Remove assert statement from non-test files

ema_workbench/analysis/cart.py

@@ -142,7 +142,8 @@ def boxes(self):
         # based on
         # http://stackoverflow.com/questions/20224526/how-to-extract-the-
         # decision-rules-from-scikit-learn-decision-tree
-        assert self.clf
+        if not self.clf:
+            raise AssertionError
 
         left = self.clf.tree_.children_left
         right = self.clf.tree_.children_right

ema_workbench/analysis/plotting_util.py

@@ -660,8 +660,10 @@ def make_continuous_grouping_specifiers(array, nr_of_groups=5):
     maximum = np.max(array)
     step = (maximum - minimum) / nr_of_groups
     a = [(minimum + step * x, minimum + step * (x + 1)) for x in range(nr_of_groups)]
-    assert a[0][0] == minimum
-    assert a[-1][1] == maximum
+    if a[0][0] != minimum:
+        raise AssertionError
+    if a[-1][1] != maximum:
+        raise AssertionError
     return a
 
 

ema_workbench/analysis/prim_util.py

@@ -42,8 +42,10 @@ def get_quantile(data, quantile):
                the desired quantile
 
     """
-    assert quantile > 0
-    assert quantile < 1
+    if quantile <= 0:
+        raise AssertionError
+    if quantile >= 1:
+        raise AssertionError
 
     data = np.sort(data)
 

ema_workbench/analysis/scenario_discovery_util.py

@@ -278,7 +278,8 @@ def _setup(results, classify, incl_unc=[]):
     else:
         raise TypeError("unknown type for classify")
 
-    assert y.ndim == 1
+    if y.ndim != 1:
+        raise AssertionError
 
     return x, y, mode
 

ema_workbench/connectors/simio_connector.py

@@ -89,7 +89,8 @@ def __init__(
 
         """
         super().__init__(name, wd=wd, model_file=model_file)
-        assert main_model != None
+        if main_model == None:
+            raise AssertionError
         self.main_model_name = main_model
         self.output = {}
         self.n_replications = n_replications

ema_workbench/em_framework/evaluators.py

@@ -768,9 +768,12 @@ def robust_optimize(
 
     """
     for rf in robustness_functions:
-        assert isinstance(rf, ScalarOutcome)
-        assert rf.kind != AbstractOutcome.INFO
-        assert rf.function is not None
+        if not isinstance(rf, ScalarOutcome):
+            raise AssertionError
+        if rf.kind == AbstractOutcome.INFO:
+            raise AssertionError
+        if rf.function is None:
+            raise AssertionError
 
     problem = to_robust_problem(
         model,

ema_workbench/em_framework/optimization.py

@@ -115,14 +115,18 @@ def __init__(
 
         super().__init__(len(parameters), len(outcome_names), nconstrs=len(constraints))
         #         assert len(parameters) == len(parameter_names)
-        assert searchover in ("levers", "uncertainties", "robust")
+        if searchover not in ("levers", "uncertainties", "robust"):
+            raise AssertionError
 
         if searchover == "levers":
-            assert not reference or isinstance(reference, Scenario)
+            if not (not reference or isinstance(reference, Scenario)):
+                raise AssertionError
         elif searchover == "uncertainties":
-            assert not reference or isinstance(reference, Policy)
+            if not (not reference or isinstance(reference, Policy)):
+                raise AssertionError
         else:
-            assert not reference
+            if reference:
+                raise AssertionError
 
         self.searchover = searchover
         self.parameters = parameters
@@ -140,7 +144,8 @@ def __init__(
         self, parameters, outcome_names, scenarios, robustness_functions, constraints
     ):
         super().__init__("robust", parameters, outcome_names, constraints)
-        assert len(robustness_functions) == len(outcome_names)
+        if len(robustness_functions) != len(outcome_names):
+            raise AssertionError
         self.scenarios = scenarios
         self.robustness_functions = robustness_functions
 
@@ -604,7 +609,8 @@ def __init__(
         self.logging_freq = logging_freq
 
         for metric in metrics:
-            assert isinstance(metric, AbstractConvergenceMetric)
+            if not isinstance(metric, AbstractConvergenceMetric):
+                raise AssertionError
             metric.reset()
 
     def __call__(

ema_workbench/em_framework/outcomes.py

@@ -549,7 +549,8 @@ class Constraint(ScalarOutcome):
     """
 
     def __init__(self, name, parameter_names=None, outcome_names=None, function=None):
-        assert callable(function)
+        if not callable(function):
+            raise AssertionError
         if not parameter_names:
             parameter_names = []
         elif isinstance(parameter_names, str):
@@ -574,7 +575,8 @@ def __init__(self, name, parameter_names=None, outcome_names=None, function=None
 
     def process(self, values):
         value = super().process(values)
-        assert value >= 0
+        if value < 0:
+            raise AssertionError
         return value
 
 

ema_workbench/em_framework/parameters.py

@@ -159,9 +159,10 @@ def from_dist(cls, name, dist, **kwargs):
         **kwargs : valid keyword arguments for Parameter instance
 
         """
-        assert isinstance(
+        if not isinstance(
             dist, sp.stats._distn_infrastructure.rv_frozen
-        )  # @UndefinedVariable
+        ):
+            raise AssertionError
         self = cls.__new__(cls)
         self.dist = dist
         self.name = name