I am running the loop in this method for around 1 million times but it is taking a lot of time maybe due O(n^2) , so is there any way to improve these two modules :-
def genIndexList(length,ID):
indexInfoList = []
id = list(str(ID))
for i in range(length):
i3 = (str(decimalToBase3(i)))
while len(i3) != 12:
i3 = '0' + i3
p = (int(str(ID)[0]) + int(i3[0]) + int(i3[2]) + int(i3[4]) + int(i3[6]) + int(i3[8]) + int(i3[10]))%3
indexInfoList.append(str(ID)+i3+str(p))
return indexInfoList
and here is the method for to convert number to base3 :-
def decimalToBase3(num):
i = 0
if num != 0 and num != 1 and num != 2:
number = ""
while num != 0 :
remainder = num % 3
num = num / 3
number = str(remainder) + number
return int(number)
else:
return num
I am using python to make a software and these 2 functions are a part of it.Please suggest why these 2 methods are so slow and how to improve efficiency of these methods.
The first function can be reduced to:
def genIndexList(length, ID):
indexInfoList = []
id0 = str(ID)[0]
for i in xrange(length):
i3 = format(decimalToBase3(i), '012d')
p = sum(map(int, id0 + i3[::2])) % 3
indexInfoList.append('{}{}{}'.format(ID, i3, p))
return indexInfoList
You may want to make it a generator instead:
def genIndexList(length, ID):
id0 = str(ID)[0]
for i in xrange(length):
i3 = format(decimalToBase3(i), '012d')
p = sum(map(int, id0 + i3[::2])) % 3
yield '{}{}{}'.format(ID, i3, p)
The second function could be:
def decimalToBase3(num):
if 0 <= num < 3: return num
result = ""
while num:
num, digit = divmod(num, 3)
result = str(digit) + result
return int(result)
Next step; you are just generating a sequence of base-3 digits. Just generate these directly:
from itertools import product, imap
def base3sequence(l=12, digits='012'):
return imap(''.join, product(digits, repeat=l))
This produces base3 values, 0-padded to 12 digits:
>>> gen = base3sequence()
>>> for i in range(10):
... print next(gen)
...
000000000000
000000000001
000000000002
000000000010
000000000011
000000000012
000000000020
000000000021
000000000022
000000000100
and genIndexList() becomes:
from itertools import islice
def genIndexList(length, ID):
id0 = str(ID)[0]
for i3 in islice(base3sequence(), length):
p = sum(map(int, id0 + i3[::2])) % 3
yield '{}{}{}'.format(ID, i3, p)
Related
I tried to use MillerRabin + PollardP1_rho method to factorize an integer into primes in Python3 for reducing time complexity as much as I could.But it failed some tests,I knew where the problem was.But I am a tyro in algorithm, I didn't know how to fix it.So I will put all relative codes here.
import random
def gcd(a, b):
"""
a, b: integers
returns: a positive integer, the greatest common divisor of a & b.
"""
if a == 0:
return b
if a < 0:
return gcd(-a, b)
while b > 0:
c = a % b
a, b = b, c
return a
def mod_mul(a, b, n):
# Calculate a * b % n iterately.
result = 0
while b > 0:
if (b & 1) > 0:
result = (result + a) % n
a = (a + a) % n
b = (b >> 1)
return result
def mod_exp(a, b, n):
# Calculate (a ** b) % n iterately.
result = 1
while b > 0:
if (b & 1) > 0:
result = mod_mul(result, a, n)
a = mod_mul(a, a, n)
b = (b >> 1)
return result
def MillerRabinPrimeCheck(n):
if n in {2, 3, 5, 7, 11}:
return True
elif (n == 1 or n % 2 == 0 or n % 3 == 0 or n % 5 == 0 or n % 7 == 0 or n % 11 == 0):
return False
k = 0
u = n - 1
while not (u & 1) > 0:
k += 1
u = (u >> 1)
random.seed(0)
s = 5 #If the result isn't right, then add the var s.
for i in range(s):
x = random.randint(2, n - 1)
if x % n == 0:
continue
x = mod_exp(x, u, n)
pre = x
for j in range(k):
x = mod_mul(x, x, n)
if (x == 1 and pre != 1 and pre != n - 1):
return False
pre = x
if x != 1:
return False
return True
def PollardP1_rho(n, c):
'''
Consider c as a constant integer.
'''
i = 1
k = 2
x = random.randrange(1, n - 1) + 1
y = x
while 1:
i += 1
x = (mod_mul(x, x, n) + c) % n
d = gcd(y - x, n)
if 1 < d < n:
return d
elif x == y:
return n
elif i == k:
y = x
k = (k << 1)
result = []
def PrimeFactorsListGenerator(n):
if n <= 1:
pass
elif MillerRabinPrimeCheck(n) == True:
result.append(n)
else:
a = n
while a == n:
a = PollardP1_rho(n, random.randrange(1,n - 1) + 1)
PrimeFactorsListGenerator(a)
PrimeFactorsListGenerator(n // a)
When I tried to test this:
PrimeFactorsListGenerator(4)
It didn't stop and looped this:
PollardP1_rho(4, random.randrange(1,4 - 1) + 1)
I have already tested the functions before PollardP1_rho and they work normally,so I know the function PollardP1_rho cannot deal the number 4 correctly,also the number 5.How can I fix that?
I have solved it myself.
There is 1 mistake in the code.
I should not use a var 'result' outside of the function as a global var,I should define in the function and use result.extend() to ensure the availability of the whole recursive process.So I rewrote PollardP1_rho(n, c) and PrimeFactorsListGenerator(n):
def Pollard_rho(x, c):
'''
Consider c as a constant integer.
'''
i, k = 1, 2
x0 = random.randint(0, x)
y = x0
while 1:
i += 1
x0 = (mod_mul(x0, x0, x) + c) % x
d = gcd(y - x0, x)
if d != 1 and d != x:
return d
if y == x0:
return x
if i == k:
y = x0
k += k
def PrimeFactorsListGenerator(n):
result = []
if n <= 1:
return None
if MillerRabinPrimeCheck(n):
return [n]
p = n
while p >= n:
p = Pollard_rho(p, random.randint(1, n - 1))
result.extend(PrimeFactorsListGenerator(p))
result.extend(PrimeFactorsListGenerator(n // p))
return result
#PrimeFactorsListGenerator(400)
#PrimeFactorsListGenerator(40000)
There is an additional tip: You don't need to write a function mod_mul(a, b, n) at all, using Python built-in pow(a, b, n) will do the trick and it is fully optimized.
I came across an interesting problem:
How would you count the number of 1 digits in the representation of 11 to the power of N, 0<N<=1000.
Let d be the number of 1 digits
N=2 11^2 = 121 d=2
N=3 11^3 = 1331 d=2
Worst time complexity expected O(N^2)
The simple approach where you compute the number and count the number of 1 digits my getting the last digit and dividing by 10, does not work very well. 11^1000 is not even representable in any standard data type.
Powers of eleven can be stored as a string and calculated quite quickly that way, without a generalised arbitrary precision math package. All you need is multiply by ten and add.
For example, 111 is 11. To get the next power of 11 (112), you multiply by (10 + 1), which is effectively the number with a zero tacked the end, added to the number: 110 + 11 = 121.
Similarly, 113 can then be calculated as: 1210 + 121 = 1331.
And so on:
11^2 11^3 11^4 11^5 11^6
110 1210 13310 146410 1610510
+11 +121 +1331 +14641 +161051
--- ---- ----- ------ -------
121 1331 14641 161051 1771561
So that's how I'd approach, at least initially.
By way of example, here's a Python function to raise 11 to the n'th power, using the method described (I am aware that Python has support for arbitrary precision, keep in mind I'm just using it as a demonstration on how to do this an an algorithm, which is how the question was tagged):
def elevenToPowerOf(n):
# Anything to the zero is 1.
if n == 0: return "1"
# Otherwise, n <- n * 10 + n, once for each level of power.
num = "11"
while n > 1:
n = n - 1
# Make multiply by eleven easy.
ten = num + "0"
num = "0" + num
# Standard primary school algorithm for adding.
newnum = ""
carry = 0
for dgt in range(len(ten)-1,-1,-1):
res = int(ten[dgt]) + int(num[dgt]) + carry
carry = res // 10
res = res % 10
newnum = str(res) + newnum
if carry == 1:
newnum = "1" + newnum
# Prepare for next multiplication.
num = newnum
# There you go, 11^n as a string.
return num
And, for testing, a little program which works out those values for each power that you provide on the command line:
import sys
for idx in range(1,len(sys.argv)):
try:
power = int(sys.argv[idx])
except (e):
print("Invalid number [%s]" % (sys.argv[idx]))
sys.exit(1)
if power < 0:
print("Negative powers not allowed [%d]" % (power))
sys.exit(1)
number = elevenToPowerOf(power)
count = 0
for ch in number:
if ch == '1':
count += 1
print("11^%d is %s, has %d ones" % (power,number,count))
When you run that with:
time python3 prog.py 0 1 2 3 4 5 6 7 8 9 10 11 12 1000
you can see that it's both accurate (checked with bc) and fast (finished in about half a second):
11^0 is 1, has 1 ones
11^1 is 11, has 2 ones
11^2 is 121, has 2 ones
11^3 is 1331, has 2 ones
11^4 is 14641, has 2 ones
11^5 is 161051, has 3 ones
11^6 is 1771561, has 3 ones
11^7 is 19487171, has 3 ones
11^8 is 214358881, has 2 ones
11^9 is 2357947691, has 1 ones
11^10 is 25937424601, has 1 ones
11^11 is 285311670611, has 4 ones
11^12 is 3138428376721, has 2 ones
11^1000 is 2469932918005826334124088385085221477709733385238396234869182951830739390375433175367866116456946191973803561189036523363533798726571008961243792655536655282201820357872673322901148243453211756020067624545609411212063417307681204817377763465511222635167942816318177424600927358163388910854695041070577642045540560963004207926938348086979035423732739933235077042750354729095729602516751896320598857608367865475244863114521391548985943858154775884418927768284663678512441565517194156946312753546771163991252528017732162399536497445066348868438762510366191040118080751580689254476068034620047646422315123643119627205531371694188794408120267120500325775293645416335230014278578281272863450085145349124727476223298887655183167465713337723258182649072572861625150703747030550736347589416285606367521524529665763903537989935510874657420361426804068643262800901916285076966174176854351055183740078763891951775452021781225066361670593917001215032839838911476044840388663443684517735022039957481918726697789827894303408292584258328090724141496484460001, has 105 ones
real 0m0.609s
user 0m0.592s
sys 0m0.012s
That may not necessarily be O(n2) but it should be fast enough for your domain constraints.
Of course, given those constraints, you can make it O(1) by using a method I call pre-generation. Simply write a program to generate an array you can plug into your program which contains a suitable function. The following Python program does exactly that, for the powers of eleven from 1 to 100 inclusive:
def mulBy11(num):
# Same length to ease addition.
ten = num + '0'
num = '0' + num
# Standard primary school algorithm for adding.
result = ''
carry = 0
for idx in range(len(ten)-1, -1, -1):
digit = int(ten[idx]) + int(num[idx]) + carry
carry = digit // 10
digit = digit % 10
result = str(digit) + result
if carry == 1:
result = '1' + result
return result
num = '1'
print('int oneCountInPowerOf11(int n) {')
print(' static int numOnes[] = {-1', end='')
for power in range(1,101):
num = mulBy11(num)
count = sum(1 for ch in num if ch == '1')
print(',%d' % count, end='')
print('};')
print(' if ((n < 0) || (n > sizeof(numOnes) / sizeof(*numOnes)))')
print(' return -1;')
print(' return numOnes[n];')
print('}')
The code output by this script is:
int oneCountInPowerOf11(int n) {
static int numOnes[] = {-1,2,2,2,2,3,3,3,2,1,1,4,2,3,1,4,2,1,4,4,1,5,5,1,5,3,6,6,3,6,3,7,5,7,4,4,2,3,4,4,3,8,4,8,5,5,7,7,7,6,6,9,9,7,12,10,8,6,11,7,6,5,5,7,10,2,8,4,6,8,5,9,13,14,8,10,8,7,11,10,9,8,7,13,8,9,6,8,5,8,7,15,12,9,10,10,12,13,7,11,12};
if ((n < 0) || (n > sizeof(numOnes) / sizeof(*numOnes)))
return -1;
return numOnes[n];
}
which should be blindingly fast when plugged into a C program. On my system, the Python code itself (when you up the range to 1..1000) runs in about 0.6 seconds and the C code, when compiled, finds the number of ones in 111000 in 0.07 seconds.
Here's my concise solution.
def count1s(N):
# When 11^(N-1) = result, 11^(N) = (10+1) * result = 10*result + result
result = 1
for i in range(N):
result += 10*result
# Now count 1's
count = 0
for ch in str(result):
if ch == '1':
count += 1
return count
En c#:
private static void Main(string[] args)
{
var res = Elevento(1000);
var countOf1 = res.Select(x => int.Parse(x.ToString())).Count(s => s == 1);
Console.WriteLine(countOf1);
}
private static string Elevento(int n)
{
if (n == 0) return "1";
//Otherwise, n <- n * 10 + n, once for each level of power.
var num = "11";
while (n > 1)
{
n--;
// Make multiply by eleven easy.
var ten = num + "0";
num = "0" + num;
//Standard primary school algorithm for adding.
var newnum = "";
var carry = 0;
foreach (var dgt in Enumerable.Range(0, ten.Length).Reverse())
{
var res = int.Parse(ten[dgt].ToString()) + int.Parse(num[dgt].ToString()) + carry;
carry = res/10;
res = res%10;
newnum = res + newnum;
}
if (carry == 1)
newnum = "1" + newnum;
// Prepare for next multiplication.
num = newnum;
}
//There you go, 11^n as a string.
return num;
}
I am using MATLAB to find all of the possible combinations of k elements out of n possible elements. I stumbled across this question, but unfortunately it does not solve my problem. Of course, neither does nchoosek as my n is around 100.
Truth is, I don't need all of the possible combinations at the same time. I will explain what I need, as there might be an easier way to achieve the desired result. I have a matrix M of 100 rows and 25 columns.
Think of a submatrix of M as a matrix formed by ALL columns of M and only a subset of the rows. I have a function f that can be applied to any matrix which gives a result of either -1 or 1. For example, you can think of the function as sign(det(A)) where A is any matrix (the exact function is irrelevant for this part of the question).
I want to know what is the biggest number of rows of M for which the submatrix A formed by these rows is such that f(A) = 1. Notice that if f(M) = 1, I am done. However, if this is not the case then I need to start combining rows, starting of all combinations with 99 rows, then taking the ones with 98 rows, and so on.
Up to this point, my implementation had to do with nchoosek which worked when M had only a few rows. However, now that I am working with a relatively bigger dataset, things get stuck. Do any of you guys think of a way to implement this without having to use the above function? Any help would be gladly appreciated.
Here is my minimal working example, it works for small obs_tot but fails when I try to use bigger numbers:
value = -1; obs_tot = 100; n_rows = 25;
mat = randi(obs_tot,n_rows);
while value == -1
posibles = nchoosek(1:obs_tot,i);
[num_tries,num_obs] = size(possibles);
num_try = 1;
while value == 0 && num_try <= num_tries
check = mat(possibles(num_try,:),:);
value = sign(det(check));
num_try = num_try + 1;
end
i = i - 1;
end
obs_used = possibles(num_try-1,:)';
Preamble
As yourself noticed in your question, it would be nice not to have nchoosek to return all possible combinations at the same time but rather to enumerate them one by one in order not to explode memory when n becomes large. So something like:
enumerator = CombinationEnumerator(k, n);
while(enumerator.MoveNext())
currentCombination = enumerator.Current;
...
end
Here is an implementation of such enumerator as a Matlab class. It is based on classic IEnumerator<T> interface in C# / .NET and mimics the subfunction combs in nchoosek (the unrolled way):
%
% PURPOSE:
%
% Enumerates all combinations of length 'k' in a set of length 'n'.
%
% USAGE:
%
% enumerator = CombinaisonEnumerator(k, n);
% while(enumerator.MoveNext())
% currentCombination = enumerator.Current;
% ...
% end
%
%% ---
classdef CombinaisonEnumerator < handle
properties (Dependent) % NB: Matlab R2013b bug => Dependent must be declared before their get/set !
Current; % Gets the current element.
end
methods
function [enumerator] = CombinaisonEnumerator(k, n)
% Creates a new combinations enumerator.
if (~isscalar(n) || (n < 1) || (~isreal(n)) || (n ~= round(n))), error('`n` must be a scalar positive integer.'); end
if (~isscalar(k) || (k < 0) || (~isreal(k)) || (k ~= round(k))), error('`k` must be a scalar positive or null integer.'); end
if (k > n), error('`k` must be less or equal than `n`'); end
enumerator.k = k;
enumerator.n = n;
enumerator.v = 1:n;
enumerator.Reset();
end
function [b] = MoveNext(enumerator)
% Advances the enumerator to the next element of the collection.
if (~enumerator.isOkNext),
b = false; return;
end
if (enumerator.isInVoid)
if (enumerator.k == enumerator.n),
enumerator.isInVoid = false;
enumerator.current = enumerator.v;
elseif (enumerator.k == 1)
enumerator.isInVoid = false;
enumerator.index = 1;
enumerator.current = enumerator.v(enumerator.index);
else
enumerator.isInVoid = false;
enumerator.index = 1;
enumerator.recursion = CombinaisonEnumerator(enumerator.k - 1, enumerator.n - enumerator.index);
enumerator.recursion.v = enumerator.v((enumerator.index + 1):end); % adapt v (todo: should use private constructor)
enumerator.recursion.MoveNext();
enumerator.current = [enumerator.v(enumerator.index) enumerator.recursion.Current];
end
else
if (enumerator.k == enumerator.n),
enumerator.isInVoid = true;
enumerator.isOkNext = false;
elseif (enumerator.k == 1)
enumerator.index = enumerator.index + 1;
if (enumerator.index <= enumerator.n)
enumerator.current = enumerator.v(enumerator.index);
else
enumerator.isInVoid = true;
enumerator.isOkNext = false;
end
else
if (enumerator.recursion.MoveNext())
enumerator.current = [enumerator.v(enumerator.index) enumerator.recursion.Current];
else
enumerator.index = enumerator.index + 1;
if (enumerator.index <= (enumerator.n - enumerator.k + 1))
enumerator.recursion = CombinaisonEnumerator(enumerator.k - 1, enumerator.n - enumerator.index);
enumerator.recursion.v = enumerator.v((enumerator.index + 1):end); % adapt v (todo: should use private constructor)
enumerator.recursion.MoveNext();
enumerator.current = [enumerator.v(enumerator.index) enumerator.recursion.Current];
else
enumerator.isInVoid = true;
enumerator.isOkNext = false;
end
end
end
end
b = enumerator.isOkNext;
end
function [] = Reset(enumerator)
% Sets the enumerator to its initial position, which is before the first element.
enumerator.isInVoid = true;
enumerator.isOkNext = (enumerator.k > 0);
end
function [c] = get.Current(enumerator)
if (enumerator.isInVoid), error('Enumerator is positioned (before/after) the (first/last) element.'); end
c = enumerator.current;
end
end
properties (GetAccess=private, SetAccess=private)
k = [];
n = [];
v = [];
index = [];
recursion = [];
current = [];
isOkNext = false;
isInVoid = true;
end
end
We can test implementation is ok from command window like this:
>> e = CombinaisonEnumerator(3, 6);
>> while(e.MoveNext()), fprintf(1, '%s\n', num2str(e.Current)); end
Which returns as expected the following n!/(k!*(n-k)!) combinations:
1 2 3
1 2 4
1 2 5
1 2 6
1 3 4
1 3 5
1 3 6
1 4 5
1 4 6
1 5 6
2 3 4
2 3 5
2 3 6
2 4 5
2 4 6
2 5 6
3 4 5
3 4 6
3 5 6
4 5 6
Implementation of this enumerator may be further optimized for speed, or by enumerating combinations in an order more appropriate for your case (e.g., test some combinations first rather than others) ... Well, at least it works! :)
Problem solving
Now solving your problem is really easy:
n = 100;
m = 25;
matrix = rand(n, m);
k = n;
cont = true;
while(cont && (k >= 1))
e = CombinationEnumerator(k, n);
while(cont && e.MoveNext());
cont = f(matrix(e.Current(:), :)) ~= 1;
end
if (cont), k = k - 1; end
end
I want to write a program to convert from decimal to negabinary.
I cannot figure out how to convert from decimal to negabinary.
I have no idea about how to find the rule and how it works.
Example: 7(base10)-->11011(base-2)
I just know it is 7 = (-2)^0*1 + (-2)^1*1 + (-2)^2*0 + (-2)^3*1 + (-2)^4*1.
The algorithm is described in http://en.wikipedia.org/wiki/Negative_base#Calculation. Basically, you just pick the remainder as the positive base case and make sure the remainder is nonnegative and minimal.
7 = -3*-2 + 1 (least significant digit)
-3 = 2*-2 + 1
2 = -1*-2 + 0
-1 = 1*-2 + 1
1 = 0*-2 + 1 (most significant digit)
def neg2dec(arr):
n = 0
for i, num in enumerate(arr[::-1]):
n+= ((-2)**i)*num
return n
def dec2neg(num):
if num == 0:
digits = ['0']
else:
digits = []
while num != 0:
num, remainder = divmod(num, -2)
if remainder < 0:
num, remainder = num + 1, remainder + 2
digits.append(str(remainder))
return ''.join(digits[::-1])
Just my two cents (C#):
public static int[] negaBynary(int value)
{
List<int> result = new List<int> ();
while (value != 0)
{
int remainder = value % -2;
value = value / -2;
if (remainder < 0)
{
remainder += 2;
value += 1;
}
Console.WriteLine (remainder);
result.Add(remainder);
}
return result.ToArray();
}
There is a method (attributed to Librik/Szudzik/Schröppel) that is much more efficient:
uint64_t negabinary(int64_t num) {
const uint64_t mask = 0xAAAAAAAAAAAAAAAA;
return (mask + num) ^ mask;
}
The conversion method and its reverse are described in more detail in this answer.
Here is some code that solves it and display the math behind it.
Some code taken from "Birender Singh"
#https://onlinegdb.com/xR1E5Cj7L
def neg2dec(arr):
n = 0
for i, num in enumerate(arr[::-1]):
n+= ((-2)**i)*num
return n
def dec2neg(num):
oldNum = num
if num == 0:
digits = ['0']
else:
digits = []
while num != 0:
num, remainder = divmod(num, -10)
if remainder < 0:
num, remainder = num + 1, remainder + 10
print(str(oldNum) + " = " + str(num) + " * -10 + " + str(remainder))
oldNum = num
digits.append(str(remainder))
return ''.join(digits[::-1])
print(dec2neg(-8374932))
Output:
-8374932 = 837494 * -10 + 8
837494 = -83749 * -10 + 4
-83749 = 8375 * -10 + 1
8375 = -837 * -10 + 5
-837 = 84 * -10 + 3
84 = -8 * -10 + 4
-8 = 1 * -10 + 2
1 = 0 * -10 + 1
12435148
How to design an algorithm to simulate multiplication by addition. input two integers. they may be zero, positive or negative..
def multiply(a, b):
if (a == 1):
return b
elif (a == 0):
return 0
elif (a < 0):
return -multiply(-a, b)
else:
return b + multiply(a - 1, b)
some pseudocode:
function multiply(x, y)
if abs(x) = x and abs(y) = y or abs(x) <> x and abs(y) <> y then sign = 'plus'
if abs(x) = x and abs(y) <> y or abs(x) <> x and abs(y) = y then sign = 'minus'
res = 0
for i = 0 to abs(y)
res = res + abs(x)
end
if sign = 'plus' return res
else return -1 * res
end function
val:= 0
bothNegative:=false
if(input1 < 0) && if(input2 < 0)
bothNegative=true
if(bothNegative)
smaller_number:=absolute_value_of(smaller_number)
for [i:=absolute_value_of(bigger_number);i!=0;i--]
do val+=smaller_number
return val;
mul(a,b)
{
sign1=sign2=1;
if(a==0 || b==0)
return 0;
if(a<0){
sign1=-1;
a=-a;
}
if(b<0){
sign2=-1;
b=-b;
}
s=a;
for(i=1;i<b;i++)
s+=a;
if(sign1==sign2)
return s;
else
return -s;
}
How about this for integers:
int multiply(int a, int b)
{
int product = 0;
int i;
if ( b > 0 )
{
for(i = 0; i < b ; i++)
{
product += a;
}
}
else
{
for(i = 0; i > b ; i--)
{
product -= a;
}
}
return product;
}
I got here because I was looking for multiplication algorithm without using * operation. All I see here is just adding or subtracting number n-times. It's O(n) and it's ok, but...
If you have bitwise shift operations you can get O(log n) algorithm for multiplication.
Here is my pseudocode:
function mul(n, x)
if n < 0 then # 'n' cannot be negative
n := -n
x := -x
endif
y := 0
while n != 0 do
if n % 2 == 0 then
x := x << 1 # x := x + x
n := n >> 1 # n := n / 2
else
y := y + x
x := x << 1 # x := x + x
n := n - 1 # n := (n-1)/2
n := n >> 1
endif
endwhile
return y # y = n * x
end
Remember that function above for mul(1000000, 2) is O(log 1000000) and for mul(2, 1000000) is only O(log 2).
Of course, you will get the same results, but keep in mind that the order of the parameters in function call does matter.
Edit: sidenote for using n % 2
Implementation of n % 2 using bitwise shift
It's pretty straightforward. First divide n by 2, then multiply n by 2 and check if n has changed. Pseudocode:
function is_even(n)
n_original := n
n := n >> 1 # n := n / 2
n := n << 1 # n := n * 2
if n = n_original then
return true # n is even
else
return false # n is not even
endif
end
Implementation of n % 2 using bitwise and
function is_even(n)
if n and 1 = 0 then
return true
else
return false
endif
end