Include warnings in set_components

docs/whats_new.rst

@@ -21,13 +21,15 @@ Documentation
 
 Performance
 ~~~~~~~~~~~
-- Improved performace of :py:class:`pysd.py_backend.output.DataFrameHandler` by creating the dataframe at the end of the run (:issue:`374`). (`@easyas314159 <https://github.com/easyas314159>`_ and `@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+- Improved performace of :py:class:`pysd.py_backend.output.DataFrameHandler` by creating the dataframe at the end of the run (:issue:`374` and :issue:`330`). (`@easyas314159 <https://github.com/easyas314159>`_ and `@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
 
 Internal Changes
 ~~~~~~~~~~~~~~~~
 - Move old :py:meth:`pysd.py_backend.model.Macro.set_components` to :py:meth:`pysd.py_backend.model.Macro._set_components`, and create new method with the same name without the `new` argument. (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
 - Move old :py:meth:`pysd.py_backend.model.Macro.set_stateful` to :py:meth:`pysd.py_backend.model.Macro._set_stateful`. (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
 - Make integration tests filter only specific warnings. (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+- Include warnings in :py:meth:`pysd.py_backend.model.Macro.set_components` when changing the behaviour of the component (:issue:`58`). (`@enekomartinmartinez <https://github.com/enekomartinmartinez>`_)
+
 
 v3.12.0 (2023/10/02)
 --------------------

pysd/py_backend/model.py

@@ -1129,6 +1129,10 @@ def _set_components(self, params, new):
                     obj
                 ).set_values(value)
 
+                if not isinstance(value, pd.Series):
+                    warnings.warn(
+                        "Replacing interpolation data with constant values.")
+
                 # Update dependencies
                 if func_type == "Data":
                     if isinstance(value, pd.Series):
@@ -1140,18 +1144,38 @@ def _set_components(self, params, new):
 
                 continue
 
+            if func_type == "Stateful":
+                warnings.warn(
+                    "Replacing the value of Stateful variable with "
+                    "an expression. To set initial conditions use "
+                    "`set_initial_condition` instead..."
+                )
+
             if isinstance(value, pd.Series):
+                if func_type == "Constant":
+                    warnings.warn(
+                        "Replacing a constant value with a "
+                        "time-dependent value. The value will be "
+                        "interpolated over time."
+                    )
                 new_function, deps = self._timeseries_component(
                     value, dims)
                 self._dependencies[func_name] = deps
             elif callable(value):
+                if func_type == "Constant":
+                    warnings.warn(
+                        "Replacing a constant value with a callable. "
+                        "The value may not be constant anymore."
+                    )
                 new_function = value
                 # Using step cache adding time as dependency
                 # TODO it would be better if we can parse the content
                 # of the function to get all the dependencies
                 self._dependencies[func_name] = {"time": 1}
 
             else:
+                if func_type != "Constant":
+                    warnings.warn("Replacing a variable by a constant value.")
                 new_function = self._constant_component(value, dims)
                 self._dependencies[func_name] = {}
 

tests/pytest_pysd/pytest_pysd.py

@@ -309,11 +309,14 @@ def test_set_timeseries_parameter(self, model):
             index=timeseries,
             data=(50 + np.random.rand(len(timeseries)).cumsum())
         )
-        res = model.run(
-            params={"room_temperature": temp_timeseries},
-            return_columns=["room_temperature"],
-            return_timestamps=timeseries,
-        )
+        warn_message = "Replacing a constant value with a time-dependent "\
+                       "value. The value will be interpolated over time."
+        with pytest.warns(UserWarning, match=warn_message):
+            res = model.run(
+                params={"room_temperature": temp_timeseries},
+                return_columns=["room_temperature"],
+                return_timestamps=timeseries,
+            )
         assert (res["room_temperature"] == temp_timeseries).all()
 
     @pytest.mark.parametrize("model_path", [test_model])
@@ -323,7 +326,11 @@ def test_set_timeseries_parameter_inline(self, model):
             index=timeseries,
             data=(50 + np.random.rand(len(timeseries)).cumsum())
         )
-        model.components.room_temperature = temp_timeseries
+        warn_message = "Replacing a constant value with a time-dependent "\
+                       "value. The value will be interpolated over time."
+        with pytest.warns(UserWarning, match=warn_message):
+            model.components.room_temperature = temp_timeseries
+
         res = model.run(
             return_columns=["room_temperature"],
             return_timestamps=timeseries,
@@ -352,8 +359,10 @@ def test_set_components_warnings(self, model):
     def test_set_components_with_function(self, model):
         def test_func():
             return 5
-
-        model.set_components({"Room Temperature": test_func})
+        warn_message = "Replacing a constant value with a callable. "\
+                       "The value may not be constant anymore."
+        with pytest.warns(UserWarning, match=warn_message):
+            model.set_components({"Room Temperature": test_func})
         res = model.run(return_columns=["Room Temperature"])
         assert test_func() == res["Room Temperature"].iloc[0]
 
@@ -549,12 +558,15 @@ def test_set_subscripted_timeseries_parameter_with_constant(self, model):
         xr_series = [xr.DataArray(val, coords, dims) for val in val_series]
 
         temp_timeseries = pd.Series(index=timeseries, data=val_series)
-        res = model.run(
-            params={"initial_values": temp_timeseries, "final_time": 10},
-            return_columns=["initial_values"],
-            return_timestamps=timeseries,
-            flatten_output=False
-        )
+        warn_message = "Replacing a constant value with a time-dependent "\
+                       "value. The value will be interpolated over time."
+        with pytest.warns(UserWarning, match=warn_message):
+            res = model.run(
+                params={"initial_values": temp_timeseries, "final_time": 10},
+                return_columns=["initial_values"],
+                return_timestamps=timeseries,
+                flatten_output=False
+            )
 
         assert np.all(
             [
@@ -583,8 +595,11 @@ def test_set_subscripted_timeseries_parameter_with_partial_xarray(self,
                                                               ).cumsum()]
         temp_timeseries = pd.Series(index=timeseries, data=val_series)
         out_series = [out_b + val for val in val_series]
-        model.set_components({"initial_values": temp_timeseries,
-                              "final_time": 10})
+        warn_message = "Replacing a constant value with a time-dependent "\
+                       "value. The value will be interpolated over time."
+        with pytest.warns(UserWarning, match=warn_message):
+            model.set_components({"initial_values": temp_timeseries,
+                                  "final_time": 10})
         res = model.run(
             return_columns=["initial_values"], flatten_output=False)
         assert np.all(
@@ -610,12 +625,15 @@ def test_set_subscripted_timeseries_parameter_with_xarray(self, model):
             data=[init_val + rd for rd in np.random.rand(len(timeseries)
                                                          ).cumsum()],
         )
-        res = model.run(
-            params={"initial_values": temp_timeseries, "final_time": 10},
-            return_columns=["initial_values"],
-            return_timestamps=timeseries,
-            flatten_output=False
-        )
+        warn_message = "Replacing a constant value with a time-dependent "\
+                       "value. The value will be interpolated over time."
+        with pytest.warns(UserWarning, match=warn_message):
+            res = model.run(
+                params={"initial_values": temp_timeseries, "final_time": 10},
+                return_columns=["initial_values"],
+                return_timestamps=timeseries,
+                flatten_output=False
+            )
 
         assert np.all(
             [
@@ -947,10 +965,24 @@ def test_set_initial_value_subscripted_value_with_numpy_error(self, model):
         with pytest.raises(TypeError):
             model.set_initial_value(new_time + 2, {'_integ_stock_a': input3})
 
+    @pytest.mark.parametrize("model_path", [test_model])
+    def test_replace_stateful(self, model):
+        warn_message = "Replacing the value of Stateful variable with "\
+                       "an expression. To set initial conditions use "\
+                       "`set_initial_condition` instead..."
+        with pytest.warns(UserWarning, match=warn_message):
+            model.components.teacup_temperature = 3
+
+        stocks = model.run()
+        assert np.all(stocks["Teacup Temperature"] == 3)
+
     @pytest.mark.parametrize("model_path", [test_model])
     def test_replace_element(self, model):
         stocks1 = model.run()
-        model.components.characteristic_time = lambda: 3
+        warn_message = "Replacing a constant value with a callable. "\
+                       "The value may not be constant anymore."
+        with pytest.warns(UserWarning, match=warn_message):
+            model.components.characteristic_time = lambda: 3
         stocks2 = model.run()
         assert stocks1["Teacup Temperature"].loc[10]\
             > stocks2["Teacup Temperature"].loc[10]
@@ -1341,7 +1373,10 @@ def test_no_crosstalk(self, _root):
         model_2 = pysd.read_vensim(
             _root.joinpath("test-models/samples/SIR/SIR.mdl"))
 
-        model_1.components.initial_time = lambda: 10
+        warn_message = "Replacing a constant value with a callable. "\
+                       "The value may not be constant anymore."
+        with pytest.warns(UserWarning, match=warn_message):
+            model_1.components.initial_time = lambda: 10
         assert model_2.components.initial_time != 10
 
         # check that the model time is not shared between the two objects
@@ -1480,9 +1515,13 @@ def test_change_constant_pipe(self, model):
 
         # we should ensure that the constant_cache is removed
         # when passing new param
-        out2 = model.run(params={"constant1": new_var})
+        warn_message = "Replacing a constant value with a "\
+                       "time-dependent value. The value will "\
+                       "be interpolated over time."
+        with pytest.warns(UserWarning, match=warn_message):
+            out2 = model.run(params={"constant1": new_var})
 
-        assert not np.all(out1 - out2 == 0)
+        assert not np.array_equal(out1, out2)
 
         for key in pipe:
             assert model.cache_type[key] == "step"

tests/pytest_pysd/pytest_select_submodel.py

@@ -177,7 +177,10 @@ def test_select_submodel(self, model, variables, modules,
                 assert var in str(record[-1].message)
             assert np.any(np.isnan(model.run()))
             # redefine dependencies
-            assert not np.any(np.isnan(model.run(params=dep_vars)))
+            warn_message = "Replacing a variable by a constant value."
+            with pytest.warns(UserWarning, match=warn_message):
+                out = model.run(params=dep_vars)
+            assert not np.any(np.isnan(out))
 
         # select submodel using contour values
         model.reload()

tests/pytest_types/data/pytest_data_with_model.py

@@ -120,10 +120,11 @@ def test_get_data_and_run(self, model, expected):
             expected)
 
     def test_modify_data(self, model, expected):
-        out = model.run(params={
-            "var1": pd.Series(index=[1, 3, 7], data=[10, 20, 30]),
-            "var2": 10
-        })
+        with pytest.warns(UserWarning, match="Replacing .*"):
+            out = model.run(params={
+                "var1": pd.Series(index=[1, 3, 7], data=[10, 20, 30]),
+                "var2": 10
+            })
 
         assert (out["var2"] == 10).all()
         assert (