python-control · dapperfu · Feb 17, 2017 · Feb 17, 2017 · Feb 18, 2017 · Feb 18, 2017
diff --git a/.gitignore b/.gitignore
@@ -18,3 +18,4 @@ examples/.ipynb_checkpoints/
 .project
 Untitled*.ipynb
 *.idea/
+.eggs
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_test.py - test TransferFunction class
+# RMM, 30 Mar 2011 (based on TestXferFcn from v0.4a)
+
+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()
diff --git a/control/xferfcn.py b/control/xferfcn.py
@@ -10,6 +10,7 @@
 # Python 3 compatibility (needs to go here)
 from __future__ import print_function
 from __future__ import division
+from __future__ import absolute_import
 
 """Copyright (c) 2010 by California Institute of Technology
 All rights reserved.
@@ -55,6 +56,13 @@
 from numpy import angle, any, array, empty, finfo, insert, ndarray, ones, \
     polyadd, polymul, polyval, roots, sort, sqrt, zeros, squeeze, exp, pi, \
     where, delete, real, poly, poly1d
+
+from numpy import int, int8, int16, int32, int64
+from numpy import float, float16, float32, float64, float128
+from numpy import complex, complex64, complex128, complex256
+
+from copy import deepcopy
+
 import numpy as np
 from scipy.signal import lti, tf2zpk, zpk2tf, cont2discrete
 from copy import deepcopy
@@ -96,7 +104,7 @@ def __init__(self, *args):
         where sys is a TransferFunction object (continuous or discrete).
 
         """
-
+        args = deepcopy(args)
         if len(args) == 2:
             # The user provided a numerator and a denominator.
             (num, den) = args
@@ -120,48 +128,8 @@ def __init__(self, *args):
             raise ValueError("Needs 1, 2 or 3 arguments; received %i."
                              % len(args))
 
-        # Make num and den into lists of lists of arrays, if necessary.
-        # Beware: this is a shallow copy! This should be okay,
-        # but be careful.
-        data = [num, den]
-        for i in range(len(data)):
-            # Check for a scalar (including 0d ndarray)
-            if (isinstance(data[i], (int, float, complex)) or
-                (isinstance(data[i], ndarray) and data[i].ndim == 0)):
-                # Convert scalar to list of list of array.
-                if (isinstance(data[i], int)):
-                    # Convert integers to floats at this point
-                    data[i] = [[array([data[i]], dtype=float)]]
-                else:
-                    data[i] = [[array([data[i]])]]
-            elif (isinstance(data[i], (list, tuple, ndarray)) and
-                    isinstance(data[i][0], (int, float, complex))):
-                # Convert array to list of list of array.
-                if (isinstance(data[i][0], int)):
-                    # Convert integers to floats at this point
-                    #! Not sure this covers all cases correctly
-                    data[i] = [[array(data[i], dtype=float)]]
-                else:
-                    data[i] = [[array(data[i])]]
-            elif (isinstance(data[i], list) and
-                    isinstance(data[i][0], list) and
-                    isinstance(data[i][0][0], (list, tuple, ndarray)) and
-                    isinstance(data[i][0][0][0], (int, float, complex))):
-                # We might already have the right format.  Convert the
-                # coefficient vectors to arrays, if necessary.
-                for j in range(len(data[i])):
-                    for k in range(len(data[i][j])):
-                        if (isinstance(data[i][j][k], int)):
-                            data[i][j][k] = array(data[i][j][k], dtype=float)
-                        else:
-                            data[i][j][k] = array(data[i][j][k])
-            else:
-                # If the user passed in anything else, then it's unclear what
-                # the meaning is.
-                raise TypeError("The numerator and denominator inputs must be \
-scalars or vectors (for\nSISO), or lists of lists of vectors (for SISO or \
-MIMO).")
-        [num, den] = data
+        num = cleanPart(num)
+        den = cleanPart(den)
 
         inputs = len(num[0])
         outputs = len(num)
@@ -1349,3 +1317,42 @@ def tfdata(sys):
     tf = _convertToTransferFunction(sys)
 
     return (tf.num, tf.den)
+
+def cleanPart(data):
+    '''
+    Return a valid, cleaned up numerator or denominator 
+    for the TransferFunction class.
+
+    Parameters:
+    data: numerator or denominator of a transfer function.
+
+    Returns:
+    data: correctly formatted transfer function part.
+    ;
+    '''
+    valid_types = (int, int8, int16, int32, int64,
+                   float, float16, float32, float64, float128)
+    valid_collection = (list, tuple, ndarray)
+
+    if (isinstance(data, valid_types) or
+        (isinstance(data, ndarray) and data.ndim == 0)):
+        return [[array([data], dtype=float)]]
+    elif (isinstance(data, valid_collection) and
+            all([isinstance(d, valid_types) for d in data])):
+        return [[array(data, dtype=float)]]
+    elif (isinstance(data, (list, tuple)) and
+          isinstance(data[0], (list, tuple)) and
+              (isinstance(data[0][0], valid_collection) and 
+               all([isinstance(d, valid_types) for d in data[0][0]]))):
+        data = list(data)
+        for j in range(len(data)):
+            data[j] = list(data[j])
+            for k in range(len(data[j])):
+                data[j][k] = array(data[j][k], dtype=float)
+        return data
+    else:
+        # If the user passed in anything else, then it's unclear what
+        # the meaning is.
+        raise TypeError("The numerator and denominator inputs must be \
+scalars or vectors (for\nSISO), or lists of lists of vectors (for SISO or \
+MIMO).")
-Original file line number
+Diff line change
@@ Expand Up / @@ -18,3 +18,4 @@ examples/.ipynb_checkpoints/ @@
     .project
     Untitled*.ipynb
     *.idea/
+    .eggs