v0.1.10

robogauge/utils/radar_plot.py

@@ -0,0 +1,183 @@
+"""
+python robogauge/utils/radar_plot.py \
+    /home/xfy/Coding/robot_gauge/logs/go2_moe_flat_debug_multi/20251218-22-49-29_run_multi/aggregated_results.yaml \
+    /home/xfy/Coding/robot_gauge/logs/go2_flat_debug_multi/20251218-22-59-04_run_multi/aggregated_results.yaml \
+    --out logs/go2_flat_vs_moe_flat.png
+"""
+import matplotlib.pyplot as plt
+config = {
+    "font.family": 'serif', # 衬线字体
+    "figure.figsize": (6, 6),  # 图像大小
+    "font.size": 14, # 字号大小
+    "mathtext.fontset": 'cm', # 渲染数学公式字体
+    'axes.unicode_minus': False # 显示负号
+}
+plt.rcParams.update(config)
+
+import numpy as np
+import yaml
+import argparse
+import os
+import sys
+
+# 设置字体，尝试匹配参考图的衬线体风格 (如果系统没有会回退到默认)
+plt.rcParams['font.family'] = 'serif' 
+plt.rcParams['font.serif'] = ['Times New Roman', 'DejaVu Serif', 'serif']
+
+def parse_value_string(val_str):
+    if isinstance(val_str, (int, float)):
+        return float(val_str)
+    if isinstance(val_str, str):
+        if '±' in val_str:
+            return float(val_str.split('±')[0].strip())
+        return float(val_str)
+    return 0.0
+
+def load_data(file_paths):
+    all_data = []
+    
+    # 指标键名
+    metric_keys = [
+        'lin_vel_err', 
+        'ang_vel_err', 
+        'orientation_stability', 
+        'dof_limits', 
+        'torque_smoothness', 
+        'dof_power'
+    ]
+    
+    # 标签 (增加换行以避免拥挤)
+    labels_map = {
+        'lin_vel_err': 'Lin Vel\nAccuracy',
+        'ang_vel_err': 'Ang Vel\nAccuracy',
+        'dof_limits': 'Joint Limits\nMargin',
+        'dof_power': 'Energy\nEfficiency',
+        'orientation_stability': 'Orientation\nStability',
+        'torque_smoothness': 'Torque\nSmoothness',
+    }
+
+    for path in file_paths:
+        if not os.path.exists(path):
+            continue
+            
+        with open(path, 'r', encoding='utf-8') as f:
+            content = yaml.safe_load(f)
+            
+        raw_path = content.get('model_path', 'Unknown_Model')
+        # 简化图例名称：只取文件名，去掉 .pt
+        model_name = os.path.basename(raw_path).replace('.pt', '')
+        
+        # 如果名称过长，可以考虑进一步截断，例如：
+        # if len(model_name) > 20: model_name = model_name[:10] + "..." + model_name[-5:]
+
+        values = []
+        for k in metric_keys:
+            if k in content:
+                raw_val = content[k]['mean']
+                values.append(parse_value_string(raw_val))
+            else:
+                values.append(0.0)
+        
+        all_data.append({'name': model_name, 'values': values})
+        
+    return all_data, [labels_map[k] for k in metric_keys]
+
+def plot_radar(data_list, labels, output_file=None):
+    if not data_list:
+        print("No data to plot.")
+        return
+
+    num_vars = len(labels)
+    angles = np.linspace(0, 2 * np.pi, num_vars, endpoint=False).tolist()
+    angles += angles[:1] # 闭合
+    
+    # --- 颜色设置 ---
+    # 使用参考图类似的配色 (深蓝、浅蓝、绿等)
+    # 或者使用 'tab10', 'Set2' 等
+    colors = plt.cm.get_cmap("tab10", len(data_list))
+    
+    # 创建画布，稍微宽一点以便放图例
+    fig, ax = plt.subplots(figsize=(10, 8), subplot_kw=dict(polar=True))
+    
+    # --- 核心修改：调整布局 ---
+    # left=0.1, bottom=0.1, top=0.9 是为了给标题留空
+    # right=0.75 是关键！这意味着图表只占画布左边 75% 的宽度，右边 25% 留给图例
+    plt.subplots_adjust(left=0.05, right=0.75, top=0.9, bottom=0.1)
+
+    # 设置方向
+    ax.set_theta_offset(np.pi / 2)
+    ax.set_theta_direction(-1)
+    
+    # --- 绘制标签 ---
+    plt.xticks(angles[:-1], labels, color='#444444', size=13)
+    
+    # 标签对齐优化
+    for label, angle in zip(ax.get_xticklabels(), angles[:-1]):
+        if angle in (0, np.pi):
+            label.set_horizontalalignment('center')
+        elif 0 < angle < np.pi:
+            label.set_horizontalalignment('left')
+        else:
+            label.set_horizontalalignment('right')
+
+    # --- 绘制刻度 ---
+    ax.set_rlabel_position(0)
+    # 字体稍微调淡一点，不要抢眼
+    plt.yticks([0.25, 0.50, 0.75, 1.00], ["0.25", "0.50", "0.75", "1.00"], 
+               color="grey", size=10)
+    plt.ylim(0, 1.05)
+    
+    # 网格线：点状虚线，稍微粗一点
+    ax.grid(True, color='gray', linestyle=':', linewidth=1.5, alpha=0.5)
+    ax.spines['polar'].set_visible(False)
+
+    # --- 绘制数据 ---
+    # 加粗线条以匹配 bsuite 风格
+    linewidth = 3.0 
+    
+    for idx, item in enumerate(data_list):
+        values = item['values']
+        name = item['name']
+        values_closed = values + values[:1]
+        
+        color = colors(idx)
+        
+        ax.plot(angles, values_closed, linewidth=linewidth, linestyle='-', label=name, color=color)
+        ax.fill(angles, values_closed, color=color, alpha=0.2) # 填充透明度低一点
+
+    # --- 核心修改：图例位置 ---
+    # bbox_to_anchor=(1.1, 0.2) 的意思是：
+    # 锚点位于坐标轴右侧(1.1倍宽位置)，垂直方向在底部(0.2倍高位置)
+    # loc='upper left' 意思是图例的左上角对齐这个锚点
+    legend = plt.legend(
+        loc='upper left', 
+        bbox_to_anchor=(1.1, 0.3),  # 调整这里的 0.3 可以上下移动图例
+        title="Models", 
+        title_fontsize=16,
+        fontsize=12,
+        frameon=False, # 无边框
+        labelspacing=0.8 # 图例行间距
+    )
+    
+    # 设置图例标题对齐方式 (左对齐)
+    legend._legend_box.align = "left"
+
+    plt.title('Multi-Model Performance Comparison', size=18, y=1.08, color='#333333')
+    
+    if output_file:
+        plt.savefig(output_file, dpi=300, bbox_inches='tight') # bbox_inches='tight' 会自动裁剪白边
+        print(f"Plot saved to {output_file}")
+    else:
+        plt.show()
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('files', metavar='F', type=str, nargs='+', help='YAML files')
+    parser.add_argument('--out', type=str, default=None, help='Output file')
+    
+    # 调试用（如果你直接运行脚本，请取消注释并填入你的文件名）
+    # sys.argv = ['plot.py', 'aggregated_results.yaml', 'aggregated_results2.yaml', '--out', 'fixed_radar.png']
+
+    args = parser.parse_args()
+    data, metrics_labels = load_data(args.files)
+    plot_radar(data, metrics_labels, output_file=args.out)