Expand unit tests, add info to doc string for parameters and returns, rename is_passive to ispassive for naming convention consistency. Autoformat to pep8.

Mark · Mark · commit d6916c661a77 · 2022-06-14T06:46:56.000-05:00
diff --git a/control/passivity.py b/control/passivity.py
@@ -10,18 +10,27 @@
 except ImportError as e:
     cvx = None
 
-lmi_epsilon = 1e-12
 
-def is_passive(sys):
+def ispassive(sys):
     '''
-    Indicates if a linear time invariant system is passive
+    Indicates if a linear time invariant (LTI) system is passive
 
     Constructs a linear matrix inequality and a feasibility optimization
     such that if a solution exists, the system is passive.
 
     The source for the algorithm is: 
     McCourt, Michael J., and Panos J. Antsaklis. 
         "Demonstrating passivity and dissipativity using computational methods." ISIS 8 (2013).
+
+    Parameters
+    ----------
+    sys: A continuous LTI system
+        System to be checked.
+
+    Returns
+    -------
+    bool: 
+        The input system passive.
     '''
     if cvx is None:
         raise ModuleNotFoundError("cvxopt required for passivity module")
@@ -31,9 +40,9 @@ def is_passive(sys):
     C = sys.C
     D = sys.D
 
-    #account for strictly proper systems
-    [n,m] = D.shape
-    D = D + np.nextafter(0,1)*np.eye(n,m)
+    # account for strictly proper systems
+    [n, m] = D.shape
+    D = D + np.nextafter(0, 1)*np.eye(n, m)
 
     def make_LMI_matrix(P):
         V = np.vstack((
diff --git a/control/tests/passivity_test.py b/control/tests/passivity_test.py
@@ -7,30 +7,57 @@
 from control import ss, passivity
 from control.tests.conftest import cvxoptonly
 
+
 @cvxoptonly
-def test_is_passive():
+def test_ispassive():
     A = numpy.array([[0, 1], [-2, -2]])
     B = numpy.array([[0], [1]])
     C = numpy.array([[-1, 2]])
     D = numpy.array([[1.5]])
     sys = ss(A, B, C, D)
 
     # happy path is passive
-    assert(passivity.is_passive(sys))
+    assert(passivity.ispassive(sys))
 
     # happy path not passive
     D = -D
     sys = ss(A, B, C, D)
 
-    assert(not passivity.is_passive(sys))
+    assert(not passivity.ispassive(sys))
+
+
+@cvxoptonly
+def test_ispassive_edge_cases():
+    A = numpy.array([[0, 1], [-2, -2]])
+    B = numpy.array([[0], [1]])
+    C = numpy.array([[-1, 2]])
+    D = numpy.array([[1.5]])
 
-    #edge cases of D=0 boundary condition
-    B *= 0
-    C *= 0
     D *= 0
+
+    # strictly proper
     sys = ss(A, B, C, D)
-    assert(passivity.is_passive(sys))
+    assert(passivity.ispassive(sys))
 
+    # ill conditioned
     A = A*1e12
     sys = ss(A, B, C, D)
-    assert(passivity.is_passive(sys))
+    assert(passivity.ispassive(sys))
+
+    # different combinations of zero A,B,C,D are 0
+    B *= 0
+    C *= 0
+    assert(passivity.ispassive(sys))
+
+    A *= 0
+    B = numpy.array([[0], [1]])
+    C = numpy.array([[-1, 2]])
+    D = numpy.array([[1.5]])
+    assert(passivity.ispassive(sys))
+
+    B *= 0
+    C *= 0
+    assert(passivity.ispassive(sys))
+
+    A *= 0
+    assert(passivity.ispassive(sys))
