semvec/pypi-packages huggingface dataset:
morphing-agents 1.5.1
Collection Of Dynamic Morphology Agents For MuJoCo
License: MIT
Keywords: MuJoCo,Agents,Dynamic Morphology

# Morphing Agents

The majority of MuJoCo benchmarks involve an agent with a fixed morphology. In this package, we provide a suite of continuous control tasks, where the agent samples its morphology at runtime. Have Fun! -Brandon

# Installation

You may install the package directly from PyPI using the following command.

```bash
pip install morphing-agents
```

# Usage

At this time I have created three agents with dynamic morphologies. You can instantiate them like this.

```python
from morphing_agents.mujoco.ant.env import MorphingAntEnv
env0 = MorphingAntEnv(num_legs=4, expose_design=True)

from morphing_agents.mujoco.dog.env import MorphingDogEnv
env1 = MorphingDogEnv(num_legs=4, expose_design=True)

from morphing_agents.mujoco.dkitty.env import MorphingDKittyEnv
env2 = MorphingDKittyEnv(expose_design=True)
```

These environments inherit from `gym.Env` and can be used as such. The parameter `num_legs` determines the number of legs in the agent's design specification, which is sampled at random at the beginning of an episode. The parameter `expose_design` vectorizes the design specification and concatenates it with the observation.

# Package Structure

The package is organized such that for every agent, there is a `elements.py` and `designs.py` file that specifies the atomic design elements, and combinations of these elements in a list format respectively. In addition, each agent has a default design present in its `designs.py` and a `sample_uniformly` function for sampling designs.

Each agent expects to have an `expose_design` parameter, and possibly a `num_legs` parameter if the number of legs can change. For environments like the DKitty, where this number cannot change, it is omitted from the constructor arguments of the environment class. Each environment conforms to `gym.Env`.
deco-helper 0.1.0
Decorator Helper
License: MIT
Requires Python: >=3.6

Decorator Helper
================

:Version: 0.0.2
:Download: https://pypi.org/project/deco-helper/
:Source: https://github.com/Kcheonwoong/deco_helper
:Keywords: decorator

- Python (3.6, 3.7, 3.8, 3.9)


    .. code-block:: python

        from deco_helper import helper

        @helper
        def my_decorator(func, f_args, f_kwargs, *deco_args, **deco_kwargs):
            print(deco_args, deco_kwargs)
            result = func(*f_args, **f_kwargs)
            return result


        @my_decorator('first', 'end', k='v')
        def my_function(a, b, c=None):
            print(a, b, c)
            return 'hello world'


        print(my_function(1, 2, 3))

- **Simple Declaration**

    You  don't need to check your decorator receive function when your decorator have some arguments.

    The helper wraps your function that have your decorator for meta(__name__, __doc__).

    The helper automatically delegate function args and decorator args.


Installation
============

You can install Celery either via the Python Package Index (PyPI)
or from source.

To install using ``pip``:

::

    $ pip install deco_helper


License
=======

MIT