What is numericalmodel?

The Python package numericalmodel is an attempt to make prototyping simple numerical models in Python an easy and painless task.

Why should I prototype a numerical model in Python?

During development phase of a model, it is very handy to be able to flexibly change crucial model parts. One might want to quickly:

• add more variables/parameters/forcings
• add another model equation
• have specific forcings be time-dependent
• test another numerical scheme
• use different numerical schemes for each equation
• combine numerical schemes to solve different equation parts
• etc.

Quickly achieving this in a compiled, inflexible language like Fortran or C may not be that easy. Also, debugging or unit testing such a language is way more inconvenient than it is in Python. With Python, one can take advantage of the extreme flexibility that object orientation and object introspection provides.

While it is obvious, that such a prototyped model written in an interpreted language like Python will never come up to the speed and efficiency of a compiled language, it may seem very appealing in terms of flexibility. Once it’s clear how the model should look like and fundamental changes are unlikely to occur anymore, it can be translated into another, faster language.

Can I implement any numerical model with numericalmodel?

No, at least for now :-). Currently, there are a couple of restrictions:

• only zero-dimensional models are supported for now. Support for more dimensions is on the TODO-list.
• numericalmodel is focused on physical models

But that doesn’t mean that you can’t create new subclasses from numericalmodel to fit your needs.

Is setting up a numerical model with numericalmodel really that easy?

Have a look at the Basics, Setting up a model and the Examples and see for yourself.