[pymvpa] ENET error

[Richard Dinga]

I guess you have invariant features in your dataset, therefore you will get
problems when trying to divide by 0. There is a function to remove them.

On Fri, Sep 16, 2016 at 8:01 PM, Liang, Guangsheng <guangsheng.liang at ttu.edu
> wrote:

> 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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