On Tue, Mar 9, 2010 at 11:44 AM, Dag Sverre Seljebotn
<[email protected]> wrote:
> Ondrej Certik wrote:
>> On Tue, Mar 9, 2010 at 9:29 AM, Dag Sverre Seljebotn
>> <[email protected]> wrote:

>
> I must say I almost fell off my chair when I found a Python library
> using lists of floating point numbers for solving ODEs; the API could do
> with a NumPy-aware remake or addition. But apart from that I like the
> explicitness of method selection etc. and code quality in general better
> than SciPy -- SciPy tends to dump things to stdout and not propagate
> exceptions raised in the callback all the way to the odeint -- ugh!!

I noticed the same (I'm doing some ODE integration currently, too) --
taking a look at the code, it's coming from odepack code wrapped by
f2py.  The original f77 code is, as you'd expect, an enormous monolith
that has control & error logic  all mashed together.  I'd be tempted
to leave it be myself :-)

For the record, I'm using scipy.integrate.ode which is a nicer
interface than scipy.integrate.odeint.  The ode class has a
.successful method that easily lets you check to see if anything's
wrong.  And scipy.integrate.ode propogates exceptions raised in the
rhs callback properly, too.  It's all in python, of course, so not
amenable to fast Cython callbacks, however...

Kurt
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