Function mapping
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This English edition is an AI candidate and does not yet have an OCME Atlas (GPT-6) Twin closure receipt.
The notation f:X→Y states that the function f maps the domain X into the codomain Y.
mko-function-mapping · definition · v0.8.0
Mathematical statement
A function f:X→Y assigns exactly one output in Y to every input in X; the codomain Y need not equal the function's actual range.
Representative formula (exact TeX)
f:X\to Y
Assumptions
- X and Y are specified sets or compatible types.
- Every input in X has exactly one output under f.
Symbol scope
f— functionX— domainY— codomain→— mapping arrow
Intuition, definition, and misconceptions
The core of a function is not a drawn curve but a rule that associates every permitted input with exactly one output.
The declaration f:X→Y specifies the domain and codomain. The set of outputs actually attained may be only a subset of Y.
The Lean theorem function_total_unique proves, for every f:X→Y and x:X, that there exists a unique y:Y satisfying f x=y.
A common mistake is to treat the codomain, range, and graph of a function as the same object, or to identify effectful or failure-prone program functions directly with pure total mathematical functions.
Adopted derivation guide
Function mapping: deciding whether a rule is a function, and separating codomain, range and graphThe original MKO is retained. The guide has its own append-only revision and verification boundaries, not a new Lean proof.
Prerequisites
- Set membership — Function inputs and outputs belong to the domain and codomain respectively.
Verification boundary
Lean formalizes the core total-function claim that every input has a unique output. Partial functions, side effects, randomness, and execution failure lie outside this statement.
formalized_total_function_core
Next obligation
Add objects for range, injection, surjection, bijection, and partial functions, keeping the typed codomain distinct from the set of outputs actually attained.
Same-source structured data
This page and the interactive view use the same object and existing language edition; this adds no proof or human review.
Canonical MKO JSON · Plain Markdown