semvec/pypi-packages huggingface dataset:
exdes 0.2.3
Experimental Design for Python
Requires Python: >=3.6

# exdes: Experimental Design for Python

`exdes` is a python package for design of experiments 

With `exdes` you can create the following designs

- Orthogonal Arrays
- D-efficient Designs
- Conference Designs
- Central Composite Designs *(CCD)*
- Definitive Screening Designs *(DSD)*
- Orthogonal Array Composite Designs *(OACD)*
- Definitive Screening Composite Designs *(DSCD)*

Other functionality includes:

- Calculate design properties of orthogonal arrays, conference designs, and 
response surface designs. These include D-efficiency, A-efficiency, E-efficiency,
generalized world length pattern, projection properties, and more 

Construction of orthogonal arrays, D-efficient designs, and conference designs are simple wrappers
from the package [OApackage](http://www.pietereendebak.nl/oapackage/). For more generalized constructions of those design refer to [OApackage](http://www.pietereendebak.nl/oapackage/)

For further details on the above designs and their properties, check out the references under
[REFERENCES.md](https://github.com/toledo60/exdes/blob/main/REFERENCES.md)

## Installation

`exdes` can be installed from PyPI

```
pip install exdes
```

The latest development version can be installed from the main branch using pip:

```
pip install git+https://github.com/toledo60/exdes.git
```

The main dependencies for `exdes` are [NumPy](https://numpy.org/) and [OApackage](http://www.pietereendebak.nl/oapackage/). Currently tested on Python 3.6+


## TODO

Include Jupyter notebooks to demonstrate the main functionalities of `exdes`