'Parameters
x : ndarray
Points at which to evaluate the cumulative distribution function.
mean : ndarray
Mean of the distribution
cov : array_like
Covariance matrix of the distribution
maxpts: integer
The maximum number of points to use for integration
abseps: float
Absolute error tolerance
releps: float
Relative error tolerance
Notes
As this function does no argument checking, it should not be
called directly; use \'cdf\' instead.
.. versionadded:: 1.0.0'

def _cdf(self, x, mean, cov, maxpts, abseps, releps):

    lower = np.full(mean.shape, (- np.inf))
    func1d = (lambda x_slice: mvn.mvnun(lower, x_slice, mean, cov, maxpts, abseps, releps)[0])
    out = np.apply_along_axis(func1d, (-1), x)
    return _squeeze_output(out)
