semvec/pypi-packages huggingface dataset:
MDSdata 0.1.5
A package providing the datasets for the MDS-book.
License: MIT
Requires Python: <4.0,>=3.9

# MDS-data

This is a package through which the example datasets of the MDS-book can be easily imported.



## Change Log

### 0.1.5 (Feb 11, 2025)
- remove unnecessary print output from Alpydin DS
- bugfix 
- fix typo in iris docstring

#### 0.1.4 (Feb 09, 2024)
- fine tune the wrapper function `load_...()`
- add Iris dataset (DS-1) and Fisher-1936 paper
- adapt show_MDS4_chemical_elements.py 

#### 0.1.3 (Feb 2, 2024)
- add "Alpaydin" NIST dataset (DS-2 light)
- add function wrapper around (M)DS-x classes to provide intuitive 
- refactor package structure

#### 0.1.2 (Jan 30, 2024)
- remove temporary files
- add, edit and extent documentation of datasets
- add MNIST dataset (DS-2)

#### 0.1.1 (Dec 26, 2023)
- cleanup pyproject.toml and README.md

#### 0.1.0 (Dec 26, 2023)
- first release
planarenvs 1.6.0
Default template for PDM package
License: MIT
Requires Python: ==3.10.*

### Generic Planar Robots

In this package, generic robot for simple tests are made available for gym environments.

## Dependencies

This package depends on casadi for dynamics generation and gym.
Dependencies will be installed through pip installation, see below.
It uses the lightweight implementation for forward kinematics in casadi.



## Installation
Clone the repository 
```bash
git clone git@github.com:maxspahn/gym_envs_planar.git
```
### virtual environment installation using poetry
If you are not familiar with poetry see [Poetry Installation](https://python-poetry.org/docs/).
Once poetry is installed you can run
```bash
poetry install
```
If you want the motion planning scenes
```bash
poetry install -E scenes
```
The virtual environment with everything installed is entered with
```bash
poetry shell
```

### global installation via pip
```bash
pip3 install .
```

When obstacles are required, you must use
```bash
pip3 install ".[scenes]"
```

## Switching

Environments can be created using the normal gym syntax.
For example the below code line creates a planar robot with 3 links and a constant k.
Actions are torques to the individual joints.
```python
env = gym.make('nLink-reacher-tor-v0', n=3, dt=0.01, k=2.1)
```
## Examples

For a constant controlled torque, the simulation is displayed below:

 
![Example of torque controlled environment](./assets/torques.gif)