add run_notebooks script + fix Jupyter notebook errors

murrayrm · murrayrm · commit b6e73c709f36 · 2021-01-26T21:32:56.000-08:00
diff --git a/.github/workflows/install_examples.yml b/.github/workflows/install_examples.yml
@@ -22,7 +22,7 @@ jobs:
         conda install pip pytest
 
         # Install python-control dependencies
-        conda install numpy matplotlib scipy
+        conda install numpy matplotlib scipy jupyter
         conda install -c conda-forge slycot pmw
 
     - name: Install with setup.py
@@ -32,3 +32,4 @@ jobs:
       run: |
         cd examples
         ./run_examples.sh
+        ./run_notebooks.sh
diff --git a/examples/bode-and-nyquist-plots.ipynb b/examples/bode-and-nyquist-plots.ipynb
@@ -6,7 +6,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import seaborn as sns\n",
     "import scipy as sp\n",
     "import matplotlib.pyplot as plt\n",
     "import control as ct"
@@ -10025,9 +10024,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python (pctest)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "pctest"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/examples/run_notebooks.sh b/examples/run_notebooks.sh
@@ -0,0 +1,29 @@
+#!/bin/bash
+# run_notbooks.sh - run Jupyter notebooks
+# RMM, 26 Jan 2021
+#
+# This script runs all of the Jupyter notebooks to make sure that there
+# are no errors.
+
+# Keep track of files that generate errors
+notebook_errors=""
+
+# Go through each Jupyter notebook
+for example in *.ipynb; do
+    echo "Running ${example}"
+    if ! jupyter nbconvert --to notebook --execute ${example}; then
+        notebook_errors="${notebook_errors} ${example}"
+    fi
+done
+
+# Get rid of the output files
+rm *.nbconvert.ipynb
+
+# List any files that generated errors
+if [ -n "${notebook_errors}" ]; then
+    echo These examples had errors:
+    echo "${notebook_errors}"
+    exit 1
+else
+    echo All examples ran successfully
+fi
diff --git a/examples/steering.ipynb b/examples/steering.ipynb
@@ -312,7 +312,7 @@
     "    clsys = ct.StateSpace(A - B @ K, B, lateral_normalized.C, 0)\n",
     "    \n",
     "    # Compute the feedforward gain based on the zero frequency gain of the closed loop\n",
-    "    kf = np.real(1/clsys.evalfr(0))\n",
+    "    kf = np.real(1/clsys(0))\n",
     "\n",
     "    # Scale the input by the feedforward gain\n",
     "    clsys *= kf\n",
@@ -488,7 +488,7 @@
     "tau = v0 * T_curvy / b\n",
     "\n",
     "# Simulate the estimator, with a small initial error in y position\n",
-    "t, y_est, x_est = ct.forced_response(est, tau, [delta_curvy, y_ref], [0.5, 0])\n",
+    "t, y_est, x_est = ct.forced_response(est, tau, [delta_curvy, y_ref], [0.5, 0], return_x=True)\n",
     "\n",
     "# Configure matplotlib plots to be a bit bigger and optimize layout\n",
     "plt.figure(figsize=[9, 4.5])\n",
@@ -596,7 +596,7 @@
     "    np.zeros((2,1)))\n",
     "\n",
     "# Simulate the system\n",
-    "t, y, x = ct.forced_response(clsys, tau, y_ref, [0.4, 0, 0.0, 0])\n",
+    "t, y, x = ct.forced_response(clsys, tau, y_ref, [0.4, 0, 0.0, 0], return_x=True)\n",
     "\n",
     "# Calcaluate the input used to generate the control response\n",
     "u_sfb = kf * y_ref - K @ x[0:2]\n",
@@ -1081,7 +1081,7 @@
     "zc = 0.707\n",
     "eigs = np.roots([1, 2*zc*wc, wc**2])\n",
     "K = ct.place(A, B, eigs)\n",
-    "kr = np.real(1/clsys.evalfr(0))\n",
+    "kr = np.real(1/clsys(0))\n",
     "print(\"K = \", np.squeeze(K))\n",
     "\n",
     "# Compute the estimator gain using eigenvalue placement\n",
@@ -1126,7 +1126,7 @@
     "zc = 2.6\n",
     "eigs = np.roots([1, 2*zc*wc, wc**2])\n",
     "K = ct.place(A, B, eigs)\n",
-    "kr = np.real(1/clsys.evalfr(0))\n",
+    "kr = np.real(1/clsys(0))\n",
     "print(\"K = \", np.squeeze(K))\n",
     "\n",
     "# Construct an output-based controller for the system\n",
