I'm currently analyzing a 16 bit binary string - something like 0010001010110100. I have approximately 30 of these strings. I have written a simple program in Matlab that counts the numbers of 1's in each bit for all 30 strings.
So, for example:
1 30
2 15
3 1
4 10
etc
I want to generate more strings (100s) that roughly follow the frequency distribution above. Is there a Matlab (or Python or R) command that does that?
What I'm looking for is something like this: http://www.prenhall.com/weiss_dswin/html/simulate.htm
In MATLAB: just use < (or lt, less than) on rand:
len = 16; % string length
% counts of 1s for each bit (just random integer here)
counts = randi([0 30],[1 len]);
% probability for 1 in each bit
prob = counts./30;
% generate 100 random strings
n = 100;
moreStrings = rand(100,len);
% for each bit check if number is less than the probability of the bit
moreStrings = bsxfun(@lt, moreStrings, prob); % lt(x,y) := x < y
In Python:
import numpy as np
len = 16 # string length
# counts of 1's for each bit (just random integer here)
counts = np.random.randint(0, 30, (1,16)).astype(float)
# probability for 1 in each bit
prob = counts/30
# generate 100 random strings
n = 100
moreStrings = np.random.rand(100,len)
# for each bit check if number is less than the probability of the bit
moreStrings = moreStrings < prob