Python library for the analysis of dynamic measurements

Archived

This project is archived since May 2024. It will not receive any security related or other patches anymore and we cannot guarantee any form of support in the future.

Getting started:

• Python library for the analysis of dynamic measurements
  • Archived
  • Original description
  • Table of content
  • Quickstart
  • Features
  • Module diagram
  • Documentation
  • Installation
  • Contributing
  • Examples
  • Citation
  • Acknowledgement
  • Disclaimer
  • License

Detailed information:

• Installation
• Changelog
• Contributor Covenant Code of Conduct
• Advices and tips for contributors

Examples:

• Examples
  • Quick Examples
  • Detailed examples

Tutorials:

• Get assistance in using PyDynamic
  • Getting started with the tutorials
  • Deconvolution
  • Uncertainty

Code Reference:

• Evaluation of uncertainties
• Model estimation
• Miscellaneous
• Signal

Indices and tables

• Index

• Module Index

• Search Page

References

[Eichst2016]

S. Eichstädt und V. Wilkens GUM2DFT — a software tool for uncertainty evaluation of transient signals in the frequency domain. Meas. Sci. Technol., 27(5), 055001, 2016. https://dx.doi.org/10.1088/0957-0233/27/5/055001

[Eichst2012]

S. Eichstädt, A. Link, P. M. Harris and C. Elster Efficient implementation of a Monte Carlo method for uncertainty evaluation in dynamic measurements Metrologia, vol 49(3), 401 https://dx.doi.org/10.1088/0026-1394/49/3/401

[Eichst2010]

S. Eichstädt, C. Elster, T. J. Esward and J. P. Hessling Deconvolution filters for the analysis of dynamic measurement processes: a tutorial Metrologia, vol. 47, nr. 5 https://stacks.iop.org/0026-1394/47/i=5/a=003?key=crossref.310be1c501bb6b6c2056bc9d22ec93d4

[Elster2008]

C. Elster and A. Link Uncertainty evaluation for dynamic measurements modelled by a linear time-invariant system Metrologia, vol 45 464-473, 2008 https://dx.doi.org/10.1088/0026-1394/45/4/013

[Link2009]

A. Link and C. Elster Uncertainty evaluation for IIR filtering using a state-space approach Meas. Sci. Technol. vol. 20, 2009 https://dx.doi.org/10.1088/0957-0233/20/5/055104

[Vuer1996]

R. Vuerinckx, Y. Rolain, J. Schoukens and R. Pintelon Design of stable IIR filters in the complex domain by automatic delay selection IEEE Trans. Signal Proc., 44, 2339-44, 1996 https://dx.doi.org/10.1109/78.536690

[Smith]

Smith, J.O. Introduction to Digital Filters with Audio Applications, https://ccrma.stanford.edu/~jos/filters/, online book

[Savitzky]

A. Savitzky, M. J. E. Golay, Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chemistry, 1964, 36 (8), pp 1627-1639.

[NumRec]

Numerical Recipes 3rd Edition: The Art of Scientific Computing W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery Cambridge University Press ISBN-13: 9780521880688

[White2017]

White, D.R. Int J Thermophys (2017) 38: 39. https://doi.org/10.1007/s10765-016-2174-6

[Zhivomirov2018]

Zhivomirov, H. 2018. A Method for Colored Noise Generation. Romanian Journal of Acoustics and Vibration. 15, 1 (Aug. 2018), 14-19: http://rjav.sra.ro/index.php/rjav/article/view/40