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If you deal with integer vectors, you need to employ integer lattices rather than linear algebra. Here is our set up:

from sage.modules.free_module_integer import IntegerLattice

M = matrix(ZZ, [[0,0,1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,1,1,1], [0,0,0,1,1,0,1,1,1,1,1,2],[1,0,0,0,0,1,1,1,1,1,1,2], [0, 0, 0, 1, 0, 1, 0, 1, 1, 2, 2, 2], [ 0, 0, 1, 0, 1, 1, 1, 2, 2, 3, 3, 4], [ 0, 0, 1, 1, 0, 1, 2, 3, 3, 5, 5, 6], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 6, 6, 8], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 7, 7, 9], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 8, 7, 11], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 7, 8, 11], [0, 1, 2, 2, 2, 4, 6, 8, 9, 11, 11, 15]])

r = vector(ZZ, [1, 21, 45, 45, 55, 99, 154, 210, 231, 280, 280, 385])

First, you need to find an integer basis B of M and a transformation U between them, using LLL. As a result of LLL, B will have as many rows as M but first few of them can be zero and will not be used in the lattice basis, but we will need to trim all rows of U corresponding to zero rows of B.

B, U = M.LLL(transformation=True)
assert U*M == B
nz = sum(1 for r in B.rows() if r==0)   # number of zero rows in B
U = U[nz:,:]              # trimming first nz rows of U

Then we construct a lattice spanned by B and represent vector r as a linear combination of the basis vectors. It then remains to prepend the zeros to beginning multiply by U:

L = IntegerLattice(B)
assert r in L                        # just in case checking that r belongs to L
v = L.coordinate_vector(r) * U
assert v*M == r                  # have we got correct result?
print(v)

If you deal with integer vectors, you need to employ integer lattices rather than linear algebra. Here is our set up:

from sage.modules.free_module_integer import IntegerLattice

M = matrix(ZZ, [[0,0,1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,1,1,1], [0,0,0,1,1,0,1,1,1,1,1,2],[1,0,0,0,0,1,1,1,1,1,1,2], [0, 0, 0, 1, 0, 1, 0, 1, 1, 2, 2, 2], [ 0, 0, 1, 0, 1, 1, 1, 2, 2, 3, 3, 4], [ 0, 0, 1, 1, 0, 1, 2, 3, 3, 5, 5, 6], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 6, 6, 8], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 7, 7, 9], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 8, 7, 11], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 7, 8, 11], [0, 1, 2, 2, 2, 4, 6, 8, 9, 11, 11, 15]])

r = vector(ZZ, [1, 21, 45, 45, 55, 99, 154, 210, 231, 280, 280, 385])

First, you need to find an integer basis B of M and a transformation U between them, using LLL. As a result of LLL, B will have as many rows as M but first few of them can be zero and will not be used in the lattice basis, but basis. Thus we will need to trim all rows of U corresponding that correspond to zero rows of B.

B, U = M.LLL(transformation=True)
assert U*M == B
nz = sum(1 for r in B.rows() if r==0)   # number of zero rows in B
U = U[nz:,:]              # trimming first nz rows of U

Then we construct a the lattice L spanned by B and represent vector r as a linear combination of the basis vectors. vectors of L (which are the nonzero rows of B). It then remains to prepend the zeros to beginning multiply the coordinate vector by U: from the right:

L = IntegerLattice(B)
assert r in L                        # just in case checking that r belongs to L
v = L.coordinate_vector(r) * U
assert v*M == r                  # have we got correct result?
print(v)

If you deal with integer vectors, you need to employ integer lattices rather than linear algebra. Here is our set up:

from sage.modules.free_module_integer import IntegerLattice

M = matrix(ZZ, [[0,0,1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,1,1,1], [0,0,0,1,1,0,1,1,1,1,1,2],[1,0,0,0,0,1,1,1,1,1,1,2], [0, 0, 0, 1, 0, 1, 0, 1, 1, 2, 2, 2], [ 0, 0, 1, 0, 1, 1, 1, 2, 2, 3, 3, 4], [ 0, 0, 1, 1, 0, 1, 2, 3, 3, 5, 5, 6], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 6, 6, 8], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 7, 7, 9], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 8, 7, 11], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 7, 8, 11], [0, 1, 2, 2, 2, 4, 6, 8, 9, 11, 11, 15]])

r = vector(ZZ, [1, 21, 45, 45, 55, 99, 154, 210, 231, 280, 280, 385])

First, you need to find an integer basis B of M and a transformation U between them, using LLL. As a result of LLL, B will have as many rows as M but first few of them can be zero and will not be used in the lattice basis. Thus we will need to trim all zero rows of B and the corresponding rows of U that correspond to zero rows of B.

B, U = M.LLL(transformation=True)
assert U*M == B
nz = sum(1 for r in B.rows() if r==0)   # number of zero rows in B
B = B[nz:,:]              # trimming first nz rows of B
U = U[nz:,:]              # trimming first nz rows of U

Then we construct the lattice L spanned by B and represent vector r as a linear combination of the basis vectors of L (which are the nonzero (i.e. the rows of B). It then remains to multiply the coordinate vector by U from the right:right to get a solution:

L = IntegerLattice(B)
IntegerLattice(B, lll_reduce=False)    # our basis is already reduced, and we don't want it to be altered
assert r in L                        # just in case checking that r belongs to L
v = L.coordinate_vector(r) * U
assert v*M == r                  # have we got correct result?
print(v)

If you deal with integer vectors, you need to employ integer lattices rather than linear algebra. Here is our set up:

from sage.modules.free_module_integer import IntegerLattice

M = matrix(ZZ, [[0,0,1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,1,1,1], [0,0,0,1,1,0,1,1,1,1,1,2],[1,0,0,0,0,1,1,1,1,1,1,2], [0, 0, 0, 1, 0, 1, 0, 1, 1, 2, 2, 2], [ 0, 0, 1, 0, 1, 1, 1, 2, 2, 3, 3, 4], [ 0, 0, 1, 1, 0, 1, 2, 3, 3, 5, 5, 6], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 6, 6, 8], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 7, 7, 9], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 8, 7, 11], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 7, 8, 11], [0, 1, 2, 2, 2, 4, 6, 8, 9, 11, 11, 15]])

r = vector(ZZ, [1, 21, 45, 45, 55, 99, 154, 210, 231, 280, 280, 385])

First, you need to find an integer basis B of M and a transformation U between them, using LLL. As a result of LLL, B will have as many rows as M but first few of them can be zero and will not be used in the lattice basis. Thus we will need to trim all zero rows of B and the corresponding rows of U.

B, U = M.LLL(transformation=True)
assert U*M == B
nz = sum(1 for r in B.rows() if r==0)   # number of zero rows in B
B = B[nz:,:]              # trimming first nz rows of B
U = U[nz:,:]              # trimming first nz rows of U

Then we construct the lattice L spanned by B and represent vector r as a linear combination of the basis vectors of L (i.e. the rows of B). It then remains to multiply the coordinate vector by U from the right to get a solution:

L = IntegerLattice(B, lll_reduce=False)   # our basis is already reduced, reduced and we don't want it to should not be altered
assert r in L                        # just in case checking that r belongs to L
v = L.coordinate_vector(r) * U
assert v*M == r                  # have we got correct result?
print(v)

If you deal with integer vectors, you need to employ integer lattices rather than linear algebra. Here is our set up:

from sage.modules.free_module_integer import IntegerLattice

M = matrix(ZZ, [[0,0,1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,1,1,1], [0,0,0,1,1,0,1,1,1,1,1,2],[1,0,0,0,0,1,1,1,1,1,1,2], [0, 0, 0, 1, 0, 1, 0, 1, 1, 2, 2, 2], [ 0, 0, 1, 0, 1, 1, 1, 2, 2, 3, 3, 4], [ 0, 0, 1, 1, 0, 1, 2, 3, 3, 5, 5, 6], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 6, 6, 8], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 7, 7, 9], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 8, 7, 11], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 7, 8, 11], [0, 1, 2, 2, 2, 4, 6, 8, 9, 11, 11, 15]])

r = vector(ZZ, [1, 21, 45, 45, 55, 99, 154, 210, 231, 280, 280, 385])

First, you need to find an integer basis B of M and a transformation U between them, using LLL. As a result of LLL, B will have as many rows as M but first few of them can be zero and will not be used in the lattice basis. Thus we will need to trim all zero rows of B and the corresponding rows of U.

B, U = M.LLL(transformation=True)
assert U*M == B
nz = sum(1 for r in B.rows() if r==0)   # number of zero rows in B
B = B[nz:,:]              # trimming first nz rows of B
U = U[nz:,:]              # trimming first nz rows of U
assert U*M == B      # the key property of U

Then we construct the lattice L spanned by B and represent vector r as a linear combination of the basis vectors of L (i.e. the rows of B). It then remains to multiply the coordinate vector by U from the right to get a solution:

L = IntegerLattice(B, lll_reduce=False)  # our basis is already reduced and should not be altered
assert r in L                        # just in case checking that r belongs to L
v = L.coordinate_vector(r) * U
assert v*M == r                  # have we got correct result?
print(v)

If you deal with integer vectors, you need to employ integer lattices rather than linear algebra. Here is our set up:

from sage.modules.free_module_integer import IntegerLattice

M = matrix(ZZ, [[0,0,1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,1,1,1], [0,0,0,1,1,0,1,1,1,1,1,2],[1,0,0,0,0,1,1,1,1,1,1,2], [0, 0, 0, 1, 0, 1, 0, 1, 1, 2, 2, 2], [ 0, 0, 1, 0, 1, 1, 1, 2, 2, 3, 3, 4], [ 0, 0, 1, 1, 0, 1, 2, 3, 3, 5, 5, 6], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 6, 6, 8], [ 0, 0, 1, 1, 1, 2, 3, 5, 5, 7, 7, 9], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 8, 7, 11], [ 0, 1, 1, 1, 2, 3, 5, 6, 7, 7, 8, 11], [0, 1, 2, 2, 2, 4, 6, 8, 9, 11, 11, 15]])

r = vector(ZZ, [1, 21, 45, 45, 55, 99, 154, 210, 231, 280, 280, 385])

First, you need to find an integer basis B of M and a transformation U between them, using LLL. As a result of LLL, B will have as many rows as M but first few of them can be zero and will not be used in the lattice basis. Thus we will need to trim all zero rows of B and the corresponding rows of U.

B, U = M.LLL(transformation=True)
nz = sum(1 for r in B.rows() if r==0)   # number of zero rows in B
B = B[nz:,:]   B.delete_rows(range(nz))            # trimming first nz rows of B
U = U[nz:,:]   U.delete_rows(range(nz))            # trimming first nz rows of U
assert U*M == B      # the key property of U

Then we construct the lattice L spanned by B and represent vector r as a linear combination of the basis vectors of L (i.e. the rows of B). It then remains to multiply the coordinate vector by U from the right to get a solution:

L = IntegerLattice(B, lll_reduce=False)  # our basis is already reduced and should not be altered
assert r in L                        # just in case checking that r belongs to L
v = L.coordinate_vector(r) * U
assert v*M == r                  # have we got correct result?
print(v)