Replaced np.matrix with np.array objects

billtubbs · billtubbs · commit 0df099f84fd8 · 2019-06-08T16:08:08.000-07:00
diff --git a/examples/check-controllability-and-observability.py b/examples/check-controllability-and-observability.py
@@ -6,25 +6,25 @@
 
 from __future__ import print_function
 
-from scipy import *  # Load the scipy functions
+import numpy as np  # Load the scipy functions
 from control.matlab import *  # Load the controls systems library
 
 # Parameters defining the system
 
 m = 250.0  # system mass
-k = 40.0  # spring constant
-b = 60.0  # damping constant
+k = 40.0   # spring constant
+b = 60.0   # damping constant
 
 # System matrices
-A = matrix([[1, -1, 1.],
-            [1, -k/m, -b/m],
-            [1, 1, 1]])
+A = np.array([[1, -1, 1.],
+             [1, -k/m, -b/m],
+             [1, 1, 1]])
 
-B = matrix([[0],
-            [1/m],
-            [1]])
+B = np.array([[0],
+             [1/m],
+             [1]])
 
-C = matrix([[1., 0, 1.]])
+C = np.array([[1., 0, 1.]])
 
 sys = ss(A, B, C, 0)
 
diff --git a/examples/rss-balred.py b/examples/rss-balred.py
@@ -12,13 +12,20 @@
 
 # controllable canonical realization computed in Matlab for the transfer function:
 # num = [1 11 45 32], den = [1 15 60 200 60]
-A = np.matrix('-15., -7.5, -6.25, -1.875; \
-8., 0., 0., 0.; \
-0., 4., 0., 0.; \
-0., 0., 1., 0.')
-B = np.matrix('2.; 0.; 0.; 0.')
-C = np.matrix('0.5, 0.6875, 0.7031, 0.5')
-D = np.matrix('0.')
+A = np.array([
+    [-15., -7.5, -6.25, -1.875],
+    [8., 0., 0., 0.],
+    [0., 4., 0., 0.],
+    [0., 0., 1., 0.]
+])
+B = np.array([
+    [2.],
+    [0.],
+    [0.],
+    [0.]
+])
+C = np.array([[0.5, 0.6875, 0.7031, 0.5]])
+D = np.array([[0.]])
 
 # The full system
 fsys = StateSpace(A, B, C, D)
diff --git a/examples/slycot-import-test.py b/examples/slycot-import-test.py
@@ -14,9 +14,9 @@
 b = 60.0   # damping constant
 
 # System matrices
-A = np.matrix([[1, -1, 1.], [1, -k/m, -b/m], [1, 1, 1]])
-B = np.matrix([[0], [1/m], [1]])
-C = np.matrix([[1., 0, 1.]])
+A = np.array([[1, -1, 1.], [1, -k/m, -b/m], [1, 1, 1]])
+B = np.array([[0], [1/m], [1]])
+C = np.array([[1., 0, 1.]])
 sys = ss(A, B, C, 0)
 
 # Python control may be used without slycot, for example for a pole placement.
