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#############################################################################
##
#W pslq.gi GAP float Steve A. Linton
##
#Y Copyright (C) 2014 Steve Linton & Laurent Bartholdi
##
## This file implements the PSLQ and multi-pair PSLQ algorithms as described
## in "Parallel Integer Relation Detection: Techniques and Applications
## David H. Bailey and David J. Broadhurst" Math.Comput. 70 (2001) 1719-1736
##
## Both implementations follow the paper quite closely. The main input
## is a vector of floats in some appropriate extended precision representation
## There is currently no detection of whether the representation is extended
## enough, although the algorithm will probably not terminate if it is not
## when this class is set to level 2 or higher it prints a few numbers
## indicating progress at each iteration
# TODO: implement the multi-level version
# TODO: parallelise the multi-pair version.
# TODO: detect when there is insufficient precisiona and fail cleanly.
BindGlobal("defaultgamma@", 2.0/Sqrt(3.0));
## <#GAPDoc Label="PSLQ">
## The PSLQ algorithm has been implemented by Steve A. Linton, as an external
## contribution to <Package>Float</Package>. This algorithm receives as
## input a vector of floats <M>x</M> and a required precision <M>\epsilon</M>,
## and seeks an integer vector <M>v</M> such that
## <M>|x\cdot v|<\epsilon</M>. The implementation follows quite closely the
## original article <Cite Key="MR1836930"/>.
##
## <ManSection>
## <Func Name="PSLQ" Arg="x, epsilon[, gamma]"/>
## <Func Name="PSLQ_MP" Arg="x, epsilon[, gamma [,beta]]"/>
## <Returns>An integer vector <M>v</M> with <M>|x\cdot v|<\epsilon</M>.</Returns>
## <Description>
## The PSLQ algorithm by Bailey and Broadhurst (see <Cite Key="MR1836930"/>)
## searches for an integer relation between the entries in <M>x</M>.
##
## <P/><M>\beta</M> and <M>\gamma</M> are algorithm tuning parameters, and
## default to <M>4/10</M> and <M>2/\sqrt(3)</M> respectively.
##
## <P/>The second form implements the "Multi-pair" variant of the algorithm, which is
## better suited to parallelization.
## <Example><![CDATA[
## gap> PSLQ([1.0,(1+Sqrt(5.0))/2],1.e-2);
## [ 55, -34 ] # Fibonacci numbers
## gap> RootsFloat([1,-4,2]*1.0);
## [ 0.292893, 1.70711 ] # roots of 2x^2-4x+1
## gap> PSLQ(List([0..2],i->last[1]^i),1.e-7);
## [ 1, -4, 2 ] # a degree-2 polynomial fitting well
## ]]></Example>
## </Description>
## </ManSection>
## <#/GAPDoc>
##
BindGlobal("PSLQ", function(arg)
local sample, eps, gamma, one, zero, redentry, swapEntries, n, i,
y, A, B, s, s2, t, H, j, count, best, m, q, a, t0, t1, t2,
t3, t4, l, M, rp, ym, x;
# Process arguments and set up a few constants
if Length(arg) < 2 or Length(arg) > 4 or not ForAll(arg[1], IsFloat) then
Error("Usage: pslq(x, epsilon [, gamma] ) default gamme is 2/sqrt(3)");
fi;
x := arg[1];
sample := x[1];
eps := arg[2];
if Length(arg) = 3 then
gamma := arg[3];
else
gamma := MakeFloat(sample, defaultgamma@);
fi;
#
# We can't just use 1.0 or 0.0 because they might not have the right representation
#
one := One(sample);
zero := Zero(sample);
#
# Basic step in HNF calculations, used in a couple of places
#
redentry := function(i,j)
local t, ti;
t := Round(H[i][j]/H[j][j]);
ti := Int(t);
y[j] := y[j] + t*y[i];
AddRowVector(H[i],H[j],-t,1,j);
AddRowVector(A[i],A[j],-ti,1,n);
AddRowVector(B[j],B[i],ti,1,n);
end;
#
# swap entries m and m+1 in list a
#
swapEntries := function(a, m)
local t;
t := a[m];
a[m] := a[m+1];
a[m+1] := t;
end;
n := Length(x);
#
# If the list includes something close enough to zero, the problem is easy
#
i := PositionProperty(x, y->AbsoluteValue(y) < eps);
if i <> fail then
y := ListWithIdenticalEntries(n,0);
y[i] := 1;
return y;
fi;
#
# and now to work.
#
#
# Initial setup
#
A := IdentityMat(n,Integers);
B := IdentityMat(n,Integers);
s := [];
s2 := zero;
for i in [n,n-1..1] do
s2 := s2 + x[i]^2;
s[i] := Sqrt(s2);
od;
t := one/s[1];
y := t*x;
s := t*s;
H := List([1..n], i->[]);
for j in [1..n-1] do
for i in [1..j-1] do
H[i][j] := zero;
od;
H[j][j] := s[j+1]/s[j];
for i in [j+1..n] do
H[i][j] := -y[i]*y[j]/(s[j]*s[j+1]);
od;
od;
for i in [2..n] do
for j in [i-1,i-2..1] do
redentry(i,j);
od;
od;
count := 0;
#
# Main loop
#
repeat
count := count+1;
#
# find row to work on (maximum of gamma^i*H[i][i])
#
best := -one;
m := fail;
q := one;
for i in [1..n-1] do
q := q*gamma;
a := q*AbsoluteValue(H[i][i]);
if a > best then
m := i;
best := a;
fi;
od;
#
# exchange step
#
swapEntries(y,m);
swapEntries(A,m);
swapEntries(B,m);
swapEntries(H,m);
#
# Corner step
#
if m <= n-2 then
t0 := Sqrt(H[m][m]^2 + H[m][m+1]^2);
t1 := H[m][m]/t0;
t2 := H[m][m+1]/t0;
for i in [m..n] do
t3 := H[i][m];
t4 := H[i][m+1];
H[i][m] := t1*t3 + t2*t4;
H[i][m+1] := -t2*t3 + t1*t4;
od;
fi;
#
# Reduction step
#
for i in [m+1..n] do
l := Minimum(i-1,m+1);
for j in [l,l-1..1] do
redentry(i,j);
od;
od;
#
# Take stock at the end of the iteration
#
M := 1.0/Maximum(List([1..n-1], i->AbsoluteValue(H[i][i])));
rp := 1;
ym := AbsoluteValue(y[1]);
for i in [2..n] do
t := AbsoluteValue(y[i]);
if t < ym then
ym := t;
rp := i;
fi;
od;
Info(InfoFloat, 2, count,": ",Int(M)," ",Int(Log10(ym)));
until ym < eps;
return B[rp];
end);
BindGlobal("defaultbeta@", 4/10);
BindGlobal("PSLQ_MP", function(arg)
local swapEntries, x, eps, sample, n, one, zero, gamma, betan, i,
y, A, B, s, s2, t, H, j, count, v, q, l, used, pairs, p, m,
t0, t1, t2, t3, t4, T, k, M, rp, ym;
#
# swap entries m and m+1 in list a
#
swapEntries := function(a, m)
local t;
t := a[m];
a[m] := a[m+1];
a[m+1] := t;
end;
if Length(arg) < 2 or Length(arg) > 4 or not ForAll(arg[1],IsFloat) then
Error("Usage: pslqMP( x, epsilon[, gamma[, beta]])");
fi;
x := arg[1];
eps := arg[2];
sample := x[1];
n := Length(x);
one := One(sample);
zero := Zero(sample);
if Length(arg) > 2 then
gamma := arg[3];
else
gamma := MakeFloat(sample, defaultgamma@);
fi;
if Length(arg) > 3 then
betan := arg[4]*n;
else
betan := n*defaultbeta@;
fi;
#
# If the list includes something close enough to zero, the problem is easy
#
i := PositionProperty(x, y->AbsoluteValue(y) < eps);
if i <> fail then
y := ListWithIdenticalEntries(n,0);
y[i] := 1;
return y;
fi;
#
# Start the real work
#
A := IdentityMat(n,Integers);
B := IdentityMat(n,Integers);
s := [];
s2 := zero;
for i in [n,n-1..1] do
s2 := s2 + x[i]^2;
s[i] := Sqrt(s2);
od;
t := one/s[1];
y := t*x;
s := t*s;
H := List([1..n], i->[]);
for j in [1..n-1] do
for i in [1..j-1] do
H[i][j] := zero;
od;
H[j][j] := s[j+1]/s[j];
for i in [j+1..n] do
H[i][j] := -y[i]*y[j]/(s[j]*s[j+1]);
od;
od;
count := 0;
#
# Main loop
#
repeat
count := count+1;
v := [];
q := one;
for i in [1..n-1] do
q := q*gamma;
# negate to get the sorting order, since that's all we actually care about
Add(v, -q*AbsoluteValue(H[i][i]));
od;
l := [1..n-1];
SortParallel(v,l);
#
# Now we sort out our pairs
#
used := BlistList([1..n],[]);
pairs := [];
for i in [1..n-1] do
if not used[l[i]] and not used[l[i]+1] then
Add(pairs,l[i]);
used[l[i]] := true;
used[l[i]+1] := true;
fi;
if Length(pairs) > betan then
break;
fi;
od;
p := Length(pairs);
for m in pairs do
swapEntries(y,m);
swapEntries(A,m);
swapEntries(B,m);
swapEntries(H,m);
od;
for m in pairs do
if m <= n-2 then
t0 := Sqrt(H[m][m]^2 + H[m][m+1]^2);
t1 := H[m][m]/t0;
t2 := H[m][m+1]/t0;
for i in [m..n] do
t3 := H[i][m];
t4 := H[i][m+1];
H[i][m] := t1*t3 + t2*t4;
H[i][m+1] := -t2*t3 + t1*t4;
od;
fi;
od;
T:= List([1..n], i->[]);
for i in [2..n] do
for j in [1..n-i+1] do
l := i+j-1;
for k in [j+1..l-1] do
H[l][j] := H[l][j] - T[l][k]*H[k][j];
od;
T[l][j] := Round(H[l][j]/H[j][j]);
H[l][j] := H[l][j] - T[l][j]*H[j][j];
od;
od;
for j in [1..n-1] do
for i in [j+1..n] do
y[j] := y[j] + T[i][j]*y[i];
od;
od;
for j in [1..n-1] do
for i in [j+1..n] do
AddRowVector(A[i],A[j], -Int(T[i][j]));
AddRowVector(B[j],B[i], Int(T[i][j]));
od;
od;
M := one/Maximum(List([1..n-1], i->AbsoluteValue(H[i][i])));
rp := 1;
ym := AbsoluteValue(y[1]);
for i in [2..n] do
t := AbsoluteValue(y[i]);
if t < ym then
ym := t;
rp := i;
fi;
od;
Info(InfoFloat,2,count,": ",Int(M)," ",Int(Log10(ym)));
until ym < eps;
return B[rp];
end);
# These examples are used in the paper cited above to generate a family of test data.
BindGlobal("MakePslqTest@", function(r,s)
local alpha, xs;
alpha := Exp(Log(3.0)/r) - Exp(Log(2.0)/s);
xs := List([0..r*s], i-> alpha^i);
return xs;
end);
#############################################################################
#E
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