refactor: implement deterministic budget allocation in SoftTopkStrategy (#2077)

* refactor: implement deterministic budget allocation in SoftTopkStrategy

* style: fix formatting issues using black

* fix: remove unused imports and pass pylint

* refactor: simplify SoftTopkStrategy impact limit

* style: relocate test files per maintainer request

tests/backtest/test_soft_topk_strategy_cold_start.py

@@ -0,0 +1,38 @@
+import pandas as pd
+import pytest
+
+from qlib.contrib.strategy.cost_control import SoftTopkStrategy
+
+
+class MockPosition:
+    def __init__(self, weights):
+        self.weights = weights
+
+    def get_stock_weight_dict(self, only_stock=True):
+        return self.weights
+
+
+def create_test_strategy(topk, risk_degree, impact_limit):
+    strat = SoftTopkStrategy.__new__(SoftTopkStrategy)
+    strat.topk = topk
+    strat.risk_degree = risk_degree
+    strat.trade_impact_limit = impact_limit
+    return strat
+
+
+@pytest.mark.parametrize(
+    ("impact_limit", "expected_fill"),
+    [
+        (0.1, 0.1),
+        (1.0, 0.475),
+    ],
+)
+def test_soft_topk_cold_start_impact_limit(impact_limit, expected_fill):
+    scores = pd.Series({"C": 0.9, "D": 0.8, "A": 0.1, "B": 0.1})
+    current_pos = MockPosition({})
+
+    strat = create_test_strategy(topk=2, risk_degree=0.95, impact_limit=impact_limit)
+    res = strat.generate_target_weight_position(scores, current_pos, None, None)
+
+    assert abs(res["C"] - expected_fill) < 1e-8
+    assert abs(res["D"] - expected_fill) < 1e-8