def evaluate_builtin(self, Z, A):
result_builtin = NumpyMatrix({"u": self.N}, {"u": self.N})
for j in range(self.N):
A_Z_j = A * Z[j].vector()
for i in range(self.N):
result_builtin[i, j] = Z[i].vector().inner(A_Z_j)
return result_builtin
def evaluate_builtin(self, S, A):
result_builtin = NumpyMatrix(self.N, self.N)
for j in range(self.N):
A_S_j = A * S[j].vector()
for i in range(self.N):
result_builtin[i, j] = S[i].vector().inner(A_S_j)
return result_builtin
def RandomNumpyMatrix(N, M):
m = NumpyMatrix(N, M)
if COMM_WORLD.rank == 0:
m[:, :] = _rand(N, M)
COMM_WORLD.Bcast(m.content, root=0)
return m
def RandomNumpyMatrix(N, M):
m = NumpyMatrix(N, M)
m[:, :] = _rand(N, M)
return m