Update: I figured out the problem. I needed to use the 'opt'
directory for the results.read() call, not 'aic':
#--start of GOOD code
import glob
runs = glob.glob('prolate/round_*')
# Loop over the runs.
for name in runs:
print name
run.create(name, 'mf')
results.read(run=name, file='results', dir=name+'/opt')
chisq=self.relax.data.chi2[name]
print "%s: %1.10f" % (name, chisq)
#--end
Here is the list of chi2 values. I used 30 decimal points for the
chi2 values -- let me know if you would like something different.
"""
prolate/round_1: 785.330531871414336819725576788187
prolate/round_2: 786.656854782415166482678614556789
prolate/round_3: 784.104495289329975094005931168795
prolate/round_4: 783.543316702498373160779010504484
prolate/round_5: 786.500523476859029869956430047750
prolate/round_6: 784.433290432082458210061304271221
prolate/round_7: 786.264734828735640803643036633730
prolate/round_8: 785.887140331052023611846379935741
prolate/round_9: 785.887140331170371609914582222700
prolate/round_10: 785.887140331282466831908095628023
prolate/round_11: 785.887140331283262639772146940231
prolate/round_12: 785.887140331282807892421260476112
prolate/round_13: 785.887140331283376326609868556261
prolate/round_14: 785.887140331282921579258982092142
prolate/round_15: 785.887140331282353145070374011993
prolate/round_16: 785.887140331283262639772146940231
prolate/round_17: 785.887140331052364672359544783831
prolate/round_18: 785.887140331284172134473919868469
prolate/round_19: 785.887140331283262639772146940231
prolate/round_20: 785.887140331282694205583538860083
prolate/round_21: 785.887140331284967942337971180677
prolate/round_22: 785.887140331337491261365357786417
prolate/round_23: 785.887140331283944760798476636410
prolate/round_24: 785.887140331283376326609868556261
prolate/round_25: 785.887140331282921579258982092142
prolate/round_26: 785.887140331282353145070374011993
prolate/round_27: 785.887140331283262639772146940231
prolate/round_28: 785.887140331052364672359544783831
prolate/round_29: 785.887140331284172134473919868469
prolate/round_30: 785.887140331283262639772146940231
prolate/round_31: 785.887140331282694205583538860083
"""
On Jun 25, 2007, at 3:10 AM, Edward d'Auvergne wrote:
On 6/25/07, Douglas Kojetin <douglas.kojetin@xxxxxxxxx> wrote:
Hi Edward,
I'm trying to write a script to calculate the chisq values for each
of the prolate rounds, but I'm having some trouble as I'm not 100%
familiar with the relax subroutines.
Your code is almost there. I think I know where the script failed
though.
#--start
import glob
runs = glob.glob('prolate/round_*')
# Loop over the runs.
for name in runs:
name=name+'/aic'
run.create(name, 'mf')
results.read(name)
This should all be ok.
chi2=self.relax.data.chi2[run]
Here the 'run' variable should be replaced by 'name'.
print "%s: %1.20f" % (name, chi2)
#--end
This should also work.
But this does not seem to work. Can someone help me with the proper
code to extract chisq values from multiple runs?
If the script fails with the fix, would you be able to attach a print
out of the error message to help in solving where the script failed?
Cheers,
Edward
Re: two questions: hybrid analysis and convergence problems