[pymvpa] outputting p-values from searchlight

[Nick Oosterhof]

> 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?