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#############################################################################
##
#W obsolete.g GAP library Steve Linton
##
#H @(#)$Id: obsolete.g,v 4.13.2.3 2005/12/20 12:10:11 jjm Exp $
##
#Y Copyright (C) 1996, Lehrstuhl D fuer Mathematik, RWTH Aachen, Germany
#Y (C) 1998 School Math and Comp. Sci., University of St. Andrews, Scotland
#Y Copyright (C) 2002 The GAP Group
##
## This file contains a number of functions, or extensions of
## functions to certain numbers or combinations of arguments, which
## are now considered "deprecated" or "obsolescent", but which are presently
## included in the system to maintain backwards compatibility.
##
## Procedures for dealing with this functionality are not yet completely
## agreed, but it will probably be removed from the system over
## several releases.
##
## These functions should *NOT* be used in the library.
##
## The current contents of the file was added after the release of
## {\GAP}~4.3, is regarded as ``obsolescent'' in {\GAP}~4.4,
## and is expected to be removed with the release of {\GAP}~4.5.
## (After the release of {\GAP}~4.4, the code will be added that
## is regarded as ``obsolescent'' in {\GAP}~4.5.
##
Revision.obsolete_g :=
"@(#)$Id: obsolete.g,v 4.13.2.3 2005/12/20 12:10:11 jjm Exp $";
##### Declarations from `utils.gd' which unfortuynately are used in packages
DeclareSynonym( "PrimeOfPGroup", PrimePGroup );
## Underlying field of a vector space or algebra.
DeclareAttribute( "UnderlyingField", IsVectorSpace );
InstallMethod(UnderlyingField,"vector space",true,[IsVectorSpace],0,
LeftActingDomain);
DeclareAttribute( "UnderlyingField", IsFFEMatrixGroup );
InstallMethod(UnderlyingField,"generic",true,[IsVectorSpace],0,
FieldOfMatrixGroup);
## Dimension of matrices in an algebra.
DeclareSynonym( "MatrixDimension", DimensionOfMatrixGroup);
#####
# monomial ordering: the function was badly defined, name is now obsolete
DeclareSynonym( "MonomialTotalDegreeLess", MonomialExtGrlexLess );
#############################################################################
##
#F SmithNormalFormSQ( mat )
##
## returns D = diagonalised form, D = P * M * Q, I = Q^-1
##
BindGlobal("SmithNormalFormSQ", function( M )
local r;
Info(InfoWarning,1,"Obsolete function `SmithNormalFormSQ',\n",
"use `NormalFormIntMat' instead");
r:=NormalFormIntMat(M,15);
return rec(P:=r.rowtrans,Q:=r.coltrans,D:=r.normal,I:=r.coltrans^-1);
end );
#############################################################################
##
#F DiagonalizeIntMatNormDriven(<mat>) . . . . diagonalize an integer matrix
##
## 'DiagonalizeIntMatNormDriven' diagonalizes the integer matrix <mat>.
##
## It tries to keep the entries small through careful selection of pivots.
##
## First it selects a nonzero entry for which the product of row and column
## norm is minimal (this need not be the entry with minimal absolute value).
## Then it brings this pivot to the upper left corner and makes it positive.
##
## Next it subtracts multiples of the first row from the other rows, so that
## the new entries in the first column have absolute value at most pivot/2.
## Likewise it subtracts multiples of the 1st column from the other columns.
##
## If afterwards not all new entries in the first column and row are zero,
## then it selects a new pivot from those entries (again driven by product
## of norms) and reduces the first column and row again.
##
## If finally all offdiagonal entries in the first column and row are zero,
## then it starts all over again with the submatrix '<mat>{[2..]}{[2..]}'.
##
## It is based upon ideas by George Havas and code by Bohdan Majewski.
## G. Havas and B. Majewski, Integer Matrix Diagonalization, JSC, to appear
##
#T Should this test for mutability? SL
BindGlobal("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 );
#############################################################################
##
#F DeclarePackage( <name>, <version>, <tester> )
#F DeclareAutoPackage( <name>, <version>, <tester> )
#F DeclarePackageDocumentation( <name>, <doc>[, <short>[, <long> ] ] )
#F DeclarePackageAutoDocumentation( <name>, <doc>[, <short>[, <long> ] ] )
#F ReadPkg( ... )
#F RereadPkg( ... )
#F DoReadPkg( ... )
#F DoRereadPkg( ... )
##
## Up to {\GAP}~4.3, these functions were needed inside the `init.g' files
## of {\GAP} packages, whereas from {\GAP}~4.4 on, the `PackageInfo.g' files
## are used instead.
## So they are needed only for those packages which have a `PackageInfo.g'
## file as well as an `init.g' file that works also with {\GAP}~4.3
## (or older).
## They can be removed as soon as none of the available packages calls them.
##
BindGlobal( "DeclarePackage", Ignore );
BindGlobal( "DeclareAutoPackage", Ignore );
BindGlobal( "DeclarePackageAutoDocumentation", Ignore );
BindGlobal( "DeclarePackageDocumentation", Ignore );
BindGlobal( "ReadPkg", ReadPackage );
BindGlobal( "RereadPkg", RereadPackage );
BindGlobal( "DoReadPkg", function( arg )
ReadPackage( arg[1] );
return true;
end );
BindGlobal( "DoRereadPkg", function( arg )
RereadPackage( arg[1] );
return true;
end );
#############################################################################
##
#V KERNEL_VERSION
#V VERSION
#V GAP_ARCHITECTURE
#V GAP_ROOT_PATHS
#V USER_HOME
#V GAP_RC_FILE
#V DO_AUTOLOAD_PACKAGES
#V DEBUG_LOADING
#V CHECK_FOR_COMP_FILES
#V BANNER
#V QUIET
#V AUTOLOAD_PACKAGES
#V LOADED_PACKAGES
##
## Up to {\GAP}~4.3, these global variables were used instead of the new
## record `GAPInfo'.
##
## Note that also `AUTOLOAD_PACKAGES' gets bound in `init.g'.
##
BindGlobal( "KERNEL_VERSION", GAPInfo.KernelVersion );
BindGlobal( "VERSION", GAPInfo.Version );
BindGlobal( "GAP_ARCHITECTURE", GAPInfo.Architecture );
BindGlobal( "GAP_ROOT_PATHS", GAPInfo.RootPaths );
BindGlobal( "USER_HOME", GAPInfo.UserHome );
BindGlobal( "GAP_RC_FILE", GAPInfo.gaprc );
BindGlobal( "DO_AUTOLOAD_PACKAGES", not GAPInfo.CommandLineOptions.A );
BindGlobal( "DEBUG_LOADING", GAPInfo.CommandLineOptions.D );
BindGlobal( "CHECK_FOR_COMP_FILES", not GAPInfo.CommandLineOptions.N );
BindGlobal( "BANNER", not GAPInfo.CommandLineOptions.b );
BindGlobal( "QUIET", GAPInfo.CommandLineOptions.q );
BindGlobal( "LOADED_PACKAGES", GAPInfo.PackagesLoaded );
#############################################################################
##
#F P( <obj> )
##
## This was defined in `init.g' before `banner.g' was read.
##
P := function(a) Print(" ", a, "\n" ); end;
#############################################################################
##
#F ListSorted( <coll> )
#F AsListSorted(<coll>)
##
## These operations are obsolete and will vanish in future versions. They
## are included solely for temporary compatibility with beta releases but
## should *never* be used. Use `SSortedList' and `AsSSortedList' instead!
ListSorted := function(coll)
Info(InfoWarning,1,"The command `ListSorted' will *not* be supported in",
"further versions!");
return SSortedList(coll);
end;
AsListSorted := function(coll)
Info(InfoWarning,1,"The command `AsListSorted' will *not* be supported in",
"further versions!");
return AsSSortedList(coll);
end;
#############################################################################
##
#A NormedVectors( <V> )
##
DeclareSynonymAttr( "NormedVectors", NormedRowVectors );
#############################################################################
##
#F SameBlock( <tbl>, <p>, <omega1>, <omega2>, <relevant>, <exponents> )
##
## Let <tbl> be an ordinary character table, <p> a prime integer, <omega1>
## and <omega2> two central characters (or their values lists) of <tbl>.
## The remaining arguments <relevant> and <exponents> are lists as stored in
## the components `relevant' and `exponents' of a record returned by
## `PrimeBlocks' (see~"PrimeBlocks").
##
## `SameBlock' returns `true' if <omega1> and <omega2> are equal modulo any
## maximal ideal in the ring of complex algebraic integers containing the
## ideal spanned by <p>, and `false' otherwise.
##
## The above syntax was supported and documented in {\GAP}~4.3.
## In {\GAP}~4.4, the first and the last argument were omitted because they
## turned out to be unnecessary. (The record returned by `PrimeBlocks' does
## no longer have a component `exponents'.)
## From {\GAP}~4.5 on, only the four argument version will be supported.
##
#############################################################################
##
#F TryConwayPolynomialForFrobeniusCharacterValue( <p>, <n> )
##
## This name is needed just for backwards compatibility with {\GAP}~4.4.
## Now one should better use `IsCheapConwayPolynomial' directly.
##
DeclareSynonym( "TryConwayPolynomialForFrobeniusCharacterValue",
IsCheapConwayPolynomial );
#############################################################################
##
#E
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