Comments for Code crumbs, by Clément Pit-Claudel

Comment on Generating uniformly random data from skewed input: biased coins, loaded dice, skew correction, and the Von Neumann extractor by Do imperfections in dice make them unsuitable to make really good bitcoin private keys? - Finance Money

Thu, 27 Jan 2022 10:47:30 +0000

[…] a description of the technique here. Note that it depends on the die rolls being independent and identically distributed, so you would […]

Comment on How random is pseudo-random? Testing pseudo-random number generators and measuring randomness by Monte Carlo: what is a seed? - PhotoLens

Monte Carlo: what is a seed? - PhotoLens — Thu, 27 Jan 2022 04:25:44 +0000

[…] Image taken from here […]

Comment on Unscrambling shuffled text by Msot popele can undreatnsd tihs setennce

Msot popele can undreatnsd tihs setennce — Sat, 21 Dec 2019 00:50:43 +0000

[…] Steve Sachs set up a webpage for online garbling with AWK, and Clément Pit-Claudel offered Python code to ungarble garbled text. How would “ungarbler” do with the famous quote? See below. […]

Comment on Willy Wonka’s golden tickets: certainly the most profitable marketing campaign of all times by John

John — Sat, 15 Jun 2019 17:18:02 +0000

Loved stumbling across this thanks Clément.

I was on the computer with my sons whilst doing a Google image search for charlie and golden ticket. I wondered similarly about Veruc’s Dad’s capacity in this – thanks for examining the issue!

Best,

John

Comment on Modeling and measuring string comparison performance in C, C++, C# and Python. by Johnny Boy

Johnny Boy — Sun, 01 Apr 2018 07:12:32 +0000

If there are any C# programmers here who want to see how various methods stack up against other comparison methods, check out this blog post which benchmarks half a dozen ways:

http://cc.davelozinski.com/c-sharp/fastest-way-to-compare-strings

I like the “thinking outside the box” methods they tried like using HashSet keys (even though it isn’t practical in every day code).

Comment on Generating uniformly random data from skewed input: biased coins, loaded dice, skew correction, and the Von Neumann extractor by ray

ray — Sat, 31 Mar 2018 16:46:52 +0000

” which I will discuss in a future article, take the rejection rate down to 1.5% for perfectly balanced dice”

So I eagerly went to the home page to find this future article……only to discover that the blog ceased after only a few more articles. Bummer.

Comment on Modeling and measuring string comparison performance in C, C++, C# and Python. by segovia

segovia — Thu, 29 Mar 2018 21:02:41 +0000

Thanks for posting this interesting blog. I was wondering what about calculating the similarity of two strings instead of merely compare two strings (and get an answer of True or False). Do you think C# or C++ will be faster than Python in that case as well?

Comment on An experimental estimation of the entropy of English, in 50 lines of Python code by Hermawan Wiwit

Hermawan Wiwit — Fri, 24 Nov 2017 09:11:01 +0000

Wow, that’s a good article. What is the background of the problem?

Comment on An experimental estimation of the entropy of English, in 50 lines of Python code by XepherX

XepherX — Fri, 17 Feb 2017 07:38:23 +0000

Awesome post … thank you.

Comment on An experimental estimation of the entropy of English, in 50 lines of Python code by Mpho Kgoadi

Mpho Kgoadi — Wed, 19 Oct 2016 17:44:07 +0000

Hello

Thank you for giving a clear and concise explanation of information theory and especially the code. I am doing a final year project on information theory whilst trying to do the experiment for myself it somewhat harder to run as it is giving me an error

Thank you