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View of /branches/charisee/src/compiler/ein/mkoperators.sml

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Revision 2844 - (download) (annotate)
Tue Dec 9 18:05:29 2014 UTC (4 years, 9 months ago) by cchiw
File size: 14600 byte(s)
code cleanup
(* creates EIN operators 
 *
 * COPYRIGHT (c) 2012 The Diderot Project (http://diderot-language.cs.uchicago.edu)
 * All rights reserved.
 *)

structure mkOperators = struct

    local

    structure E = Ein
    structure P=Printer
    in
 
    fun specialize(alpha,inc)=  List.tabulate(length(alpha), (fn(x)=>E.V (x+inc)))
 
    (* Adding tensors : < X{\alpha} + Y_{\alpha}>_{\alpha} *)
    fun addTen alpha =let
        val expindex= specialize(alpha,0)
        in 
            E.EIN{
            params = [E.TEN(1,alpha), E.TEN(1,alpha)], index = alpha,
            body = E.Add[E.Tensor(0, expindex), E.Tensor(1, expindex)]
            }
        end
        
    fun createVec dim=E.EIN{
        params = [E.TEN(1,[dim])], index = [dim],
        body = E.Tensor(0, [E.V 0])
        }

     val zero=E.EIN{
        params = [], index = [],
        body = E.Const(0)
        }
        
        
     fun subTen alpha=let
        val expindex= specialize(alpha,0)
        in
            E.EIN{
            params = [E.TEN(1,alpha), E.TEN(1,alpha)], index = alpha,
            body = E.Sub(E.Tensor(0, expindex), E.Tensor(1, expindex))}
        end
    
    fun divTen alpha =let
        val expindex= specialize(alpha,0)
        in  E.EIN{
            params = [E.TEN(1,alpha), E.TEN(1,[])], index = alpha,
            body = E.Div(E.Tensor(0, expindex), E.Tensor(1,[]))
        }
        end
        
    (* Trace: <M_{i, i}>  This one Sx represents both i's*)
    fun trace dim = E.EIN{
        params = [E.TEN(1,[dim,dim])],         
        index = [],        
        body = E.Sum([(E.V 0,0,dim-1)],E.Tensor(0, [E.V 0, E.V 0]))
    }
        
    fun negTen alpha=let
        val  expindex= specialize(alpha,0)
        in E.EIN{
            params = [E.TEN(1,alpha)],
            index = alpha,
            body = E.Neg(E.Tensor(0, expindex))
        }
        end
        
    (* scalar times tensor product: <s * T_{\alpha}>_{\alpha} *)
    fun scaleTen alpha = let
        val expindex= specialize(alpha,0)
        in E.EIN{
            params = [E.TEN(1,[]), E.TEN(1,alpha)],    (* s and T *)
            index = alpha,           (* \alpha *)
            body = E.Prod[ E.Tensor(0, []),  E.Tensor(1, expindex)]
        }
        end 

    (* generic inner product: <T_{\alpha i} * T_{i \beta}>_{\alpha \beta} *)
    fun innerProduct(shape1,i::beta) = let
        val alpha= List.take(shape1,length(shape1)-1)
        val expindexA= specialize(alpha,0)
        val expindexB= specialize(beta,(length(alpha)))
        val s'=E.V(length(alpha)+ length(beta))
        val s''=[(s',0,i-1)]
        in E.EIN{
             params = [E.TEN(1,shape1) ,E.TEN(1,i::beta)],              (* T and T' *)
            index = alpha@beta,   (* \alpha \beta, i *)
            body = E.Sum(s'', E.Prod[
                E.Tensor(0, expindexA@[s']),   (* T_{\alpha i} *)
                E.Tensor(1, [s']@expindexB )  (* T'_{i \beta} *)
                ])
        }
        end
        | innerProduct _ = raise Fail "Wrong shape for inner product"

    (*<T_{\alpha i j} * B{i j \beta }>_\alpha \beta*)
    fun doubleDot(shape1,i::j::beta) = let
        val alpha= List.take(shape1,length(shape1)-2)
        val expindexA= specialize(alpha,0)
        val expindexB= specialize(beta,(length(alpha)))
        val sumi=length(alpha)+ length(beta)
        val s'=[E.V sumi,E.V(sumi+1)]
        val s''=[(E.V sumi,0,i-1),(E.V(sumi+1),0,j-1)]
        in E.EIN{
            params = [E.TEN(1,shape1),E.TEN(1,i::j::beta)],
            index = alpha@beta,
            body = E.Sum(s'',E.Prod[
                E.Tensor(0, expindexA@s'),
                E.Tensor(1,s'@expindexB)
                ])
        }
        end
        | doubleDot _ = raise Fail "Wrong shape for double dot "
        
    (*Vector Examples : <T_i * T_j>_ij..t0⊗t1*)
    fun outerProduct(dimA,dimB) =E.EIN{
        params = [E.TEN(1,[dimA]), E.TEN(1,[dimB])],
        index= [dimA,dimB],
        body= E.Prod[E.Tensor(0, [E.V 0]), E.Tensor(1, [E.V 1])]
    }
       
        
    fun transpose([i,j]) =E.EIN{
        params = [E.TEN(1,[i,j])], index= [j,i],
        body= E.Tensor(0, [E.V 1,E.V 0])
      }
    | transpose _= raise Fail "too many indices for transpose"
        

    fun modulate dim =E.EIN{
        params = [E.TEN(1,[dim]), E.TEN(1,[dim])],
        index = [dim],
        body = E.Prod[E.Tensor(0, [E.V 0]), E.Tensor(1, [E.V 0])]
        }
        
        
    (*crossProduct is on 3D vectors ..vec3 t8=t0 × t1; *)
    val crossProduct = E.EIN{
        params = [E.TEN(1,[3]), E.TEN(1,[3])],
        index= [3],
        body=E.Sum([(E. V 1,0,2),(E.V 2,0,2)],
            E.Prod[ E.Epsilon(0, 1, 2), E.Tensor(0, [E.V 1]),  E.Tensor(1, [E.V 2 ]) ])
    }
        
    (*2-d cross product Eps_{ij}U_i V_j*)
    val crossProduct2 = E.EIN{
        params = [E.TEN(1,[2]), E.TEN(1,[2])],
        index= [],
        body=E.Sum([(E. V 0,0,1),(E.V 1,0,1)],
        E.Prod[ E.Eps2(0, 1), E.Tensor(0, [E.V 0]),  E.Tensor(1, [E.V 1]) ])
        }

        
    (* Identiy: <\delta_{i j}>_{i j}  *)
    fun identity dim =E.EIN{
        params = [],
        index = [dim,dim],
        body = E.Delta(E.V(0), E.V(1))
    }
            
    (*Tensor and Fields*)
    fun addTenField dim = E.EIN{
        params = [E.TEN(1,[]),E.FLD(dim)],
        index = [],
        body = E.Add[E.Lift(E.Tensor(0, [])),E.Field(1, [])]
    }
        
    fun subTenField dim = E.EIN{
        params = [E.TEN(1,[]),E.FLD(dim)],
        index = [],
        body = E.Add[E.Lift(E.Tensor(0, [])),E.Neg(E.Field(1, []))]
    }
    
    fun subFieldTen dim = E.EIN{
        params = [E.TEN(1,[]),E.FLD(dim)],
        index = [],
        body = E.Sub(E.Field(1, []),E.Lift(E.Tensor(0, [])))
    }
    
    (* mkField functions*)
    (*Adding Fields : < F{\alpha} + G_{\alpha}>_{\alpha} *)
    fun addField(dim,shape) =let
        val expindex= specialize(shape,0)
        in E.EIN{
            params = [E.FLD(dim),E.FLD(dim)],
            index = shape,
            body = E.Add[E.Field(0, expindex),E.Field(1, expindex)]
        }
        end
        
    fun subField(dim,shape) =let
        val expindex= specialize(shape,0)
        in E.EIN{
            params = [E.FLD(dim),E.FLD(dim)],
            index = shape,
            body = E.Sub(E.Field(0, expindex),E.Field(1, expindex))
        }
        end
    
    fun scaleField(dim,shape) =let
        val  expindex= specialize(shape,0)
        in E.EIN{
            params = [E.TEN(1,[]),E.FLD(dim)],
            index = shape,
            body = E.Prod[E.Lift( E.Tensor(0,[])), E.Field(1,expindex)]
        }
        end
    
    fun divideField(dim,shape) = let
        val expindex= specialize(shape,0)
        in E.EIN{
            params = [E.FLD(dim),E.TEN(1,[])],
            index = shape,
            body = E.Div(E.Field(0, expindex),E.Lift(  E.Tensor(1, [])))
        }
        end
         
    fun negField(dim,shape) = let
        val expindex = specialize(shape,0)
        in E.EIN{
            params = [E.FLD(dim)],
            index = shape,
            body = E.Neg(E.Field(0, expindex))
        }
        end

    (*< d F /  d_i>_i  *)
        fun grad alpha=let
        val a=List.hd(alpha)
        val  expindex= specialize(alpha,0)
        in E.EIN{
            params = [E.FLD(a)],
            index =alpha,
            body = E.Apply(E.Partial(expindex),E.Field(0,[]))
        }
        end
        
        (*< Sigma d F_alpha /  d x_i>ALpha  i CHANGE HERE *)
        fun dotimes(dim,alpha)= let
             val n=length(alpha)
             fun expIndex(n,inc)=List.tabulate(n, (fn(x)=>E.V (x+inc)))
             val i'=expIndex(n,0)
        in E.EIN{
            params = [E.FLD(dim)], index =alpha@[dim],
            body = E.Apply(E.Partial [E.V n] ,E.Field(0,i'))
        }
        end
        
            (*  <d F_i /d_i> *)
        
        fun divergence(dim,alpha)=let        
            val  expindex= specialize(alpha,0)
            val sumI=length(alpha)
            val sumIndex=E.V(sumI)
            val sumIndexL=[sumIndex]
            val S=expindex@sumIndexL
       
        in E.EIN{
            params = [E.FLD(dim)],
            index = alpha,
            body = E.Sum([(sumIndex,0,dim-1)],E.Apply(E.Partial(sumIndexL),E.Field(0,S)))
        }
        end
        
    (*FLD here is bounded to image field, and dimension of h*)
    fun conv(dim,shape) =let
        val expindex= specialize(shape,0)
        in E.EIN{
            params = [E.IMG(dim,shape),E.KRN],
            index = shape,
            body= E.Conv(0,expindex,1,[])
        }
        end

    (* Probe: <F(x)>_{\alpha}   *)
    fun probe(alpha,dim) = let
        val  expindex= specialize(alpha,0)
 
        in E.EIN{
            params = [E.FLD(dim),E.TEN(0,[])],
            index= alpha,
            body= E.Probe(E.Field(0, expindex), E.Tensor(1,[]))
        }
        end

    (*(F_y/dx - F_x/dy )k*)
    (*val curl2d=E.EIN{
        params = [E.FLD 2],
        index = [],
        body = E.Sub(E.Apply(E.Partial([E.C 0]), E.Field(0,[E.C 1])),
                     E.Apply(E.Partial([E.C 1]), E.Field(0,[E.C 0])))
    }*)
        
    (*\EinExp{\sum_{ij}\mathcal{E}_{ij} \frac{ F_j}{\partial x_i}*)
        val curl2d=E.EIN{
        params = [E.FLD 2],
        index = [],
        body = E.Sum([(E.V 0,0,1), (E.V 1,0,1)],
                E.Prod[E.Eps2(0, 1),
                E.Apply( E.Partial([E.V 0]), E.Field(0,[E.V 1]))])

        }
        
    val curl3d=E.EIN{
        params = [E.TEN(1,[3])],
        index = [3],
        body = E.Sum([(E.V 1,0,2), (E.V 2,0,2)],E.Prod[E.Epsilon(0, 1, 2),E.Apply( E.Partial([E.V 1]), E.Field(0,[E.V 2]))])
    }
    
    (*Scalars*)
    (* Add Scalars*)
    val addScalar = E.EIN{
        params = [E.TEN(1,[]), E.TEN(1,[])] ,
        index = [],
        body = E.Add[ E.Tensor(0, []), E.Tensor(1, [])]
    }
        
    (* Subtract Scalars*)
    val subScalar = E.EIN{
        params = [E.TEN(1,[]), E.TEN(1,[])],
        index = [],
        body = E.Sub( E.Tensor(0, []), E.Tensor(1, []))
    }

    (* Divide Scalars*)
    val divScalar = E.EIN{
        params = [E.TEN(1,[]), E.TEN(1,[])],
        index = [],
        body = E.Div( E.Tensor(0, []), E.Tensor(1, []))
    }
        
        
    (* Product Scalars*)
    val prodScalar = E.EIN{
        params =[E.TEN(1,[]), E.TEN(1,[])],
        index = [],
        body = E.Prod[ E.Tensor(0, []), E.Tensor(1, [])]
    }
        
    (*Transform M_ij x_j+T*)
    fun transform(i, j) = E.EIN{
        params = [E.TEN(1,[i,j]), E.TEN(1,[j]), E.TEN(1,[j])],
        index = [i],
        body = E.Add
            [E.Sum([(E.V 1, 0,j-1)],E.Prod[E.Tensor(0, [E.V 0, E.V 1]), E.Tensor(1, [E.V 1])]),
              E.Tensor(2,[E.V 0])]
        }

 
    fun transformA(i, j) = E.EIN{
        params = [E.TEN(1,[i,j]), E.TEN(1,[j])],
        index = [i],
        body = E.Sum([(E.V 1, 0,j-1)],E.Prod[E.Tensor(0, [E.V 0, E.V 1]), E.Tensor(1, [E.V 1])])
        }

        
    fun transformB i = E.EIN{
        params = [E.TEN(1,[i]), E.TEN(1,[i])],
        index = [i],
        body = E.Add[E.Tensor(0, [E.V 0]), E.Tensor(1,[E.V 0])]
    }

        
        
     (*New OPs*)
    fun mulFieldss dim = E.EIN{
        params = [E.FLD(dim),E.FLD(dim)],
        index = [],
        body = E.Prod[E.Field(0, []),E.Field(1, [])]
    }
        
    fun mulFieldsf(dim,shape) =let
        val  expindex= specialize(shape,0)
        in E.EIN{
        params = [E.FLD(dim),E.FLD(dim)],
        index = shape,
        body = E.Prod[E.Field(0, []),E.Field(1, expindex)]
        }
        end
        
    fun divFieldss dim = E.EIN{
        params = [E.FLD(dim),E.FLD(dim)],
        index = [],
        body = E.Div(E.Field(0, []),E.Field(1, []))
        }
        
        
    (*Assumes same dimension vector field *)
    fun outerField dim =
        E.EIN{
            params = [E.FLD(dim),E.FLD(dim)],
            index = [dim, dim],
            body = E.Prod[E.Field(0, [E.V 0]),E.Field(1, [E.V 1])]
        }
        
        fun fs x=Int.toString(x)
        fun f x=fs(length(x))
        
     (* generic inner product: <T_{\alpha i} * T_{i \beta}>_{\alpha \beta} *)
       
    fun innerProductField(shape1,dim,i::beta) = let
        val alpha= List.take(shape1,length(shape1)-1)
        val expindexA= specialize(alpha,0)
        val expindexB= specialize(beta,(length(alpha)))
        val s'=E.V(length(alpha)+ length(beta))
        val s''=[(s',0,i-1)]
        
        val _=print(String.concat["Inner product Field. ",f(alpha)])
        in E.EIN{
            params = [E.FLD(dim) ,E.FLD(dim)],              (* T and T' *)
            index = alpha@beta,(* \alpha \beta, i *)
            body = E.Sum(s'', E.Prod[
                E.Field(0, expindexA@[s']),   (* F_{\alpha i} *)
                E.Field(1, [s']@expindexB )  (* F'_{i \beta} *)
            ])}
        end
    | innerProductField _ = raise Fail "Wrong shape for innerProductField"
            
    (*Field Cross Product*)
         val crossProductField = E.EIN{
            params = [E.FLD(3), E.FLD(3)],
            index= [3],
            body=E.Sum([(E. V 1,0,2),(E.V 2,0,2)],
            E.Prod[ E.Epsilon(0, 1, 2), E.Field(0, [E.V 1]),  E.Field(1, [E.V 2 ]) ])
         }         
         
    (* Trace: <Sigma_i F_{\alpha i, i}>  This one Sx represents both i's*)
        fun traceField(dim,alpha) =let
            val expindex= specialize(alpha,0)
            val s=E.V(length(alpha))
            in
            E.EIN{
             params = [E.FLD(dim)],         
             index = alpha,
             body = E.Sum([(s,0,dim-1)],E.Field(0, expindex@[s,s]))
             }
            end
    
    (*Transpose Field F_{ji}*)
    fun transposeField(dim,i,j) =E.EIN{
        params = [E.FLD(dim)], index= [i,j],
        body= E.Field(0, [E.V 1,E.V 0])
        }
        
    (*<F_{\alpha i j} * G{i j \beta }>_\alpha \beta*)
    fun doubleDotField(shape1,i::j::beta) = let
        val alpha= List.take(shape1,length(shape1)-2)
        val expindexA= specialize(alpha,0)
        val expindexB= specialize(beta,(length(alpha)))
        val sumi=length(alpha)+ length(beta)
        val s'=[E.V sumi,E.V(sumi+1)]
        val s''=[(E.V sumi,0,i-1),(E.V(sumi+1),0,j-1)]
        in
            E.EIN{
                params = [E.TEN(1,shape1),E.TEN(1,i::j::beta)],
                index = alpha@beta,
                body = E.Sum(s'',E.Prod[E.Field(0, expindexA@s'), E.Field(1,s'@expindexB)])
            }
        end
    | doubleDotField _ = raise Fail "Wrong shape for double dot "
            

  end; (* local *)

    end (* local *)

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