python-control · murrayrm · Jan 5, 2019 · Jan 1, 2019 · Jan 1, 2019 · Jan 1, 2019
diff --git a/.travis.yml b/.travis.yml
@@ -76,5 +76,18 @@ script:
   - 'if [ $SLYCOT != "" ]; then python -c "import slycot"; fi'
   - coverage run setup.py test
 
+  # only run examples if Slycot is install
+  # set PYTHONPATH for examples
+  # pmw needed for examples/tfvis.py
+  # future is needed for Python 2, also for examples/tfvis.py
+
+  - if [[ "$SLYCOT" != "" ]]; then
+      export PYTHONPATH=$PWD;
+      conda install -c conda-forge pmw future;
+      cd examples; bash run_examples.sh; cd ..;
+    fi
+
+# arbitrary change to try to trigger travis build
+
 after_success:
   - coveralls
diff --git a/control/phaseplot.py b/control/phaseplot.py
@@ -39,12 +39,20 @@
 
 import numpy as np
 import matplotlib.pyplot as mpl
-from matplotlib.mlab import frange, find
+
 from scipy.integrate import odeint
 from .exception import ControlNotImplemented
 
 __all__ = ['phase_plot', 'box_grid']
 
+
+def _find(condition):
+    """Returns indices where ravel(a) is true.
+    Private implementation of deprecated matplotlib.mlab.find
+    """
+    return np.nonzero(np.ravel(condition))[0]
+
+
 def phase_plot(odefun, X=None, Y=None, scale=1, X0=None, T=None,
               lingrid=None, lintime=None, logtime=None, timepts=None,
               parms=(), verbose=True):
@@ -70,11 +78,11 @@ def phase_plot(odefun, X=None, Y=None, scale=1, X0=None, T=None,
         dxdt = F(x, t) that accepts a state x of dimension 2 and
         returns a derivative dx/dt of dimension 2.
 
-    X, Y: ndarray, optional
-        Two 1-D arrays representing x and y coordinates of a grid.
-        These arguments are passed to meshgrid and generate the lists
-        of points at which the vector field is plotted.  If absent (or
-        None), the vector field is not plotted.
+    X, Y: 3-element sequences, optional, as [start, stop, npts]
+        Two 3-element sequences specifying x and y coordinates of a
+        grid.  These arguments are passed to linspace and meshgrid to
+        generate the points at which the vector field is plotted.  If
+        absent (or None), the vector field is not plotted.
 
     scale: float, optional
         Scale size of arrows; default = 1
@@ -145,8 +153,10 @@ def phase_plot(odefun, X=None, Y=None, scale=1, X0=None, T=None,
     #! TODO: Add sanity checks
     elif (X is not None and Y is not None):
         (x1, x2) = np.meshgrid(
-            frange(X[0], X[1], float(X[1]-X[0])/X[2]),
-            frange(Y[0], Y[1], float(Y[1]-Y[0])/Y[2]));
+            np.linspace(X[0], X[1], X[2]),
+            np.linspace(Y[0], Y[1], Y[2]))
+        Narrows = len(x1)
+
     else:
         # If we weren't given any grid points, don't plot arrows
         Narrows = 0;
@@ -234,12 +244,12 @@ def phase_plot(odefun, X=None, Y=None, scale=1, X0=None, T=None,
                 elif (logtimeFlag):
                     # Use an exponential time vector
                     # MATLAB: tind = find(time < (j-k) / lambda, 1, 'last');
-                    tarr = find(time < (j-k) / timefactor);
+                    tarr = _find(time < (j-k) / timefactor);
                     tind = tarr[-1] if len(tarr) else 0;
                 elif (timeptsFlag):
                     # Use specified time points
                     # MATLAB: tind = find(time < Y[j], 1, 'last');
-                    tarr = find(time < timepts[j]);
+                    tarr = _find(time < timepts[j]);
                     tind = tarr[-1] if len(tarr) else 0;
 
                 # For tailless arrows, skip the first point
@@ -295,8 +305,8 @@ def box_grid(xlimp, ylimp):
     box defined by the corners [xmin ymin] and [xmax ymax].
     """
 
-    sx10 = frange(xlimp[0], xlimp[1], float(xlimp[1]-xlimp[0])/xlimp[2])
-    sy10 = frange(ylimp[0], ylimp[1], float(ylimp[1]-ylimp[0])/ylimp[2])
+    sx10 = np.linspace(xlimp[0], xlimp[1], xlimp[2])
+    sy10 = np.linspace(ylimp[0], ylimp[1], ylimp[2])
 
     sx1 = np.hstack((0, sx10, 0*sy10+sx10[0], sx10, 0*sy10+sx10[-1]))
     sx2 = np.hstack((0, 0*sx10+sy10[0], sy10, 0*sx10+sy10[-1], sy10))

diff --git a/examples/genswitch.py b/examples/genswitch.py
@@ -5,10 +5,11 @@
 # of a genetic switch.  Plots time traces and a phase portrait using
 # the python-control library.
 
+import os
+
 import numpy as np
 import matplotlib.pyplot as mpl
 from scipy.integrate import odeint
-from matplotlib.mlab import frange
 from control import phase_plot, box_grid
 
 # Simple model of a genetic switch
@@ -34,7 +35,7 @@ def genswitch(y, t, mu=4, n=2):
 sol2 = odeint(genswitch, sol1[-1,:] + [2, -2], tim2)
 
 # First plot out the curves that define the equilibria
-u = frange(0, 4.5, 0.1)
+u = np.linspace(0, 4.5, 46)
 f = np.divide(mu, (1 + u**n))   # mu / (1 + u^n), elementwise
 
 mpl.figure(1); mpl.clf();
@@ -51,7 +52,6 @@ def genswitch(y, t, mu=4, n=2):
 mpl.figure(3); mpl.clf(); # subplot(221);
 mpl.plot(tim1, sol1[:,0], 'b-', tim1, sol1[:,1], 'g--');
 # set(pl, 'LineWidth', AM_data_linewidth);
-mpl.hold(True);
 mpl.plot([tim1[-1], tim1[-1]+1], 
          [sol1[-1,0], sol2[0,1]], 'ko:', 
          [tim1[-1], tim1[-1]+1], [sol1[-1,1], sol2[0,0]], 'ko:');
@@ -72,10 +72,11 @@ def genswitch(y, t, mu=4, n=2):
           timepts = [0.2, 0.6, 1.2])
 
 # Add the stable equilibrium points
-mpl.hold(True);
 mpl.plot(eqpt[0], eqpt[1], 'k.', eqpt[1], eqpt[0], 'k.', 
   eqpt[2], eqpt[2], 'k.')       # 'MarkerSize', AM_data_markersize*3);
 
 mpl.xlabel('Protein A [scaled]');
 mpl.ylabel('Protein B [scaled]');       # 'Rotation', 90);
 
+if 'PYCONTROL_TEST_EXAMPLES' not in os.environ:
+    mpl.show()
diff --git a/examples/phaseplots.py b/examples/phaseplots.py
@@ -4,6 +4,8 @@
 # This file contains examples of phase portraits pulled from "Feedback
 # Systems" by Astrom and Murray (Princeton University Press, 2008).
 
+import os
+
 import numpy as np
 import matplotlib.pyplot as mpl
 from control.phaseplot import phase_plot
@@ -23,7 +25,7 @@ def invpend_ode(x, t, m=1., l=1., b=0.2, g=1):
 # Set up the figure the way we want it to look
 mpl.figure(); mpl.clf(); 
 mpl.axis([-2*pi, 2*pi, -2.1, 2.1]);
-mpl.title('Inverted pendlum')
+mpl.title('Inverted pendulum')
 
 # Outer trajectories
 phase_plot(invpend_ode,
@@ -35,9 +37,7 @@ def invpend_ode(x, t, m=1., l=1., b=0.2, g=1):
     logtime = (3, 0.7) )
 
 # Separatrices
-mpl.hold(True);
 phase_plot(invpend_ode, X0 = [[-2.3056, 2.1], [2.3056, -2.1]], T=6, lingrid=0)
-mpl.show();
 
 #
 # Systems of ODEs: damped oscillator example (simulation + phase portrait)
@@ -49,9 +49,10 @@ def oscillator_ode(x, t, m=1., b=1, k=1):
 # Generate a vector plot for the damped oscillator
 mpl.figure(); mpl.clf();
 phase_plot(oscillator_ode, [-1, 1, 10], [-1, 1, 10], 0.15);
-mpl.hold(True); mpl.plot([0], [0], '.');
+#mpl.plot([0], [0], '.');
 # a=gca; set(a,'FontSize',20); set(a,'DataAspectRatio',[1,1,1]);
-mpl.xlabel('x1'); mpl.ylabel('x2');
+mpl.xlabel('$x_1$'); mpl.ylabel('$x_2$');
+mpl.title('Damped oscillator, vector field')
 
 # Generate a phase plot for the damped oscillator
 mpl.figure(); mpl.clf(); 
@@ -61,11 +62,10 @@ def oscillator_ode(x, t, m=1., b=1, k=1):
     [-1, 1], [-0.3, 1], [0, 1], [0.25, 1], [0.5, 1], [0.75, 1], [1, 1],
     [1, -1], [0.3, -1], [0, -1], [-0.25, -1], [-0.5, -1], [-0.75, -1], [-1, -1]
   ], T = np.linspace(0, 8, 80), timepts = [0.25, 0.8, 2, 3])
-mpl.hold(True); mpl.plot([0], [0], 'k.'); # 'MarkerSize', AM_data_markersize*3);
+mpl.plot([0], [0], 'k.'); # 'MarkerSize', AM_data_markersize*3);
 # set(gca,'DataAspectRatio',[1,1,1]);
-mpl.xlabel('x1'); mpl.ylabel('x2');
-
-mpl.show()
+mpl.xlabel('$x_1$'); mpl.ylabel('$x_2$');
+mpl.title('Damped oscillator, vector field and stream lines')
 
 #
 # Stability definitions
@@ -88,9 +88,10 @@ def saddle_ode(x, t):
     [-1.3,-1]
   ], T = np.linspace(0, 10, 100), 
   timepts = [0.3, 1, 2, 3], parms = (m, b, k));
-mpl.hold(True); mpl.plot([0], [0], 'k.'); # 'MarkerSize', AM_data_markersize*3);
+mpl.plot([0], [0], 'k.'); # 'MarkerSize', AM_data_markersize*3);
 # set(gca,'FontSize', 16); 
-mpl.xlabel('{\itx}_1'); mpl.ylabel('{\itx}_2');
+mpl.xlabel('$x_1$'); mpl.ylabel('$x_2$');
+mpl.title('Asymptotically stable point')
 
 # Saddle
 mpl.figure(); mpl.clf();
@@ -103,9 +104,10 @@ def saddle_ode(x, t):
     [0.95, 1], [0.9, 1], [0.8, 1], [0.6, 1], [0.4, 1], [0.2, 1],
     [-0.5, -0.45], [-0.45, -0.5], [0.5, 0.45], [0.45, 0.5],
     [-0.04, 0.04], [0.04, -0.04] ], T = np.linspace(0, 2, 20));
-mpl.hold(True); mpl.plot([0], [0], 'k.'); # 'MarkerSize', AM_data_markersize*3);
+mpl.plot([0], [0], 'k.'); # 'MarkerSize', AM_data_markersize*3);
 # set(gca,'FontSize', 16); 
-mpl.xlabel('{\itx}_1'); mpl.ylabel('{\itx}_2');
+mpl.xlabel('$x_1$'); mpl.ylabel('$x_2$');
+mpl.title('Saddle point')
 
 # Stable isL
 m = 1; b = 0; k = 1;			# zero damping
@@ -115,8 +117,10 @@ def saddle_ode(x, t):
   [pi/6, pi/3, pi/2, 2*pi/3, 5*pi/6, pi, 7*pi/6, 4*pi/3, 9*pi/6, 5*pi/3, 11*pi/6, 2*pi], 
   X0 = [ [0.2,0], [0.4,0], [0.6,0], [0.8,0], [1,0], [1.2,0], [1.4,0] ],
   T = np.linspace(0, 20, 200), parms = (m, b, k));
-mpl.hold(True); mpl.plot([0], [0], 'k.') # 'MarkerSize', AM_data_markersize*3);
+mpl.plot([0], [0], 'k.') # 'MarkerSize', AM_data_markersize*3);
 # set(gca,'FontSize', 16); 
-mpl.xlabel('{\itx}_1'); mpl.ylabel('{\itx}_2');
+mpl.xlabel('$x_1$'); mpl.ylabel('$x_2$');
+mpl.title('Undamped system\nLyapunov stable, not asympt. stable')
 
-mpl.show()
+if 'PYCONTROL_TEST_EXAMPLES' not in os.environ:
+    mpl.show()
diff --git a/examples/pvtol-lqr.py b/examples/pvtol-lqr.py
@@ -3,10 +3,12 @@
 #
 # This file works through an LQR based design problem, using the
 # planar vertical takeoff and landing (PVTOL) aircraft example from
-# Astrom and Mruray, Chapter 5.  It is intended to demonstrate the
+# Astrom and Murray, Chapter 5.  It is intended to demonstrate the
 # basic functionality of the python-control package.
 #
 
+import os
+
 from numpy import *             # Grab all of the NumPy functions
 from matplotlib.pyplot import * # Grab MATLAB plotting functions
 from control.matlab import *    # MATLAB-like functions
@@ -118,9 +120,9 @@
 (Yy, Ty) = step(H1ay, T=linspace(0,10,100));
 
 subplot(221); title("Identity weights")
-# plot(T, Y[:,1, 1], '-', T, Y[:,2, 2], '--'); hold(True);
-plot(Tx.T, Yx.T, '-', Ty.T, Yy.T, '--'); hold(True);
-plot([0, 10], [1, 1], 'k-'); hold(True);
+# plot(T, Y[:,1, 1], '-', T, Y[:,2, 2], '--');
+plot(Tx.T, Yx.T, '-', Ty.T, Yy.T, '--'); 
+plot([0, 10], [1, 1], 'k-'); 
 
 axis([0, 10, -0.1, 1.4]); 
 ylabel('position');
@@ -141,10 +143,10 @@
 [Y3, T3] = step(H1cx, T=linspace(0,10,100));
 
 subplot(222); title("Effect of input weights")
-plot(T1.T, Y1.T, 'b-'); hold(True);
-plot(T2.T, Y2.T, 'b-'); hold(True);
-plot(T3.T, Y3.T, 'b-'); hold(True);
-plot([0 ,10], [1, 1], 'k-'); hold(True);
+plot(T1.T, Y1.T, 'b-');
+plot(T2.T, Y2.T, 'b-');
+plot(T3.T, Y3.T, 'b-');
+plot([0 ,10], [1, 1], 'k-');
 
 axis([0, 10, -0.1, 1.4]); 
 
@@ -190,4 +192,6 @@
 xlabel('time'); 
 legend(('x', 'y'), loc='lower right');
 
-show()
+if 'PYCONTROL_TEST_EXAMPLES' not in os.environ:
+    show()
+
diff --git a/examples/pvtol-nested-ss.py b/examples/pvtol-nested-ss.py
@@ -98,7 +98,7 @@
 bode(L, logspace(-4, 3));
 
 # Add crossover line
-subplot(211); hold(True);
+subplot(211);
 loglog([1e-4, 1e3], [1, 1], 'k-')
 
 # Replot phase starting at -90 degrees
@@ -107,7 +107,6 @@
 
 subplot(212);
 semilogx([1e-4, 1e3], [-180, -180], 'k-')
-hold(True);
 semilogx(w, np.squeeze(phase), 'b-')
 axis([1e-4, 1e3, -360, 0]);
 xlabel('Frequency [deg]'); ylabel('Phase [deg]');
@@ -118,7 +117,7 @@
 # Nyquist plot for complete design
 #
 figure(7); clf;
-axis([-700, 5300, -3000, 3000]); hold(True);
+axis([-700, 5300, -3000, 3000]);
 nyquist(L, (0.0001, 1000));
 axis([-700, 5300, -3000, 3000]);
 
@@ -127,7 +126,7 @@
 
 # Expanded region  
 figure(8); clf; subplot(231); 
-axis([-10, 5, -20, 20]); hold(True);
+axis([-10, 5, -20, 20]);
 nyquist(L);
 axis([-10, 5, -20, 20]);
 
@@ -145,7 +144,7 @@
 
 figure(9); 
 (Yvec, Tvec) = step(T, linspace(1, 20));
-plot(Tvec.T, Yvec.T); hold(True);
+plot(Tvec.T, Yvec.T);
 
 (Yvec, Tvec) = step(Co*S, linspace(1, 20));
 plot(Tvec.T, Yvec.T);

diff --git a/examples/robust_mimo.py b/examples/robust_mimo.py
@@ -4,6 +4,8 @@
 and Postlethwaite, 1st Edition.
 """
 
+import os
+
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -68,7 +70,7 @@ def analysis():
     plt.ylabel('output')
     plt.ylim([-1.1,2.1])
     plt.legend()
-    plt.title('o/l response to input [1,0]')
+    plt.title('o/l response\nto input [1,0]')
 
     plt.subplot(1,3,2)
     plt.plot(t,yu2[0],label='$y_1$')
@@ -77,7 +79,7 @@ def analysis():
     plt.ylabel('output')
     plt.ylim([-1.1,2.1])
     plt.legend()
-    plt.title('o/l response to input [0,1]')
+    plt.title('o/l response\nto input [0,1]')
 
     plt.subplot(1,3,3)
     plt.plot(t,yuz[0],label='$y_1$')
@@ -86,7 +88,7 @@ def analysis():
     plt.ylabel('output')
     plt.ylim([-1.1,2.1])
     plt.legend()
-    plt.title('o/l response to input [1,-1]')
+    plt.title('o/l response\nto input [1,-1]')
 
 
 def synth(wb1,wb2):
@@ -103,7 +105,7 @@ def synth(wb1,wb2):
     wp2 = ss(weighting(wb=wb2, m=1.5, a=1e-4))
     wp = wp1.append(wp2)
     k,_,info = mixsyn(g,wp,wu)
-    return k, info.gamma
+    return k, info[0]
 
 
 def step_opposite(g,t):
@@ -177,4 +179,6 @@ def design():
 
 analysis()
 design()
-plt.show()
+if 'PYCONTROL_TEST_EXAMPLES' not in os.environ:
+    plt.show()
+
diff --git a/examples/robust_siso.py b/examples/robust_siso.py
@@ -4,6 +4,8 @@
 and Postlethwaite, 1st Edition.
 """
 
+import os
+
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -99,4 +101,5 @@
 plt.legend()
 plt.title('Disturbance response')
 
-plt.show()
+if 'PYCONTROL_TEST_EXAMPLES' not in os.environ:
+    plt.show()