BugFix: allow empty (no input or output) StateSpace objects.

roryyorke · roryyorke · commit e640b1785739 · 2016-09-19T20:12:59.000+02:00
Conflicts:
	control/tests/statesp_test.py
diff --git a/control/statesp.py b/control/statesp.py
@@ -52,7 +52,7 @@
 
 import numpy as np
 from numpy import all, angle, any, array, asarray, concatenate, cos, delete, \
-    dot, empty, exp, eye, matrix, ones, pi, poly, poly1d, roots, shape, sin, \
+    dot, empty, exp, eye, ones, pi, poly, poly1d, roots, shape, sin, \
     zeros, squeeze
 from numpy.random import rand, randn
 from numpy.linalg import solve, eigvals, matrix_rank
@@ -66,6 +66,19 @@
 
 __all__ = ['StateSpace', 'ss', 'rss', 'drss', 'tf2ss', 'ssdata']
 
+
+def _matrix(a):
+    """_matrix(a) -> numpy.matrix
+    a - passed to numpy.matrix
+    Wrapper around numpy.matrix; unlike that function,  _matrix([]) will be 0x0
+    """
+    from numpy import matrix
+    am = matrix(a)
+    if (1,0) == am.shape:
+        am.shape = (0,0)
+    return am
+
+
 class StateSpace(LTI):
     """A class for representing state-space models
 
@@ -122,7 +135,7 @@ def __init__(self, *args):
         else:
             raise ValueError("Needs 1 or 4 arguments; received %i." % len(args))
 
-        A, B, C, D = [matrix(M) for M in (A, B, C, D)]
+        A, B, C, D = [_matrix(M) for M in (A, B, C, D)]
 
         # TODO: use super here?
         LTI.__init__(self, inputs=D.shape[1], outputs=D.shape[0], dt=dt)
@@ -327,8 +340,9 @@ def __rmul__(self, other):
             return _convertToStateSpace(other) * self
 
         # try to treat this as a matrix
+        # TODO: doesn't _convertToStateSpace do this anyway?
         try:
-            X = matrix(other)
+            X = _matrix(other)
             C = X * self.C
             D = X * self.D
             return StateSpace(self.A, self.B, C, D, self.dt)
@@ -686,11 +700,9 @@ def _convertToStateSpace(sys, **kw):
 
     # If this is a matrix, try to create a constant feedthrough
     try:
-        D = matrix(sys)
-        outputs, inputs = D.shape
-
-        return StateSpace(0., zeros((1, inputs)), zeros((outputs, 1)), D)
-    except Exception(e):
+        D = _matrix(sys)
+        return StateSpace([], [], [], D)
+    except Exception as e:
         print("Failure to assume argument is matrix-like in" \
             " _convertToStateSpace, result %s" % e)
 
diff --git a/control/tests/statesp_test.py b/control/tests/statesp_test.py
@@ -253,6 +253,7 @@ def test_scalarStaticGain(self):
         g6 = g1.append(g2)
         np.testing.assert_array_equal(np.diag([2,3]),g6.D)
 
+
     def test_matrixStaticGain(self):
         """Regression: can we create matrix static gains?"""
         d1 = np.matrix([[1,2,3],[4,5,6]])
@@ -297,6 +298,29 @@ def test_BadEmptyMatrices(self):
         self.assertRaises(ValueError,StateSpace, [],  [],  [1], [1])
         self.assertRaises(ValueError,StateSpace, [1], [1], [1], [])
 
+
+    def test_Empty(self):
+        """Regression: can we create an empty StateSpace object?"""
+        g1=StateSpace([],[],[],[])
+        self.assertEqual(0,g1.states)
+        self.assertEqual(0,g1.inputs)
+        self.assertEqual(0,g1.outputs)
+
+
+    def test_MatrixToStateSpace(self):
+        """_convertToStateSpace(matrix) gives ss([],[],[],D)"""
+        D = np.matrix([[1,2,3],[4,5,6]])
+        g = _convertToStateSpace(D)
+        def empty(shape):
+            m = np.matrix([])
+            m.shape = shape
+            return m
+        np.testing.assert_array_equal(empty((0,0)), g.A)
+        np.testing.assert_array_equal(empty((0,D.shape[1])), g.B)
+        np.testing.assert_array_equal(empty((D.shape[0],0)), g.C)
+        np.testing.assert_array_equal(D,g.D)
+
+        
 class TestRss(unittest.TestCase):
     """These are tests for the proper functionality of statesp.rss."""
 
