From: David Mertz <voting-project_at_gnosis_dot_cx>

Date: Tue May 04 2004 - 23:48:45 CDT

Received on Mon May 31 23:17:14 2004

Date: Tue May 04 2004 - 23:48:45 CDT

OK, new version of election-entropy.py. The latest incorporates

Arthur's idea for self-delimiting encoding, now that I've worked out

his description of the formula for optimal self-delimiting encoding

size. Unlike the globally optimal (even if obeying bit-boundaries),

the encoded size depends on the symbology used (specifically, the

alphabet size). The latest version of the script lets you (optionally)

specify an alphabet size. The script docstring gives its usage:

USAGE: election-entropy.py [alphabet_size] [-verbose] <

election.summary

Where the input data has lines of the form:

contest-type slots [candidates] [# comment]

"Verbose" means that it prints out the encoded size of each contest,

not just a summary. If not specified, we assume a hexadecimal 16-char

encoding. Note that Code128 (our demo barcode) uses a 10-char

symbology (decimal digits), and PDF417 uses a 100-200 char alphabet.

For example:

$ ./election-entropy.py 10 < demo-election.data

Election summary for OVC demo ballot (write-ins count as candidate)

269995136716800 distinct votes are possible

Optimal encoding is approximately: 48 bits

Contests at bit-boundaries, approx: 53 bits

Self-delimited (10 char symbology): 88 bits

$ ./election-entropy.py 200 < demo-election.data

Election summary for OVC demo ballot (write-ins count as candidate)

269995136716800 distinct votes are possible

Optimal encoding is approximately: 48 bits

Contests at bit-boundaries, approx: 53 bits

Self-delimited (200 char symbology): 128 bits

See the beginning of this thread in the archive for a sample data file

(and write your own to match an historical election).

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