Hey Ondrej--

I'll keep this in mind, but I don't think I can post these particular 
calculations as they're proprietary...

One thing this experience suggests though is that it might speed up dsolve 
if the coefficients are replaced with simple symbols such as you had and 
then resubstituted after the solve.  I don't know if that would be true in 
every case, or if it would prevent solutions in some cases...


On Sunday, April 5, 2015 at 12:25:25 AM UTC-7, Ondřej Čertík wrote:
>
> On Sat, Apr 4, 2015 at 11:34 PM, G B <[email protected] <javascript:>> 
> wrote: 
> > Thanks, Ondrej.  In my case the coefficients are the result of a series 
> of 
> > calculations earlier in the notebook.  They are symbolic up until the 
> call 
> > to dsolve, but I am substituting values in right before the dsolve 
> because 
> > it takes several minutes to return a solution otherwise (and gives a 
> very 
> > complicated solution over a segmented domain). 
> > 
> > I let it run to completion symbolically and tried substituting into the 
> > result and I do get something that looks more reasonable.  I can also 
> run it 
> > through lambdify and plot the result.  So despite the slow computation, 
> at 
> > least it looks like I can continue what I'm doing. 
>
> Would you mind posting your whole calculation, if it is possible? We 
> are developing a very fast C++ core (https://github.com/sympy/csympy) 
> and I am always looking for examples of computations that people found 
> to be slow in SymPy, like in your case. 
>
> > 
> > Any idea why the huge integers though?  I seem to remember somewhere 
> that 
> > Sympy will try to convert floats to rationals under certain conditions. 
>  Is 
> > that what's happening?  Can I turn that behavior off? 
> > 
> > Any insight into why it won't evalf or lamdify if I substitute before 
> dsolve 
> > rather than after? 
>
> Aaron just answered these. 
>
> Ondrej 
>
> > 
> > Thanks, again! 
> > 
> > 
> > On Saturday, April 4, 2015 at 9:27:07 PM UTC-7, G B wrote: 
> >> 
> >> Still wrestling with dsolve...  Below is a call with an arbitrary 
> >> differential equation.  Any idea why dsolve is returning terms with 
> these 
> >> enormous integers?  All of the coefficients are floats in this case. 
>  The 
> >> expression is impervious to .n() (as mentioned in my earlier question). 
> >> Converting to a numpy function to evaluate the results works, but 
> throws an 
> >> exception when called. 
> >> 
> >> I can't seem to get past this point in the analysis.  Any idea how I 
> can 
> >> get this into a form I can continue working with? 
> >> 
> >> A=symbols(r'A',cls=Function) 
> >> t=symbols(r't') 
> >> 
> Eq4=-123456.78*A(t)-9876.54*A(t).diff(t)-0.00032*A(t).diff(t,2)+1357908.64 
> >> soln=dsolve(Eq4) 
> >> print(soln.n()) 
> >> 
> >> A(t) == C1*exp(125*t*(-33935533038108675 - 
> >> sqrt(1151618536954453541512853661417481))/274877906944) + 
> >> C2*exp(125*t*(-33935533038108675 + 
> >> sqrt(1151618536954453541512853661417481))/274877906944) + 
> 10.999060885923 
> >> 
> >> 
> >> fn=lambdify(t,soln.rhs,'numpy') 
> >> 
> >> 
> >> fn(3.2) 
> >> 
> >> 
> >> 
> >> 
> --------------------------------------------------------------------------- 
> >> AttributeError                            Traceback (most recent call 
> >> last) 
> >> <ipython-input-42-bde0572cbbe1> in <module>() 
> >> ----> 1 fn(3.2) 
> >> 
> >> //anaconda/lib/python3.4/site-packages/numpy/__init__.py in 
> >> <lambda>(_Dummy_73) 
> >> 
> >> AttributeError: 'int' object has no attribute 'sqrt' 
> > 
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