python-control · murrayrm · Jan 2, 2018 · Feb 17, 2017 · Feb 17, 2017 · Feb 18, 2017
diff --git a/.gitignore b/.gitignore
@@ -9,6 +9,7 @@ __conda_*.txt
 record.txt
 build.log
 *.egg-info/
+.eggs/
 .coverage
 doc/_build
 doc/generated
@@ -18,3 +19,7 @@ examples/.ipynb_checkpoints/
 .project
 Untitled*.ipynb
 *.idea/
+
+# Files created by or for emacs (RMM, 29 Dec 2017)
+*~
+TAGS
diff --git a/control/tests/input_element_int_test.py b/control/tests/input_element_int_test.py
@@ -0,0 +1,54 @@
+# input_element_int_test.py
+#
+# Author: Kangwon Lee (kangwonlee)
+# Date: 22 Oct 2017
+#
+# Unit tests contributed as part of PR #158, "SISO tf() may not work
+# with numpy arrays with numpy.int elements"
+#
+# Modified:
+# * 29 Dec 2017, RMM - updated file name and added header
+
+import unittest
+import numpy as np
+import control as ctl
+
+class TestTfInputIntElement(unittest.TestCase):
+    # currently these do not pass
+    def test_tf_den_with_numpy_int_element(self):
+        num = 1
+        den = np.convolve([1, 2, 1], [1, 1, 1])
+
+        sys = ctl.tf(num, den)
+
+        self.assertAlmostEqual(1.0, ctl.dcgain(sys))
+
+    def test_tf_num_with_numpy_int_element(self):
+        num = np.convolve([1], [1, 1])
+        den = np.convolve([1, 2, 1], [1, 1, 1])
+
+        sys = ctl.tf(num, den)
+
+        self.assertAlmostEqual(1.0, ctl.dcgain(sys))
+
+    # currently these pass
+    def test_tf_input_with_int_element_works(self):
+        num = 1
+        den = np.convolve([1.0, 2, 1], [1, 1, 1])
+
+        sys = ctl.tf(num, den)
+
+        self.assertAlmostEqual(1.0, ctl.dcgain(sys))
+
+    def test_ss_input_with_int_element(self):
+        ident = np.matrix(np.identity(2), dtype=int)
+        a = np.matrix([[0, 1],
+                       [-1, -2]], dtype=int) * ident
+        b = np.matrix([[0],
+                       [1]], dtype=int)
+        c = np.matrix([[0, 1]], dtype=int)
+        d = 0
+
+        sys = ctl.ss(a, b, c, d)
+        sys2 = ctl.ss2tf(sys)
+        self.assertAlmostEqual(ctl.dcgain(sys), ctl.dcgain(sys2))
diff --git a/control/tests/xferfcn_input_test.py b/control/tests/xferfcn_input_test.py
@@ -0,0 +1,261 @@
+#!/usr/bin/env python
+#
+# xferfcn_input_test.py - test inputs to TransferFunction class
+# jed-frey, 18 Feb 2017 (based on xferfcn_test.py)
+
+import unittest
+import numpy as np
+
+from numpy import int, int8, int16, int32, int64
+from numpy import float, float16, float32, float64, float128
+from numpy import all, ndarray, array
+
+from control.xferfcn import _cleanPart
+
+class TestXferFcnInput(unittest.TestCase):
+    """These are tests for functionality of cleaning and validating 
+    XferFucnInput."""
+
+    # Tests for raising exceptions.
+    def testBadInputType(self):
+        """Give the part cleaner invalid input type."""
+
+        self.assertRaises(TypeError, _cleanPart, [[0., 1.], [2., 3.]])
+
+    def testBadInputType2(self):
+        """Give the part cleaner another invalid input type."""
+        self.assertRaises(TypeError, _cleanPart, [1,"a"])
+
+    def testScalar(self):
+        """Test single scalar value."""
+        num = 1
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testListScalar(self):
+        """Test single scalar value in list."""
+        num = [1]
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testTupleScalar(self):
+        """Test single scalar value in tuple."""
+        num = (1)
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testList(self):
+        """Test multiple values in a list."""
+        num = [1, 2]
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0, 2.0], dtype=float))
+
+    def testTuple(self):
+        """Test multiple values in tuple."""
+        num = (1, 2)
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0, 2.0], dtype=float))
+
+    def testAllScalarTypes(self):
+        """Test single scalar value for all valid data types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = dtype(1)
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testNpArray(self):
+        """Test multiple values in numpy array."""
+        num = np.array([1, 2])
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0, 2.0], dtype=float))
+
+    def testAllNumpyArrayTypes(self):      
+        """Test scalar value in numpy array of ndim=0 for all data types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = np.array(1, dtype=dtype)
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testAllNumpyArrayTypes2(self):      
+        """Test numpy array for all types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = np.array([1, 2], dtype=dtype)
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 2.0], dtype=float))
+
+    def testListAllTypes(self):
+        """Test list of a single value for all data types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = [dtype(1)]
+            num_ = _cleanPart(num)
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testListAllTypes2(self):
+        """List of list of numbers of all data types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = [dtype(1), dtype(2)]
+            num_ = _cleanPart(num)
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 2.0], dtype=float))
+
+    def testTupleAllTypes(self):
+        """Test tuple of a single value for all data types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = (dtype(1),)
+            num_ = _cleanPart(num)
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testTupleAllTypes2(self):
+        """Test tuple of a single value for all data types."""
+        for dtype in [int, int8, int16, int32, int64, float, float16, float32, float64, float128]:
+            num = (dtype(1), dtype(2))
+            num_ = _cleanPart(num)
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1, 2], dtype=float))
+
+    def testListListListInt(self):
+        """ Test an int in a list of a list of a list."""
+        num = [[[1]]]
+        num_ = _cleanPart(num)
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testListListListFloat(self):
+        """ Test a float in a list of a list of a list."""
+        num = [[[1.0]]]
+        num_ = _cleanPart(num)
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0], dtype=float))
+
+    def testListListListInts(self):
+        """Test 2 lists of ints in a list in a list."""
+        num = [[[1,1],[2,2]]]
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+        np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testListListListFloats(self):
+        """Test 2 lists of ints in a list in a list."""
+        num = [[[1.0,1.0],[2.0,2.0]]]
+        num_ = _cleanPart(num)
+
+        assert isinstance(num_, list)
+        assert np.all([isinstance(part, list) for part in num_])
+        np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+        np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testListListArray(self):
+        """List of list of numpy arrays for all valid types."""
+        for dtype in int, int8, int16, int32, int64, float, float16, float32, float64, float128:
+            num = [[array([1,1], dtype=dtype),array([2,2], dtype=dtype)]]
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+            np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testTupleListArray(self):
+        """Tuple of list of numpy arrays for all valid types."""
+        for dtype in int, int8, int16, int32, int64, float, float16, float32, float64, float128:
+            num = ([array([1,1], dtype=dtype),array([2,2], dtype=dtype)],)
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+            np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testListTupleArray(self):
+        """List of tuple of numpy array for all valid types."""
+        for dtype in int, int8, int16, int32, int64, float, float16, float32, float64, float128:
+            num = [(array([1,1], dtype=dtype),array([2,2], dtype=dtype))]
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+            np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testTupleTuplesArrays(self):
+        """Tuple of tuples of numpy arrays for all valid types."""
+        for dtype in int, int8, int16, int32, int64, float, float16, float32, float64, float128:
+            num = ((array([1,1], dtype=dtype),array([2,2], dtype=dtype)),
+                   (array([3,4], dtype=dtype),array([4,4], dtype=dtype)))
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+            np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testListTuplesArrays(self):
+        """List of tuples of numpy arrays for all valid types."""
+        for dtype in int, int8, int16, int32, int64, float, float16, float32, float64, float128:
+            num = [(array([1,1], dtype=dtype),array([2,2], dtype=dtype)),
+                   (array([3,4], dtype=dtype),array([4,4], dtype=dtype))]
+            num_ = _cleanPart(num)
+
+            assert isinstance(num_, list)
+            assert np.all([isinstance(part, list) for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+            np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+
+    def testListListArrays(self):
+        """List of list of numpy arrays for all valid types."""
+        for dtype in int, int8, int16, int32, int64, float, float16, float32, float64, float128:
+            num = [[array([1,1], dtype=dtype),array([2,2], dtype=dtype)],
+                   [array([3,3], dtype=dtype),array([4,4], dtype=dtype)]]
+            num_ = _cleanPart(num)
+
+            assert len(num_) == 2
+            assert np.all([isinstance(part, list) for part in num_])
+            assert np.all([len(part) == 2 for part in num_])
+            np.testing.assert_array_equal(num_[0][0], array([1.0, 1.0], dtype=float))
+            np.testing.assert_array_equal(num_[0][1], array([2.0, 2.0], dtype=float))
+            np.testing.assert_array_equal(num_[1][0], array([3.0, 3.0], dtype=float))
+            np.testing.assert_array_equal(num_[1][1], array([4.0, 4.0], dtype=float))
+
+def suite():
+    return unittest.TestLoader().loadTestsFromTestCase(TestXferFcnInput)
+
+if __name__ == "__main__":
+    unittest.main()