In mathematics, a partial function from X to Y (written as f: X ↛ Y) is a function f: X' → Y, where X' is a subset of X. It generalizes the concept of a function f: X → Y by not forcing f to map every element of X to an element of Y (only some subset X' of X). If X' = X, then f is called a total function and is equivalent to a function. Partial functions are often used when the exact domain, X' , is not known (e.g. many functions in computability theory).
Specifically, we will say that for any x ∈ X, either:
- f(x) = y ∈ Y (it is defined as a single element in Y) or
- f(x) is undefined.
Thus g(n) is only defined for n that are perfect squares (i.e. 0, 1, 4, 9, 16, ...). So, g(25) = 5, but g(26) is undefined.
Domain of a partial function
There are two distinct meanings in current mathematical usage for the notion of the domain of a partial function. Most mathematicians, including recursion theorists, use the term "domain of f" for the set of all values x such that f(x) is defined ( X' above). But some, particularly category theorists, consider the domain of a partial function f:X→Y to be X, and refer to X' as the domain of definition.
Occasionally, a partial function with domain X and codomain Y is written as f: X ⇸ Y, using an arrow with vertical stroke.
A partial function is said to be injective or surjective when the total function given by the restriction of the partial function to its domain of definition is. A partial function may be both injective and surjective, but the term bijection generally only applies to total functions.
An injective partial function may be inverted to an injective partial function, and a partial function which is both injective and surjective has an injective function as inverse.
Total function is a synonym for function. The use of the prefix "total" is to suggest that it is a special case of a partial function. For example, when considering the operation of morphism composition in Concrete Categories, the composition operation is a total function if and only if has one element. The reason for this is that two morphisms and can only be composed as if , that is, the codomain of must equal the domain of .
Discussion and examples
The first diagram above represents a partial function that is not a total function since the element 1 in the left-hand set is not associated with anything in the right-hand set.
Consider the natural logarithm function mapping the real numbers to themselves. The logarithm of a non-positive real is not a real number, so the natural logarithm function doesn't associate any real number in the codomain with any non-positive real number in the domain. Therefore, the natural logarithm function is not a total function when viewed as a function from the reals to themselves, but it is a partial function. If the domain is restricted to only include the positive reals (that is, if the natural logarithm function is viewed as a function from the positive reals to the reals), then the natural logarithm is a total function.
Subtraction of natural numbers
It is only defined when .
In some automated theorem proving systems a partial function is considered as returning the bottom type when it is undefined. The Curry-Howard correspondence uses this to map proofs and computer programs to each other.
In computer science a partial function corresponds to a subroutine that raises an exception or loops forever. The IEEE floating point standard defines a Not-a-number value which is returned when a floating point operation is undefined and exceptions are suppressed, e.g. when the square root of a negative number is requested.
In a programming language where function parameters are statically typed, a function may be defined as a partial function because the language's type system cannot express the exact domain of the function, so the programmer instead gives it the smallest domain which is expressible as a type and contains the true domain.
- Injective function
- Surjective function
- Multivalued function
- Symmetric inverse semigroup
- Densely defined operator
- Martin Davis (1958), Computability and Unsolvability, McGraw-Hill Book Company, Inc, New York. Republished by Dover in 1982. ISBN 0-486-61471-9.
- Stephen Kleene (1952), Introduction to Meta-Mathematics, North-Holland Publishing Company, Amsterdam, Netherlands, 10th printing with corrections added on 7th printing (1974). ISBN 0-7204-2103-9.
- Harold S. Stone (1972), Introduction to Computer Organization and Data Structures, McGraw-Hill Book Company, New York.