v0.1.12 add all slope levels; plot radar with bar
This commit is contained in:
wty-yy
@@ -4,8 +4,10 @@ from robogauge.tasks.robots import RobotConfig, Go2Config, Go2MoEConfig
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from robogauge.tasks.pipeline import BasePipeline
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from robogauge.tasks.gauge import BaseGaugeConfig
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from robogauge.tasks.custom.go2_flat_task import Go2FlatGaugeConfig, Go2FlatConfig, Go2MoEFlatConfig, Go2MoEFlatMujocoConfig
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from robogauge.tasks.custom.go2 import *
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task_register.register('base', BasePipeline, MujocoConfig, BaseGaugeConfig, RobotConfig)
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task_register.register('go2_flat', BasePipeline, MujocoConfig, Go2FlatGaugeConfig, Go2FlatConfig)
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task_register.register('go2_moe_flat', BasePipeline, Go2MoEFlatMujocoConfig, Go2FlatGaugeConfig, Go2MoEFlatConfig)
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task_register.register('go2_flat', BasePipeline, MujocoConfig, Go2FlatGaugeConfig, Go2Config)
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task_register.register('go2_moe_flat', BasePipeline, MujocoConfig, Go2FlatGaugeConfig, Go2MoEConfig)
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task_register.register('go2_slope', BasePipeline, Go2SlopeMujocoConfig, Go2SlopeGaugeConfig, Go2Config)
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task_register.register('go2_moe_slope', BasePipeline, Go2SlopeMujocoConfig, Go2SlopeGaugeConfig, Go2MoEConfig)
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10
robogauge/tasks/custom/go2/__init__.py
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10
robogauge/tasks/custom/go2/__init__.py
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@@ -0,0 +1,10 @@
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# -*- coding: utf-8 -*-
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'''
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@File : __init__.py
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@Time : 2025/12/21 17:10:59
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@Author : wty-yy
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@Version : 1.0
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@Blog : https://wty-yy.github.io/
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'''
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from .go2_flat_task import Go2FlatGaugeConfig
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from .go2_slope_task import Go2SlopeGaugeConfig, Go2SlopeMujocoConfig
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@@ -37,24 +37,3 @@ class Go2FlatGaugeConfig(FlatGaugeConfig):
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ang_vel_yaw = 1.5 # +/- rad/s
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max_cmd_duration = 10.0 # [s] maximum duration to reach the target position
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reach_threshold = 0.1 # [m] distance threshold to consider the target reached
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class Go2FlatConfig(Go2Config):
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class commands(Go2Config.commands):
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lin_vel_x = [-1.8, 1.8] # min max [m/s]
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lin_vel_y = [-1.8, 1.8] # min max [m/s]
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ang_vel_yaw = [-2.0, 2.0] # min max [rad/s]
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class Go2MoEFlatConfig(Go2MoEConfig):
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class commands(Go2Config.commands):
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lin_vel_x = [-1.8, 1.8] # min max [m/s]
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lin_vel_y = [-1.8, 1.8] # min max [m/s]
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ang_vel_yaw = [-2.0, 2.0] # min max [rad/s]
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class control(Go2Config.control):
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model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_moe_cts_124k.pt"
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# model_path = "/home/xfy/Coding/kaiwu2025/rob_finals/sim2real/models/v6-2_106503/kaiwu_script_v6-2_106503.pt"
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class Go2MoEFlatMujocoConfig(MujocoConfig):
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class domain_rand(MujocoConfig.domain_rand):
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base_mass = 0.0
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friction = 1.0
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24
robogauge/tasks/custom/go2/go2_slope_task.py
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24
robogauge/tasks/custom/go2/go2_slope_task.py
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@@ -0,0 +1,24 @@
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# -*- coding: utf-8 -*-
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'''
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@File : go2_slope_task.py
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@Time : 2025/12/21 17:06:27
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@Author : wty-yy
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@Version : 1.0
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@Blog : https://wty-yy.github.io/
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@Desc : Go2 Slope Task Configuration
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'''
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from robogauge.tasks.robots import Go2Config, Go2MoEConfig
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from robogauge.tasks.gauge import SlopeGaugeConfig
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from robogauge.tasks.simulator.mujoco_config import MujocoConfig
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class Go2SlopeGaugeConfig(SlopeGaugeConfig):
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class metrics(SlopeGaugeConfig.metrics):
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class dof_limits(SlopeGaugeConfig.metrics.dof_limits):
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enabled = True
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soft_dof_limit_ratio = 0.7
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dof_names = ['hip', 'thigh'] # List of DOF names to monitor, None for all
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class Go2SlopeMujocoConfig(MujocoConfig):
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class domain_rand(MujocoConfig.domain_rand):
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action_delay = True
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friction = 2.4
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@@ -1,3 +1,4 @@
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from .base_gauge import BaseGauge
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from .base_gauge_config import BaseGaugeConfig
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from .gauge_configs.flat_gauge_config import FlatGaugeConfig
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from .gauge_configs.slope_gauge_config import SlopeGaugeConfig
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@@ -20,18 +20,19 @@ class BaseGaugeConfig(Config):
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class goals:
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class max_velocity: # goal with maximum velocity
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enabled = True
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enabled = False
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cmd_duration = 5.0 # [s] duration for each velocity command
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class diagonal_velocity: # goal with diagonal velocity changes
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enabled = True
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enabled = False
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cmd_duration = 6.0 # [s] duration for a pair of diagonal velocity commands
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class target_pos_velocity: # goal to reach a target position by velocity command
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enabled = True
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enabled = False
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target_pos = [5, 0, 0] # x y z [m], target position in the environment, used for target position goal
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lin_vel_x = 1.0 # +/- m/s
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ang_vel_yaw = 1.0 # +/- rad/s
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lin_vel_y = 1.0 # +/- m/s
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ang_vel_yaw = 1.5 # +/- rad/s
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max_cmd_duration = 10.0 # [s] maximum duration to reach the target position
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reach_threshold = 0.1
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@@ -16,40 +16,3 @@ class FlatGaugeConfig(BaseGaugeConfig):
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terrain_name = "flat_0" # {type}_{level}
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terrain_xml = '{ROBOGAUGE_ROOT_DIR}/resources/terrains/flat.xml'
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terrain_spawn_pos = [0, 0, 0] # x y z [m], robot freejoint spawn position on the terrain
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class goals(BaseGaugeConfig.goals):
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class max_velocity: # goal with maximum velocity
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enabled = True
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move_duration = 5.0 # [s] duration for each velocity command
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end_stance = True # whether to end with zero velocity command
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standce_duration = 2.0 # [s] duration for the ending stance command
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class diagonal_velocity: # goal with diagonal velocity changes
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enabled = True
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cmd_duration = 6.0 # [s] duration for a pair of diagonal velocity commands
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class target_pos_velocity: # goal to reach a target position by velocity command, config target at assets.target_pos
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enabled = True
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target_pos = [5, 0, 0] # x y z [m], target position in the environment, used for target position goal
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lin_vel_x = 1.0 # +/- m/s
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ang_vel_yaw = 1.0 # +/- rad/s
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max_cmd_duration = 10.0 # [s] maximum duration to reach the target position
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reach_threshold = 0.1
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class metrics(BaseGaugeConfig.metrics):
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metric_dt = 0.1 # [s] frequency to compute metrics
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class dof_limits:
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enabled = True
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soft_dof_limit_ratio = 0.9
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dof_names = None # List of DOF names to monitor, None for all
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class visualization:
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enabled = True
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dof_torque = True
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dof_pos = True
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class lin_vel_err:
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enabled = True
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class ang_vel_err:
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enabled = True
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28
robogauge/tasks/gauge/gauge_configs/slope_gauge_config.py
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28
robogauge/tasks/gauge/gauge_configs/slope_gauge_config.py
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@@ -0,0 +1,28 @@
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# -*- coding: utf-8 -*-
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'''
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@File : slope_gauge_config.py
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@Time : 2025/12/21 17:02:23
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@Author : wty-yy
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@Version : 1.0
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@Blog : https://wty-yy.github.io/
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@Desc : Slope Gauge Configuration
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'''
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from robogauge.tasks.gauge.base_gauge_config import BaseGaugeConfig
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class SlopeGaugeConfig(BaseGaugeConfig):
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gauge_class = 'BaseGauge'
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class assets(BaseGaugeConfig.assets):
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terrain_name = "slope_5" # {type}_{level}
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terrain_xml = '{ROBOGAUGE_ROOT_DIR}/resources/terrains/slope/slope_10.xml'
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terrain_spawn_pos = [0, 0, 0] # x y z [m], robot freejoint spawn position on the terrain
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class goals:
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class target_pos_velocity: # goal to reach a target position by velocity command
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enabled = True
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target_pos = [4, 0, 2.0] # x y z [m], target position in the environment, used for target position goal
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lin_vel_x = 1.0 # +/- m/s
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lin_vel_y = 1.0 # +/- m/s
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ang_vel_yaw = 1.5 # +/- rad/s
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max_cmd_duration = 20.0 # [s] maximum duration to reach the target position
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reach_threshold = 0.1
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@@ -9,6 +9,7 @@
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'''
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import yaml
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import random
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import traceback
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import numpy as np
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from pathlib import Path
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from copy import deepcopy
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@@ -104,7 +105,7 @@ class BasePipeline:
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if self.gauge.is_reset(sim_data):
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sim_data = self.reset_sim(sim_data)
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except Exception as e:
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logger.error(f"❌ Pipeline execution failed with error: {e}")
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logger.error(f"❌ Pipeline execution failed with error: {e},\n{traceback.format_exc()}")
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self.gauge.switch_to_next_goal() # save current goal metrics
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self.gauge.save_results()
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return logger.log_dir, e
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@@ -21,7 +21,7 @@ class RobotConfig(Config):
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class control:
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device = 'cpu'
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# torch script model path
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model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_cts_83501.pt"
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model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_cts_max2_100k.pt"
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control_dt = 0.02 # 50 Hz
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control_type = 'P' # Position control
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support_goal: Literal['velocity', 'position'] = 'velocity'
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@@ -20,7 +20,7 @@ class Go2Config(RobotConfig):
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class control(RobotConfig.control):
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device = 'cpu'
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model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_cts_83501.pt"
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model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_cts_max2_100k.pt"
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# model_path = "{ROBOGAUGE_ROOT_DIR}/resources/models/go2/go2_cts_cmd-1,1_38k.pt"
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control_dt = 0.02 # 50 Hz
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control_type = 'P' # Position control
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@@ -47,8 +47,8 @@ class Go2Config(RobotConfig):
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cmd = [2.0, 2.0, 0.25]
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class commands(RobotConfig.commands):
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lin_vel_x = [-1.5, 1.5] # min max [m/s]
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lin_vel_y = [-1, 1] # min max [m/s]
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lin_vel_x = [-2.0, 2.0] # min max [m/s]
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lin_vel_y = [-1.0, 1.0] # min max [m/s]
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lin_vel_z = None # min max [m/s]
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ang_vel_roll = None # min max [rad/s]
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ang_vel_pitch = None # min max [rad/s]
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@@ -15,7 +15,12 @@ from robogauge.tasks.robots.go2.go2 import Go2
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class Go2MoE(Go2):
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def get_action(self, obs: np.ndarray):
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obs_tensor = torch.tensor(obs, dtype=torch.float32).unsqueeze(0).to(self.device)
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action, weights = self.model(obs_tensor)
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action, results = self.model(obs_tensor)
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if isinstance(results, tuple):
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weights, latent = results
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latent = latent.detach().cpu().numpy().squeeze(0)
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else:
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weights = results
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action = action.detach().cpu().numpy().squeeze(0)[self.model2mj_idx]
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weights = weights.detach().cpu().numpy().squeeze(0)
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self.last_action = action
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@@ -1,183 +0,0 @@
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"""
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python robogauge/utils/radar_plot.py \
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/home/xfy/Coding/robot_gauge/logs/go2_moe_flat_debug_multi/20251218-22-49-29_run_multi/aggregated_results.yaml \
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/home/xfy/Coding/robot_gauge/logs/go2_flat_debug_multi/20251218-22-59-04_run_multi/aggregated_results.yaml \
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--out logs/go2_flat_vs_moe_flat.png
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"""
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import matplotlib.pyplot as plt
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config = {
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"font.family": 'serif', # 衬线字体
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"figure.figsize": (6, 6), # 图像大小
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"font.size": 14, # 字号大小
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"mathtext.fontset": 'cm', # 渲染数学公式字体
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'axes.unicode_minus': False # 显示负号
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}
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plt.rcParams.update(config)
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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 sys
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# 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)
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plt.rcParams['font.family'] = 'serif'
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plt.rcParams['font.serif'] = ['Times New Roman', 'DejaVu Serif', 'serif']
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def parse_value_string(val_str):
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if isinstance(val_str, (int, float)):
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return float(val_str)
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if isinstance(val_str, str):
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if '±' in val_str:
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return float(val_str.split('±')[0].strip())
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return float(val_str)
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return 0.0
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def load_data(file_paths):
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all_data = []
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# 指标键名
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metric_keys = [
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'lin_vel_err',
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'ang_vel_err',
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'orientation_stability',
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'dof_limits',
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'torque_smoothness',
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'dof_power'
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]
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# 标签 (增加换行以避免拥挤)
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labels_map = {
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'lin_vel_err': 'Lin Vel\nAccuracy',
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'ang_vel_err': 'Ang Vel\nAccuracy',
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'dof_limits': 'Joint Limits\nMargin',
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'dof_power': 'Energy\nEfficiency',
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'orientation_stability': 'Orientation\nStability',
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'torque_smoothness': 'Torque\nSmoothness',
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}
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for path in file_paths:
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if not os.path.exists(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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raw_path = content.get('model_path', 'Unknown_Model')
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# 简化图例名称：只取文件名，去掉 .pt
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model_name = os.path.basename(raw_path).replace('.pt', '')
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# 如果名称过长，可以考虑进一步截断，例如：
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# if len(model_name) > 20: model_name = model_name[:10] + "..." + model_name[-5:]
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values = []
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for k in metric_keys:
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if k in content:
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raw_val = content[k]['mean']
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values.append(parse_value_string(raw_val))
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else:
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values.append(0.0)
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all_data.append({'name': model_name, 'values': values})
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return all_data, [labels_map[k] for k in metric_keys]
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def plot_radar(data_list, labels, output_file=None):
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if not data_list:
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print("No data to plot.")
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return
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num_vars = len(labels)
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angles = np.linspace(0, 2 * np.pi, num_vars, endpoint=False).tolist()
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angles += angles[:1] # 闭合
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# --- 颜色设置 ---
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# 使用参考图类似的配色 (深蓝、浅蓝、绿等)
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# 或者使用 'tab10', 'Set2' 等
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colors = plt.cm.get_cmap("tab10", len(data_list))
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# 创建画布，稍微宽一点以便放图例
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fig, ax = plt.subplots(figsize=(10, 8), subplot_kw=dict(polar=True))
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# --- 核心修改：调整布局 ---
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# left=0.1, bottom=0.1, top=0.9 是为了给标题留空
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# 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
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plt.subplots_adjust(left=0.05, right=0.75, top=0.9, bottom=0.1)
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# 设置方向
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ax.set_theta_offset(np.pi / 2)
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ax.set_theta_direction(-1)
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# --- 绘制标签 ---
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plt.xticks(angles[:-1], labels, color='#444444', size=13)
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# 标签对齐优化
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for label, angle in zip(ax.get_xticklabels(), angles[:-1]):
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if angle in (0, np.pi):
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label.set_horizontalalignment('center')
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elif 0 < angle < np.pi:
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label.set_horizontalalignment('left')
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else:
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label.set_horizontalalignment('right')
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# --- 绘制刻度 ---
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ax.set_rlabel_position(0)
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# 字体稍微调淡一点，不要抢眼
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plt.yticks([0.25, 0.50, 0.75, 1.00], ["0.25", "0.50", "0.75", "1.00"],
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color="grey", size=10)
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plt.ylim(0, 1.05)
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# 网格线：点状虚线，稍微粗一点
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ax.grid(True, color='gray', linestyle=':', linewidth=1.5, alpha=0.5)
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ax.spines['polar'].set_visible(False)
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# --- 绘制数据 ---
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# 加粗线条以匹配 bsuite 风格
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linewidth = 3.0
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for idx, item in enumerate(data_list):
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values = item['values']
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name = item['name']
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values_closed = values + values[:1]
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color = colors(idx)
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ax.plot(angles, values_closed, linewidth=linewidth, linestyle='-', label=name, color=color)
|
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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)
|
||||
170
robogauge/utils/visualize_results.py
Normal file
170
robogauge/utils/visualize_results.py
Normal file
@@ -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()
|
||||
Reference in New Issue
Block a user