normtransform 0.2.0

Transformation for normalising data

Transformation

Transformation tools to normalise and stabilise the variance of non-normal data.

Table of Contents

• Overview

  • Installation
  • Usage
  • Contributing
  • License
  • Contact

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Overview

normtransform is a high-performance Python package (with Cython/C++ backend) for fitting univariate transformed normal distributions using maximum likelihood or maxium a posteriori (MAP) estimation, with support for left and right censoring. Typically, norm-transform is used to transform variables/data so that they can be used in modelling that assumed normality. The ability to handle scenarios where data may be treated as partially observed (e.g. rainfall) allows significant flexibility in applications.

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Installation

Recommended: Using a virtual environment and installing into. A python virtual environment is a self-contained directory that contains a Python installation for a particular version, along with additional packages. It allows you to isolate dependencies for different projects.

Use the package manager pip to install normtransform.

python -m venv venv # Create a virtual environment
source venv/bin/activate  # Activate the virtual enviroment, on Windows use `venv\Scripts\activate`
pip install normtransform #install normtransform

Note: See compatible versions

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Example Usage

This demo.py can be used as example for norm-transform. Once a python environment has been build and activated you can run demo.py from the commandline:

• In the directory where the virtual environment was created with python ./normtransform/demo.py

Contributing

Requests are welcome. Please contact the authors below.

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License

MIT

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Contact

• Andrew Schepen - [e-mail]
• David Robertson - [e-mail]