Comments (4)
I was deducing minimal allowed stepsize from eps(T)
where T
is the type of the time variable. When eps
is changed to eps(t)
, where t
is the current time your example works fine (the epsilon for t=0.0
is ~e-324
...).
EDIT: After thinking about it, the van der Pol equation should be time independent, so starting from t=1.0
brings the bug back...
from dassl.jl.
How does the time step evolve? Your fix above suggests that the time step is >eps(1)
at t1 even though the solution repeats after t1.6. Maybe it's a problem with the initial steps? Anyway, using eps(t)
instead of eps(T)
is probably good irrespective.
from dassl.jl.
This fixes the two errors I made when implementing DASSL.
- I was not using the initial value for the derivative properly (the
dy0
keyword argument). - When
dy0
was not given I was not obtaining it from solvingF(t,y0,dy0)=0
fordy0
.
These two errors combined were forcing the stepsize to go way below the sensible values thus causing the premature termination of integration due to h<hmin
.
In this fix I also rewrote the way error estimates are generated and handled (now it's clearer and simpler) and I slightly changed the order/timestep selection strategy.
Now it is possible to run the solver (with or without Jacobian) with the local error tolerances reduced to 1e-14
and still have h>1e-16
(although for this particular example it leads to larger global error due to roundoff errors).
from dassl.jl.
thanks
from dassl.jl.
Related Issues (15)
- Travis Clang? HOT 2
- Enable AppVeyor Testing
- Common API
- Move the interpolating polynomials to a separate package HOT 6
- Example is failed HOT 2
- Register 2.4.0 HOT 9
- Improve efficiency HOT 3
- [PackageEvaluator.jl] Your package DASSL may have a testing issue. HOT 1
- TagBot trigger issue HOT 2
- Fix MAXORDER=3
- Pass in exact Jacobian HOT 8
- convergence tests fails HOT 6
- allow any callable object, not just ::Function arguments HOT 6
- Move to JuliaDiffEq? HOT 1
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