ena.make.set.Rd
Generates an ENA model by constructing a dimensional reduction of adjacency (cooccurrence) vectors in an ENA data object
ena.make.set( enadata, dimensions = 2, norm.by = fun_sphere_norm, rotation.by = ena.svd, rotation.params = NULL, rotation.set = NULL, endpoints.only = T, node.position.method = lws.positions.sq, as.list = TRUE, ... )
enadata 


dimensions  The number of dimensions to include in the dimensional reduction 
norm.by  A function to be used to normalize adjacency (cooccurrence) vectors before computing the dimensional reduction, default: sphere_norm_c() 
rotation.by  A function to be used to compute the dimensional reduction, default: ena.svd() 
rotation.params  (optional) A character vector containing additional parameters for the function in rotation.by, if needed 
rotation.set  A previouslyconstructed ENARotationSet object to use for the dimensional reduction 
endpoints.only  A logical variable which determines whether to only show endpoints for trajectory models 
node.position.method  A function to be used to determine node positions based on the dimensional reduction, default: lws.position.es() 
as.list  R6 objects will be deprecated, but if this is TRUE, the original R6 object will be returned, otherwise a list with class `ena.set` 
...  additional parameters addressed in inner function 
ENAset
class object that can be further processed for analysis or plotting
This function generates an ENAset object from an ENAdata object. Takes the adjacency (cooccurrence) vectors from enadata, computes a dimensional reduction (projection), and calculates node positions in the projected ENA space. Returns location of the units in the projected space, as well as locations for node positions, and normalized adjacency (cooccurrence) vectors to construct network graphs
data(RS.data) codeNames = c('Data','Technical.Constraints','Performance.Parameters', 'Client.and.Consultant.Requests','Design.Reasoning','Collaboration'); accum = ena.accumulate.data( units = RS.data[,c("UserName","Condition")], conversation = RS.data[,c("Condition","GroupName")], metadata = RS.data[,c("CONFIDENCE.Change","CONFIDENCE.Pre","CONFIDENCE.Post")], codes = RS.data[,codeNames], window.size.back = 4 ) set = ena.make.set( enadata = accum ) set.means.rotated = ena.make.set( enadata = accum, rotation.by = ena.rotate.by.mean, rotation.params = list( accum$meta.data$Condition=="FirstGame", accum$meta.data$Condition=="SecondGame" ) )