Op Thursday 30 Apr 2015 20:53 CEST schreef Dave Angel:
> On 04/30/2015 11:59 AM, Cecil Westerhof wrote:
>> I implemented happy_number function:
>> _happy_set = { '1' }
>> _unhappy_set = set()
>>
>> def happy_number(n):
>> """
>> Check if a number is a happy number
>> https://en.wikipedia.org/wiki/Happy_number
>> """
>>
>> def create_current(n):
>> current_array = sorted([value for value in str(n) if value != '0'])
>> return (current_array, ''.join(current_array))
>>
>> global _happy_set
>> global _unhappy_set
>>
>> current_run = set()
>> current_array, \
>> current_string = create_current(n)
>> if current_string in _happy_set:
>> return True
>> if current_string in _unhappy_set:
>> return False
>> while True:
>> current_run.add(current_string)
>> current_array, \
>> current_string = create_current(sum([int(value) ** 2
>> for value in current_string]))
>> if current_string in current_run | _unhappy_set:
>> _unhappy_set |= current_run
>> return False
>> if current_string in _happy_set:
>> _happy_set |= current_run
>> return True
>>
>> Besides it need some documentation: is it a good implementation? Or
>> are there things I should do differently?
>>
>> To decide for the values from 1 to 1E8 if it is happy or not, takes
>> 280 seconds. Not to bad I think. Also not very good.
>>
>
> First comment, if you're coding a complex implementation like this,
> take the time to do a brute force one as well. Then you can compare
> the results between brute force and your optimized one for all
> possible values, and make sure you haven't introduced any bugs.
Not a bad idea.
> My brute force looks like:
>
> #Dave's version, brute force
>
> def davea1(n):
> cache = []
> anum = str(n)
> newnum = 0
> while newnum != 1:
> newnum = sum(int(i)*int(i) for i in anum)
> anum = str(newnum)
> if newnum in cache:
> return False #not a happy number
> cache.append(newnum)
> return True #found a happy number
>
> I then tried an optimized one, and my speed is only about 10% faster
> than yours for 1e7 loops. I show it anyway, since I think it reads a
> little better. And readability counts much more than a little
> performance.
Well if it performs better and reads better you surely should show it.
> #optimizations: cached happy and unhappy sets sort the digits, and
> # compare only the sorted values, without zeroes davea_happy = {1}
> # davea_unhappy = set()
>
> SQUARES = dict((str(i), i*i) for i in xrange(10))
>
> def davea2(n):
> global davea_happy, davea_unhappy
> cache = set()
> newnum = n
> while newnum != 1:
> newnum = int("".join(sorted(str(newnum))))
> if newnum in davea_unhappy or newnum in cache:
> davea_unhappy |= cache
> return False #not a happy number
> if newnum in davea_happy:
> break
> cache.add(newnum)
> newnum = sum(SQUARES[ch] for ch in str(newnum))
> davea_happy |= cache
> return True #found a happy number
>
> Finally, I did some testing on Jon Ribben's version. His was
> substantially faster for smaller sets, and about the same for 10*7.
> So it's likely it'll be slower than yours and mine for 10**8. But
> the real reason I didn't like it was it produced a much larger set
> of happy_numbers, which could clog memory a lot sooner. For 10**7
> items, I had 3250 happy members, and 19630 unhappy. And Jon had
> 1418854 happy members.
My version has 1625 and 9814. I do not understand the difference.
--
Cecil Westerhof
Senior Software Engineer
LinkedIn: http://www.linkedin.com/in/cecilwesterhof
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