test: disallow both value range and allowed values.

tests/test_strategies.py

@@ -83,6 +83,7 @@ def variable_integer_strategy(draw, name=None, label=None, units=None, covariate
     )
     value_type = ValueType.INTEGER
     dtype = int
+
     value_range = draw(
         st.one_of(
             st.none(),
@@ -92,20 +93,10 @@ def variable_integer_strategy(draw, name=None, label=None, units=None, covariate
         )
     )
     if value_range is None:
-        allowed_values = draw(
-            st.one_of(st.none(), st.lists(st.integers(), unique=True, min_size=1))
-        )
+        allowed_values = draw(st.one_of(st.none(), st.sets(st.integers(), min_size=1)))
     else:
-        allowed_values = draw(
-            st.one_of(
-                st.none(),
-                st.lists(
-                    st.integers(min_value=value_range[0], max_value=value_range[1]),
-                    unique=True,
-                    min_size=1,
-                ),
-            )
-        )
+        allowed_values = None
+
     rescale = draw(
         st.one_of(
             st.just(1),
@@ -146,25 +137,9 @@ def variable_real_strategy(draw, name=None, label=None, units=None, covariate=No
     )
 
     if value_range is None:
-        allowed_values = draw(
-            st.one_of(st.none(), st.lists(range_strategy, unique=True, min_size=1))
-        )
+        allowed_values = draw(st.one_of(st.none(), st.sets(range_strategy, min_size=1)))
     else:
-        allowed_values = draw(
-            st.one_of(
-                st.none(),
-                st.lists(
-                    st.floats(
-                        min_value=value_range[0],
-                        max_value=value_range[1],
-                        allow_nan=False,
-                        allow_subnormal=False,
-                    ),
-                    unique=True,
-                    min_size=1,
-                ),
-            )
-        )
+        allowed_values = None
     rescale = draw(st.one_of(st.just(1), range_strategy))
     return Variable(
         name=name,
@@ -256,32 +231,35 @@ def variable_class_strategy(draw, name=None, label=None, units=None, covariate=N
     )
 
 
+VARIABLE_STRATEGIES = (
+    variable_boolean_strategy,
+    variable_integer_strategy,
+    variable_probability_strategy,
+    variable_sigmoid_strategy,
+    variable_real_strategy,
+    variable_class_strategy,
+)
+
+
 @st.composite
-def variable_strategy(draw, value_type: Optional[ValueType] = None, **kwargs):
+def variable_strategy(
+    draw, elements=VARIABLE_STRATEGIES, value_type: Optional[ValueType] = None, **kwargs
+):
     if value_type is None:
-        return draw(
-            st.one_of(
-                variable_boolean_strategy(**kwargs),
-                variable_integer_strategy(**kwargs),
-                variable_real_strategy(**kwargs),
-                variable_probability_strategy(**kwargs),
-                variable_sigmoid_strategy(**kwargs),
-                variable_class_strategy(**kwargs),
-            )
-        )
+        strategy = draw(st.sampled_from(elements))
+
     else:
-        return draw(
-            {
-                ValueType.BOOLEAN: variable_boolean_strategy,
-                ValueType.INTEGER: variable_integer_strategy,
-                ValueType.REAL: variable_real_strategy,
-                ValueType.SIGMOID: variable_sigmoid_strategy,
-                ValueType.PROBABILITY: variable_probability_strategy,
-                # ValueType.PROBABILITY_SAMPLE: variable_PROBABILITY_SAMPLE_strategy,
-                # ValueType.PROBABILITY_DISTRIBUTION: variable_PROBABILITY_DISTRIBUTION_strategy,
-                ValueType.CLASS: variable_class_strategy,
-            }[value_type](**kwargs)
-        )
+        strategy = {
+            ValueType.BOOLEAN: variable_boolean_strategy,
+            ValueType.INTEGER: variable_integer_strategy,
+            ValueType.REAL: variable_real_strategy,
+            ValueType.SIGMOID: variable_sigmoid_strategy,
+            ValueType.PROBABILITY: variable_probability_strategy,
+            # ValueType.PROBABILITY_SAMPLE: variable_PROBABILITY_SAMPLE_strategy,
+            # ValueType.PROBABILITY_DISTRIBUTION: variable_PROBABILITY_DISTRIBUTION_strategy,
+            ValueType.CLASS: variable_class_strategy,
+        }[value_type]
+    return draw(strategy(**kwargs))
 
 
 @given(variable_strategy())
@@ -292,6 +270,8 @@ def test_variable_strategy_creation(o):
 @st.composite
 def variablecollection_strategy(
     draw,
+    elements=VARIABLE_STRATEGIES,
+    value_type: Optional[ValueType] = None,
     max_ivs=5,
     max_dvs=1,
     max_covariates=2,
@@ -317,13 +297,28 @@ def variablecollection_strategy(
         )
     )
     independent_variables = [
-        draw(variable_strategy(name=names.pop(), **kwargs)) for _ in range(n_ivs)
+        draw(
+            variable_strategy(
+                name=names.pop(), value_type=value_type, elements=elements, **kwargs
+            )
+        )
+        for _ in range(n_ivs)
     ]
     dependent_variables = [
-        draw(variable_strategy(name=names.pop(), **kwargs)) for _ in range(n_dvs)
+        draw(
+            variable_strategy(
+                name=names.pop(), value_type=value_type, elements=elements, **kwargs
+            )
+        )
+        for _ in range(n_dvs)
     ]
     covariates = [
-        draw(variable_strategy(name=names.pop(), **kwargs)) for _ in range(n_covariates)
+        draw(
+            variable_strategy(
+                name=names.pop(), value_type=value_type, elements=elements, **kwargs
+            )
+        )
+        for _ in range(n_covariates)
     ]
 
     vc = VariableCollection(
@@ -343,17 +338,19 @@ def test_variablecollection_strategy_creation(o):
 def dataframe_strategy(
     draw,
     variables: Optional[Sequence[Variable]] = None,
+    value_type: Optional[ValueType] = None,
 ):
     if variables is None:
-        variable_collection = draw(variablecollection_strategy())
+        variable_collection = draw(variablecollection_strategy(value_type=value_type))
         variables = (
             variable_collection.independent_variables
             + variable_collection.dependent_variables
             + variable_collection.covariates
         )
+
     df: pd.DataFrame = draw(
         st_pd.data_frames(
-            columns=[st_pd.column(name=v.name, dtype=v.data_type) for v in variables],
+            columns=[st_pd.column(dtype=v.data_type) for v in variables],
         )
     )