copulas package

Subpackages

• copulas.bivariate package
  • Submodules
    • copulas.bivariate.base module
    • copulas.bivariate.clayton module
    • copulas.bivariate.frank module
    • copulas.bivariate.gumbel module
    • copulas.bivariate.independence module
    • copulas.bivariate.utils module
  • Module contents
• copulas.multivariate package
  • Submodules
    • copulas.multivariate.base module
    • copulas.multivariate.gaussian module
    • copulas.multivariate.tree module
    • copulas.multivariate.vine module
  • Module contents
• copulas.optimize package
  • Module contents
• copulas.univariate package
  • Submodules
    • copulas.univariate.base module
    • copulas.univariate.beta module
    • copulas.univariate.gamma module
    • copulas.univariate.gaussian module
    • copulas.univariate.gaussian_kde module
    • copulas.univariate.log_laplace module
    • copulas.univariate.selection module
    • copulas.univariate.student_t module
    • copulas.univariate.truncated_gaussian module
    • copulas.univariate.uniform module
  • Module contents

Submodules

• copulas.datasets module
• copulas.visualization module

Module contents

Top-level package for Copulas.

exception copulas.NotFittedError

Bases: Exception

NotFittedError class.

copulas.check_valid_values(function)

Raise an exception if the given values are not supported.

Parameters

function (callable) – Method whose unique argument is a numpy.array-like object.

Returns

Decorated function

Return type

callable

Raises

ValueError – If there are missing or invalid values or if the dataset is empty.

copulas.get_instance(obj, **kwargs)

Create new instance of the obj argument.

Parameters

obj (str, type, instance) –

copulas.get_qualified_name(_object)

Return the Fully Qualified Name from an instance or class.

copulas.random_state(function)

Set the random state before calling the function.

Parameters

function (Callable) – The function to wrap around.

copulas.scalarize(function)

Allow methods that only accepts 1-d vectors to work with scalars.

Parameters

function (callable) – Function that accepts and returns vectors.

Returns

Decorated function that accepts and returns scalars.

Return type

callable

copulas.set_random_state(random_state, set_model_random_state)

Context manager for managing the random state.

Parameters

• random_state (int or np.random.RandomState) – The random seed or RandomState.

• set_model_random_state (function) – Function to set the random state on the model.

copulas.store_args(__init__)

Save *args and **kwargs used in the __init__ of a copula.

Parameters

__init__ (callable) – __init__ function to store their arguments.

Returns

Decorated __init__ function.

Return type

callable

copulas.validate_random_state(random_state)

Validate random state argument.

Parameters

random_state (int, numpy.random.RandomState, tuple, or None) – Seed or RandomState for the random generator.

Output:

numpy.random.RandomState

copulas.vectorize(function)

Allow a method that only accepts scalars to accept vectors too.

This decorator has two different behaviors depending on the dimensionality of the array passed as an argument:

1-d array

It will work under the assumption that the function argument is a callable with signature:

function(self, X, *args, **kwargs)

where X is an scalar magnitude.

In this case the arguments of the input array will be given one at a time, and both the input and output of the decorated function will have shape (n,).

2-d array

It will work under the assumption that the function argument is a callable with signature:

function(self, X0, ..., Xj, *args, **kwargs)

where Xi are scalar magnitudes.

It will pass the contents of each row unpacked on each call. The input is espected to have shape (n, j), the output a shape of (n,)

It will return a function that is guaranteed to return a numpy.array.

Parameters

function (callable) – Function that only accept and return scalars.

Returns

Decorated function that can accept and return numpy.array.

Return type

callable