hetero_synapse.py 文件源码

def __init__(self, systems, dt=None, elementwise=False, method='zoh'):
        if not is_iterable(systems) or isinstance(systems, LinearSystem):
            systems = [systems]
        self.systems = systems
        self.dt = dt
        self.elementwise = elementwise

        self.A = []
        self.B = []
        self.C = []
        self.D = []
        for sys in systems:
            sys = LinearSystem(sys)
            if dt is not None:
                sys = cont2discrete(sys, dt, method=method)
            elif sys.analog:
                raise ValueError(
                    "system (%s) must be digital if not given dt" % sys)

            A, B, C, D = sys.ss
            self.A.append(A)
            self.B.append(B)
            self.C.append(C)
            self.D.append(D)

        # TODO: If all of the synapses are single order, than A is diagonal
        # and so np.dot(self.A, self._x) is trivial. But perhaps
        # block_diag is already optimized for this.

        # Note: ideally we could put this into CCF to reduce the A mapping
        # to a single dot product and a shift operation. But in general
        # since this is MIMO it is not controllable from a single input.
        # Instead we might want to consider balanced reduction to
        # improve efficiency.
        self.A = block_diag(*self.A)
        self.B = block_diag(*self.B) if elementwise else np.vstack(self.B)
        self.C = block_diag(*self.C)
        self.D = block_diag(*self.D) if elementwise else np.vstack(self.D)
        # TODO: shape validation

        self._x = np.zeros(len(self.A))[:, None]