Edit detail for SandBoxLinearOperator revision 4 of 15

(1) -> )lib CARTEN MONAL PROP LIN

   )library cannot find the file LIN.
   CartesianTensor is now explicitly exposed in frame initial 
   CartesianTensor will be automatically loaded when needed from 
      /var/aw/var/LatexWiki/CARTEN.NRLIB/CARTEN
   Monoidal is now explicitly exposed in frame initial 
   Monoidal will be automatically loaded when needed from 
      /var/aw/var/LatexWiki/MONAL.NRLIB/MONAL
   Prop is now explicitly exposed in frame initial 
   Prop will be automatically loaded when needed from 
      /var/aw/var/LatexWiki/PROP.NRLIB/PROP

)abbrev domain LAZY LazyLinearOperator
LazyLinearOperator(dim:NNI,gener:OrderedFinite,K:CommutativeRing): Exports == Implementation where
  NNI ==> NonNegativeInteger
  NAT ==> PositiveInteger
  T ==> CartesianTensor(1,dim,K)

  Exports ==> Join(Ring, BiModule(K,K), Monoidal NNI, RetractableTo K) with
    inp: List K -> %
      ++ incoming vector
    inp: List % -> %
    out: List K -> %
      ++ output vector
    out: List % -> %
    arity: % -> Prop %
    basisVectors: () -> List %
    basisForms: () -> List %
    tensor: % -> T
    map: (K->K,%) -> %
    if K has Evalable(K) then Evalable(K)
    eval: % -> %
    ravel: % -> List K
    unravel: (Prop %,List K) -> %
    coerce:(x:List NAT) -> %
      ++ identity for composition and permutations of its products
    coerce:(x:List None) -> %
      ++ [] = 1
    elt: (%,%) -> %
    elt: (%,NAT) -> %
    elt: (%,NAT,NAT) -> %
    elt: (%,NAT,NAT,NAT) -> %
    _/: (Tuple %,Tuple %) -> %
    _/: (Tuple %,%) -> %
    _/: (%,Tuple %) -> %
      ++ yet another syntax for product
    ev: NAT -> %
      ++ (2,0)-tensor for evaluation
    co: NAT -> %
      ++ (0,2)-tensor for co-evaluation

  Implementation ==> add
    import List NNI
    import NAT
    L ==> Record(domain:NNI, codomain:NNI, data:T)
    -- FreeMonoid provides unevaluated products
    Rep == FreeMonoid L
    RR ==> Record(gen:L,exp:NNI)
    rep(x:%):Rep == x pretend Rep
    per(x:Rep):% == x pretend %

    -- Prop (arity)
    dom(f:%):NNI ==
      r:NNI := 0
      for y in factors(rep f) repeat
        r:=r+(y.gen.domain)*(y.exp)
      return r
    cod(f:%):NNI ==
      r:NNI := 0
      for y in factors(rep f) repeat
        r:=r+(y.gen.codomain)*(y.exp)
      return r

    prod(f:L,g:L):L ==
      r:T := product(f.data,g.data)
      -- dom(f) + cod(f) + dom(g) + cod(g)
      p:List Integer := concat                _
        [[i for i in 1..(f.domain)],              _
        [(f.domain)+(f.codomain)+i for i in 1..(g.domain)], _
        [(f.domain)+i for i in 1..(f.codomain)],        _
        [(f.domain)+(g.domain)+(f.codomain)+i for i in 1..(g.codomain)]]
        -- dom(f) + dom(g) + cod(f) + cod(g)
      [(f.domain)+(g.domain),(f.codomain)+(g.codomain),reindex(r,p)]

    dats(fs:List RR):L ==
      r:L := [0,0,1$T]
      for y in fs repeat
        t:L:=y.gen
        for n in 1..y.exp repeat
          r:=prod(r,t)
      return r

    dat(f:%):L == dats factors rep f

    arity(f:%):Prop % == f::Prop %

    eval(f:%):% == per coerce dat(f)

    retractIfCan(f:%):Union(K,"failed") ==
      dom(f)=0 and cod(f)=0 => retract(dat(f).data)$T
      return "failed"
    retract(f:%):K ==
      dom(f)=0 and cod(f)=0 => retract(dat(f).data)$T
      error "failed"

    -- basis
    basisVectors():List % == [per coerce [0,1,entries(row(1,i)$SquareMatrix(dim,K))::T] for i in 1..dim]
    basisForms():List % == [per coerce [1,0,entries(row(1,i)$SquareMatrix(dim,K))::T] for i in 1..dim]
    ev(n:NAT):% ==
      dx:= basisForms()
      reduce(_+,[ (dx.i)^n * (dx.i)^n for i in 1..dim])
    co(n:NAT):% == 
      Dx:= basisVectors()
      reduce(_+,[ (Dx.i)^n * (Dx.i)^n for i in 1..dim])

    -- manipulation
    map(f:K->K, g:%):% == per coerce [dom g,cod g,unravel(map(f,ravel dat(g).data))$T]
    if K has Evalable(K) then
      eval(g:%,f:List Equation K):% == map((x:K):K+->eval(x,f),g)
    ravel(g:%):List K == ravel dat(g).data
    unravel(p:Prop %,r:List K):% ==
      dim^(dom(p)+cod(p)) ~= #r => error "failed"
      per coerce [dom(p),cod(p),unravel(r)$T]
    tensor(x:%):T == dat(x).data

    -- sum
    (f:% + g:%):% ==
      dat(f).data=0 => g
      dat(g).data=0 => f
      dom(f) ~= dom(g) or cod(f) ~= cod(g) => error "arity"
      per coerce [dom f,cod f,dat(f).data+dat(g).data]

    (f:% - g:%):% ==
      dat(f).data=0 => g
      dat(g).data=0 => f
      dom(f) ~= dom(f) or cod(g) ~= cod(g) => error "arity"
      per coerce [dom f, cod f,dat(f).data-dat(g).data]

    _-(f:%):% == per coerce [dom f, cod f,-dat(f).data]

    -- repeated sum
    (p:NNI * f:%):% ==
      p=1 => f
      q:=subtractIfCan(p,1)
      q case NNI => q*f + f
      -- zero map (non-trivial)
      per coerce [dom f,cod f,0*dat(f).data]

    -- identity for sum (trivial zero map)
    0 == per coerce [0,0,0]
    zero?(f:%):Boolean == dat(f).data = 0 * dat(f).data
    -- identity for product
    1:% == per coerce [0,0,1]
    one?(f:%):Boolean == dat(f).data = 1$T
    -- identity for composition
    I == per coerce [1,1,kroneckerDelta()$T]
    (x:% = y:%):Boolean == zero? (x - y)

    -- permutations and identities
    coerce(p:List NAT):% ==
      r:=I^#p
      #p = 1 and p.1 = 1 => return r
      p1:List Integer:=[i for i in 1..#p]
      p2:List Integer:=[#p+i for i in p]
      p3:=concat(p1,p2)
      per coerce [#p,#p,reindex(dat(r).data,p3)]
    coerce(p:List None):% == per coerce [0,0,1]
    coerce(x:K):% == 1*x

    -- product
    elt(f:%,g:%):% == f * g
    elt(f:%,g:NAT):% == f * I^g
    elt(f:%,g1:NAT,g2:NAT):% == f * [g1 @ NAT,g2 @ NAT]::List NAT::%
    elt(f:%,g1:NAT,g2:NAT,g3:NAT):% == f * [g1 @ NAT,g2 @ NAT,g3 @ NAT]::List NAT::%
    apply(f:%,g:%):% == f * g
    (f:% * g:%):% == per(rep f * rep g)

    -- repeated product
    (f:% ^ p:NNI):% ==
      p=1 => f
      q:=subtractIfCan(p,1)
      q case NNI => f^q * f
      1

    -- composition:
    -- f/g : A^n -> A^p = f:A^n -> A^m / g:A^m -> A^p
    (ff:% / gg:%):% ==
      g:=gg; f:=ff
      -- partial application from the left
      n:=subtractIfCan(cod ff,dom gg)
      if n case NNI and n>0 then
      -- apply g on f from the left, pass extra f outputs on the right
        print(hconcat([message("arity warning: "), _
              over(arity(ff)::OutputForm, _
                   arity(gg)::OutputForm*(arity(I)::OutputForm)^n::OutputForm) ]))$OutputForm
        g:=gg*I^n
      m:=subtractIfCan(dom gg, cod ff)
      --  apply g on f from the left, add extra g inputs on the left
      if m case NNI and m>0 then
        print(hconcat([message("arity warning: "), _
              over((arity(I)::OutputForm)^m::OutputForm*arity(ff)::OutputForm, _
                   arity(gg)::OutputForm)]))$OutputForm
        f:=I^m*ff

      -- optimize leading and trailing identities
      I1:L:=[1,1,kroneckerDelta()$T]
      fs:=factors rep f
      gs:=factors rep g

      l1:NNI:=0
      nf := first(fs).exp
      ng := first(gs).exp
      if first(fs).gen=I1 then
        if first(gs).gen=I1 then
          if nf < ng then
            l1 := nf
            ng := (ng - nf) pretend NNI
            nf := 0
          else
            l1 := ng
            nf := (nf - ng) pretend NNI
            ng := 0
        else
          ng := 0
      else
        nf := 0
      if not first(gs).gen=I1 then
        ng := 0

      if nf>0 and ng>0 then error "either nf or ng or both must be 0"
      print(bracket [nf::OutputForm,ng::OutputForm])$OutputForm

      t1:NNI:=0
      fn := last(fs).exp
      gn := last(gs).exp
      if last(fs).gen=I1 then
        if last(gs).gen=I1 then
          if fn < gn then
            t1 := fn
            gn := (gn - fn) pretend NNI
            fn := 0
          else
            t1 := gn
            fn := (fn - gn) pretend NNI
            gn := 0
        else
          gn := 0
      else
        fn := 0
      if not last(gs).gen=I1 then
        gn := 0

      if fn>0 and fn>0 then error "either fn or gn or both must be 0"
      print(bracket [fn::OutputForm,gn::OutputForm])$OutputForm

      print(bracket [l1::OutputForm,t1::OutputForm])$OutputForm

      -- debugging defeat optimizations
      nf:=0; ng:=0
      fn:=0; gn:=0
      --l1:=0; t1:=0

      if l1 > 0 then
        first(fs).exp := nf 
        first(gs).exp := ng
      if t1>0 then
        last(fs).exp := fn
        last(gs).exp := gn

      if nf>0 then
        -- leading input identities (I^n*f)/g
        fs := last(fs,(#fs-1) pretend NNI)
      if ng>0 then
        -- leading output identities g/(I^n*g)
        gs := last(gs,(#gs-1) pretend NNI)
      if fn>0 then
        -- trailing input identities (f*I^n)/g
        fs := first(fs,(#fs-1) pretend NNI)
      if gn>0 then
        -- trailing output identities f/(g*I^n)
        gs := first(gs,(#gs-1) pretend NNI)

      f := per coerce dats(fs)
      g := per coerce dats(gs)

      if nf=0 and ng=0 then
        if fn=0 and gn=0 then
          -- no leading or trailing input or output
          f1:Integer:=dom(f)+1
          r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
        else if fn>0 then
          -- trailing input 
          f1:Integer:=dom(f)+1
          r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
        else
          -- tailing output
          f1:Integer:=dom(f)+1
          r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
      else
        if nf>0 then
          if fn=0 and gn=0 then
            -- leading input
            f1:Integer:=dom(f)+1
            r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
          else if fn>0 then
            -- leading input and trailing input
            f1:Integer:=dom(f)+1
            r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
          else
            -- leading input trailing output
            f1:Integer:=dom(f)+1
            r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
        else
          if fn=0 and gn=0 then
            -- leading output
            f1:Integer:=dom(f)+1
            r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
          else if fn>0 then
            -- leading output and trailing input
            f1:Integer:=dom(f)+1
            r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)
          else
            -- leading output and trailing output
            f1:Integer:=dom(f)+1
            r:T := contract(cod(f), dat(f).data,f1, dat(g).data,1)

      I^l1 * per coerce [dom(f),cod(g),r] * I^t1

    -- another notation for composition of products
    (t:Tuple % / x:%):% == t / construct([x])$PrimitiveArray(%)::Tuple(%)
    (x:% / t:Tuple %):% == construct([x])$PrimitiveArray(%)::Tuple(%) / t
    (f:Tuple % / g:Tuple %):% ==
      fs:List % := [select(f,i) for i in 0..length(f)-1]
      gs:List % := [select(g,i) for i in 0..length(g)-1]
      fr:=reduce(elt@(%,%)->%,fs,1)
      gr:=reduce(elt@(%,%)->%,gs,1)
      fr / gr

    (x:K * y:%):% == per coerce [dom y, cod y,x*dat(y).data]
    (x:% * y:K):% == per coerce [dom x,cod x,dat(x).data*y]
    (x:Integer * y:%):% == per coerce [dom y,cod y,x*dat(y).data]

    -- constructors
    inp(x:List K):% == per coerce [1,0,entries(x)::T]
    inp(x:List %):% ==
      #removeDuplicates([dom(y) for y in x]) ~= 1 or
        #removeDuplicates([cod(y) for y in x]) ~= 1 => error "arity"
      per coerce [dom(first x)+1, cod(first x), [dat(y).data for y in x]::T]$L
    out(x:List K):% == per coerce [0,1,entries(x)::T]
    out(x:List %):% ==
      #removeDuplicates([dom(y) for y in x])~=1 or
        #removeDuplicates([cod(y) for y in x])~=1 => error "arity"
      per coerce [dom(first x), cod(first x)+1, [dat(y).data for y in x]::T]$L

    -- display operators using basis
    show(x:%):OutputForm ==
      dom(x)=0 and cod(x)=0 => return (dat(x).data)::OutputForm
      if size()$gener > 0 then
        gens:List OutputForm:=[index(i::PositiveInteger)$gener::OutputForm for i in 1..dim]
      else
        -- default to numeric indices
        gens:List OutputForm:=[i::OutputForm for i in 1..dim]
      -- input basis
      inps:List OutputForm := []
      for i in 1..dom(x) repeat
        empty? inps => inps:=gens
        inps:=concat [[(inps.k * gens.j) for j in 1..dim] for k in 1..#inps]
      -- output basis
      outs:List OutputForm := []
      for i in 1..cod(x) repeat
        empty? outs => outs:=gens
        outs:=concat [[(outs.k * gens.j) for j in 1..dim] for k in 1..#outs]
      -- combine input (superscripts) and/or output(subscripts) to form basis symbols
      bases:List OutputForm
      if #inps > 0 and #outs > 0 then
        bases:=concat([[ scripts(message("|"),[i,j]) for i in outs] for j in inps])
      else if #inps > 0 then
        bases:=[super(message("|"),i) for i in inps]
      else if #outs > 0 then
        bases:=[sub(message("|"),j) for j in outs]
      else
        bases:List OutputForm:= []
      -- merge bases with data to form term list
      terms:=[(k=1 => base;k::OutputForm*base)
        for base in bases for k in ravel dat(x).data | k~=0]
      empty? terms => return 0::OutputForm
      -- combine the terms
      return reduce(_+,terms)

    coerce(x:%):OutputForm ==
      r:OutputForm := empty()
      for y in factors(rep x) repeat
        if y.exp = 1 then
          if size rep x = 1 then
            r := show per coerce y.gen
          else
            r:=r*paren(list show per coerce y.gen)
        else
          r:=r*paren(list show per coerce y.gen)^(y.exp::OutputForm)
      return r

   Compiling FriCAS source code from file 
      /var/lib/zope2.10/instance/axiom-wiki/var/LatexWiki/3672196540805373868-25px002.spad
      using old system compiler.
   LAZY abbreviates domain LazyLinearOperator 
------------------------------------------------------------------------
   initializing NRLIB LAZY for LazyLinearOperator 
   compiling into NRLIB LAZY 
   importing List NonNegativeInteger
   importing PositiveInteger
   processing macro definition L ==> Record(domain: NonNegativeInteger,codomain: NonNegativeInteger,data: CartesianTensor(One,dim,K)) 
************* USER ERROR **********
available signatures for Rep: 
    NONE
NEED Rep: () -> ?
****** comp fails at level 1 with expression: ******
((DEF (|Rep|) (NIL)
  (|FreeMonoid|
   (|Record| (|:| |domain| (|NonNegativeInteger|))
             (|:| |codomain| (|NonNegativeInteger|))
             (|:| |data| (|CartesianTensor| 1 |dim| K))))))
****** level 1  ******
x:= (DEF (Rep) (NIL) (FreeMonoid (Record (: domain (NonNegativeInteger)) (: codomain (NonNegativeInteger)) (: data (CartesianTensor (One) dim K)))))
m:= $EmptyMode
f:=
((((L #) (* #) (+ #) (< #) ...)))

   >> Apparent user error:
   unspecified error

Tests

L:=LAZY(2,OVAR [],EXPR INT)

   LazyLinearOperator is an unknown constructor and so is unavailable. 
      Did you mean to use -> but type something different instead?