Oh hey, that's kinda neat. On one of the slides you mention that by generating equations symbolically > you can change change algorithmic complexity. Can you give an example of > this?
That hasn't happened yet, but is planned. Mostly, it has to do with the idea that in SymPy we have knowledge about the properties of the computations. We know if a variable is always positive, or real, or (most importantly) the properties of a matrix (upper triangular, symmetric, positive definite, etc...). For selecting matrix solving routines, this is important. Based on Matthew's talk at SciPy a few years back. This is a long way off, but should be achievable. In the immediate future we can start applying transformations to the expressions to improve computation speed (not an order of complexity change, but still speed improvements). Horner's method is already part of sympy, and could be applied to polynomials by default to reduce the number of flops needed to compute. We can also apply CSE at a much higher level than gcc will, which is necessary for some of the large expressions that are computed in mechanics. -Jim On Thursday, September 18, 2014 1:33:48 PM UTC-5, Aaron Meurer wrote: > > They are good slides. Good job Jim. > > On one of the slides you mention that by generating equations symbolically > you can change change algorithmic complexity. Can you give an example of > this? > > Aaron Meurer > > On Thu, Sep 18, 2014 at 1:29 PM, Jason Moore <moore...@gmail.com > <javascript:>> wrote: > >> Jim's slides on SymPy code gen got into the Python weekly. >> >> Jason >> moorepants.info >> +01 530-601-9791 >> >> ---------- Forwarded message ---------- >> From: Python Weekly <ra...@pythonweekly.com <javascript:>> >> Date: Thu, Sep 18, 2014 at 11:06 AM >> Subject: Python Weekly - Issue 157 >> To: moore...@gmail.com <javascript:> >> >> >> Email not displaying correctly? 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