Package gmisclib :: Module entropy
[frames] | no frames]

Module entropy

source code

Functions
 
P(x) source code
 
multinomial_logp(x, cF) source code
 
multinomial_fixer(x, c) source code
 
information_gained(c, pc=None)
Suppose there is an experiment where you have N conditions and in each conditions there are M possible measurements.
source code
Variables
  __package__ = 'gmisclib'

Imports: math, random, Num, mcmc, mcmc_helper, gpkavg, gpkmisc


Function Details

information_gained(c, pc=None)

source code 

Suppose there is an experiment where you have N conditions and in each conditions there are M possible measurements. The outcomes are represented by c[N,M] matrix of counts: how many times you observe each possible measurement for each condition.

We want to ask what's the information gained by taking a measurement. We assume the probability of each condition is a pc[N] vector, which defaults to the frequencies in c. (We assume that the choice of condition is not a random variable, but is made in advance, like most experiments.)