inductive Std.BinomialHeap.Imp.HeapNode (α : Type u) : Type u

A HeapNode is one of the internal nodes of the binomial heap. It is always a perfect binary tree, with the depth of the tree stored in the Heap. However the interpretation of the two pointers is different: we view the child as going to the first child of this node, and sibling goes to the next sibling of this tree. So it actually encodes a forest where each node has children node.child, node.child.sibling, node.child.sibling.sibling, etc.

Each edge in this forest denotes a le a b relation that has been checked, so the root is smaller than everything else under it.

• nil: {α : Type u} → Std.BinomialHeap.Imp.HeapNode α

  An empty forest, which has depth 0.

• node: {α : Type u} → α → Std.BinomialHeap.Imp.HeapNode α → Std.BinomialHeap.Imp.HeapNode α → Std.BinomialHeap.Imp.HeapNode α

  A forest of rank r + 1 consists of a root a, a forest child of rank r elements greater than a, and another forest sibling of rank r.

instance Std.BinomialHeap.Imp.instReprHeapNode : {α : Type u_1} → [inst : Repr α] → Repr (Std.BinomialHeap.Imp.HeapNode α)

Equations

• Std.BinomialHeap.Imp.instReprHeapNode = { reprPrec := Std.BinomialHeap.Imp.reprHeapNode✝ }

def Std.BinomialHeap.Imp.HeapNode.realSize {α : Type u_1} : Std.BinomialHeap.Imp.HeapNode α → Nat

The "real size" of the node, counting up how many values of type α are stored. This is O(n) and is intended mainly for specification purposes. For a well formed HeapNode the size is always 2^n - 1 where n is the depth.

Equations

• Std.BinomialHeap.Imp.HeapNode.realSize Std.BinomialHeap.Imp.HeapNode.nil = 0
• Std.BinomialHeap.Imp.HeapNode.realSize (Std.BinomialHeap.Imp.HeapNode.node a a_1 a_2) = Std.BinomialHeap.Imp.HeapNode.realSize a_1 + 1 + Std.BinomialHeap.Imp.HeapNode.realSize a_2

def Std.BinomialHeap.Imp.HeapNode.singleton {α : Type u_1} (a : α) : Std.BinomialHeap.Imp.HeapNode α

A node containing a single element a.

Equations

• Std.BinomialHeap.Imp.HeapNode.singleton a = Std.BinomialHeap.Imp.HeapNode.node a Std.BinomialHeap.Imp.HeapNode.nil Std.BinomialHeap.Imp.HeapNode.nil

def Std.BinomialHeap.Imp.HeapNode.rank {α : Type u_1} : Std.BinomialHeap.Imp.HeapNode α → Nat

O(log n). The rank, or the number of trees in the forest. It is also the depth of the forest.

Equations

• Std.BinomialHeap.Imp.HeapNode.rank Std.BinomialHeap.Imp.HeapNode.nil = 0
• Std.BinomialHeap.Imp.HeapNode.rank (Std.BinomialHeap.Imp.HeapNode.node a a_1 a_2) = Std.BinomialHeap.Imp.HeapNode.rank a_2 + 1

inductive Std.BinomialHeap.Imp.Heap (α : Type u) : Type u

A Heap is the top level structure in a binomial heap. It consists of a forest of HeapNodes with strictly increasing ranks.

• nil: {α : Type u} → Std.BinomialHeap.Imp.Heap α

  An empty heap.

• cons: {α : Type u} → Nat → α → Std.BinomialHeap.Imp.HeapNode α → Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α

  A cons node contains a tree of root val, children node and rank rank, and then next which is the rest of the forest.

instance Std.BinomialHeap.Imp.instReprHeap : {α : Type u_1} → [inst : Repr α] → Repr (Std.BinomialHeap.Imp.Heap α)

Equations

• Std.BinomialHeap.Imp.instReprHeap = { reprPrec := Std.BinomialHeap.Imp.reprHeap✝ }

def Std.BinomialHeap.Imp.Heap.realSize {α : Type u_1} : Std.BinomialHeap.Imp.Heap α → Nat

O(n). The "real size" of the heap, counting up how many values of type α are stored. This is intended mainly for specification purposes. Prefer Heap.size, which is the same for well formed heaps.

Equations

• Std.BinomialHeap.Imp.Heap.realSize Std.BinomialHeap.Imp.Heap.nil = 0
• Std.BinomialHeap.Imp.Heap.realSize (Std.BinomialHeap.Imp.Heap.cons a a_1 a_2 a_3) = Std.BinomialHeap.Imp.HeapNode.realSize a_2 + 1 + Std.BinomialHeap.Imp.Heap.realSize a_3

def Std.BinomialHeap.Imp.Heap.size {α : Type u_1} : Std.BinomialHeap.Imp.Heap α → Nat

O(log n). The number of elements in the heap.

Equations

• Std.BinomialHeap.Imp.Heap.size Std.BinomialHeap.Imp.Heap.nil = 0
• Std.BinomialHeap.Imp.Heap.size (Std.BinomialHeap.Imp.Heap.cons a a_1 a_2 a_3) = 1 <<< a + Std.BinomialHeap.Imp.Heap.size a_3

@[inline]

def Std.BinomialHeap.Imp.Heap.isEmpty {α : Type u_1} : Std.BinomialHeap.Imp.Heap α → Bool

O(1). Is the heap empty?

Equations

• Std.BinomialHeap.Imp.Heap.isEmpty x = match x with | Std.BinomialHeap.Imp.Heap.nil => true | x => false

@[inline]

def Std.BinomialHeap.Imp.Heap.singleton {α : Type u_1} (a : α) : Std.BinomialHeap.Imp.Heap α

O(1). The heap containing a single value a.

Equations

• Std.BinomialHeap.Imp.Heap.singleton a = Std.BinomialHeap.Imp.Heap.cons 0 a Std.BinomialHeap.Imp.HeapNode.nil Std.BinomialHeap.Imp.Heap.nil

def Std.BinomialHeap.Imp.Heap.rankGT {α : Type u_1} : Std.BinomialHeap.Imp.Heap α → Nat → Prop

O(1). Auxiliary for Heap.merge: Is the minimum rank in Heap strictly larger than n?

Equations

• Std.BinomialHeap.Imp.Heap.rankGT x✝ x = match x✝, x with | Std.BinomialHeap.Imp.Heap.nil, x => True | Std.BinomialHeap.Imp.Heap.cons r val node next, n => n < r

instance Std.BinomialHeap.Imp.instDecidableRankGT : {α : Type u_1} → {s : Std.BinomialHeap.Imp.Heap α} → {n : Nat} → Decidable (Std.BinomialHeap.Imp.Heap.rankGT s n)

Equations

• One or more equations did not get rendered due to their size.

def Std.BinomialHeap.Imp.Heap.length {α : Type u_1} : Std.BinomialHeap.Imp.Heap α → Nat

O(log n). The number of trees in the forest.

Equations

• Std.BinomialHeap.Imp.Heap.length Std.BinomialHeap.Imp.Heap.nil = 0
• Std.BinomialHeap.Imp.Heap.length (Std.BinomialHeap.Imp.Heap.cons a a_1 a_2 a_3) = Std.BinomialHeap.Imp.Heap.length a_3 + 1

@[inline]

def Std.BinomialHeap.Imp.combine {α : Type u_1} (le : α → α → Bool) (a₁ : α) (a₂ : α) (n₁ : Std.BinomialHeap.Imp.HeapNode α) (n₂ : Std.BinomialHeap.Imp.HeapNode α) : α × Std.BinomialHeap.Imp.HeapNode α

O(1). Auxiliary for Heap.merge: combines two heap nodes of the same rank into one with the next larger rank.

Equations

• Std.BinomialHeap.Imp.combine le a₁ a₂ n₁ n₂ = if le a₁ a₂ = true then (a₁, Std.BinomialHeap.Imp.HeapNode.node a₂ n₂ n₁) else (a₂, Std.BinomialHeap.Imp.HeapNode.node a₁ n₁ n₂)

@[specialize #[]]

def Std.BinomialHeap.Imp.Heap.merge {α : Type u_1} (le : α → α → Bool) : Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α

Merge two forests of binomial trees. The forests are assumed to be ordered by rank and merge maintains this invariant.

Equations

• One or more equations did not get rendered due to their size.
• Std.BinomialHeap.Imp.Heap.merge le Std.BinomialHeap.Imp.Heap.nil x = x
• Std.BinomialHeap.Imp.Heap.merge le x Std.BinomialHeap.Imp.Heap.nil = x

def Std.BinomialHeap.Imp.HeapNode.toHeap {α : Type u_1} (s : Std.BinomialHeap.Imp.HeapNode α) : Std.BinomialHeap.Imp.Heap α

O(log n). Convert a HeapNode to a Heap by reversing the order of the nodes along the sibling spine.

Equations

• Std.BinomialHeap.Imp.HeapNode.toHeap s = Std.BinomialHeap.Imp.HeapNode.toHeap.go s (Std.BinomialHeap.Imp.HeapNode.rank s) Std.BinomialHeap.Imp.Heap.nil

def Std.BinomialHeap.Imp.HeapNode.toHeap.go {α : Type u_1} : Std.BinomialHeap.Imp.HeapNode α → Nat → Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α

Computes s.toHeap ++ res tail-recursively, assuming n = s.rank.

Equations

• Std.BinomialHeap.Imp.HeapNode.toHeap.go Std.BinomialHeap.Imp.HeapNode.nil x✝ x = x
• Std.BinomialHeap.Imp.HeapNode.toHeap.go (Std.BinomialHeap.Imp.HeapNode.node a c s) x✝ x = Std.BinomialHeap.Imp.HeapNode.toHeap.go s (x✝ - 1) (Std.BinomialHeap.Imp.Heap.cons (x✝ - 1) a c x)

@[specialize #[]]

def Std.BinomialHeap.Imp.Heap.headD {α : Type u_1} (le : α → α → Bool) (a : α) : Std.BinomialHeap.Imp.Heap α → α

O(log n). Get the smallest element in the heap, including the passed in value a.

Equations

• Std.BinomialHeap.Imp.Heap.headD le a Std.BinomialHeap.Imp.Heap.nil = a
• Std.BinomialHeap.Imp.Heap.headD le a (Std.BinomialHeap.Imp.Heap.cons a_1 a_2 a_3 a_4) = Std.BinomialHeap.Imp.Heap.headD le (if le a a_2 = true then a else a_2) a_4

@[inline]

def Std.BinomialHeap.Imp.Heap.head? {α : Type u_1} (le : α → α → Bool) : Std.BinomialHeap.Imp.Heap α → Option α

O(log n). Get the smallest element in the heap, if it has an element.

Equations

• One or more equations did not get rendered due to their size.

structure Std.BinomialHeap.Imp.FindMin (α : Type u_1) : Type u_1

The return type of FindMin, which encodes various quantities needed to reconstruct the tree in deleteMin.

• before : Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α

  The list of elements prior to the minimum element, encoded as a "difference list".

• val : α

  The minimum element.

• node : Std.BinomialHeap.Imp.HeapNode α

  The children of the minimum element.

• next : Std.BinomialHeap.Imp.Heap α

  The forest after the minimum element.

@[specialize #[]]

def Std.BinomialHeap.Imp.Heap.findMin {α : Type u_1} (le : α → α → Bool) (k : Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α) : Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.FindMin α → Std.BinomialHeap.Imp.FindMin α

O(log n). Find the minimum element, and return a data structure FindMin with information needed to reconstruct the rest of the binomial heap.

Equations

• One or more equations did not get rendered due to their size.
• Std.BinomialHeap.Imp.Heap.findMin le k Std.BinomialHeap.Imp.Heap.nil x = x

def Std.BinomialHeap.Imp.Heap.deleteMin {α : Type u_1} (le : α → α → Bool) : Std.BinomialHeap.Imp.Heap α → Option (α × Std.BinomialHeap.Imp.Heap α)

O(log n). Find and remove the the minimum element from the binomial heap.

Equations

• One or more equations did not get rendered due to their size.

@[inline]

def Std.BinomialHeap.Imp.Heap.tail? {α : Type u_1} (le : α → α → Bool) (h : Std.BinomialHeap.Imp.Heap α) : Option (Std.BinomialHeap.Imp.Heap α)

O(log n). Get the tail of the binomial heap after removing the minimum element.

Equations

• Std.BinomialHeap.Imp.Heap.tail? le h = Option.map (fun (x : α × Std.BinomialHeap.Imp.Heap α) => x.snd) (Std.BinomialHeap.Imp.Heap.deleteMin le h)

@[inline]

def Std.BinomialHeap.Imp.Heap.tail {α : Type u_1} (le : α → α → Bool) (h : Std.BinomialHeap.Imp.Heap α) : Std.BinomialHeap.Imp.Heap α

O(log n). Remove the minimum element of the heap.

Equations

• Std.BinomialHeap.Imp.Heap.tail le h = Option.getD (Std.BinomialHeap.Imp.Heap.tail? le h) Std.BinomialHeap.Imp.Heap.nil

theorem Std.BinomialHeap.Imp.Heap.realSize_merge {α : Type u_1} (le : α → α → Bool) (s₁ : Std.BinomialHeap.Imp.Heap α) (s₂ : Std.BinomialHeap.Imp.Heap α) : Std.BinomialHeap.Imp.Heap.realSize (Std.BinomialHeap.Imp.Heap.merge le s₁ s₂) = Std.BinomialHeap.Imp.Heap.realSize s₁ + Std.BinomialHeap.Imp.Heap.realSize s₂

theorem Std.BinomialHeap.Imp.HeapNode.realSize_toHeap {α : Type u_1} (s : Std.BinomialHeap.Imp.HeapNode α) : Std.BinomialHeap.Imp.Heap.realSize (Std.BinomialHeap.Imp.HeapNode.toHeap s) = Std.BinomialHeap.Imp.HeapNode.realSize s

theorem Std.BinomialHeap.Imp.HeapNode.realSize_toHeap.go {α : Type u_1} {n : Nat} {res : Std.BinomialHeap.Imp.Heap α} (s : Std.BinomialHeap.Imp.HeapNode α) : Std.BinomialHeap.Imp.Heap.realSize (Std.BinomialHeap.Imp.HeapNode.toHeap.go s n res) = Std.BinomialHeap.Imp.HeapNode.realSize s + Std.BinomialHeap.Imp.Heap.realSize res

theorem Std.BinomialHeap.Imp.Heap.realSize_deleteMin {α : Type u_1} {le : α → α → Bool} {a : α} {s' : Std.BinomialHeap.Imp.Heap α} {s : Std.BinomialHeap.Imp.Heap α} (eq : Std.BinomialHeap.Imp.Heap.deleteMin le s = some (a, s')) : Std.BinomialHeap.Imp.Heap.realSize s = Std.BinomialHeap.Imp.Heap.realSize s' + 1

theorem Std.BinomialHeap.Imp.Heap.realSize_tail? {α : Type u_1} {le : α → α → Bool} {s' : Std.BinomialHeap.Imp.Heap α} {s : Std.BinomialHeap.Imp.Heap α} : Std.BinomialHeap.Imp.Heap.tail? le s = some s' → Std.BinomialHeap.Imp.Heap.realSize s = Std.BinomialHeap.Imp.Heap.realSize s' + 1

theorem Std.BinomialHeap.Imp.Heap.realSize_tail {α : Type u_1} (le : α → α → Bool) (s : Std.BinomialHeap.Imp.Heap α) : Std.BinomialHeap.Imp.Heap.realSize (Std.BinomialHeap.Imp.Heap.tail le s) = Std.BinomialHeap.Imp.Heap.realSize s - 1

@[specialize #[]]

def Std.BinomialHeap.Imp.Heap.foldM {m : Type u_1 → Type u_2} {α : Type u_3} {β : Type u_1} [Monad m] (le : α → α → Bool) (s : Std.BinomialHeap.Imp.Heap α) (init : β) (f : β → α → m β) : m β

O(n log n). Monadic fold over the elements of a heap in increasing order, by repeatedly pulling the minimum element out of the heap.

Equations

• One or more equations did not get rendered due to their size.

@[inline]

def Std.BinomialHeap.Imp.Heap.fold {α : Type u_1} {β : Type u_2} (le : α → α → Bool) (s : Std.BinomialHeap.Imp.Heap α) (init : β) (f : β → α → β) : β

O(n log n). Fold over the elements of a heap in increasing order, by repeatedly pulling the minimum element out of the heap.

Equations

• Std.BinomialHeap.Imp.Heap.fold le s init f = Id.run (Std.BinomialHeap.Imp.Heap.foldM le s init f)

@[inline]

def Std.BinomialHeap.Imp.Heap.toArray {α : Type u_1} (le : α → α → Bool) (s : Std.BinomialHeap.Imp.Heap α) : Array α

O(n log n). Convert the heap to an array in increasing order.

Equations

• Std.BinomialHeap.Imp.Heap.toArray le s = Std.BinomialHeap.Imp.Heap.fold le s #[] Array.push

@[inline]

def Std.BinomialHeap.Imp.Heap.toList {α : Type u_1} (le : α → α → Bool) (s : Std.BinomialHeap.Imp.Heap α) : List α

O(n log n). Convert the heap to a list in increasing order.

Equations

• Std.BinomialHeap.Imp.Heap.toList le s = Array.toList (Std.BinomialHeap.Imp.Heap.toArray le s)

@[specialize #[]]

def Std.BinomialHeap.Imp.HeapNode.foldTreeM {m : Type u_1 → Type u_2} {β : Type u_1} {α : Type u_3} [Monad m] (nil : β) (join : α → β → β → m β) : Std.BinomialHeap.Imp.HeapNode α → m β

O(n). Fold a monadic function over the tree structure to accumulate a value.

Equations

• One or more equations did not get rendered due to their size.
• Std.BinomialHeap.Imp.HeapNode.foldTreeM nil join Std.BinomialHeap.Imp.HeapNode.nil = pure nil

@[specialize #[]]

def Std.BinomialHeap.Imp.Heap.foldTreeM {m : Type u_1 → Type u_2} {β : Type u_1} {α : Type u_3} [Monad m] (nil : β) (join : α → β → β → m β) : Std.BinomialHeap.Imp.Heap α → m β

O(n). Fold a monadic function over the tree structure to accumulate a value.

Equations

• One or more equations did not get rendered due to their size.
• Std.BinomialHeap.Imp.Heap.foldTreeM nil join Std.BinomialHeap.Imp.Heap.nil = pure nil

@[inline]

def Std.BinomialHeap.Imp.Heap.foldTree {β : Type u_1} {α : Type u_2} (nil : β) (join : α → β → β → β) (s : Std.BinomialHeap.Imp.Heap α) : β

O(n). Fold a function over the tree structure to accumulate a value.

Equations

• Std.BinomialHeap.Imp.Heap.foldTree nil join s = Id.run (Std.BinomialHeap.Imp.Heap.foldTreeM nil join s)

def Std.BinomialHeap.Imp.Heap.toListUnordered {α : Type u_1} (s : Std.BinomialHeap.Imp.Heap α) : List α

O(n). Convert the heap to a list in arbitrary order.

Equations

• Std.BinomialHeap.Imp.Heap.toListUnordered s = Std.BinomialHeap.Imp.Heap.foldTree id (fun (a : α) (c s : List α → List α) (l : List α) => a :: c (s l)) s []

def Std.BinomialHeap.Imp.Heap.toArrayUnordered {α : Type u_1} (s : Std.BinomialHeap.Imp.Heap α) : Array α

O(n). Convert the heap to an array in arbitrary order.

Equations

• Std.BinomialHeap.Imp.Heap.toArrayUnordered s = Std.BinomialHeap.Imp.Heap.foldTree id (fun (a : α) (c s : Array α → Array α) (r : Array α) => s (c (Array.push r a))) s #[]

def Std.BinomialHeap.Imp.HeapNode.WF {α : Type u_1} (le : α → α → Bool) (a : α) : Std.BinomialHeap.Imp.HeapNode α → Nat → Prop

The well formedness predicate for a heap node. It asserts that:

• If a is added at the top to make the forest into a tree, the resulting tree is a le-min-heap (if le is well-behaved)
• When interpreting child and sibling as left and right children of a binary tree, it is a perfect binary tree with depth r

Equations

• One or more equations did not get rendered due to their size.
• Std.BinomialHeap.Imp.HeapNode.WF le a Std.BinomialHeap.Imp.HeapNode.nil x = (x = 0)

def Std.BinomialHeap.Imp.Heap.WF {α : Type u_1} (le : α → α → Bool) (n : Nat) : Std.BinomialHeap.Imp.Heap α → Prop

The well formedness predicate for a binomial heap. It asserts that:

• It consists of a list of well formed trees with the specified ranks
• The ranks are in strictly increasing order, and all are at least n

Equations

• Std.BinomialHeap.Imp.Heap.WF le n Std.BinomialHeap.Imp.Heap.nil = True
• Std.BinomialHeap.Imp.Heap.WF le n (Std.BinomialHeap.Imp.Heap.cons a a_1 a_2 a_3) = (n ≤ a ∧ Std.BinomialHeap.Imp.HeapNode.WF le a_1 a_2 a ∧ Std.BinomialHeap.Imp.Heap.WF le (a + 1) a_3)

theorem Std.BinomialHeap.Imp.Heap.WF.nil : ∀ {α : Type u_1} {le : α → α → Bool} {n : Nat}, Std.BinomialHeap.Imp.Heap.WF le n Std.BinomialHeap.Imp.Heap.nil

theorem Std.BinomialHeap.Imp.Heap.WF.singleton : ∀ {α : Type u_1} {a : α} {le : α → α → Bool}, Std.BinomialHeap.Imp.Heap.WF le 0 (Std.BinomialHeap.Imp.Heap.singleton a)

theorem Std.BinomialHeap.Imp.Heap.WF.of_rankGT : ∀ {α : Type u_1} {le : α → α → Bool} {n' : Nat} {s : Std.BinomialHeap.Imp.Heap α} {n : Nat}, Std.BinomialHeap.Imp.Heap.rankGT s n → Std.BinomialHeap.Imp.Heap.WF le n' s → Std.BinomialHeap.Imp.Heap.WF le (n + 1) s

theorem Std.BinomialHeap.Imp.Heap.WF.of_le {n : Nat} {n' : Nat} : ∀ {α : Type u_1} {le : α → α → Bool} {s : Std.BinomialHeap.Imp.Heap α}, n ≤ n' → Std.BinomialHeap.Imp.Heap.WF le n' s → Std.BinomialHeap.Imp.Heap.WF le n s

theorem Std.BinomialHeap.Imp.Heap.rankGT.of_le : ∀ {α : Type u_1} {s : Std.BinomialHeap.Imp.Heap α} {n n' : Nat}, Std.BinomialHeap.Imp.Heap.rankGT s n → n' ≤ n → Std.BinomialHeap.Imp.Heap.rankGT s n'

theorem Std.BinomialHeap.Imp.Heap.WF.rankGT : ∀ {α : Type u_1} {lt : α → α → Bool} {n : Nat} {s : Std.BinomialHeap.Imp.Heap α}, Std.BinomialHeap.Imp.Heap.WF lt (n + 1) s → Std.BinomialHeap.Imp.Heap.rankGT s n

theorem Std.BinomialHeap.Imp.Heap.WF.merge' : ∀ {α : Type u_1} {le : α → α → Bool} {s₁ s₂ : Std.BinomialHeap.Imp.Heap α} {n : Nat}, Std.BinomialHeap.Imp.Heap.WF le n s₁ → Std.BinomialHeap.Imp.Heap.WF le n s₂ → Std.BinomialHeap.Imp.Heap.WF le n (Std.BinomialHeap.Imp.Heap.merge le s₁ s₂) ∧ ((Std.BinomialHeap.Imp.Heap.rankGT s₁ n ↔ Std.BinomialHeap.Imp.Heap.rankGT s₂ n) → Std.BinomialHeap.Imp.Heap.rankGT (Std.BinomialHeap.Imp.Heap.merge le s₁ s₂) n)

theorem Std.BinomialHeap.Imp.Heap.WF.merge : ∀ {α : Type u_1} {le : α → α → Bool} {s₁ s₂ : Std.BinomialHeap.Imp.Heap α} {n : Nat}, Std.BinomialHeap.Imp.Heap.WF le n s₁ → Std.BinomialHeap.Imp.Heap.WF le n s₂ → Std.BinomialHeap.Imp.Heap.WF le n (Std.BinomialHeap.Imp.Heap.merge le s₁ s₂)

theorem Std.BinomialHeap.Imp.HeapNode.WF.rank_eq {α : Type u_1} {le : α → α → Bool} {a : α} {n : Nat} {s : Std.BinomialHeap.Imp.HeapNode α} : Std.BinomialHeap.Imp.HeapNode.WF le a s n → Std.BinomialHeap.Imp.HeapNode.rank s = n

theorem Std.BinomialHeap.Imp.HeapNode.WF.toHeap {α : Type u_1} {le : α → α → Bool} {a : α} {n : Nat} {s : Std.BinomialHeap.Imp.HeapNode α} (h : Std.BinomialHeap.Imp.HeapNode.WF le a s n) : Std.BinomialHeap.Imp.Heap.WF le 0 (Std.BinomialHeap.Imp.HeapNode.toHeap s)

theorem Std.BinomialHeap.Imp.HeapNode.WF.toHeap.go {α : Type u_1} {le : α → α → Bool} {a : α} {res : Std.BinomialHeap.Imp.Heap α} {n : Nat} {s : Std.BinomialHeap.Imp.HeapNode α} : Std.BinomialHeap.Imp.HeapNode.WF le a s n → Std.BinomialHeap.Imp.Heap.WF le (Std.BinomialHeap.Imp.HeapNode.rank s) res → Std.BinomialHeap.Imp.Heap.WF le 0 (Std.BinomialHeap.Imp.HeapNode.toHeap.go s (Std.BinomialHeap.Imp.HeapNode.rank s) res)

structure Std.BinomialHeap.Imp.FindMin.WF {α : Type u_1} (le : α → α → Bool) (res : Std.BinomialHeap.Imp.FindMin α) : Type

The well formedness predicate for a FindMin value. This is not actually a predicate, as it contains an additional data value rank corresponding to the rank of the returned node, which is omitted from findMin.

• rank : Nat

  The rank of the minimum element

• before : ∀ {s : Std.BinomialHeap.Imp.Heap α}, Std.BinomialHeap.Imp.Heap.WF le self.rank s → Std.BinomialHeap.Imp.Heap.WF le 0 (res.before s)

  before is a difference list which can be appended to a binomial heap with ranks at least rank to produce another well formed heap.

• node : Std.BinomialHeap.Imp.HeapNode.WF le res.val res.node self.rank

  node is a well formed forest of rank rank with val at the root.

• next : Std.BinomialHeap.Imp.Heap.WF le (self.rank + 1) res.next

  next is a binomial heap with ranks above rank + 1.

def Std.BinomialHeap.Imp.Heap.WF.findMin {α : Type u_1} {le : α → α → Bool} {n : Nat} {k : Std.BinomialHeap.Imp.Heap α → Std.BinomialHeap.Imp.Heap α} {res : Std.BinomialHeap.Imp.FindMin α} {s : Std.BinomialHeap.Imp.Heap α} (h : Std.BinomialHeap.Imp.Heap.WF le n s) (hr : Std.BinomialHeap.Imp.FindMin.WF le res) (hk : ∀ {s : Std.BinomialHeap.Imp.Heap α}, Std.BinomialHeap.Imp.Heap.WF le n s → Std.BinomialHeap.Imp.Heap.WF le 0 (k s)) : Std.BinomialHeap.Imp.FindMin.WF le (Std.BinomialHeap.Imp.Heap.findMin le k s res)

The conditions under which findMin is well-formed.

Equations

• One or more equations did not get rendered due to their size.
• Std.BinomialHeap.Imp.Heap.WF.findMin h_2 hr hk = hr

theorem Std.BinomialHeap.Imp.Heap.WF.deleteMin {α : Type u_1} {le : α → α → Bool} {n : Nat} {a : α} {s' : Std.BinomialHeap.Imp.Heap α} {s : Std.BinomialHeap.Imp.Heap α} (h : Std.BinomialHeap.Imp.Heap.WF le n s) (eq : Std.BinomialHeap.Imp.Heap.deleteMin le s = some (a, s')) : Std.BinomialHeap.Imp.Heap.WF le 0 s'

theorem Std.BinomialHeap.Imp.Heap.WF.tail? {α : Type u_1} {s : Std.BinomialHeap.Imp.Heap α} {le : α → α → Bool} {n : Nat} {tl : Std.BinomialHeap.Imp.Heap α} (hwf : Std.BinomialHeap.Imp.Heap.WF le n s) : Std.BinomialHeap.Imp.Heap.tail? le s = some tl → Std.BinomialHeap.Imp.Heap.WF le 0 tl

theorem Std.BinomialHeap.Imp.Heap.WF.tail {α : Type u_1} {s : Std.BinomialHeap.Imp.Heap α} {le : α → α → Bool} {n : Nat} (hwf : Std.BinomialHeap.Imp.Heap.WF le n s) : Std.BinomialHeap.Imp.Heap.WF le 0 (Std.BinomialHeap.Imp.Heap.tail le s)

def Std.BinomialHeap (α : Type u) (le : α → α → Bool) : Type u

A binomial heap is a data structure which supports the following primary operations:

• insert : α → BinomialHeap α → BinomialHeap α: add an element to the heap
• deleteMin : BinomialHeap α → Option (α × BinomialHeap α): remove the minimum element from the heap
• merge : BinomialHeap α → BinomialHeap α → BinomialHeap α: combine two heaps

The first two operations are known as a "priority queue", so this could be called a "mergeable priority queue". The standard choice for a priority queue is a binary heap, which supports insert and deleteMin in O(log n), but merge is O(n). With a BinomialHeap, all three operations are O(log n).

Equations

• Std.BinomialHeap α le = { h : Std.BinomialHeap.Imp.Heap α // Std.BinomialHeap.Imp.Heap.WF le 0 h }

@[inline]

def Std.mkBinomialHeap (α : Type u) (le : α → α → Bool) : Std.BinomialHeap α le

O(1). Make a new empty binomial heap.

Equations

• Std.mkBinomialHeap α le = { val := Std.BinomialHeap.Imp.Heap.nil, property := ⋯ }

@[inline]

def Std.BinomialHeap.empty {α : Type u} {le : α → α → Bool} : Std.BinomialHeap α le

O(1). Make a new empty binomial heap.

Equations

• Std.BinomialHeap.empty = Std.mkBinomialHeap α le

instance Std.BinomialHeap.instEmptyCollectionBinomialHeap {α : Type u} {le : α → α → Bool} : EmptyCollection (Std.BinomialHeap α le)

Equations

• Std.BinomialHeap.instEmptyCollectionBinomialHeap = { emptyCollection := Std.BinomialHeap.empty }

instance Std.BinomialHeap.instInhabitedBinomialHeap {α : Type u} {le : α → α → Bool} : Inhabited (Std.BinomialHeap α le)

Equations

• Std.BinomialHeap.instInhabitedBinomialHeap = { default := Std.BinomialHeap.empty }

@[inline]

def Std.BinomialHeap.isEmpty {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Bool

O(1). Is the heap empty?

Equations

• Std.BinomialHeap.isEmpty b = Std.BinomialHeap.Imp.Heap.isEmpty b.val

@[inline]

def Std.BinomialHeap.size {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Nat

O(log n). The number of elements in the heap.

Equations

• Std.BinomialHeap.size b = Std.BinomialHeap.Imp.Heap.size b.val

@[inline]

def Std.BinomialHeap.singleton {α : Type u} {le : α → α → Bool} (a : α) : Std.BinomialHeap α le

O(1). Make a new heap containing a.

Equations

• Std.BinomialHeap.singleton a = { val := Std.BinomialHeap.Imp.Heap.singleton a, property := ⋯ }

@[inline]

def Std.BinomialHeap.merge {α : Type u} {le : α → α → Bool} : Std.BinomialHeap α le → Std.BinomialHeap α le → Std.BinomialHeap α le

O(log n). Merge the contents of two heaps.

Equations

• Std.BinomialHeap.merge x✝ x = match x✝, x with | { val := b₁, property := h₁ }, { val := b₂, property := h₂ } => { val := Std.BinomialHeap.Imp.Heap.merge le b₁ b₂, property := ⋯ }

@[inline]

def Std.BinomialHeap.insert {α : Type u} {le : α → α → Bool} (a : α) (h : Std.BinomialHeap α le) : Std.BinomialHeap α le

O(log n). Add element a to the given heap h.

Equations

• Std.BinomialHeap.insert a h = Std.BinomialHeap.merge (Std.BinomialHeap.singleton a) h

def Std.BinomialHeap.ofList {α : Type u} (le : α → α → Bool) (as : List α) : Std.BinomialHeap α le

O(n log n). Construct a heap from a list by inserting all the elements.

Equations

• Std.BinomialHeap.ofList le as = List.foldl (flip Std.BinomialHeap.insert) Std.BinomialHeap.empty as

def Std.BinomialHeap.ofArray {α : Type u} (le : α → α → Bool) (as : Array α) : Std.BinomialHeap α le

O(n log n). Construct a heap from a list by inserting all the elements.

Equations

• Std.BinomialHeap.ofArray le as = Array.foldl (flip Std.BinomialHeap.insert) Std.BinomialHeap.empty as 0

@[inline]

def Std.BinomialHeap.deleteMin {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Option (α × Std.BinomialHeap α le)

O(log n). Remove and return the minimum element from the heap.

Equations

• Std.BinomialHeap.deleteMin b = match eq : Std.BinomialHeap.Imp.Heap.deleteMin le b.val with | none => none | some (a, tl) => some (a, { val := tl, property := ⋯ })

instance Std.BinomialHeap.instStreamBinomialHeap {α : Type u} {le : α → α → Bool} : Stream (Std.BinomialHeap α le) α

Equations

• Std.BinomialHeap.instStreamBinomialHeap = { next? := Std.BinomialHeap.deleteMin }

def Std.BinomialHeap.forIn {α : Type u} {le : α → α → Bool} {m : Type u_1 → Type u_2} {β : Type u_1} [Monad m] (b : Std.BinomialHeap α le) (x : β) (f : α → β → m (ForInStep β)) : m β

O(n log n). Implementation of for x in (b : BinomialHeap α le) ... notation, which iterates over the elements in the heap in increasing order.

Equations

• Std.BinomialHeap.forIn b x f = ForInStep.run <$> Std.BinomialHeap.Imp.Heap.foldM le b.val (ForInStep.yield x) fun (x : ForInStep β) (a : α) => ForInStep.bind x (f a)

instance Std.BinomialHeap.instForInBinomialHeap {α : Type u} {le : α → α → Bool} {m : Type u_1 → Type u_2} : ForIn m (Std.BinomialHeap α le) α

Equations

• Std.BinomialHeap.instForInBinomialHeap = { forIn := fun {β : Type u_1} [Monad m] => Std.BinomialHeap.forIn }

@[inline]

def Std.BinomialHeap.head? {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Option α

O(log n). Returns the smallest element in the heap, or none if the heap is empty.

Equations

• Std.BinomialHeap.head? b = Std.BinomialHeap.Imp.Heap.head? le b.val

@[inline]

def Std.BinomialHeap.head! {α : Type u} {le : α → α → Bool} [Inhabited α] (b : Std.BinomialHeap α le) : α

O(log n). Returns the smallest element in the heap, or panics if the heap is empty.

Equations

• Std.BinomialHeap.head! b = Option.get! (Std.BinomialHeap.head? b)

@[inline]

def Std.BinomialHeap.headI {α : Type u} {le : α → α → Bool} [Inhabited α] (b : Std.BinomialHeap α le) : α

O(log n). Returns the smallest element in the heap, or default if the heap is empty.

Equations

• Std.BinomialHeap.headI b = Option.getD (Std.BinomialHeap.head? b) default

@[inline]

def Std.BinomialHeap.tail? {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Option (Std.BinomialHeap α le)

O(log n). Removes the smallest element from the heap, or none if the heap is empty.

Equations

• Std.BinomialHeap.tail? b = match eq : Std.BinomialHeap.Imp.Heap.tail? le b.val with | none => none | some tl => some { val := tl, property := ⋯ }

@[inline]

def Std.BinomialHeap.tail {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Std.BinomialHeap α le

O(log n). Removes the smallest element from the heap, if possible.

Equations

• Std.BinomialHeap.tail b = { val := Std.BinomialHeap.Imp.Heap.tail le b.val, property := ⋯ }

@[inline]

def Std.BinomialHeap.foldM {α : Type u} {le : α → α → Bool} {m : Type u_1 → Type u_2} {β : Type u_1} [Monad m] (b : Std.BinomialHeap α le) (init : β) (f : β → α → m β) : m β

O(n log n). Monadic fold over the elements of a heap in increasing order, by repeatedly pulling the minimum element out of the heap.

Equations

• Std.BinomialHeap.foldM b init f = Std.BinomialHeap.Imp.Heap.foldM le b.val init f

@[inline]

def Std.BinomialHeap.fold {α : Type u} {le : α → α → Bool} {β : Type u_1} (b : Std.BinomialHeap α le) (init : β) (f : β → α → β) : β

O(n log n). Fold over the elements of a heap in increasing order, by repeatedly pulling the minimum element out of the heap.

Equations

• Std.BinomialHeap.fold b init f = Std.BinomialHeap.Imp.Heap.fold le b.val init f

@[inline]

def Std.BinomialHeap.toList {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : List α

O(n log n). Convert the heap to a list in increasing order.

Equations

• Std.BinomialHeap.toList b = Std.BinomialHeap.Imp.Heap.toList le b.val

@[inline]

def Std.BinomialHeap.toArray {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Array α

O(n log n). Convert the heap to an array in increasing order.

Equations

• Std.BinomialHeap.toArray b = Std.BinomialHeap.Imp.Heap.toArray le b.val

@[inline]

def Std.BinomialHeap.toListUnordered {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : List α

O(n). Convert the heap to a list in arbitrary order.

Equations

• Std.BinomialHeap.toListUnordered b = Std.BinomialHeap.Imp.Heap.toListUnordered b.val

@[inline]

def Std.BinomialHeap.toArrayUnordered {α : Type u} {le : α → α → Bool} (b : Std.BinomialHeap α le) : Array α

O(n). Convert the heap to an array in arbitrary order.

Equations

• Std.BinomialHeap.toArrayUnordered b = Std.BinomialHeap.Imp.Heap.toArrayUnordered b.val