Metadata-Version: 2.1
Name: pycsep
Version: 0.1.0
Summary: Python tools from the Collaboratory for the Study of Earthquake Predictability
Home-page: https://github.com/SCECCode/csep2
Author: William Savran
Author-email: wsavran@usc.edu
License: LICENSE
Description: # PyCSEP: Collaboratory for the Study of Earthquake Predictability
        
        ![](http://hypocenter.usc.edu/research/badges/CSEP2_Logo_CMYK.png)
        
        ![Python version](http://hypocenter.usc.edu/research/badges/pycsep-python.svg)
        ![Python application](https://github.com/SCECCode/csep2/workflows/Python%20application/badge.svg)
        [![Build sphinx documentation](https://github.com/SCECCode/csep2/workflows/Build%20sphinx%20documentation/badge.svg)](https://cseptesting.org)
        [![codecov](https://codecov.io/gh/SCECcode/csep2/branch/dev/graph/badge.svg)](https://codecov.io/gh/SCECcode/csep2)
        
        The PyCSEP tools help earthquake forecast model developers evaluate their forecasts with the goal of understanding
        earthquake predictability.
        
        PyCSEP should:
        1. Help modelers become familiar with formats, procedures, and evaluations used in CSEP Testing Centers.
        2. Provide vetted software for model developers to use in their research.
        3. Provide quantative and visual tools to assess earthquake forecast quality.
        4. Promote open-science ideas by ensuring transparency and availability of scientific code and results.
        5. Curate benchmark models and data sets for modelers to conduct retrospective experiments of their forecasts.
        
        ## Installing PyCSEP
        
        PyCSEP can be installed using `pip` or built from source. We are working on a `conda-forge` recipe that will greatly
        simplify the installation process and remove the need to install system dependencies. If you plan on contributing to this 
        package, visit the [contribution guidelines](https://github.com/SCECcode/pycsep/blob/master/CONTRIBUTING.md) for 
        installation instructions.
        
            pip install pycsep
        
        Before this installation will work, you must **first** install the following system dependencies. The remaining dependencies
        should be installed by the installation script. To help manage dependency issues, we recommend using virtual environments 
        like `virtualenv`.
        
        Python 3.7 or later (https://python.org)
        
        NumPy 1.10 or later (https://numpy.org)  
        &nbsp;&nbsp;&nbsp;&nbsp;Python package for scientific computing and numerical calculations.
        
        GEOS 3.3.3 or later (https://trac.osgeo.org/geos/)  
        &nbsp;&nbsp;&nbsp;&nbsp;C++ library for processing geometry.
        
        PROJ 4.9.0 or later (https://proj4.org/)  
        &nbsp;&nbsp;&nbsp;&nbsp;Library for cartographic projections. 
        
        Example for Ubuntu:
        
            sudo apt-get install libproj-dev proj-data proj-bin  
            sudo apt-get install libgeos-dev 
            pip install --upgrade pip
            pip install numpy
            
        Example for MacOS:
        
            brew install proj geos
            pip install --upgrade pip
            pip install numpy
            
        ### From Source
        
        Use this approach if you want the most up-to-date code. This creates an editable installation that can be synced with 
        the latest GitHub commit. 
        
        We recommend using virtual environments when installing python packages from source to avoid any dependency conflicts. We prefer 
        `conda` as the package manager over `pip`, because `conda` does a good job of handling binary distributions of packages
        across multiple platforms. Also, we recommend using the `miniconda` installer, because it is lightweight and only includes
        necessary pacakages like `pip` and `zlib`. 
        
        #### Using Conda
        If you don't have `conda` on your machine, download and install [Miniconda](https://docs.conda.io/en/latest/miniconda.html).
        
            git clone https://github.com/SCECcode/pycsep
            cd pycsep
            conda env create -f requirements.yml
            conda activate csep-dev
            # Installs in editor mode with all dependencies
            pip install -e .
            
        Note: If you want to go back to your default environment use the command `conda deactivate`.
        
        #### Using Pip / Virtualenv
        
        We highly recommend using Conda, because this tools helps to manage binary dependencies on Python packages. If you
        must use [Virtualenv](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/)
        follow these instructions:  
        
            git clone https://github.com/SCECcode/pycsep
            cd pycsep
            python -m virtualenv venv
            source venv/bin/activate
            # Installs in editor mode with all dependencies
            pip install -e .[all]
            
         Note: If you want to go back to your default environment use the command `deactivate`.   
        
        ## Documentation and Changelog
        
        The documentation can be found at [here](https://cseptesting.org), and the changelog can be found 
        [here](https://github.com/SCECcode/pycsep/blob/master/CHANGELOG.txt).
        
        ## Releases 
        
        We follow [semver](https://semver.org/) for our versioning strategy. 
        
Platform: UNKNOWN
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: test
Provides-Extra: dev
Provides-Extra: all
