updates for NumPy 2.0 compatibility in CI tests (#1013)

murrayrm · web-flow · commit ad6b49e09034 · 2024-06-26T08:49:20.000-07:00
diff --git a/control/bdalg.py b/control/bdalg.py
@@ -201,11 +201,11 @@ def negate(sys):
     --------
     >>> G = ct.tf([2], [1, 1])
     >>> G.dcgain()
-    2.0
+    np.float64(2.0)
 
     >>> Gn = ct.negate(G) # Same as sys2 = -sys1.
     >>> Gn.dcgain()
-    -2.0
+    np.float64(-2.0)
 
     """
     return -sys
diff --git a/control/descfcn.py b/control/descfcn.py
@@ -525,11 +525,11 @@ class saturation_nonlinearity(DescribingFunctionNonlinearity):
     --------
     >>> nl = ct.saturation_nonlinearity(5)
     >>> nl(1)
-    1
+    np.int64(1)
     >>> nl(10)
-    5
+    np.int64(5)
     >>> nl(-10)
-    -5
+    np.int64(-5)
 
     """
     def __init__(self, ub=1, lb=None):
diff --git a/control/lti.py b/control/lti.py
@@ -525,7 +525,7 @@ def dcgain(sys):
     --------
     >>> G = ct.tf([1], [1, 2])
     >>> ct.dcgain(G)                                            # doctest: +SKIP
-    0.5
+    np.float(0.5)
 
     """
     return sys.dcgain()
diff --git a/control/modelsimp.py b/control/modelsimp.py
@@ -87,7 +87,7 @@ def hsvd(sys):
     >>> G = ct.tf2ss([1], [1, 2])
     >>> H = ct.hsvd(G)
     >>> H[0]
-    0.25
+    np.float64(0.25)
 
     """
     # TODO: implement for discrete time systems
diff --git a/control/robust.py b/control/robust.py
@@ -73,7 +73,7 @@ def h2syn(P, nmeas, ncon):
     --------
     >>> # Unstable first order SISI system
     >>> G = ct.tf([1], [1, -1], inputs=['u'], outputs=['y'])
-    >>> max(G.poles()) < 0  # Is G stable?
+    >>> all(G.poles() < 0)  # Is G stable?
     False
 
     >>> # Create partitioned system with trivial unity systems
@@ -87,7 +87,7 @@ def h2syn(P, nmeas, ncon):
     >>> # Synthesize H2 optimal stabilizing controller
     >>> K = ct.h2syn(P, nmeas=1, ncon=1)
     >>> T = ct.feedback(G, K, sign=1)
-    >>> max(T.poles()) < 0  # Is T stable?
+    >>> all(T.poles() < 0)  # Is T stable?
     True
 
     """
@@ -154,7 +154,7 @@ def hinfsyn(P, nmeas, ncon):
     --------
     >>> # Unstable first order SISI system
     >>> G = ct.tf([1], [1,-1], inputs=['u'], outputs=['y'])
-    >>> max(G.poles()) < 0
+    >>> all(G.poles() < 0)
     False
 
     >>> # Create partitioned system with trivial unity systems
@@ -167,7 +167,7 @@ def hinfsyn(P, nmeas, ncon):
     >>> # Synthesize Hinf optimal stabilizing controller
     >>> K, CL, gam, rcond = ct.hinfsyn(P, nmeas=1, ncon=1)
     >>> T = ct.feedback(G, K, sign=1)
-    >>> max(T.poles()) < 0
+    >>> all(T.poles() < 0)
     True
 
     """
diff --git a/control/statefbk.py b/control/statefbk.py
@@ -1011,7 +1011,7 @@ def ctrb(A, B, t=None):
     >>> G = ct.tf2ss([1], [1, 2, 3])
     >>> C = ct.ctrb(G.A, G.B)
     >>> np.linalg.matrix_rank(C)
-    2
+    np.int64(2)
 
     """
 
@@ -1053,7 +1053,7 @@ def obsv(A, C, t=None):
     >>> G = ct.tf2ss([1], [1, 2, 3])
     >>> C = ct.obsv(G.A, G.C)
     >>> np.linalg.matrix_rank(C)
-    2
+    np.int64(2)
 
     """
 
diff --git a/control/sysnorm.py b/control/sysnorm.py
@@ -117,7 +117,7 @@ def norm(system, p=2, tol=1e-6, print_warning=True, method=None):
     >>> round(ct.norm(Gc, 2), 3)
     0.5
     >>> round(ct.norm(Gc, 'inf', tol=1e-5, method='scipy'), 3)
-    1.0
+    np.float64(1.0)
     """
            
     if not isinstance(system, (ct.StateSpace, ct.TransferFunction)):
diff --git a/control/xferfcn.py b/control/xferfcn.py
@@ -1241,7 +1241,7 @@ def dcgain(self, warn_infinite=False):
         --------
         >>> G = ct.tf([1], [1, 4])
         >>> G.dcgain()
-        0.25
+        np.float64(0.25)
 
         """
         return self._dcgain(warn_infinite)
diff --git a/examples/tfvis.py b/examples/tfvis.py
@@ -45,13 +45,8 @@
 import Pmw
 import matplotlib.pyplot as plt
 from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
-from numpy.lib.polynomial import polymul
-from numpy.lib.type_check import real
-from numpy.core.multiarray import array
-from numpy.core.fromnumeric import size
-# from numpy.lib.function_base import logspace
 from control.matlab import logspace
-from numpy import conj
+from numpy import array, conj, polymul, real, size
 
 
 def make_poly(facts):
