有没有比这个方法更简洁的方法来获取整数的位数?
int numDigits = String.valueOf(1000).length();
当前回答
出于好奇，我试着对其进行基准测试……
import org.junit.Test;
import static org.junit.Assert.*;
public class TestStack1306727 {
@Test
public void bench(){
int number=1000;
int a= String.valueOf(number).length();
int b= 1 + (int)Math.floor(Math.log10(number));
assertEquals(a,b);
int i=0;
int s=0;
long startTime = System.currentTimeMillis();
for(i=0, s=0; i< 100000000; i++){
a= String.valueOf(number).length();
s+=a;
}
long stopTime = System.currentTimeMillis();
long runTime = stopTime - startTime;
System.out.println("Run time 1: " + runTime);
System.out.println("s: "+s);
startTime = System.currentTimeMillis();
for(i=0,s=0; i< 100000000; i++){
b= number==0?1:(1 + (int)Math.floor(Math.log10(Math.abs(number))));
s+=b;
}
stopTime = System.currentTimeMillis();
runTime = stopTime - startTime;
System.out.println("Run time 2: " + runTime);
System.out.println("s: "+s);
assertEquals(a,b);
}
}
结果如下:
Run time 1: 6765 s: 400000000 Run time 2: 6000 s: 400000000
现在我想知道我的基准测试是否真的意味着什么，但我确实在基准测试本身的多次运行中得到了一致的结果(一毫秒内的变化)……:)看起来这是无用的尝试和优化…
编辑:根据ptomli的注释，我在上面的代码中用' I '替换'number'，并在5次运行的bench中得到以下结果:
Run time 1: 11500 s: 788888890 Run time 2: 8547 s: 788888890 Run time 1: 11485 s: 788888890 Run time 2: 8547 s: 788888890 Run time 1: 11469 s: 788888890 Run time 2: 8547 s: 788888890 Run time 1: 11500 s: 788888890 Run time 2: 8547 s: 788888890 Run time 1: 11484 s: 788888890 Run time 2: 8547 s: 788888890
其他回答
最快的方法:分而治之。
Assuming your range is 0 to MAX_INT, then you have 1 to 10 digits. You can approach this interval using divide and conquer, with up to 4 comparisons per each input. First, you divide [1..10] into [1..5] and [6..10] with one comparison, and then each length 5 interval you divide using one comparison into one length 3 and one length 2 interval. The length 2 interval requires one more comparison (total 3 comparisons), the length 3 interval can be divided into length 1 interval (solution) and a length 2 interval. So, you need 3 or 4 comparisons.
没有除法，没有浮点运算，没有昂贵的对数，只有整数比较。
代码(长但快):
if (n < 100000) {
// 5 or less
if (n < 100){
// 1 or 2
if (n < 10)
return 1;
else
return 2;
} else {
// 3 or 4 or 5
if (n < 1000)
return 3;
else {
// 4 or 5
if (n < 10000)
return 4;
else
return 5;
}
}
} else {
// 6 or more
if (n < 10000000) {
// 6 or 7
if (n < 1000000)
return 6;
else
return 7;
} else {
// 8 to 10
if (n < 100000000)
return 8;
else {
// 9 or 10
if (n < 1000000000)
return 9;
else
return 10;
}
}
}
基准测试(在JVM预热之后)——查看下面的代码以了解基准测试是如何运行的:
基线方法(使用String.length): 2145毫秒 Log10方法:711ms = 3.02次 和基线一样快 重复除:2797ms = 0.77次 和基线一样快 分治:74ms = 28.99 时间和基线一样快
完整的代码:
public static void main(String[] args) throws Exception {
// validate methods:
for (int i = 0; i < 1000; i++)
if (method1(i) != method2(i))
System.out.println(i);
for (int i = 0; i < 1000; i++)
if (method1(i) != method3(i))
System.out.println(i + " " + method1(i) + " " + method3(i));
for (int i = 333; i < 2000000000; i += 1000)
if (method1(i) != method3(i))
System.out.println(i + " " + method1(i) + " " + method3(i));
for (int i = 0; i < 1000; i++)
if (method1(i) != method4(i))
System.out.println(i + " " + method1(i) + " " + method4(i));
for (int i = 333; i < 2000000000; i += 1000)
if (method1(i) != method4(i))
System.out.println(i + " " + method1(i) + " " + method4(i));
// work-up the JVM - make sure everything will be run in hot-spot mode
allMethod1();
allMethod2();
allMethod3();
allMethod4();
// run benchmark
Chronometer c;
c = new Chronometer(true);
allMethod1();
c.stop();
long baseline = c.getValue();
System.out.println(c);
c = new Chronometer(true);
allMethod2();
c.stop();
System.out.println(c + " = " + StringTools.formatDouble((double)baseline / c.getValue() , "0.00") + " times as fast as baseline");
c = new Chronometer(true);
allMethod3();
c.stop();
System.out.println(c + " = " + StringTools.formatDouble((double)baseline / c.getValue() , "0.00") + " times as fast as baseline");
c = new Chronometer(true);
allMethod4();
c.stop();
System.out.println(c + " = " + StringTools.formatDouble((double)baseline / c.getValue() , "0.00") + " times as fast as baseline");
}
private static int method1(int n) {
return Integer.toString(n).length();
}
private static int method2(int n) {
if (n == 0)
return 1;
return (int)(Math.log10(n) + 1);
}
private static int method3(int n) {
if (n == 0)
return 1;
int l;
for (l = 0 ; n > 0 ;++l)
n /= 10;
return l;
}
private static int method4(int n) {
if (n < 100000) {
// 5 or less
if (n < 100) {
// 1 or 2
if (n < 10)
return 1;
else
return 2;
} else {
// 3 or 4 or 5
if (n < 1000)
return 3;
else {
// 4 or 5
if (n < 10000)
return 4;
else
return 5;
}
}
} else {
// 6 or more
if (n < 10000000) {
// 6 or 7
if (n < 1000000)
return 6;
else
return 7;
} else {
// 8 to 10
if (n < 100000000)
return 8;
else {
// 9 or 10
if (n < 1000000000)
return 9;
else
return 10;
}
}
}
}
private static int allMethod1() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method1(i);
for (int i = 1000; i < 100000; i += 10)
x = method1(i);
for (int i = 100000; i < 1000000; i += 100)
x = method1(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method1(i);
return x;
}
private static int allMethod2() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method2(i);
for (int i = 1000; i < 100000; i += 10)
x = method2(i);
for (int i = 100000; i < 1000000; i += 100)
x = method2(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method2(i);
return x;
}
private static int allMethod3() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method3(i);
for (int i = 1000; i < 100000; i += 10)
x = method3(i);
for (int i = 100000; i < 1000000; i += 100)
x = method3(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method3(i);
return x;
}
private static int allMethod4() {
int x = 0;
for (int i = 0; i < 1000; i++)
x = method4(i);
for (int i = 1000; i < 100000; i += 10)
x = method4(i);
for (int i = 100000; i < 1000000; i += 100)
x = method4(i);
for (int i = 1000000; i < 2000000000; i += 200)
x = method4(i);
return x;
}
基准:
基线方法(String.length): 2145ms Log10方法:711ms =基线速度的3.02倍 重复除:2797ms =基线速度的0.77倍 分治:74毫秒= 28.99倍的基线速度
Edit
在我写完基准测试之后，我偷偷地看了一下Integer。toString来自Java 6，我发现它使用:
final static int [] sizeTable = { 9, 99, 999, 9999, 99999, 999999, 9999999,
99999999, 999999999, Integer.MAX_VALUE };
// Requires positive x
static int stringSize(int x) {
for (int i=0; ; i++)
if (x <= sizeTable[i])
return i+1;
}
我以我的分治方案为基准:
分治法:104毫秒 Java 6解决方案-迭代和比较:406ms
我的速度大约是Java 6解决方案的4倍。
对数是你的朋友:
int n = 1000;
int length = (int)(Math.log10(n)+1);
NB:只对n >有效0。
由于以10为基数的整数的位数只是1 + truncate(log10(number))，您可以这样做:
public class Test {
public static void main(String[] args) {
final int number = 1234;
final int digits = 1 + (int)Math.floor(Math.log10(number));
System.out.println(digits);
}
}
被编辑是因为我的最后一次编辑修复了代码示例，但没有修复描述。
我们可以使用递归循环来实现这一点
public static int digitCount(int numberInput, int i) {
while (numberInput > 0) {
i++;
numberInput = numberInput / 10;
digitCount(numberInput, i);
}
return i;
}
public static void printString() {
int numberInput = 1234567;
int digitCount = digitCount(numberInput, 0);
System.out.println("Count of digit in ["+numberInput+"] is ["+digitCount+"]");
}
下面是JDK开发人员给出的解决方案。JDK 17 (Long类):
/**
* Returns the string representation size for a given long value.
*
* @param x long value
* @return string size
*
* @implNote There are other ways to compute this: e.g. binary search,
* but values are biased heavily towards zero, and therefore linear search
* wins. The iteration results are also routinely inlined in the generated
* code after loop unrolling.
*/
static int stringSize(long x) {
int d = 1;
if (x >= 0) {
d = 0;
x = -x;
}
long p = -10;
for (int i = 1; i < 19; i++) {
if (x > p)
return i + d;
p = 10 * p;
}
return 19 + d;
}
注意，如果需要的话，该方法会考虑减号。
不幸的是，该方法没有公开。
在性能方面，您可以从评论中看到，JDK开发人员与其他选项相比至少考虑了这一点。我猜 分而治之的方法倾向于较小的数字，效果会稍好一些 更好，因为CPU可以比整数更快地进行整数比较 乘法。但这种差异可能小到无法测量。
无论如何，我希望JDK中已经公开了这个方法，这样人们就不会开始使用自己的方法了。
