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

一个非常简单的解决方案:

public int numLength(int n) {
  for (int length = 1; n % Math.pow(10, length) != n; length++) {}
  return length;
}

其他回答

计算int变量中数字数的有效方法之一是定义一个方法digitsCounter,其中包含所需数量的条件语句。 方法很简单,我们将检查n位数字所在的每个范围: 0: 9为个位数 10:99是两位数 100: 999是三位数等等……

    static int digitsCounter(int N)
    {   // N = Math.abs(N); // if `N` is -ve
        if (0 <= N && N <= 9) return 1;
        if (10 <= N && N <= 99) return 2;
        if (100 <= N && N <= 999) return 3;
        if (1000 <= N && N <= 9999) return 4;
        if (10000 <= N && N <= 99999) return 5;
        if (100000 <= N && N <= 999999) return 6;
        if (1000000 <= N && N <= 9999999) return 7;
        if (10000000 <= N && N <= 99999999) return 8;
        if (100000000 <= N && N <= 999999999) return 9;
        return 10;
    }

一种更干净的方法是取消下限检查,因为如果我们按顺序进行,就不需要下限检查了。

    static int digitsCounter(int N)
    {
        N = N < 0 ? -N : N;
        if (N <= 9) return 1;
        if (N <= 99) return 2;
        if (N <= 999) return 3;
        if (N <= 9999) return 4;
        if (N <= 99999) return 5;
        if (N <= 999999) return 6;
        if (N <= 9999999) return 7;
        if (N <= 99999999) return 8;
        if (N <= 999999999) return 9;
        return 10; // Max possible digits in an 'int'
    }

我还没有看到基于乘法的解决方案。对数、除法和基于字符串的解决方案将在数百万个测试用例中变得相当笨拙,所以这里有一个int型的解决方案:

/**
 * Returns the number of digits needed to represents an {@code int} value in 
 * the given radix, disregarding any sign.
 */
public static int len(int n, int radix) {
    radixCheck(radix); 
    // if you want to establish some limitation other than radix > 2
    n = Math.abs(n);

    int len = 1;
    long min = radix - 1;

    while (n > min) {
        n -= min;
        min *= radix;
        len++;
    }

    return len;
}

以10为基底,这是可行的,因为n本质上是与9,99,999…因为min是9,90,900…n被减去9,90,900…

不幸的是,仅仅因为溢出而替换int的每个实例是不能移植到long的。另一方面,它恰好适用于2垒和10垒(但对于大多数其他垒来说严重失败)。您将需要一个用于溢出点的查找表(或除法测试……)电子战)

/**
 * For radices 2 &le r &le Character.MAX_VALUE (36)
 */
private static long[] overflowpt = {-1, -1, 4611686018427387904L,
    8105110306037952534L, 3458764513820540928L, 5960464477539062500L,
    3948651115268014080L, 3351275184499704042L, 8070450532247928832L,
    1200757082375992968L, 9000000000000000000L, 5054470284992937710L,
    2033726847845400576L, 7984999310198158092L, 2022385242251558912L,
    6130514465332031250L, 1080863910568919040L, 2694045224950414864L,
    6371827248895377408L, 756953702320627062L, 1556480000000000000L,
    3089447554782389220L, 5939011215544737792L, 482121737504447062L,
    839967991029301248L, 1430511474609375000L, 2385723916542054400L,
    3902460517721977146L, 6269893157408735232L, 341614273439763212L,
    513726300000000000L, 762254306892144930L, 1116892707587883008L,
    1617347408439258144L, 2316231840055068672L, 3282671350683593750L,
    4606759634479349760L};

public static int len(long n, int radix) {
    radixCheck(radix);
    n = abs(n);

    int len = 1;
    long min = radix - 1;
    while (n > min) {
        len++;
        if (min == overflowpt[radix]) break;
        n -= min;
        min *= radix;

    }

    return len;
}

简单的解决方案:

public class long_length {
    long x,l=1,n;
    for (n=10;n<x;n*=10){
        if (x/n!=0){
            l++;
        }
    }
    System.out.print(l);
}

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。

这取决于你对“整洁”的定义。我认为下面的代码相当简洁,运行速度也很快。

它基于Marian的回答,扩展到所有long值,并使用?:运营商。

private static long[] DIGITS = { 1l,
                                 10l,
                                 100l,
                                 1000l,
                                 10000l,
                                 100000l,
                                 1000000l,
                                 10000000l,
                                 100000000l,
                                 1000000000l,
                                 10000000000l,
                                 100000000000l,
                                 1000000000000l,
                                 10000000000000l,
                                 100000000000000l,
                                 1000000000000000l,
                                 10000000000000000l,
                                 100000000000000000l,
                                 1000000000000000000l };

public static int numberOfDigits(final long n)
{
    return n == Long.MIN_VALUE ? 19 : n < 0l ? numberOfDigits(-n) :
            n < DIGITS[8] ? // 1-8
              n < DIGITS[4] ? // 1-4
                n < DIGITS[2] ? // 1-2
                  n < DIGITS[1] ? 1 : 2 : // 1-2
                        n < DIGITS[3] ? 3 : 4 : // 3-4
                      n < DIGITS[6] ? // 5-8
                        n < DIGITS[5] ? 5 : 6 : // 5-6
                      n < DIGITS[7] ? 7 : 8 : // 7-8
            n < DIGITS[16] ? // 9-16
              n < DIGITS[12] ? // 9-12
                n < DIGITS[10] ? // 9-10
                  n < DIGITS[9] ? 9 : 10 : // 9-10
                        n < DIGITS[11] ? 11 : 12 : // 11-12
                      n < DIGITS[14] ? // 13-16
                        n < DIGITS[13] ? 13 : 14 : // 13-14
                      n < DIGITS[15] ? 15 : 16 : // 15-16
            n < DIGITS[17] ? 17 :  // 17-19
            n < DIGITS[18] ? 18 :
            19;
}