def test_inputshift(self):
"""input shift factors of different formats should be correctly interpreted or rejected"""
esn = ESN(N_in, N_out, input_shift=1)
self.assertTrue(np.all(1 + self.X == esn._scale_inputs(self.X)))
esn.fit(self.X, self.y)
esn.predict(self.Xp)
esn = ESN(N_in, N_out, input_shift=[1] * N_in)
self.assertTrue(np.all(1 + self.X == esn._scale_inputs(self.X)))
esn.fit(self.X, self.y)
esn.predict(self.Xp)
esn = ESN(N_in, N_out, input_shift=np.array([1] * N_in))
self.assertTrue(np.all(1 + self.X == esn._scale_inputs(self.X)))
esn.fit(self.X, self.y)
esn.predict(self.Xp)
with self.assertRaises(ValueError):
esn = ESN(N_in, N_out, input_shift=[1] * (N_in + 1))
with self.assertRaises(ValueError):
esn = ESN(N_in, N_out, input_shift=np.array([[1] * N_in]))
def test_inputshift(self):
"""input shift factors of different formats should be correctly interpreted or rejected"""
esn = ESN(N_in,N_out,input_shift=1)
self.assertTrue(np.all(1+self.X == esn._scale_inputs(self.X)))
esn.fit(self.X,self.y)
esn.predict(self.Xp)
esn = ESN(N_in,N_out,input_shift=[1]*N_in)
self.assertTrue(np.all(1+self.X == esn._scale_inputs(self.X)))
esn.fit(self.X,self.y)
esn.predict(self.Xp)
esn = ESN(N_in,N_out,input_shift=np.array([1]*N_in))
self.assertTrue(np.all(1+self.X == esn._scale_inputs(self.X)))
esn.fit(self.X,self.y)
esn.predict(self.Xp)
with self.assertRaises(ValueError):
esn = ESN(N_in,N_out,input_shift=[1]*(N_in+1))
with self.assertRaises(ValueError):
esn = ESN(N_in,N_out,input_shift=np.array([[1]*N_in]))
