som/basic_som.py
def neighbourhood(self, node1, node2, t):
        """Returns the neighbourhood influence of node1 over node2 at
        iteration t. This uses a gaussian distribution.
        """
        return self._gaussian(node1, node2, t)
        # M-SOM
        # return max(0, 1 - self.distance_squared(node1, node2))
Returns the neighbourhood influence of node1 over node2 at
        iteration t. This uses a gaussian distribution.
        
Returns the neighbourhood influence of node1 over node2 at
iteration t. This uses a gaussian distribution.
Returns the neighbourhood influence of node1 over node2 at iteration t . This uses a gaussian distribution .
def neighbourhood(self, node1, node2, t):
        return self._gaussian(node1, node2, t)
def neighbourhood ( self , node1 , node2 , t ) : return self . _gaussian ( node1 , node2 , t )
Returns the neighbourhood influence of node1 over node2 at
iteration t. This uses a gaussian distribution.
Returns the neighbourhood influence of node1 over node2 at iteration t . This uses a gaussian distribution .
"""Returns the neighbourhood influence of node1 over node2 at
        iteration t. This uses a gaussian distribution.
        """ # M-SOM # return max(0, 1 - self.distance_squared(node1, node2))
self
node1
node2
t