#Do i have matlab symbolic toolbox code#
let Matlab do the coding for you! Then when you need performance, rewrite your code in Fortran or C++.ĮDIT EDIT Here is an example of timing comparison on my NURBS case. Yeah, probably not as fast as carefully written Matlab, but now you can trivially use any shapefunction. 200th order etc) you could write a single shapefunction routine, and have it crank out a pretty fast anonymous function.
![do i have matlab symbolic toolbox do i have matlab symbolic toolbox](https://i.stack.imgur.com/2TpE4.png)
Instead of having to develop individual functions for each possible order of element (i.e. Results are equivalent to working precisionĮDIT: As a further example of where this can be useful, imagine you're writing an FEA solver. Symbolic Substitution of 1000 elements takes 0.23737 seconds.Īnonymous Function Evaluation of 1000 elements takes 6.4416e-06 seconds.Īnonymous Function Evaluation of 1000 elements is 36850x faster than Symbolic Substitution. The output from this code, on my PC, displays the following: Plot(u,y2,'-','DisplayName','Anonymous Function') Plot(u,y1,'DisplayName', 'Symbolic Evaluation') * otherwiseValueĭisp("Anonymous Function Evaluation of " + string(length(u)) + " elements takes " + string(time2) + " seconds.")ĭisp("Anonymous Function Evaluation of " + string(length(u)) + " elements is " + string(round(time1/time2)) + "x faster than Symbolic Substitution.")ĭisp("Results are equivalent to working precision") Y1 = double(subs(fx,x,u)) % Plot the functionįx = condition. I provide the following example that, while not NURBS, will fit within a Reddit response and demonstrates the functionality: %% SYMBOLIC SUBSTITUTION (SLOW!!)įx = piecewise(condition,valueIfTrue,otherwiseValue)ĭisp("Symbolic Substitution of " + string(length(u)) + " elements takes " + string(time1) + " seconds.")
![do i have matlab symbolic toolbox do i have matlab symbolic toolbox](https://slideplayer.com/slide/17147037/99/images/3/Laplace+Transform+(Try+typing+‘help+laplace’+in+MATLAB…)+LAPLACE+Laplace+transform..jpg)
(Every piece of literature will state something to the effect of "by using the recursive definition we never have to explicitly construct the basis functions") Let me offer up a rebuttal: If you've got complex equations, but you also care about performance, then the Symbolic Toolbox is still a great tool for the job! The key is to use the toolbox's matlabFunction function to convert your symbolic equation into either an anonymous function or m-file.Īs an example, I've recently been working with Non-Uniform Rational B-Splines (NURBS) and found it easier to verify the math if I constructed the basis functions symbolically. If your interested I have it on my computer at home, I can upload it later today. Also, Ive found you can automatically fix most of these errors by wrapping ToMatlab in another function doing something like myToMatlab:=StringReplace,WhiteSpace->""],"old string"->"new string"] A few things dont quite get converted right (special symbols and subscripts immediately come to mind), but for the most part it does a pretty good job. Anything tricky enough that I dont want to do with pen and paper is usually complicated enough to warrent using mathematica rather than matlab.įYI: somewherea long the way I picked up a function for Mathematica called "ToMatlab" that takes some expression in mathematica and converts it to a format that Matlab will accept. If what you want at the end is an equation, well then I still don't use the symbolic toolbox, I use Mathematica. If your final answer is a number- don't touch the symbolic toolbox. The part that originally used symbolic math (which was responsible for all but ~8 seconds of the original runtime of >1 hour) was reduced to about 0.06 seconds, meaning that the actual operation that required symbolic math before got a speedup of >50,000x. But that is beside the point).Įdit: I should mention that the "8 seconds" i quoted was for the entire code to run. It involved an eigensystem decomposition where the eigenvalues were a variable in the matrix being decomposed, and it took me the better part of a week and a fair amount of swearing directed at Mathematica to get an analytic solution. (In past me's defense, the part implemented using symbolic variables and solve was rather tricky.
![do i have matlab symbolic toolbox do i have matlab symbolic toolbox](https://www.humusoft.sk/blog/20190531-symbolic-math/obr1.png)
Its not just a trivial speed increase, it is literally the difference between something taking a day and something taking a couple of minutes. That is why you should avoid using the symbolic toolbox outside of a few select situations. That puts the overall increase in speed at around a factor of ~ 500x. Now, what used to take over an hour to run using symbolic math takes about 8 seconds to run with a purely numeric approach. Now this code was slow, and I needed it to be not so slow, so I went about updating the code to not use symbolic math any more. And, being the Matlab newbie that I was at the time, I had implemented part of this code using symbolic variables and the solve function.
![do i have matlab symbolic toolbox do i have matlab symbolic toolbox](https://4.bp.blogspot.com/-zc42gEPTrtA/VnfXEpFUf4I/AAAAAAAAAW0/lhOBH7i1kgQ/w1200-h630-p-k-no-nu/MATLAB-R2015a-Free-Download.jpg)
Recently, I found myself needing to do something in Matlab that I had implemented in Matlab 4-5 years ago, when I had only been using Matlab for a few months. You often hear "dont use the symbolic toolbox" but rarely do you get a quantitative example of why.