uses copy-on-write whenever possible. If you write expressions like B=A , MATLAB does not copy A, instead both variables A and B are references to the