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## 2022-03-12

## Channels

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- # shadow-cljs (103)

Hey. Is there a way to do a square root when using a finite domain lvar? It can be lossful but it's fine.

I think that finding data for a specific standard deviation is not the best problem for the solver. But maybe I'm just mistaken.
I get this as one of my errors and it doesn't get more understandable from here...
`Error printing return value (StackOverflowError) at clojure.lang.Numbers/hasheq (Numbers.java:1129).`

Probably the search space is too deep...

👋 I’m new to logic programming and am looking solve a constraint problem that is think is best modeled as a finite domain.
• Given a set of mentors and mentees
• Each mentee can have a list of mentor preferences
• I want to find all solutions to matching mentees with their mentor preferences.
• Each mentor can only be a mentor for **one** mentee
My thinking was to look at this as a finite domain (translating names to numbers) and using a `lvar`

for each mentor.
By using `(fd/distinct (vec lmentors))`

I was hoping to solve for “each mentor only gets to have a single mentee”.
**Problem**: As the number of lvars becomes large (say ~40) then running `(fd/distinct (vec lmentors))`

is very slow. If I remove this constraint the program finds solutions immediately.
Are there ways to optimize this or just program this smarter?
core logic:

```
(let [lmentors (repeatedly (count mentees) lvar) ;; one lvar for each mentee to match
solutions (pldb/with-db db ;; db pre populated with mentee, mentor and preferences relations
(run 1 [q]
(== q (vec ;; q is [[mentee1 lvar-mentor2] [mentee2 lvar-mentor2] ... ]
(map vector (keys mentees) lmentors)))
(everyg #(fd/in % mentor-domain) lmentors)
(fd/distinct (vec lmentors))
(and*
(map
(fn [tee tor]
(fresh [tors]
(mentee tee)
(mentor tor)
(preferences tee tors)
(membero tor tors)))
(keys mentees)
lmentors))))]
(map keyword-solution solutions))
```

Full sample (seems to work at small scale)
https://gist.github.com/krukow/9ab5a708458e4d3d758032b081a5707a