Add support for scipy 0.16.x, fix #60

ggventurini · Aug 5, 2015 · 17268d3 · 17268d3
1 parent 701c94b
commit 17268d3
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Showing 5 changed files with 23 additions and 7 deletions.
diff --git a/deltasigma/_calculateTF.py b/deltasigma/_calculateTF.py
@@ -48,6 +48,9 @@ def calculateTF(ABCD, k=1.):
     **Returns:**
 
     (NTF, STF) : a tuple of two LTI objects (or of two lists of LTI objects).
+                 If a version of the ``scipy`` library equal to 0.16.x or 
+                 greater is in use, the objects will be ``ZeroPolesGain``
+                 objects, a subclass of ``scipy.signal.lti``.
 
     If the system has multiple quantizers, multiple STFs and NTFs will be
     returned.

diff --git a/deltasigma/_mapCtoD.py b/deltasigma/_mapCtoD.py
@@ -52,8 +52,8 @@ def mapCtoD(sys_c, t=(0, 1), f0=0.):
 
      * the ABCD matrix,
      * a list-like containing the A, B, C, D matrices,
-     * a list of zpk tuples (internally converted to SS representation).
-     * a list of LTI objects
+     * a list of zpk tuples (internally converted to SS representation),
+     * a list of LTI objects.
 
     t : array_like
         The edge times of the DAC pulse used to make CT waveforms

diff --git a/deltasigma/_mod1.py b/deltasigma/_mod1.py
@@ -27,7 +27,14 @@ def mod1():
     **Returns:**
 
     ABCD, NTF, STF : a tuple of (ndarray, lti, lti)
-        The elements are the ABCD matrix (ndarray), the NTF (lti object), the STF (lti object).
+        The elements are the ABCD matrix (ndarray), the NTF (LTI object), the
+        STF (LTI object).
+
+    .. note::
+
+        If a version of the ``scipy`` library equal to 0.16.x or greater is in
+        use, the NTF and STF objects will be ``ZeroPolesGain`` objects, a
+        subclass of the scipy LTI object (``scipy.signal.lti``).
 
     """
     A = np.array([[1.]])

diff --git a/deltasigma/_mod2.py b/deltasigma/_mod2.py
@@ -28,7 +28,13 @@ def mod2():
 
     ABCD, NTF, STF : a tuple of (ndarray, lti, lti)
         The elements are the ABCD matrix (ndarray),
-        the NTF (lti object), the STF (lti object).
+        the NTF (LTI object), the STF (LTI object).
+
+    .. note::
+
+        If a version of the ``scipy`` library equal to 0.16.x or greater is in
+        use, the NTF and STF objects will be ``ZeroPolesGain`` objects, a
+        subclass of the scipy LTI object (``scipy.signal.lti``).
 
     """
     A = np.array([[1., 0.], [1., 1.]])

diff --git a/deltasigma/_utils.py b/deltasigma/_utils.py
@@ -433,7 +433,7 @@ def _get_zpk(arg, input=0):
         # ABCD matrix
         A, B, C, D = partitionABCD(arg)
         z, p, k = ss2zpk(A, B, C, D, input=input)
-    elif hasattr(arg, '__class__') and arg.__class__.__name__ == 'lti':
+    elif isinstance(arg, lti):
         z, p, k = arg.zeros, arg.poles, arg.gain
     elif _is_zpk(arg):
         z, p, k = np.atleast_1d(arg[0]), np.atleast_1d(arg[1]), arg[2]
@@ -513,7 +513,7 @@ def _get_num_den(arg, input=0):
         # ABCD matrix
         A, B, C, D = partitionABCD(arg)
         num, den = ss2tf(A, B, C, D, input=input)
-    elif hasattr(arg, '__class__') and arg.__class__.__name__ == 'lti':
+    elif isinstance(arg, lti):
         num, den = arg.num, arg.den
     elif _is_num_den(arg):
         num, den = carray(arg[0]).squeeze(), carray(arg[1]).squeeze()
@@ -597,7 +597,7 @@ def _getABCD(arg):
     if isinstance(arg, np.ndarray):
         # ABCD matrix
         A, B, C, D = partitionABCD(arg)
-    elif hasattr(arg, '__class__') and arg.__class__.__name__ == 'lti':
+    elif isinstance(arg, lti):
         A, B, C, D = arg.A, arg.B, arg.C, np.atleast_2d(arg.D)
     elif _is_zpk(arg) or _is_num_den(arg) or _is_A_B_C_D(arg):
         sys = lti(*arg)