def __init__(self, K, dt_max=10.0,
                 bkgd_hypers={},
                 impulse_hypers={},
                 weight_hypers={},
                 network=None, network_hypers={}):
        self.K      = K
        self.dt_max = dt_max

        # Initialize the bias
        # Use the given basis hyperparameters
        self.bkgd_hypers = copy.deepcopy(self._default_bkgd_hypers)
        self.bkgd_hypers.update(bkgd_hypers)
        from pyhawkes.internals.bias import ContinuousTimeGammaBias
        self.bias_model = ContinuousTimeGammaBias(self, self.K, **self.bkgd_hypers)

        # Initialize the impulse response model
        self.impulse_hypers = copy.deepcopy(self._default_impulse_hypers)
        self.impulse_hypers.update(impulse_hypers)
        from pyhawkes.internals.impulses import ContinuousTimeImpulseResponses
        self.impulse_model = \
            ContinuousTimeImpulseResponses(self, **self.impulse_hypers)

        # Initialize the network model
        # Initialize the network model
        if network is not None:
            assert network.K == self.K
            self.network = network
        else:
            # Use the given network hyperparameters
            self.network_hypers = copy.deepcopy(self._default_network_hypers)
            self.network_hypers.update(network_hypers)
            self.network = \
                self._network_class(K=self.K, **self.network_hypers)

        # Initialize the weight model
        from pyhawkes.internals.weights import SpikeAndSlabContinuousTimeGammaWeights
        self.weight_hypers = copy.deepcopy(self._default_weight_hypers)
        self.weight_hypers.update(weight_hypers)
        self.weight_model = \
            SpikeAndSlabContinuousTimeGammaWeights(self,  **self.weight_hypers)

        # Initialize the data list to empty
        self.data_list = []


    # Expose basic variables
Initialize a discrete time network Hawkes model with K processes.
dataset/ETHPy150Open slinderman/pyhawkes/pyhawkes/models.py/ContinuousTimeNetworkHawkesModel.__init__