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    <font size="-1"><font face="Arial">Thanks again!<br>
        I am on Debian testing (well, reverted on stable now, because of
        troubles with gcc5) and have version 2.3.1.<br>
        I will give a try to the one from git.<br>
        Best,<br>
        Marco<br>
        <br>
        <br>
        PyMVPA:<br>
          Version:       2.3.1<br>
          Hash:          d1da5a749dc9cc606bd7f425d93d25464bf43454<br>
          Path:         
        /usr/lib/python2.7/dist-packages/mvpa2/__init__.pyc<br>
          Version control (GIT):<br>
          GIT information could not be obtained due <br>
        "/usr/lib/python2.7/dist-packages/mvpa2/.. is not under GIT"<br>
        SYSTEM:<br>
          OS:            posix Linux 4.1.0-1-amd64 #1 SMP Debian 4.1.3-1
        (2015-08-03)<br>
          Distribution:  debian/stretch/sid<br>
      </font></font><br>
    <br>
    <blockquote type="cite"><b>Yaroslav Halchenko</b> <a
href="mailto:pkg-exppsy-pymvpa%40lists.alioth.debian.org?Subject=Re%3A%20%5Bpymvpa%5D%20Confusion%20Matrix%20for%20each%20Node%20with%0A%20sphere_gnbsearchlight&In-Reply-To=%3C20150828161509.GS19455%40onerussian.com%3E"
        title="[pymvpa] Confusion Matrix for each Node with
        sphere_gnbsearchlight">debian at onerussian.com </a><br>
      <i>Fri Aug 28 16:15:09 UTC 2015</i>
      <hr>
      <pre>On Fri, 28 Aug 2015, marco tettamanti wrote:

><i>    Dear Yaroslav,
</i>><i>    thank you very much for your reply. I have made several attempts, trying
</i>><i>    to guess a solution, but it seems I always get a
</i>><i>    'TypeError: 'NoneType' object is not callable'.
</i>
oh shoot... forgotten that this one was implemented after the last 2.4.0
release: in upstream/2.4.0-34-g55e147e this June... we should release I
guess. what system are you on and what version of pymvpa currently?
if you could use/try the one from git directly... ?

><i>    Case 1:
</i>><i>    slght = sphere_gnbsearchlight(clf, partitioner, radius=slradius,
</i>><i>    space='voxel_indices', errorfx=None, postproc=mean_sample())
</i>
not the problem here BUT there should  be no mean_sample() if errorfx is
None -- you wouldn't want to average labels ;)

-- 
Yaroslav O. Halchenko, Ph.D.
<a href="http://neuro.debian.net">http://neuro.debian.net</a> <a href="http://www.pymvpa.org">http://www.pymvpa.org</a> <a href="http://www.fail2ban.org">http://www.fail2ban.org</a>
Research Scientist,            Psychological and Brain Sciences Dept.
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
WWW:   <a href="http://www.linkedin.com/in/yarik">http://www.linkedin.com/in/yarik</a>        

</pre>
    </blockquote>
    <br>
    <br>
    <br>
    <div class="moz-cite-prefix">On 08/28/2015 05:28 PM, marco
      tettamanti wrote:<br>
    </div>
    <blockquote cite="mid:55E07E37.7030500@gmail.com" type="cite">
      <meta content="text/html; charset=utf-8" http-equiv="Content-Type">
      Dear Yaroslav,<br>
      thank you very much for your reply. I have made several attempts,
      trying to guess a solution, but it seems I always get a<br>
      'TypeError: 'NoneType' object is not callable'.<br>
      <br>
      Any further advice is greatly appreciated!<br>
      Best,<br>
      Marco<br>
      <br>
      <br>
      Case 1:<br>
      slght = sphere_gnbsearchlight(clf, partitioner, radius=slradius,
      space='voxel_indices', errorfx=None, postproc=mean_sample())<br>
      slght_map = slght(fds)<br>
      <br>
      <blockquote>In [70]: slght = sphere_gnbsearchlight(clf,
        partitioner, radius=slradius, space='voxel_indices',
        errorfx=None, postproc=mean_sample())<br>
        <br>
        In [71]: slght_map = slght(fds)<br>
        [SLC] DBG:             Phase 1. Initializing partitions using
        <NFoldPartitioner> on <Dataset: 108x111@float32,
        <sa: chunks,targets,time_coords,time_indices>, <fa:
        voxel_indices>, <a:
        imgaffine,imghdr,imgtype,mapper,voxel_dim,voxel_eldim>><br>
        [SLC] DBG:             Phase 2. Blocking data for 18 splits and
        3 labels<br>
        [SLC] DBG:             Phase 3. Computing statistics for 54
        blocks<br>
        [SLC] DBG:             Phase 4. Deducing neighbors information
        for 111 ROIs<br>
        [SLC] DBG:             Phase 4b. Converting neighbors to sparse
        matrix representation<br>
        [SLC] DBG:             Phase 5. Major loop<br>
        [SLC] DBG:              Split 0 out of 18<br>
        [SLC] DBG:                'Training' is done<br>
        [SLC] DBG:                Doing 'Searchlight'<br>
        [SLC] DBG:               Assessing accuracies<br>
---------------------------------------------------------------------------<br>
        TypeError                                 Traceback (most recent
        call last)<br>
        <ipython-input-71-1146d298ca06> in <module>()<br>
        ----> 1 slght_map = slght(fds)<br>
        <br>
        /usr/lib/python2.7/dist-packages/mvpa2/base/learner.pyc in
        __call__(self, ds)<br>
            257                                    "used and auto
        training is disabled."<br>
            258                                    % str(self))<br>
        --> 259         return super(Learner, self).__call__(ds)<br>
            260 <br>
            261 <br>
        <br>
        /usr/lib/python2.7/dist-packages/mvpa2/base/node.pyc in
        __call__(self, ds)<br>
            119 <br>
            120         self._precall(ds)<br>
        --> 121         result = self._call(ds)<br>
            122         result = self._postcall(ds, result)<br>
            123 <br>
        <br>
        /usr/lib/python2.7/dist-packages/mvpa2/measures/searchlight.pyc
        in _call(self, dataset)<br>
            141 <br>
            142         # pass to subclass<br>
        --> 143         results = self._sl_call(dataset, roi_ids,
        nproc)<br>
            144 <br>
            145         if 'mapper' in dataset.a:<br>
        <br>
        /usr/lib/python2.7/dist-packages/mvpa2/measures/adhocsearchlightbase.pyc

        in _sl_call(self, dataset, roi_ids, nproc)<br>
            513                 # error functions without a chance to
        screw up<br>
            514                 for i, fpredictions in
        enumerate(predictions.T):<br>
        --> 515                     results[isplit, i] =
        errorfx(fpredictions, targets)<br>
            516 <br>
            517 <br>
        <br>
        TypeError: 'NoneType' object is not callable<br>
      </blockquote>
      <br>
      <br>
      <br>
      Similarly for other cases and combinations of them:<br>
      <br>
      Case 2:<br>
      slght = sphere_gnbsearchlight(clf, partitioner, radius=slradius,
      space='voxel_indices', errorfx=ConfusionMatrixError(),
      postproc=mean_sample())<br>
      slght_map = slght(fds)<br>
      <br>
      <br>
      Case3:<br>
      class KeepConfusionMatrix(Node):<br>
            def _call(self, fds):<br>
                out = np.zeros(1, dtype=object)<br>
                out[0] = (fds.samples)<br>
                return out<br>
      <br>
      slght = sphere_gnbsearchlight(clf, partitioner, errorfx=None,
      radius=slradius, space='voxel_indices',
      postproc=ChainNode([Confusion(labels=fds.UT)]))<br>
      slght.postproc.append(KeepConfusionMatrix())<br>
      slght_map = slght(fds)<br>
      <br>
      <br>
      Case4:<br>
      class KeepConfusionMatrix(Node):<br>
            def _call(self, fds):<br>
                out = np.zeros(1, dtype=object)<br>
                out[0] = (fds.samples)<br>
                return out<br>
      <br>
      slght = sphere_gnbsearchlight(clf, partitioner, errorfx=None,
      radius=slradius, space='voxel_indices',
      postproc=ChainNode([mean_sample(),Confusion(labels=fds.UT)]))<br>
      slght.postproc.append(KeepConfusionMatrix())<br>
      slght_map = slght(fds)<br>
      <br>
      <br>
      <br>
      Case5:<br>
      class KeepConfusionMatrix(Node):<br>
            def _call(self, fds):<br>
                out = np.zeros(1, dtype=object)<br>
                out[0] = (fds.samples)<br>
                return out<br>
      <br>
      slght = sphere_gnbsearchlight(clf, partitioner,
      errorfx=ConfusionMatrixError(), radius=slradius,
      space='voxel_indices',
      postproc=ChainNode([mean_sample(),Confusion(labels=fds.UT)]))<br>
      slght.postproc.append(KeepConfusionMatrix())<br>
      slght_map = slght(fds)<br>
      <br>
      <br>
      <br>
      <blockquote type="cite">Yaroslav Halchenko debian at
        onerussian.com<br>
        Fri Aug 28 13:16:38 UTC 2015<br>
        <pre>quick an possible partial reply

1. "not sure" -- if it pukes then probably not, although judging from
the code I foresaw arbitrary shape of the errorfx output

2. but you could make sphere_gnbsearchlight to return labels (not
errors) and then post-process to get those confusion matrices.  Just
specify  errorfx=None  to it (not to CV).  But you could also try
passing errorfx=ConfusionMatrixError and see how that goes

Please share what you discover/end up with.
mvpa2/tests/test_usecases.py  has more of usecase demos for gnb
searchlights which might come handy

-- 
Yaroslav O. Halchenko, Ph.D.
<a moz-do-not-send="true" href="http://neuro.debian.net">http://neuro.debian.net</a> <a moz-do-not-send="true" href="http://www.pymvpa.org">http://www.pymvpa.org</a> <a moz-do-not-send="true" href="http://www.fail2ban.org">http://www.fail2ban.org</a>
Research Scientist,            Psychological and Brain Sciences Dept.
Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755
Phone: +1 (603) 646-9834                       Fax: +1 (603) 646-1419
WWW:   <a moz-do-not-send="true" href="http://www.linkedin.com/in/yarik">http://www.linkedin.com/in/yarik</a>        

</pre>
      </blockquote>
      <br>
      <div class="moz-cite-prefix">On 08/28/2015 01:48 PM, marco
        tettamanti wrote:<br>
      </div>
      <blockquote cite="mid:55E04A89.1050500@gmail.com" type="cite">
        <meta http-equiv="content-type" content="text/html;
          charset=utf-8">
        <font size="-1"><font face="Arial">Dear all,<br>
            is it possible to obtain confusion matrices for all nodes
            with "sphere_gnbsearchlight", as was suggested before with
            "sphere_searchlight":<br>
            <br>
            slcvte = CrossValidation(clf, partitioner, errorfx=None,
            postproc=ChainNode([Confusion(labels=fds.UT)]))<br>
            class KeepConfusionMatrix(Node):<br>
                 def _call(self, fds):<br>
                     out = np.zeros(1, dtype=object)<br>
                     out[0] = (fds.samples)<br>
                     return out<br>
            <br>
            slcvte.postproc.append(KeepConfusionMatrix())<br>
            slght = sphere_searchlight(slcvte, radius=slradius,
            space='voxel_indices', nproc=4, postproc=mean_sample())<br>
            slght_map = slght(fds)<br>
            <br>
            <br>
            Thank you and best wishes,<br>
            Marco<br>
          </font></font>
        <pre class="moz-signature" cols="80">-- 
Marco Tettamanti, Ph.D.
Nuclear Medicine Department & Division of Neuroscience
San Raffaele Scientific Institute
Via Olgettina 58
I-20132 Milano, Italy
Phone ++39-02-26434888
Fax ++39-02-26434892
Email: <a moz-do-not-send="true" class="moz-txt-link-abbreviated" href="mailto:tettamanti.marco@hsr.it">tettamanti.marco@hsr.it</a>
Skype: mtettamanti</pre>
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