Generate random numbers that sum up to n










4















How to generate between 1 and n random numbers (positive integers greater than 0) which sum up to exactly n?



Example results if n=10:



10
2,5,3
1,1,1,1,1,1,1,1,1,1
1,1,5,1,1,1


Each of the permutations should have the same probability of occurring, however, I don't need it to be mathematically precise. So if the probabilities are not the same due to some modulo error, I don't care.



Is there a go-to algorithm for this? I only found algorithms where the number of values is fixed (i.e., give me exactly m random numbers which sum up to n).










share|improve this question



















  • 1





    @ceejayoz: I thought of this algorithm too, however, it looks like it's way off the "same probability for each permutation", isn't it? There are easily more than 10 permutations, but "10" has a probability of 1/10th. (I know, I said it doesn't have to be mathematically precise, but it shouldn't be way off)

    – D.R.
    Nov 15 '18 at 20:16







  • 1





    Just to clarify - you say "numbers" but your examples are all integer. Are you excluding floating point solutions? Are negative values allowed? How about zeros?

    – pjs
    Nov 15 '18 at 20:34






  • 2





    I'm unsure why people are close-voting the question as "too broad", how can I improve the question? Please leave a comment, thank you!

    – D.R.
    Nov 16 '18 at 10:51






  • 1





    No attempt and no tag to indicate what language you're writing this in. To me, this looks more like a Mathematics question than a programming one.

    – Toby Speight
    Nov 16 '18 at 11:24






  • 1





    @TobySpeight: In the end I want to have C# code, but I've omitted the C# tag as I'm interested in the algorithm and not a specific implementation. Are algorithm questions not part of StackOverflow? As for the attempt, if I can't find an approach myself, I'm not entitled to post here?

    – D.R.
    Nov 16 '18 at 11:26















4















How to generate between 1 and n random numbers (positive integers greater than 0) which sum up to exactly n?



Example results if n=10:



10
2,5,3
1,1,1,1,1,1,1,1,1,1
1,1,5,1,1,1


Each of the permutations should have the same probability of occurring, however, I don't need it to be mathematically precise. So if the probabilities are not the same due to some modulo error, I don't care.



Is there a go-to algorithm for this? I only found algorithms where the number of values is fixed (i.e., give me exactly m random numbers which sum up to n).










share|improve this question



















  • 1





    @ceejayoz: I thought of this algorithm too, however, it looks like it's way off the "same probability for each permutation", isn't it? There are easily more than 10 permutations, but "10" has a probability of 1/10th. (I know, I said it doesn't have to be mathematically precise, but it shouldn't be way off)

    – D.R.
    Nov 15 '18 at 20:16







  • 1





    Just to clarify - you say "numbers" but your examples are all integer. Are you excluding floating point solutions? Are negative values allowed? How about zeros?

    – pjs
    Nov 15 '18 at 20:34






  • 2





    I'm unsure why people are close-voting the question as "too broad", how can I improve the question? Please leave a comment, thank you!

    – D.R.
    Nov 16 '18 at 10:51






  • 1





    No attempt and no tag to indicate what language you're writing this in. To me, this looks more like a Mathematics question than a programming one.

    – Toby Speight
    Nov 16 '18 at 11:24






  • 1





    @TobySpeight: In the end I want to have C# code, but I've omitted the C# tag as I'm interested in the algorithm and not a specific implementation. Are algorithm questions not part of StackOverflow? As for the attempt, if I can't find an approach myself, I'm not entitled to post here?

    – D.R.
    Nov 16 '18 at 11:26













4












4








4


2






How to generate between 1 and n random numbers (positive integers greater than 0) which sum up to exactly n?



Example results if n=10:



10
2,5,3
1,1,1,1,1,1,1,1,1,1
1,1,5,1,1,1


Each of the permutations should have the same probability of occurring, however, I don't need it to be mathematically precise. So if the probabilities are not the same due to some modulo error, I don't care.



Is there a go-to algorithm for this? I only found algorithms where the number of values is fixed (i.e., give me exactly m random numbers which sum up to n).










share|improve this question
















How to generate between 1 and n random numbers (positive integers greater than 0) which sum up to exactly n?



Example results if n=10:



10
2,5,3
1,1,1,1,1,1,1,1,1,1
1,1,5,1,1,1


Each of the permutations should have the same probability of occurring, however, I don't need it to be mathematically precise. So if the probabilities are not the same due to some modulo error, I don't care.



Is there a go-to algorithm for this? I only found algorithms where the number of values is fixed (i.e., give me exactly m random numbers which sum up to n).







algorithm random






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 16 '18 at 13:55







D.R.

















asked Nov 15 '18 at 20:08









D.R.D.R.

9,5701450122




9,5701450122







  • 1





    @ceejayoz: I thought of this algorithm too, however, it looks like it's way off the "same probability for each permutation", isn't it? There are easily more than 10 permutations, but "10" has a probability of 1/10th. (I know, I said it doesn't have to be mathematically precise, but it shouldn't be way off)

    – D.R.
    Nov 15 '18 at 20:16







  • 1





    Just to clarify - you say "numbers" but your examples are all integer. Are you excluding floating point solutions? Are negative values allowed? How about zeros?

    – pjs
    Nov 15 '18 at 20:34






  • 2





    I'm unsure why people are close-voting the question as "too broad", how can I improve the question? Please leave a comment, thank you!

    – D.R.
    Nov 16 '18 at 10:51






  • 1





    No attempt and no tag to indicate what language you're writing this in. To me, this looks more like a Mathematics question than a programming one.

    – Toby Speight
    Nov 16 '18 at 11:24






  • 1





    @TobySpeight: In the end I want to have C# code, but I've omitted the C# tag as I'm interested in the algorithm and not a specific implementation. Are algorithm questions not part of StackOverflow? As for the attempt, if I can't find an approach myself, I'm not entitled to post here?

    – D.R.
    Nov 16 '18 at 11:26












  • 1





    @ceejayoz: I thought of this algorithm too, however, it looks like it's way off the "same probability for each permutation", isn't it? There are easily more than 10 permutations, but "10" has a probability of 1/10th. (I know, I said it doesn't have to be mathematically precise, but it shouldn't be way off)

    – D.R.
    Nov 15 '18 at 20:16







  • 1





    Just to clarify - you say "numbers" but your examples are all integer. Are you excluding floating point solutions? Are negative values allowed? How about zeros?

    – pjs
    Nov 15 '18 at 20:34






  • 2





    I'm unsure why people are close-voting the question as "too broad", how can I improve the question? Please leave a comment, thank you!

    – D.R.
    Nov 16 '18 at 10:51






  • 1





    No attempt and no tag to indicate what language you're writing this in. To me, this looks more like a Mathematics question than a programming one.

    – Toby Speight
    Nov 16 '18 at 11:24






  • 1





    @TobySpeight: In the end I want to have C# code, but I've omitted the C# tag as I'm interested in the algorithm and not a specific implementation. Are algorithm questions not part of StackOverflow? As for the attempt, if I can't find an approach myself, I'm not entitled to post here?

    – D.R.
    Nov 16 '18 at 11:26







1




1





@ceejayoz: I thought of this algorithm too, however, it looks like it's way off the "same probability for each permutation", isn't it? There are easily more than 10 permutations, but "10" has a probability of 1/10th. (I know, I said it doesn't have to be mathematically precise, but it shouldn't be way off)

– D.R.
Nov 15 '18 at 20:16






@ceejayoz: I thought of this algorithm too, however, it looks like it's way off the "same probability for each permutation", isn't it? There are easily more than 10 permutations, but "10" has a probability of 1/10th. (I know, I said it doesn't have to be mathematically precise, but it shouldn't be way off)

– D.R.
Nov 15 '18 at 20:16





1




1





Just to clarify - you say "numbers" but your examples are all integer. Are you excluding floating point solutions? Are negative values allowed? How about zeros?

– pjs
Nov 15 '18 at 20:34





Just to clarify - you say "numbers" but your examples are all integer. Are you excluding floating point solutions? Are negative values allowed? How about zeros?

– pjs
Nov 15 '18 at 20:34




2




2





I'm unsure why people are close-voting the question as "too broad", how can I improve the question? Please leave a comment, thank you!

– D.R.
Nov 16 '18 at 10:51





I'm unsure why people are close-voting the question as "too broad", how can I improve the question? Please leave a comment, thank you!

– D.R.
Nov 16 '18 at 10:51




1




1





No attempt and no tag to indicate what language you're writing this in. To me, this looks more like a Mathematics question than a programming one.

– Toby Speight
Nov 16 '18 at 11:24





No attempt and no tag to indicate what language you're writing this in. To me, this looks more like a Mathematics question than a programming one.

– Toby Speight
Nov 16 '18 at 11:24




1




1





@TobySpeight: In the end I want to have C# code, but I've omitted the C# tag as I'm interested in the algorithm and not a specific implementation. Are algorithm questions not part of StackOverflow? As for the attempt, if I can't find an approach myself, I'm not entitled to post here?

– D.R.
Nov 16 '18 at 11:26





@TobySpeight: In the end I want to have C# code, but I've omitted the C# tag as I'm interested in the algorithm and not a specific implementation. Are algorithm questions not part of StackOverflow? As for the attempt, if I can't find an approach myself, I'm not entitled to post here?

– D.R.
Nov 16 '18 at 11:26












2 Answers
2






active

oldest

votes


















7














Imagine the number n as a line built of n equal, indivisible sections. Your numbers are lengths of those sections that sum up to the whole. You can cut the original length between any two sections, or none.



This means there are n-1 potential cut points.



Choose a random n-1-bit number, that is a number between 0 and 2^(n-1); its binary representation tells you where to cut.



0 : 000 : [-|-|-|-] : 1,1,1,1
1 : 001 : [-|-|- -] : 1,1,2
3 : 011 : [-|- - -] : 1,3
5 : 101 : [- -|- -] : 2,2
7 : 111 : [- - - -] : 4


etc.




Implementation in python-3



import random


def perm(n, np):
p =
d = 1
for i in range(n):
if np % 2 == 0:
p.append(d)
d = 1
else:
d += 1
np //= 2
return p


def test(ex_n):
for ex_p in range(2 ** (ex_n - 1)):
p = perm(ex_n, ex_p)
print(len(p), p)


def randperm(n):
np = random.randint(0, 2 ** (n - 1))
return perm(n, np)

print(randperm(10))


you can verify it by generating all possible solutions for small n



test(4)


output:



4 [1, 1, 1, 1]
3 [2, 1, 1]
3 [1, 2, 1]
2 [3, 1]
3 [1, 1, 2]
2 [2, 2]
2 [1, 3]
1 [4]





share|improve this answer




















  • 1





    Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

    – Toby Speight
    Nov 16 '18 at 15:10







  • 1





    I love the way you have solved it and I really like how you illustrated the example.

    – maytham-ɯɐɥʇʎɐɯ
    Nov 16 '18 at 15:16


















0














Use a modulo.



This should make your day:



#include <stdio.h>
#include <stdlib.h>
#include <time.h>

int main()

srand(time(0));
int n=10;
int x=0; /* sum of previous random number */
while (x<n)
int r = rand() % (n-x) + 1;
printf("%d ", r);
x += r;

/* done */
printf("n");



Example output:



10
1 1 8
3 4 1 1 1
6 3 1
9 1
6 1 1 1 1
5 4 1





share|improve this answer


















  • 1





    This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

    – Toby Speight
    Nov 16 '18 at 15:14










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2 Answers
2






active

oldest

votes








2 Answers
2






active

oldest

votes









active

oldest

votes






active

oldest

votes









7














Imagine the number n as a line built of n equal, indivisible sections. Your numbers are lengths of those sections that sum up to the whole. You can cut the original length between any two sections, or none.



This means there are n-1 potential cut points.



Choose a random n-1-bit number, that is a number between 0 and 2^(n-1); its binary representation tells you where to cut.



0 : 000 : [-|-|-|-] : 1,1,1,1
1 : 001 : [-|-|- -] : 1,1,2
3 : 011 : [-|- - -] : 1,3
5 : 101 : [- -|- -] : 2,2
7 : 111 : [- - - -] : 4


etc.




Implementation in python-3



import random


def perm(n, np):
p =
d = 1
for i in range(n):
if np % 2 == 0:
p.append(d)
d = 1
else:
d += 1
np //= 2
return p


def test(ex_n):
for ex_p in range(2 ** (ex_n - 1)):
p = perm(ex_n, ex_p)
print(len(p), p)


def randperm(n):
np = random.randint(0, 2 ** (n - 1))
return perm(n, np)

print(randperm(10))


you can verify it by generating all possible solutions for small n



test(4)


output:



4 [1, 1, 1, 1]
3 [2, 1, 1]
3 [1, 2, 1]
2 [3, 1]
3 [1, 1, 2]
2 [2, 2]
2 [1, 3]
1 [4]





share|improve this answer




















  • 1





    Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

    – Toby Speight
    Nov 16 '18 at 15:10







  • 1





    I love the way you have solved it and I really like how you illustrated the example.

    – maytham-ɯɐɥʇʎɐɯ
    Nov 16 '18 at 15:16















7














Imagine the number n as a line built of n equal, indivisible sections. Your numbers are lengths of those sections that sum up to the whole. You can cut the original length between any two sections, or none.



This means there are n-1 potential cut points.



Choose a random n-1-bit number, that is a number between 0 and 2^(n-1); its binary representation tells you where to cut.



0 : 000 : [-|-|-|-] : 1,1,1,1
1 : 001 : [-|-|- -] : 1,1,2
3 : 011 : [-|- - -] : 1,3
5 : 101 : [- -|- -] : 2,2
7 : 111 : [- - - -] : 4


etc.




Implementation in python-3



import random


def perm(n, np):
p =
d = 1
for i in range(n):
if np % 2 == 0:
p.append(d)
d = 1
else:
d += 1
np //= 2
return p


def test(ex_n):
for ex_p in range(2 ** (ex_n - 1)):
p = perm(ex_n, ex_p)
print(len(p), p)


def randperm(n):
np = random.randint(0, 2 ** (n - 1))
return perm(n, np)

print(randperm(10))


you can verify it by generating all possible solutions for small n



test(4)


output:



4 [1, 1, 1, 1]
3 [2, 1, 1]
3 [1, 2, 1]
2 [3, 1]
3 [1, 1, 2]
2 [2, 2]
2 [1, 3]
1 [4]





share|improve this answer




















  • 1





    Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

    – Toby Speight
    Nov 16 '18 at 15:10







  • 1





    I love the way you have solved it and I really like how you illustrated the example.

    – maytham-ɯɐɥʇʎɐɯ
    Nov 16 '18 at 15:16













7












7








7







Imagine the number n as a line built of n equal, indivisible sections. Your numbers are lengths of those sections that sum up to the whole. You can cut the original length between any two sections, or none.



This means there are n-1 potential cut points.



Choose a random n-1-bit number, that is a number between 0 and 2^(n-1); its binary representation tells you where to cut.



0 : 000 : [-|-|-|-] : 1,1,1,1
1 : 001 : [-|-|- -] : 1,1,2
3 : 011 : [-|- - -] : 1,3
5 : 101 : [- -|- -] : 2,2
7 : 111 : [- - - -] : 4


etc.




Implementation in python-3



import random


def perm(n, np):
p =
d = 1
for i in range(n):
if np % 2 == 0:
p.append(d)
d = 1
else:
d += 1
np //= 2
return p


def test(ex_n):
for ex_p in range(2 ** (ex_n - 1)):
p = perm(ex_n, ex_p)
print(len(p), p)


def randperm(n):
np = random.randint(0, 2 ** (n - 1))
return perm(n, np)

print(randperm(10))


you can verify it by generating all possible solutions for small n



test(4)


output:



4 [1, 1, 1, 1]
3 [2, 1, 1]
3 [1, 2, 1]
2 [3, 1]
3 [1, 1, 2]
2 [2, 2]
2 [1, 3]
1 [4]





share|improve this answer















Imagine the number n as a line built of n equal, indivisible sections. Your numbers are lengths of those sections that sum up to the whole. You can cut the original length between any two sections, or none.



This means there are n-1 potential cut points.



Choose a random n-1-bit number, that is a number between 0 and 2^(n-1); its binary representation tells you where to cut.



0 : 000 : [-|-|-|-] : 1,1,1,1
1 : 001 : [-|-|- -] : 1,1,2
3 : 011 : [-|- - -] : 1,3
5 : 101 : [- -|- -] : 2,2
7 : 111 : [- - - -] : 4


etc.




Implementation in python-3



import random


def perm(n, np):
p =
d = 1
for i in range(n):
if np % 2 == 0:
p.append(d)
d = 1
else:
d += 1
np //= 2
return p


def test(ex_n):
for ex_p in range(2 ** (ex_n - 1)):
p = perm(ex_n, ex_p)
print(len(p), p)


def randperm(n):
np = random.randint(0, 2 ** (n - 1))
return perm(n, np)

print(randperm(10))


you can verify it by generating all possible solutions for small n



test(4)


output:



4 [1, 1, 1, 1]
3 [2, 1, 1]
3 [1, 2, 1]
2 [3, 1]
3 [1, 1, 2]
2 [2, 2]
2 [1, 3]
1 [4]






share|improve this answer














share|improve this answer



share|improve this answer








edited Nov 16 '18 at 15:08









Toby Speight

17.1k134267




17.1k134267










answered Nov 15 '18 at 21:38









Milo BemMilo Bem

822418




822418







  • 1





    Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

    – Toby Speight
    Nov 16 '18 at 15:10







  • 1





    I love the way you have solved it and I really like how you illustrated the example.

    – maytham-ɯɐɥʇʎɐɯ
    Nov 16 '18 at 15:16












  • 1





    Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

    – Toby Speight
    Nov 16 '18 at 15:10







  • 1





    I love the way you have solved it and I really like how you illustrated the example.

    – maytham-ɯɐɥʇʎɐɯ
    Nov 16 '18 at 15:16







1




1





Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

– Toby Speight
Nov 16 '18 at 15:10






Thanks for adding the explanation - that's a really good answer now. And we don't need to generate all n bits of the decision tree at once - if we have a source of random bits, we can just take them as we need them. That can avoid the overhead of huge arithmetic numbers which we won't be using for arithmetic.

– Toby Speight
Nov 16 '18 at 15:10





1




1





I love the way you have solved it and I really like how you illustrated the example.

– maytham-ɯɐɥʇʎɐɯ
Nov 16 '18 at 15:16





I love the way you have solved it and I really like how you illustrated the example.

– maytham-ɯɐɥʇʎɐɯ
Nov 16 '18 at 15:16













0














Use a modulo.



This should make your day:



#include <stdio.h>
#include <stdlib.h>
#include <time.h>

int main()

srand(time(0));
int n=10;
int x=0; /* sum of previous random number */
while (x<n)
int r = rand() % (n-x) + 1;
printf("%d ", r);
x += r;

/* done */
printf("n");



Example output:



10
1 1 8
3 4 1 1 1
6 3 1
9 1
6 1 1 1 1
5 4 1





share|improve this answer


















  • 1





    This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

    – Toby Speight
    Nov 16 '18 at 15:14















0














Use a modulo.



This should make your day:



#include <stdio.h>
#include <stdlib.h>
#include <time.h>

int main()

srand(time(0));
int n=10;
int x=0; /* sum of previous random number */
while (x<n)
int r = rand() % (n-x) + 1;
printf("%d ", r);
x += r;

/* done */
printf("n");



Example output:



10
1 1 8
3 4 1 1 1
6 3 1
9 1
6 1 1 1 1
5 4 1





share|improve this answer


















  • 1





    This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

    – Toby Speight
    Nov 16 '18 at 15:14













0












0








0







Use a modulo.



This should make your day:



#include <stdio.h>
#include <stdlib.h>
#include <time.h>

int main()

srand(time(0));
int n=10;
int x=0; /* sum of previous random number */
while (x<n)
int r = rand() % (n-x) + 1;
printf("%d ", r);
x += r;

/* done */
printf("n");



Example output:



10
1 1 8
3 4 1 1 1
6 3 1
9 1
6 1 1 1 1
5 4 1





share|improve this answer













Use a modulo.



This should make your day:



#include <stdio.h>
#include <stdlib.h>
#include <time.h>

int main()

srand(time(0));
int n=10;
int x=0; /* sum of previous random number */
while (x<n)
int r = rand() % (n-x) + 1;
printf("%d ", r);
x += r;

/* done */
printf("n");



Example output:



10
1 1 8
3 4 1 1 1
6 3 1
9 1
6 1 1 1 1
5 4 1






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answered Nov 15 '18 at 20:50









user803422user803422

9722724




9722724







  • 1





    This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

    – Toby Speight
    Nov 16 '18 at 15:14












  • 1





    This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

    – Toby Speight
    Nov 16 '18 at 15:14







1




1





This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

– Toby Speight
Nov 16 '18 at 15:14





This seems biased towards the shorter sequences; only one of the example outputs begins with 1, but we'd expect about half of them to begin with 1 if it selected fairly from all possibilities.

– Toby Speight
Nov 16 '18 at 15:14

















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