Transparent calculations with uncertainties on the quantities involved (aka "error propagation") ; calculation of derivatives
Project description
``uncertainties`` allows calculation such as (0.2 +- 0.01)**2 = 0.04 +- 0.004
to be performed transparently.
**Correlations** between expressions are correctly taken into account
(``x-x`` is exactly zero, for instance).
Basic examples::
# Mathematical operations:
x = uncertainties.Number_with_uncert((0.20, 0.01)) # x = 0.20+-0.01
x = uncertainties.Number_with_uncert("0.20(1)") # Other representation
print x**2 # Prints "0.04+-0.004"
print math.sin(x**2) # Prints "0.0399...+-0.00399..."
# Access to the value at the origin, and to the uncertainty:
y = x**2
print y # Prints "0.04+-0.004"
print y.origin_value # Prints "0.04"
print y.std_dev() # Prints "0.004..."
print y.derivatives[x] # Partial derivative: prints "2"
print y - x*x # Exactly zero: correlations taken into account
**Almost all mathematical operations** are supported, including most
functions from the standard ``math`` module and functions from the
third-party numpy_ module (fast operations on arrays and matrices).
There is no restriction on the complexity of the expressions, or on the
number of variables involved.
Another possible use of this module is the calculation of **partial
derivatives** of mathematical functions.
More examples and additional information can be obtained with ``pydoc
uncertainties`` after installation.
Please send feature requests, bug reports, or compliments to the author.
.. _numpy: http://numpy.scipy.org/
to be performed transparently.
**Correlations** between expressions are correctly taken into account
(``x-x`` is exactly zero, for instance).
Basic examples::
# Mathematical operations:
x = uncertainties.Number_with_uncert((0.20, 0.01)) # x = 0.20+-0.01
x = uncertainties.Number_with_uncert("0.20(1)") # Other representation
print x**2 # Prints "0.04+-0.004"
print math.sin(x**2) # Prints "0.0399...+-0.00399..."
# Access to the value at the origin, and to the uncertainty:
y = x**2
print y # Prints "0.04+-0.004"
print y.origin_value # Prints "0.04"
print y.std_dev() # Prints "0.004..."
print y.derivatives[x] # Partial derivative: prints "2"
print y - x*x # Exactly zero: correlations taken into account
**Almost all mathematical operations** are supported, including most
functions from the standard ``math`` module and functions from the
third-party numpy_ module (fast operations on arrays and matrices).
There is no restriction on the complexity of the expressions, or on the
number of variables involved.
Another possible use of this module is the calculation of **partial
derivatives** of mathematical functions.
More examples and additional information can be obtained with ``pydoc
uncertainties`` after installation.
Please send feature requests, bug reports, or compliments to the author.
.. _numpy: http://numpy.scipy.org/
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