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#############################################################################
##
#W  obsolete.gi                  GAP library                     Steve Linton
##
##
#Y  Copyright (C)  1996,  Lehrstuhl D für Mathematik,  RWTH Aachen,  Germany
#Y  (C) 1998 School Math and Comp. Sci., University of St Andrews, Scotland
#Y  Copyright (C) 2002 The GAP Group
##
##  See the comments in `lib/obsolete.gd'.
##


#############################################################################
##
#F  DiagonalizeIntMatNormDriven(<mat>)  . . . . diagonalize an integer matrix
##
#T  Should this test for mutability? SL
##
InstallGlobalFunction( DiagonalizeIntMatNormDriven, function ( mat )
    local   nrrows,     # number of rows    (length of <mat>)
            nrcols,     # number of columns (length of <mat>[1])
            rownorms,   # norms of rows
            colnorms,   # norms of columns
            d,          # diagonal position
            pivk, pivl, # position of a pivot
            norm,       # product of row and column norms of the pivot
            clear,      # are the row and column cleared
            row,        # one row
            col,        # one column
            ent,        # one entry of matrix
            quo,        # quotient
            h,          # gap width in shell sort
            k, l,       # loop variables
            max, omax;  # maximal entry and overall maximal entry
            
    # give some information
    Info( InfoMatrix, 1, "DiagonalizeMat called" );
    omax := 0;

    # get the number of rows and columns
    nrrows := Length( mat );
    if nrrows <> 0  then
        nrcols := Length( mat[1] );
    else
        nrcols := 0;
    fi;
    rownorms := [];
    colnorms := [];

    # loop over the diagonal positions
    d := 1;
    Info( InfoMatrix, 2, "  divisors:" );

    while d <= nrrows and d <= nrcols  do

        # find the maximal entry
        Info( InfoMatrix, 3, "    d=", d );
        if 3 <= InfoLevel( InfoMatrix ) then
            max := 0;
            for k  in [ d .. nrrows ]  do
                for l  in [ d .. nrcols ]  do
                    ent := mat[k][l];
                    if   0 < ent and max <  ent  then
                        max :=  ent;
                    elif ent < 0 and max < -ent  then
                        max := -ent;
                    fi;
                od;
            od;
            Info( InfoMatrix, 3, "    max=", max );
            if omax < max  then omax := max;  fi;
        fi;

        # compute the Euclidean norms of the rows and columns
        for k  in [ d .. nrrows ]  do
            row := mat[k];
            rownorms[k] := row * row;
        od;
        for l  in [ d .. nrcols ]  do
            col := mat{[d..nrrows]}[l];
            colnorms[l] := col * col;
        od;
        Info( InfoMatrix, 3, "    n" );

        # push rows containing only zeroes down and forget about them
        for k  in [ nrrows, nrrows-1 .. d ]  do
            if k < nrrows and rownorms[k] = 0  then
                row         := mat[k];
                mat[k]      := mat[nrrows];
                mat[nrrows] := row;
                norm             := rownorms[k];
                rownorms[k]      := rownorms[nrrows];
                rownorms[nrrows] := norm;
            fi;
            if rownorms[nrrows] = 0  then
                nrrows := nrrows - 1;
            fi;
        od;

        # quit if there are no more nonzero entries
        if nrrows < d  then
            #N  1996/04/30 mschoene should 'break'
            Info( InfoMatrix, 3, "  overall maximal entry ", omax );
            Info( InfoMatrix, 1, "DiagonalizeMat returns" );
            return;
        fi;

        # push columns containing only zeroes right and forget about them
        for l  in [ nrcols, nrcols-1 .. d ]  do
            if l < nrcols and colnorms[l] = 0  then
                col                      := mat{[d..nrrows]}[l];
                mat{[d..nrrows]}[l]      := mat{[d..nrrows]}[nrcols];
                mat{[d..nrrows]}[nrcols] := col;
                norm             := colnorms[l];
                colnorms[l]      := colnorms[nrcols];
                colnorms[nrcols] := norm;
            fi;
            if colnorms[nrcols] = 0  then
                nrcols := nrcols - 1;
            fi;
        od;

        # sort the rows with respect to their norms
        h := 1;  while 9 * h + 4 < nrrows-(d-1)  do h := 3 * h + 1;  od;
        while 0 < h  do
            for l  in [ h+1 .. nrrows-(d-1) ]  do
                norm := rownorms[l+(d-1)];
                row := mat[l+(d-1)];
                k := l;
                while h+1 <= k  and norm < rownorms[k-h+(d-1)]  do
                    rownorms[k+(d-1)] := rownorms[k-h+(d-1)];
                    mat[k+(d-1)] := mat[k-h+(d-1)];
                    k := k - h;
                od;
                rownorms[k+(d-1)] := norm;
                mat[k+(d-1)] := row;
            od;
            h := QuoInt( h, 3 );
        od;

        # choose a pivot in the '<mat>{[<d>..]}{[<d>..]}' submatrix
        # the pivot must be the topmost nonzero entry in its column,
        # now that the rows are sorted with respect to their norm
        pivk := 0;  pivl := 0;
        norm := Maximum(rownorms) * Maximum(colnorms) + 1;
        for l  in [ d .. nrcols ]  do
            k := d;
            while mat[k][l] = 0  do
                k := k + 1;
            od;
            if rownorms[k] * colnorms[l] < norm  then
                pivk := k;  pivl := l;
                norm := rownorms[k] * colnorms[l];
            fi;
        od;
        Info( InfoMatrix, 3, "    p" );

        # move the pivot to the diagonal and make it positive
        if d <> pivk  then
            row       := mat[d];
            mat[d]    := mat[pivk];
            mat[pivk] := row;
        fi;
        if d <> pivl  then
            col                    := mat{[d..nrrows]}[d];
            mat{[d..nrrows]}[d]    := mat{[d..nrrows]}[pivl];
            mat{[d..nrrows]}[pivl] := col;
        fi;
        if mat[d][d] < 0  then
            MultRowVector(mat[d],-1);
        fi;

        # now perform row operations so that the entries in the
        # <d>-th column have absolute value at most pivot/2
        clear := true;
        row := mat[d];
        for k  in [ d+1 .. nrrows ]  do
            quo := BestQuoInt( mat[k][d], mat[d][d] );
            if quo = 1  then
                AddRowVector(mat[k], row, -1);
            elif quo = -1  then
                AddRowVector(mat[k], row);
            elif quo <> 0  then
                AddRowVector(mat[k], row, -quo);
            fi;
            clear := clear and mat[k][d] = 0;
        od;
        Info( InfoMatrix, 3, "    c" );

        # now perform column operations so that the entries in
        # the <d>-th row have absolute value at most pivot/2
        col := mat{[d..nrrows]}[d];
        for l  in [ d+1 .. nrcols ]  do
            quo := BestQuoInt( mat[d][l], mat[d][d] );
            if quo = 1  then
                mat{[d..nrrows]}[l] := mat{[d..nrrows]}[l] - col;
            elif quo = -1  then
                mat{[d..nrrows]}[l] := mat{[d..nrrows]}[l] + col;
            elif quo <> 0  then
                mat{[d..nrrows]}[l] := mat{[d..nrrows]}[l] - quo * col;
            fi;
            clear := clear and mat[d][l] = 0;
        od;
        Info( InfoMatrix, 3, "    r" );

        # repeat until the <d>-th row and column are totally cleared
        while not clear  do

            # compute the Euclidean norms of the rows and columns
            # that have a nonzero entry in the <d>-th column resp. row
            for k  in [ d .. nrrows ]  do
                if mat[k][d] <> 0  then
                    row := mat[k];
                    rownorms[k] := row * row;
                fi;
            od;
            for l  in [ d .. nrcols ]  do
                if mat[d][l] <> 0  then
                    col := mat{[d..nrrows]}[l];
                    colnorms[l] := col * col;
                fi;
            od;
            Info( InfoMatrix, 3, "    n" );

            # choose a pivot in the <d>-th row or <d>-th column
            pivk := 0;  pivl := 0;
            norm := Maximum(rownorms) * Maximum(colnorms) + 1;
            for l  in [ d+1 .. nrcols ]  do
                if 0 <> mat[d][l] and rownorms[d] * colnorms[l] < norm  then
                    pivk := d;  pivl := l;
                    norm := rownorms[d] * colnorms[l];
                fi;
            od;
            for k  in [ d+1 .. nrrows ]  do
                if 0 <> mat[k][d] and rownorms[k] * colnorms[d] < norm  then
                    pivk := k;  pivl := d;
                    norm := rownorms[k] * colnorms[d];
                fi;
            od;
            Info( InfoMatrix, 3, "    p" );

            # move the pivot to the diagonal and make it positive
            if d <> pivk  then
                row       := mat[d];
                mat[d]    := mat[pivk];
                mat[pivk] := row;
            fi;
            if d <> pivl  then
                col                    := mat{[d..nrrows]}[d];
                mat{[d..nrrows]}[d]    := mat{[d..nrrows]}[pivl];
                mat{[d..nrrows]}[pivl] := col;
            fi;
            if mat[d][d] < 0  then
                MultRowVector(mat[d],-1);
            fi;

            # now perform row operations so that the entries in the
            # <d>-th column have absolute value at most pivot/2
            clear := true;
            row := mat[d];
            for k  in [ d+1 .. nrrows ]  do
                quo := BestQuoInt( mat[k][d], mat[d][d] );
	        if quo = 1  then
                    AddRowVector(mat[k],row,-1);
                elif quo = -1  then
                    AddRowVector(mat[k],row);
                elif quo <> 0  then
                    AddRowVector(mat[k], row, -quo);
                fi;
                clear := clear and mat[k][d] = 0;
            od;
            Info( InfoMatrix, 3, "    c" );

            # now perform column operations so that the entries in
            # the <d>-th row have absolute value at most pivot/2
            col := mat{[d..nrrows]}[d];
            for l  in [ d+1.. nrcols ]  do
                quo := BestQuoInt( mat[d][l], mat[d][d] );
                if quo = 1  then
                    mat{[d..nrrows]}[l] := mat{[d..nrrows]}[l] - col;
                elif quo = -1  then
                    mat{[d..nrrows]}[l] := mat{[d..nrrows]}[l] + col;
                elif quo <> 0  then
                    mat{[d..nrrows]}[l] := mat{[d..nrrows]}[l] - quo * col;
                fi;
                clear := clear and mat[d][l] = 0;
            od;
            Info( InfoMatrix, 3, "    r" );

        od;

        # print the diagonal entry (for information only)
        Info( InfoMatrix, 3, "    div=" );
        Info( InfoMatrix, 2, "      ", mat[d][d] );

        # go on to the next diagonal position
        d := d + 1;

    od;

    # close with some more information
    Info( InfoMatrix, 3, "  overall maximal entry ", omax );
    Info( InfoMatrix, 1, "DiagonalizeMat returns" );
end );


#############################################################################
##
#M  CharacteristicPolynomial( <F>, <mat> )
#M  CharacteristicPolynomial( <field>, <matrix>, <indnum> )
##
##  The documentation of these usages of CharacteristicPolynomial was
##  ambiguous, leading to surprising results if mat was over F but
##  DefaultField (mat) properly contained F.
##  Now there is a four argument version which allows to specify the field
##  which specifies the linear action of mat, and another which specifies
##  the vector space which mat acts upon.
##
##  In the future, the versions above could be given a differnt meaning,
##  where the first argument simply specifies both fields in the case
##  when they are the same.
##
##  The following provides backwards compatibility with  {\GAP}~4.4. in the
##  cases where there is no ambiguity.
##
InstallOtherMethod( CharacteristicPolynomial,
     "supply indeterminate 1",
    [ IsField, IsMatrix ],
    function( F, mat )
        return CharacteristicPolynomial (F, mat, 1);
    end );

InstallOtherMethod( CharacteristicPolynomial,
    "check default field, print error if ambiguous",
    IsElmsCollsX,
    [ IsField, IsOrdinaryMatrix, IsPosInt ],
function( F, mat, inum )
        if IsSubset (F, DefaultFieldOfMatrix (mat)) then
            Info (InfoWarning, 1, "This usage of `CharacteristicPolynomial' is no longer supported. ",
                "Please specify two fields instead.");
            return CharacteristicPolynomial (F, F, mat, inum);
        else
            Error ("this usage of `CharacteristicPolynomial' is no longer supported, ",
                "please specify two fields instead.");
        fi;
end );


#############################################################################
##
#M  ShrinkCoeffs( <list> )
##
InstallMethod( ShrinkCoeffs,"call `ShrinkRowVector'",
    [ IsList and IsMutable ],
function( l1 )
    Info( InfoWarning, 1,
        "the operation `ShrinkCoeffs' is not supported anymore,\n",
        "#I  use `ShrinkRowVector' instead" );
    ShrinkRowVector(l1);
    return Length(l1);
end );

InstallOtherMethod( ShrinkCoeffs,"error if immutable",
    [ IsList ],
    L1_IMMUTABLE_ERROR);

#############################################################################
##
#M  ShrinkCoeffs( <vec> )
##
InstallMethod( ShrinkCoeffs, "8 bit vector",
        [IsMutable and IsRowVector and Is8BitVectorRep ],
        function(vec)
    local r;
    Info( InfoWarning, 1,
        "the operation `ShrinkCoeffs' is not supported anymore,\n",
        "#I  use `ShrinkRowVector' instead" );
    r := RIGHTMOST_NONZERO_VEC8BIT(vec);
    RESIZE_VEC8BIT(vec, r);
    return r;
end);

#############################################################################
##
#M  ShrinkCoeffs( <gf2vec> )  . . . . . . . . . . . . . . shrink a GF2 vector
##
InstallMethod( ShrinkCoeffs,
    "for GF2 vector",
    [ IsMutable and IsRowVector and IsGF2VectorRep ],
function( l1 )
    Info( InfoWarning, 1,
        "the operation `ShrinkCoeffs' is not supported anymore,\n",
        "#I  use `ShrinkRowVector' instead" );
    return SHRINKCOEFFS_GF2VEC(l1);
end ); 


#############################################################################
##
#F  TeX( <obj1>, ... )  . . . . . . . . . . . . . . . . . . . . . TeX objects
##
##  <ManSection>
##  <Func Name="TeX" Arg='obj1, ...'/>
##
##  <Description>
##  </Description>
##  </ManSection>
##
BIND_GLOBAL( "TeX", function( arg )
    local   str,  res,  obj;

    str := "";
    for obj  in arg  do
        res := TeXObj(obj);
        APPEND_LIST_INTR( str, res );
        APPEND_LIST_INTR( str, "%\n" );
    od;
    CONV_STRING(str);
    return str;
end );


#############################################################################
##
#F  LaTeX( <obj1>, ... )  . . . . . . . . . . . . . . . . . . . LaTeX objects
##
##  <#GAPDoc Label="LaTeX">
##
##  <ManSection>
##  <Func Name="LaTeX" Arg='obj1, obj2, ...'/>
##  
##  <Description>
##  Returns a LaTeX string describing the objects <A>obj1</A>, <A>obj2</A>, ... .
##  This string can for example be pasted to a &LaTeX; file, or one can use
##  it in composing a temporary &LaTeX; file,
##  which is intended for being &LaTeX;'ed afterwards from within &GAP;.
##  <P/>
##  <Example><![CDATA[
##  gap> LaTeX(355/113);
##  "\\frac{355}{113}%\n"
##  gap> LaTeX(Z(9)^5);
##  "Z(3^{2})^{5}%\n"
##  gap> Print(LaTeX([[1,2,3],[4,5,6],[7,8,9]]));
##  \left(\begin{array}{rrr}%
##  1&2&3\\%
##  4&5&6\\%
##  7&8&9\\%
##  \end{array}\right)%
##  ]]></Example>
##  </Description>
##  </ManSection>
##  <#/GAPDoc>
##
BIND_GLOBAL( "LaTeX", function( arg )
    local   str,  res,  obj;

    str := "";
    for obj  in arg  do
        res := LaTeXObj(obj);
        APPEND_LIST_INTR( str, res );
        APPEND_LIST_INTR( str, "%\n" );
    od;
    CONV_STRING(str);
    return str;
end );


#############################################################################
##
#M  LaTeXObj( <ffe> ) . . . . . .  convert a finite field element into a string
##
InstallMethod(LaTeXObj,"for an internal FFE",true,[IsFFE and IsInternalRep],0,
function ( ffe )
local   str, log,deg,char;
  char:=Characteristic(ffe);
  if   IsZero( ffe )  then
    str := Concatenation("0\*Z(",String(char),")");
  else
    str := Concatenation("Z(",String(char));
    deg:=DegreeFFE(ffe);
    if deg <> 1  then
      str := Concatenation(str,"^{",String(deg),"}");
    fi;
    str := Concatenation(str,")");
    log:= LogFFE(ffe,Z( char ^ deg ));
    if log <> 1 then
      str := Concatenation(str,"^{",String(log),"}");
    fi;
  fi;
  ConvertToStringRep( str );
  return str;
end );


#############################################################################
##
#M  LaTeXObj( <elm> ) . . . . . . . for packed word in default representation
##
InstallMethod( LaTeXObj,"for an element of an f.p. group (default repres.)",
  true, [ IsElementOfFpGroup and IsPackedElementDefaultRep ],0,
function( obj )
  return LaTeXObj( obj![1] );
end );


#############################################################################
##
#M  LaTeXObj
##
InstallMethod(LaTeXObj,"matrix",
  [IsMatrix],
function(m)
local i,j,l,n,s;
  l:=Length(m);
  n:=Length(m[1]);
  s:="\\left(\\begin{array}{";
  for i in [1..n] do
    Add(s,'r');
  od;
  Append(s,"}%\n");
  for i in [1..l] do
    for j in [1..n] do
      Append(s,LaTeXObj(m[i][j]));
      if j<n then
        Add(s,'&');
      fi;
    od;
    Append(s,"\\\\%\n");
  od;
  Append(s,"\\end{array}\\right)");
  return s;
end);


InstallMethod( LaTeXObj,"polynomial",true, [ IsPolynomial ],0,function(pol)
local fam, ext, str, zero, one, mone, le, c, s, b, ind, i, j;

  fam:=FamilyObj(pol);
  ext:=ExtRepPolynomialRatFun(pol);
  str:="";
  zero := fam!.zeroCoefficient;
  one := fam!.oneCoefficient;
  mone := -one;
  le:=Length(ext);

  if le=0 then
    return String(zero);
  fi;
  for i  in [ le-1,le-3..1] do
    if i<le-1 then
      # this is the second summand, so arithmetic will occur
    fi;

    if ext[i+1]=one then
      if i<le-1 then
	Add(str,'+');
      fi;
      c:=false;
    elif ext[i+1]=mone then
      Add(str,'-');
      c:=false;
    else
      if IsRat(ext[i+1]) and ext[i+1]<0 then
	s:=Concatenation("-",LaTeXObj(-ext[i+1]));
      else
	s:=LaTeXObj(ext[i+1]);
      fi;

      b:=false;
      if '+' in s and s[1]<>'(' then
	s:=Concatenation("(",s,")");
      fi;

      if i<le-1 and s[1]<>'-' then
	Add(str,'+');
      fi;
      Append(str,s);
      c:=true;
    fi;

    if Length(ext[i])<2 then
      # trivial monomial. Do we have to add a '1'?
      if c=false then
        Append(str,String(one));
      fi;
    else
      #if c then
#	Add(str,'*');
#      fi;
      for j  in [ 1, 3 .. Length(ext[i])-1 ]  do
#	if 1 < j  then
#	  Add(str,'*');
#	fi;
	ind:=ext[i][j];
	if HasIndeterminateName(fam,ind) then
	  Append(str,IndeterminateName(fam,ind));
	else
	  Append(str,"x_{");
	  Append(str,String(ind)); 
	  Add(str,'}');
	fi;
	if 1 <> ext[i][j+1]  then
	  Append(str,"^{");
	  Append(str,String(ext[i][j+1]));
	  Add(str,'}');
	fi;
      od;
    fi;
  od;

  return str;
end);


#############################################################################
##
#M  LaTeXObj
##
InstallMethod(LaTeXObj,"rational",
  [IsRat],
function(r)
local n,d;
  if IsInt(r) then
    return String(r);
  fi;
  n:=NumeratorRat(r);
  d:=DenominatorRat(r);
  if AbsInt(n)<5 and AbsInt(d)<5 then
    return Concatenation(String(n),"/",String(d));
  else
    return Concatenation("\\frac{",String(n),"}{",String(d),"}");
  fi;
end);


InstallMethod(LaTeXObj,"assoc word in letter rep",true,
  [IsAssocWord and IsLetterAssocWordRep],0,
function(elm)
local names,len,i,g,h,e,a,s;

  names:= ShallowCopy(FamilyObj( elm )!.names);
  for i in [1..Length(names)] do
    s:=names[i];
    e:=Length(s);
    while e>0 and s[e] in CHARS_DIGITS do
      e:=e-1;
    od;
    if e<Length(s) then
      if e=Length(s)-1 then
	s:=Concatenation(s{[1..e]},"_",s{[e+1..Length(s)]});
      else
	s:=Concatenation(s{[1..e]},"_{",s{[e+1..Length(s)]},"}");
      fi;
      names[i]:=s;
    fi;
  od;

  s:="";
  elm:=LetterRepAssocWord(elm);
  len:= Length( elm );
  i:= 2;
  if len = 0 then
    return( "id" );
  else
    g:=AbsInt(elm[1]);
    e:=SignInt(elm[1]);
    while i <= len do
      h:=AbsInt(elm[i]);
      if h=g then
        e:=e+SignInt(elm[i]);
      else
	Append(s, names[g] );
	if e<>1 then
	  Append(s,"^{");
	  Append(s,String(e));
	  Append(s,"}");
	fi;
        g:=h;
	e:=SignInt(elm[i]);
      fi;
      i:=i+1;
    od;
    Append(s, names[g] );
    if e<>1 then
      Append(s,"^{");
      Append(s,String(e));
      Append(s,"}");
    fi;
  fi;
  return s;
end);


#############################################################################
##
#F  CharacterTableDisplayPrintLegendDefault( <data> )
##
##  for backwards compatibility only ...
##
BindGlobal( "CharacterTableDisplayPrintLegendDefault",
    function( data )
    Info( InfoWarning, 1,
        "the function `CharacterTableDisplayPrintLegendDefault' is no longer\n",
        "#I  supported and may be removed from future versions of GAP" );
    Print( CharacterTableDisplayLegendDefault( data ) );
    end );


#############################################################################
##
#F  ConnectGroupAndCharacterTable( <G>, <tbl>[, <arec>] )
#F  ConnectGroupAndCharacterTable( <G>, <tbl>, <bijection> )
##
InstallGlobalFunction( ConnectGroupAndCharacterTable, function( arg )
    local G, tbl, arec, ccl, compat;
    
    Info( InfoWarning, 1,
        "the function `ConnectGroupAndCharacterTable' is not supported anymore,\n",
        "#I  use `CharacterTableWithStoredGroup' instead" );

    # Get and check the arguments.
    if   Length( arg ) = 2 and IsGroup( arg[1] )
                           and IsOrdinaryTable( arg[2] ) then
      arec:= rec();
    elif Length( arg ) = 3 and IsGroup( arg[1] )
                           and IsOrdinaryTable( arg[2] )
                           and ( IsRecord( arg[3] ) or IsList(arg[3]) ) then
      arec:= arg[3];
    else
      Error( "usage: ConnectGroupAndCharacterTable(<G>,<tbl>[,<arec>])" );
    fi;

    G   := arg[1];
    tbl := arg[2];

    if HasUnderlyingGroup( tbl ) then
      Error( "<tbl> has already underlying group" );
    elif HasOrdinaryCharacterTable( G ) then
      Error( "<G> has already a character table" );
    fi;

    ccl:= ConjugacyClasses( G );
#T How to exploit the known character table
#T if the conjugacy classes of <G> are not yet computed?

    if IsList( arec ) then
      compat:= arec;
    else
      compat:= CompatibleConjugacyClasses( G, ccl, tbl, arec );
    fi;

    if IsList( compat ) then

      # Permute the classes if necessary.
      if compat <> [ 1 .. Length( compat ) ] then
        ccl:= ccl{ compat };
      fi;

      # The identification is unique, store attribute values.
      SetUnderlyingGroup( tbl, G );
      SetOrdinaryCharacterTable( G, tbl );
      SetConjugacyClasses( tbl, ccl );
      SetIdentificationOfConjugacyClasses( tbl, compat );

      return true;

    else
      return false;
    fi;

    end );


#############################################################################
##
#E