def set_parameters(self, params):
        A, W, beta, lambda0, c, p, v, m = params
        K, B, = self.K, self.basis.B

        assert isinstance(A, np.ndarray) and A.shape == (K,K), \
            "A must be a KxK adjacency matrix"

        assert isinstance(W, np.ndarray) and W.shape == (K,K) \
               and np.amin(W) >= 0, \
            "W must be a KxK weight matrix"

        assert isinstance(beta, np.ndarray) and beta.shape == (K,K,B) and \
               np.allclose(beta.sum(axis=2), 1.0), \
            "beta must be a KxKxB impulse response array"

        assert isinstance(lambda0, np.ndarray) and lambda0.shape == (K,) \
               and np.amin(lambda0) >=0, \
            "lambda0 must be a K-vector of background rates"

        self.weight_model.A = A
        self.weight_model.W = W
        self.impulse_model.g = beta
        self.bias_model.lambda0 = lambda0
        self.network.c = c
        self.network.p = p
        self.network.v = v
        self.network.m = m
Checks whether this version is newer or as new as the build that it
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/models.py/_DiscreteTimeNetworkHawkesModelBase.set_parameters--crossover with--dataset/ETHPy150Open rwl/muntjac/muntjac/demo/sampler/Feature.py/Version.isNew