Hi Mark, Very nice project, thanks for sharing. Music theory is indeed very interesting. I was recently playing with a numerical solver for guitar strings:
https://gitlab.com/certik/stringsim But I didn't have time to finish it yet. I was going to use sympy for the method of manufactured solutions to verify the solver. I was wondering if you can produce realistic sounds by literally solving the string equation for an electric guitar (it's my understanding that to first order it's just the strings and the pickups, as well as how and where you pluck the string, but everything else is secondary, unlike for a piano or an acoustic guitar) and feed it to some software amplifier. I think that's how some of the guitar simulators work, but I think they take shortcuts (like they don't actually solve the equation, but just have some modes or even samples and mix them up). I was curious if I can have a regular numerical solver, as I am used to solving other equations. I wasn't able to find anything online or in literature. Ondrej On Tue, Apr 4, 2017 at 7:36 AM, Mark Conway Wirt <[email protected]> wrote: > Hello SymPy People, > > On the SymPy project page they mention letting the list know if you're using > SymPy in a project. > > My particular project may (or may not) be interesting to the folks on the > list, owing to the fact that the domain is a good deal different form the > standard SymPy domain. From the project description: > > PyTuning is a Python library intended for the exploration of musical scales > and microtonalities. It can be used by developers who need ways of > calculating, analyzing, and manipulating musical scales, but it can also be > used interactively. > > It makes heavy use of the SymPy package, a pure-Python computer algebra > system, which allows scales and scale degrees to be manipulated > symbolically, with no loss of precision. There is also an optional > dependency on Matplotlib (and Seaborn) for some visualizations that have > been included in the package. > > > It is released under an MIT-style license. Source code is hosted on GitHub. > Pypi entry is here. > > Thanks for all the work that's gone into this great package! (I also use it > at work more in line with its default use-cases.) > > --mcw > > -- > You received this message because you are subscribed to the Google Groups > "sympy" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To post to this group, send email to [email protected]. > Visit this group at https://groups.google.com/group/sympy. > To view this discussion on the web visit > https://groups.google.com/d/msgid/sympy/58123d8c-ea4d-4a5b-84b4-e798374ebb28%40googlegroups.com. > For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CADDwiVB1PkHi-JF4ghHWysvg4h5eBTnBszU%2BDfe%3DKHCw%3DRk_Uw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
