"Meta4": './Results/CarMixed2/combine/Aug17_12-34-416129', "rerun0": agents[0], "rerun1": agents[1] } paths = { "mixed": sys.argv[1], #for slide left "slide only": "./Results/CarSlideTurn/combine/Aug21_01-11-478424", "turn only": "./Results/CarSlideTurn/combine/Aug21_01-09-255914" } paths = { "mixed": sys.argv[1], #for slide left "slide only": "./Results/CarSlideTurn/combine/Aug21_01-25-746419", "turn only": "./Results/CarSlideTurn/combine/Aug21_01-38-448884" } paths = { "mixed": sys.argv[1], #for mixed # "random_local": "./Results/CarSlideTurn/combine/Aug21_09-22-664025", # "turn only": "" } # paths = {"temp": "./GeneratedAgents/RCCarSlide/Aug19_05-26-824448"} # paths = { #"QLearning": "./Results/Gridworld/Agent0/Aug03_10-47-459778/", # "2 agents": "./Results/Mixed2/combine/Aug04_02-24-597933", # "3 agents": "./Results/Mixed3/combine/Aug04_02-11-618909", # "4 agents": "./Results/Mixed4/combine/Aug04_02-21-237975"} merger = MultiExperimentTrials(paths) fig = merger.plot_avg_sem("learning_episode", "avg_return") save_figure(fig, "tmp/test2.pdf")
import rlpy.Tools.results as rt paths = { "RBFs": "./Results/Tutorial/InfTrackCartPole/RBFs", "Tabular": "./Results/Tutorial/InfTrackCartPole/Tabular" } merger = rt.MultiExperimentResults(paths) fig = merger.plot_avg_sem("learning_steps", "return") rt.save_figure(fig, "./Results/Tutorial/plot.pdf")
from __future__ import unicode_literals from __future__ import print_function from __future__ import division from __future__ import absolute_import from future import standard_library standard_library.install_aliases() import rlpy.Tools.results as rt paths = {"RBFs": "./Results/Tutorial/InfTrackCartPole/RBFs", "Tabular": "./Results/Tutorial/InfTrackCartPole/Tabular"} merger = rt.MultiExperimentResults(paths) fig = merger.plot_avg_sem("learning_steps", "return") rt.save_figure(fig, "./Results/Tutorial/plot.pdf")
import rlpy.Tools.results as rt paths = {"Tabular": "./results/ITab", "RBF": "./results/RBF"} merger = rt.MultiExperimentResults(paths) fig = merger.plot_avg_sem("learning_steps", "return") rt.save_figure(fig, "plot.pdf")
import rlpy.Tools.results as rt paths = { "Control": "./Results/Experiments/GridWorld/ControlSegment", "Segmented Reward": "./Results/Experiments/GridWorld/RewardSegment" } merger = rt.MultiExperimentResults(paths) fig = merger.plot_avg_sem("learning_steps", "return") rt.save_figure(fig, "./Results/Experiments/GridWorld/plot.png")
from rlpy.Tools.run import run import rlpy.Tools.results as rt import os import sys if __name__ == '__main__': experiment_name = sys.argv[1] experiment_dir = os.path.expanduser("~/work/clipper/models/rl/") result_dir = "./Results/" + experiment_name + "/" run(experiment_dir + experiment_name + "Experiment.py", result_dir, ids=range(6), parallelization="joblib") paths = {experiment_name: result_dir} merger = rt.MultiExperimentResults(paths) fig = merger.plot_avg_sem("learning_steps", "return") rt.save_figure(fig, result_dir + "plot.pdf")
# } agents = [ './Results/Car/Agent1Post/Aug16_08-24-086841', './Results/Car/Agent1Post/Aug16_08-33-831932' ] paths = { "Meta0": './Results/CarMixed2/combine/Aug17_12-06-345773', # "Meta1": "./Results/CarMixed2/combine/Aug16_04-59-246235/", # "Meta2": "./Results/CarMixed2/combine/Aug16_05-05-251391/", "Meta4": './Results/CarMixed2/combine/Aug17_12-34-416129', "rerun0": agents[0], "rerun1": agents[1] } # paths = {"egreed": "/home/jarvis/work/clipper/models/rl/Results/CarSlide/combine/Aug19_01-45-210261/"} paths = {"mixed": sys.argv[1]} # paths = { #"QLearning": "./Results/Gridworld/Agent0/Aug03_10-47-459778/", # "2 agents": "./Results/Mixed2/combine/Aug04_02-24-597933", # "3 agents": "./Results/Mixed3/combine/Aug04_02-11-618909", # "4 agents": "./Results/Mixed4/combine/Aug04_02-21-237975"} merger = rt.MultiExperimentResults(paths) fig = merger.plot_avg_sem("learning_episode", "return") text = "These experiments used the following: " + "\n" + "\n ".join( paths.values()) + "\n\n2 trained agents and X Noop agents were used." fig.text(.1, -0.5, text) rt.save_figure(fig, "tmp/test.pdf")