Ejemplo n.º 1
0
def test_EndomorphismRing_represent():
    T = Poly(cyclotomic_poly(5, x))
    A = PowerBasis(T)
    R = A.endomorphism_ring()
    phi = R.inner_endomorphism(A(1))
    col = R.represent(phi)
    assert col.transpose() == DomainMatrix(
        [[0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, -1, -1, -1, -1]], (1, 16), ZZ)

    B = A.submodule_from_matrix(DomainMatrix.zeros((4, 0), ZZ))
    S = B.endomorphism_ring()
    psi = S.inner_endomorphism(A(1))
    col = S.represent(psi)
    assert col == DomainMatrix([], (0, 0), ZZ)

    raises(NotImplementedError, lambda: R.represent(3.14))
Ejemplo n.º 2
0
    def fill(self, value):
        """Fill self with the given value.

        Notes
        =====

        Unless many values are going to be deleted (i.e. set to zero)
        this will create a matrix that is slower than a dense matrix in
        operations.

        Examples
        ========

        >>> from sympy.matrices import SparseMatrix
        >>> M = SparseMatrix.zeros(3); M
        Matrix([
        [0, 0, 0],
        [0, 0, 0],
        [0, 0, 0]])
        >>> M.fill(1); M
        Matrix([
        [1, 1, 1],
        [1, 1, 1],
        [1, 1, 1]])

        See Also
        ========

        zeros
        ones
        """
        value = _sympify(value)
        if not value:
            self._rep = DomainMatrix.zeros(self.shape, EXRAW)
        else:
            elements_dod = {
                i: {j: value
                    for j in range(self.cols)}
                for i in range(self.rows)
            }
            self._rep = DomainMatrix(elements_dod, self.shape, EXRAW)
Ejemplo n.º 3
0
 def zeros(cls, m, n, gens):
     return cls.from_dm(DomainMatrix.zeros((m, n), QQ[gens]))
Ejemplo n.º 4
0
 def _eval_zeros(cls, rows, cols):
     rep = DomainMatrix.zeros((rows, cols), ZZ)
     return cls._fromrep(rep)