A quick generation of a Gaussian data with small noise

generate_randomized_Gaussian.py

import numpy as np

x = np.linspace(0, 10, 51)
A = 42
mu = 4.2
sigma = 0.666
c = 10

sig_y = 3*np.ones(len(x)) #np.sqrt(y)

y = np.round(
  np.random.normal(A * np.exp(-0.5*((x-mu)/sigma)**2) + c, sig_y)
)
np.savetxt('gaussianData.xye', np.c_[x, y, sig_y], 
  header='x\ty\tsy',
  delimiter='\t',
  fmt='%10.5f'
)