Dictionaries in `Julia`

(and other programming languages) are *onto* functions, mathematically speaking. That is to say

$f:A\rightarrow B$

where
$f$
is a function defined for every
$x\in A,$
and also for every
$y\in B$
there exists at least one
$x\in A$
such that
$f(x)=y,$
that is an *onto*(or surjective) function. The

*inverse image*of $f$ is a function

$f^{(-1)}:\wp(B)\rightarrow\wp(A)$

where
$\wp(B)$
is the collection of all the subsets of
$B,$
that is the *power set*of $B,$ and where

$f^{(-1)}(C) = \{x \in A: f(x) \in C\}$

for any
$C \subseteq B.$
In other words, if
$f$
is a function that maps the elements of a set
$A$
onto a set
$B$
and if
$C$
is a subset of
$B$
then the inverse image
$f^{(-1)}(C)$
is a subset of
$A$
with all the elements that are mapped by
$f$
onto the set
$C.$
If `D`

is a `Dict`

then `D`

is the equivalent to
$f$
where
$A =$
`keys(D)`

and
$B =$
`values(D)`

. To define the inverse image function
$f^{(-1)}$
it is just necesary to code:

```
invImg(C::Set, D::Dict) = Set(filter(x -> D[x] âˆˆ C, keys(D)))
```

For example:

```
D = Dict([1,2,3,4,5,6,7] .=> ['a','a','b','a','b','a','c'])
C = Set(['a','c'])
invImg(C, D)
```

obtaining $f^{(-1)}(C) = \{1,2,4,6,7\}$ as expected.

## Oldest comments (2)

I am not sure I fully grasp this, can you add some commentary for folks who don't have a rigoruous math background like myself?

I added a comment Â«In other words...Â» I hope may help. Probably what I had in mind was more an invitation for mathematicians to see the advantages of using Julia to exemplify set theory concepts.