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v1.0.1

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wty-yy
2025-12-30 15:59:07 +08:00
parent 5a5500668b
commit de7d740012
7 changed files with 46 additions and 26 deletions
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20
robogauge/tasks/pipeline/multi_pipeline.py
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@@ -133,7 +133,7 @@ class MultiPipeline:
""" Process results from all processes and aggregate them. """
multi_logger.info("📊 Aggregating Results from all runs...")
summary = {'success': {}, **self.static_info, 'summary': {}, 'terrain_weighted_summary': {}, 'quality_score': {}, 'terrain_quality_score': {}}
summary = {'success': {}, **self.static_info, 'summary': {}, 'terrain_weighted_summary': {}}
finish_msg = (
f"""\n{'='*20} Run Finish Summary {'='*20}\n"""
f"""{'Seed':^10}{'Base Mass':^15}{'Friction':^15}{'Status':^10}\n"""
@@ -152,7 +152,6 @@ class MultiPipeline:
multi_logger.error("No results to aggregate.")
return
quality_score, terrain_quality_score = summary['quality_score'], summary['terrain_quality_score']
value_collections = defaultdict(lambda: defaultdict(list))
for result in all_results:
for goal, metrics in result['results'].items():
@@ -161,27 +160,20 @@ class MultiPipeline:
for metric, means in metrics.items():
for mean_name, mean_value in means.items():
value_collections[metric][mean_name].append(float(mean_value.split(' ')[0]))
quality_score[mean_name] = 1
for metric, means in value_collections.items():
summary['summary'][metric] = {}
summary['terrain_weighted_summary'][metric] = {}
for mean_name, values in means.items():
v = float(np.mean(values))
summary['summary'][metric][mean_name] = f"{v:.4f} ± {float(np.std(values)):.4f}"
twv = v
if 'quality_score' in metric: continue
summary['terrain_weighted_summary'][metric] = {}
for mean_name, values in means.items():
twv = float(np.mean(values))
if summary['terrain_name'] in SEARCH_LEVELS_TERRAINS:
twv = 0.09 * (summary['terrain_level'] - 1) + 0.19 * v
summary['terrain_weighted_summary'][metric][mean_name] = f"{twv:.4f} ± {float(np.std(values)):.4f}"
weight = 1
if metric in ['ang_vel_err', 'lin_vel_err']:
weight = 2
quality_score[mean_name] *= min(max(1e-9, v), 1.0) ** weight
for mean_name in quality_score:
quality_score[mean_name] = quality_score[mean_name] ** (1 / 8) # 2 + 2 + 1 * 4
terrain_quality_score[mean_name] = quality_score[mean_name]
if summary['terrain_name'] in SEARCH_LEVELS_TERRAINS:
terrain_quality_score[mean_name] = 0.09 * (summary['terrain_level'] - 1) + 0.19 * quality_score[mean_name]
save_path = multi_logger.log_dir / "aggregated_results.yaml"
with open(save_path, 'w') as file: