On September 20, 2016 3:46:40 PM EDT, "Liang, Guangsheng" 
<guangsheng.li...@ttu.edu> wrote:
>Hello,
>
>Thank you very much for your kindly response.
>Which function that I can remove them?
>
>Thanks again!
>Carl
>
>From: Pkg-ExpPsy-PyMVPA
>[mailto:pkg-exppsy-pymvpa-bounces+guangsheng.liang=ttu....@lists.alioth.debian.org]
>On Behalf Of Richard Dinga
>Sent: Tuesday, September 20, 2016 3:50 AM
>To: Development and support of PyMVPA
><pkg-exppsy-pymvpa@lists.alioth.debian.org>
>Subject: Re: [pymvpa] ENET error
>
>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.li...@ttu.edu<mailto:guangsheng.li...@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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>
>
>
>------------------------------------------------------------------------
>
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http://www.pymvpa.org/faq.html#is-there-an-easy-way-to-remove-invariant-features-from-a-dataset
;-)
-- 
Sent from a phone which beats iPhone.
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