Depracation warning for parameter names not being valid python identifiers

ema_workbench/em_framework/parameters.py

@@ -42,6 +42,10 @@ def __set_name__(self, cls, name):
         self.name = name
         self.internal_name = "_" + name
 
+    @abc.abstractmethod
+    def get_bound(self, instance):
+        ...
+
 
 class UpperBound(Bound):
     def get_bound(self, instance):
@@ -63,7 +67,7 @@ def get_bound(self, owner):
         return bound
 
 
-class Constant(NamedObject):
+class Constant(Variable):
     """Constant class,
 
     can be used for any parameter that has to be set to a fixed value
@@ -78,8 +82,10 @@ def __repr__(self, *args, **kwargs):
         return f"{self.__class__.__name__}('{self.name}', {self.value})"
 
 
-class Category(Constant):
-    pass
+class Category(NamedObject):
+    def __init__(self, name, value):
+        super().__init__(name)
+        self.value = value
 
 
 def create_category(cat):

ema_workbench/em_framework/util.py

@@ -62,6 +62,13 @@ def variable_name(self, name):
             name = [name]
         self._variable_name = name
 
+    def __init__(self, name):
+        if not name.isidentifier():
+            DeprecationWarning(
+                f"'{name}' is not a valid Python identifier. In future versions of the workbench, names must be valid python identifiers"
+            )
+        super().__init__(name)
+
 
 class NamedObjectMap:
     def __init__(self, kind):  # @ReservedAssignment

ema_workbench/examples/example_pysd_teacup.py

@@ -18,7 +18,9 @@
 
     model = PysdModel(mdl_file=mdl_file)
 
-    model.uncertainties = [RealParameter("Room Temperature", 33, 120)]
-    model.outcomes = [TimeSeriesOutcome("Teacup Temperature")]
+    model.uncertainties = [
+        RealParameter("room_temperature", 33, 120, variable_name="Room Temperature")
+    ]
+    model.outcomes = [TimeSeriesOutcome("teacup_temperature", variable_name="Teacup Temperature")]
 
     perform_experiments(model, 100)

ema_workbench/examples/example_vensim_advanced_flu.py

@@ -35,17 +35,20 @@ def time_of_max(infected_fraction, time):
 
     # outcomes
     model.outcomes = [
-        TimeSeriesOutcome("deceased population region 1"),
-        TimeSeriesOutcome("infected fraction R1"),
+        TimeSeriesOutcome(
+            "deceased_population_region_1", variable_name="deceased population region 1"
+        ),
+        TimeSeriesOutcome("infected_fraction_R1", variable_name="infected fraction R1"),
         ScalarOutcome(
-            "max infection fraction", variable_name="infected fraction R1", function=np.max
+            "max_infection_fraction", variable_name="infected fraction R1", function=np.max
         ),
         ScalarOutcome(
-            "time of max", variable_name=["infected fraction R1", "TIME"], function=time_of_max
+            "time_of_max", variable_name=["infected fraction R1", "TIME"], function=time_of_max
         ),
     ]
 
     # create uncertainties based on csv
+    # FIXME csv is missing
     model.uncertainties = parameters_from_csv("./models/flu/flu_uncertainties.csv")
 
     # add policies

ema_workbench/examples/example_vensim_energy.py

@@ -0,0 +1,217 @@
+"""
+Created on 27 Jan 2014
+
+@author: jhkwakkel
+"""
+from ema_workbench import (
+    RealParameter,
+    TimeSeriesOutcome,
+    ema_logging,
+    MultiprocessingEvaluator,
+    ScalarOutcome,
+    perform_experiments,
+    CategoricalParameter,
+    save_results,
+    Policy,
+)
+from ema_workbench.connectors.vensim import VensimModel
+from ema_workbench.em_framework.evaluators import SequentialEvaluator
+
+
+def get_energy_model():
+    model = VensimModel(
+        "energyTransition",
+        wd="./models",
+        model_file="RB_V25_ets_1_policy_modified_adaptive_extended_outcomes.vpm",
+    )
+
+    model.outcomes = [
+        TimeSeriesOutcome(
+            "cumulative_carbon_emissions", variable_name="cumulative carbon emissions"
+        ),
+        TimeSeriesOutcome(
+            "carbon_emissions_reduction_fraction",
+            variable_name="carbon emissions reduction fraction",
+        ),
+        TimeSeriesOutcome("fraction_renewables", variable_name="fraction renewables"),
+        TimeSeriesOutcome("average_total_costs", variable_name="average total costs"),
+        TimeSeriesOutcome("total_costs_of_electricity", variable_name="total costs of electricity"),
+    ]
+
+    model.uncertainties = [
+        RealParameter(
+            "demand_fuel_price_elasticity_factor",
+            0,
+            0.5,
+            variable_name="demand fuel price elasticity factor",
+        ),
+        RealParameter(
+            "economic_lifetime_biomass", 30, 50, variable_name="economic lifetime biomass"
+        ),
+        RealParameter("economic_lifetime_coal", 30, 50, variable_name="economic lifetime coal"),
+        RealParameter("economic_lifetime_gas", 25, 40, variable_name="economic lifetime gas"),
+        RealParameter("economic_lifetime_igcc", 30, 50, variable_name="economic lifetime igcc"),
+        RealParameter("economic_lifetime_ngcc", 25, 40, variable_name="economic lifetime ngcc"),
+        RealParameter(
+            "economic_lifetime_nuclear", 50, 70, variable_name="economic lifetime nuclear"
+        ),
+        RealParameter("economic_lifetime_pv", 20, 30, variable_name="economic lifetime pv"),
+        RealParameter("economic_lifetime_wind", 20, 30, variable_name="economic lifetime wind"),
+        RealParameter("economic_lifetime_hydro", 50, 70, variable_name="economic lifetime hydro"),
+        RealParameter(
+            "uncertainty_initial_gross_fuel_costs",
+            0.5,
+            1.5,
+            variable_name="uncertainty initial gross fuel costs",
+        ),
+        RealParameter(
+            "investment_proportionality_constant",
+            0.5,
+            4,
+            variable_name="investment proportionality constant",
+        ),
+        RealParameter(
+            "investors_desired_excess_capacity_investment",
+            0.2,
+            2,
+            variable_name="investors desired excess capacity investment",
+        ),
+        RealParameter(
+            "price_demand_elasticity_factor",
+            -0.07,
+            -0.001,
+            variable_name="price demand elasticity factor",
+        ),
+        RealParameter(
+            "price_volatility_global_resource_markets",
+            0.1,
+            0.2,
+            variable_name="price volatility global resource markets",
+        ),
+        RealParameter("progress_ratio_biomass", 0.85, 1, variable_name="progress ratio biomass"),
+        RealParameter("progress_ratio_coal", 0.9, 1.05, variable_name="progress ratio coal"),
+        RealParameter("progress_ratio_gas", 0.85, 1, variable_name="progress ratio gas"),
+        RealParameter("progress_ratio_igcc", 0.9, 1.05, variable_name="progress ratio igcc"),
+        RealParameter("progress_ratio_ngcc", 0.85, 1, variable_name="progress ratio ngcc"),
+        RealParameter("progress_ratio_nuclear", 0.9, 1.05, variable_name="progress ratio nuclear"),
+        RealParameter("progress_ratio_pv", 0.75, 0.9, variable_name="progress ratio pv"),
+        RealParameter("progress_ratio_wind", 0.85, 1, variable_name="progress ratio wind"),
+        RealParameter("progress_ratio_hydro", 0.9, 1.05, variable_name="progress ratio hydro"),
+        RealParameter(
+            "starting_construction_time", 0.1, 3, variable_name="starting construction time"
+        ),
+        RealParameter(
+            "time_of_nuclear_power_plant_ban",
+            2013,
+            2100,
+            variable_name="time of nuclear power plant ban",
+        ),
+        RealParameter(
+            "weight_factor_carbon_abatement", 1, 10, variable_name="weight factor carbon abatement"
+        ),
+        RealParameter(
+            "weight_factor_marginal_investment_costs",
+            1,
+            10,
+            variable_name="weight factor marginal investment costs",
+        ),
+        RealParameter(
+            "weight_factor_technological_familiarity",
+            1,
+            10,
+            variable_name="weight factor technological familiarity",
+        ),
+        RealParameter(
+            "weight_factor_technological_growth_potential",
+            1,
+            10,
+            variable_name="weight factor technological growth potential",
+        ),
+        RealParameter(
+            "maximum_battery_storage_uncertainty_constant",
+            0.2,
+            3,
+            variable_name="maximum battery storage uncertainty constant",
+        ),
+        RealParameter(
+            "maximum_no_storage_penetration_rate_wind",
+            0.2,
+            0.6,
+            variable_name="maximum no storage penetration rate wind",
+        ),
+        RealParameter(
+            "maximum_no_storage_penetration_rate_pv",
+            0.1,
+            0.4,
+            variable_name="maximum no storage penetration rate pv",
+        ),
+        CategoricalParameter(
+            "SWITCH_lookup_curve_TGC", (1, 2, 3, 4), variable_name="SWITCH lookup curve TGC"
+        ),
+        CategoricalParameter(
+            "SWTICH_preference_carbon_curve", (1, 2), variable_name="SWTICH preference carbon curve"
+        ),
+        CategoricalParameter(
+            "SWITCH_economic_growth", (1, 2, 3, 4, 5, 6), variable_name="SWITCH economic growth"
+        ),
+        CategoricalParameter(
+            "SWITCH_electrification_rate",
+            (1, 2, 3, 4, 5, 6),
+            variable_name="SWITCH electrification rate",
+        ),
+        CategoricalParameter(
+            "SWITCH_Market_price_determination",
+            (1, 2),
+            variable_name="SWITCH Market price determination",
+        ),
+        CategoricalParameter(
+            "SWITCH_physical_limits", (1, 2), variable_name="SWITCH physical limits"
+        ),
+        CategoricalParameter(
+            "SWITCH_low_reserve_margin_price_markup",
+            (1, 2, 3, 4),
+            variable_name="SWITCH low reserve margin price markup",
+        ),
+        CategoricalParameter(
+            "SWITCH_interconnection_capacity_expansion",
+            (1, 2, 3, 4),
+            variable_name="SWITCH interconnection capacity expansion",
+        ),
+        CategoricalParameter(
+            "SWITCH_storage_for_intermittent_supply",
+            (1, 2, 3, 4, 5, 6, 7),
+            variable_name="SWITCH storage for intermittent supply",
+        ),
+        CategoricalParameter("SWITCH_carbon_cap", (1, 2, 3), variable_name="SWITCH carbon cap"),
+        CategoricalParameter(
+            "SWITCH_TGC_obligation_curve", (1, 2, 3), variable_name="SWITCH TGC obligation curve"
+        ),
+        CategoricalParameter(
+            "SWITCH_carbon_price_determination",
+            (1, 2, 3),
+            variable_name="SWITCH carbon price determination",
+        ),
+    ]
+    return model
+
+
+if __name__ == "__main__":
+    ema_logging.log_to_stderr(ema_logging.INFO)
+    model = get_energy_model()
+
+    policies = [
+        Policy("no policy", model_file="RB_V25_ets_1_extended_outcomes.vpm"),
+        Policy("static policy", model_file="ETSPolicy.vpm"),
+        Policy(
+            "adaptive policy",
+            model_file="RB_V25_ets_1_policy_modified_adaptive_extended_outcomes.vpm",
+        ),
+    ]
+
+    n = 100000
+    with MultiprocessingEvaluator(model) as evaluator:
+        experiments, outcomes = evaluator.perform_experiments(n, policies=policies)
+    #
+    # outcomes.pop("TIME")
+    # results = experiments, outcomes
+    # save_results(results, f"./data/{n}_lhs.tar.gz")