Metadata-Version: 2.1
Name: MaterialsInformatics
Version: 1.0.1
Summary: Clean and add extra information to data ...
Home-page: https://github.com/MaterialInformatics/MaterialsInfomatics
License: BSD
Description: .. inclusion-marker-do-not-remove
        
        Analysis of Imaging Data (DIC/SEM/TEM/Optical): 
          1. Folder Inp.
          2. Operation
          3. Folder Out.
          4. Done.
        
        Contents -->
          1. Identification of Features (PCA/SEA/Correlation/Wavelet/blibla/... Analysis) --> Outp to Tmp folder, plots/feature-txt-files
          2. Collection of Features to Library (from PCA, from Correlations, from Wavelets, from Images, from defects) --> 
          3. Reconstruction of Synthetic microstructure  (EDX --> LAMMPS) --> 
          4. Interatomic Potential Finder/Machine-Learner (ASE) --> 
          5. Simulation of Synthetic Microstructure (LAMMPS, ASE) --> 
          6. Machine Training (given feature files) --> 
          7. Machine Predicting --> 
        ==================================================================================================
        
        **MaterialsInformatics** is a Python package that provides direct, easy-to-use black-box solutions for materials informatics based on imaging data that emerge in materials science.
        
        Example
        -------
        
        The **example.py** runs over the given example data, producing a new file and a plot that compares the original and the prepared data. To run this
        example, simply type: :code:`python example.py`.
        
        Requirements and Installation
        -----------------------------
        
        This code has been developed in Python 3.7.1 and it is compatible with Python above 3.5 versions. The code has been tested to run in Windows, OSX and Linux operating systems. 
        
        This code uses numpy as specified in docs/requirements.txt. The ploting routine from the *example.py* also requires the use of matplotlib.
        
        The code can be run directly from a cloned GitHub `repository`_ or it can also be installed as a python `package`_ through pip:
        
        .. code::
        
           pip install MaterialsInformatics
        
        The software can be used in two ways:
         - Either through the GUI, by using:
        
           python -m MaterialsInformatics
        
         - Or through importing the library as
        
           import MaterialsInformatics as MATI
        
        The code has been tested within Anaconda3 
        
        .. _compability:
        
        Compatibility
        -------------
        
        This code has been tested with data generated by different versions of
        the `ASE`_ and `LAMMPS`_ software. If you encounter issues running the code for
        any version of these software report an issue. Note that an example
        file will be needed in order to improve the code. List of the `ASE`_ and `LAMMPS`_
        software is below. If you encounter issues running the code for any version of the MaterialsInformatics software report an issue. Note that an example file will be needed in order to improve the code.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/plain
