Modelling of dynamical systems is essential in science and engineering and being able to simulate a solution in a software tool with sufficient ease and efficiency stil presents a challenge. This talk will give an overview of a new modelling libray called LCL and of my experience of modelling dynamicals systems using Python.
LCL is a powerful library for working with dynamical systems which can be easily defined in a Domain Specific Language (DSL). We will introduce LCL and key aspects of simulation, selection, approximation and optimisation using this library. We will review worked examples from the LCL library and lessons learned from implementing LCL as a scientific Python library.
This should be of interest both to people using Python in a scientific setting and to those with an interest in DSLs as we will cover such topics as - Defining and simulating dynamical systems using a DSL - Modelling stochastic systems - Refining and calibrating models by optimisation - Approximating models using genetic algorithms - Distributed computation of dynamical systems