semvec/pypi-packages huggingface dataset:
zrHAPPY 0.3
A python library to analyse hydride morphology present in light optical and scanning electron micrographs.
Requires Python: >=3.5
Keywords: micrograph,zirconium,hydride

[![Documentation Status](https://readthedocs.org/projects/happy-hydride-analysis-package-in-python/badge/?version=latest)](https://happy-hydride-analysis-package-in-python.readthedocs.io/en/latest/?badge=latest)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/miamaric12/HAPPY/HEAD)
[![PyPI version](https://badge.fury.io/py/zrHAPPy.svg)](https://badge.fury.io/py/zrHAPPy)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4519833.svg)](https://doi.org/10.5281/zenodo.4519833)


# HAPPy (Hydride Analysis Package in Python)

This is a Python package developed to aid in the charactacterisation and quantification of hydrides from micrographs. The main functions of this package are to:
- Determine the Radial Hydride Fraction (RHF)
- Characterise the extent of branching
- Determine the most probable crack path within a micrograph

## **How to install**

- Instal from PyPi link above


## **How to use**

- Enter `jupyter lab` into the anaconda terminal and Jupyter lab will open in your browser.
- Open the example notebook, provided with the folder downloaded earlier.
- Examples of how to use the software are included, as well as an example micrograph.

## **Documentation**

- happy-hydride-analysis-package-in-python.readthedocs.io

## **Credits**

The software uses the following open source packages:

- [jupyter-notebook](http://jupyter.org/)
- [numpy](http://numpy.org/)
- [matplotlib](http://matplotlib.org/)
- [scikit-image](http://scikit-image.org/)
- [scipy](https://scipy.org/scipylib/)
- [skan](https://jni.github.io/skan/)
- [networkx](https://networkx.org/)
- [toolz](https://github.com/pytoolz/toolz/)
- [matplotlib-scalebar](https://pypi.org/project/matplotlib-scalebar/)

## **Contacts**

- Miss Mia Maric (mia.maric@manchester.ac.uk)
- Dr Pratheek Shanthraj (pratheek.shanthraj@manchester.ac.uk)
- Dr Rhys Thomas (rhys.thomas@manchester.ac.uk)
- Dr Michael Atkinson (michael.atkinson@manchester.ac.uk)
- Dr Juan Nunez-Iglesias (juan.nunez-iglesias@monash.edu)
libglcmsw 1.3.1
A module that is able to produce GLCM sliding window images of large files
Requires Python: >3.6
Keywords: glcm sliding window parallel computationalimaging

# libglcmsw

## Introduction
The library uses [`openslide-python`](https://github.com/openslide/openslide-python) and [`scikit-image`](https://github.com/scikit-image/scikit-image)
to provide the necessary tools to generate sliding window images. It accepts a variety of formats: 
- those supported by PIL
- supported by OpenSlide (for biomedical images):
  - Aperio (.svs, .tif)
  - Hamamatsu (.vms, .vmu, .ndpi)
  - Leica (.scn)
  - MIRAX (.mrxs)
  - Philips (.tiff)
  - Sakura (.svslide)
  - Trestile (.tif)
  - Ventana (.bif, .tif)
  - Generic tiled TIFF (.tif) 

## Tree of the module
```
libglcmsw/
    __init__.py
    io/
        __init__.py
        crashrecovery.py
        openimg.py
    render/
        __init__.py
        cpu.py
        gpu.py
        nvidia.py
        cl.py
        src-varbitdepth.cl
    tiling/
        __init__.py
        reconstruct.py
        tilegen.py
```

## Documentation
see DOCUMENTATION.md

## Installation
After installing the openslide binaries (see [Distribution packages, respectively Windows binaries](https://openslide.org/download/)),

```pip3 install libglcmsw```


## Building binaries

In order to install a version from another branch, one needs to first build the binaries for installation.
Run `python3 setup.py sdist bdist_wheel` and run the commands from the Installation section.

## Note for testing parallel execution

The script is named ```examples/coretest-tilingrenderer.py```. Before running it, under the ```if __name__ == "__main__"``` clause, change the ```coresmax``` variable so that it corresponds to the number of logical processors in the system. The only thing needed is to run the script. It will generate a text file named ```corestest```, to which stdout is redirected. After completion of the testing process, please send this to my email address, along with CPU model and RAM frequency and size (for instance: i7-9750H, DDR4-2666 16GB)