scala - Correct usage of inheritance for wrapper classes -

i trying write scala-wrapper matrix operations, using ejml library. use simplematrix. however, want different classes matrix , vector, example able invert matrix or explicitly state function returns vector, not matrix. currently, having trouble returning concrete classes instead of trait.

i started trait, mlmatrixlike:

trait mlmatrixlike {   def data: simplematrix   protected def internalmult(implicit that: mlmatrixlike): simplematrix = {     data.mult(that.data)   }   def *(implicit that: mlmatrixlike): mlvector = mlvector(internalmult) } 

both matrix class , vector class extending trait:

case class mlmatrix(data: simplematrix) extends mlmatrixlike {    def this(rawdata: array[array[double]]) = this(new simplematrix(rawdata))    def apply(row: int, col:int): double = data.get(row, col)    def transpose(): mlmatrix = mlmatrix(data.transpose())    def invert(): mlmatrix = mlmatrix(data.invert())    def *(implicit that: mlmatrix): mlmatrix = mlmatrix(internalmult)    def *(that: double): mlmatrix = mlmatrix(data.scale(that))    def -(that: mlmatrix): mlmatrix = mlmatrix(data.minus(that.data)) }  object mlmatrix {   def apply(rawdata: array[array[double]]) = new mlmatrix(rawdata) }  case class mlvector(data: simplematrix) extends mlmatrixlike {    def this(rawdata: array[double]) = {     this(new simplematrix(array(rawdata)).transpose())   }    def apply(index: int): double = data.get(index)    def transpose(): mlvector = mlvector(data.transpose())    def -(that: mlvector): mlvector = mlvector(data.minus(that.data)) }  object mlvector {   def apply(rawdata: array[double]) = new mlvector(rawdata) } 

to mind, setup not good. define multiply (*) once, since simplematrix-call same , can infer type of parameter "that" whether return type should matrix or vector. define single function in mlmatrixlike along lines of (not working) function:

def *[t <: mlmatrixlike](that :t): t = {   new t(data.mult(that.data)) } 

of course, not work, since there no such constructor t, fail see, how can similar work. returning mlmatrixlike not correct mind, since way cannot check during compilation if correct type returned.

a similar problem applies transpose, , minus - here return type own class.

thank much!

i'm not sure benefits of wrapping simplematrix in 2 other classes are. however, solve duplication problem making mlmatrixlike generic self-type, , defining abstract constructor.

trait mlmatrixlike[self <: mlmatrixlike[self]] {   this: self =>   def data: simplematrix    def createnew(data: simplematrix): self    def *[t <: mlmatrixlike[t]](that: t): t = that.createnew(data.mult(that.data))    def *(that: double): self = createnew(data.scale(that))    def -(that: self): self = createnew(data.minus(that.data))    def transpose: self = createnew(data.transpose()) }  case class mlmatrix(data: simplematrix) extends mlmatrixlike[mlmatrix] {   this: mlmatrix =>    def this(rawdata: array[array[double]]) = this(new simplematrix(rawdata))    override def createnew(data: simplematrix): mlmatrix = mlmatrix(data)    def apply(row: int, col: int): double = data.get(row, col)    def invert(): mlmatrix = mlmatrix(data.invert())  }  object mlmatrix {   def apply(rawdata: array[array[double]]) = new mlmatrix(rawdata) }  case class mlvector(data: simplematrix) extends mlmatrixlike[mlvector] {   this: mlvector =>    def this(rawdata: array[double]) = {     this(new simplematrix(array(rawdata)).transpose())   }    override def createnew(data: simplematrix): mlvector = mlvector(data)    def apply(index: int): double = data.get(index)  }  object mlvector {   def apply(rawdata: array[double]) = new mlvector(rawdata) } 

by way, note, column vector times row vector matrix, signature of multiplication should not return type of that. however, based on static information (you need know dimensions of both arguments) cannot tell whether multiplication returns vector or matrix, may aswell return mlmatrixlike.