[Numpy-discussion] PEP 31XX: A Type Hierarchy for Numbers (and other algebraic entities)
Wed Apr 25 03:36:06 CDT 2007
Here's a draft of the numbers ABCs PEP. The most up to date version
will live in the darcs repository at
http://jeffrey.yasskin.info/darcs/PEPs/pep-3141.txt (unless the number
changes) for now. Naming a PEP about numbers 3.141 seems cute, but of
course, I don't get to pick the number. :) This is my first PEP, so
apologies for any obvious mistakes.
I'd particularly like the numpy people's input on whether I've gotten
floating-point support right.
Title: A Type Hierarchy for Numbers (and other algebraic entities)
Version: $Revision: 54928 $
Last-Modified: $Date: 2007-04-23 16:37:29 -0700 (Mon, 23 Apr 2007) $
Author: Jeffrey Yasskin <email@example.com>
Type: Standards Track
Post-History: Not yet posted
This proposal defines a hierarchy of Abstract Base Classes (ABCs)
[#pep3119] to represent numbers and other algebraic entities similar
to numbers. It proposes:
* A hierarchy of algebraic concepts, including monoids, groups, rings,
and fields with successively more operators and constraints on their
operators. This will be added as a new library module named
* A hierarchy of specifically numeric types, which can be converted to
and from the native Python types. This will be added as a new
library module named "numbers".
Functions that take numbers as arguments should be able to determine
the properties of those numbers, and if and when overloading based on
types is added to the language, should be overloadable based on the
types of the arguments. This PEP defines some abstract base classes
that are useful in numerical calculations. A function can check that
variable is an instance of one of these classes and then rely on the
properties specified for them. Of course, the language cannot check
these properties, so where I say something is "guaranteed", I really
just mean that it's one of those properties a user should be able to
This PEP tries to find a balance between providing fine-grained
distinctions and specifying types that few people will ever use.
Although this PEP uses terminology from PEP3119, the hierarchy is
meaningful for any systematic method of defining sets of
classes. **Todo:** link to the Interfaces PEP when it's ready. I'm
also using the extra notation from [#pep3107] (annotations) to specify
Object oriented systems have a general problem in constraining
functions that take two arguments. To take addition as an example,
``int(3) + int(4)`` is defined, and ``vector(1,2,3) + vector(3,4,5)``
is defined, but ``int(3) + vector(3,4,5)`` doesn't make much sense. So
``a + b`` is not guaranteed to be defined for any two instances of
``AdditiveGroup``, but it is guaranteed to be defined when ``type(a)
== type(b)``. On the other hand, ``+`` does make sense for any sorts
of numbers, so the ``Complex`` ABC refines the properties for plus so
that ``a + b`` is defined whenever ``isinstance(a,Complex) and
isinstance(b,Complex)``, even if ``type(a) != type(b)``.
Monoids (http://en.wikipedia.org/wiki/Monoid) consist of a set with an
associative operation, and an identity element under that
operation. **Open issue**: Is a @classmethod the best way to define
constants that depend only on the type?::
"""+ is associative but not necessarily commutative and has an
identity given by plus_identity().
Subclasses follow the laws:
a + (b + c) === (a + b) + c
a.plus_identity() + a === a === a + a.plus_identity()
Sequences are monoids under plus (in Python) but are not
def __add__(self, other):
I skip ordinary non-commutative groups here because I don't have any
common examples of groups that use ``+`` as their operator but aren't
commutative. If we find some, the class can be added later.::
"""Defines a commutative group whose operator is +, and whose inverses
are produced by -x.
Where a, b, and c are instances of the same subclass of
AdditiveGroup, the operations should follow these laws, where
'zero' is a.__class__.zero().
a + b === b + a
(a + b) + c === a + (b + c)
zero + a === a
a + (-a) === zero
a - b === a + -b
Some abstract subclasses, such as Complex, may extend the
definition of + to heterogenous subclasses, but AdditiveGroup only
guarantees it's defined on arguments of exactly the same types.
Vectors are AdditiveGroups but are not Rings.
def __add__(self, other):
"""Associative commutative operation, whose inverse is negation."""
**Open issue:** Do we want to give people a choice of which of the
following to define, or should we pick one arbitrarily?::
"""Must define this or __sub__()."""
return self.zero() - self
def __sub__(self, other):
"""Must define this or __neg__()."""
return self + -other
"""A better name for +'s identity as we move into more mathematical
Including Semiring (http://en.wikipedia.org/wiki/Semiring) would help
a little with defining a type for the natural numbers. That can be
split out once someone needs it (see ``IntegralDomain`` for how).::
"""A mathematical ring over the operations + and *.
In addition to the requirements of the AdditiveGroup superclass, a
Ring has an associative but not necessarily commutative
multiplication operation with identity (one) that distributes over
addition. A Ring can be constructed from any integer 'i' by adding
'one' to itself 'i' times. When R is a subclass of Ring, the
additive identity is R(0), and the multiplicative identity is
Matrices are Rings but not Commutative Rings or Division
Rings. The quaternions are a Division Ring but not a
Field. The integers are a Commutative Ring but not a Field.
def __init__(self, i:int):
"""An instance of a Ring may be constructed from an integer.
This may be a lossy conversion, as in the case of the integers
def __mul__(self, other):
a * (b * c) === (a * b) * c
one * a === a
a * one === a
a * (b + c) === a * b + a * c
where one == a.__class__(1)
I'm skipping both CommutativeRing and DivisionRing here.
"""The class Field adds to Ring the requirement that * be a
commutative group operation except that zero does not have an
Practically, that means we can define division on a Field. The
additional laws are:
a * b === b * a
a / a === a.__class_(1) # when a != a.__class__(0)
Division lets us construct a Field from any Python float,
although the conversion is likely to be lossy. Some Fields
include the real numbers, rationals, and integers mod a
prime. Python's ``float`` resembles a Field closely.
def __init__(self, f:float):
"""A Field should be constructible from any rational number, which
includes Python floats."""
def __div__(self, divisor):
Division is somewhat complicated in Python. You have both __floordiv__
and __div__, and ints produce floats when they're divided. For the
purposes of this hierarchy, ``__floordiv__(a, b)`` is defined by
``floor(__div__(a, b))``, and, since int is not a subclass of Field,
it's allowed to do whatever it wants with __div__.
There are four more reasonable classes that I'm skipping here in the
interest of keeping the initial library simple. They are:
Rational powers of its elements are defined (and maybe a few other
(http://en.wikipedia.org/wiki/Algebraic_number). Complex numbers
are the most well-known algebraic set. Real numbers are _not_
algebraic, but Python does define these operations on floats,
which makes defining this class somewhat difficult.
The elementary functions
defined. These are basically arbitrary powers, trig functions, and
logs, the contents of ``cmath``.
The following two classes can be reasonably combined with ``Integral``
Defines gcd and lcm.
If someone needs to split them later, they can use code like::
class IntegralDomain(Ring): ...
numbers.Integral.__bases__ = (IntegralDomain,) + numbers.Integral.__bases__
Finally, we get to numbers. This is where we switch from the "algebra"
module to the "numbers" module.::
class Complex(Ring, Hashable):
"""The ``Complex`` ABC indicates that the value lies somewhere
on the complex plane, not that it in fact has a complex
component: ``int`` is a subclass of ``Complex``. Because these
actually represent complex numbers, they can be converted to
the ``complex`` type.
``Complex`` finally gets around to requiring its subtypes to
be immutable so they can be hashed in a standard way.
``Complex`` also requires its operations to accept
heterogenous arguments. Subclasses should override the
operators to be more accurate when they can, but should fall
back on the default definitions to handle arguments of
different (Complex) types.
**Open issue:** __abs__ doesn't fit here because it doesn't
exist for the Gaussian integers
(http://en.wikipedia.org/wiki/Gaussian_integer). In fact, it
only exists for algebraic complex numbers and real numbers. We
could define it in both places, or leave it out of the
``Complex`` classes entirely and let it be a custom extention
of the ``complex`` type.
The Gaussian integers are ``Complex`` but not a ``Field``.
"""Any Complex can be converted to a native complex object."""
def real(self) => Real:
def imag(self) => Real:
def __add__(self, other):
"""The other Ring operations should be implemented similarly."""
if isinstance(other, Complex):
return complex(self) + complex(other)
``FractionalComplex(Complex, Field)`` might fit here, except that it
wouldn't give us any new operations.
class Real(Complex, TotallyOrdered):
"""Numbers along the real line. Some subclasses of this class
may contain NaNs that are not ordered with the rest of the
instances of that type. Oh well. **Open issue:** what problems
will that cause? Is it worth it in order to get a
straightforward type hierarchy?
def real(self) => self.__class__:
def imag(self) => self.__class__:
def __abs__(self) => self.__class__:
if self < 0: return -self
else: return self
class FractionalReal(Real, Field):
"""Rationals and floats. This class provides concrete
definitions of the other four methods from properfraction and
allows you to convert fractional reals to integers in a
def properfraction(self) => (int, self.__class__):
"""Returns a pair (n,f) such that self == n+f, and:
* n is an integral number with the same sign as self; and
* f is a fraction with the same type and sign as self, and with
absolute value less than 1.
def floor(self) => int:
n, r = self.properfraction()
if r < 0 then n - 1 else n
def ceiling(self) => int: ...
def __trunc__(self) => int: ...
def round(self) => int: ...
**Open issue:** What's the best name for this class? RealIntegral? Integer?::
def __or__(self, other):
def __xor__(self, other):
def __and__(self, other):
def __lshift__(self, other):
def __rshift__(self, other):
Floating point values may not exactly obey several of the properties
you would expect from their superclasses. For example, it is possible
for ``(large_val + -large_val) + 3 == 3``, but ``large_val +
(-large_val + 3) == 0``. On the values most functions deal with this
isn't a problem, but it is something to be aware of. Types like this
inherit from ``FloatingReal`` so that functions that care can know to
use a numerically stable algorithm on them. **Open issue:** Is this
the proper way to handle floating types?::
"""A "floating" number is one that is represented as
``mantissa * radix**exponent`` where mantissa, radix, and
exponent are all integers. Subclasses of FloatingReal don't
follow all the rules you'd expect numbers to follow. If you
really care about the answer, you have to use numerically
stable algorithms, whatever those are.
**Open issue:** What other operations would be useful here?
These include floats and Decimals.
def radix(cls) => int:
def digits(cls) => int:
"""The number of significant digits of base cls.radix()."""
def exponentRange(cls) => (int, int):
"""A pair of the (lowest,highest) values possible in the exponent."""
def decode(self) => (int, int):
"""Returns a pair (mantissa, exponent) such that
mantissa*self.radix()**exponent == self."""
.. [#pep3119] Introducing Abstract Base Classes
.. [#pep3107] Function Annotations
..  Possible Python 3K Class Tree?, wiki page created by Bill Janssen
.. [#numericprelude] NumericPrelude: An experimental alternative
hierarchy of numeric type classes
Thanks to Neil Norwitz for helping me through the PEP process.
The Haskell Numeric Prelude [#numericprelude] nicely condensed a lot
of experience with the Haskell numeric hierarchy into a form that was
relatively easily adaptable to Python.
This document has been placed in the public domain.
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