Fatih Karakurt karakfa

## cov2corr.py
# extract correlation matrix from covariance matrix
def cov2corr(cov):
    d = np.diagonal(cov)
    s = np.reciprocal(np.sqrt(d))
    return np.multiply(s,np.multiply(s,cov).T)

## gcd.hs
-- Knuth's way
-- from the blog post http://videlalvaro.github.io/2016/10/knuth-first-erlang-programmer.html

gcd m n = f m n 0 1
   where f m n r 1 = f m n (mod m n) 2
         f m n 0 2 = n
         f m n r 2 = f n r r 1

## ExponentialDistribution.ipynb

      
        
          
            
              
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                karakfa
                / ExponentialDistribution.ipynb
            
            
              Created
              October 21, 2015 20:35
            
              
                exponential distribution
              
          
        
      
        
  
    
    

          
    
      
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	# extract correlation matrix from covariance matrix
	def cov2corr(cov):
	d = np.diagonal(cov)
	s = np.reciprocal(np.sqrt(d))
	return np.multiply(s,np.multiply(s,cov).T)
	-- Knuth's way
	-- from the blog post http://videlalvaro.github.io/2016/10/knuth-first-erlang-programmer.html

	gcd m n = f m n 0 1
	where f m n r 1 = f m n (mod m n) 2
	f m n 0 2 = n
	f m n r 2 = f n r r 1