package colibri2
val run_exn :
?nodec:unit ->
?step_limit:int ->
?last_effort_limit:last_effort_limit ->
?learning:bool ->
?options:Colibri2_core.ForSchedulers.Options.options ->
theories:(Colibri2_core.Egraph.wt -> unit) list ->
(Colibri2_core.Egraph.wt -> Colibri2_core.Egraph.wt -> 'a) ->
'a
run_exn ?nodec ?limit ?learning ~theories add_assertions
.
add_assertions d
should add the assertions. The resulting function is applied on the environment after propagation and possibly decisions
val run :
?nodec:unit ->
?step_limit:int ->
?last_effort_limit:last_effort_limit ->
?options:Colibri2_core.ForSchedulers.Options.options ->
theories:(Colibri2_core.Egraph.wt -> unit) list ->
(Colibri2_core.Egraph.wt -> Colibri2_core.Egraph.wt -> 'a) ->
[> `Contradiction | `Done of 'a ]
val new_solver :
learning:bool ->
?last_effort_limit:last_effort_limit ->
?options:Colibri2_core.ForSchedulers.Options.options ->
unit ->
t
val init_theories :
theories:(Colibri2_core.Egraph.wt -> unit) list ->
t ->
unit
val add_assertion : t -> (Colibri2_core.Egraph.wt -> unit) -> unit
val check_sat :
?step_limit:int ->
t ->
[> `Unsat
| `Sat of Colibri2_core.Egraph.wt
| `Unknown of Colibri2_core.Egraph.wt ]
val get_steps : t -> int
val get_context : t -> Colibri2_stdlib.Context.creator
sectionYPositions = computeSectionYPositions($el), 10)"
x-init="setTimeout(() => sectionYPositions = computeSectionYPositions($el), 10)"
>