CLN: Remove unreachable code

Author: bashtage

linearmodels/iv/model.py

@@ -50,7 +50,6 @@
     OneWayClusteredWeightMatrix,
 )
 from linearmodels.iv.results import IVGMMResults, IVResults, OLSResults
-from linearmodels.panel.utility import InvalidFormulaError
 from linearmodels.shared.exceptions import IndexWarning, missing_warning
 from linearmodels.shared.hypotheses import InvalidTestStatistic, WaldTestStatistic
 from linearmodels.shared.linalg import has_constant, inv_sqrth
@@ -300,11 +299,6 @@ def predict(
             parser = IVFormulaParser(self.formula, data, eval_env=eval_env)
             exog = parser.exog
             endog = parser.endog
-            if exog is None and exog is None:
-                raise InvalidFormulaError(
-                    f"Parsed formula ({self.formula}) has no exog and no endog. One "
-                    f"of these must be included in the formula to make a prediction."
-                )
         if all(a is None for a in (exog, endog, data)):
             raise ValueError("At least one of exog, endog, or data must be provided.")
         if exog is None:

linearmodels/panel/utility.py

@@ -24,7 +24,6 @@
 __all__ = [
     "AbsorbingEffectError",
     "AbsorbingEffectWarning",
-    "InvalidFormulaError",
     "_drop_singletons",
     "_py_drop_singletons",
     "_remove_node",
@@ -689,7 +688,3 @@ def generate_panel_data(
     clusters = concat([vc1_df, vc2_df], sort=False)
     data = concat([y_df, x_df], axis=1, sort=False)
     return PanelModelData(data, w_df, other_eff, clusters)
-
-
-class InvalidFormulaError(Exception):
-    pass

linearmodels/tests/iv/test_formulas.py

@@ -416,3 +416,27 @@ def test_predict_no_rhs(data, model_and_func):
     pred1 = res.predict(data=data)
     pred1.columns = pred0.columns
     assert_frame_equal(pred0, pred1)
+
+
+@pytest.mark.parametrize(
+    "fmla",
+    [
+        "y ~ 1",
+        "y ~ 1 + x3",
+        "y ~ [x1 + x2 ~ 1 + z1 + z2 + z3]",
+        "y ~ 1 + [x1 + x2 ~ z1 + z2 + z3]",
+    ],
+)
+def test_formula_single(data, model_and_func, fmla):
+    model, func = model_and_func
+    res = model.from_formula(fmla, data).fit()
+    pred0 = res.predict()
+    pred1 = res.predict(data=data)
+
+    mod2 = func(fmla, data)
+    res2 = mod2.fit()
+    pred2 = res2.predict(data=data)
+    pred1.columns = pred0.columns
+    pred2.columns = pred0.columns
+    assert_frame_equal(pred1, pred2)
+    assert_frame_equal(pred0, pred1)