Unpickling methods¶
Python saves objects by providing a pair (f, data) such that f(data)
reconstructs the object. This module collects the loading (_unpickling_ in
Python terminology) functions for Sage’s matroids.
Note
The reason this code was separated out from the classes was to make it
play nice with lazy importing of the Matroid() and matroids
keywords.
AUTHORS:
Rudi Pendavingh, Stefan van Zwam (2013-07-01): initial version
Giorgos Mousa (2024-01-01): add CircuitsMatroid and FlatsMatroid
- sage.matroids.unpickling.unpickle_basis_matroid(version, data)[source]¶
Unpickle a BasisMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; expected to be 0data– tuple(E, R, name, BB)in whichEis the groundset of the matroid,Ris the rank,nameis a custom name, andBBis the bitpacked list of bases, as pickled by Sage’sbitset_pickle.
OUTPUT: matroid
Warning
Users should never call this function directly.
EXAMPLES:
sage: from sage.matroids.advanced import * sage: M = BasisMatroid(matroids.catalog.Vamos()) sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> from sage.matroids.advanced import * >>> M = BasisMatroid(matroids.catalog.Vamos()) >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_binary_matrix(version, data)[source]¶
Reconstruct a
BinaryMatrixobject (internal Sage data structure).Warning
Users should not call this method directly.
EXAMPLES:
sage: from sage.matroids.lean_matrix import * sage: A = BinaryMatrix(2, 5) sage: A == loads(dumps(A)) # indirect doctest True sage: C = BinaryMatrix(2, 2, Matrix(GF(2), [[1, 1], [0, 1]])) sage: C == loads(dumps(C)) True
>>> from sage.all import * >>> from sage.matroids.lean_matrix import * >>> A = BinaryMatrix(Integer(2), Integer(5)) >>> A == loads(dumps(A)) # indirect doctest True >>> C = BinaryMatrix(Integer(2), Integer(2), Matrix(GF(Integer(2)), [[Integer(1), Integer(1)], [Integer(0), Integer(1)]])) >>> C == loads(dumps(C)) True
- sage.matroids.unpickling.unpickle_binary_matroid(version, data)[source]¶
Unpickle a BinaryMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently 0)data– tuple(A, E, B, name)whereAis the representation matrix,Eis the groundset of the matroid,Bis the currently displayed basis, andnameis a custom name.OUTPUT:
BinaryMatroid
Warning
Users should never call this function directly.
EXAMPLES:
sage: M = Matroid(Matrix(GF(2), [[1, 0, 0, 1], [0, 1, 0, 1], ....: [0, 0, 1, 1]])) sage: M == loads(dumps(M)) # indirect doctest True sage: M.rename('U34') sage: loads(dumps(M)) U34
>>> from sage.all import * >>> M = Matroid(Matrix(GF(Integer(2)), [[Integer(1), Integer(0), Integer(0), Integer(1)], [Integer(0), Integer(1), Integer(0), Integer(1)], ... [Integer(0), Integer(0), Integer(1), Integer(1)]])) >>> M == loads(dumps(M)) # indirect doctest True >>> M.rename('U34') >>> loads(dumps(M)) U34
- sage.matroids.unpickling.unpickle_circuit_closures_matroid(version, data)[source]¶
Unpickle a CircuitClosuresMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; expected to be 0data– tuple(E, CC, name)in whichEis the groundset of the matroid,CCis the dictionary of circuit closures, andnameis a custom name.
OUTPUT: matroid
Warning
Users should never call this function directly.
EXAMPLES:
sage: M = matroids.catalog.Vamos() sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> M = matroids.catalog.Vamos() >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_circuits_matroid(version, data)[source]¶
Unpickle a CircuitsMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; expected to be 0data– tuple(E, C, name)in whichEis the groundset of the matroid,Cis the list of circuits , andnameis a custom name.
OUTPUT: matroid
Warning
Users should never call this function directly.
EXAMPLES:
sage: M = matroids.Theta(5) sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> M = matroids.Theta(Integer(5)) >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_dual_matroid(version, data)[source]¶
Unpickle a DualMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; expected to be 0data– tuple(M, name)in whichMis the internal matroid, andnameis a custom name
OUTPUT: matroid
Warning
Users should not call this function directly. Instead, use load/save.
EXAMPLES:
sage: M = matroids.catalog.Vamos().dual() sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> M = matroids.catalog.Vamos().dual() >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_flats_matroid(version, data)[source]¶
Unpickle a
FlatsMatroid.Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; expected to be 0data– tuple(E, F, name)in whichEis the groundset of the matroid,Fis the dictionary of flats, andnameis a custom name.
OUTPUT: matroid
Warning
Users should never call this function directly.
EXAMPLES:
sage: from sage.matroids.flats_matroid import FlatsMatroid sage: M = FlatsMatroid(matroids.catalog.Vamos()) sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> from sage.matroids.flats_matroid import FlatsMatroid >>> M = FlatsMatroid(matroids.catalog.Vamos()) >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_gammoid(version, data)[source]¶
Unpickle a
Gammoid.Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; expected to be 0data– tuple(D, roots, E, name)in whichDis a loopless DiGraph representing the gammoid,rootsis a subset of the vertices,Eis the groundset of the matroid, andnameis a custom name.
OUTPUT: matroid
Warning
Users should never call this function directly.
EXAMPLES:
sage: from sage.matroids.gammoid import Gammoid sage: M = Gammoid(digraphs.TransitiveTournament(5), roots=[3, 4]) sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> from sage.matroids.gammoid import Gammoid >>> M = Gammoid(digraphs.TransitiveTournament(Integer(5)), roots=[Integer(3), Integer(4)]) >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_generic_matrix(version, data)[source]¶
Reconstruct a
GenericMatrixobject (internal Sage data structure).Warning
Users should not call this method directly.
EXAMPLES:
sage: from sage.matroids.lean_matrix import * sage: A = GenericMatrix(2, 5, ring=QQ) sage: A == loads(dumps(A)) # indirect doctest True
>>> from sage.all import * >>> from sage.matroids.lean_matrix import * >>> A = GenericMatrix(Integer(2), Integer(5), ring=QQ) >>> A == loads(dumps(A)) # indirect doctest True
- sage.matroids.unpickling.unpickle_graphic_matroid(version, data)[source]¶
Unpickle a GraphicMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently 0)data– tuple consisting of a SageMath graph and a name
OUTPUT:
GraphicMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: M = Matroid(graphs.DiamondGraph()) # needs sage.graphs sage: M == loads(dumps(M)) # needs sage.graphs True
>>> from sage.all import * >>> M = Matroid(graphs.DiamondGraph()) # needs sage.graphs >>> M == loads(dumps(M)) # needs sage.graphs True
- sage.matroids.unpickling.unpickle_linear_matroid(version, data)[source]¶
Unpickle a LinearMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently 0)data– tuple(A, E, reduced, name)whereAis the representation matrix,Eis the groundset of the matroid,reducedis a boolean indicating whetherAis a reduced matrix, andnameis a custom name.
OUTPUT:
LinearMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: M = Matroid(Matrix(GF(7), [[1, 0, 0, 1, 1], [0, 1, 0, 1, 2], ....: [0, 1, 1, 1, 3]])) sage: M == loads(dumps(M)) # indirect doctest True sage: M.rename('U35') sage: loads(dumps(M)) U35
>>> from sage.all import * >>> M = Matroid(Matrix(GF(Integer(7)), [[Integer(1), Integer(0), Integer(0), Integer(1), Integer(1)], [Integer(0), Integer(1), Integer(0), Integer(1), Integer(2)], ... [Integer(0), Integer(1), Integer(1), Integer(1), Integer(3)]])) >>> M == loads(dumps(M)) # indirect doctest True >>> M.rename('U35') >>> loads(dumps(M)) U35
- sage.matroids.unpickling.unpickle_minor_matroid(version, data)[source]¶
Unpickle a MinorMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer; currently \(0\)data– tuple(M, C, D, name), whereMis the original matroid of which the output is a minor,Cis the set of contractions,Dis the set of deletions, andnameis a custom name.
OUTPUT:
MinorMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: M = matroids.catalog.Vamos().minor('abc', 'g') sage: M == loads(dumps(M)) # indirect doctest True
>>> from sage.all import * >>> M = matroids.catalog.Vamos().minor('abc', 'g') >>> M == loads(dumps(M)) # indirect doctest True
- sage.matroids.unpickling.unpickle_plus_minus_one_matrix(version, data)[source]¶
Reconstruct an
PlusMinusOneMatrixobject (internal Sage data structure).Warning
Users should not call this method directly.
EXAMPLES:
sage: from sage.matroids.lean_matrix import * sage: A = PlusMinusOneMatrix(2, 5) sage: A == loads(dumps(A)) # indirect doctest True
>>> from sage.all import * >>> from sage.matroids.lean_matrix import * >>> A = PlusMinusOneMatrix(Integer(2), Integer(5)) >>> A == loads(dumps(A)) # indirect doctest True
- sage.matroids.unpickling.unpickle_quaternary_matrix(version, data)[source]¶
Reconstruct a
QuaternaryMatrixobject (internal Sage data structure).Warning
Users should not call this method directly.
EXAMPLES:
sage: # needs sage.rings.finite_rings sage: from sage.matroids.lean_matrix import * sage: A = QuaternaryMatrix(2, 5, ring=GF(4, 'x')) sage: A == loads(dumps(A)) # indirect doctest True sage: C = QuaternaryMatrix(2, 2, Matrix(GF(4, 'x'), [[1, 1], [0, 1]])) sage: C == loads(dumps(C)) True
>>> from sage.all import * >>> # needs sage.rings.finite_rings >>> from sage.matroids.lean_matrix import * >>> A = QuaternaryMatrix(Integer(2), Integer(5), ring=GF(Integer(4), 'x')) >>> A == loads(dumps(A)) # indirect doctest True >>> C = QuaternaryMatrix(Integer(2), Integer(2), Matrix(GF(Integer(4), 'x'), [[Integer(1), Integer(1)], [Integer(0), Integer(1)]])) >>> C == loads(dumps(C)) True
- sage.matroids.unpickling.unpickle_quaternary_matroid(version, data)[source]¶
Unpickle a QuaternaryMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently 0)data– tuple(A, E, B, name)whereAis the representation matrix,Eis the groundset of the matroid,Bis the currently displayed basis, andnameis a custom name.
OUTPUT:
TernaryMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: from sage.matroids.advanced import * sage: M = QuaternaryMatroid(Matrix(GF(3), [[1, 0, 0, 1], [0, 1, 0, 1], ....: [0, 0, 1, 1]])) sage: M == loads(dumps(M)) # indirect doctest True sage: M.rename('U34') sage: loads(dumps(M)) U34 sage: M = QuaternaryMatroid(Matrix(GF(4, 'x'), [[1, 0, 1], # needs sage.rings.finite_rings ....: [1, 0, 1]])) sage: loads(dumps(M)).representation() # needs sage.rings.finite_rings [1 0 1] [1 0 1]
>>> from sage.all import * >>> from sage.matroids.advanced import * >>> M = QuaternaryMatroid(Matrix(GF(Integer(3)), [[Integer(1), Integer(0), Integer(0), Integer(1)], [Integer(0), Integer(1), Integer(0), Integer(1)], ... [Integer(0), Integer(0), Integer(1), Integer(1)]])) >>> M == loads(dumps(M)) # indirect doctest True >>> M.rename('U34') >>> loads(dumps(M)) U34 >>> M = QuaternaryMatroid(Matrix(GF(Integer(4), 'x'), [[Integer(1), Integer(0), Integer(1)], # needs sage.rings.finite_rings ... [Integer(1), Integer(0), Integer(1)]])) >>> loads(dumps(M)).representation() # needs sage.rings.finite_rings [1 0 1] [1 0 1]
- sage.matroids.unpickling.unpickle_rational_matrix(version, data)[source]¶
Reconstruct a
sage.matroids.lean_matrix.RationalMatrixobject (internal Sage data structure).Warning
Users should not call this method directly.
EXAMPLES:
sage: from sage.matroids.lean_matrix import RationalMatrix sage: A = RationalMatrix(2, 5) sage: A == loads(dumps(A)) # indirect doctest True
>>> from sage.all import * >>> from sage.matroids.lean_matrix import RationalMatrix >>> A = RationalMatrix(Integer(2), Integer(5)) >>> A == loads(dumps(A)) # indirect doctest True
- sage.matroids.unpickling.unpickle_regular_matroid(version, data)[source]¶
Unpickle a RegularMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently 0)data– tuple(A, E, reduced, name)whereAis the representation matrix,Eis the groundset of the matroid,reducedis a boolean indicating whetherAis a reduced matrix, andnameis a custom name.
OUTPUT:
RegularMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: M = matroids.catalog.R10() sage: M == loads(dumps(M)) # indirect doctest True sage: M.rename('R_{10}') sage: loads(dumps(M)) R_{10}
>>> from sage.all import * >>> M = matroids.catalog.R10() >>> M == loads(dumps(M)) # indirect doctest True >>> M.rename('R_{10}') >>> loads(dumps(M)) R_{10}
- sage.matroids.unpickling.unpickle_ternary_matrix(version, data)[source]¶
Reconstruct a
TernaryMatrixobject (internal Sage data structure).Warning
Users should not call this method directly.
EXAMPLES:
sage: from sage.matroids.lean_matrix import * sage: A = TernaryMatrix(2, 5) sage: A == loads(dumps(A)) # indirect doctest True sage: C = TernaryMatrix(2, 2, Matrix(GF(3), [[1, 1], [0, 1]])) sage: C == loads(dumps(C)) True
>>> from sage.all import * >>> from sage.matroids.lean_matrix import * >>> A = TernaryMatrix(Integer(2), Integer(5)) >>> A == loads(dumps(A)) # indirect doctest True >>> C = TernaryMatrix(Integer(2), Integer(2), Matrix(GF(Integer(3)), [[Integer(1), Integer(1)], [Integer(0), Integer(1)]])) >>> C == loads(dumps(C)) True
- sage.matroids.unpickling.unpickle_ternary_matroid(version, data)[source]¶
Unpickle a TernaryMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently 0)data– tuple(A, E, B, name)whereAis the representation matrix,Eis the groundset of the matroid,Bis the currently displayed basis, andnameis a custom name.
OUTPUT:
TernaryMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: from sage.matroids.advanced import * sage: M = TernaryMatroid(Matrix(GF(3), [[1, 0, 0, 1], [0, 1, 0, 1], ....: [0, 0, 1, 1]])) sage: M == loads(dumps(M)) # indirect doctest True sage: M.rename('U34') sage: loads(dumps(M)) U34
>>> from sage.all import * >>> from sage.matroids.advanced import * >>> M = TernaryMatroid(Matrix(GF(Integer(3)), [[Integer(1), Integer(0), Integer(0), Integer(1)], [Integer(0), Integer(1), Integer(0), Integer(1)], ... [Integer(0), Integer(0), Integer(1), Integer(1)]])) >>> M == loads(dumps(M)) # indirect doctest True >>> M.rename('U34') >>> loads(dumps(M)) U34
- sage.matroids.unpickling.unpickle_transversal_matroid(version, data)[source]¶
Unpickle a TransversalMatroid.
Pickling is Python’s term for the loading and saving of objects. Functions like these serve to reconstruct a saved object. This all happens transparently through the
loadandsavecommands, and you should never have to call this function directly.INPUT:
version– integer (currently \(0\))data– tuple(sets, groundset, name), wheregroundsetis afrozensetof elements, andsetsis afrozensetof tuples consisting of a name for the set, and afrozensetof groundset elements it contains.
OUTPUT:
TransversalMatroidWarning
Users should never call this function directly.
EXAMPLES:
sage: from sage.matroids.transversal_matroid import * sage: sets = [range(6)] * 3 sage: M = TransversalMatroid(sets) sage: M == loads(dumps(M)) True sage: M.rename('U36') sage: loads(dumps(M)) U36
>>> from sage.all import * >>> from sage.matroids.transversal_matroid import * >>> sets = [range(Integer(6))] * Integer(3) >>> M = TransversalMatroid(sets) >>> M == loads(dumps(M)) True >>> M.rename('U36') >>> loads(dumps(M)) U36