updates
This commit is contained in:
Maximilian Huettenrauch
parent
516c956d58
commit
d9a201754c
@ -1,4 +1,7 @@
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#!/usr/bin/env python3
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"""Use the high-level API of TianShou to evaluate the PPO algorithm on a MuJoCo environment with multiple seeds for a
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given configuration. After the agents are trained, the results are evaluated using rliable API.
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"""
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import os
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from collections.abc import Sequence
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@ -18,18 +21,19 @@ from tianshou.highlevel.params.dist_fn import (
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)
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from tianshou.highlevel.params.lr_scheduler import LRSchedulerFactoryLinear
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from tianshou.highlevel.params.policy_params import PPOParams
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from tianshou.utils import logging
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from tianshou.utils.logging import datetime_tag
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def main(
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experiment_config: ExperimentConfig,
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task: str = "Ant-v4",
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num_experiments: int = 5,
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num_experiments: int = 2,
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buffer_size: int = 4096,
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hidden_sizes: Sequence[int] = (64, 64),
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lr: float = 3e-4,
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gamma: float = 0.99,
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epoch: int = 100,
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epoch: int = 1,
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step_per_epoch: int = 30000,
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step_per_collect: int = 2048,
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repeat_per_collect: int = 10,
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@ -105,13 +109,10 @@ def main(
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def eval_experiments(log_dir: str):
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results = RLiableExperimentResult.load_from_disk(log_dir, "PPO", None)
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eval_results(results)
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results = RLiableExperimentResult.load_from_disk(log_dir, "PPO")
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eval_results(results, save_figure=True)
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if __name__ == "__main__":
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# logging.run_cli(main)
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# experiment_config = ExperimentConfig(watch=False)
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# log_dir = logging.run_main(partial(main, experiment_config, epoch=2))
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log_dir = "log/Ant-v4/ppo/20240312-114646"
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log_dir = logging.run_cli(main)
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eval_experiments(log_dir)
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@ -23,7 +23,7 @@ class RLiableExperimentResult:
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score_thresholds: np.ndarray
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@staticmethod
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def load_from_disk(exp_dir: str, algo_name: str, score_thresholds: np.ndarray | None):
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def load_from_disk(exp_dir: str, algo_name: str, score_thresholds: np.ndarray | None = None):
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"""Load the experiment result from disk.
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:param exp_dir: The directory from where the experiment results are restored.
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@ -63,7 +63,15 @@ class RLiableExperimentResult:
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)
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def eval_results(results: RLiableExperimentResult):
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def eval_results(results: RLiableExperimentResult, save_figure=False):
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"""Evaluate the results of an experiment and create the performance profile and sample efficiency curve.
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:param results: The results of the experiment. Needs to be compatible with the rliable API. This can be achieved by
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calling the method `load_from_disk` from the RLiableExperimentResult class.
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:param save_figure: Whether to save the figures as png to the experiment directory.
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:return: The axes of the created figures.
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"""
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import matplotlib.pyplot as plt
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import scipy.stats as sst
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import seaborn as sns
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@ -74,7 +82,7 @@ def eval_results(results: RLiableExperimentResult):
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iqm_scores, iqm_cis = rly.get_interval_estimates(results.score_dict, iqm, reps=50000)
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# Plot IQM sample efficiency curve
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fig, ax = plt.subplots(ncols=1, figsize=(7, 5))
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fig, ax1 = plt.subplots(ncols=1, figsize=(7, 5))
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plot_utils.plot_sample_efficiency_curve(
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results.env_steps,
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iqm_scores,
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@ -82,9 +90,11 @@ def eval_results(results: RLiableExperimentResult):
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algorithms=results.algorithms,
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xlabel=r"Number of env steps",
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ylabel="IQM episode return",
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ax=ax,
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ax=ax1,
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)
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plt.savefig(os.path.join(results.exp_dir, "iqm_sample_efficiency_curve.png"))
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if save_figure:
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plt.savefig(os.path.join(results.exp_dir, "iqm_sample_efficiency_curve.png"))
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final_score_dict = {algo: returns[:, [-1]] for algo, returns in results.score_dict.items()}
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score_distributions, score_distributions_cis = rly.create_performance_profile(
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@ -93,7 +103,7 @@ def eval_results(results: RLiableExperimentResult):
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)
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# Plot score distributions
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fig, ax = plt.subplots(ncols=1, figsize=(7, 5))
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fig, ax2 = plt.subplots(ncols=1, figsize=(7, 5))
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plot_utils.plot_performance_profiles(
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score_distributions,
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results.score_thresholds,
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@ -106,9 +116,13 @@ def eval_results(results: RLiableExperimentResult):
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),
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),
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xlabel=r"Episode return $(\tau)$",
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ax=ax,
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ax=ax2,
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)
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plt.savefig(os.path.join(results.exp_dir, "performance_profile.png"))
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if save_figure:
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plt.savefig(os.path.join(results.exp_dir, "performance_profile.png"))
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return ax1, ax2
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def find_all_files(root_dir, pattern):
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678
poetry.lock
generated
678
poetry.lock
generated
@ -1,4 +1,4 @@
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# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
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# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand.
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[[package]]
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name = "absl-py"
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@ -152,6 +152,44 @@ files = [
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{file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
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]
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[[package]]
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name = "arch"
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version = "5.3.0"
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description = "ARCH for Python"
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optional = true
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python-versions = ">=3.7"
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files = [
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]
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[package.dependencies]
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numpy = ">=1.17"
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pandas = ">=1.0"
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property-cached = ">=1.6.4"
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scipy = ">=1.3"
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statsmodels = ">=0.11"
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[[package]]
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name = "argon2-cffi"
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version = "23.1.0"
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@ -719,6 +757,69 @@ traitlets = ">=4"
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[package.extras]
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test = ["pytest"]
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[[package]]
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name = "contourpy"
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version = "1.2.0"
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description = "Python library for calculating contours of 2D quadrilateral grids"
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optional = true
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python-versions = ">=3.9"
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[package.dependencies]
|
||||
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||||
|
||||
[package.extras]
|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
|
||||
[[package]]
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|
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|
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = {version = ">=1.23.2,<2", markers = "python_version == \"3.11\""}
|
||||
python-dateutil = ">=2.8.2"
|
||||
pytz = ">=2020.1"
|
||||
tzdata = ">=2022.7"
|
||||
|
||||
[package.extras]
|
||||
all = ["PyQt5 (>=5.15.9)", "SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)", "beautifulsoup4 (>=4.11.2)", "bottleneck (>=1.3.6)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=2022.12.0)", "fsspec (>=2022.11.0)", "gcsfs (>=2022.11.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.9.2)", "matplotlib (>=3.6.3)", "numba (>=0.56.4)", "numexpr (>=2.8.4)", "odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "pandas-gbq (>=0.19.0)", "psycopg2 (>=2.9.6)", "pyarrow (>=10.0.1)", "pymysql (>=1.0.2)", "pyreadstat (>=1.2.0)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "qtpy (>=2.3.0)", "s3fs (>=2022.11.0)", "scipy (>=1.10.0)", "tables (>=3.8.0)", "tabulate (>=0.9.0)", "xarray (>=2022.12.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)", "zstandard (>=0.19.0)"]
|
||||
aws = ["s3fs (>=2022.11.0)"]
|
||||
clipboard = ["PyQt5 (>=5.15.9)", "qtpy (>=2.3.0)"]
|
||||
compression = ["zstandard (>=0.19.0)"]
|
||||
computation = ["scipy (>=1.10.0)", "xarray (>=2022.12.0)"]
|
||||
consortium-standard = ["dataframe-api-compat (>=0.1.7)"]
|
||||
excel = ["odfpy (>=1.4.1)", "openpyxl (>=3.1.0)", "python-calamine (>=0.1.7)", "pyxlsb (>=1.0.10)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.5)"]
|
||||
feather = ["pyarrow (>=10.0.1)"]
|
||||
fss = ["fsspec (>=2022.11.0)"]
|
||||
gcp = ["gcsfs (>=2022.11.0)", "pandas-gbq (>=0.19.0)"]
|
||||
hdf5 = ["tables (>=3.8.0)"]
|
||||
html = ["beautifulsoup4 (>=4.11.2)", "html5lib (>=1.1)", "lxml (>=4.9.2)"]
|
||||
mysql = ["SQLAlchemy (>=2.0.0)", "pymysql (>=1.0.2)"]
|
||||
output-formatting = ["jinja2 (>=3.1.2)", "tabulate (>=0.9.0)"]
|
||||
parquet = ["pyarrow (>=10.0.1)"]
|
||||
performance = ["bottleneck (>=1.3.6)", "numba (>=0.56.4)", "numexpr (>=2.8.4)"]
|
||||
plot = ["matplotlib (>=3.6.3)"]
|
||||
postgresql = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "psycopg2 (>=2.9.6)"]
|
||||
pyarrow = ["pyarrow (>=10.0.1)"]
|
||||
spss = ["pyreadstat (>=1.2.0)"]
|
||||
sql-other = ["SQLAlchemy (>=2.0.0)", "adbc-driver-postgresql (>=0.8.0)", "adbc-driver-sqlite (>=0.8.0)"]
|
||||
test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
|
||||
xml = ["lxml (>=4.9.2)"]
|
||||
|
||||
[[package]]
|
||||
name = "pandocfilters"
|
||||
version = "1.5.0"
|
||||
@ -3460,6 +3929,24 @@ files = [
|
||||
{file = "pathtools-0.1.2.tar.gz", hash = "sha256:7c35c5421a39bb82e58018febd90e3b6e5db34c5443aaaf742b3f33d4655f1c0"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "patsy"
|
||||
version = "0.5.6"
|
||||
description = "A Python package for describing statistical models and for building design matrices."
|
||||
optional = true
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "patsy-0.5.6-py2.py3-none-any.whl", hash = "sha256:19056886fd8fa71863fa32f0eb090267f21fb74be00f19f5c70b2e9d76c883c6"},
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{file = "patsy-0.5.6.tar.gz", hash = "sha256:95c6d47a7222535f84bff7f63d7303f2e297747a598db89cf5c67f0c0c7d2cdb"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = ">=1.4"
|
||||
six = "*"
|
||||
|
||||
[package.extras]
|
||||
test = ["pytest", "pytest-cov", "scipy"]
|
||||
|
||||
[[package]]
|
||||
name = "pettingzoo"
|
||||
version = "1.24.2"
|
||||
@ -3709,6 +4196,17 @@ files = [
|
||||
[package.dependencies]
|
||||
wcwidth = "*"
|
||||
|
||||
[[package]]
|
||||
name = "property-cached"
|
||||
version = "1.6.4"
|
||||
description = "A decorator for caching properties in classes (forked from cached-property)."
|
||||
optional = true
|
||||
python-versions = ">= 3.5"
|
||||
files = [
|
||||
{file = "property-cached-1.6.4.zip", hash = "sha256:3e9c4ef1ed3653909147510481d7df62a3cfb483461a6986a6f1dcd09b2ebb73"},
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||||
]
|
||||
|
||||
[[package]]
|
||||
name = "protobuf"
|
||||
version = "3.20.3"
|
||||
@ -4094,6 +4592,20 @@ files = [
|
||||
{file = "PyOpenGL-3.1.7.tar.gz", hash = "sha256:eef31a3888e6984fd4d8e6c9961b184c9813ca82604d37fe3da80eb000a76c86"},
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||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pyparsing"
|
||||
version = "3.1.2"
|
||||
description = "pyparsing module - Classes and methods to define and execute parsing grammars"
|
||||
optional = true
|
||||
python-versions = ">=3.6.8"
|
||||
files = [
|
||||
{file = "pyparsing-3.1.2-py3-none-any.whl", hash = "sha256:f9db75911801ed778fe61bb643079ff86601aca99fcae6345aa67292038fb742"},
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|
||||
]
|
||||
|
||||
[package.extras]
|
||||
diagrams = ["jinja2", "railroad-diagrams"]
|
||||
|
||||
[[package]]
|
||||
name = "pytest"
|
||||
version = "7.4.3"
|
||||
@ -4157,6 +4669,17 @@ files = [
|
||||
{file = "python_json_logger-2.0.7-py3-none-any.whl", hash = "sha256:f380b826a991ebbe3de4d897aeec42760035ac760345e57b812938dc8b35e2bd"},
|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "pytz"
|
||||
version = "2024.1"
|
||||
description = "World timezone definitions, modern and historical"
|
||||
optional = true
|
||||
python-versions = "*"
|
||||
files = [
|
||||
{file = "pytz-2024.1-py2.py3-none-any.whl", hash = "sha256:328171f4e3623139da4983451950b28e95ac706e13f3f2630a879749e7a8b319"},
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|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pywin32"
|
||||
version = "306"
|
||||
@ -4536,6 +5059,24 @@ files = [
|
||||
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|
||||
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|
||||
|
||||
[[package]]
|
||||
name = "rliable"
|
||||
version = "1.0.8"
|
||||
description = "rliable: Reliable evaluation on reinforcement learning and machine learning benchmarks."
|
||||
optional = true
|
||||
python-versions = "*"
|
||||
files = [
|
||||
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|
||||
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|
||||
|
||||
[package.dependencies]
|
||||
absl-py = ">=0.9.0"
|
||||
arch = "5.3.0"
|
||||
numpy = ">=1.16.4"
|
||||
scipy = ">=1.7.0"
|
||||
seaborn = ">=0.11.2"
|
||||
|
||||
[[package]]
|
||||
name = "rpds-py"
|
||||
version = "0.13.0"
|
||||
@ -4803,6 +5344,27 @@ dev = ["click", "cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyl
|
||||
doc = ["jupytext", "matplotlib (>2)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
|
||||
test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
|
||||
|
||||
[[package]]
|
||||
name = "seaborn"
|
||||
version = "0.13.2"
|
||||
description = "Statistical data visualization"
|
||||
optional = true
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
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|
||||
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|
||||
|
||||
[package.dependencies]
|
||||
matplotlib = ">=3.4,<3.6.1 || >3.6.1"
|
||||
numpy = ">=1.20,<1.24.0 || >1.24.0"
|
||||
pandas = ">=1.2"
|
||||
|
||||
[package.extras]
|
||||
dev = ["flake8", "flit", "mypy", "pandas-stubs", "pre-commit", "pytest", "pytest-cov", "pytest-xdist"]
|
||||
docs = ["ipykernel", "nbconvert", "numpydoc", "pydata_sphinx_theme (==0.10.0rc2)", "pyyaml", "sphinx (<6.0.0)", "sphinx-copybutton", "sphinx-design", "sphinx-issues"]
|
||||
stats = ["scipy (>=1.7)", "statsmodels (>=0.12)"]
|
||||
|
||||
[[package]]
|
||||
name = "send2trash"
|
||||
version = "1.8.2"
|
||||
@ -5630,6 +6192,106 @@ pure-eval = "*"
|
||||
[package.extras]
|
||||
tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
|
||||
|
||||
[[package]]
|
||||
name = "statsmodels"
|
||||
version = "0.14.0"
|
||||
description = "Statistical computations and models for Python"
|
||||
optional = true
|
||||
python-versions = ">=3.8"
|
||||
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{file = "statsmodels-0.14.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:1c7724ad573af26139a98393ae64bc318d1b19762b13442d96c7a3e793f495c3"},
|
||||
{file = "statsmodels-0.14.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3b0a135f3bfdeec987e36e3b3b4c53e0bb87a8d91464d2fcc4d169d176f46fdb"},
|
||||
{file = "statsmodels-0.14.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ce28eb1c397dba437ec39b9ab18f2101806f388c7a0cf9cdfd8f09294ad1c799"},
|
||||
{file = "statsmodels-0.14.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:68b1c768dd94cc5ba8398121a632b673c625491aa7ed627b82cb4c880a25563f"},
|
||||
{file = "statsmodels-0.14.0-cp39-cp39-win_amd64.whl", hash = "sha256:8d1e3e10dfbfcd58119ba5a4d3c7d519182b970a2aebaf0b6f539f55ae16058d"},
|
||||
{file = "statsmodels-0.14.0.tar.gz", hash = "sha256:6875c7d689e966d948f15eb816ab5616f4928706b180cf470fd5907ab6f647a4"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = ">=1.18"
|
||||
packaging = ">=21.3"
|
||||
pandas = ">=1.0"
|
||||
patsy = ">=0.5.2"
|
||||
scipy = ">=1.4,<1.9.2 || >1.9.2"
|
||||
|
||||
[package.extras]
|
||||
build = ["cython (>=0.29.26)"]
|
||||
develop = ["colorama", "cython (>=0.29.26)", "cython (>=0.29.28,<3.0.0)", "flake8", "isort", "joblib", "matplotlib (>=3)", "oldest-supported-numpy (>=2022.4.18)", "pytest (>=7.0.1,<7.1.0)", "pytest-randomly", "pytest-xdist", "pywinpty", "setuptools-scm[toml] (>=7.0.0,<7.1.0)"]
|
||||
docs = ["ipykernel", "jupyter-client", "matplotlib", "nbconvert", "nbformat", "numpydoc", "pandas-datareader", "sphinx"]
|
||||
|
||||
[[package]]
|
||||
name = "statsmodels"
|
||||
version = "0.14.1"
|
||||
description = "Statistical computations and models for Python"
|
||||
optional = true
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "statsmodels-0.14.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:43af9c0b07c9d72f275cf14ea54a481a3f20911f0b443181be4769def258fdeb"},
|
||||
{file = "statsmodels-0.14.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:a16975ab6ad505d837ba9aee11f92a8c5b49c4fa1ff45b60fe23780b19e5705e"},
|
||||
{file = "statsmodels-0.14.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e278fe74da5ed5e06c11a30851eda1af08ef5af6be8507c2c45d2e08f7550dde"},
|
||||
{file = "statsmodels-0.14.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c0564d92cb05b219b4538ed09e77d96658a924a691255e1f7dd23ee338df441b"},
|
||||
{file = "statsmodels-0.14.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:5385e22e72159a09c099c4fb975f350a9f3afeb57c1efce273b89dcf1fe44c0f"},
|
||||
{file = "statsmodels-0.14.1-cp310-cp310-win_amd64.whl", hash = "sha256:0a8aae75a2e08ebd990e5fa394f8e32738b55785cb70798449a3f4207085e667"},
|
||||
{file = "statsmodels-0.14.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b69a63ad6c979a6e4cde11870ffa727c76a318c225a7e509f031fbbdfb4e416a"},
|
||||
{file = "statsmodels-0.14.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7562cb18a90a114f39fab6f1c25b9c7b39d9cd5f433d0044b430ca9d44a8b52c"},
|
||||
{file = "statsmodels-0.14.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b3abaca4b963259a2bf349c7609cfbb0ce64ad5fb3d92d6f08e21453e4890248"},
|
||||
{file = "statsmodels-0.14.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b0f727fe697f6406d5f677b67211abe5a55101896abdfacdb3f38410405f6ad8"},
|
||||
{file = "statsmodels-0.14.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:b6838ac6bdb286daabb5e91af90fd4258f09d0cec9aace78cc441cb2b17df428"},
|
||||
{file = "statsmodels-0.14.1-cp311-cp311-win_amd64.whl", hash = "sha256:709bfcef2dbe66f705b17e56d1021abad02243ee1a5d1efdb90f9bad8b06a329"},
|
||||
{file = "statsmodels-0.14.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:f32a7cd424cf33304a54daee39d32cccf1d0265e652c920adeaeedff6d576457"},
|
||||
{file = "statsmodels-0.14.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:f8c30181c084173d662aaf0531867667be2ff1bee103b84feb64f149f792dbd2"},
|
||||
{file = "statsmodels-0.14.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2de2b97413913d52ad6342dece2d653e77f78620013b7705fad291d4e4266ccb"},
|
||||
{file = "statsmodels-0.14.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c3420f88289c593ba2bca33619023059c476674c160733bd7d858564787c83d3"},
|
||||
{file = "statsmodels-0.14.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:c008e16096f24f0514e53907890ccac6589a16ad6c81c218f2ee6752fdada555"},
|
||||
{file = "statsmodels-0.14.1-cp312-cp312-win_amd64.whl", hash = "sha256:bc0351d279c4e080f0ce638a3d886d312aa29eade96042e3ba0a73771b1abdfb"},
|
||||
{file = "statsmodels-0.14.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:bf293ada63b2859d95210165ad1dfcd97bd7b994a5266d6fbeb23659d8f0bf68"},
|
||||
{file = "statsmodels-0.14.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:44ca8cb88fa3d3a4ffaff1fb8eb0e98bbf83fc936fcd9b9eedee258ecc76696a"},
|
||||
{file = "statsmodels-0.14.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d5373d176239993c095b00d06036690a50309a4e00c2da553b65b840f956ae6"},
|
||||
{file = "statsmodels-0.14.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a532dfe899f8b6632cd8caa0b089b403415618f51e840d1817a1e4b97e200c73"},
|
||||
{file = "statsmodels-0.14.1-cp38-cp38-win_amd64.whl", hash = "sha256:4fe0a60695952b82139ae8750952786a700292f9e0551d572d7685070944487b"},
|
||||
{file = "statsmodels-0.14.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:04293890f153ffe577e60a227bd43babd5f6c1fc50ea56a3ab1862ae85247a95"},
|
||||
{file = "statsmodels-0.14.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3e70a2e93d54d40b2cb6426072acbc04f35501b1ea2569f6786964adde6ca572"},
|
||||
{file = "statsmodels-0.14.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ab3a73d16c0569adbba181ebb967e5baaa74935f6d2efe86ac6fc5857449b07d"},
|
||||
{file = "statsmodels-0.14.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:eefa5bcff335440ee93e28745eab63559a20cd34eea0375c66d96b016de909b3"},
|
||||
{file = "statsmodels-0.14.1-cp39-cp39-win_amd64.whl", hash = "sha256:bc43765710099ca6a942b5ffa1bac7668965052542ba793dd072d26c83453572"},
|
||||
{file = "statsmodels-0.14.1.tar.gz", hash = "sha256:2260efdc1ef89f39c670a0bd8151b1d0843567781bcafec6cda0534eb47a94f6"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = ">=1.18,<2"
|
||||
packaging = ">=21.3"
|
||||
pandas = ">=1.0,<2.1.0 || >2.1.0"
|
||||
patsy = ">=0.5.4"
|
||||
scipy = ">=1.4,<1.9.2 || >1.9.2"
|
||||
|
||||
[package.extras]
|
||||
build = ["cython (>=0.29.33)"]
|
||||
develop = ["colorama", "cython (>=0.29.33)", "cython (>=0.29.33,<4.0.0)", "flake8", "isort", "joblib", "matplotlib (>=3)", "oldest-supported-numpy (>=2022.4.18)", "pytest (>=7.3.0)", "pytest-cov", "pytest-randomly", "pytest-xdist", "pywinpty", "setuptools-scm[toml] (>=8.0,<9.0)"]
|
||||
docs = ["ipykernel", "jupyter-client", "matplotlib", "nbconvert", "nbformat", "numpydoc", "pandas-datareader", "sphinx"]
|
||||
|
||||
[[package]]
|
||||
name = "swig"
|
||||
version = "4.2.0"
|
||||
@ -5946,6 +6608,17 @@ files = [
|
||||
{file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tzdata"
|
||||
version = "2024.1"
|
||||
description = "Provider of IANA time zone data"
|
||||
optional = true
|
||||
python-versions = ">=2"
|
||||
files = [
|
||||
{file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
|
||||
{file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "uc-micro-py"
|
||||
version = "1.0.2"
|
||||
@ -6219,6 +6892,7 @@ atari = ["ale-py", "autorom", "opencv_python", "shimmy"]
|
||||
box2d = ["box2d_py", "pygame", "swig"]
|
||||
classic-control = ["pygame"]
|
||||
envpool = ["envpool"]
|
||||
eval = ["rliable"]
|
||||
mujoco = ["imageio", "mujoco"]
|
||||
mujoco-py = ["cython", "mujoco-py"]
|
||||
pybullet = ["pybullet"]
|
||||
@ -6228,4 +6902,4 @@ vizdoom = ["vizdoom"]
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.11"
|
||||
content-hash = "0d4ff98ed02fe3f34c0d05b5d175822a82ac08a5ed52e57b7f847a48c302add6"
|
||||
content-hash = "4aec2debf89f1318e837ca6cce127b41fa6603701aecd05f1bed6fabfaf4e9ee"
|
||||
|
||||
@ -62,6 +62,7 @@ mujoco-py = { version = ">=2.1,<2.2", optional = true }
|
||||
opencv_python = { version = "*", optional = true }
|
||||
pybullet = { version = "*", optional = true }
|
||||
pygame = { version = ">=2.1.3", optional = true }
|
||||
rliable = { version = "*", optional = true }
|
||||
shimmy = { version = ">=0.1.0,<1.0", optional = true }
|
||||
swig = { version = "4.*", optional = true }
|
||||
vizdoom = { version = "*", optional = true }
|
||||
@ -76,6 +77,7 @@ pybullet = ["pybullet"]
|
||||
envpool = ["envpool"]
|
||||
robotics = ["gymnasium-robotics"]
|
||||
vizdoom = ["vizdoom"]
|
||||
eval = ["rliable"]
|
||||
|
||||
|
||||
[tool.poetry.group.dev]
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user