Can somebody tell me what work has been done on this project and what kind
of implementations have been done ?
On Tuesday, January 28, 2014 10:24:08 PM UTC+5:30, RAJAT AGGARWAL wrote:
Hi
I was going through the GSoc 2014 Project Ideas Page, and i found an idea
about the step-by-step
What we have in the BASH - we already have in the Python for years. Use
something like pdb to debug the code.
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What i meant with BASH debug thing is for user who are looking for the step
wise solution of a problem, one like we do in out high school exams. and
not like the debug thing because user need not to debug code..
On Thursday, January 30, 2014 5:06:15 PM UTC+5:30, Sergey Kirpichev wrote:
What
This may seem like an ad-hoc way of doing things, but can we think of using
DNF for satisfiability of formulae with small number of atoms? Since DNF
generally causes an extremely dangerous explosion in the size of an
expression, its use to check satisfiability is usually frowned upon by the
logic
I have gone through the package and it seems to have integrated sage and
SnapPy for computing Alexander's polynomial. They have used the idea of
manifolds to implement (I would like to mention that my grasp of subject is
not that far even though I understand the basics of manifold as a local
I am currently pursuing B.Sc in Mathematics and Computer Science. I have
done some python programming in Group Theory but still working my way
through SymPy. I have earlier coded in C and Haskell. Presently I am
getting familiar with GAP and reading
Using Tseitin for small formulas with few arguments is an overkill. In such
cases, switching to some other method sounds like a good idea. Will work on
it and post the test results for comparison.
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Hi Rajat,
I completely understand what you are looking for and I was also looking
for some module like that in sympy. My application is to teach students
engineering mathematics.
I'd like a module that shows how sympy arrived at the final result . For
example, how it simplified the
A few people have expressed interest in the step-by-step GSoC project.
I've recently added a segment on the wiki about what I think is a sane and
effective strategy for this problem.
I've included the addition below for convenience.
In case people are curious, here is the Hacker News effect. The dip to
zero was when we hit our pay quota.
I guess now we need to improve Gamma more. And if you are interested,
GSoC applications to work on Gamma (and/or Live) are welcome.
Aaron Meurer
On Wed, Jan 29, 2014 at 11:06 PM, David Li
I would time the various ways. Unless someone really understands the
theory of DPLL well to know what will and won't be fast, I think this
is the only way we can know what tricks to use when.
In general, though, if something is only faster for very small inputs,
it's not really worth doing,
Why did you subtracted ?
On Tuesday, January 28, 2014 12:31:52 PM UTC+5:30, Sachin p wrote:
How to solve such kind of matrices(see attached pic) for each variable. I
tried using solve_linear_sysem() but no success.
Expected values:
b1 = 0.6566
b2 = 0.7576
b3 = 0.6536
b4 = 0.0893
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If the formulae are small, then the approach there is just fine. If the
formulae is huge but the number of variables small, then just enumerating
the models should be done. If neither of those cases hold, then the best
you could hope for is to try and detect how far the input is from either
CNF
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