Related
I'm having difficulty with simplifying the following function into several several atomic binary operations, it feels like it's possible however I'm unable to do it, I'm scratching my head for few hours already:
public UInt32 reverse_xor_lshift(UInt32 y, Int32 shift)
{
var x = y & (UInt32)((1 << shift) - 1);
for (int i = 0; i < (32 - shift); i++) {
var bit = ((x & (1 << i)) >> i) ^ ((y & (1 << (shift + i))) >> (shift + i));
x |= (UInt32)(bit << (shift + i));
}
return x;
}
what the function does is just it computes the inverse of the Z = X ^ (X << Y), in other words reverse_xor_lshift(Z, Y) == X
You can inverse it with much fewer operations, though in a harder to understand way, by using the same technique as used in converting back from grey code:
Apply the transformation z ^= z << i where i starts at shift and doubles every iteration.
In pseudocode:
while (i < 32)
x ^= x << i
i *= 2
This works because in the first step, you xor the lowest bits (unaffected) by the place where they were "xored in", thus "xoring them out". Then the part that has been changed to the original is twice as wide. The new number is then of the form x ^ (x << k) ^ (x << k) ^ (x << 2k) = x ^ (x << 2k) which is the same thing again but with twice the offset, so the same trick will work again, decoding yet more of the original bits.
Given a range [a,b] (both inclusive) I need to find the smallest number with the maximum number of '1's in binary representation. My current approach is I find the number of bits set in all numbers from a to b and keep track of the maximum.
However this is very slow, any faster method?
Let's find most significant bit which is different in a and b. It will be 0 in a, 1 in b. If we place all other bits to the right to 1 - resulting number will be still in range [a; b]. And it will the single number with maximum number of ones in representation.
EDIT. The result of this algorithm always returns the number with n-1 bits set to one, where n is number of bits which can be changed. As pointed in comments - there is a bug in case if all of there n bits in b are set to 1. Here is the fixed code snippet:
int maximizeBits(int a, int b) {
if (a == b) {
return a;
}
int m = a ^ b, pow2 = 1; // MSB of m=a^b is bit that we need to find
while (m > pow2) { // Set other bits to 0
if ((m & pow2) != 0) {
m ^= pow2;
}
pow2 <<= 1;
}
int res = a | (m - 1); // Now m is in form of 2^n and m - 1 would be mask of n-1 bits
if ((res | b) <= b) { // Fix of problem if all n bits in b are set to 1
res = b;
}
return res;
}
You can replace the loop in Jarlax' answer by a "parallel suffix OR", like this
uint32_t m = (a ^ b) >> 1;
m |= m >> 1;
m |= m >> 2;
m |= m >> 4;
m |= m >> 8;
m |= m >> 16;
uint32_t res = a | m;
if ((res | b) <= b)
res = b;
return res;
It generalizes to different sizes integer, using ceil(log(k)) steps in general. The initial test a == b is not necessary, a ^ b would be zero, therefore m is zero, so nothing interesting happens anyway.
Alternatively, here's a completely different approach: keep changing the lowest 0 to a 1 until it is no longer possible.
unsigned x = a;
while (x < b) {
unsigned newx = (x + 1) | x; // set lowest 0
if (newx <= b)
x = newx;
else
break;
}
return x;
Given positive numbers N, K, D (1<= N <= 10^5, 1<=K<=N, 1<=D<=9). How many numbers with N digits are there, that have K consecutive digits D? Write the answer mod (10^9 + 7).
For example: N = 4, K = 3, D = 6, there are 18 numbers:
1666, 2666, 3666, 4666, 5666, 6660,
6661, 6662, 6663, 6664, 6665, 6666, 6667, 6668, 6669, 7666, 8666 and 9666.
Can we calculate the answer in O(N*K) (maybe dynamic programming)?
I've tried using combination.
If
N = 4, K = 3, D = 6. The number I have to find is abcd.
+) if (a = b = c = D), I choose digit for d. There are 10 ways (6660, 6661, 6662, 6663, 6664, 6665, 6666, 6667, 6668, 6669)
+) if (b = c = d = D), I choose digit for a (a > 0). There are 9 ways (1666, 2666, 3666, 4666, 5666, 6666, 7666, 8666, 9666)
But in two cases, the number 6666 is counted twice. N and K is very large, how can I count all of them?
If one is looking for a mathematical solution (vs. necessarily an algorithmic one) it's good to look at it in terms of the base cases and some formulas. They might turn out to be something you can do some kind of refactoring and get a tidy formula for. So just for the heck of it...here's a take on it that doesn't deal with the special treatment of zeros. Because that throws some wrenches in.
Let's look at a couple of base cases, and call our answer F(N,K) (not considering D, as it isn't relevant to account for; but taking it as a parameter anyway.):
when N = 0
You'll never find any length sequences of digits when there's no digit.
F(0, K) = 0 for any K.
when N = 1
Fairly obvious. If you're looking for K sequential digits in a single digit, the options are limited. Looking for more than one? No dice.
F(1, K) = 0 for any K > 1
Looking for exactly one? Okay, there's one.
F(1, 1) = 1
Sequences of zero sequential digits allowed? Then all ten digits are fine.
F(1, 0) = 10
for N > 1
when K = 0
Basically, all N-digit numbers will qualify. So the number of possibilities meeting the bar is 10^N. (e.g. when N is 3 then 000, 001, 002, ... 999 for any D)
F(N, 0) = 10^N for any N > 1
when K = 1
Possibilities meeting the condition is any number with at least one D in it. How many N-digit numbers are there which contain at least one digit D? Well, it's going to be 10^N minus all the numbers that have no instances of the digit D. 10^N - 9^N
F(N, 1) = 10^N - 9^N for any N > 1
when N < K
No way to get K sequential digits if N is less than K
F(N, K) = 0 when N < K
when N = K
Only one possible way to get K sequential digits in N digits.
F(N, K) = 1 when N = K
when N > K
Okay, we already know that N > 1 and K > 1. So this is going to be the workhorse where we hope to use subexpressions for things we've already solved.
Let's start by considering popping off the digit at the head, leaving N-1 digits on the tail. If that N-1 series could achieve a series of K digits all by itself, then adding another digit will not change anything about that. That gives us a term 10 * F(N-1, K)
But if our head digit is a D, that is special. Our cases will be:
It might be the missing key for a series that started with K-1 instances of D, creating a full range of K.
It might complete a range of K-1 instances of D, but on a case that already had a K series of adjacent D (that we thus accounted for in the above term)
It might not help at all.
So let's consider two separate categories of tail series: those that start with K-1 instances of D and those that do not. Let's say we have N=7 shown as D:DDDXYZ and with K=4. We subtract one from N and from K to get 6 and 3, and if we subtract them we get how many trailing any-digits (XYZ here) are allowed to vary. Our term for the union of (1) and (2) to add in is 10^((N-1)-(K-1)).
Now it's time for some subtraction for our double-counts. We haven't double counted any cases that didn't start with K-1 instances of D, so we keep our attention on that (DDDXYZ). If the value in the X slot is a D then it was definitely double counted. We can subtract out the term for that as 10^(((N - 1) - 1) - (K - 1)); in this case giving us all the pairings of YZ digits you can get with X as D. (100).
The last thing to get rid of are the cases where X is not a D, but in whatever that leftover after the X position there was still a K length series of D. Again we reuse our function, and subtract a term 9 * F(N - K, K, D).
Paste it all together and simplify a couple of terms you get:
F(N, K) = 10 * F(N-1,K,D) + 10^(N-K) - 10^(10,N-K-1) - 9 * F(N-K-1,K,D)
Now we have a nice functional definition suitable for Haskelling or whatever. But I'm still awkward with that, and it's easy enough to test in C++. So here it is (assuming availability of a long integer power function):
long F(int N, int K, int D) {
if (N == 0) return 0;
if (K > N) return 0;
if (K == N) return 1;
if (N == 1) {
if (K == 0) return 10;
if (K == 1) return 1;
return 0;
}
if (K == 0)
return power(10, N);
if (K == 1)
return power(10, N) - power(9, N);
return (
10 * F(N - 1, K, D)
+ power(10, N - K)
- power(10, N - K - 1)
- 9 * F(N - K - 1, K, D)
);
}
To double-check this against an exhaustive generator, here's a little C++ test program that builds the list of vectors that it scans using std::search_n. It checks the slow way against the fast way for N and K. I ran it from 0 to 9 for each:
#include <iostream>
#include <algorithm>
#include <vector>
using namespace std;
// http://stackoverflow.com/a/1505791/211160
long power(int x, int p) {
if (p == 0) return 1;
if (p == 1) return x;
long tmp = power(x, p/2);
if (p%2 == 0) return tmp * tmp;
else return x * tmp * tmp;
}
long F(int N, int K, int D) {
if (N == 0) return 0;
if (K > N) return 0;
if (K == N) return 1;
if (N == 1) {
if (K == 0) return 10;
if (K == 1) return 1;
return 0;
}
if (K == 0)
return power(10, N);
if (K == 1)
return power(10, N) - power(9, N);
return (
10 * F(N - 1, K, D)
+ power(10, N - K)
- power(10, N - K - 1)
- 9 * F(N - K - 1, K, D)
);
}
long FSlowCore(int N, int K, int D, vector<int> & digits) {
if (N == 0) {
if (search_n(digits.begin(), digits.end(), K, D) != end(digits)) {
return 1;
} else
return 0;
}
long total = 0;
digits.push_back(0);
for (int curDigit = 0; curDigit <= 9; curDigit++) {
total += FSlowCore(N - 1, K, D, digits);
digits.back()++;
}
digits.pop_back();
return total;
}
long FSlow(int N, int K, int D) {
vector<int> digits;
return FSlowCore(N, K, D, digits);
}
bool TestF(int N, int K, int D) {
long slow = FSlow(N, K, D);
long fast = F(N, K, D);
cout << "when N = " << N
<< " and K = " << K
<< " and D = " << D << ":\n";
cout << "Fast way gives " << fast << "\n";
cout << "Slow way gives " << slow << "\n";
cout << "\n";
return slow == fast;
}
int main() {
for (int N = 0; N < 10; N++) {
for (int K = 0; K < 10; K++) {
if (!TestF(N, K, 6)) {
exit(1);
}
}
}
}
Of course, since it counts leading zeros it will be different from the answers you got. See the test output here in this gist.
Modifying to account for the special-case zero handling is left as an exercise for the reader (as is modular arithmetic). Eliminating the zeros make it messier. Either way, this may be an avenue of attack for reducing the number of math operations even further with some transformations...perhaps.
Miquel is almost correct, but he missed a lot of cases. So, with N = 8, K = 5, and D = 6, we will need to look for those numbers that has the form:
66666xxx
y66666xx
xy66666x
xxy66666
with additional condition that y cannot be D.
So we can have our formula for this example:
66666xxx = 10^3
y66666xx = 8*10^2 // As 0 can also not be the first number
xy66666x = 9*9*10
xxy66666 = 9*10*9
So, the result is 3420.
For case N = 4, K = 3 and D = 6, we have
666x = 10
y666 = 8//Again, 0 is not counted!
So, we have 18 cases!
Note: We need to be careful that the first number cannot be 0! And we need to handle the case when D is zero too!
Update Java working code, Time complexity O(N-K)
static long cal(int n, int k, int d) {
long Mod = 1000000007;
long result = 0;
for (int i = 0; i <= n - k; i++) {//For all starting positions
if (i != 0 || d != 0) {
int left = n - k;
int upper_half = i;//Amount of digit that preceding DDD
int lower_half = n - k - i;//Amount of digit following DDD
long tmp = 1;
if (upper_half == 1) {
if (d == 0) {
tmp = 9;
} else {
tmp = 8;
}
}else if(upper_half >= 2){
//The pattern is x..yDDD...
tmp = (long) (9 * 9 * Math.pow(10, upper_half - 2));
}
tmp *= Math.pow(10, lower_half);
//System.out.println(tmp + " " + upper_half + " " + lower_half);
result += tmp;
result %= Mod;
}
}
return result;
}
Sample Tests:
N = 8, K = 5, D = 6
Output
3420
N = 4, K = 3, D = 6
Output
18
N = 4, K = 3, D = 0
Output
9
Suppose you have two numbers, both signed integers, and you want to sum them but can't use your language's conventional + and - operators. How would you do that?
Based on http://www.ocf.berkeley.edu/~wwu/riddles/cs.shtml
Not mine, but cute
int a = 42;
int b = 17;
char *ptr = (char*)a;
int result = (int)&ptr[b];
Using Bitwise operations just like Adder Circuits
Cringe. Nobody builds an adder from 1-bit adders anymore.
do {
sum = a ^ b;
carry = a & b;
a = sum;
b = carry << 1;
} while (b);
return sum;
Of course, arithmetic here is assumed to be unsigned modulo 2n or twos-complement. It's only guaranteed to work in C if you convert to unsigned, perform the calculation unsigned, and then convert back to signed.
Since ++ and -- are not + and - operators:
int add(int lhs, int rhs) {
if (lhs < 0)
while (lhs++) --rhs;
else
while (lhs--) ++rhs;
return rhs;
}
Using bitwise logic:
int sum = 0;
int carry = 0;
while (n1 > 0 || n2 > 0) {
int b1 = n1 % 2;
int b2 = n2 % 2;
int sumBits = b1 ^ b2 ^ carry;
sum = (sum << 1) | sumBits;
carry = (b1 & b2) | (b1 & carry) | (b2 & carry);
n1 /= 2;
n2 /= 2;
}
Here's something different than what's been posted already. Use the facts that:
log (a^b) = b * log a
e^a * e^b = e^(a + b)
So:
log (e^(a + b)) = log(e^a * e^b) = a + b (if the log is base e)
So just find log(e^a * e^b).
Of course this is just theoretical, in practice this is going to be inefficient and most likely inexact too.
If we're obeying the letter of the rules:
a += b;
Otherwise http://www.geekinterview.com/question_details/67647 has a pretty complete list.
This version has a restriction on the number range:
(((int64_t)a << 32) | ((int64_t)b & INT64_C(0xFFFFFFFF)) % 0xFFFFFFFF
This also counts under the "letter of the rules" category.
Simple example in Python, complete with a simple test:
NUM_BITS = 32
def adder(a, b, carry):
sum = a ^ b ^ carry
carry = (a & b) | (carry & (a ^ b))
#print "%d + %d = %d (carry %d)" % (a, b, sum, carry)
return sum, carry
def add_two_numbers(a, b):
carry = 0
result = 0
for n in range(NUM_BITS):
mask = 1 << n
bit_a = (a & mask) >> n
bit_b = (b & mask) >> n
sum, carry = adder(bit_a, bit_b, carry)
result = result | (sum << n)
return result
if __name__ == '__main__':
assert add_two_numbers(2, 3) == 5
assert add_two_numbers(57, 23) == 80
for a in range(10):
for b in range(10):
result = add_two_numbers(a, b)
print "%d + %d == %d" % (a, b, result)
assert result == a + b
In Common Lisp:
(defun esoteric-sum (a b)
(let ((and (logand a b)))
(if (zerop and)
;; No carrying necessary.
(logior a b)
;; Combine the partial sum with the carried bits again.
(esoteric-sum (logxor a b) (ash and 1)))))
That's taking the bitwise-and of the numbers, which figures out which bits need to carry, and, if there are no bits that require shifting, returns the bitwise-or of the operands. Otherwise, it shifts the carried bits one to the left and combines them again with the bitwise-exclusive-or of the numbers, which sums all the bits that don't need to carry, until no more carrying is necessary.
Here's an iterative alternative to the recursive form above:
(defun esoteric-sum-iterative (a b)
(loop for first = a then (logxor first second)
for second = b then (ash and 1)
for and = (logand first second)
until (zerop and)
finally (return (logior first second))))
Note that the function needs another concession to overcome Common Lisp's reluctance to employ fixed-width two's complement arithmetic—normally an immeasurable asset—but I'd rather not cloud the form of the function with that accidental complexity.
If you need more detail on why that works, please ask a more detailed question to probe the topic.
Not very creative, I know, but in Python:
sum([a,b])
I realize that this might not be the most elegant solution to the problem, but I figured out a way to do this using the len(list) function as a substitute for the addition operator.
'''
Addition without operators: This program obtains two integers from the user
and then adds them together without using operators. This is one of the 'hard'
questions from 'Cracking the Coding Interview' by
'''
print('Welcome to addition without a plus sign!')
item1 = int(input('Please enter the first number: '))
item2 = int(input('Please eneter the second number: '))
item1_list = []
item2_list = []
total = 0
total_list = []
marker = 'x'
placeholder = 'placeholder'
while len(item1_list) < item1:
item1_list.append(marker)
while len(item2_list) < item2:
item2_list.append(marker)
item1_list.insert(1, placeholder)
item1_list.insert(1, placeholder)
for item in range(1, len(item1_list)):
total_list.append(item1_list.pop())
for item in range(1, len(item2_list)):
total_list.append(item2_list.pop())
total = len(total_list)
print('The sum of', item1, 'and', item2, 'is', total)
#include <stdio.h>
int main()
{
int n1=5,n2=55,i=0;
int sum = 0;
int carry = 0;
while (n1 > 0 || n2 > 0)
{
int b1 = n1 % 2;
int b2 = n2 % 2;
int sumBits = b1 ^ b2 ^ carry;
sum = sum | ( sumBits << i);
i++;
carry = (b1 & b2) | (b1 & carry) | (b2 & carry);
n1 /= 2;
n2 /= 2;
}
sum = sum | ( carry << i );
printf("%d",sum);
return 0;
}
There is a lot of information on how to find the next power of 2 of a given value (see refs) but I cannot find any to get the previous power of two.
The only way I find so far is to keep a table with all power of two up to 2^64 and make a simple lookup.
Acius' Snippets
gamedev
Bit Twiddling Hacks
Stack Overflow
From Hacker's Delight, a nice branchless solution:
uint32_t flp2 (uint32_t x)
{
x = x | (x >> 1);
x = x | (x >> 2);
x = x | (x >> 4);
x = x | (x >> 8);
x = x | (x >> 16);
return x - (x >> 1);
}
This typically takes 12 instructions. You can do it in fewer if your CPU has a "count leading zeroes" instruction.
uint32_t previous_power_of_two( uint32_t x ) {
if (x == 0) {
return 0;
}
// x--; Uncomment this, if you want a strictly less than 'x' result.
x |= (x >> 1);
x |= (x >> 2);
x |= (x >> 4);
x |= (x >> 8);
x |= (x >> 16);
return x - (x >> 1);
}
Thanks for the responses. I will try to sum them up and explain a little bit clearer.
What this algorithm does is changing to 'ones' all bits after the first 'one' bit, cause these are the only bits that can make our 'x' larger than its previous power of two.
After making sure they are 'ones', it just removes them, leaving the first 'one' bit intact. That single bit in its place is our previous power of two.
Here is a one liner for posterity (ruby):
2**Math.log(input, 2).floor(0)
Probably the simplest approach (for positive numbers):
// find next (must be greater) power, and go one back
p = 1; while (p <= n) p <<= 1; p >>= 1;
You can make variations in many ways if you want to optimize.
The g++ compiler provides a builtin function __builtin_clz that counts leading zeros:
So we could do:
int previousPowerOfTwo(unsigned int x) {
return 1 << (sizeof(x)*8 - 1) - __builtin_clz(x);
}
int main () {
std::cout << previousPowerOfTwo(7) << std::endl;
std::cout << previousPowerOfTwo(31) << std::endl;
std::cout << previousPowerOfTwo(33) << std::endl;
std::cout << previousPowerOfTwo(8) << std::endl;
std::cout << previousPowerOfTwo(91) << std::endl;
return 0;
}
Results:
4
16
32
8
64
But note that, for x == 0, __builtin_clz return is undefined.
If you can get the next-higher power of 2, the next-lower power of 2 is either that next-higher or half that. It depends on what you consider to be the "next higher" for any power of 2 (and what you consider to be the next-lower power of 2).
What about
if (tt = v >> 16)
{
r = (t = tt >> 8) ? 0x1000000 * Table256[t] : 0x10000 * Table256[tt];
}
else
{
r = (t = v >> 8) ? 0x100 * Table256[t] : Table256[v];
}
It is just modified method from http://graphics.stanford.edu/~seander/bithacks.html#IntegerLogLookup.
This require like 7 operations and it might be faster to replace multiplications whit shift.
Solution with bit manipulation only:
long FindLargestPowerOf2LowerThanN(long n)
{
Assert.IsTrue(n > 0);
byte digits = 0;
while (n > 0)
{
n >>= 1;
digits++;
}
return 1 << (digits - 1);
}
Example:
FindLargestPowerOf2LowerThanN(6):
Our Goal is to get 4 or 100
1) 6 is 110
2) 110 has 3 digits
3) Since we need to find the largest power of 2 lower than n we subtract 1 from digits
4) 1 << 2 is equal to 100
FindLargestPowerOf2LowerThanN(132):
Our Goal is to get 128 or 10000000
1) 6 is 10000100
2) 10000100 has 8 digits
3) Since we need to find the largest power of 2 lower than n we subtract 1 from digits
4) 1 << 7 is equal to 10000000
I write my answer here just in case I need to reference it in the future.
For C language, this is what I believed to be the "ultimate" solution for the previous power of 2 function. The following code:
is targeted for C language (not C++),
uses compiler built-ins to yield efficient code (CLZ or BSR instruction) if compiler supports any,
is portable (standard C and no assembly) with the exception of built-ins, and
addresses undefined behavior of the compiler built-ins (when x is 0).
If you're writing in C++, you may adjust the code appropriately. Note that C++20 introduces std::bit_floor which does the exact same thing.
#include <limits.h>
#ifdef _MSC_VER
# if _MSC_VER >= 1400
/* _BitScanReverse is introduced in Visual C++ 2005 and requires
<intrin.h> (also introduced in Visual C++ 2005). */
#include <intrin.h>
#pragma intrinsic(_BitScanReverse)
#pragma intrinsic(_BitScanReverse64)
# define HAVE_BITSCANREVERSE 1
# endif
#endif
/* Macro indicating that the compiler supports __builtin_clz().
The name HAVE_BUILTIN_CLZ seems to be the most common, but in some
projects HAVE__BUILTIN_CLZ is used instead. */
#ifdef __has_builtin
# if __has_builtin(__builtin_clz)
# define HAVE_BUILTIN_CLZ 1
# endif
#elif defined(__GNUC__)
# if (__GNUC__ > 3)
# define HAVE_BUILTIN_CLZ 1
# elif defined(__GNUC_MINOR__)
# if (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)
# define HAVE_BUILTIN_CLZ 1
# endif
# endif
#endif
/**
* Returns the largest power of two that is not greater than x. If x
* is 0, returns 0.
*/
unsigned int prev_power_of_2(unsigned int x)
{
#ifdef HAVE_BITSCANREVERSE
if (x <= 0) {
return 0;
} else {
unsigned long int index;
(void) _BitScanReverse(&index, x);
return (1U << index);
}
#elif defined(HAVE_BUILTIN_CLZ)
if (x <= 0) {
return 0;
}
return (1U << (sizeof(x) * CHAR_BIT - 1 - __builtin_clz(x)));
#else
/* Fastest known solution without compiler built-ins or integer
logarithm instructions.
From the book "Hacker's Delight".
Converted to a loop for smaller code size.
("gcc -O3" will unroll this.) */
{
unsigned int shift;
for (shift = 1; shift < sizeof(x) * CHAR_BIT; shift <<= 1) {
x |= (x >> shift);
}
}
return (x - (x >> 1));
#endif
}
unsigned long long prev_power_of_2_long_long(unsigned long long x)
{
#if (defined(HAVE_BITSCANREVERSE) && \
ULLONG_MAX == 18446744073709551615ULL)
if (x <= 0) {
return 0;
} else {
/* assert(sizeof(__int64) == sizeof(long long)); */
unsigned long int index;
(void) _BitScanReverse64(&index, x);
return (1ULL << index);
}
#elif defined(HAVE_BUILTIN_CLZ)
if (x <= 0) {
return 0;
}
return (1ULL << (sizeof(x) * CHAR_BIT - 1 - __builtin_clzll(x)));
#else
{
unsigned int shift;
for (shift = 1; shift < sizeof(x) * CHAR_BIT; shift <<= 1) {
x |= (x >> shift);
}
}
return (x - (x >> 1));
#endif
}
Using a count leading zeros function (a.k.a. bitscan right), determining the next lowest power of 2 is easy:
uint32_t lower_power_of_2(uint32_t x) {
assert(x != 0);
return 1 << (31 - __builtin_clz(x));
}
Here, __builtin_clz is recognized by gcc and clang. Use _BitScanReverse with a Microsoft compiler.
This is my way:
//n is the number you want to find the previus power of 2
long m = 1;
while(n > 1){
n >>= 1;
m <<= 1;
}
//m is the previous power of two
When you work in base 2, you can jump from a power of two to the next one by just adding or removing a digit from the right.
For instance, the previous power of two of the number 8 is the number 4. In binary:
01000 -> 0100 (we remove the trailing zero to get number 4)
So the algorithm to solve the calculus of the previous power of two is:
previousPower := number shr 1
previousPower = number >> 1
(or any other syntax)
This can be done in one line.
int nextLowerPowerOf2 = i <= 0
? 0
: ((i & (~i + 1)) == i)
? i >> 1
: (1 << (int)Math.Log(i, 2));
result
i power_of_2
-2 0
-1 0
0 0
1 0
2 1
3 2
4 2
5 4
6 4
7 4
8 4
9 8
Here's a more readable version in c#, with the <=0 guard clause distributed to the utility methods.
int nextLowerPowerOf2 = IsPowerOfTwo(i)
? i >> 1 // shift it right
: GetPowerOfTwoLessThanOrEqualTo(i);
public static int GetPowerOfTwoLessThanOrEqualTo(int x)
{
return (x <= 0 ? 0 : (1 << (int)Math.Log(x, 2)));
}
public static bool IsPowerOfTwo(int x)
{
return (((x & (~x + 1)) == x) && (x > 0));
}
Below code will find the previous power of 2:
int n = 100;
n /= 2;//commenting this will gives the next power of 2
n |= n>>1;
n |= n>>2;
n |= n>>4;
n |= n>>16;
System.out.println(n+1);
This is my current solution to find the next and previous powers of two of any given positive integer n and also a small function to determine if a number is power of two.
This implementation is for Ruby.
class Integer
def power_of_two?
(self & (self - 1) == 0)
end
def next_power_of_two
return 1 if self <= 0
val = self
val = val - 1
val = (val >> 1) | val
val = (val >> 2) | val
val = (val >> 4) | val
val = (val >> 8) | val
val = (val >> 16) | val
val = (val >> 32) | val if self.class == Bignum
val = val + 1
end
def prev_power_of_two
return 1 if self <= 0
val = self
val = val - 1
val = (val >> 1) | val
val = (val >> 2) | val
val = (val >> 4) | val
val = (val >> 8) | val
val = (val >> 16) | val
val = (val >> 32) | val if self.class == Bignum
val = val - (val >> 1)
end
end
Example use:
10.power_of_two? => false
16.power_of_two? => true
10.next_power_of_two => 16
10.prev_power_of_two => 8
For the previous power of two, finding the next and dividing by two is slightly slower than the method above.
I am not sure how it works with Bignums.