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Get mean.py and cov.py from Mean and Covariance, then do:
mean.py
cov.py
# Import the mean and covariance from mean import M from cov import C from pymc.gp import * # Generate realizations f_list=[Realization(M, C) for i in range(3)] #### - Plot - #### if __name__ == '__main__': from pylab import * x=arange(-1.,1.,.01) clf() plot_envelope(M, C, x) for f in f_list: plot(x, f(x)) xlabel('x') ylabel('f(x)') title('Three realizations of the GP') axis('tight') # show()