Add test for ModelicaSystem.optimize()

adeas31 · Apr 23, 2025 · Apr 9, 2025 · Apr 9, 2025 · Apr 9, 2025 · Apr 10, 2025
commit 04714e63efa97bd71fefc5278355fc6a37c028ce
diff --git a/tests/test_optimization.py b/tests/test_optimization.py
@@ -0,0 +1,78 @@
+import OMPython
+import tempfile
+import shutil
+import unittest
+import pathlib
+import numpy as np
+
+
+class Test_Linearization(unittest.TestCase):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.tmp = pathlib.Path(tempfile.mkdtemp(prefix='tmpOMPython.tests'))
+
+    def __del__(self):
+        shutil.rmtree(self.tmp, ignore_errors=True)
+
+    def test_example(self):
+        model_file = self.tmp / "BangBang2021.mo"
+        model_file.write_text("""
+model BangBang2021 "Model to verify that optimization gives bang-bang optimal control"
+   parameter Real m = 1;
+   parameter Real p = 1 "needed for final constraints";
+
+   Real a;
+   Real v(start = 0, fixed = true);
+   Real pos(start = 0, fixed = true);
+   Real pow(min = -30, max = 30) = f * v annotation(isConstraint = true);
+
+   input Real f(min = -10, max = 10);
+
+   Real costPos(nominal = 1) = -pos "minimize -pos(tf)" annotation(isMayer=true);
+
+   Real conSpeed(min = 0, max = 0) = p * v " 0<= p*v(tf) <=0" annotation(isFinalConstraint = true);
+
+equation
+
+   der(pos) = v;
+   der(v) = a;
+   f = m * a;
+
+annotation(experiment(StartTime = 0, StopTime = 1, Tolerance = 1e-07, Interval = 0.01),
+__OpenModelica_simulationFlags(s="optimization", optimizerNP="1"),
+__OpenModelica_commandLineOptions="+g=Optimica");
+
+end BangBang2021;
+""")
+
+        mod = OMPython.ModelicaSystem(model_file.as_posix(), "BangBang2021",
+                                      raiseerrors=True)
+
+        mod.setOptimizationOptions(["numberOfIntervals=16", "stopTime=1",
+                                    "stepSize=0.001", "tolerance=1e-8"])
+
+        # test the getter
+        assert mod.getOptimizationOptions()["stopTime"] == "1"
+        assert mod.getOptimizationOptions("stopTime") == ["1"]
+        assert mod.getOptimizationOptions(["tolerance", "stopTime"]) == ["1e-8", "1"]
+
+        r = mod.optimize()
+        # it is necessary to specify resultfile, otherwise it wouldn't find it.
+        time, f, v = mod.getSolutions(["time", "f", "v"], resultfile=r["resultFile"])
+        assert np.isclose(f[0], 10)
+        assert np.isclose(f[-1], -10)
+
+        def f_fcn(time, v):
+            if time < 0.3:
+                return 10
+            if time <= 0.5:
+                return 30 / v
+            if time < 0.7:
+                return -30 / v
+            return -10
+        f_expected = [f_fcn(t, v) for t, v in zip(time, v)]
+
+        # The sharp edge at time=0.5 probably won't match, let's leave that out.
+        matches = np.isclose(f, f_expected, 1e-3)
+        assert matches[:498].all()
+        assert matches[502:].all()