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Hamming numbers: Difference between revisions
→Alternate version using "Cyclic Iterators"
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===Alternate version using "Cyclic Iterators"===
The original author is Raymond Hettinger and the code was first published [http://code.activestate.com/recipes/576961/ here] under the MIT license. This implementation is quite memory efficient.
This implementation is the fastest of the Python implementations and is quite memory efficient.▼
<lang python>from itertools import tee, chain, groupby
from heapq import merge
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Results are the same as before.
===Alternate version from the Java version===
▲This
<lang python>import psyco
def hamming(limit):
h = [1] * limit
x2, x3, x5 = 2, 3, 5
i = j = k = 0
for n in xrange(1, limit):
h[n] = min(x2, x3, x5)
if x2 == h[n]:
i += 1
x2 = 2 * h[i]
if x3 == h[n]:
j += 1
x3 = 3 * h[j]
if x5 == h[n]:
k += 1
x5 = 5 * h[k]
return h[-1]
psyco.bind(hamming)
print [hamming(i) for i in xrange(1, 21)]
print hamming(1691)
print hamming(1000000)</lang>
=={{header|R}}==
Recursively find the Hamming numbers below <math>2^{31}</math>. Works for larger limits, however to find the <math>1000000^{th}</math> value, one needs guess the correct limit
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