Say we have a function that maps a string of size $n$ of some finite alphabet to another such string of size $n$. Or alternatively, a function that maps an $n$ dimensional real vector to another one.
I am looking for a term/concept that captures the notion of how "local" the transformation is. For example, if such a function maps a string of 5000 digits to the same string, except multiplying the 43'th digit by 2 or by 10 billion, then it is extremely local, since if you change one digit in the input, this will only change the same digit in the output.
But if we have a cryptographic hash function, then changing one digit even slightly, will completely change all the output digits, and all of them in different ways. So such a function is highly "non-local"
Is there a formal concept of this notion of "locality" of a transformation?
One measure of locality of a function $f:X^n\to Y^m$ would be the maximum value of $$ \frac{\|f(v)-f(w)\|_0}{\|v-w\| _0} $$ over all pairs $v,w\in X^n$ where $v\neq w$. Here, $\|v-w\| _0$ is the number of coordinates where $v$ and $w$ differ, also known as their Hamming distance. This quantity is more generally known as the Lipschitz norm of $f$, and is defined for any map between two metric spaces (provided one takes the supremum instead of the maximum).
For example, if this quantity was $1$, then changing any coordinate of the input would change at most coordinate of the output, indicating the function is very local. The largest it could be is $m$, indicating that there exists a vector whose output can be completely changed by altering a single coordinate.
A possible drawback is that this measure the worst case non-locality of $f$, instead of the average non-locality.