labfis

Adds a new float type with uncertainty


Keywords
python, physics, error-propagation, ifsc, uncertainties, experimental-physics, uncertainty-calculations
License
MIT
Install
pip install labfis==1.1.4

Documentation

labfis.py

Travis - CI PyPI License

Description

Small library for uncertainty calculations and error propagation.

Error propagation:

The uncertainty is calculated analytically in accordance with the gaussian propagation aproximation established by the International Bureau of Weights and Measures (BIPM):

To compare two labfloats it is used the following methods:

Assuming:

  • If they are equal they must satisfy:

  • If they are different they must satisfy:

NOTE: Two labfloats can be not different and not equal at the same time by these methods.

Made by and for Physics Laboratory students in IFSC, who can't use uncertainties.py because of mean’s absolute deviation used in its calculation.

Usage

Just import with from labfis import labfloat and create an labfloat object, as this exemple below:

>>> from labfis import labfloat
>>> a = labfloat(1,3)
>>> b = labfloat(2,4)
>>> a*b
(2 ± 7)

Check the Wiki for more details.

Instalation

Intstall main releases with:

pip install labfis

Install development version with:

pip install git+https://github.com/phisgroup/labfis.py@development

References

  1. Kirchner, James. "Data Analysis Toolkit #5: Uncertainty Analysis and Error Propagation" (PDF). Berkeley Seismology Laboratory. University of California. Retrieved 22 April 2016.
  2. Goodman, Leo (1960). "On the Exact Variance of Products". Journal of the American Statistical Association. 55 (292): 708–713. doi:10.2307/2281592. JSTOR 2281592.
  3. Ochoa1,Benjamin; Belongie, Serge "Covariance Propagation for Guided Matching"
  4. Ku, H. H. (October 1966). "Notes on the use of propagation of error formulas". Journal of Research of the National Bureau of Standards. 70C (4): 262. doi:10.6028/jres.070c.025. ISSN 0022-4316. Retrieved 3 October 2012.
  5. Clifford, A. A. (1973). Multivariate error analysis: a handbook of error propagation and calculation in many-parameter systems. John Wiley & Sons. ISBN 978-0470160558.
  6. Lee, S. H.; Chen, W. (2009). "A comparative study of uncertainty propagation methods for black-box-type problems". Structural and Multidisciplinary Optimization. 37 (3): 239–253. doi:10.1007/s00158-008-0234-7.
  7. Johnson, Norman L.; Kotz, Samuel; Balakrishnan, Narayanaswamy (1994). Continuous Univariate Distributions, Volume 1. Wiley. p. 171. ISBN 0-471-58495-9.
  8. Lecomte, Christophe (May 2013). "Exact statistics of systems with uncertainties: an analytical theory of rank-one stochastic dynamic systems". Journal of Sound and Vibrations. 332 (11): 2750–2776. doi:10.1016/j.jsv.2012.12.009.
  9. "A Summary of Error Propagation" (PDF). p. 2. Retrieved 2016-04-04.
  10. "Propagation of Uncertainty through Mathematical Operations" (PDF). p. 5. Retrieved 2016-04-04.
  11. "Strategies for Variance Estimation" (PDF). p. 37. Retrieved 2013-01-18.
  12. Harris, Daniel C. (2003), Quantitative chemical analysis(6th ed.), Macmillan, p. 56, ISBN 978-0-7167-4464-1
  13. "Error Propagation tutorial" (PDF). Foothill College. October 9, 2009. Retrieved 2012-03-01.
  14. Helene, O.; Vanin, V.. Tratamento estatístico de dados em física experimental. São Paulo: Editora Edgard Blücher, 1981.
  15. Vuolo, J. E.. Fundamentos da teoria de erros. 2. ed. São Paulo: Editora Edgard Blücher, 1993.