Search Results for "python text parser"

The Functional Mock-up Interface (FMI) specification intentionally provides only the most essential and fundamental functionalities in the form of a C interface. On the one hand, this increases flexibility in use and portability to virtually any platform. On the other hand, such a low-level approach implies several prerequisites a simulation tool has to fulfill in order to be able to utilize such an FMI component. The FMI++ library addresses this problem for models and tools with...

Typically, to program a GUI is time consuming and requires experience with graphic libraries. OpenNum lets you create a graphical interface adapted to your solvers by simply editing an XML configuration file. More specifically, OpenNum lets you · to collect a hierarchical dataset, · to call any executable file and · to visualize scalar and vector fields, plot graphs or show simple plain text files. It also has other useful utilities specifically designed for numerical...

TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. When multiple values are provided (e.g. for TCP...

ASCEND is a modelling environment and solver for large or small systems of non-linear equations, for use in engineering, thermodynamics, chemistry, physics, mathematics and biology. Solvers for both steady and dynamic (NLA & DAE) problems, are provid

PetriKit is a modular toolkit for Petri Net analysis. It allows the extraction of basic properties, extraction of invariants, and generation of reachability graph. Results can be formatted in plain text, HTML or XML files.

A script to generate random text using Markov chains. Output text will be stylistically similar to the training text.