Skip to main content

deephonor-gym physics simulator

Project description

deephonor_gym Package

This package is part of the RL (Reinforcement Learning) project.
You can call this tool DHGym.

这个库取名 DHGym,因为我很喜爱这个库。

Overview

The development purpose of deephonor-gym is to significantly lower the barriers to reinforcement learning and physical simulation.
Based on this library, users can very quickly view and train robots.
While this simulation platform has limited performance, it offers high accuracy, making it well-suited for algorithm validation by students, companies, and individual enthusiasts.

翻译:易用,好用,免费

Installation

The recommended way to install this package is via PyPI:

pip install deephonor-gym --no-cache-dir

or

pip install deephonor-gym

License

This project is licensed under the GNU Affero General Public License v3.0.
See LICENSE for the full text.

Detail

  • explain_action

    • 'ball' is link name. -> 'Impulse.ball' = direction array
    • 'KP1' is joint name. -> 'joint.ball' = angle
  • explain_reset

    • 'ball' is link name.
    • 'KP1' is joint name.
   Y 
   |     Z screen 
   |     .—— —— X

Usage

Once installed, the package can be imported via from deephonor_gym import DHgym, DHgym_VecEnv, open_browser, Upload Or, you can read the source code to access additional details.

Example

具体见 example 目录下的 train.ipynb ,哪里有详细的解释

# 首先打开网页
from deephonor_gym import open_browser
open_browser() # 打开网页


# 然后和网页连接
from deephonor_gym import DHgym, DHgym_VecEnv, open_browser, Upload

conn = DHgym.connect() # 与网页连接,仅运行一次

class myEnv(DHgym) :
    """用户自己写的代码"""
    def init(self):
        ...

    def explain_obs(self,obs):
        ...

    def explain_action(self,action):
        ...

    def explain_reset(self,reset_array):
        ...

    def reward(self,state):
        ...
env_Engine = DHgym_VecEnv( [lambda : myEnv(conn)]) # 查看 env

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

deephonor_gym-0.1.3.tar.gz (3.6 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

deephonor_gym-0.1.3-py3-none-any.whl (3.6 MB view details)

Uploaded Python 3

File details

Details for the file deephonor_gym-0.1.3.tar.gz.

File metadata

  • Download URL: deephonor_gym-0.1.3.tar.gz
  • Upload date:
  • Size: 3.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for deephonor_gym-0.1.3.tar.gz
Algorithm Hash digest
SHA256 7b85e462b427608dfd9a641e62ec1247a9ac5916892a7ab687281fb1f2af5de7
MD5 922bd098b014cafb0dc671311db32e20
BLAKE2b-256 071fc434c1c35e06e06ad59ea7c69d9acc66c797b07f70e0f807992100dd8a09

See more details on using hashes here.

File details

Details for the file deephonor_gym-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: deephonor_gym-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 3.6 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for deephonor_gym-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 2f36a33a5ca18524b0d433ada6f7a1c22119c28cf9f29dbfdbbc45c37b99bc94
MD5 003ae69539187b6833dff6369f5fd010
BLAKE2b-256 5c4ccd9a7caacea71365f66aacc1d309fdbcf9c975729e150806216ad12e527d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page