Metadata-Version: 2.1
Name: muDIC
Version: 0.2.1
Summary: A digital image correlation toolkit
Home-page: https://github.com/PolymerGuy/muDIC
Author: PolymerGuy
Author-email: sindre.n.olufsen@ntnu.no
License: UNKNOWN
Description: ![](documentation/logo.png)
        # µDIC: A Python toolkit for Digital Image Correlation (DIC)
        [![CircleCI](https://circleci.com/gh/PolymerGuy/muDIC.svg?style=svg)](https://circleci.com/gh/PolymerGuy/muDIC) [![codecov](https://codecov.io/gh/PolymerGuy/muDIC/branch/master/graph/badge.svg)](https://codecov.io/gh/PolymerGuy/muDIC) [![Documentation Status](https://readthedocs.org/projects/mudic/badge/?version=latest)](https://mudic.readthedocs.io/en/latest/?badge=latest)[![PyPI version](https://badge.fury.io/py/muDIC.svg)](https://badge.fury.io/py/muDIC)
        
        
        ## Overview
        This project aims at providing a “batteries included” toolkit for digital image correlation in Python. 
        The functionality you need to perform digital image correlation on experimental data as well as for doing virtual experiments are included.
        
        ![alt text](documentation/examples/figures/GIF.gif)![alt text](documentation/examples/figures/GIF_mesh.gif)
        
        Typical usage is demonstrated in the examples located in the /Examples folder.
        
        
        This toolkit includes the following:
        * Image reader tools
        * Virtual lab
            * Speckle image generators
            * Image deformation tools
            * Noise injection
            * Image down-sampling
        * B-spline finite elements
            * Arbitrary polynomial order
            * Knot vectors can be manipulated
        * Meshing tools:
            * A light weight GUI for structured meshing
        * Image correlation routines:
            * Non linear least squares solver
        * Post processor
            * Calculates most popular strain measures
            * Light weight visualization
        * Logging
         
        ## Release notes
        The following changes were done in version 0.2.0:
        * Added Q4 element support
        * Q4 elements are now the default
        * Removed uneccessary scaling when images are deformed using displacement functions
        * Added quiver plots for displacements
        * Python 2.7 is no longer supported
        * Removed Perlin noise support as the package is only available for Python 2.7
        * Various bug fixes (See commit history)
        
        
        
        ## Getting Started
        
        These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
        ### Prerequisites
        This toolkit is tested on Python 3.7 and need all dependencies listen in requirements.txt
        
        ### Installing
        
        #### Installing by a package manager:
        Make sure you have Python 3 installed with pip and virtualenv
        
        Make new folder and use a terminal to make a virtual environment:
        ```
        $ python -m venv env
        $ source env/bin/activate #On Linux and Mac OS
        $ env\Scripts\activate.bat #On Windows
        ```
        We can now install µDIC inside this environment using pip
        ```
        $ pip install muDIC
        ```
        Now, lets run all the tests included by using nosetests
        ```
        $ nosetests muDIC
        ```
        
        
        #### Installing by cloning the repos:
        Start to clone this repo to your preferred location:
        ```
        $ cd /path/to/project/
        $ git init
        $ git clone https://github.com/PolymerGuy/muDIC.git
        ```
        
        We recommend that you always use virtual environments, either by virtualenv or by Conda env
        
        Virtual env:
        ```
        $ cd /path/to/muDIC
        $ python -m venv env
        $ source ./env/bin/activate #On Linux and Mac OS
        $ env\Scripts\activate.bat #On Windows
        $ pip install -r requirements.txt
        ```
        
        ## Running the tests
        
        The tests should always be launched to check your installation.
        
        If you installed by a package manager:
        ```
        $ nosetests muDIC #Note capital cases
        ```
        
        If you cloned the repo:
        ```
        $ cd /path/to/muDIC/
        $ nosetests
        ```
        
        ## Documentation
        Documentation is found here: [Read the docs](https://mudic.readthedocs.io/en/latest/)
        
        
        ## Our motivation
        The motivation for this work was the need for a transparent code which could be modified and extended easily, without digging deep into C or C++ source code. The implementation is pure python with the exception of third-party packages such as Scipy, Numy etc.
        
        
        ## Contributing
        Clone the repository, add your changes, add new tests and you are ready for a pull request
        
        ## Authors
        * **Sindre Olufsen** - *Implementation* - [PolymerGuy](https://github.com/polymerguy)
        * **Marius Endre Andersen** - *Wrote the Matlab code which was the starting point for this project*
        
        ## License
        This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
        
        ## Citing this project
        This project is described in the following paper and citation is highly appreciated
        [µDIC: An open-source toolkit for digital image correlation](https://doi.org/10.1016/j.softx.2019.100391)
        
        
        
        
        
        
        
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
