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)abbrev category POLYCAT PolynomialCategory
++ Description:
++ The category for general multi-variate polynomials over a ring
++ R, in variables from VarSet, with exponents from the
++ \spadtype{OrderedAbelianMonoidSup}.

PolynomialCategory(R,E,VarSet) : Category == SIG where
  R : Ring
  E : OrderedAbelianMonoidSup
  VarSet : OrderedSet

  PDR   ==> PartialDifferentialRing(VarSet)
  FAMR  ==> FiniteAbelianMonoidRing(R, E)
  EV    ==> Evalable(%)
  IEVR  ==> InnerEvalable(VarSet, R)
  IEVP  ==> InnerEvalable(VarSet, %)
  RT    ==> RetractableTo(VarSet)
  FLERO ==> FullyLinearlyExplicitRingOver(R)

  SIG ==> Join(PDR,FAMR,EV,IEVR,IEVP,RT,FLERO) with

    degree : (%,VarSet) -> NonNegativeInteger
      ++ degree(p,v) gives the degree of polynomial p with respect 
      ++ to the variable v.

    degree : (%,List(VarSet)) -> List(NonNegativeInteger)
      ++ degree(p,lv) gives the list of degrees of polynomial p
      ++ with respect to each of the variables in the list lv.

    coefficient : (%,VarSet,NonNegativeInteger) -> %
      ++ coefficient(p,v,n) views the polynomial p as a univariate
      ++ polynomial in v and returns the coefficient of the \spad{v**n} term.

    coefficient : (%,List VarSet,List NonNegativeInteger) -> %
      ++ coefficient(p, lv, ln) views the polynomial p as a polynomial
      ++ in the variables of lv and returns the coefficient of the term
      ++ \spad{lv**ln}, \spad{prod(lv_i ** ln_i)}.

    monomials : % -> List %
      ++ monomials(p) returns the list of non-zero monomials of 
      ++ polynomial p, 
      ++ \spad{monomials(sum(a_(i) X^(i))) = [a_(1) X^(1),...,a_(n) X^(n)]}.

    univariate : (%,VarSet) -> SparseUnivariatePolynomial(%)
      ++ univariate(p,v) converts the multivariate polynomial p
      ++ into a univariate polynomial in v, whose coefficients are still
      ++ multivariate polynomials (in all the other variables).

    univariate : % -> SparseUnivariatePolynomial(R)
      ++ univariate(p) converts the multivariate polynomial p,
      ++ which should actually involve only one variable,
      ++ into a univariate polynomial
      ++ in that variable, whose coefficients are in the ground ring.
      ++ Error: if polynomial is genuinely multivariate

    mainVariable : % -> Union(VarSet,"failed")
      ++ mainVariable(p) returns the biggest variable which actually
      ++ occurs in the polynomial p, or "failed" if no variables are
      ++ present.
      ++ fails precisely if polynomial satisfies ground?

    minimumDegree : (%,VarSet) -> NonNegativeInteger
      ++ minimumDegree(p,v) gives the minimum degree of polynomial p
      ++ with respect to v, viewed a univariate polynomial in v

    minimumDegree : (%,List(VarSet)) -> List(NonNegativeInteger)
      ++ minimumDegree(p, lv) gives the list of minimum degrees of the
      ++ polynomial p with respect to each of the variables in the list lv

    monicDivide : (%,%,VarSet) -> Record(quotient:%,remainder:%)
      ++ monicDivide(a,b,v) divides the polynomial a by the polynomial b,
      ++ with each viewed as a univariate polynomial in v returning
      ++ both the quotient and remainder.
      ++ Error: if b is not monic with respect to v.

    monomial : (%,VarSet,NonNegativeInteger) -> %
      ++ monomial(a,x,n) creates the monomial \spad{a*x**n} where \spad{a} is
      ++ a polynomial, x is a variable and n is a nonnegative integer.

    monomial : (%,List VarSet,List NonNegativeInteger) -> %
      ++ monomial(a,[v1..vn],[e1..en]) returns \spad{a*prod(vi**ei)}.

    multivariate : (SparseUnivariatePolynomial(R),VarSet) -> %
      ++ multivariate(sup,v) converts an anonymous univariable
      ++ polynomial sup to a polynomial in the variable v.

    multivariate : (SparseUnivariatePolynomial(%),VarSet) -> %
      ++ multivariate(sup,v) converts an anonymous univariable
      ++ polynomial sup to a polynomial in the variable v.

    isPlus : % -> Union(List %, "failed")
      ++ isPlus(p) returns \spad{[m1,...,mn]} if polynomial 
      ++ \spad{p = m1 + ... + mn} and
      ++ \spad{n >= 2} and each mi is a nonzero monomial.

    isTimes : % -> Union(List %, "failed")
      ++ isTimes(p) returns \spad{[a1,...,an]} if polynomial 
      ++ \spad{p = a1 ... an} and \spad{n >= 2}, and, for each i, 
      ++ ai is either a nontrivial constant in R or else of the
      ++ form \spad{x**e}, where \spad{e > 0} is an integer 
      ++ and x in a member of VarSet.

    isExpt : % -> Union(Record(var:VarSet, exponent:NonNegativeInteger),_
                       "failed")
      ++ isExpt(p) returns \spad{[x, n]} if polynomial p has the 
      ++ form \spad{x**n} and \spad{n > 0}.

    totalDegree : % -> NonNegativeInteger
      ++ totalDegree(p) returns the largest sum over all monomials
      ++ of all exponents of a monomial.

    totalDegree : (%,List VarSet) -> NonNegativeInteger
      ++ totalDegree(p, lv) returns the maximum sum (over all monomials 
      ++ of polynomial p) of the variables in the list lv.

    variables : % -> List(VarSet)
      ++ variables(p) returns the list of those variables actually
      ++ appearing in the polynomial p.

    primitiveMonomials : % -> List %
      ++ primitiveMonomials(p) gives the list of monomials of the
      ++ polynomial p with their coefficients removed. Note that
      ++ \spad{primitiveMonomials(sum(a_(i) X^(i))) = [X^(1),...,X^(n)]}.

    if R has OrderedSet  then OrderedSet

    -- OrderedRing view removed to allow EXPR to define abs

    --if R has OrderedRing then OrderedRing

    if (R has ConvertibleTo InputForm) and
       (VarSet has ConvertibleTo InputForm) then
         ConvertibleTo InputForm

    if (R has ConvertibleTo Pattern Integer) and
       (VarSet has ConvertibleTo Pattern Integer) then
         ConvertibleTo Pattern Integer

    if (R has ConvertibleTo Pattern Float) and
       (VarSet has ConvertibleTo Pattern Float) then
         ConvertibleTo Pattern Float

    if (R has PatternMatchable Integer) and
       (VarSet has PatternMatchable Integer) then
         PatternMatchable Integer

    if (R has PatternMatchable Float) and
       (VarSet has PatternMatchable Float) then
         PatternMatchable Float

    if R has CommutativeRing then

      resultant : (%,%,VarSet) -> %
         ++ resultant(p,q,v) returns the resultant of the polynomials
         ++ p and q with respect to the variable v.

      discriminant : (%,VarSet) -> %
         ++ discriminant(p,v) returns the disriminant of the polynomial p
         ++ with respect to the variable v.

    if R has GcdDomain then

      GcdDomain

      content : (%,VarSet) -> %
        ++ content(p,v) is the gcd of the coefficients of the polynomial p
        ++ when p is viewed as a univariate polynomial with respect to the
        ++ variable v.
        ++ Thus, for polynomial 7*x**2*y + 14*x*y**2, the gcd of the
        ++ coefficients with respect to x is 7*y.

      primitivePart : % -> %
        ++ primitivePart(p) returns the unitCanonical associate of the
        ++ polynomial p with its content divided out.

      primitivePart : (%,VarSet) -> %
        ++ primitivePart(p,v) returns the unitCanonical associate of the
        ++ polynomial p with its content with respect to the variable v
        ++ divided out.

      squareFree : % -> Factored %
        ++ squareFree(p) returns the square free factorization of the
        ++ polynomial p.

      squareFreePart : % -> %
        ++ squareFreePart(p) returns product of all the irreducible factors
        ++ of polynomial p each taken with multiplicity one.

    -- assertions

    if R has canonicalUnitNormal then canonicalUnitNormal
             ++ we can choose a unique representative for each
             ++ associate class.
             ++ This normalization is chosen to be normalization of
             ++ leading coefficient (by default).

    if R has PolynomialFactorizationExplicit then

       PolynomialFactorizationExplicit

   add

     p:%
     v:VarSet
     ln:List NonNegativeInteger
     lv:List VarSet
     n:NonNegativeInteger
     pp,qq:SparseUnivariatePolynomial %
 
     eval(p:%, l:List Equation %) ==
       empty? l => p
       for e in l repeat
         retractIfCan(lhs e)@Union(VarSet,"failed") case "failed" => 
              error "cannot find a variable to evaluate"
       lvar:=[retract(lhs e)@VarSet for e in l]
       eval(p, lvar,[rhs e for e in l]$List(%))
 
     monomials p ==
       ml:= empty$List(%)
       while p ^= 0 repeat
         ml:=concat(leadingMonomial p, ml)
         p:= reductum p
       reverse ml
 
     isPlus p ==
       empty? rest(l := monomials p) => "failed"
       l
 
     isTimes p ==
       empty?(lv := variables p) or not monomial? p => "failed"
       l := [monomial(1, v, degree(p, v)) for v in lv]
       ((r := leadingCoefficient p) = 1) =>
         empty? rest lv => "failed"
         l
       concat(r::%, l)
 
     isExpt p ==
       (u := mainVariable p) case "failed" => "failed"
       p = monomial(1, u::VarSet, d := degree(p, u::VarSet)) =>
         [u::VarSet, d]
       "failed"
 
     coefficient(p,v,n) == coefficient(univariate(p,v),n)
 
     coefficient(p,lv,ln) ==
        empty? lv =>
          empty? ln => p
          error "mismatched lists in coefficient"
        empty? ln  => error "mismatched lists in coefficient"
        coefficient(coefficient(univariate(p,first lv),first ln),
                    rest lv,rest ln)
 
     monomial(p,lv,ln) ==
        empty? lv =>
          empty? ln => p
          error "mismatched lists in monomial"
        empty? ln  => error "mismatched lists in monomial"
        monomial(monomial(p,first lv, first ln),rest lv, rest ln)
 
     retract(p:%):VarSet ==
       q := mainVariable(p)::VarSet
       q::% = p => q
       error "Polynomial is not a single variable"
 
     retractIfCan(p:%):Union(VarSet, "failed") ==
       ((q := mainVariable p) case VarSet) and (q::VarSet::% = p) => q
       "failed"
 
     mkPrim(p:%):% == monomial(1,degree p)
 
     primitiveMonomials p == [mkPrim q for q in monomials p]
 
     totalDegree p ==
         ground? p => 0
         u := univariate(p, mainVariable(p)::VarSet)
         d: NonNegativeInteger := 0
         while u ^= 0 repeat
           d := max(d, degree u + totalDegree leadingCoefficient u)
           u := reductum u
         d
 
     totalDegree(p,lv) ==
         ground? p => 0
         u := univariate(p, v:=(mainVariable(p)::VarSet))
         d: NonNegativeInteger := 0
         w: NonNegativeInteger := 0
         if member?(v, lv) then w:=1
         while u ^= 0 repeat
           d := max(d, w*(degree u) + totalDegree(leadingCoefficient u,lv))
           u := reductum u
         d
 
     if R has CommutativeRing then

         resultant(p1,p2,mvar) ==
           resultant(univariate(p1,mvar),univariate(p2,mvar))
 
         discriminant(p,var) ==
           discriminant(univariate(p,var))
 
     if R has IntegralDomain then

       allMonoms(l:List %):List(%) ==
         removeDuplicates_! concat [primitiveMonomials p for p in l]
 
       P2R(p:%, b:List E, n:NonNegativeInteger):Vector(R) ==
         w := new(n, 0)$Vector(R)
         for i in minIndex w .. maxIndex w for bj in b repeat
           qsetelt_!(w, i, coefficient(p, bj))
         w
 
       eq2R(l:List %, b:List E):Matrix(R) ==
         matrix [[coefficient(p, bj) for p in l] for bj in b]
 
       reducedSystem(m:Matrix %):Matrix(R) ==
         l := listOfLists m
         b := removeDuplicates_!
                            concat [allMonoms r for r in l]$List(List(%))
         d := [degree bj for bj in b]
         mm := eq2R(first l, d)
         l := rest l
         while not empty? l repeat
           mm := vertConcat(mm, eq2R(first l, d))
           l := rest l
         mm
 
       reducedSystem(m:Matrix %, v:Vector %):
        Record(mat:Matrix R, vec:Vector R) ==
         l := listOfLists m
         r := entries v
         b : List % := removeDuplicates_! concat(allMonoms r,
                           concat [allMonoms s for s in l]$List(List(%)))
         d := [degree bj for bj in b]
         n := #d
         mm := eq2R(first l, d)
         w := P2R(first r, d, n)
         l := rest l
         r := rest r
         while not empty? l repeat
           mm := vertConcat(mm, eq2R(first l, d))
           w := concat(w, P2R(first r, d, n))
           l := rest l
           r := rest r
         [mm, w]
 
     if R has PolynomialFactorizationExplicit then
       -- we might be in trouble if its actually only
       -- a univariate polynomial category - have to remember to
       -- over-ride these in UnivariatePolynomialCategory

       PFBR ==>PolynomialFactorizationByRecursion(R,E,VarSet,%)

       gcdPolynomial(pp,qq) ==
          gcdPolynomial(pp,qq)$GeneralPolynomialGcdPackage(E,VarSet,R,%)

       solveLinearPolynomialEquation(lpp,pp) ==
         solveLinearPolynomialEquationByRecursion(lpp,pp)$PFBR

       factorPolynomial(pp) ==
         factorByRecursion(pp)$PFBR

       factorSquareFreePolynomial(pp) ==
         factorSquareFreeByRecursion(pp)$PFBR

       factor p ==
         v:Union(VarSet,"failed"):=mainVariable p
         v case "failed" =>
           ansR:=factor leadingCoefficient p
           makeFR(unit(ansR)::%,
                  [[w.flg,w.fctr::%,w.xpnt] for w in factorList ansR])
         up:SparseUnivariatePolynomial %:=univariate(p,v)
         ansSUP:=factorByRecursion(up)$PFBR
         makeFR(multivariate(unit(ansSUP),v),
                [[ww.flg,multivariate(ww.fctr,v),ww.xpnt]
                 for ww in factorList ansSUP])

       if R has CharacteristicNonZero then

          mat: Matrix %

          conditionP mat ==
            ll:=listOfLists transpose mat  --hence each list corresponds to a
                                           --column, to one variable
            llR:List List R := [ empty() for z in first ll]
            monslist:List List % := empty()
            ch:=characteristic()$%
            for l in ll repeat
                mons:= "setUnion"/[primitiveMonomials u for u in l]
                redmons:List % :=[]
                for m in mons repeat
                    vars:=variables m
                    degs:=degree(m,vars)
                    deg1:List NonNegativeInteger
                    deg1:=[ ((nd:=d:Integer exquo ch:Integer)
                               case "failed" => return "failed" ;
                                nd::Integer::NonNegativeInteger)
                           for d in degs ]
                    redmons:=[monomial(1,vars,deg1),:redmons]
                    llR:=[[ground coefficient(u,vars,degs),:v]_
                            for u in l for v in llR]
                monslist:=[redmons,:monslist]
            ans:=conditionP transpose matrix llR
            ans case "failed" => "failed"
            i:NonNegativeInteger:=0
            [ +/[m*(ans.(i:=i+1))::% for m in mons ]
              for mons in monslist]

     if R has CharacteristicNonZero then

          charthRootlv:(%,List VarSet,NonNegativeInteger) ->
                                                Union(%,"failed")
          charthRoot p ==
            vars:= variables p
            empty? vars =>
              ans := charthRoot ground p
              ans case "failed" => "failed"
              ans::R::%
            ch:=characteristic()$%
            charthRootlv(p,vars,ch)

          charthRootlv(p,vars,ch) ==
            empty? vars =>
              ans := charthRoot ground p
              ans case "failed" => "failed"
              ans::R::%
            v:=first vars
            vars:=rest vars
            d:=degree(p,v)
            ans:% := 0
            while (d>0) repeat
               (dd:=(d::Integer exquo ch::Integer)) case "failed" =>
                      return "failed"
               cp:=coefficient(p,v,d)
               p:=p-monomial(cp,v,d)
               ansx:=charthRootlv(cp,vars,ch)
               ansx case "failed" => return "failed"
               d:=degree(p,v)
               ans:=ans+monomial(ansx,v,dd::Integer::NonNegativeInteger)
            ansx:=charthRootlv(p,vars,ch)
            ansx case "failed" => return "failed"
            return ans+ansx

     monicDivide(p1,p2,mvar) ==
       result:=monicDivide(univariate(p1,mvar),univariate(p2,mvar))
       [multivariate(result.quotient,mvar),
        multivariate(result.remainder,mvar)]

     if R has GcdDomain then

       if R has EuclideanDomain and R has CharacteristicZero then

         squareFree p == squareFree(p)$MultivariateSquareFree(E,VarSet,R,%)

       else

         squareFree p == squareFree(p)$PolynomialSquareFree(VarSet,E,R,%)

       squareFreePart p ==
         unit(s := squareFree p) * */[f.factor for f in factors s]

       content(p,v) == content univariate(p,v)

       primitivePart p ==
         zero? p => p
         unitNormal((p exquo content p) ::%).canonical
 
       primitivePart(p,v) ==
         zero? p => p
         unitNormal((p exquo content(p,v)) ::%).canonical
 
     if R has OrderedSet then

       p:% < q:% ==
         (dp:= degree p) < (dq := degree q) => (leadingCoefficient q) > 0
         dq < dp => (leadingCoefficient p) < 0
         leadingCoefficient(p - q) < 0
 
       if (R has PatternMatchable Integer) and
          (VarSet has PatternMatchable Integer) then

            patternMatch(p:%, pat:Pattern Integer,
             l:PatternMatchResult(Integer, %)) ==
               patternMatch(p, pat,
                 l)$PatternMatchPolynomialCategory(Integer,E,VarSet,R,%)
 
       if (R has PatternMatchable Float) and
          (VarSet has PatternMatchable Float) then

            patternMatch(p:%, pat:Pattern Float,
             l:PatternMatchResult(Float, %)) ==
               patternMatch(p, pat,
                 l)$PatternMatchPolynomialCategory(Float,E,VarSet,R,%)
 
     if (R has ConvertibleTo Pattern Integer) and
        (VarSet has ConvertibleTo Pattern Integer) then

          convert(x:%):Pattern(Integer) ==
            map(convert, convert,
               x)$PolynomialCategoryLifting(E,VarSet,R,%,Pattern Integer)
 
     if (R has ConvertibleTo Pattern Float) and
        (VarSet has ConvertibleTo Pattern Float) then

          convert(x:%):Pattern(Float) ==
            map(convert, convert,
             x)$PolynomialCategoryLifting(E, VarSet, R, %, Pattern Float)
 
     if (R has ConvertibleTo InputForm) and
        (VarSet has ConvertibleTo InputForm) then

          convert(p:%):InputForm ==
            map(convert, convert,
                     p)$PolynomialCategoryLifting(E,VarSet,R,%,InputForm)