source: git/Singular/LIB/solve.lib @ b3ce75

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version="$Id: solve.lib,v 1.9 1999-07-06 15:32:57 Singular Exp $";
info="
LIBRARY: solve.lib     PROCEDURES TO SOLVE POLYNOMIAL SYSTEMS
AUTHOR:  Moritz Wenk,  email: wenk@mathematik.uni-kl.de

PROCEDURES:
 ures_solve(i,..);      find all roots of 0-dimensional ideal i with resultants
 mp_res_mat(i,..);      multipolynomial resultant matrix of ideal i
 laguerre_solve(p,..);  find all roots of univariate polynom p
 interpolate(i,j,d);    interpolate poly from evaluation points i and results j
";

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proc ures_solve( ideal gls, list # )
"USAGE:   ures_solve(i[,k,l,m]); i ideal, k,l,m integers
         k=0: use sparse resultant matrix of Gelfand, Kapranov and Zelevinsky
         k=1: use resultant matrix of Macaulay (k=0 is default)
         l>0: defines precision of fractional part if ground field is Q
         m=0,1,2: number of iterations for approximation of roots (default=2)
ASSUME:  i is a zerodimensional ideal with
         nvars(basering) = ncols(i) = number of vars actually occuring in i
RETURN:  list of all (complex) roots of the polynomial system i = 0,
         of type number if the ground field is the complex numbers,
         of type string if the ground field is the rational or real numbers
EXAMPLE: example ures_solve; shows an example
"
{
  int typ=0;
  int polish=2;
  int prec=30;

  if ( size(#) >= 1 )
  {
    typ= #[1];
    if ( typ < 0 || typ > 1 )
    {
      ERROR("Valid values for second parameter k are:
      0: use sparse Resultant (default)
      1: use Macaulay Resultant");
    }
  }
  if ( size(#) >= 2 )
  {
    prec= #[2];
    if ( prec == 0 ) { prec = 30; }
    if ( prec < 0 )
    {
      ERROR("Third parameter l must be positive!");
    }
  }
  if ( size(#) >= 3 )
  {
    polish= #[3];
    if ( polish < 0 || polish > 2 )
    {
      ERROR("Valid values for fourth parameter m are:
      0,1,2: number of iterations for approximation of roots");
    }
  }

  if ( size(#) > 3 )
  {
    ERROR("only three parameters allowed!");
  }

  int digits= system("setFloatDigits",prec);

  return(uressolve(gls,typ,polish));

}
example
{
  "EXAMPLE:";echo=2;
  // compute the intersection points of two curves
  ring rsq = 0,(x,y),lp;
  ideal gls=  x2 + y2 - 10, x2 + xy + 2y2 - 16;
  ures_solve(gls);
  // result is a list (x,y)-coordinates as strings

  pause();
  // now with complex coefficient field, precision is 10 digits
  ring rsc= (real,10,I),(x,y),lp;
  ideal i = (2+3*I)*x2 + (0.35+I*45.0e-2)*y2 - 8, x2 + xy + (42.7)*y2;
  ures_solve(i);
  // result is a list of (x,y)-coordinates of complex numbers
}
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proc laguerre_solve( poly f, list # )
"USAGE:   laguerre_solve( p[,l,m]); f poly, l,m integers
         l>0: defines precision of fractional part if ground field is Q
         m=0,1,2: number of iterations for approximation of roots (default=2)
ASSUME:  p is an univariate polynom
RETURN:  list of all (complex) roots of the polynomial p;
         of type number if the ground field is the complex numbers,
         of type string if the ground field is the rational or real numbers
EXAMPLE: example laguerre_solve; shows an example
"
{
  int polish=2;
  int prec=30;

  if ( size(#) >= 1 )
  {
    prec= #[1];
    if ( prec == 0 ) { prec = 30; }
    if ( prec < 0 )
    {
      ERROR("Fisrt parameter must be positive!");
    }
  }
  if ( size(#) >= 2 )
  {
    polish= #[2];
    if ( polish < 0 || polish > 2 )
    {
      ERROR("Valid values for third parameter are:
      0,1,2: number of iterations for approximation of roots");
    }
  }
  if ( size(#) > 2 )
  {
    ERROR("only two parameters allowed!");
  }

  int digits= system("setFloatDigits",prec);

  return(laguerre(f,polish));

}
example
{
  "EXAMPLE:";echo=2;
  // Find all roots of an univariate polynomial using Laguerre's method:
  ring rs1= 0,(x,y),lp;
  poly f = 15x5 + x3 + x2 - 10;
  laguerre_solve(f);

  pause();
  // Now with 10 digits precision:
  laguerre_solve(f,10);

  pause();
  // Now with complex coefficients, precision is 20 digits:
  ring rsc= (real,20,I),x,lp;
  poly f = (15.4+I*5)*x^5 + (25.0e-2+I*2)*x^3 + x2 - 10*I;
  list l = laguerre_solve(f);
  l;
}
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proc mp_res_mat( ideal i, list # )
"USAGE:   mp_res_mat(i[,k]); i ideal, k integer
         k=0: sparse resultant matrix of Gelfand, Kapranov and Zelevinsky
         k=1: resultant matrix of Macaulay (k=0 is default)
ASSUME:  nvars(basering) = ncols(i)-1 = number of vars actually occuring in i,
         for k=1 i must be homogeneous
RETURN:  module representing the multipolynomial resultant matrix
EXAMPLE: example mp_res_mat; shows an example
"
{
  int typ=2;

  if ( size(#) == 1 )
  {
    typ= #[1];
    if ( typ < 0 || typ > 1 )
    {
      ERROR("Valid values for third parameter are:
      0: sparse resultant (default)
      1: Macaulay resultant");
    }
  }
  if ( size(#) > 1 )
  {
    ERROR("only two parameters allowed!");
  }

  return(mpresmat(i,typ));

}
example
{
  "EXAMPLE:";echo=2;
  // compute resultant matrix in ring with parameters (sparse resultant matrix)
  ring rsq= (0,u0,u1,u2),(x1,x2),lp;
  ideal i= u0+u1*x1+u2*x2,x1^2 + x2^2 - 10,x1^2 + x1*x2 + 2*x2^2 - 16;
  module m = mp_res_mat(i);
  print(m);
  // computing sparse resultant
  det(m);

  pause();
  // compute resultant matrix (Macaulay resultant matrix)
  ring rdq= (0,u0,u1,u2),(x0,x1,x2),lp;
  ideal h=  homog(imap(rsq,i),x0);
  hgls;
  module m = mp_res_mat(h,1);
  print(m);
  // computing Macaulay resultant (should be the same as above!)
  det(m);

  pause();
  // compute numerical sparse resultant matrix
  setring rsq;
  ideal ir= 15+2*x1+5*x2,x1^2 + x2^2 - 10,x1^2 + x1*x2 + 2*x2^2 - 16;
  module mn = mp_res_mat(ir);
  print(mn);
  // computing sparse resultant
  det(mn);
}
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proc interpolate( ideal p, ideal w, int d )
"USAGE:   interpolate(p,v,d); p,v ideals, d int
ASSUME:  ground field K is the rational numbers,
         p and v consist of numbers of the ground filed K, p must have
         n elements, v must have N=(d+1)^n elements where n=nvars(basering)
         and d=deg(f) (f is the unknown polynomial in K[x1,...,xn])
COMPUTE: polynomial f with values given by v at points p1,..,pN derived from p;
         more precisely: consider p as point in K^n and v as N elements in K,
         let p1,..,pN be the points in K^n obtained by evaluating all monomials
         of degree 0,1,...,N at p in lexicographical order,
         then the procedure computes the polynomial f satisfying f(pi) = v[i]
RETURN:  polynomial f of degree d
NOTE:    mainly useful for n=1, with f satisfying f(p^(i-1)) = v[i], i=1..d+1
EXAMPLE: example interpolate; shows an example
"
{
  return(vandermonde(p,w,d));
}
example
{
  "EXAMPLE:";  echo=2;
  ring r1 = 0,(x),lp;
  // determine f with deg(f) = 4 and
  // v = values of f at points 3^0, 3^1, 3^2, 3^3, 3^4
  ideal v=16,0,11376,1046880,85949136;
  interpolate( 3, v, 4 );

  ring r2 = 0,(x,y),dp;
  // determine f with deg(f) = 3 and
  // v = values of f at 16 points (2,3)^0=(1,1),...,(2,3)^15=(2^15,3^15)
  // valuation point (2,3)
  ideal p = 2,3;
  ideal v= 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16;
  interpolate( p,v,3 );
}
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