Polish the chapter

introduction, computational complexity.
This commit is contained in:
krahets
2023-08-20 14:51:39 +08:00
parent 5fb728b3d6
commit 2626de8d0b
87 changed files with 375 additions and 371 deletions
@@ -140,33 +140,33 @@ enum TimeComplexity {
print("输入数据大小 n = \(n)")
var count = constant(n: n)
print("常数阶的计算操作数量 = \(count)")
print("常数阶的操作数量 = \(count)")
count = linear(n: n)
print("线性阶的计算操作数量 = \(count)")
print("线性阶的操作数量 = \(count)")
count = arrayTraversal(nums: Array(repeating: 0, count: n))
print("线性阶(遍历数组)的计算操作数量 = \(count)")
print("线性阶(遍历数组)的操作数量 = \(count)")
count = quadratic(n: n)
print("平方阶的计算操作数量 = \(count)")
print("平方阶的操作数量 = \(count)")
var nums = Array(stride(from: n, to: 0, by: -1)) // [n,n-1,...,2,1]
count = bubbleSort(nums: &nums)
print("平方阶(冒泡排序)的计算操作数量 = \(count)")
print("平方阶(冒泡排序)的操作数量 = \(count)")
count = exponential(n: n)
print("指数阶(循环实现)的计算操作数量 = \(count)")
print("指数阶(循环实现)的操作数量 = \(count)")
count = expRecur(n: n)
print("指数阶(递归实现)的计算操作数量 = \(count)")
print("指数阶(递归实现)的操作数量 = \(count)")
count = logarithmic(n: Double(n))
print("对数阶(循环实现)的计算操作数量 = \(count)")
print("对数阶(循环实现)的操作数量 = \(count)")
count = logRecur(n: Double(n))
print("对数阶(递归实现)的计算操作数量 = \(count)")
print("对数阶(递归实现)的操作数量 = \(count)")
count = linearLogRecur(n: Double(n))
print("线性对数阶(递归实现)的计算操作数量 = \(count)")
print("线性对数阶(递归实现)的操作数量 = \(count)")
count = factorialRecur(n: n)
print("阶乘阶(递归实现)的计算操作数量 = \(count)")
print("阶乘阶(递归实现)的操作数量 = \(count)")
}
}
+2 -2
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@@ -69,7 +69,7 @@ class MaxHeap {
while true {
// i
let p = parent(i: i)
//
//
if p < 0 || maxHeap[i] <= maxHeap[p] {
break
}
@@ -110,7 +110,7 @@ class MaxHeap {
if r < size(), maxHeap[r] > maxHeap[ma] {
ma = r
}
// i l, r
// i l, r
if ma == i {
break
}
+1 -1
View File
@@ -18,7 +18,7 @@ func siftDown(nums: inout [Int], n: Int, i: Int) {
if r < n, nums[r] > nums[ma] {
ma = r
}
// i l, r
// i l, r
if ma == i {
break
}
+1 -1
View File
@@ -84,7 +84,7 @@ class AVLTree {
return leftRotate(node: node)
}
}
//
//
return node
}