@Sanjeet Gupta answer is good but could be condensed. This question is specifically asking about the “Fastest” way but I only see times on one answer so I’ll post a comparison of using scipy and numpy to the original poster’s entropy2 answer with slight alterations. Four different approaches: (1) scipy/numpy, (2) numpy/math, (3) pandas/numpy, (4) … Read more
As you know, “truly random” means each of the bits is independent of everything else as well as uniformly distributed. However, this ideal is hard, if not impossible, to achieve in practice. In general, the closest way to get “truly random data” in practice is to gather hard-to-guess bits from nondeterministic sources, then condense those … Read more
To calculate the joint entropy, you need to calculate the joint histogram between two images. The joint histogram is essentially the same as a normal 1D histogram but the first dimension logs intensities for the first image and the second dimension logs intensities for the second image. This is very similar to what is commonly … Read more
At the end: Calculate the “average” value for the array. Initialize a counter with zero, and for each of the array’s entries: add the entry’s difference to “average” to the counter. With some modifications you can get Shannon’s entropy: rename “average” to “entropy” (float) entropy = 0 for i in the array[256]:Counts do (float)p = … Read more
You should be able to select the faster-but-slightly-less-secure /dev/urandom on Linux using: -Djava.security.egd=file:/dev/urandom However, this doesn’t work with Java 5 and later (Java Bug 6202721). The suggested work-around is to use: -Djava.security.egd=file:/dev/./urandom (note the extra /./)