Bridges
=======

.. py:module:: GLDF.bridges
    :synopsis: Bridges for third-party package integration.

In :py:mod:`bridges <GLDF.bridges>` we provide wrappers for seamless integration with
CD-algorithm implemenations in other packages.

To integrate further third-party or your own algorithms and implemenations,
they only have to be wrapped to satisfy the format :py:type:`abstract_cd_t<GLDF.hccd.abstract_cd_t>`,
for more details see :ref:`label-abstract-cd`.


Tigramite Integration
---------------------

.. py:module:: GLDF.bridges.tigramite
    :synopsis: Bridge for tigramite integration.

.. py:currentmodule:: GLDF.bridges.tigramite

Bridge for `tigramite <https://jakobrunge.github.io/tigramite/>`_ integration.
Tigramite specializes to causal methods (including causal discovery) for *time-series*.
Our output-graphs (see :py:type:`graph_t<GLDF.hccd.graph_t>`) are in tigramite's internal format,
and can be used directly e.g. with effect-estimation or mediation code from tigramite.

.. autofunction:: alg_pcmci

.. autofunction:: alg_pcmciplus

.. autofunction:: alg_lpcmci


Causal Learn Integration
------------------------

.. py:module:: GLDF.bridges.causal_learn
    :synopsis: Bridge for causal-learn integration.

.. py:currentmodule:: GLDF.bridges.causal_learn

Bridge for `causal-learn <https://causal-learn.readthedocs.io/en/latest/index.html>`_ [ZHC+24]_ integration.
Causal Learn provides a broad range of causal methods, currently our framework is
ready for use with their basic IID-data constraint-based CD-method implementations.

.. autofunction:: alg_pc

.. autofunction:: alg_pc_stable

.. autofunction:: alg_fci