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v0.1.18

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wty-yy
2025-12-28 21:25:08 +08:00
parent 9bcee5004a
commit f1040af529
11 changed files with 140 additions and 39 deletions
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17
robogauge/tasks/pipeline/multi_pipeline.py
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@@ -25,6 +25,7 @@ from robogauge.utils.logger import Logger
from robogauge.utils.process_utils import NoDaemonPool
from robogauge.utils.progress_monitor import report_progress, ProgressTypes, ProgressData
from robogauge.utils.file_utils import compress_directory
from robogauge.tasks.gauge.gauge_configs.terrain_levels_config import SEARCH_LEVELS_TERRAINS
multi_logger = Logger() # MultiPipeline logger
@@ -132,7 +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': {}}
summary = {'success': {}, **self.static_info, 'summary': {}, 'quality_score': {}, 'terrain_quality_score': {}}
finish_msg = (
f"""\n{'='*20} Run Finish Summary {'='*20}\n"""
f"""{'Seed':^10}{'Base Mass':^15}{'Friction':^15}{'Status':^10}\n"""
@@ -151,6 +152,7 @@ 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():
@@ -159,11 +161,22 @@ 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] = {}
for mean_name, values in means.items():
summary['summary'][metric][mean_name] = f"{float(np.mean(values)):.4f} ± {float(np.std(values)):.4f}"
v = float(np.mean(values))
summary['summary'][metric][mean_name] = f"{v:.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: