support/models.py
def evalDist(self, w):
        '''
        The l2 norm of the difference between the estimate
        vector and the true underlying model vector.
        '''
        return np.linalg.norm(w-self.w_true)

        The l2 norm of the difference between the estimate
        vector and the true underlying model vector.
        
The l2 norm of the difference between the estimate
vector and the true underlying model vector.
The l2 norm of the difference between the estimate vector and the true underlying model vector .
def evalDist(self, w):
        return np.linalg.norm(w-self.w_true)
def evalDist ( self , w ) : return np . linalg . norm ( w - self . w_true )
The l2 norm of the difference between the estimate
vector and the true underlying model vector.
The l2 norm of the difference between the estimate vector and the true underlying model vector .
'''
        The l2 norm of the difference between the estimate
        vector and the true underlying model vector.
        '''
self
w