Metadata-Version: 1.1
Name: amlearn
Version: 0.0.1rc1
Summary: Machine Learning package for amorphous materials.
Home-page: https://github.com/Qi-max/amlearn
Author: Qi Wang
Author-email: qwang.mse@gmail.com
License: modified BSD
Download-URL: https://github.com/Qi-max/amlearn/archive/0.0.1.tar.gz
Description: # <img alt="amlearn" src="docs_rst/_static/amlearn_logo.png" width="300">
        Machine Learning package for amorphous materials(Working in Progress).
        
        We integrate Fortran90 with Python (using f2py) to achieve combination of the
        flexibility and fast-computation (>10x times faster than pure Python) of features. Please see examples
        in the short-range ordering (SRO) and medium-range ordering (MRO) representations
        in the featurizers folder. The SRO and MRO representation are based on a recent
        paper by Qi Wang and Anubhav Jain (to be published).
        
        Wrapper classes and utility functions for featurizers powered by matminer/amp and machine
        learning algorithms supported by scikit-learn are also included.
        
        
        
        
        ## Installation
        
        Before installing amlearn, please install numpy (version 1.7.0 or greater) first.
        
        We recommend to use the conda install.
        
        ```sh
        conda install numpy
        ```
        
        or you can find numpy installation guide from [Numpy installation instructions](https://www.scipy.org/install.html).
        
        
        Then, you can install amlearn. There are two ways to install amlearn:
        
        - **Install amlearn from PyPI (recommended):**
        
        ```sh
        pip install amlearn
        ```
        
        
        - **Alternatively: install amlearn from the GitHub source:**
        
        First, clone amlearn using `git`:
        
        ```sh
        git clone https://github.com/Qi-max/amlearn
        ```
        
         Then, `cd` to the amlearn folder and run the `setup.py`:
        ```sh
        cd amlearn
        sudo python setup.py install
        ```
        
        
Keywords: amorphous materials,Materials Genome Initiative,machine learning,data science,data mining,AI,artificial intelligence,featurizer,auto featurizerauto machine learning
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Fortran
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
