def correlation_matrix(nums_with_uncert):
ufuncs = list(map(to_uncertain_func, nums_with_uncert))<EOL>data = np.vstack([ufunc._mcpts for ufunc in ufuncs])<EOL>return np.corrcoef(data.T, rowvar=<NUM_LIT:0>)<EOL>
Calculate the correlation matrix of uncertain variables, oriented by the
order of the inputs

Parameters
----------
nums_with_uncert : array-like
    A list of variables that have an associated uncertainty

Returns
-------
corr_matrix : 2d-array-like
    A nested list containing covariance values

Example
-------

    >>> x = N(1, 0.1)
    >>> y = N(10, 0.1)
    >>> z = x + 2*y
    >>> correlation_matrix([x,y,z])
    [[ 0.99969486  0.00254001  0.4489385 ]
     [ 0.00254001  0.99982321  0.89458702]
     [ 0.4489385   0.89458702  1.        ]]