fix: mypy errors on Literal method/sign args in test_piecewise_constraints

CI's type checker flagged six argument-type errors after we tightened
add_piecewise_formulation's signature to Literal-typed method and sign.
The failing sites are all inside existing tests that loop over method
strings (or take method/sign as a pytest.parametrize arg typed as str).

Fix by introducing local Sign / Method TypeAliases that mirror the
piecewise.py signature, then annotating the loop-variable lists and the
one parametrized fixture accordingly.  No behaviour change; the
parametrize("method", ["sos2", "incremental"]) contract was always a
subset of the allowed Literal.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: FBumann

test/test_piecewise_constraints.py

@@ -4,6 +4,7 @@
 
 import logging
 from pathlib import Path
+from typing import Literal, TypeAlias
 
 import numpy as np
 import pandas as pd
@@ -40,6 +41,9 @@
 )
 from linopy.solver_capabilities import SolverFeature, get_available_solvers_with_feature
 
+Sign: TypeAlias = Literal["==", "<=", ">="]
+Method: TypeAlias = Literal["sos2", "incremental", "lp", "auto"]
+
 _sos2_solvers = get_available_solvers_with_feature(
     SolverFeature.SOS_CONSTRAINTS, available_solvers
 )
@@ -1633,7 +1637,8 @@ def test_lp_consistency_with_sos2(self) -> None:
         y_pts = [0, 20, 30, 35]  # concave
 
         solutions = {}
-        for method in ["lp", "sos2", "incremental"]:
+        methods: list[Method] = ["lp", "sos2", "incremental"]
+        for method in methods:
             m = Model()
             power = m.add_variables(lower=0, upper=30, name="power")
             fuel = m.add_variables(lower=0, upper=40, name="fuel")
@@ -1686,7 +1691,8 @@ def test_lp_per_entity_nan_padding(self) -> None:
         bp_y = pd.DataFrame([[0, 20, 30, 35], [0, 10, 15, np.nan]], index=["a", "b"])
         bp_x = pd.DataFrame([[0, 10, 20, 30], [0, 5, 15, np.nan]], index=["a", "b"])
         results: dict[str, float] = {}
-        for method in ["lp", "sos2"]:
+        methods: list[Method] = ["lp", "sos2"]
+        for method in methods:
             m = Model()
             coord = pd.Index(["a", "b"], name="entity")
             x = m.add_variables(lower=0, upper=20, coords=[coord], name="x")
@@ -1723,7 +1729,7 @@ def test_lp_rejects_decreasing_x_concave_ge(self) -> None:
 
     @pytest.mark.skipif(not _sos2_solvers, reason="no SOS2-capable solver available")
     @pytest.mark.parametrize("method", ["sos2", "incremental"])
-    def test_active_off_with_sign_le_leaves_lower_open(self, method: str) -> None:
+    def test_active_off_with_sign_le_leaves_lower_open(self, method: Method) -> None:
         """
         Documents the asymmetry between sign='==' and sign='<=' under
         active=0: equality forces y=0, but '<=' only bounds y ≤ 0 — the
@@ -1816,7 +1822,8 @@ def test_lp_accepts_linear_curve(self) -> None:
         A linear curve is both convex and concave per detection, so
         LP must accept it with either sign and build the formulation.
         """
-        for sign in ["<=", ">="]:
+        signs: list[Sign] = ["<=", ">="]
+        for sign in signs:
             m = Model()
             x = m.add_variables(lower=0, upper=30, name="x")
             y = m.add_variables(lower=0, upper=60, name="y")
@@ -1877,7 +1884,8 @@ def test_lp_matches_sos2_on_multi_dim_variables(self) -> None:
         bp_x = pd.DataFrame([[0, 10, 20, 30], [0, 10, 20, 30]], index=["a", "b"])
         bp_y = pd.DataFrame([[0, 20, 30, 35], [0, 15, 25, 30]], index=["a", "b"])
         ys: dict[str, xr.DataArray] = {}
-        for method in ["lp", "sos2"]:
+        methods: list[Method] = ["lp", "sos2"]
+        for method in methods:
             m = Model()
             x = m.add_variables(lower=0, upper=30, coords=[entities], name="x")
             y = m.add_variables(lower=0, upper=40, coords=[entities], name="y")
@@ -1905,9 +1913,10 @@ def test_lp_consistency_with_sos2_both_directions(self) -> None:
         """
         x_pts = [0, 10, 20, 30]
         y_pts = [0, 20, 30, 35]  # concave
+        methods: list[Method] = ["lp", "sos2"]
         for obj_sign in [-1.0, +1.0]:
             sols: dict[str, float] = {}
-            for method in ["lp", "sos2"]:
+            for method in methods:
                 m = Model()
                 p = m.add_variables(lower=0, upper=30, name="p")
                 f = m.add_variables(lower=0, upper=50, name="f")