168 lines
5.8 KiB
Python
168 lines
5.8 KiB
Python
# -*- coding: utf-8 -*-
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'''
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@File : plot_terrain_levels.py
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@Time : 2025/12/27 23:04:01
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@Author : wty-yy, Gemini3 Pro
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@Version : 1.0
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@Blog : https://wty-yy.github.io/
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@Desc : None
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@Desc : 可视化不同地形下随着摩擦力变化的关卡通过等级 (Terrain Level vs Friction)
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'''
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import matplotlib.pyplot as plt
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from pathlib import Path
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import numpy as np
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import yaml
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import argparse
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import os
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import re
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# --- 配置 Matplotlib 样式 ---
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config = {
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"font.family": 'serif',
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"figure.figsize": (18, 10),
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"font.size": 12,
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"mathtext.fontset": 'cm',
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'axes.unicode_minus': False
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}
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plt.rcParams.update(config)
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plt.rcParams['font.serif'] = ['Times New Roman', 'DejaVu Serif', 'serif']
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def load_terrain_data(file_paths):
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"""
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加载数据并按模型、地形、摩擦力组织
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Returns:
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model_data: {model_name: {terrain_type: {friction: level}}}
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"""
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target_terrains = ['wave', 'slope_fd', 'slope_bd', 'stairs_fd', 'stairs_bd', 'obstacle']
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model_data = {}
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# 用于从键名中提取 friction 的正则 (例如 friction1.25)
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friction_pattern = re.compile(r'friction([\d\.]+)')
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for path in file_paths:
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if not os.path.exists(path):
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print(f"[ERROR] File not found: {path}")
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continue
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with open(path, 'r', encoding='utf-8') as f:
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content = yaml.safe_load(f)
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# 获取模型名称
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raw_path = content.get('model_path', 'Unknown_Model')
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model_name = os.path.basename(raw_path).replace('.pt', '')
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if model_name not in model_data:
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model_data[model_name] = {t: {} for t in target_terrains}
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# 遍历YAML中的每个测试条目
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for key, value in content.items():
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if key in ['model_path', 'summary']:
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continue
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# 1. 检查地形是否在目标列表中
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t_name = value.get('terrain_name')
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if t_name not in target_terrains:
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continue
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# 2. 从 key 中提取摩擦力
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match = friction_pattern.search(key)
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if not match:
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continue
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friction = float(match.group(1))
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# 3. 获取地形等级 (取该条件下该地形的最大值，防止重复)
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level = value.get('terrain_level', 0)
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# 记录数据
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current_max = model_data[model_name][t_name].get(friction, -1)
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if level > current_max:
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model_data[model_name][t_name][friction] = level
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return model_data, target_terrains
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def plot_results(model_data, terrain_labels, output_file=None):
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"""绘制 2x3 的子图"""
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if not model_data:
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print("No data to plot.")
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return
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# 设置 2行3列 的布局
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fig, axes = plt.subplots(2, 3, figsize=(18, 10), sharex=True, sharey=True)
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axes = axes.flatten()
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# 自动获取颜色映射
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colors = plt.cm.get_cmap("tab10", len(model_data))
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# 遍历前5个地形进行绘图
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for i, t_name in enumerate(terrain_labels):
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ax = axes[i]
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for idx, (model_name, terrains) in enumerate(model_data.items()):
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data_points = terrains.get(t_name, {})
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if not data_points:
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continue
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# 排序 (Friction, Level)
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sorted_points = sorted(data_points.items())
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xs, ys = zip(*sorted_points)
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ax.plot(xs, ys, marker='o', linestyle='-', linewidth=2,
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label=model_name, color=colors(idx), alpha=0.8)
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ax.set_title(t_name.replace('_', ' ').title(), fontsize=14)
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ax.grid(True, linestyle='--', alpha=0.6)
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# --- 第6张图：绘制平均值 (Average) ---
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ax_avg = axes[5]
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for idx, (model_name, terrains) in enumerate(model_data.items()):
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# 聚合该模型下所有地形的数据用于计算平均值
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# 结构: friction -> [level_slope, level_wave, ...]
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friction_agg = {}
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for t_name in terrain_labels:
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for f, l in terrains[t_name].items():
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if f not in friction_agg:
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friction_agg[f] = []
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friction_agg[f].append(l)
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if not friction_agg:
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continue
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# 计算平均值并排序
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sorted_frictions = sorted(friction_agg.keys())
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avg_levels = [np.mean(friction_agg[f]) for f in sorted_frictions]
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ax_avg.plot(sorted_frictions, avg_levels, marker='s', linestyle='-', linewidth=2,
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label=model_name, color=colors(idx), alpha=0.8)
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ax_avg.set_title('Average Performance', fontsize=14)
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ax_avg.grid(True, linestyle='--', alpha=0.6)
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# 仅在最后一张图显示图例，避免遮挡
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ax_avg.legend(loc='best', frameon=False, title="Models")
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# 最下面一行设置 X 轴标签
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for i in [3, 4, 5]:
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axes[i].set_xlabel('Friction ($\mu$)')
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# 最左边一列设置 Y 轴标签
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for i in [0, 3]:
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axes[i].set_ylabel('Terrain Level')
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plt.tight_layout()
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# 稍微调整间距防止标签重叠
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# plt.subplots_adjust(wspace=0.1, hspace=0.15)
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if output_file:
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plt.savefig(output_file, dpi=300, bbox_inches='tight')
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print(f"Plot saved to {output_file}")
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else:
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plt.show()
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Plot terrain level vs friction curves.")
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parser.add_argument('files', metavar='F', type=str, nargs='+', help='YAML result files')
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parser.add_argument('--out', type=str, default='terrain_analysis.jpg', help='Output image filename')
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args = parser.parse_args()
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data, labels = load_terrain_data(args.files)
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plot_results(data, labels, output_file=args.out) |