Yes, as Jason said, it's best to just submit a pull request as soon as you have code, so that we can see it and start commenting on it.
But to answer your actual question, you just need to enable the Travis hook in your GitHub. If you look on the Travis site there are instructions. Aaron Meurer On Fri, Aug 2, 2013 at 2:00 PM, Ondřej Čertík <[email protected]> wrote: > On Fri, Aug 2, 2013 at 10:48 AM, Cristóvão Sousa <[email protected]> wrote: >> Hi, >> >> Is it possible to execute the Travis or SymPyBot tests without making a PR? > > You can setup Travis for your own branch at github. > > You can run sympy-bot locally I think. You can also just execute tests > using bin/test. > > Ondrej > >> >> I would like to run the whole test set prior to make a PR, however, tests >> are too slow my poor laptop (and they seem to burn it :/ ). >> >> On Friday, July 12, 2013 8:36:48 PM UTC+1, Ondřej Čertík wrote: >>> >>> Hi Cristóvão, >>> >>> Excellent. Let us know if you need help with submitting a PR. >>> >>> Ondrej >>> >>> On Fri, Jul 12, 2013 at 1:32 PM, Cristóvão Sousa <[email protected]> wrote: >>> > Ok, I've added CSE of Add and Mul arguments (only commutative terms): >>> > http://nbviewer.ipython.org/5986996 >>> > >>> > It runs faster compared to current sympy.cse, even more if applying it >>> > to >>> > large expressions. >>> > However, it still lacks a lot of features, which I'll try to address >>> > using >>> > sympy.cse unit tests. >>> > >>> > >>> > On Wednesday, July 3, 2013 2:52:13 PM UTC+1, Cristóvão Sousa wrote: >>> >> >>> >> Forwarded from PyDy mailing list, >>> >> https://groups.google.com/forum/#!topic/pydy/PjZ9SP8PYDA . >>> >> >>> >> >>> >> >>> >> Hi, >>> >> >>> >> I'm posting here because of one of GSoC 2013 ideas, "Efficient Code >>> >> Generation". >>> >> >>> >> You stated that "Common subexpression elimination (cse) takes a long >>> >> time >>> >> (>1 hour) to run on systems of equations that are derived in a very >>> >> short >>> >> period of time (< 1 minute). This needs to be improved." >>> >> [https://pydy.org/gsoc_2013_ideas#efficient_code_generation] >>> >> >>> >> Indeed, I've verified that myself on my work on SymPyBotics >>> >> (https://github.com/cdsousa/sympybotics), a tool I'm developing to help >>> >> me >>> >> on my PhD studies. >>> >> So, I've developed a kind of CSE, faster than SymPy CSE though less >>> >> general and with some quirks. >>> >> Such CSE functionality is implemented in SymCode package >>> >> (https://github.com/cdsousa/symcode). >>> >> >>> >> Be aware that both SymPyBotics and SymCode are badly documented and >>> >> probably reimplement some functionalities which could be taken from >>> >> SymPy/PyDy (and I probably implement them in worse ways :) >>> >> >>> >> The cse core function is "fast_cse()" which can be found in >>> >> symcode/subexprs.py >>> >> (https://github.com/cdsousa/symcode/blob/master/symcode/subexprs.py.) >>> >> (It uses Subexprs class, which can be used alone to store intermediate >>> >> variables in recursive computations). >>> >> >>> >> I've profiled SymPy cse and noticed that the main time consumption is >>> >> due >>> >> to "count" and "subs" functions, so I tried a different approach. >>> >> First, fast_cse function reversely parses the expression tree and >>> >> recreate >>> >> each unique operation with non-atom arguments substituted by temporary >>> >> symbols (this is the "collect" phase). >>> >> Each unique operation is stored on an "unique_op:tmp_symbol" >>> >> dictionary. >>> >> For example, >>> >> a + b*c + cos(b*c) >>> >> is transformed into >>> >> t2 >>> >> while the dictionary holds >>> >> a + t0 + t1 : t2 >>> >> cos(t0) : t1 >>> >> b * c : t0 >>> >> Additional, match of multiple argument Mul and Add operations is made, >>> >> in >>> >> a similar way to SymPy cse, although argument commutativity is always >>> >> assumed. >>> >> Then, in the "get" phase, the expression tree is recreated from the >>> >> dictionary while temporary "used more than once" symbols are >>> >> maintained. >>> >> The example output will be >>> >> ( [(t0, b*c)], a + t0 + cos(t0) ) >>> >> This is much faster than SymPy CSE although output is generally >>> >> different. >>> >> Also, it still doesn't work with "iterable" arguments, and, as said, >>> >> non-commutativity is not respected . >>> >> >>> >> >>> >> I would love to have time to work on this, or to work on SymPy CSE >>> >> optimization directly, but I'm currently in work overload. >>> >> Nevertheless, I'm showing you this since some ideas can be useful. >>> >> >>> >> Best regards, >>> >> Cristóvão Sousa >>> >> >>> > -- >>> > 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 http://groups.google.com/group/sympy. >>> > For more options, visit https://groups.google.com/groups/opt_out. >>> > >>> > >> >> -- >> 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 http://groups.google.com/group/sympy. >> For more options, visit https://groups.google.com/groups/opt_out. >> >> > > -- > 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 http://groups.google.com/group/sympy. > For more options, visit https://groups.google.com/groups/opt_out. > > -- You received this message because you are subscribed to the Google Groups "sympy" group. 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