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fix: Use int instead of float for the example code of log time complexity (#1164)

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* Use int instead of float for the example code of log time complexity

* Bug fixes

* Bug fixes
pull/1170/head
Yudong Jin 8 months ago committed by GitHub
parent fc8473ccfe
commit 3ea91bda99
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
12 changed files with 69 additions and 69 deletions
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6
codes/c/chapter_computational_complexity/time_complexity.c
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@ -90,7 +90,7 @@ int expRecur(int n) {
}
/* 对数阶（循环实现） */
int logarithmic(float n) {
int logarithmic(int n) {
int count = 0;
while (n > 1) {
n = n / 2;
@ -100,14 +100,14 @@ int logarithmic(float n) {
}
/* 对数阶（递归实现） */
int logRecur(float n) {
int logRecur(int n) {
if (n <= 1)
return 0;
return logRecur(n / 2) + 1;
}
/* 线性对数阶 */
int linearLogRecur(float n) {
int linearLogRecur(int n) {
if (n <= 1)
return 1;
int count = linearLogRecur(n / 2) + linearLogRecur(n / 2);

12
codes/cpp/chapter_computational_complexity/time_complexity.cpp
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@ -86,7 +86,7 @@ int expRecur(int n) {
}
/* 对数阶（循环实现） */
int logarithmic(float n) {
int logarithmic(int n) {
int count = 0;
while (n > 1) {
n = n / 2;
@ -96,14 +96,14 @@ int logarithmic(float n) {
}
/* 对数阶（递归实现） */
int logRecur(float n) {
int logRecur(int n) {
if (n <= 1)
return 0;
return logRecur(n / 2) + 1;
}
/* 线性对数阶 */
int linearLogRecur(float n) {
int linearLogRecur(int n) {
if (n <= 1)
return 1;
int count = linearLogRecur(n / 2) + linearLogRecur(n / 2);
@ -153,12 +153,12 @@ int main() {
count = expRecur(n);
cout << "指数阶（递归实现）的操作数量 = " << count << endl;
count = logarithmic((float)n);
count = logarithmic(n);
cout << "对数阶（循环实现）的操作数量 = " << count << endl;
count = logRecur((float)n);
count = logRecur(n);
cout << "对数阶（递归实现）的操作数量 = " << count << endl;
count = linearLogRecur((float)n);
count = linearLogRecur(n);
cout << "线性对数阶（递归实现）的操作数量 = " << count << endl;
count = factorialRecur(n);

14
codes/csharp/chapter_computational_complexity/time_complexity.cs
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@ -10,7 +10,7 @@ public class time_complexity {
void Algorithm(int n) {
int a = 1; // +0（技巧 1）
a += n; // +0（技巧 1）
// +n（技巧 2）
// +n（技巧 2）
for (int i = 0; i < 5 * n + 1; i++) {
Console.WriteLine(0);
}
@ -118,7 +118,7 @@ public class time_complexity {
}
/* 对数阶（循环实现） */
int Logarithmic(float n) {
int Logarithmic(int n) {
int count = 0;
while (n > 1) {
n /= 2;
@ -128,13 +128,13 @@ public class time_complexity {
}
/* 对数阶（递归实现） */
int LogRecur(float n) {
int LogRecur(int n) {
if (n <= 1) return 0;
return LogRecur(n / 2) + 1;
}
/* 线性对数阶 */
int LinearLogRecur(float n) {
int LinearLogRecur(int n) {
if (n <= 1) return 1;
int count = LinearLogRecur(n / 2) + LinearLogRecur(n / 2);
for (int i = 0; i < n; i++) {
@ -181,12 +181,12 @@ public class time_complexity {
count = ExpRecur(n);
Console.WriteLine("指数阶（递归实现）的操作数量 = " + count);
count = Logarithmic((float)n);
count = Logarithmic(n);
Console.WriteLine("对数阶（循环实现）的操作数量 = " + count);
count = LogRecur((float)n);
count = LogRecur(n);
Console.WriteLine("对数阶（递归实现）的操作数量 = " + count);
count = LinearLogRecur((float)n);
count = LinearLogRecur(n);
Console.WriteLine("线性对数阶（递归实现）的操作数量 = " + count);
count = FactorialRecur(n);

12
codes/dart/chapter_computational_complexity/time_complexity.dart
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@ -87,25 +87,25 @@ int expRecur(int n) {
}
/* 对数阶（循环实现） */
int logarithmic(num n) {
int logarithmic(int n) {
int count = 0;
while (n > 1) {
n = n / 2;
n = n ~/ 2;
count++;
}
return count;
}
/* 对数阶（递归实现） */
int logRecur(num n) {
int logRecur(int n) {
if (n <= 1) return 0;
return logRecur(n / 2) + 1;
return logRecur(n ~/ 2) + 1;
}
/* 线性对数阶 */
int linearLogRecur(num n) {
int linearLogRecur(int n) {
if (n <= 1) return 1;
int count = linearLogRecur(n / 2) + linearLogRecur(n / 2);
int count = linearLogRecur(n ~/ 2) + linearLogRecur(n ~/ 2);
for (var i = 0; i < n; i++) {
count++;
}

8
codes/go/chapter_computational_complexity/time_complexity.go
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@ -87,7 +87,7 @@ func expRecur(n int) int {
}
/* 对数阶（循环实现）*/
func logarithmic(n float64) int {
func logarithmic(n int) int {
count := 0
for n > 1 {
n = n / 2
@ -97,7 +97,7 @@ func logarithmic(n float64) int {
}
/* 对数阶（递归实现）*/
func logRecur(n float64) int {
func logRecur(n int) int {
if n <= 1 {
return 0
}
@ -105,12 +105,12 @@ func logRecur(n float64) int {
}
/* 线性对数阶 */
func linearLogRecur(n float64) int {
func linearLogRecur(n int) int {
if n <= 1 {
return 1
}
count := linearLogRecur(n/2) + linearLogRecur(n/2)
for i := 0.0; i < n; i++ {
for i := 0; i < n; i++ {
count++
}
return count

6
codes/go/chapter_computational_complexity/time_complexity_test.go
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@ -35,12 +35,12 @@ func TestTimeComplexity(t *testing.T) {
count = expRecur(n)
fmt.Println("指数阶（递归实现）的操作数量 =", count)
count = logarithmic(float64(n))
count = logarithmic(n)
fmt.Println("对数阶（循环实现）的操作数量 =", count)
count = logRecur(float64(n))
count = logRecur(n)
fmt.Println("对数阶（递归实现）的操作数量 =", count)
count = linearLogRecur(float64(n))
count = linearLogRecur(n)
fmt.Println("线性对数阶（递归实现）的操作数量 =", count)
count = factorialRecur(n)

12
codes/java/chapter_computational_complexity/time_complexity.java
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@ -87,7 +87,7 @@ public class time_complexity {
}
/* 对数阶（循环实现） */
static int logarithmic(float n) {
static int logarithmic(int n) {
int count = 0;
while (n > 1) {
n = n / 2;
@ -97,14 +97,14 @@ public class time_complexity {
}
/* 对数阶（递归实现） */
static int logRecur(float n) {
static int logRecur(int n) {
if (n <= 1)
return 0;
return logRecur(n / 2) + 1;
}
/* 线性对数阶 */
static int linearLogRecur(float n) {
static int linearLogRecur(int n) {
if (n <= 1)
return 1;
int count = linearLogRecur(n / 2) + linearLogRecur(n / 2);
@ -153,12 +153,12 @@ public class time_complexity {
count = expRecur(n);
System.out.println("指数阶（递归实现）的操作数量 = " + count);
count = logarithmic((float) n);
count = logarithmic(n);
System.out.println("对数阶（循环实现）的操作数量 = " + count);
count = logRecur((float) n);
count = logRecur(n);
System.out.println("对数阶（递归实现）的操作数量 = " + count);
count = linearLogRecur((float) n);
count = linearLogRecur(n);
System.out.println("线性对数阶（递归实现）的操作数量 = " + count);
count = factorialRecur(n);

12
codes/kotlin/chapter_computational_complexity/time_complexity.kt
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@ -87,7 +87,7 @@ fun expRecur(n: Int): Int {
}
/* 对数阶（循环实现） */
fun logarithmic(n: Float): Int {
fun logarithmic(n: Int): Int {
var n1 = n
var count = 0
while (n1 > 1) {
@ -98,14 +98,14 @@ fun logarithmic(n: Float): Int {
}
/* 对数阶（递归实现） */
fun logRecur(n: Float): Int {
fun logRecur(n: Int): Int {
if (n <= 1)
return 0
return logRecur(n / 2) + 1
}
/* 线性对数阶 */
fun linearLogRecur(n: Float): Int {
fun linearLogRecur(n: Int): Int {
if (n <= 1)
return 1
var count = linearLogRecur(n / 2) + linearLogRecur(n / 2)
@ -153,12 +153,12 @@ fun main() {
count = expRecur(n)
println("指数阶（递归实现）的操作数量 = $count")
count = logarithmic(n.toFloat())
count = logarithmic(n)
println("对数阶（循环实现）的操作数量 = $count")
count = logRecur(n.toFloat())
count = logRecur(n)
println("对数阶（递归实现）的操作数量 = $count")
count = linearLogRecur(n.toFloat())
count = linearLogRecur(n)
println("线性对数阶（递归实现）的操作数量 = $count")
count = factorialRecur(n)

6
codes/python/chapter_computational_complexity/time_complexity.py
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@ -77,7 +77,7 @@ def exp_recur(n: int) -> int:
return exp_recur(n - 1) + exp_recur(n - 1) + 1
def logarithmic(n: float) -> int:
def logarithmic(n: int) -> int:
"""对数阶（循环实现）"""
count = 0
while n > 1:
@ -86,14 +86,14 @@ def logarithmic(n: float) -> int:
return count
def log_recur(n: float) -> int:
def log_recur(n: int) -> int:
"""对数阶（递归实现）"""
if n <= 1:
return 0
return log_recur(n / 2) + 1
def linear_log_recur(n: float) -> int:
def linear_log_recur(n: int) -> int:
"""线性对数阶"""
if n <= 1:
return 1

24
codes/rust/chapter_computational_complexity/time_complexity.rs
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@ -90,29 +90,29 @@ fn exp_recur(n: i32) -> i32 {
}
/* 对数阶（循环实现） */
fn logarithmic(mut n: f32) -> i32 {
fn logarithmic(mut n: i32) -> i32 {
let mut count = 0;
while n > 1.0 {
n = n / 2.0;
while n > 1 {
n = n / 2;
count += 1;
}
count
}
/* 对数阶（递归实现） */
fn log_recur(n: f32) -> i32 {
if n <= 1.0 {
fn log_recur(n: i32) -> i32 {
if n <= 1 {
return 0;
}
log_recur(n / 2.0) + 1
log_recur(n / 2) + 1
}
/* 线性对数阶 */
fn linear_log_recur(n: f32) -> i32 {
if n <= 1.0 {
fn linear_log_recur(n: i32) -> i32 {
if n <= 1 {
return 1;
}
let mut count = linear_log_recur(n / 2.0) + linear_log_recur(n / 2.0);
let mut count = linear_log_recur(n / 2) + linear_log_recur(n / 2);
for _ in 0..n as i32 {
count += 1;
}
@ -157,12 +157,12 @@ fn main() {
count = exp_recur(n);
println!("指数阶（递归实现）的操作数量 = {}", count);
count = logarithmic(n as f32);
count = logarithmic(n);
println!("对数阶（循环实现）的操作数量 = {}", count);
count = log_recur(n as f32);
count = log_recur(n);
println!("对数阶（递归实现）的操作数量 = {}", count);
count = linear_log_recur(n as f32);
count = linear_log_recur(n);
println!("线性对数阶（递归实现）的操作数量 = {}", count);
count = factorial_recur(n);

12
codes/swift/chapter_computational_complexity/time_complexity.swift
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@ -88,7 +88,7 @@ func expRecur(n: Int) -> Int {
}
/* 对数阶（循环实现） */
func logarithmic(n: Double) -> Int {
func logarithmic(n: Int) -> Int {
var count = 0
var n = n
while n > 1 {
@ -99,7 +99,7 @@ func logarithmic(n: Double) -> Int {
}
/* 对数阶（递归实现） */
func logRecur(n: Double) -> Int {
func logRecur(n: Int) -> Int {
if n <= 1 {
return 0
}
@ -107,7 +107,7 @@ func logRecur(n: Double) -> Int {
}
/* 线性对数阶 */
func linearLogRecur(n: Double) -> Int {
func linearLogRecur(n: Int) -> Int {
if n <= 1 {
return 1
}
@ -158,12 +158,12 @@ enum TimeComplexity {
count = expRecur(n: n)
print("指数阶（递归实现）的操作数量 = \(count)")
count = logarithmic(n: Double(n))
count = logarithmic(n: n)
print("对数阶（循环实现）的操作数量 = \(count)")
count = logRecur(n: Double(n))
count = logRecur(n: n)
print("对数阶（递归实现）的操作数量 = \(count)")
count = linearLogRecur(n: Double(n))
count = linearLogRecur(n: n)
print("线性对数阶（递归实现）的操作数量 = \(count)")
count = factorialRecur(n: n)

14
codes/zig/chapter_computational_complexity/time_complexity.zig
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@ -95,7 +95,7 @@ fn expRecur(n: i32) i32 {
}
// 对数阶（循环实现）
fn logarithmic(n: f32) i32 {
fn logarithmic(n: i32) i32 {
var count: i32 = 0;
var n_var = n;
while (n_var > 1)
@ -107,16 +107,16 @@ fn logarithmic(n: f32) i32 {
}
// 对数阶（递归实现）
fn logRecur(n: f32) i32 {
fn logRecur(n: i32) i32 {
if (n <= 1) return 0;
return logRecur(n / 2) + 1;
}
// 线性对数阶
fn linearLogRecur(n: f32) i32 {
fn linearLogRecur(n: i32) i32 {
if (n <= 1) return 1;
var count: i32 = linearLogRecur(n / 2) + linearLogRecur(n / 2);
var i: f32 = 0;
var i: i32 = 0;
while (i < n) : (i += 1) {
count += 1;
}
@ -163,12 +163,12 @@ pub fn main() !void {
count = expRecur(n);
std.debug.print("指数阶（递归实现）的操作数量 = {}\n", .{count});
count = logarithmic(@as(f32, n));
count = logarithmic(n);
std.debug.print("对数阶（循环实现）的操作数量 = {}\n", .{count});
count = logRecur(@as(f32, n));
count = logRecur(n);
std.debug.print("对数阶（递归实现）的操作数量 = {}\n", .{count});
count = linearLogRecur(@as(f32, n));
count = linearLogRecur(n);
std.debug.print("线性对数阶（递归实现）的操作数量 = {}\n", .{count});
count = factorialRecur(n);

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