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import numpy as np
import scipy as sp
def get_1D_gauss(n,m,s):
"return a 1D histogram for a gaussian distribution (n bins, mean m and std s) "
x=np.arange(n,dtype=np.float64)
h=np.exp(-(x-m)**2/(2*s^2))
return h/h.sum()
def get_2D_samples_gauss(n,m,sigma):
"return samples from 2D gaussian (n samples, mean m and cov sigma) "
if np.isscalar(sigma):
sigma=np.array([sigma,])
if len(sigma)>1:
P=sp.linalg.sqrtm(sigma)
res= np.random.randn(n,2).dot(P)+m
else:
res= np.random.randn(n,2)*np.sqrt(sigma)+m
return res
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