Metadata-Version: 2.1
Name: upy2
Version: 2.0.1b6
Summary: A package for uncertainty propagation
Home-page: http://github.com/friedrichromstedt/upy/
Author: Friedrich Romstedt
Author-email: friedrichromstedt@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Description-Content-Type: text/x-rst
Requires-Dist: numpy (>=1.13.0)

Measurements are precise only up to a particular *uncertainty*.
Such measurement results are thus called *uncertain quantities*.  When
performing calculations with uncertain quantities, the uncertainties
of the results depend on the uncertainties of the operands involved.
The quantification of uncertainties resulting from a mathematical
operation involving uncertain operands is called *uncertainty
propagation*.
From a programmer's point of view, uncertainties might be associated
with the respective nominal values, such that the propagation of
uncertainties happens automatically, and existing algorithms can be
re-used with the *uncertain quantities* as arguments.
Here I am proposing a Python package to define uncertain operands, to
carry out calculations using such operands *with uncertainty
propagation*, and to provide string representations of uncertain
quantities involved.
Complex numbers can be used to define uncertain quantities; for such
complex-valued uncertainties no net uncertainty can be calculated.
The objects holding uncertain values have array properties, though
scalar arrays can be used; elements of an uncertain array behave as if
they were uncertain quantities on their own.  When requesting a string
representation of an uncertain quantity, the typeset result depends on
the number of standard deviations to use and on the chosen precision,
given by the number of digits with respect to the uncertainty.
Furthermore, when typesetting multidimensional arrays with
uncertainty, the decimal fractions are aligned to improve readability
of the results.
``upy`` uses *algorithmic differentiation* (also known as *automatic
differentation*) to track uncertainties through the operations.
Uncertain values might be used in calculations together with other
uncertain values as well as with any numeric Python or ``numpy``
objects.  A range of mathematical functions is supported.
``upy`` provides several syntactic conventions appropriate to the
subject.  For instance, defining uncertain quantities is possible by
writing:

.. code:: python

    uvalue = nominal +- u(uncertainty)

where ``u`` is a function provided by ``upy``.  Uncertain values
constructed in this way will be independent of each other with respect
to their uncertainties; ``upy`` will keep track of the correlations
arising from combination of uncertain quantities in mathematical
operations.  All functionality is suited both for use in the
interactive Python shell as well as in programs for numerical
analysis. 

