which sorting
Author
suppose i have an array with elements as 0 and 1 only. What will be the best way(running time) to sort it.
I thought about adding all elements and then filling arrays with no of 0's and then 1's.
Is there any better method than this??
You have a O(n) algorithm, it can't get any better than that in terms of time complexity.
This is how I would do it (assuming C++)
Two pointers are kept, one (p) scans over the entire array, and each time it encounters a 0, a 0 is written at *q, and q is moved one position to the right. After p has scanned over the entire array, q is used to change all remaining elements to 1.
This is how I would do it (assuming C++)
void sort(int* p, int size){ int* q = p; while ( size-- != 0 ) { if ( !*p++ ) { *q++ = 0; } } while ( p != q ) { *q++ = 1; }}Two pointers are kept, one (p) scans over the entire array, and each time it encounters a 0, a 0 is written at *q, and q is moved one position to the right. After p has scanned over the entire array, q is used to change all remaining elements to 1.
Author
I guess my algorithm requires O(2n) time...isn't it
for(i=0;i<size;i++) { num += arr; } for(i=0;i<size-num;i++) { arr =0; } for(i=num;i<size;i++) { arr =1; }
In a way, yes. But as far as I know, people consider O(n) = O(2n).
The algorithm I posted is O(2n) as well.
I wouldn't know which one of our algorithms performs better in practice.
The algorithm I posted is O(2n) as well.
I wouldn't know which one of our algorithms performs better in practice.
Author
I profiled it with only 10 elements
Time taken little more than 3 ms -My Version
Time Taken apprx 9 ms -Your version
Time taken little more than 3 ms -My Version
Time Taken apprx 9 ms -Your version
Usually, for profiling to be accurate, you should test with various array's size (and a lot bigger than 10 elements)
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And different array's setup (already sorted, 1-0-1-0-1-0..., random, etc.) to test worse case / best case scenarios!
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And different array's setup (already sorted, 1-0-1-0-1-0..., random, etc.) to test worse case / best case scenarios!
With 10000000 elements, using patterns [1,0,1,0,...], [1,1,1,...,0,0,0,...], [0,0,0,...,1,1,1,...] and [0,0,0,0,...], my version is faster, but not by much. Yours is faster with [1,1,1,1,...].
(Not that this way of benchmarking is in any way accurate...)
(Not that this way of benchmarking is in any way accurate...)
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