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Dear Sir, I have some test vectors as raw binary stream files. Hope you will try these, and I would love to hear your opinion.
the files are large# # ## **1. * **, so they are hosted on Google Drive]
These files are donated to the public domain, these may be useful as testing vectors to aid, train, and model development of specific domain(s) encoding.
These are the raw binary output files as result output of a generator (see below).
Filename: OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20220503012928.OUTFN_EXT Binary size: 160000000000 bits 2.1G Link (Google drive public share) : https://drive.google.com/file/d/1p4xYwedQnHPw692j6qibAEmZ4K342Sqc/view?usp=sharing sha384sum 3f36a74097af4448af092adab87025aa489133c3a25e60833462a4a476ceed42d98ff06cf4bd2c61a4076d0c5fecc19d Value Char Occurrences Fraction
0 8000001327 0.500000 1 7999998673 0.500000
Filename: OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20220428041502.OUTFN_EXT Binary size: 160000000000 bits 2.1G Link (Google drive public share) : https://drive.google.com/file/d/1bZbmyvhDhEc_8CBv2xWcjC4jhCzDKZNM/view?usp=sharing sha384sum 53810c0774d8c5cc3c41da23cb8a81230b44fdf44a852fc315daa7ad7335a6f67cd4389d6f6bc4b6c0c119b9ad43082d Value Char Occurrences Fraction
0 7999995089 0.500000 1 8000004911 0.500000
Filename: OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20220503150116.OUTFN_EXT Binary size: 160000000000 bits 2.1G Link (Google drive public share) : https://drive.google.com/file/d/1qfogi4qOkFtyQHSTU4BydVv30b_7Ru8e/view?usp=sharing sha384sum 9a9960fc73557c493bbe21180eba89c03f5f72f13df81e8219529741a76fea383a42a66856662acecc428e61db7da7ce Value Char Occurrences Fraction
0 8000005320 0.500000 1 7999994680 0.500000
Filename: OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20220505000308.OUTFN_EXT Binary size:160000000000 bits 2.1G Link (Google drive public share) : https://drive.google.com/file/d/1OASf6oCLQLx2zd6ENFvjGZGwdJ0SWveW/view?usp=sharing sha384sum 1f7c741d8ec99db7711e03f4593433d519244fd6487dfd5b8bfe946685717bf79005ecfb575465a6e770f1281c14c07d Value Char Occurrences Fraction
0 8000010560 0.500001 1 7999989440 0.499999
binary size:160000000000 bits 2.1G Filename: OUTFN_BASE-OUTFN_VER-OUTFN_VERMIN-20220505034220.OUTFN_EXT sha384sum c2af543e3aa00b7ccb9775f715461d46fda933e115ee2bee9ada5ed94e12272fe18f09146e6e2ae3055defd2e47e085e Link (Google drive public share) : https://drive.google.com/file/d/1ECmg69TYLTuJauIfuOrw--d9tk5mZ0Ui/view?usp=sharing Value Char Occurrences Fraction
0 8000045275 0.500003 1 7999954725 0.499997
- these are unprocessed files, no "whitewashing" has been applied to modulate (balance) symbol population densities or evaluate any conformance. Hence the use of "ent". - no specific parameters have been altered, no selective seed strategy (no count of jitter, cycles nor monotonic chrono - I generated these in the last few days.
page 269 // A brief history of the generator function: The generator was developed in 2016 as a part of a data science project to have an interactive re-keying facility to operating systems that would adapt the facility as a non-blocking character device. This would allow system control to configure processes to have designated access to separated pools of re-keying material, with configurable sources of 'statistical entropy' 'probabilistic randomness' and to yield complexity from added routines for asynchrony spatial, temporal, quantitative properties added to affect the algorithmic constructs that produce these permutable class streams derived from a non-perturbative domain. I would like to thank all the people that helped with this project, thanks To Ms. Tamara Kroonen for her contribution.
Thanks
Con Kolivas - the creator of lrzip Others listed in original README file. README Authors
For lrzip-next Peter Hyman (pete4abw on Guthub) pete@peterhyman.com Sun, 04 Jan 2009, README Mon, 28 Apr 2021: README.md
For lrzip Con Kolivas (ckolivas` on GitHub) kernel@kolivas.org Fri, 10 June 2016: README
Diehard, Dieharder, github.com, code.google.com - modified version of Robert G. Brown's "dieharder" tests for random number generators. - passed specific exhaustive t2d tests for P
aec
PractRand (github.com, sourceforge) - passed exhaustive tests for long range correlations
ent By John Walker http://www.fourmilab.ch/
- what bounds and properties - is there parity to witness flip of a symbol - visualize - rebuilding it's structure - striding strategies - surface mapping - photon pathway
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