Le lundi 21 mars 2011 à 11:08 -0700, Matthew a écrit : > Hello again SymPy Community, > > I'm leaning now towards a GSoC project in Stats/Uncertainty. I like > the work done in the uncertainties package > http://packages.python.org/uncertainties/index.html > and am interested in moving the ideas over to the symbolic world. In a > nutshell the existing package gives you the ability to work with > variables that are enhanced with a single parameter uncertainty (i.e. > standard deviation). > Basic example copied from the link above: > >>> x = ufloat((1, 0.1)) # x = 1+/-0.1 > >>> print 2*x > 2.0+/-0.2 > >>> sin(2*x) # In a Python shell, "print" is optional > 0.90929742682568171+/-0.083229367309428481 > > To me the symbolic equivalent of this is to work with probability > distributions on continuous random variables. Equivalent of the simple > example above: > >>> A = Normal(mean=0, std=1) > >>> A.pdf(x) > 2**(1/2)*exp(-y**2/2)/(2*pi**(1/2)) > >>> sin(A).pdf(x) > 2**(1/2)*exp(-asin(x)**2/2)/(2*pi**(1/2)*(1 - x**2)**(1/2)) > Very good idea! I'll comment more in a few hours.
> - Is this an appropriate direction to take a GSoC project? > - Is this a useful contribution to SymPy? > - What are the relevant parts of SymPy that would need to be enhanced > (right now I see sympy.statistics.distributions)? > - What are some interesting directions people see this going? > - Is there a better way to approach this problem? > - What are some fun examples where this would be useful? > > Feedback strongly appreciated > -Matt > > On Mar 20, 7:22 am, Vinzent Steinberg > <vinzent.steinb...@googlemail.com> wrote: > > Hi Matt, > > > > On Mar 20, 5:32 am, Matthew <mrock...@gmail.com> wrote: > > > > > > > > > > > > > > > > > > > > > Hello SymPy Community, > > > > > I'm looking for an interesting project to work on during some free > > > time I have this Summer and I'm wondering if we're a good fit. Here is > > > a bit about me: > > > > > I'm a PhD student studying Computer Science at the University of > > > Chicago with a background in Physics and Mathematics. I'm a heavy user > > > of Python and its open source developments but have never contributed > > > more than bug reports. I code a fair amount but it's all research- > > > grade and not suitable for public use. My goal for this project would > > > be to focus on crafting code and a clear end-user experience rather > > > than focusing on a scientific research question. I would also like to > > > engage and join the Python community a bit; I've always been "just an > > > end-user." > > > > > I'm searching for an appropriate project for a summer. I'm looking > > > over the provided list and at the existing functionality in SymPy. I > > > have a few ideas but I'd appreciate suggestions. > > > > > My interests include the following: Scientific Computing (generally), > > > Numerical Linear Algebra, Physics (generally), Geometry/Relativity, > > > Dynamical Systems, Statistics (generally), Uncertainty/Sensitivity, > > > Optimization, Education. > > > > > Thoughts: > > > My ideal project would be to develop a code-base for General > > > Relativity. However I see that someone else already has some code that > > > they're thinking of contributing. Would it be best to wait on this? > > > Are there supporting aspects of this topic that I could help with > > > (reworking tensors for example). Relevant thread here:http://goo.gl/zRmDs > > > I could probably improve sympy Matrices. I'm curious, how many people > > > use the existing functionality? What are common applications for > > > symbolic matrices? If I go this route I want to make sure that there > > > are some good motivating use cases. I wonder if something akin to > > > numpy's ndarray would be appropriate to merge both this and the above > > > topic. A lot of functionality is shared and currently (I think) > > > codeveloped in both branches. > > > > The matrices module was written by a GSoC student some time ago. Most > > of the basic stuff is implemented, but the interface could be > > improved. If you want to choose this as a project, I guess you'll have > > to find some more advanced functionality to implement. > > > > Adding pure python numpy-like ndarray support to sympy would be nice. > > This probably requires a lot of work. > > > > > Brian Granger's quantum physics projects seem appropriate. > > > I'm also tangentially interested in code generation. Any suggestions > > > on this front? > > > > Øyvind worked on this during last GSoC, so he may have some > > suggestions. > > > > > Anyone have thoughts for applications in education? Something like > > > sympy might aid significantly in learning calculus for example. > > > > I think sympy has a lot of potential in education. If you want to > > know, you can easily look up the implementation (using ?? or the > > source() command). Do you have any thoughts? To me, this is a not-so- > > obvious project to do. > > > > > Can anyone think of projects that would be appropriate for someone of > > > my background that haven't yet been added to the ideas list? > > > > Any project about statistics or uncertainity. > > > > My suggestion is to choose the project that interests you the most > > (given that it is a project that is likely to be accepted). > > > > Vinzent > -- You received this message because you are subscribed to the Google Groups "sympy" group. To post to this group, send email to sympy@googlegroups.com. To unsubscribe from this group, send email to sympy+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/sympy?hl=en.
