Metadata-Version: 2.1
Name: scipolate
Version: 0.1.3
Summary: helper for running different scipy 2D interpolations
Home-page: UNKNOWN
Author: Mirko Maelicke
Author-email: mirko.maelicke@kit.edu
License: GNU 3.0
Description: SciPolate
        =========
        
        Scipolate offers a small helper class that can be used to perform 
        2D interpolation tasks using scipy. It is meant to be used as a common 
        interface to run and validate the task automated in the same way.
        
        Installation
        ============
        
        Install Scipolate using pip:
        
        ```bash
        pip install scipolate
        ```
        
        Note
        ====
        
        Scipolate was originally a part of a interpolation web-app used in one of my 
        lectures. That means it was used in an API. Hence, the parameters are set in 
        one single JSON-like dictionary, which is un-pythonic.
        For the same reason, the class does provide an output *Report* including the 
        result as a base64 encoded image. Nevertheless, the class can be used outside 
        of a web-application context. Mind that performance was not important during 
        development. In case you need a fast algorithm, use scipy directly, or 
        something like the [interpolation](https://pypi.org/project/interpolation/) 
        library.
        
        With the new version the Interpolation itself is outsourced into a class on 
        its own. All the image processing and transformation used for the reporting 
        tools in my web based applications, a class called `WebInterface` is implemented.
        
        Usage
        =====
        
        There are two main interfaces that can be used:
        
        * The *Interpolator* class, which is the core class performing the 
        interpolation.
        
        * The *WebInterface* class which is meant to be used in a API, as it takes the
        arguments as JSON and returns JSON along with base64 encoded images.
        
         
         Example
         -------
         
         An Example will follow.
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
