Hi,
The simplest way to do this would be to use a while loop using a
modified version of the convergence() function which returns 1 or 0
depending on whether the results have converged (exactly like your
suggestion). I have added this looping ability to the
full_analysis.py script in the relax repository (to both the 1.2 and
1.3 lines). This is not activated by default though and the scripts
in the repository are significantly different from that in the relax
1.2.10 version (all the variables which should be modified by the user
have been shifted to the top of the script). Would you be able to
test if this automatic looping over all rounds of optimisation until
convergence actually works? There could possibly be bugs lurking
there. Thanks.
The problem that you encountered with the calling of the __init__()
function is because this function should not be called. Using that
type of approach, the looping should have been outside of the Main
class to work.
Cheers,
Edward
On 6/16/07, Douglas Kojetin <douglas.kojetin@xxxxxxxxx> wrote:
Hi All,
Is it possible to edit full_analysis.py so the optimization of MII to
MV (self.round > 0) is done automatically by looping until
convergence?
Do you mean that the script will automatically
I tried to do this by modifying the following in
convergence() [near the end]:
"""
# Final print out.
##################
print "\nConvergence:"
if chi2_converged and models_converged and params_converged:
print " [ Yes ]"
return 1
else:
print " [ No ]"
return 0
"""
then modifying __init__(), at the end of the "elif DIFF_MODEL ==
'sphere' or DIFF_MODEL == 'prolate' or DIFF_MODEL == 'oblate' or
DIFF_MODEL == 'ellipsoid':" statement:
"""
# Test for convergence.
test=self.convergence(run=name)
if test == 0:
__init__(self.relax)
#Main(self.relax)
"""
but it did not work properly. I think the problem has something to
do with the call to __init__() or Main(). I'll see if I can dig up
the error reported by relax.
Thanks,
Doug
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Re: looping the optimization in full_analysis.py