neuroprob/likelihoods.py
def sample(self, rate, neuron=None, XZ=None):
        """
        Sample activity trains [trial, neuron, timestep]
        """
        neuron = self._validate_neuron(neuron)
        act = rate + torch.exp(self.log_var).data.sqrt().cpu().numpy()*np.random.randn((rate.shape[0], len(neuron), rate.shape[-1]))
        return act

        Sample activity trains [trial, neuron, timestep]
        
Sample activity trains [trial, neuron, timestep]
Sample activity trains [ trial neuron timestep ]
def sample(self, rate, neuron=None, XZ=None):
        neuron = self._validate_neuron(neuron)
        act = rate + torch.exp(self.log_var).data.sqrt().cpu().numpy()*np.random.randn((rate.shape[0], len(neuron), rate.shape[-1]))
        return act
def sample ( self , rate , neuron = None , XZ = None ) : neuron = self . _validate_neuron ( neuron ) act = rate + torch . exp ( self . log_var ) . data . sqrt ( ) . cpu ( ) . numpy ( ) * np . random . randn ( ( rate . shape [ 0 ] , len ( neuron ) , rate . shape [ - 1 ] ) ) return act
Sample activity trains [trial, neuron, timestep]
Sample activity trains [ trial neuron timestep ]
"""
        Sample activity trains [trial, neuron, timestep]
        """
self
rate
neuron
XZ