Thank you, Tim. My comments are below.
On 2009-08-07 13:19:47 -0400, Tim Chase <python.l...@tim.thechases.com> said:
After I have written a short Python script that hashes my textfile line by
line and collects the numbers next to the original, I checked what I got.
Instead of getting around 25% in each treatment, the range is 17.8%-31.3%.
That sounds suspiciously like 25% with a +/- 7% fluctuation one might
expect to see from non-random source data.
Could you help me where this range comes from? (If all my lines were
"42", I wouldn't hit this range. So it cannot be a rule. Right?)
Remember that your outputs are driven purely by your inputs in a
deterministic fashion -- if your inputs are purely random, then your
outputs should more closely match your expected bin'ing. If your
inputs aren't random, you get a taste of your own medicine ("my file
has just the number 42 on every line...why isn't my output random?").
And randomness-of-hash-output is a red herring since hashing is *not*
random.
Thanks, I tried to be correct with "pseudo-random". I understand that
everything is dependent on input. I want it to be the case. However, I
hoped that good hashes produce random-looking output from input with
very little variation. It would be strange if I could not get more than
18% of lines with a remainder of 3 (after division by 4), whatever hash
I try just because these are names of people.
Your input is also finite -- an aspect which leaves you a far cry from
the full hash-space. If an md5 has 32 bytes (256 bits) of data, your
input would have to cover 2**256 possible inputs to see the full
profile of your outputs. That's a lot of input :)
-tkc
OK, I understand. Could anyone suggest a better way to do this, then?
(Recap: random-looking, close-to uniform assignment of one number out
of four possibilities to strings.)
Thanks, everyone.
Laszlo
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