Here's some of the text file: Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1 Rest 1
Oh, maybe now I'm seeing what the problem is. The second string of characters needs a whitespace after it as well maybe? On Thu, Mar 23, 2017 at 8:01 AM, < pkg-exppsy-pymvpa-requ...@lists.alioth.debian.org> wrote: > Send Pkg-ExpPsy-PyMVPA mailing list submissions to > pkg-exppsy-pymvpa@lists.alioth.debian.org > > To subscribe or unsubscribe via the World Wide Web, visit > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/ > pkg-exppsy-pymvpa > > or, via email, send a message with subject or body 'help' to > pkg-exppsy-pymvpa-requ...@lists.alioth.debian.org > > You can reach the person managing the list at > pkg-exppsy-pymvpa-ow...@lists.alioth.debian.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of Pkg-ExpPsy-PyMVPA digest..." > > > Today's Topics: > > 1. Re: Understanding Classification + HRF (Christopher Markiewicz) > 2. Re: Advice for input to SampleAttributes? Text file may have > too many columns? (Nick Oosterhof) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Wed, 22 Mar 2017 09:05:33 -0400 > From: Christopher Markiewicz <effig...@bu.edu> > To: Development and support of PyMVPA > <pkg-exppsy-pymvpa@lists.alioth.debian.org> > Subject: Re: [pymvpa] Understanding Classification + HRF > Message-ID: > <CAHE-diO1qJiQ=3JNDboic-8C1oSkeR02HeLLByde5-dwaNsd4w@ > mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Hi Anaelia, > > I wouldn't necessarily be concerned about the <50% classification rate. If > you have 6 classes, your chance rate is ~16.7%. I'd expect a "high" > classification rate for 1/6 to be something in the 25-35% range. If you're > doing searchlight, you should see a normal-ish looking distribution with a > mode around 16-17%. > > When it comes to HRF modeling events for classification, I mostly see > people take two routes: > > 1) Model one regressor for each event type (> baseline) per run, so you'll > get 60 images, and each fold will train on 54 and test on 6. > 2) Model one regressor for each individual event, so supposing you have 30 > events of each type plus ten baseline per run, after z scoring, each fold > will train on 1620 images and test on 180. > > The former tends to produce much higher cross-validation accuracies than > the latter, because the variance of each class within runs is removed. It's > also much faster, and HRF estimation is more stable if you're not modeling > individual events. > > The latter is nice if conceptually what you want is to predict individual > responses. I like this because the results are more intuitively > interpretable. Estimation stability is an issue here for individual events, > and I'd recommend checking out Mumford et al 2011 ( > https://dx.doi.org/10.1016/j.neuroimage.2011.08.076). In our 2016 paper ( > https://dx.doi.org/10.1016/j.neuroimage.2016.07.023), we used a variation > on their method (see especially p178 ?5 and p187 ?1). > > For your second question: What do you mean by a "map for each class"? I'm > not really sure where to start here, without a better idea of what you want > the content of the map to be. > > Best, > Chris Markiewicz > > > On Tue, Mar 21, 2017 at 7:12 PM, Anaelia Ovalle <anaeliaova...@gmail.com> > wrote: > > > Hi all, > > > > I am a relatively new pyMVPA user and have 2 questions. > > > > 1) > > > > I'm working with 10 chunks of data (190 rows each) with 6 classes + > > baseline and am looking to classify them using a linear classifier > however > > my results are <50%. I think there's something wrong with how I may be > > setting this up. Being that this is a rapid-event design, I'm looking to > > classify groups of voxel activity to their respective classes. In the > > tutorial, I use a zscored and polydetrended dataset and apply: > > > > clf = LinearCSVMC() > > cvte = CrossValidation(clf, NFoldPartitioner(), > > errorfx= lambda p,t: np.mean(p==t),enable_ca=['stats']) > > cv_results = cvte(df) > > > > > > *However, *since this is an event based task (where the subject's answer > > is placed into a certain class), shouldn't I instead be looking to do an > > event-related analysis, shown in : http://www.pymvpa.org/tutori > > al_eventrelated.html ? Here, would I first do some response modeling via > > fitting a hemodynamic response model? If so, how does this fit into my > > pattern classification? > > > > > > Any clarification regarding these steps would be appreciated. > > > > > > 2) > > > > My final goal after classifying neuronal activity is to then have a map > > for each class. Is this the same as doing a sensitivity mapping with the > > pyMVPA functions for this? > > > > > > > > Thank you, > > > > Anaelia Ovalle > > > > > > > > _______________________________________________ > > Pkg-ExpPsy-PyMVPA mailing list > > Pkg-ExpPsy-PyMVPA@lists.alioth.debian.org > > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/ > pkg-exppsy-pymvpa > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: <http://lists.alioth.debian.org/pipermail/pkg-exppsy- > pymvpa/attachments/20170322/93c2fd16/attachment-0001.html> > > ------------------------------ > > Message: 2 > Date: Wed, 22 Mar 2017 14:44:48 -0300 > From: Nick Oosterhof <n.n.ooster...@googlemail.com> > To: Development and support of PyMVPA > <pkg-exppsy-pymvpa@lists.alioth.debian.org> > Subject: Re: [pymvpa] Advice for input to SampleAttributes? Text file > may have too many columns? > Message-ID: <21795409-964e-4758-8ec4-837698378...@googlemail.com> > Content-Type: text/plain; charset=us-ascii > > > > On 21 Mar 2017, at 16:53, Lauren Nelson <lmnel...@bu.edu> wrote: > > > > I'm having trouble passing a text file to SampleAttributes, and I > -think- what my problem might be is that my text file has more columns than > I thought it did. Vim seems to think it has 3894 columns. > > What makes you think that? Do you mean columns as in (1) strings separated > by some separator string (e.g. whitespace), or (2) columns as in characters? > > > I have a couple questions. Does the following error message seem > consistent with this? > > And if so, is there a possible way to fix this? Even better, is there a > way to read in an Excel spreadsheet? That's the file format I'm starting > with. > > > > >>> attr = SampleAttributes(attr_fname) > > Traceback (most recent call last): > > File "<stdin>", line 1, in <module> > > File "/usr/lib/python2.7/dist-packages/mvpa2/misc/io/base.py", line > 426, in __init__ > > sep=None, dtype=dtypes) > > File "/usr/lib/python2.7/dist-packages/mvpa2/misc/io/base.py", line > 118, in __init__ > > dtype=dtype, skiplines=skiplines) > > File "/usr/lib/python2.7/dist-packages/mvpa2/misc/io/base.py", line > 258, in _from_file > > "of columns in header [%i]." % (len(l), len(hdr)) > > RuntimeError: Number of entries in line [3] does not match number of > columns in header [2]. > > Can you provide the output of the first few lines of your text file? > PyMVPA seems to think there are either 2 or 3 columns (with meaning (1), > separated by some separator string) > > > > > ------------------------------ > > Subject: Digest Footer > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > Pkg-ExpPsy-PyMVPA@lists.alioth.debian.org > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa > > ------------------------------ > > End of Pkg-ExpPsy-PyMVPA Digest, Vol 108, Issue 9 > ************************************************* >
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