def __init__(self, n_terms=<NUM_LIT:3>, initial_y=None):
self.n_terms = n_terms<EOL>self.num_parameters = <NUM_LIT:3> * self.n_terms + <NUM_LIT:1><EOL>self.psi = np.ones((self.n_terms, <NUM_LIT:3>))<EOL>super(TanhFunction, self).__init__(name='<STR_LIT>')<EOL>self.psi = Param('<STR_LIT>', self.psi)<EOL>self.psi[:, :<NUM_LIT:2>].constrain_positive()<EOL>self.d = Param('<STR_LIT:%s>' % ('<STR_LIT:d>'), <NUM_LIT:1.0>, Logexp())<EOL>self.link_parameter(self.psi)<EOL>self.link_parameter(self.d)<EOL>self.initial_y = initial_y<EOL>
n_terms specifies the number of tanh terms to be used