Note 17-04-18: The information below needs an update
Please keep in mind the toolbox is still under (ongoing) development, and the author has (unfortunately...) put more emphasis on the implementation of features than writing a truly comprehensive BVQXtools Documentation.
However, for objects of a given type, help is available via a method list. This can be produced (displayed) with a call to .Help on any valid object:
glm = BVQXfile('new:glm');
glm.Help
ans =
GLM::FillMissingVertices - fill missing vertices in beta maps / Syntax: [glm] = glm.FillMissingVertices(srf [, method])
GLM::JoinFFX - join two fixed effects GLMs / Syntax: combined = glm1.JoinFFX(glm2);
GLM::JoinRFX - join two random effects GLMs / Syntax: combined = glm1.JoinRFX(glm2);
GLM::MapNames - return a cell array (Nx1) of map names / Syntax: mnames = glm.MapNames;
GLM::PlotBetas - plot betas / Syntax: [ax] = glm.PlotBetas(c [, plotopts])
GLM::PSCMaps - calculate PSC maps for single study GLM / Syntax: pscmap = glm.PSCMaps;
GLM::RemoveSubject - remove subject(s) from GLM / Syntax: [glm = ] glm.RemoveSubject(sid);
GLM::RFX_RemovePredictors - removes predictors for each subject / Syntax: [glm] = glm.RFX_RemovePredictors(removep)
GLM::RFX_rMap - calculate a second-level r contrast map / Syntax: map = glm.RFX_rMap(c, r [, mapopts])
GLM::RFX_tMap - calculate a t contrast map / Syntax: map = glm.RFX_tMap([c, mapopts])
GLM::SingleStudy_tMap - calculate a t contrast map / Syntax: map = glm.SingleStudy_tMap([c, mapopts])
GLM::SubjectPredictors - return list of subject predictor names / Syntax: spreds = glm.SubjectPredictors;
GLM::Subjects - return list of subjects of multi-subject GLM / Syntax: subjects = glm.Subjects;
GLM::VOIBetas - returns a table of VOI betas (per subjects) / Syntax: vb = glm.VOIBetas(voi [, opts]);
GLM::WriteAnalyzeBetas - write beta images as Analyze / Syntax: glm.WriteAnalyzeBetas(tfolder [, cv [, aformat]])
GLM::WriteAnalyzeVols - write Analyze images from a GLM file / Syntax: [success = ] glm.WriteAnalyzeVols(cons)
And, naturally, the details are still accessible with specifying the method in question:
glm.Help('VOIBetas')
ans =
GLM::VOIBetas - returns a table of VOI betas (per subjects)
FORMAT: vb = glm.VOIBetas(voi [, opts]);
Input fields:
voi VOI object
opts optional settings
.c contrasts (defaults: each beta map on its own)
.interp either of {'nearest'}, 'linear', 'cubic'
.rmean remove mean (of map) first
.vl indices of VOIs in object to sample (default: all)
Output fields:
vb SxCxV double table with data
A complete list of all available methods (on all object types) can be produced by a call to Help using the root object:
root = BVQXfile;
root.Help