:mod:`fpectl` --- Floating point exception control
The :mod:`fpectl` module is not built by default, and its usage is discouraged and may be dangerous except in the hands of experts. See also the section :ref:`fpectl-limitations` on limitations for more details.
Most computers carry out floating point operations in conformance with the so-called IEEE-754 standard. On any real computer, some floating point operations produce results that cannot be expressed as a normal floating point value. For example, try
>>> import math >>> math.exp(1000) inf >>> math.exp(1000) / math.exp(1000) nan
(The example above will work on many platforms. DEC Alpha may be one exception.) "Inf" is a special, non-numeric value in IEEE-754 that stands for "infinity", and "nan" means "not a number." Note that, other than the non-numeric results, nothing special happened when you asked Python to carry out those calculations. That is in fact the default behaviour prescribed in the IEEE-754 standard, and if it works for you, stop reading now.
In some circumstances, it would be better to raise an exception and stop processing at the point where the faulty operation was attempted. The :mod:`fpectl` module is for use in that situation. It provides control over floating point units from several hardware manufacturers, allowing the user to turn on the generation of :const:`SIGFPE` whenever any of the IEEE-754 exceptions Division by Zero, Overflow, or Invalid Operation occurs. In tandem with a pair of wrapper macros that are inserted into the C code comprising your python system, :const:`SIGFPE` is trapped and converted into the Python :exc:`FloatingPointError` exception.
The :mod:`fpectl` module defines the following functions and may raise the given exception:
The following example demonstrates how to start up and test operation of the :mod:`fpectl` module.
>>> import fpectl >>> import fpetest >>> fpectl.turnon_sigfpe() >>> fpetest.test() overflow PASS FloatingPointError: Overflow div by 0 PASS FloatingPointError: Division by zero [ more output from test elided ] >>> import math >>> math.exp(1000) Traceback (most recent call last): File "<stdin>", line 1, in ? FloatingPointError: in math_1
Limitations and other considerations
Setting up a given processor to trap IEEE-754 floating point errors currently requires custom code on a per-architecture basis. You may have to modify :mod:`fpectl` to control your particular hardware.
Conversion of an IEEE-754 exception to a Python exception requires that the wrapper macros PyFPE_START_PROTECT and PyFPE_END_PROTECT be inserted into your code in an appropriate fashion. Python itself has been modified to support the :mod:`fpectl` module, but many other codes of interest to numerical analysts have not.
The :mod:`fpectl` module is not thread-safe.