r"""
Copulas are a type dependency structure imposed on independent variables to
achieve to more complex problems without adding too much complexity.

To construct a copula one needs a copula transformation and the
Copula wrapper::

    >>> dist = chaospy.Iid(chaospy.Uniform(), 2)
    >>> copula = chaospy.Gumbel(dist, theta=1.5)

The resulting copula is then ready for use::

    >>> print(numpy.around(copula.sample(5), 4))
    [[0.6536 0.115  0.9503 0.4822 0.8725]
     [0.6286 0.0654 0.96   0.5073 0.9705]]

"""
from .baseclass import Copula
from .archimedean import Archimedean

from .gumbel import Gumbel
from .clayton import Clayton
from .joe import Joe
from .nataf import Nataf
from .t_copula import TCopula

r"""
Copulas are a type dependency structure imposed on independent variables to
achieve to more complex problems without adding too much complexity.

To construct a copula one needs a copula transformation and the
Copula wrapper::

    >>> dist = chaospy.Iid(chaospy.Uniform(), 2)
    >>> copula = chaospy.Gumbel(dist, theta=1.5)

The resulting copula is then ready for use::

    >>> print(numpy.around(copula.sample(5), 4))
    [[0.6536 0.115  0.9503 0.4822 0.8725]
     [0.6286 0.0654 0.96   0.5073 0.9705]]

"""
from .baseclass import Copula
from .archimedean import Archimedean

from .gumbel import Gumbel
from .clayton import Clayton
from .joe import Joe
from .nataf import Nataf
from .t_copula import TCopula

Copulas are a type dependency structure imposed on independent variables to achieve to more complex problems without adding too much complexity.  To construct a copula one needs a copula transformation and the Copula wrapper::      >>> dist = chaospy.Iid(chaospy.Uniform(), 2)     >>> copula = chaospy.Gumbel(dist, theta=1.5)  The resulting copula is then ready for use::      >>> print(numpy.around(copula.sample(5), 4))     [[0.6536 0.115  0.9503 0.4822 0.8725]      [0.6286 0.0654 0.96   0.5073 0.9705]]