v0.1.12 add all slope levels; plot radar with bar

robogauge/utils/radar_plot.py

@@ -1,183 +0,0 @@
-"""
-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=(1.0, 0.1),  # 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)

robogauge/utils/visualize_results.py

@@ -0,0 +1,170 @@
+import matplotlib.pyplot as plt
+from pathlib import Path
+import numpy as np
+import yaml
+import argparse
+import os
+
+# --- 配置 Matplotlib 样式 ---
+config = {
+    "font.family": 'serif',
+    "figure.figsize": (8, 6),
+    "font.size": 12,
+    "mathtext.fontset": 'cm',
+    'axes.unicode_minus': False
+}
+plt.rcParams.update(config)
+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 = []
+    metric_keys = ['lin_vel_err', 'ang_vel_err', 'orientation_stability', 'dof_limits', 'torque_smoothness', 'dof_power']
+    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):
+            print(f"[ERROR] File not found: {path}")
+            continue
+        with open(path, 'r', encoding='utf-8') as f:
+            content = yaml.safe_load(f)
+        
+        raw_path = content.get('model_path', 'Unknown_Model')
+        model_name = os.path.basename(raw_path).replace('.pt', '')
+
+        values = []
+        for k in metric_keys:
+            if k in content:
+                raw_val = content[k]['mean@50']
+                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, r_range=(0, 1.05)):
+    """绘制雷达图"""
+    if not data_list:
+        return
+
+    num_vars = len(labels)
+    angles = np.linspace(0, 2 * np.pi, num_vars, endpoint=False).tolist()
+    angles += angles[:1]
+    
+    colors = plt.cm.get_cmap("tab10", len(data_list))
+    fig, ax = plt.subplots(figsize=(10, 8), subplot_kw=dict(polar=True))
+    plt.subplots_adjust(left=0.05, right=0.75, top=0.9, bottom=0.1)
+
+    ax.set_theta_offset(np.pi / 2)
+    ax.set_theta_direction(-1)
+    
+    plt.xticks(angles[:-1], labels, color='#444444', size=11)
+    
+    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')
+
+    r_min, r_max = r_range
+    ax.set_ylim(r_min, r_max)
+    
+    ticks = np.linspace(r_min, r_max, 5)
+    plt.yticks(ticks, [f"{t:.2f}" for t in ticks], color="grey", size=10)
+    
+    ax.set_rlabel_position(180)
+    ax.grid(True, color='gray', linestyle=':', linewidth=1.5, alpha=0.5)
+    ax.spines['polar'].set_visible(False)
+
+    linewidth = 2.5 
+    for idx, item in enumerate(data_list):
+        values_closed = item['values'] + [item['values'][0]]
+        color = colors(idx)
+        ax.plot(angles, values_closed, linewidth=linewidth, label=item['name'], color=color)
+        ax.fill(angles, values_closed, color=color, alpha=0.15)
+
+    plt.legend(loc='lower left', bbox_to_anchor=(0.82, 0.0), title="Models", frameon=False)
+    plt.title('Performance Comparison (Radar)', size=16, y=1.06)
+    
+    if output_file:
+        plt.savefig(output_file, dpi=300, bbox_inches='tight')
+        print(f"Radar plot saved to {output_file}")
+
+def plot_bar(data_list, labels, output_file=None, h_range=(0, 1.05)):
+    """绘制柱状图"""
+    if not data_list:
+        return
+
+    num_models = len(data_list)
+    num_metrics = len(labels)
+    
+    # 设置柱状图参数
+    x = np.arange(num_metrics)
+    width = 0.8 / num_models  # 自动计算柱子宽度
+    
+    fig, ax = plt.subplots(figsize=(12, 6))
+    colors = plt.cm.get_cmap("tab10", num_models)
+    
+    for idx, item in enumerate(data_list):
+        # 计算每个模型柱子的偏移量
+        offset = (idx - (num_models - 1) / 2) * width
+        ax.bar(x + offset, item['values'], width, label=item['name'], color=colors(idx), alpha=0.8)
+
+    ax.set_ylabel('Score / Value')
+    ax.set_title('Performance Comparison (Bar)', size=16)
+    ax.set_xticks(x)
+    # 将标签中的换行符去掉或处理，使其在柱状图中更美观
+    clean_labels = [l.replace('\n', ' ') for l in labels]
+    ax.set_xticklabels(clean_labels, rotation=15, ha='right')
+    ax.legend(title="Models", bbox_to_anchor=(1.05, 1), loc='upper left', frameon=False)
+    ax.grid(axis='y', linestyle='--', alpha=0.7)
+    if h_range:
+        ax.set_ylim(h_range)
+
+    plt.tight_layout()
+    
+    if output_file:
+        plt.savefig(output_file, dpi=300, bbox_inches='tight')
+        print(f"Bar plot saved to {output_file}")
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('files_or_dir', metavar='F', type=str, nargs='+', help='YAML files or directory')
+    parser.add_argument('--out', type=str, help='Base name for output files')
+    parser.add_argument('--range', type=float, nargs=2, default=[0.0, 1.0], help='Axis range for radar and bar plots')
+    args = parser.parse_args()
+    
+    # 获取文件列表
+    files = args.files_or_dir
+    if Path(args.files_or_dir[0]).is_dir():
+        dir_path = Path(args.files_or_dir[0])
+        files = [str(p) for p in dir_path.glob('*.yaml')]
+    
+    data, metrics_labels = load_data(files)
+
+    # 处理输出文件名
+    radar_out, bar_out = None, None
+    if args.out:
+        out_path = Path(args.out)
+        radar_out = str(out_path.with_name(f"{out_path.stem}_radar{out_path.suffix}"))
+        bar_out = str(out_path.with_name(f"{out_path.stem}_bar{out_path.suffix}"))
+
+    # 分别调用绘图函数
+    plot_radar(data, metrics_labels, output_file=radar_out, r_range=args.range)
+    plot_bar(data, metrics_labels, output_file=bar_out, h_range=args.range)
+    plt.show()