semvec/pypi-packages huggingface dataset:
egogym 0.1.1
EgoGym is a lightweight benchmark suite for egocentric robot policies
License: MIT
Requires Python: >=3.8
Keywords: robotics, reinforcement-learning, mujoco, gymnasium

# EgoGym

EgoGym is a lightweight benchmark suite for egocentric robot policies

```python
env = gym.make(
    "Egogym-Pick-v0",           # Options: "Egogym-Pick-v0", "Egogym-Open-v0", "Egogym-Close-v0"
    robot="rum",                # Options: "rum", "droid"
    action_space="delta",       # Options: "delta", "absolute"
    num_objs=5,                 # Options: 1-5
)
```

**Actions (17-dim):**
- `[0-15]`: flattened 4x4 transformation
- `[16]`: continuous gripper (0=open, 1=close)

**Coordinate Frame:**
- **x**: Right of camera
- **y**: Up of camera
- **z**: Backward of camera
ladim 2.1.7
Lagrangian Advection and Diffusion Model
License: MIT
Requires Python: >=3.7

LADiM – the Lagrangian Advection and Diffusion Model
====================================================

LADiM is an off-line ocean particle tracking code. Presently  using results
from the ocean model [ROMS](http://www.myroms.org/) as input.

Try out LADiM
-------------

The model is written in python and requires python 3.6 and some scientific
packages. The anaconda python distribution is recommended.

Download the code from `github` and install by:

    python setup.py install.

Get a small example data set by running the download script in
`examples/data`. The different examples can be run by the sequence of
commands:

    python make_release.py
    ladim


Source code and documentation
-----------------------------

The code is open source using the MIT License. It is available from
[github](https://github.com/bjornaa/ladim).

The documentation is hosted on [readthedocs](https://ladim.readthedocs.io/en/master).
A [pdf version](https://media.readthedocs.org/pdf/ladim/master/ladim.pdf)
is also available.