fix behavior of iddata initial conditions

Author: rssalessio

test/test_reference.py

@@ -52,14 +52,15 @@ def test_virtualReference(self):
         t,y = scipysig.dlsim(sys, u, t)
         y = y[:,0]
         data = iddata(y,u,t_step,[0,0])
-        #wrong initial conditions
-        with self.assertRaises(ValueError):
-            virtualReference(data, num, den)
+        
+        r, _ = virtualReference(data, num, den)
+        for i in range(len(r)):
+            self.assertTrue(np.isclose(r[i], u[i]))
 
-        #wrong initial conditions
         data = iddata(y,u,t_step,[0,0,0])
-        with self.assertRaises(ValueError):
-            virtualReference(data, num, den)
+        r, _ = virtualReference(data, num, den)
+        for i in range(len(r)):
+            self.assertTrue(np.isclose(r[i], u[i]))
 
         #test good data, first order
         data = iddata(y,u,t_step,[0])
@@ -80,3 +81,4 @@ def test_virtualReference(self):
         r, _ = virtualReference(data, num, den)
         for i in range(len(r)):
             self.assertTrue(np.isclose(r[i], u[i]))
+ 

test/test_vrft.py

@@ -78,10 +78,10 @@ def test_iv(self):
                 ExtendedTF([1], [1,0,0,0], dt=t_step),
                 ExtendedTF([1, 0], [1,1], dt=t_step)]
 
-        ##import pdb
+        #import pdb
         #pdb.set_trace()
 
-        # theta, _, loss, _ = compute_vrft(data, refModel, control, prefilter, iv=True)
+        #theta, _, loss, _ = compute_vrft(data, refModel, control, prefilter, iv=True)
 
 
 

vrft/iddata.py

@@ -61,10 +61,9 @@ def __init__(self, y: np.ndarray,
         else:
             self.y0 = np.array(y0) if not isinstance(y0, np.ndarray) else np.array([y0]).flatten()
 
-            if self.y0.size == 0:
+            if self.y0.size == 0 or self.y0.ndim == None or \
+                    np.allclose(self.y0, 0.):
                 self.y0 = None
-            elif self.y0.ndim == 0:
-                self.y0 = np.expand_dims(self.y0, axis=0)
 
 
     def check(self):

vrft/vrft_algo.py

@@ -38,12 +38,13 @@ def virtualReference(data: iddata, num: np.ndarray, den: np.ndarray) -> np.ndarr
     offset_M = len(num) - M - 1
     offset_N = len(den) - N - 1
 
-    lag = N - M  #number of initial conditions
+    lag = N - M  # number of initial conditions
+    y0 = data.y0
 
-    if (lag > 0 and data.y0 is None):
-        raise ValueError("Wrong initial condition.")
+    if y0 is None:
+        y0 = [0.] * lag
 
-    if (lag != len(data.y0)):
+    if y0 is not None and (lag != len(y0)):
         raise ValueError("Wrong initial condition size.")
 
     reference = np.zeros_like(data.y)
@@ -60,7 +61,7 @@ def virtualReference(data: iddata, num: np.ndarray, den: np.ndarray) -> np.ndarr
             index = k + i - N
             if (index < 0):
                 left_side += den[offset_N +
-                                 abs(i - N)] * data.y0[abs(index) - 1]
+                                 abs(i - N)] * y0[abs(index) - 1]
             else:
                 left_side += den[offset_N + abs(i - N)] * (
                     data.y[index] if index < L else 0)