Welcome to upy’s documentation!

Compiled August 21, 2010

Rationale

upy is a package for calculating error propagation in the programming language Python. It is intended to make calculations with measurement uncertainties easy but correct. For the needed derivative information, automatic differentiation (AD) is used. (AD is also known under the name algorithmic differentiation.)

upy is based on numpy, and can be used to store multidimensional arrays with uncertainty. For details, see The upy uncertain ndarray: class undarray.

There is also a upy Webcast.

Usage Instructions

• Go directly to Reference Manual to see an annotated table of contents of the reference manual.
• upy Tutorial is intended as a starting point for beginners and is not fully fledged yet.

See also: Search Page

Contents

• upy Tutorial
  • Webcast
  • Example Python Session
• Reference Manual
  • The upy uncertain ndarray: class undarray
  • undarray Printing Framework
  • Averaging Functions
  • Linear Regression Functions
  • The Dependency class
  • The upy.characteristic.Characterstic class
  • numpy Operator Overloading
  • Universal Math Functions
  • The Unittests

Useful Weblinks

• For download of upy, please go to http://github.com/friedrichromstedt/upy/downloads. Notice that the documentation is in this case beyond the released state of the project, i.e., not all features documented are in a tagged version, or even committed to the repo.

  To get the bleeding-edge version of upy, use:

  git clone git://github.com/friedrichromstedt/upy.git

  and assorted commands of git.

• For support, email to mailto:friedrichromstedt@gmail.com

• To join the mailing list, visit https://lists.sourceforge.net/lists/listinfo/upy-discussion

• To see the project’s sourceforge site, go to http:///sourceforge.net/projects/upy.