Hi, Yaroslav, Thanks. Perhaps I was not clear. I would certainly save all performance rates, I am familiar with chance-distributions in the brain :-) What I meant is that if the searchlight function is not currently set up to allow me to save all the additional parameters what I want for a large number of searchlights (e.g., weights, confusion matrices), then it might be easier to create an ROI containing my voxels of interest and then rerun those classifiers without the searchlight function. But, your suggestion of mapper.getInId makes sense. Thanks! John
On Sun, Aug 23, 2009 at 2:31 PM, Yaroslav Halchenko<[email protected]> wrote: > > On Sun, 23 Aug 2009, John Clithero wrote: >> If I ran a searchlight analysis like the one I proposed, what would be >> the best way to save the peak performing (or other voxels of interest) >> voxel's coordinate/index and the index for the searchlight's >> neighboring voxels? I could then, I suppose, rerun the classifier on >> that searchlight ROI (without using the searchlight function) and >> harvest other properties (e.g., weights and confusion matrix) that I >> want. >> Again, many thanks for this, I am trying to learn quickly! > Sorry John, I do not quite understand what is the problem if any ;) you > just store your results in whatever structure you like (e.g. list or > ndarray), if you went through all indexes incrementally - you can simply > then use mapper.getInId to get coordinates... or just map all results > back into original 3D space and work there and get feature id for > interesting voxel with getOutId. > > I would advise to store all performances through the whole brain/ROI > since it might give you better sense of 'by chance' distribution (all > those in the left tail of below-chance performances) > -- > .-. > =------------------------------ /v\ ----------------------------= > Keep in touch // \\ (yoh@|www.)onerussian.com > Yaroslav Halchenko /( )\ ICQ#: 60653192 > Linux User ^^-^^ [175555] > > > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa > _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
