Remove deprecated code in ModelicaSystem set*() functions

OMPython/ModelicaSystem.py

@@ -1115,7 +1115,7 @@ def getSolutions(self, varList: Optional[str | list[str]] = None, resultfile: Op
 
     @staticmethod
     def _prepare_input_data(
-            raw_input: str | list[str] | dict[str, Any],
+            input_kwargs: dict[str, Any],
     ) -> dict[str, str]:
         """
         Convert raw input to a structured dictionary {'key1': 'value1', 'key2': 'value2'}.
@@ -1133,38 +1133,20 @@ def prepare_str(str_in: str) -> dict[str, str]:
 
         input_data: dict[str, str] = {}
 
-        if isinstance(raw_input, str):
-            warnings.warn(message="The definition of values to set should use a dictionary, "
-                                  "i.e. {'key1': 'val1', 'key2': 'val2', ...}. Please convert all cases which "
-                                  "use a string ('key=val') or list ['key1=val1', 'key2=val2', ...]",
-                          category=DeprecationWarning,
-                          stacklevel=3)
-            return prepare_str(raw_input)
-
-        if isinstance(raw_input, list):
-            warnings.warn(message="The definition of values to set should use a dictionary, "
-                                  "i.e. {'key1': 'val1', 'key2': 'val2', ...}. Please convert all cases which "
-                                  "use a string ('key=val') or list ['key1=val1', 'key2=val2', ...]",
-                          category=DeprecationWarning,
-                          stacklevel=3)
-
-            for item in raw_input:
-                input_data |= prepare_str(item)
-
-            return input_data
-
-        if isinstance(raw_input, dict):
-            for key, val in raw_input.items():
-                # convert all values to strings to align it on one type: dict[str, str]
-                # spaces have to be removed as setInput() could take list of tuples as input and spaces would
-                str_val = str(val).replace(' ', '')
+        if len(input_kwargs):
+            for key, val in input_kwargs.items():
+                # ensure all values are strings to align it on one type: dict[str, str]
+                if not isinstance(val, str):
+                    # spaces have to be removed as setInput() could take list of tuples as input and spaces would
+                    # result in an error on recreating the input data
+                    str_val = str(val).replace(' ', '')
+                else:
+                    str_val = val
                 if ' ' in key or ' ' in str_val:
                     raise ModelicaSystemError(f"Spaces not allowed in key/value pairs: {repr(key)} = {repr(val)}!")
                 input_data[key] = str_val
 
-            return input_data
-
-        raise ModelicaSystemError(f"Invalid type of input: {type(raw_input)}")
+        return input_data
 
     def _set_method_helper(
             self,
@@ -1196,8 +1178,7 @@ def _set_method_helper(
 
         for key, val in inputdata.items():
             if key not in classdata:
-                raise ModelicaSystemError("Unhandled case in setMethodHelper.apply_single() - "
-                                          f"{repr(key)} is not a {repr(datatype)} variable")
+                raise ModelicaSystemError(f"Invalid variable for type {repr(datatype)}: {repr(key)}")
 
             if datatype == "parameter" and not self.isParameterChangeable(key):
                 raise ModelicaSystemError(f"It is not possible to set the parameter {repr(key)}. It seems to be "
@@ -1225,17 +1206,15 @@ def isParameterChangeable(
 
     def setContinuous(
             self,
-            cvals: str | list[str] | dict[str, Any],
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
-        This method is used to set continuous values. It can be called:
-        with a sequence of continuous name and assigning corresponding values as arguments as show in the example below:
-        usage
-        >>> setContinuous("Name=value")  # depreciated
-        >>> setContinuous(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setContinuous(cvals={"Name1": "value1", "Name2": "value2"})
+        This method is used to set continuous values.
+        >>> setContinuous(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setContinuous(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=cvals)
+        inputdata = self._prepare_input_data(input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1245,17 +1224,15 @@ def setContinuous(
 
     def setParameters(
             self,
-            pvals: str | list[str] | dict[str, Any],
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
-        This method is used to set parameter values. It can be called:
-        with a sequence of parameter name and assigning corresponding value as arguments as show in the example below:
-        usage
-        >>> setParameters("Name=value")  # depreciated
-        >>> setParameters(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setParameters(pvals={"Name1": "value1", "Name2": "value2"})
+        This method is used to set parameter values.
+        >>> setParameters(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setParameters(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=pvals)
+        inputdata = self._prepare_input_data(input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1265,17 +1242,15 @@ def setParameters(
 
     def setSimulationOptions(
             self,
-            simOptions: str | list[str] | dict[str, Any],
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
-        This method is used to set simulation options. It can be called:
-        with a sequence of simulation options name and assigning corresponding values as arguments as show in the example below:
-        usage
-        >>> setSimulationOptions("Name=value")  # depreciated
-        >>> setSimulationOptions(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setSimulationOptions(simOptions={"Name1": "value1", "Name2": "value2"})
+        This method is used to set simulation options.
+        >>> setSimulationOptions(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setSimulationOptions(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=simOptions)
+        inputdata = self._prepare_input_data(input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1285,17 +1260,15 @@ def setSimulationOptions(
 
     def setLinearizationOptions(
             self,
-            linearizationOptions: str | list[str] | dict[str, Any],
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
-        This method is used to set linearization options. It can be called:
-        with a sequence of linearization options name and assigning corresponding value as arguments as show in the example below
-        usage
-        >>> setLinearizationOptions("Name=value")  # depreciated
-        >>> setLinearizationOptions(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setLinearizationOptions(linearizationOtions={"Name1": "value1", "Name2": "value2"})
+        This method is used to set linearization options.
+        >>> setLinearizationOptions(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setLinearizationOptions(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=linearizationOptions)
+        inputdata = self._prepare_input_data(input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1305,17 +1278,17 @@ def setLinearizationOptions(
 
     def setOptimizationOptions(
             self,
-            optimizationOptions: str | list[str] | dict[str, Any],
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
         This method is used to set optimization options. It can be called:
         with a sequence of optimization options name and assigning corresponding values as arguments as show in the example below:
         usage
-        >>> setOptimizationOptions("Name=value")  # depreciated
-        >>> setOptimizationOptions(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setOptimizationOptions(optimizationOptions={"Name1": "value1", "Name2": "value2"})
+        >>> setOptimizationOptions(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setOptimizationOptions(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=optimizationOptions)
+        inputdata = self._prepare_input_data(input_kwargs=kwargs)
 
         return self._set_method_helper(
             inputdata=inputdata,
@@ -1325,19 +1298,18 @@ def setOptimizationOptions(
 
     def setInputs(
             self,
-            name: str | list[str] | dict[str, Any],
+            **kwargs: dict[str, Any],
     ) -> bool:
         """
-        This method is used to set input values. It can be called with a sequence of input name and assigning
-        corresponding values as arguments as show in the example below. Compared to other set*() methods this is a
-        special case as value could be a list of tuples - these are converted to a string in _prepare_input_data()
-        and restored here via ast.literal_eval().
-
-        >>> setInputs("Name=value")  # depreciated
-        >>> setInputs(["Name1=value1","Name2=value2"])  # depreciated
-        >>> setInputs(name={"Name1": "value1", "Name2": "value2"})
+        This method is used to set input values.
+
+        Compared to other set*() methods this is a special case as value could be a list of tuples - these are
+        converted to a string in _prepare_input_data() and restored here via ast.literal_eval().
+        >>> setInputs(Name1="value1", Name2="value2")
+        >>> param = {"Name1": "value1", "Name2": "value2"}
+        >>> setInputs(**param)
         """
-        inputdata = self._prepare_input_data(raw_input=name)
+        inputdata = self._prepare_input_data(input_kwargs=kwargs)
 
         for key, val in inputdata.items():
             if key not in self._inputs:

tests/test_ModelicaSystem.py

@@ -34,9 +34,9 @@ def test_setParameters():
     model_path = omc.sendExpression("getInstallationDirectoryPath()") + "/share/doc/omc/testmodels/"
     mod = OMPython.ModelicaSystem(model_path + "BouncingBall.mo", "BouncingBall")
 
-    # method 1
-    mod.setParameters(pvals={"e": 1.234})
-    mod.setParameters(pvals={"g": 321.0})
+    # method 1 (test depreciated variants)
+    mod.setParameters(e=1.234)
+    mod.setParameters(g=321.0)
     assert mod.getParameters("e") == ["1.234"]
     assert mod.getParameters("g") == ["321.0"]
     assert mod.getParameters() == {
@@ -46,8 +46,9 @@ def test_setParameters():
     with pytest.raises(KeyError):
         mod.getParameters("thisParameterDoesNotExist")
 
-    # method 2
-    mod.setParameters(pvals={"e": 21.3, "g": 0.12})
+    # method 2 (new style)
+    pvals = {"e": 21.3, "g": 0.12}
+    mod.setParameters(**pvals)
     assert mod.getParameters() == {
         "e": "21.3",
         "g": "0.12",
@@ -64,8 +65,8 @@ def test_setSimulationOptions():
     mod = OMPython.ModelicaSystem(fileName=model_path + "BouncingBall.mo", modelName="BouncingBall")
 
     # method 1
-    mod.setSimulationOptions(simOptions={"stopTime": 1.234})
-    mod.setSimulationOptions(simOptions={"tolerance": 1.1e-08})
+    mod.setSimulationOptions(stopTime=1.234)
+    mod.setSimulationOptions(tolerance=1.1e-08)
     assert mod.getSimulationOptions("stopTime") == ["1.234"]
     assert mod.getSimulationOptions("tolerance") == ["1.1e-08"]
     assert mod.getSimulationOptions(["tolerance", "stopTime"]) == ["1.1e-08", "1.234"]
@@ -77,7 +78,7 @@ def test_setSimulationOptions():
         mod.getSimulationOptions("thisOptionDoesNotExist")
 
     # method 2
-    mod.setSimulationOptions(simOptions={"stopTime": 2.1, "tolerance": "1.2e-08"})
+    mod.setSimulationOptions(stopTime=2.1, tolerance=1.2e-08)
     d = mod.getSimulationOptions()
     assert d["stopTime"] == "2.1"
     assert d["tolerance"] == "1.2e-08"
@@ -119,7 +120,9 @@ def test_getSolutions(model_firstorder):
     a = -1
     tau = -1 / a
     stopTime = 5*tau
-    mod.setSimulationOptions(simOptions={"stopTime": stopTime, "stepSize": 0.1, "tolerance": 1e-8})
+
+    simOptions = {"stopTime": stopTime, "stepSize": 0.1, "tolerance": 1e-8}
+    mod.setSimulationOptions(**simOptions)
     mod.simulate()
 
     x = mod.getSolutions("x")
@@ -298,7 +301,7 @@ def test_getters(tmp_path):
     x0 = 1.0
     x_analytical = -b/a + (x0 + b/a) * np.exp(a * stopTime)
     dx_analytical = (x0 + b/a) * a * np.exp(a * stopTime)
-    mod.setSimulationOptions(simOptions={"stopTime": stopTime})
+    mod.setSimulationOptions(stopTime=stopTime)
     mod.simulate()
 
     # getOutputs after simulate()
@@ -327,7 +330,7 @@ def test_getters(tmp_path):
         mod.getContinuous("a")  # a is a parameter
 
     with pytest.raises(OMPython.ModelicaSystemError):
-        mod.setSimulationOptions(simOptions={"thisOptionDoesNotExist": 3})
+        mod.setSimulationOptions(thisOptionDoesNotExist=3)
 
 
 def test_simulate_inputs(tmp_path):
@@ -345,7 +348,8 @@ def test_simulate_inputs(tmp_path):
 """)
     mod = OMPython.ModelicaSystem(fileName=model_file.as_posix(), modelName="M_input")
 
-    mod.setSimulationOptions(simOptions={"stopTime": 1.0})
+    simOptions = {"stopTime": 1.0}
+    mod.setSimulationOptions(**simOptions)
 
     # integrate zero (no setInputs call) - it should default to None -> 0
     assert mod.getInputs() == {
@@ -357,7 +361,7 @@ def test_simulate_inputs(tmp_path):
     assert np.isclose(y[-1], 0.0)
 
     # integrate a constant
-    mod.setInputs(name={"u1": 2.5})
+    mod.setInputs(u1=2.5)
     assert mod.getInputs() == {
         "u1": [
             (0.0, 2.5),
@@ -374,7 +378,8 @@ def test_simulate_inputs(tmp_path):
     assert np.isclose(y[-1], 2.5)
 
     # now let's integrate the sum of two ramps
-    mod.setInputs(name={"u1": [(0.0, 0.0), (0.5, 2), (1.0, 0)]})
+    inputs = {"u1": [(0.0, 0.0), (0.5, 2), (1.0, 0)]}
+    mod.setInputs(**inputs)
     assert mod.getInputs("u1") == [[
         (0.0, 0.0),
         (0.5, 2.0),
@@ -387,17 +392,20 @@ def test_simulate_inputs(tmp_path):
     # let's try some edge cases
     # unmatched startTime
     with pytest.raises(OMPython.ModelicaSystemError):
-        mod.setInputs(name={"u1": [(-0.5, 0.0), (1.0, 1)]})
+        mod.setInputs(u1=[(-0.5, 0.0), (1.0, 1)])
         mod.simulate()
     # unmatched stopTime
     with pytest.raises(OMPython.ModelicaSystemError):
-        mod.setInputs(name={"u1": [(0.0, 0.0), (0.5, 1)]})
+        mod.setInputs(u1=[(0.0, 0.0), (0.5, 1)])
         mod.simulate()
 
     # Let's use both inputs, but each one with different number of
     # samples. This has an effect when generating the csv file.
-    mod.setInputs(name={"u1": [(0.0, 0), (1.0, 1)],
-                        "u2": [(0.0, 0), (0.25, 0.5), (0.5, 1.0), (1.0, 0)]})
+    inputs = {
+        "u1": [(0.0, 0), (1.0, 1)],
+        "u2": [(0.0, 0), (0.25, 0.5), (0.5, 1.0), (1.0, 0)],
+    }
+    mod.setInputs(**inputs)
     csv_file = mod._createCSVData()
     assert pathlib.Path(csv_file).read_text() == """time,u1,u2,end
 0.0,0.0,0.0,0

tests/test_linearization.py

@@ -62,10 +62,10 @@ def test_getters(tmp_path):
     assert "startTime" in d
     assert "stopTime" in d
     assert mod.getLinearizationOptions(["stopTime", "startTime"]) == [d["stopTime"], d["startTime"]]
-    mod.setLinearizationOptions(linearizationOptions={"stopTime": 0.02})
+    mod.setLinearizationOptions(stopTime=0.02)
     assert mod.getLinearizationOptions("stopTime") == ["0.02"]
 
-    mod.setInputs(name={"u1": 10, "u2": 0})
+    mod.setInputs(u1=10, u2=0)
     [A, B, C, D] = mod.linearize()
     g = float(mod.getParameters("g")[0])
     l = float(mod.getParameters("l")[0])

tests/test_optimization.py

@@ -35,10 +35,13 @@ def test_optimization_example(tmp_path):
 
     mod = OMPython.ModelicaSystem(fileName=model_file.as_posix(), modelName="BangBang2021")
 
-    mod.setOptimizationOptions(optimizationOptions={"numberOfIntervals": 16,
-                                                    "stopTime": 1,
-                                                    "stepSize": 0.001,
-                                                    "tolerance": 1e-8})
+    optimizationOptions = {
+        "numberOfIntervals": 16,
+        "stopTime": 1,
+        "stepSize": 0.001,
+        "tolerance": 1e-8,
+    }
+    mod.setOptimizationOptions(**optimizationOptions)
 
     # test the getter
     assert mod.getOptimizationOptions()["stopTime"] == "1"