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.

Install Scipolate using pip:

pip install scipolate

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 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.

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.

An Example will follow.