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def
Lean.Meta.generalizeTargetsEq
(mvarId : Lean.MVarId)
(motiveType : Lean.Expr)
(targets : Array Lean.Expr)
:
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- mvarId : Lean.MVarId
- indicesFVarIds : Array Lean.FVarId
- fvarId : Lean.FVarId
- numEqs : Nat
Similar to generalizeTargets but customized for the casesOn motive.
Given a metavariable mvarId representing the
Ctx, h : I A j, D |- T
where fvarId is hs id, and the type I A j is an inductive datatype where A are parameters,
and j the indices. Generate the goal
Ctx, h : I A j, D, j' : J, h' : I A j' |- j == j' -> h == h' -> T
Remark: (j == j' -> h == h') is a "telescopic" equality.
Remark: j is sequence of terms, and j' a sequence of free variables.
The result contains the fields
mvarId: the new goalindicesFVarIds:j'idsfvarId:h'idnumEqs: number of equations in the target
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- inductiveVal : Lean.InductiveVal
- casesOnVal : Lean.DefinitionVal
- nminors : Nat
- majorDecl : Lean.LocalDecl
- majorTypeFn : Lean.Expr
partial def
Lean.Meta.Cases.unifyEqs?
(numEqs : Nat)
(mvarId : Lean.MVarId)
(subst : Lean.Meta.FVarSubst)
(caseName? : optParam (Option Lean.Name) none)
:
def
Lean.Meta.Cases.cases
(mvarId : Lean.MVarId)
(majorFVarId : Lean.FVarId)
(givenNames : optParam (Array Lean.Meta.AltVarNames) #[])
:
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def
Lean.Meta.cases
(mvarId : Lean.MVarId)
(majorFVarId : Lean.FVarId)
(givenNames : optParam (Array Lean.Meta.AltVarNames) #[])
:
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- Lean.Meta.cases mvarId majorFVarId givenNames = Lean.Meta.Cases.cases mvarId majorFVarId givenNames
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