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<div class="moz-cite-prefix">Hi,<br>
<br>
With some great input from Michael I figured out now, that
contrary to the common sphere_searchlight, the
sphere_gnbsearchlight already implements a cross-validation. So
the code got modified now as pasted below. This code runs without
any error. However, the sl.ca.null_prob.samples have all the same
value. This is not the case for the 'common' searchlight
implementation (second snippet below).<br>
<br>
Has anybody an idea, where the code is wrong<tt>, making
MCNullDist</tt> always produce the same permutation?<br>
<br>
Thanks for any hints,<br>
wolf<br>
<br>
<br>
<br>
### GNB-Searchlight<br>
<tt>clf = GNB()</tt><tt><br>
</tt><tt> splt = NFoldPartitioner(cvtype=2, attr='chunks')</tt><tt><br>
</tt> <tt><br>
</tt><tt> repeater = Repeater(count=100)</tt><tt><br>
</tt><tt> permutator = AttributePermutator('targets',
limit={'partitions': 1}, count=1)</tt><tt><br>
</tt> <tt><br>
</tt><tt> null_sl = sphere_gnbsearchlight(clf, ChainNode([splt,
permutator], space=splt.get_space()),</tt><tt><br>
</tt><tt> radius=3,
space='voxel_indices', enable_ca=['roi_sizes'],</tt><tt><br>
</tt><tt> postproc=mean_sample(),
errorfx=mean_mismatch_error)</tt><tt><br>
</tt><tt> distr_est = MCNullDist(repeater, tail='left',
measure=null_sl,</tt><tt><br>
</tt><tt> enable_ca=['dist_samples'])</tt><tt><br>
</tt><tt> sl = sphere_gnbsearchlight(clf,splt, radius=3,
space='voxel_indices',</tt><tt><br>
</tt><tt> enable_ca=['roi_sizes'],
reuse_neighbors=True,</tt><tt><br>
</tt><tt> null_dist=distr_est,
postproc=mean_sample(),</tt><tt><br>
</tt><tt> errorfx=mean_mismatch_error)</tt><tt><br>
</tt><tt> sl_map = sl(ds)</tt><br>
<br>
<br>
<tt>### 'normal' Searchlight</tt><tt><br>
</tt> <tt>clf = GNB()</tt><tt><br>
</tt><tt>splt = NFoldPartitioner(cvtype=2, attr='chunks')</tt><tt><br>
</tt><tt><br>
</tt><tt>repeater = Repeater(count=100)</tt><tt><br>
</tt><tt>permutator = AttributePermutator('targets',
limit={'partitions': 1}, count=1)</tt><tt><br>
</tt><tt>null_cv = CrossValidation(clf, ChainNode([splt,
permutator],space=splt.get_space()),<br>
postproc=mean_sample())</tt><tt><br>
</tt><tt>null_sl = sphere_searchlight(null_cv, radius=3,
space='voxel_indices',</tt><tt><br>
</tt><tt> enable_ca=['roi_sizes'],
nproc=4)</tt><tt><br>
</tt><tt>distr_est = MCNullDist(repeater,tail='left',
measure=null_sl,</tt><tt><br>
enable_ca=['dist_samples'])</tt><tt><br>
</tt><tt>cv = CrossValidation(clf,splt,
errorfx=mean_mismatch_error, <br>
enable_ca=['stats'], postproc=mean_sample()
)</tt><tt><br>
</tt><tt>sl = sphere_searchlight(cv, radius=3,
space='voxel_indices', nproc=4,</tt><tt><br>
</tt><tt> enable_ca=['roi_sizes'],
null_dist=distr_est)</tt><tt><br>
</tt><tt>sl_map = sl(ds)</tt><tt><br>
</tt><br>
<br>
On 10/09/2012 04:49 PM, wolf zinke wrote:<br>
</div>
<blockquote
cite="mid:5040_1349794189_5074398D_5040_2029_1_50743985.6070201@ovgu.de"
type="cite">
<meta http-equiv="content-type" content="text/html;
charset=ISO-8859-1">
Hi,<br>
<br>
I try to use sphere_gnbsearchlight for Monte Carlo Testing to
speed things up a bit. After figuring out the difference of
arguments between sphere_gnbsearchlight and sphere_searchlight, I
was able to set up everything without an argument error. However,
when I run the searchlight analysis, it produces an error. Maybe,
I misunderstood the usage of the arguments for
sphere_gnbsearchlight, especially the generator argument. Any
ideas what I am doing wrong here?<br>
<br>
thanks,<br>
wolf<br>
<br>
<small><tt>clf = GNB() </tt><tt><br>
</tt><tt>splt = NFoldPartitioner(cvtype=2, attr='chunks') </tt><tt><br>
</tt><tt>repeater = Repeater(count=100) </tt><tt><br>
</tt><tt>permutator = AttributePermutator('targets',
limit={'partitions': 1}, count=1) </tt><tt><br>
</tt><tt>null_cv = CrossValidation( clf, ChainNode([splt,
permutator], space=splt.get_space()),
errorfx=mean_mismatch_error, postproc=mean_sample()) </tt><tt><br>
</tt><tt>distr_est = MCNullDist(repeater, tail='left',
measure=null_cv, enable_ca=['dist_samples']) </tt><tt><br>
</tt><tt>cv = CrossValidation(clf, splt,
errorfx=mean_mismatch_error, enable_ca=['stats'], </tt><tt>postproc=mean_sample(),
null_dist=distr_est) </tt><tt><br>
</tt><tt>sl = sphere_gnbsearchlight(clf, cv, radius=3,
space='voxel_indices', enable_ca=['roi_sizes']) </tt><tt><br>
</tt></small>
<blockquote type="cite">---------------------------------------------------------------------------<br>
ValueError Traceback (most recent
call last)<br>
<br>
/home/data/exppsy/zinke/binding/pub_related/mvpa_splitset_epispace/comb/<ipython
console> in <module>()<br>
<br>
/usr/lib/pymodules/python2.6/mvpa2/base/learner.pyc in
__call__(self, ds)<br>
237 "used and auto
training is disabled."<br>
238 % str(self))<br>
--> 239 return super(Learner, self).__call__(ds)<br>
240 <br>
241 <br>
<br>
/usr/lib/pymodules/python2.6/mvpa2/base/node.pyc in
__call__(self, ds)<br>
82 <br>
83 self._precall(ds)<br>
---> 84 result = self._call(ds)<br>
85 result = self._postcall(ds, result)<br>
86 <br>
<br>
/usr/lib/pymodules/python2.6/mvpa2/measures/searchlight.pyc in
_call(self, dataset)<br>
132 <br>
133 # pass to subclass<br>
<br>
--> 134 results = self._sl_call(dataset, roi_ids,
nproc)<br>
135 <br>
136 if 'mapper' in dataset.a:<br>
<br>
/usr/lib/pymodules/python2.6/mvpa2/measures/adhocsearchlightbase.pyc
in _sl_call(self, dataset, roi_ids, nproc)<br>
366 # labels<br>
<br>
367 combinations[:, 0] = labels_numeric<br>
--> 368 for ipartition, (split1, split2) in
enumerate(splits):<br>
369 combinations[split1.samples[:, 0],
1+ipartition] = 1<br>
370 combinations[split2.samples[:, 0],
1+ipartition] = 2<br>
<br>
ValueError: need more than 1 value to unpack<br>
</blockquote>
<br>
<br>
<br>
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<br>
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