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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer, expected to be 0

  • data – a tuple (E, R, name, BB) in which E is the groundset of the matroid, R is the rank, name is a custom name, and BB is the bitpacked list of bases, as pickled by Sage’s bitset_pickle.

OUTPUT:

A 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 BinaryMatrix object (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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer (currently 0).

  • data – a tuple (A, E, B, name) where A is the representation matrix, E is the groundset of the matroid, B is the currently displayed basis, and name is a custom name.

    OUTPUT:

    A BinaryMatroid instance.

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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer, expected to be 0

  • data – a tuple (E, CC, name) in which E is the groundset of the matroid, CC is the dictionary of circuit closures, and name is a custom name.

OUTPUT:

A 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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer, expected to be 0

  • data – a tuple (E, C, name) in which E is the groundset of the matroid, C is the list of circuits , and name is a custom name.

OUTPUT:

A 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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer, expected to be 0

  • data – a tuple (M, name) in which M is the internal matroid, and name is a custom name.

OUTPUT:

A 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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer, expected to be 0

  • data – a tuple (E, F, name) in which E is the groundset of the matroid, F is the dictionary of flats, and name is a custom name.

OUTPUT:

A 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_generic_matrix(version, data)[source]#

Reconstruct a GenericMatrix object (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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer (currently 0).

  • data – a tuple consisting of a SageMath graph and a name.

OUTPUT:

A GraphicMatroid instance.

Warning

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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer (currently 0).

  • data – a tuple (A, E, reduced, name) where A is the representation matrix, E is the groundset of the matroid, reduced is a boolean indicating whether A is a reduced matrix, and name is a custom name.

OUTPUT:

A LinearMatroid instance.

Warning

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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer, currently \(0\).

  • data – a tuple (M, C, D, name), where M is the original matroid of which the output is a minor, C is the set of contractions, D is the set of deletions, and name is a custom name.

OUTPUT:

A MinorMatroid instance.

Warning

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 PlusMinusOneMatrix object (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 QuaternaryMatrix object (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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer (currently 0).

  • data – a tuple (A, E, B, name) where A is the representation matrix, E is the groundset of the matroid, B is the currently displayed basis, and name is a custom name.

OUTPUT:

A TernaryMatroid instance.

Warning

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.RationalMatrix object (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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer (currently 0).

  • data – a tuple (A, E, reduced, name) where A is the representation matrix, E is the groundset of the matroid, reduced is a boolean indicating whether A is a reduced matrix, and name is a custom name.

OUTPUT:

A RegularMatroid instance.

Warning

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 TernaryMatrix object (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 load and save commands, and you should never have to call this function directly.

INPUT:

  • version – an integer (currently 0).

  • data – a tuple (A, E, B, name) where A is the representation matrix, E is the groundset of the matroid, B is the currently displayed basis, and name is a custom name.

OUTPUT:

A TernaryMatroid instance.

Warning

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