MATHMET Dynamic

Analysis of dynamic measurements

Software supporting dynamic metrology

This page provides an overview of scientific software that is either developed by MATHMET Members or which is recommended by MATHMET Dynamic.

For more information or a request to add a software to that list contact MATHMET Secretary.

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Software developed by MATHMET Members

PyDynamic - Software environment for dynamic metrology

The goal of this package is to provide a starting point for users in metrology and related areas who deal with time-dependent, i.e. dynamic, measurements. The software is part of the joint EMPIR research project 14SIP08 of the national metrology institutes from Germany and the UK, i.e. Physikalisch-Technische Bundesanstalt and the National Physical Laboratory.
Software repository at GitHub

Installation
via
  pip install PyDynamic

Data Fusion and Network Design Simulation Software

This software can be used to simulate distributed measuring systems and networks in which sensors may be faulty, noisy or interdependent. The software can be used to study network design, to compare data fusion algorithms and to evaluate measurement uncertainties associated with aggregated data in networks.
Software download at NPL Website

Lock-In Amplifier Simulation Software

The objective of the simulation software is to help answer questions about how well a lock-in amplifier can recover a signal from noise (the 'accuracy' of the result provided by the instrument) and about the possible dispersion of values obtained (the 'precision' of the result). The software allows users to investigate the performance and limitations of ideal and imperfect instruments applied to simulated and real test signals.
Software download at NPL Website

GUM Monte Carlo for dynamic measurements

The propagation of measurement uncertainty using the GUM Supplement 2 Monte Carlo method requires an efficient implementation in the case of dynamic measurements in order to achieve high accuracies.
Download
0

Richardson-Lucy for spectral deconvolution

The correction of deviations in spectra measured with a spectrometer is often necessary in order to obtain accurate results. The classical approach for such a correction is based on a method by Stearns. However, it has been demonstrated that the Richardson-Lucy method can produce much better results here.
Download
0
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