About

GSEGUtils provides some tools and functionality that could be used across other development or research projects. These are particularly focussed in the direction of research within the group.

The main goal if this repo is to help software processing efforts and allow more focus on algorithm development and research.

Currently this repository includes:

Package	Description
BaseArrays	Sub-classable array objects with automated validation on type, shape and attributes
Lazy Disk Cache	Automated data offloading for memory management
Util	Includes utility functions such as angle unit conversions
Validators	Helper functions for performing validation and normalisation

Installation

This can be done directly from the repository directory:

pip install "GSEGUtils @ git+https://github.com/gseg-ethz/GSEGUtils.git"

or by cloning it

git clone https://github.com/gseg-ethz/GSEGUtils.git
cd GSEGUtils
pip intstall .

Usage

Accessing the different classes can then be easily done by importing from GSEGUtils:

>>> from GSEGUtils.base_arrays import BaseArray, ArrayNx3, BaseVector
>>> import numpy as np
>>> data = np.random.rand(10,20,3)
>>> array = BaseArray(data)
>>> array.shape
(10, 20, 3)
>>> np.all(array == data)
np.True_

>>> a = ArrayNx3(np.random.rand(10, 3))
>>> b = a + 10
>>> np.all(b == a + 10)
np.True_

coords3D = Array_Nx3(np.random.rand(20))
coords3d.arr = np.random.rand(100) # Valid
coords3d.arr = np.random.rand(100, 3) # RAISES ERROR -> invalid shape not of (N, 3), expected (N,)