In general, there are many ways to express the same linear relationship
between variables. clp(Q,R) does not care to distinguish between
them, but the user might. The predicate
`ordering(`

`+Spec``)`

gives you some control over the
variable ordering. Suppose that instead of `B`, you want
`Mp` to be the defined variable:

clp(r) ?-mg(P,12,0.01,B,Mp).{B=1.1268250301319698*P-12.682503013196973*Mp}

This is achieved with:

clp(r) ?-mg(P,12,0.01,B,Mp), ordering([Mp]).{Mp= -0.0788487886783417*B+0.08884878867834171*P}

One could go one step further and require `P` to appear before
(to the left of) `B` in an addition:

clp(r) ?-mg(P,12,0.01,B,Mp), ordering([Mp,P]).{Mp=0.08884878867834171*P-0.0788487886783417*B}

`Spec` in `ordering(`

`+Spec``)`

is either a list of
variables with the intended ordering, or of the form
`A``<`

`B`. The latter form means that `A` goes to the
left of `B`. In fact, `ordering([A,B,C,D])`

is shorthand for:

ordering(A < B), ordering(A < C), ordering(A < D), ordering(B < C), ordering(B < D), ordering(C < D)

The ordering specification only affects the final presentation of the
constraints. For all other operations of clp(Q,R), the ordering is immaterial.
Note that `ordering/1`

acts like a constraint: you can put it anywhere
in the computation, and you can submit multiple specifications.

clp(r) ?-ordering(B < Mp), mg(P,12,0.01,B,Mp).{B= -12.682503013196973*Mp+1.1268250301319698*P} clp(r) ?-ordering(B < Mp), mg(P,12,0.01,B,Mp), ordering(P < Mp).{P=0.8874492252651537*B+11.255077473484631*Mp}

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