Fast Shannon Entropy Calculation
Okay, so the answer is that there is no way to do it without calculating the log function, but if you pre-calculate the logs, it's not so bad. My buffer is 4096 bytes in size, so there are between 1..2048 of each possible 2-byte value. So the logs of 1/2048...
Compress/Decompress based on probability
encoding,decompression,entropy
Since you "seem to understand entropy", you can simply use the formula for entropy to do your homework. Here is a hint from Boltzmann's tombstone: ...
How to use GnuPG inside Docker containers, as it is missing entropy?
Missing Entropy Docker does not provide a virtual /dev/[u]random devices. If you haven't got enough entropy in the container, you haven't got enough entropy on the host. Check the contents of /proc/sys/kernel/random/entropy_avail, they should be pretty much the same on both the Docker host and container (if the number is...
How to write single bits to a file in C
You can't write individual bits to a file, the resolution is a single byte. If you want to write bits in sequence, you have to batch them up until you have a full byte, then write that. Psuedo-code (though C-like) for that would be along the lines of: currbyte =...
Counting Data based on Cover_Type using pandas
You can do the following import pandas as pd df = pd.read_csv('train_data.csv') grouped = df[['elevation','cover_type']].groupby(['elevation','cover_type'], as_index = False, sort = False)['cover_type'].count() ...
Hierarchical clustering using Mutual Information as similarity measure?
python,scipy,hierarchical-clustering,entropy
According to the paragraph on wikipedia that @cel pointed to, the Jaccard distance is a distance variant of Mutual Information. The module distance.pdist from scipy has support for computing the distance matrix using the Jaccard distance.
How to measure redundancy in code bases?
architecture,software-engineering,software-design,redundancy,entropy
What you are looking for is clone detection which is an established research area and there are a number of tools available to detect clones in you code. The central metric used to quantify the amount of redundancy in the code is called clone coverage. It measures the percentage of...
Reading large flat file of x,y,z into table of row names x, column names y, and values z
r,io,probability,sparse-matrix,entropy
Sample data Creating a data frame with only non-zero z values (suppose we can remove all of the zero lines from the flat file before importing data). N <- 50000 S <- N * 0.8 df_input <- data.frame( x = sample(1:N, S), y = sample(1:N, S), z = runif(S)) #...
Word VBA Script for Shannon entropy of the alphabetic characters
Well, from what I can tell you have 27 characters total each with a pre-defined value and you want to simply sum them up? Let's start with variables: dim characters(1 to 27) as double dim x as integer 'for looping dim total as double 'The final value Define the values:...
Image Parameters (Standard Deviation, Mean and Entropy) of an RGB Image
matlab,image-processing,rgb,entropy,standard-deviation
After reading the paper, because you are dealing with colour images, you have three channels of information to access. This means that you could alter one of the channels for a colour image and it could still affect the information it's trying to portray. The author wasn't very clear on...
MATLAB: Entropy associated to the intensity-gradient joint histogram
matlab,image-processing,entropy,information-theory
Yes, you can still use my post. Looking at your question above, the Kronecker Delta function is used such that for each i and j in your joint histogram, you want to search for all values where we encounter an intensity i in the image as well as the gradient...
Joint Entropy Performance in Julia
performance,julia-lang,entropy
Here are a few ideas to speed up your function. If the range of all the columns is roughly the same, you can move the extrema computations outside the loop and reuse the same h array. hist2d creates a new array: you can use hist2d! to reuse the previous one....
High entropy random data creating functions?
You are most likely looking for Pseudo-Random Number Generators. They are initialized by a seed, thus taking in a finite amount of entropy. Good generators have a decent entropy coming out, supposing you judge it only from its output (thus you ignore the seed and/or the algorithm to generate the...
entropy and histogram
matlab,image-processing,entropy
Recall from definition that the entropy (Shannon) is defined as: In this case, b = 2. What you need to do is assuming we have a grayscale image, we need to find the probability distribution function of the image, then use the above definition to calculate our entropy. The entropy...
Calculating Entropy
Ultimately I find no error in your code as it runs without error. The part I think you are missing is the calculation of the class frequencies and you will get your answer. Quickly running through the different objects you provide I suspect you are looking at buys. buys <-...
Matplotlib mlab entropy calculation incorrect?
The documentation is incorrect, as confirmed by @user333700. Following advice on the matplotlib-users mailing list, I have submitted a pull request to fix the documentation....
How to make in matlab three vectors with probabilities with a sum of one for each set?
matlab,vector,probability,entropy
You can generate a vector p of 3 real numbers between zero and one p = rand(1,3); then normalize p p = p / sum(p); Then p(1) + p(2) + p(3) is 1. EDIT: to respond to OP's comment N = 100; p = rand(N, 3); for k = 1:...
Probability of getting the same value using Math.random
javascript,random,probability,entropy
You're up against something called the birthday problem: even though there are 366 possible birthdays, when you get only 26 people in a room, the chance that some pair will have the same birthday is better than 50-50. In general, collisions are likely when your numbers approach the square root...
Entropy of pure split caculated to NaN
I would suggest you create your own log2 function function res=mylog2(a) res=log2(a); res(isinf(res))=0; end This function, while breaking the log2 behaviour, can be used in your specific example because you are multiplying the result with the inside of the log, thus making it zero. It is not "mathematically correct", but...
Entropy of IP packet information
Using numpy and the built-in collections module you can greatly simplify the code: import numpy as np import collections sample_ips = [ "131.084.001.031", "131.084.001.031", "131.284.001.031", "131.284.001.031", "131.284.001.000", ] C = collections.Counter(sample_ips) counts = np.array(C.values(),dtype=float) prob = counts/counts.sum() shannon_entropy = (-prob*np.log2(prob)).sum() print (shannon_entropy) ...