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))
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)
def zeros(cls, m, n, gens):
return cls.from_dm(DomainMatrix.zeros((m, n), QQ[gens]))
def _eval_zeros(cls, rows, cols):
rep = DomainMatrix.zeros((rows, cols), ZZ)
return cls._fromrep(rep)