zwitschi
e73a987d25
- Updated README.md to reflect new features and usage instructions. - Removed deprecated Dashboard.html component and integrated dashboard functionality directly into the main application. - Revised architecture documentation for clarity and added module map and request flow diagrams. - Enhanced maintenance model to include equipment association and cost tracking. - Updated requirements.txt to include new dependencies (httpx, pandas, numpy). - Improved consumption, maintenance, production, and reporting routes with better validation and response handling. - Added unit tests for maintenance and production routes, ensuring proper CRUD operations and validation. - Enhanced reporting service to calculate and return detailed summary statistics. - Redesigned Dashboard.html for improved user experience and integrated Chart.js for visualizing simulation results.
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
from statistics import mean, median, pstdev
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from typing import Dict, Iterable, List, Union
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def _extract_results(simulation_results: Iterable[Dict[str, float]]) -> List[float]:
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values: List[float] = []
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for item in simulation_results:
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if not isinstance(item, dict):
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continue
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value = item.get("result")
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if isinstance(value, (int, float)):
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values.append(float(value))
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return values
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def _percentile(values: List[float], percentile: float) -> float:
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if not values:
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return 0.0
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sorted_values = sorted(values)
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if len(sorted_values) == 1:
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return sorted_values[0]
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index = (percentile / 100) * (len(sorted_values) - 1)
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lower = int(index)
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upper = min(lower + 1, len(sorted_values) - 1)
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weight = index - lower
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return sorted_values[lower] * (1 - weight) + sorted_values[upper] * weight
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def generate_report(simulation_results: List[Dict[str, float]]) -> Dict[str, Union[float, int]]:
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"""Aggregate basic statistics for simulation outputs."""
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values = _extract_results(simulation_results)
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if not values:
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return {
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"count": 0,
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"mean": 0.0,
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"median": 0.0,
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"min": 0.0,
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"max": 0.0,
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"std_dev": 0.0,
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"percentile_10": 0.0,
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"percentile_90": 0.0,
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}
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summary: Dict[str, Union[float, int]] = {
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"count": len(values),
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"mean": mean(values),
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"median": median(values),
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"min": min(values),
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"max": max(values),
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"percentile_10": _percentile(values, 10),
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"percentile_90": _percentile(values, 90),
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}
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summary["std_dev"] = pstdev(values) if len(values) > 1 else 0.0
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return summary
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