Seb,
I've downloaded and unpacked the tar file. I then ran:
$ relax full_analysis_modified.py
This started a calculation (the grid search took far too long for a
system test), and the last print outs were:
-----
Parameter values: array([ 9.00134731e+03, 6.44630021e-16,
-2.80379884e-01,
-6.87605719e-01, 9.47607578e-01, 6.45728529e+01,
9.47607578e-01, 1.70166648e+04, 4.48411813e-18])
Function value: 17.649643455012111
Iterations: 58
Function calls: 716
Gradient calls: 65
Hessian calls: 58
Warning: None
relax> results.write(file='results', dir='prolate/round_2/opt',
force=True, compress_type=1)
Opening the file 'prolate/round_2/opt/results.bz2' for writing.
#####################
# Convergence tests #
#####################
Chi-squared test:
Traceback (most recent call last):
File "/data/relax/relax-1.3/relax", line 420, in <module>
Relax()
File "/data/relax/relax-1.3/relax", line 128, in __init__
self.interpreter.run(self.script_file)
File "/data/relax/relax-1.3/prompt/interpreter.py", line 276, in run
return run_script(intro=self.__intro_string, local=self.local,
script_file=script_file, quit=self.__quit_flag,
show_script=self.__show_script,
raise_relax_error=self.__raise_relax_error)
File "/data/relax/relax-1.3/prompt/interpreter.py", line 545, in
run_script
return console.interact(intro, local, script_file, quit,
show_script=show_script, raise_relax_error=raise_relax_error)
File "/data/relax/relax-1.3/prompt/interpreter.py", line 441, in
interact_script
exec(compile(open(script_file).read(), script_file, 'exec'), local)
File "full_analysis_modified.py", line 677, in <module>
Main(self.relax)
File "full_analysis_modified.py", line 317, in __init__
converged = self.convergence()
File "full_analysis_modified.py", line 416, in convergence
print((" chi2 (k-1): " + repr(prev_pipe.chi2)))
AttributeError: 'PipeContainer' object has no attribute 'chi2'
-----
Is this what is supposed to happen?
Cheers,
Edward
2009/9/4 Sébastien Morin <NO-REPLY.INVALID-ADDRESS@xxxxxxx>:
Follow-up Comment #11, bug #13259 (project relax):
Hi,
Here is a minimal dataset that reproduces the problem.
The script enclosed ('full_analysis_modified.py') will make minimisation
round 'round_2', minimising models 'm1' and 'm8' and proceeding to aic
model
selection. There, model 'm8' will be chosen for residue ALA44 despite a ts
of
~2e-8 (20 ns).
The failure of the script after the aic step is normal and of no importance
for this bug (it is just a result of the hacking of the script)...
Séb
(file #6572)
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