openest.lincombo.continuous_sampled module

class openest.lincombo.continuous_sampled.ContinuousSampled(func)[source]

Bases: scipy.stats._distn_infrastructure.rv_continuous

guess_ranges(mini, maxi, count=10000)[source]
guess_ranges_gridded(mini, maxi, count=10000)[source]
pdf(xxs)[source]

Probability density function at x of the given RV.

Parameters:
  • x (array_like) – quantiles
  • arg2, arg3,.. (arg1,) – The shape parameter(s) for the distribution (see docstring of the instance object for more information)
  • loc (array_like, optional) – location parameter (default=0)
  • scale (array_like, optional) – scale parameter (default=1)
Returns:

pdf – Probability density function evaluated at x
Return type:

ndarray
prepare_draws(mini, maxi, count=10000)[source]
prepare_draws_gridded(mini, maxi, count=10000)[source]
rvs(size=1, random_state=None)[source]

Random variates of given type.

Parameters:
  • arg2, arg3,.. (arg1,) – The shape parameter(s) for the distribution (see docstring of the instance object for more information).
  • loc (array_like, optional) – Location parameter (default=0).
  • scale (array_like, optional) – Scale parameter (default=1).
  • size (int or tuple of ints, optional) – Defining number of random variates (default is 1).
  • random_state (None or int or np.random.RandomState instance, optional) – If int or RandomState, use it for drawing the random variates. If None, rely on self.random_state. Default is None.
Returns:

rvs – Random variates of given size.
Return type:

ndarray or scalar