forked from UNN/2026-rff_mp
66 lines
2.5 KiB
Python
66 lines
2.5 KiB
Python
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from __future__ import annotations
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import csv
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from collections import defaultdict
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from pathlib import Path
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import matplotlib.pyplot as plt
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from typing import List, Dict, Any
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# Карта соответствия заголовков CSV для удобства поддержки
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_CSV_KEYS = {
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"STRUCTURE": "Структура",
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"MODE": "Режим",
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"OP": "Операция",
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"MEASURE": "Замер",
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"TIME": "Время (сек)"
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}
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def load_average_results(csv_file: str) -> List[Dict[str, Any]]:
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"""Загружает только строки со средними значениями из CSV."""
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with open(csv_file, "r", encoding="utf-8") as fh:
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return [
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{
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"structure": row[_CSV_KEYS["STRUCTURE"]],
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"mode": row[_CSV_KEYS["MODE"]],
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"operation": row[_CSV_KEYS["OP"]],
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"time": float(row[_CSV_KEYS["TIME"]])
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}
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for row in csv.DictReader(fh)
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if row[_CSV_KEYS["MEASURE"]] == "среднее"
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]
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def _render_chart(operation: str, data: List[Dict[str, Any]], save_path: Path) -> None:
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"""Вспомогательная функция для отрисовки одного столбчатого графика."""
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fig, ax = plt.subplots(figsize=(10, 5))
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labels = [f"{rec['structure']}\n{rec['mode']}" for rec in data]
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values = [rec["time"] for rec in data]
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ax.bar(labels, values, color="cornflowerblue", edgecolor="navy")
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ax.set_title(f"{operation.capitalize()} Performance Comparison")
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ax.set_xlabel("Data Structure & Input Order")
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ax.set_ylabel("Execution Time (seconds)")
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ax.tick_params(axis="x", rotation=15)
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fig.tight_layout()
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fig.savefig(save_path, dpi=150)
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plt.close(fig)
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print(f"Saved chart: {save_path}")
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def build_graphs(results: List[Dict[str, Any]], output_dir: str = "docs/data") -> None:
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"""Группирует результаты по операциям и сохраняет графики."""
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out_path = Path(output_dir)
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out_path.mkdir(parents=True, exist_ok=True)
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grouped = defaultdict(list)
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for record in results:
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grouped[record["operation"]].append(record)
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for op_name in ("insert", "find", "delete"):
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if op_name in grouped:
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target_file = out_path / f"{op_name}.png"
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_render_chart(op_name, grouped[op_name], target_file)
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def main():
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avg_data = load_average_results("results.csv")
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build_graphs(avg_data)
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if __name__ == "__main__":
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main()
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