v2 init

services/reporting.py

@@ -1,79 +0,0 @@
-from statistics import mean, median, pstdev
-from typing import Any, Dict, Iterable, List, Mapping, Union, cast
-
-
-def _extract_results(simulation_results: Iterable[object]) -> List[float]:
-    values: List[float] = []
-    for item in simulation_results:
-        if not isinstance(item, Mapping):
-            continue
-        mapping_item = cast(Mapping[str, Any], item)
-        value = mapping_item.get("result")
-        if isinstance(value, (int, float)):
-            values.append(float(value))
-    return values
-
-
-def _percentile(values: List[float], percentile: float) -> float:
-    if not values:
-        return 0.0
-    sorted_values = sorted(values)
-    if len(sorted_values) == 1:
-        return sorted_values[0]
-    index = (percentile / 100) * (len(sorted_values) - 1)
-    lower = int(index)
-    upper = min(lower + 1, len(sorted_values) - 1)
-    weight = index - lower
-    return sorted_values[lower] * (1 - weight) + sorted_values[upper] * weight
-
-
-def generate_report(
-    simulation_results: List[Dict[str, float]],
-) -> Dict[str, Union[float, int]]:
-    """Aggregate basic statistics for simulation outputs."""
-
-    values = _extract_results(simulation_results)
-
-    if not values:
-        return {
-            "count": 0,
-            "mean": 0.0,
-            "median": 0.0,
-            "min": 0.0,
-            "max": 0.0,
-            "std_dev": 0.0,
-            "variance": 0.0,
-            "percentile_10": 0.0,
-            "percentile_90": 0.0,
-            "percentile_5": 0.0,
-            "percentile_95": 0.0,
-            "value_at_risk_95": 0.0,
-            "expected_shortfall_95": 0.0,
-        }
-
-    summary: Dict[str, Union[float, int]] = {
-        "count": len(values),
-        "mean": mean(values),
-        "median": median(values),
-        "min": min(values),
-        "max": max(values),
-        "percentile_10": _percentile(values, 10),
-        "percentile_90": _percentile(values, 90),
-        "percentile_5": _percentile(values, 5),
-        "percentile_95": _percentile(values, 95),
-    }
-
-    std_dev = pstdev(values) if len(values) > 1 else 0.0
-    summary["std_dev"] = std_dev
-    summary["variance"] = std_dev**2
-
-    var_95 = summary["percentile_5"]
-    summary["value_at_risk_95"] = var_95
-
-    tail_values = [value for value in values if value <= var_95]
-    if tail_values:
-        summary["expected_shortfall_95"] = mean(tail_values)
-    else:
-        summary["expected_shortfall_95"] = var_95
-
-    return summary