I am a beginner currently in first semester. I have been practising on Code Chef and am stuck at this problem. They are asking to reduce the execution time of my code. The problem goes as follows:
Meliodas and Ban are fighting over chocolates. Meliodas has X chocolates, while Ban has Y. Whoever has lesser number of chocolates eats as many chocolates as he has from the other's collection. This eatfest war continues till either they have the same number of chocolates, or at least one of them is left with no chocolates.
Can you help Elizabeth predict the total no of chocolates they'll be left with at the end of their war?
Input:
First line will contain T, number of testcases. Then the testcases follow.
Each testcase contains of a single line of input, which contains two integers X,Y, the no of chocolates Meliodas and Ban have, respectively.
Output:
For each testcase, output in a single line the no of chocolates that remain after Ban and Meliodas stop fighting.
Sample Input:
3
5 3
10 10
4 8
Sample Output:
2
20
8
My code is as follows:
#include <iostream>
using namespace std;
int main()
{
unsigned int t,B,M;
cin>>t;
while(t--)
{
cin>>M>>B;
if(B==M)
{
cout<<B+M<<endl;
}
else
{
for(int i=1;B!=M;i++)
{
if(B>M)
B=B-M;
else
M=M-B;
}
cout<<M+B<<endl;
}
}
return 0;
}
Assuming that Band Mare different from 0, this algorithm corresponds to one version of the Euclidean algorithm. Therefore, you can simply:
std::cout << 2 * std::gcd(B, M) << "\n";
If at least one of the quantity is equal to 0, then just print B + M.
After realizing that your code was correct, I wondered where could be any algorithmic improvement. And I realized that eating as many chocolate from the peer as one has was in fact close to a modulo operation. If both number are close, a minus operation could be slightly faster than a modulo one, but if one number is high, while the other is 1, you immediately get it instead of looping a great number of times...
The key to prevent stupid errors is to realize that if a modulo is 0, that means that the high number is a multiple of the small one and we must stop immediately writing twice the lower value.
And care should be taken that if one of the initial counts are 0, the total number will never change.
So the outer loop should become:
if(B==M || B == 0 || M == 0)
{
cout<<B+M<<"\0";
}
else {
for (;;) {
if (M < B) {
B = B % M;
if (B == 0) {
cout << M * 2 << '\n';
break;
}
}
else {
M = M % B;
if (M == 0) {
cout << B * 2 << '\n';
break;
}
}
}
}
...
Note: no infinite loop is possible here because a modulo ensures that for example is M > B > 0' after M = M % Byou will haveB > M >= 0and as the case== 0` is explicitely handled the number of loops cannot be higher than the lower number.
I am writing code in Hackerrank. And recently the problem said, convert decimal to base 2 and then count the max consecutive 1's in the binary number. And first I come with following solution. It works fine. But I do not understand the counting part of it, even though I wrote it.
The code is
int main(){
int n,ind=0, count=0, mmax=0;
char bin[100];
cin >> n;
while(n){
if(n%2==0) {
bin[ind]='0';
n = n / 2;
ind = ind + 1;
}
else if(n%2==1) {
bin[ind]='1';
n = n / 2;
ind = ind + 1;
}
}
for(int i=0; i<=(ind-1); i++){
if(bin[i] == '1' && bin[i+1] == '1'){
count++;
if(mmax < count)
mmax = count;
}
else
count=0;
}
cout << mmax + 1 << endl;
return 0;
}
In the above code, I guess that variable mmax will give me the max consecutive number of 1's but it gives me value that has (max consecutive - 1), So I just wrote like that and submitted the code. But I am curious about. why it is working that way. I am little bit of confused the way that code works like this.
Thanks
Lets say you have this binary sequence:
11110
Your code will compare starting from the first and second:
|11|110 1 && 1 -> max = 1
1|11|10 1 && 1 -> max = 2
11|11|0 1 && 1 -> max = 3
111|10| 1 && 0 -> max = 3
you can see, that although there are 4 1's you only do 3 comparisons, so your max will always be -1 of the actual max. You can fix this by adding mmax += 1 after your for loop.
Just a little bit of trace using small example will show why.
First, lets say there is only 1 '1' in your array.
Since you require both the current position and your next position to be '1', you will always get 0 for this case.
Let's say I have "11111". At the first '1', since next position is also '1', you increment count once. This repeats until 4th '1' and you increment your count 4 times in total so far. When you reach 5th '1', your next position is not '1', thus your count stops at 4.
In general, your method is like counting gaps between fingers, given 5 fingers, you get 4 gaps.
Side note: your code will fail for the case when there is no '1' in your array.
I was trying to solve the following problem but I am stuck. I think it is an dynamic programming problem.
Could you please give some ideas?
Problem:
Given a positive number n (n<=18) and a positive number m (m<=100).
Call S(x) is sum of digits of x.
For example S(123)=6
Count the number of integer number x that has n digits and S(x)=S(x*m)
Example:
n= 1, m= 2 result= 2
n= 18, m=1 result = 1000000000000000000
Thanks in advance.
First, we need to come up with a recursive formula:
Starting from the least significant digit (LSD) to the most significant digit (MSD), we have a valid solution if after we compute the MSD, we have S(x) = S(x*m)
To verify whether a number is a valid solution, we need to know three things:
What is the current sum of digit S(x)
What is the current sum of digit S(x*m)
What is the current digit.
So, to answer for the first and last, it is easy, we just need to maintain two parameters sumand digit. To compute the second, we need to maintain two additional parameters, sumOfProduct and lastRemaining.
sumOfProduct is the current S(x*m)
lastRemaining is the result of (m * current digit value + lastRemaining) / 10
For example, we have x = 123 and m = 23
First digit = 3
sum = 3
digit = 0
sumOfProduct += (lastRemaining + 3*m) % 10 = 9
lastRemaining = (m*3 + 0)/10 = 6
Second digit = 2
sum = 5
digit = 1
sumOfProduct += (lastRemaining + 2*m) % 10 = 11
lastRemaining = (m*2 + lastRemaining)/10 = 5
Last digit = 1
sum = 6
digit = 2
sumOfProduct += (lastRemaining + m) % 10 = 19
lastRemaining = (m + lastRemaining)/10 = 2
As this is the last digit, sumOfProduct += S(lastRemaining) = 21.
So, x = 123 and m = 23 is not a valid number. Check x*m = 2829 -> S(x*m) = S(2829) = 21.
So, we can have a recursive formula with state (digit, sum, sumOfProdut, lastRemaining).
Thus, our dynamic programming state is dp[18][18*9 + 1][18*9 + 1][200] (as m <= 100, so lastRemaining not larger than 200).
Now the dpstate is over 300 MB, but if we use an iterative approach, it will become smaller, using about 30MB
This problem can be calculated directly.
From those documents: 1, 2, and 3 (thanks to #LouisRicci for finding them), we can state:
The Repeating Cycle of Sum of Digits of Multiples starts repeating at the last digit but one from the base-number (9 for base-10)
S(x) can be defined as: let a equal x mod 9, if a is zero, take 9 as result, else take a. You can play it in the ES6 snippet below:
IN.oninput= (_=> OUT.value= (IN.value % 9) || 9);
IN.oninput();
Input x:<br>
<input id=IN value=123><br>
S(x):<br>
<input id=OUT disabled>
Multiplication rule: S(x * y) = S(S(x) * S(y)).
S(x) and S(x*m) will always be true for x=0, this way there is no zero result.
With the above statements in mind, we should calc the Repeating Cycle of Sum of Digits of Multiples for S(m):
int m = 88;
int Sm = S(m); // 7
int true_n_times_in_nine = 0;
for (int i=1; i<=9; i++) {
true_n_times_in_nine += i == S(i * Sm);
}
The answer then:
result = ((pow(10, n) / 9) * true_n_times_in_nine);
Plus one because of case zero:
result++;
Here is an ES6 solution:
S= x=> (x % 9) || 9;
TrueIn9= (m, Sm=S(m))=> [1,2,3,4,5,6,7,8,9].filter(i=> i==S(i*Sm)).length;
F= (n,m)=> ~~(eval('1e'+n)/9) * TrueIn9(m) + 1;
N.oninput=
M.oninput=
f=(_=> OUT.value= F(N.value | 0, M.value | 0));
f();
Input n: (number of digits)<br>
<input id=N value=1><br>
Input m: (multiplicative number)<br>
<input id=M value=2><br>
F(n,m):<br>
<input id=OUT disabled><br>
There are n groups of friends staying in the queue in front of bus station. The i-th group consists of ai men. Also, there is a single bus that works on the route. The size of the bus is x, that is it can transport x men simultaneously.
When the bus comes (it always comes empty) to the bus station, several groups from the head of the queue goes into the bus. Of course, groups of friends don't want to split, so they go to the bus only if the bus can hold the whole group. In the other hand, none wants to lose his position, that is the order of groups never changes.
The question is: how to choose the size x of the bus in such a way that the bus can transport all the groups and everytime when the bus moves off the bus station there is no empty space in the bus (the total number of men inside equals to x)?
Input Format:
The first line contains the only integer n (1≤n≤10^5). The second line contains n space-separated integers a1,a2,…,an (1≤ai≤10^4).
Output Format:
Print all the possible sizes of the bus in the increasing order.
Sample:
8
1 2 1 1 1 2 1 3
Output:
3 4 6 12
I made this code:
#include <iostream>
#include <vector>
#include <algorithm>
using namespace std;
int main(void)
{
int max=0,sum=0,i,n;
cin>>n;
int values[100000];
for ( i = 0; i < n; i++ )
{
cin>>values[i];
sum = sum + values[i];
if ( values[i] > max )
max = values[i];
}
int p = 0,j;
int count = 0;
vector<int> final;
for ( i = 0; i < n; i++ )
{
p = p + values[i];
j = 0;
if ( p >= max && sum%p == 0)
{
flag = 0;
while ( j < n )
{
garb = p;
while (garb!= 0)
{
garb = garb - values[j++];
if ( garb < 0 )
flag = 1;
}
}
if ( flag == 0 )
{
final.push_back(p);
count++;
}
}
}
sort(final.begin(),final.end());
for ( j = 0; j < count; j++ )
{
cout<<final[j]<<"\t";
}
return 0;
}
Edit: I did this in which basically, I am checking if the found divisor satisfies the condition, and if at any point of time, I get a negative integer on taking difference with the values, I mark it by using a flag. However, it seems to give me a seg fault now. Why?
I firstly, calculated the maximum value out of the all possible values, and then, I checked if its a divisor of the sum of the values. However, this approach doesn't work for the input as:
10
2 2 1 1 1 1 1 2 1 2
My output is
2 7 14
whereas the output should be
7 14
only.
Any other approach that I can go with?
Thanks!
I can think of the following simple solution (since your present concern is correctness and not time complexity):
Calculate the sum of all ai's (as you are already doing).
Calculate the maximum of all ai's (as you are already doing).
Find all the factors of sum that are > max(ai).
For each factor, iterate through the ai's and check whether the bus condition is satisfied.
The “Narcissistic numbers”, are n digit numbers where the sum of all the nth power of their digits is equal to the number.
So, 153 is a narcissistic number because 1^3 + 5^3 + 3^3 = 153.
Now given N, find all Narcissistic numbers that are N digit length ?
My Approach : was to iterate over all numbers doing sum of powers of digits
and check if its the same number or not, and I per calculated the powers.
but that's not good enough, so is there any faster way ?!
Update:
In nature there is just 88 narcissistic numbers, and the largest is 39 digits long,
But I just need the numbers with length 12 or less.
My Code :
long long int powers[11][12];
// powers[x][y] is x^y. and its already calculated
bool isNarcissistic(long long int x,int n){
long long int r = x;
long long int sum = 0;
for(int i=0; i<n ; ++i){
sum += powers[x%10][n];
if(sum > r)
return false;
x /= 10;
}
return (sum == r);
}
void find(int n,vector<long long int> &vv){
long long int start = powers[10][n-1];
long long int end = powers[10][n];
for(long long int i=start ; i<end ; ++i){
if(isNarcissistic(i,n))
vv.push_back(i);
}
}
Since there are only 88 narcisstic numbers in total, you can just store them in a look up table and iterate over it: http://mathworld.wolfram.com/NarcissisticNumber.html
Start from the other end. Iterate over the set of all nondecreasing sequences of d digits, compute the sum of the d-th powers, and check whether that produces (after sorting) the sequence you started with.
Since there are
9×10^(d-1)
d-digit numbers, but only
(10+d-1) `choose` d
nondecreasing sequences of d digits, that reduces the search space by a factor close to d!.
The code below implements the idea of #Daniel Fischer. It duplicates the table referenced at Mathworld and then prints a few more 11-digit numbers and verifies that there are none with 12 digits as stated here.
It would actually be simplier and probably a little faster to generate all possible histograms of non-increasing digit strings rather than the strings themselves. By a histogram I mean a table indexed 0-9 of frequencies of the respective digit. These can be compared directly without sorting. But the code below runs in < 1 sec, so I'm not going to implement the histogram idea.
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define MAX_DIGITS 12
// pwr[d][n] is d^n
long long pwr[10][MAX_DIGITS + 1];
// Digits and final index of number being considered.
int digits[MAX_DIGITS];
int m;
// Fill pwr.
void fill_tbls(void)
{
for (int d = 0; d < 10; d++) {
pwr[d][0] = 1;
for (int p = 1; p <= MAX_DIGITS; p++)
pwr[d][p] = pwr[d][p-1] * d;
}
}
// qsort comparison for integers descending
int cmp_ints_desc(const void *vpa, const void *vpb)
{
const int *pa = vpa, *pb = vpb;
return *pb - *pa;
}
// Test current number and print if narcissistic.
void test(void)
{
long long sum = 0;
for (int i = 0; i <= m; i++)
sum += pwr[digits[i]][m + 1];
int sum_digits[MAX_DIGITS * 2];
int n = 0;
for (long long s = sum; s; s /= 10)
sum_digits[n++] = s % 10;
if (n == m + 1) {
qsort(sum_digits, n, sizeof(int), cmp_ints_desc);
if (memcmp(sum_digits, digits, n * sizeof(int)) == 0)
printf("%lld\n", sum);
}
}
// Recursive generator of non-increasing digit strings.
// Calls test when a string is complete.
void gen(int i, int min, int max)
{
if (i > m)
test();
else {
for (int d = min; d <= max; d++) {
digits[i] = d;
gen(i + 1, 0, d);
}
}
}
// Fill tables and generate.
int main(void)
{
fill_tbls();
for (m = 0; m < MAX_DIGITS; m++)
gen(0, 1, 9);
return 0;
}
I wrote a program in Lua which found all the narcissistic numbers in 30829.642 seconds. The basis of the program is a recursive digit-value count array generator function which calls a checking function when it's generated the digit-value count for all the digit-values. Each nested loop iterates:
FROM i=
The larger of 0 and the solution to a+x*d^o+(s-x)*(d-1)^o >= 10^(o-1) for x
where
- 'a' is the accumulative sum of powers of digits so far,
- 'd' is the current digit-value (0-9 for base 10),
- 'o' is the total number of digits (which the sum of the digit-value count array must add up to),
- 's' represents the remaining slots available until the array adds to 'o'
UP TO i<=
The smaller of 's' and the solution to a+x*d^o < 10^o for x with the same variables.
This ensures that the numbers checked will ALWAYS have the same number of digits as 'o', and therefore be more likely to be narcissistic while avoiding unnecessary computation.
In the loop, it does the recursive call for which it decrements the digit-value 'd' adds the current digit-value's contribution (a=a+i*d^o) and takes the i digit-slots used up away from 's'.
The gist of what I wrote is:
local function search(o,d,s,a,...) --Original number of digits, digit-value, remaining digits, accumulative sum, number of each digit-value in descending order (such as 5 nines)
if d>0 then
local d0,d1=d^o,(d-1)^o
local dd=d0-d1
--a+x*d^o+(s-x)*(d-1)^o >= 10^(o-1) , a+x*d^o < 10^o
for i=max(0,floor((10^(o-1)-s*d1-a)/dd)),min(s,ceil((10^o-a)/dd)-1) do
search(o,d-1,s-i,a+i*d0,i,...) --The digit counts are passed down as extra arguments.
end
else
--Check, with the count of zeroes set to 's', if the sum 'a' has the same count of each digit-value as the list specifies, and if so, add it to a list of narcissists.
end
end
local digits=1 --Skip the trivial single digit narcissistic numbers.
while #found<89 do
digits=digits+1
search(digits,9,digits,0)
end
EDIT: I forgot to mention that my program finds 89 narcissistic numbers! These are what it finds:
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 153, 370, 371, 407, 1634, 8208, 9474, 54748, 92727, 93084, 548834, 1741725, 4210818, 9800817, 9926315, 24678050, 24678051, 88593477, 146511208, 472335975, 534494836, 912985153, 4679307774, 32164049650, 32164049651, 40028394225, 42678290603, 44708635679, 49388550606, 82693916578, 94204591914, 28116440335967, 4338281769391370, 4338281769391371, 21897142587612075, 35641594208964132, 35875699062250035, 1517841543307505039, 3289582984443187032, 4498128791164624869, 4929273885928088826, 63105425988599693916, 128468643043731391252,449177399146038697307, 21887696841122916288858, 27879694893054074471405, 27907865009977052567814, 28361281321319229463398, 35452590104031691935943, 174088005938065293023722, 188451485447897896036875, 239313664430041569350093, 1550475334214501539088894, 1553242162893771850669378, 3706907995955475988644380, 3706907995955475988644381, 4422095118095899619457938, 121204998563613372405438066, 121270696006801314328439376, 128851796696487777842012787, 174650464499531377631639254, 177265453171792792366489765, 14607640612971980372614873089, 19008174136254279995012734740, 19008174136254279995012734741, 23866716435523975980390369295, 1145037275765491025924292050346, 1927890457142960697580636236639, 2309092682616190307509695338915, 17333509997782249308725103962772, 186709961001538790100634132976990, 186709961001538790100634132976991, 1122763285329372541592822900204593, 12639369517103790328947807201478392, 12679937780272278566303885594196922, 1219167219625434121569735803609966019, 12815792078366059955099770545296129367, 115132219018763992565095597973971522400, 115132219018763992565095597973971522401
For posterity ;-) This is most similar to #Krakow10's approach, generating bags of digits recursively, starting with 9, then 8, then 7 ... to 0.
It's Python3 code and finds all base-10 solutions with 1 through 61 digits (the first "obviously impossible" width) in less than 10 minutes (on my box). It's by far the fastest code I've ever heard of for this problem. What's the trick? No trick - just tedium ;-) As we go along, the partial sum so far yields a world of constraints on feasible continuations. The code just pays attention to those, and so is able to cut off vast masses of searches early.
Note: this doesn't find 0. I don't care. While all the references say there are 88 solutions, their tables all have 89 entries. Some eager editor must have added "0" later, and then everyone else mindlessly copied it ;-)
EDIT New version is over twice as fast, by exploiting some partial-sum constraints earlier in the search - now finishes in a little over 4 minutes on my box.
def nar(width):
from decimal import Decimal as D
import decimal
decimal.getcontext().prec = width + 10
if width * 9**width < 10**(width - 1):
raise ValueError("impossible at %d" % width)
pows = [D(i) ** width for i in range(10)]
mintotal, maxtotal = D(10)**(width - 1), D(10)**width - 1
def extend(d, todo, total):
# assert d > 0
powd = pows[d]
d1 = d-1
powd1 = pows[d1]
L = total + powd1 * todo # largest possible taking no d's
dL = powd - powd1 # the change to L when i goes up 1
for i in range(todo + 1):
if i:
total += powd
todo -= 1
L += dL
digitcount[d] += 1
if total > maxtotal:
break
if L < mintotal:
continue
if total < mintotal or L > maxtotal:
yield from extend(d1, todo, total)
continue
# assert mintotal <= total <= L <= maxtotal
t1 = total.as_tuple().digits
t2 = L.as_tuple().digits
# assert len(t1) == len(t2) == width
# Every possible continuation has sum between total and
# L, and has a full-width sum. So if total and L have
# some identical leading digits, a solution must include
# all such leading digits. Count them.
c = [0] * 10
for a, b in zip(t1, t2):
if a == b:
c[a] += 1
else:
break
else: # the tuples are identical
# assert d == 1 or todo == 0
# assert total == L
# This is the only sum we can get - no point to
# recursing. It's a solution iff each digit has been
# picked exactly as many times as it appears in the
# sum.
# If todo is 0, we've picked all the digits.
# Else todo > 0, and d must be 1: all remaining
# digits must be 0.
digitcount[0] += todo
# assert sum(c) == sum(digitcount) == width
if digitcount == c:
yield total
digitcount[0] -= todo
continue
# The tuples aren't identical, but may have leading digits
# in common. If, e.g., "9892" is a common prefix, then to
# get a solution we must pick at least one 8, at least two
# 9s, and at least one 2.
if any(digitcount[j] < c[j] for j in range(d, 10)):
# we're done picking digits >= d, but don't have
# enough of them
continue
# for digits < d, force as many as we need for the prefix
newtodo, newtotal = todo, total
added = []
for j in range(d):
need = c[j] - digitcount[j]
# assert need >= 0
if need:
newtodo -= need
added.append((j, need))
if newtodo < 0:
continue
for j, need in added:
newtotal += pows[j] * need
digitcount[j] += need
yield from extend(d1, newtodo, newtotal)
for j, need in added:
digitcount[j] -= need
digitcount[d] -= i
digitcount = [0] * 10
yield from extend(9, width, D(0))
assert all(i == 0 for i in digitcount)
if __name__ == "__main__":
from datetime import datetime
start_t = datetime.now()
width = total = 0
while True:
this_t = datetime.now()
width += 1
print("\nwidth", width)
for t in nar(width):
print(" ", t)
total += 1
end_t = datetime.now()
print(end_t - this_t, end_t - start_t, total)
I think the idea is to generate similar numbers. For example, 61 is similar to 16 as you are just summing
6^n +1^n
so
6^n+1^n=1^n+6^n
In this way you can reduce significant amount of numbers. For example in 3 digits scenario,
121==112==211,
you get the point. You need to generate those numbers first.
And you need to generate those numbers without actually iterating from 0-n.
Python version is:
def generate_power_list(power):
return [i**power for i in range(0,10)]
def find_narcissistic_numbers_naive(min_length, max_length):
for number_length in range(min_length, max_length):
power_dict = generate_power_dictionary(number_length)
max_number = 10 ** number_length
number = 10** (number_length -1)
while number < max_number:
value = 0
for digit in str(number):
value += power_dict[digit]
if value == number:
logging.debug('narcissistic %s ' % number)
number += 1
Recursive solution:
In this solution each recursion handles a single digit of the array of digits being used, and tries all appropriate combinations of that digit
def execute_recursive(digits, number_length):
index = len(digits)
if digits:
number = digits[-1]
else:
number = 0
results = []
digits.append(number)
if len(digits) < number_length:
while number < 10:
results += execute_recursive(digits[:], number_length)
number += 1
digits[index] = number
else:
while number < 10:
digit_value = sum_digits(digits)
if check_numbers_match_group(digit_value, digits):
results.append(digit_value)
logging.debug(digit_value)
number += 1
digits[index] = number
return results
def find_narcissistic_numbers(min_length, max_length):
for number_length in range(min_length, max_length):
digits = []
t_start = time.clock()
results = execute_recursive(digits, number_length)
print 'duration: %s for number length: %s' %(time.clock() - t_start, number_length)
Narcissistic number check
In the base version, when checking that a number matched the digits, we iterated through each digit type, to ensure that there were the same number of each type. In this version we have added the optimisation of checking the digit length is correct before doing the full check.
I expected that this would have more of an effect on small number lengths, because as number length increases, there will tend to be more numbers in the middle of the distribution. This was somewhat upheld by the results:
n=16: 11.5% improvement
n=19: 9.8% improvement
def check_numbers_match_group(number, digits):
number_search = str(number)
# new in v1.3
if len(number_search) != len(digits):
return False
for digit in digit_list:
if number_search.count(digit[0]) != digits.count(digit[1]):
return False
return True
I think you could use Multinomial theorem for some optimisation of cheacking if it is Narcissistic number.
you can calculate (a+b+c+..)^n- sum of non n-th powers values
for example for n=2 you should compare x and (a+b)^2-2*a*b where a and b is digits of number x
'''We can use Nar() function to calculate the Narcissitic Number.'''
import math
def Nar(num):
sum=0
n=len(str(num))
while n>0:
temp=num%10
sum=sum+math.pow(temp,n)
num=num/10
return sum
x=input()
y=Nar(x)
if x==y:
print x,' is a Narcissistic number'
else:
print x,' is not a Narcissistic number'