Thanks for the info. Nick. It makes sense. My use case is a bit different from the intended one. Let me know if this approach of using SQEs for that makes sense: I want to get voxels corresponding to nodes at a particular hop/distance from a center node (not less than or equal to that distance). This is similar to HollowSphere in volume searchlights. One approach I am thinking of is to use multiple SQEs at difference hops and eliminate nodes from SQE with smaller radius. I already have SurfaceVerticesQueryEngine with r=0, which lets me get voxels assigned to any particular node, so that I can quickly get all voxels associated with any set of nodes.
Since my initial email, I thought of another approach by using SVQE with largest radius I want and using 'center_distances' to get voxels at a particular distance. I am assuming those are Euclidean distances from center node, is that correct? Eitherway, is there a way to pass that 'fa' to Measure along with the dataset using standard Searchlight()? Thanks, Swaroop On Mon, Jan 5, 2015 at 10:47 AM, Nick Oosterhof <[email protected]> wrote: > Hi Swaroop, > > On 4 January 2015 at 21:06, Swaroop Guntupalli <[email protected]> wrote: >> >> I am trying to use SurfaceQueryEngine, but looks like training >> requires a dataset with node_indices as fa. How do I generate a >> dataset with surface information? > > > First of all: SQE is intended for surface-based searchlights where the input > is a surface dataset. (If the input is a volumetric dataset, use > SurfaceVerticesQueryEngine). > > An existing surface-based dataset in AFNI NIML format can be loaded using > afni_niml_dset.py (in mvpa2/support/nibabel), and converted from and to the > PyMVPA dataset structure using niml.py (in mvpa2/datasets). > > In other cases: if you already have a dataset but without .fa.node_indices, > you would have to set this yourself. In the case of a surface dataset for N > nodes with no missing data (i.e. all nodes have data associated with it) and > data in order (the k-th node on the surface corresponds to the k-th feature > in dataset), you can set it .fa.node_indices to [0, 1, ..., (N-1)]. > >> Is there a helper function to >> achieve that? > > > Not that I know of, apart from the NIML support mentioned above. >> >> >> Since SQE is node-to-nodes mapping, can we skip training with volume >> dataset altogether? > > > Yes. Note that for the SQE, training with a *surface*-based dataset (with > .fa.node_indices) *is* required. > > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
