[pymvpa] outputting p-values from searchlight

[William Graves]

Yes, that works perfectly now. Thanks Nick!

For some reason, I had to remove the enable_ca=‘ca.pvalues’ argument from the sphere_searchlight function, but as soon as I did that, it worked great.

Thanks again,
Will

> On May 19, 2017, at 10:29 AM, Nick Oosterhof <n.n.oosterhof at googlemail.com> wrote:
> 
> 
>> On 19 May 2017, at 16:24, Nick Oosterhof <n.n.oosterhof at googlemail.com> wrote:
>> 
>>> 
>>> On 19 May 2017, at 16:16, William Graves <william.wyatt.graves at gmail.com> wrote:
>>> 
>>> Hi Nick,
>>> 
>>> Thanks for the quick reply!
>>> 
>>> The problem is, when I run the searchlight without setting “corrcoef_only” to “True”, I get this error (here are the last few lines of the output, let me know if it doesn’t show up properly):
>>> 
>>> [SLC] DBG:              +0:00:57 ======[100%]====== 0:00:00  ROI 1465 (1465/1465), 36 features
>>> 
>>> [SLC] DBG:               hstacking 1465 results of shape (1, 2)
>>> [SLC] DBG:               hstacked shape (1, 2930)
>>> ---------------------------------------------------------------------------
>>> ValueError                                Traceback (most recent call last)
>>> <ipython-input-185-a11e1def05a0> in <module>()
>>> ----> 1 slres = sl(ds)
>>> 
>>> /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/base/learner.pyc in __call__(self, ds)
>>>   256                                    "used and auto training is disabled."
>>>   257                                    % str(self))
>>> --> 258         return super(Learner, self).__call__(ds)
>>>   259 
>>>   260     is_trained = property(fget=lambda x: x.__is_trained, fset=_set_trained,
>>> 
>>> /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/base/node.pyc in __call__(self, ds, _call_kwargs)
>>>   135 
>>>   136         self._precall(ds)
>>> --> 137         result = self._call(ds, **(_call_kwargs or self._get_call_kwargs(ds)))
>>>   138         result = self._postcall(ds, result)
>>>   139 
>>> 
>>> /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/measures/searchlight.pyc in _call(self, dataset)
>>>   152 
>>>   153         # pass to subclass
>>> --> 154         results = self._sl_call(dataset, roi_ids, nproc)
>>>   155 
>>>   156         if 'mapper' in dataset.a:
>>> 
>>> /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/measures/searchlight.pyc in _sl_call(self, dataset, roi_ids, nproc)
>>>   382                                     dataset=dataset,
>>>   383                                     roi_ids=roi_ids,
>>> --> 384                                     results=self.__handle_all_results(p_results))
>>>   385 
>>>   386         # Assure having a dataset (for paranoid ones)
>>> 
>>> /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/measures/searchlight.pyc in _concat_results(sl, dataset, roi_ids, results)
>>>   262 
>>>   263         # store the center ids as a feature attribute
>>> --> 264         result_ds.fa['center_ids'] = roi_ids
>>>   265 
>>>   266         return result_ds
>>> 
>>> /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/mvpa2/base/collections.pyc in __setitem__(self, key, value)
>>>   597                                 len(value.value),
>>>   598                                 ulength,
>>> --> 599                                 str(self)))
>>>   600         # tell the attribute to maintain the desired length
>>>   601         value.set_length_check(ulength)
>>> 
>>> ValueError: Collectable 'center_ids' with length [1465] does not match the required length [2930] of collection '<FeatureAttributesCollection: metrics>'.
>>> 
>>> Presumably there’s a clever way to get around this that I just haven’t figured out.
>> 
>> This could actually be a bug in mvpa2/measures/rsa.py, the line that causes trouble (git blame):
>> 
>> d3885f6c (Michael Hanke         2016-01-22 15:18:23 +0100 293)             return Dataset([[rho, p]], fa={'metrics': ['rho', 'p']})
>> 
>> where the dataset returned is of size 1x2 (1 sample, 2 features). To me it would make more sense to return a 2x1 dataset (2 samples, 1 feature) so that datasets can be stacked for the searchlight output.
>> 
>> @Michael Hanke, would you agree? 
> 
> So it's seems it's not a bug but intended (and tested!)  behaviour; I just found this in mvpa2/tests/test_rsa.py, line 225-226:
> 
>   # now with both but we need to transpose datasets
>    tdcm1_both = PDistTargetSimilarity(tdsm, postproc=TransposeMapper())
> 
> This approach with the postproc works together with a searchlight. 
> 
> 
> 
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