Hello PyMVPA community,

I am currently working on a fMRI data applying an ENET classifier.
My PyMVPA is running under Linux environment, with python 2.7.12.
The design of the data is a repeated measurement with pre and post conditions.
In my understanding, in my case, chunk value should store subject ID, target 
value should store the time conditions.
I am using the classifier code that I found in the maillist: 
http://lists.alioth.debian.org/pipermail/pkg-exppsy-pymvpa/2009q1/000412.html

clf = FeatureSelectionClassifier(\
                ENET(lm=1.0,max_steps=500,trace=False,normalize=False),\
                SensitivityBasedFeatureSelection(\
                                CorrStability(),\
                                
FixedNElementTailSelector(5000,mode='select',tail='upper')),\
                descr="ENET on 5K best(CorrStability) features")


I am also using 1000 times of permutation to test the null hypothesis, which 
are almost the same as those in the tutorial: 
http://www.pymvpa.org/tutorial_significance.html#the-following-content-is-incomplete-and-experimental
 (section: Avoiding the trap OR Advanced magic 101)

However, errors suspend my program:

/lustre/work/apps/anaconda/lib/python2.7/site-packages/mvpa2/measures/corrstability.py:94:
 RuntimeWarning: invalid value encountered in divide
  covar = (dat1*dat2).mean(0) / (dat1.std(0) * dat2.std(0))
/lustre/work/apps/anaconda/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185:
 RRuntimeWarning: Error in y - mu : non-numeric argument to binary operator

  warnings.warn(x, RRuntimeWarning)
Traceback (most recent call last):
  File "15subj_enet.py", line 68, in <module>
    err_fds = cv_mc_corr_fds(fds)
  File 
"/lustre/work/apps/anaconda/lib/python2.7/site-packages/mvpa2/base/learner.py", 
line 258, in __call__
    return super(Learner, self).__call__(ds)
  File 
"/lustre/work/apps/anaconda/lib/python2.7/site-packages/mvpa2/base/node.py", 
line 136, in __call__
    self._precall(ds)
  File 
"/lustre/work/apps/anaconda/lib/python2.7/site-packages/mvpa2/measures/base.py",
 line 120, in _precall
    self.__null_dist.fit(measure, ds)
  File 
"/lustre/work/apps/anaconda/lib/python2.7/site-packages/mvpa2/clfs/stats.py", 
line 427, in fit
    % (measure, skipped))
RuntimeError: Failed to obtain any value from <CrossValidation>. 1000 
measurements were skipped. Check above warnings, and your code/data


I was wondering if someone could kindly explain what are those mean, and how do 
I resolve this?

Thank you very much!
Carl

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