booldog.io.biomodels
====================

.. py:module:: booldog.io.biomodels

.. autoapi-nested-parse::

   API to download and use SBML-qual models from bio.models directly.



Attributes
----------

.. autoapisummary::

   booldog.io.biomodels.logger
   booldog.io.biomodels.BIOMODELS_BASE_URL
   booldog.io.biomodels.MAMO_ACCESSIONS
   booldog.io.biomodels.EXAMPLE_MODEL_ID


Functions
---------

.. autoapisummary::

   booldog.io.biomodels.fetch_model
   booldog.io.biomodels.fetch_model_info
   booldog.io.biomodels._download


Module Contents
---------------

.. py:data:: logger

.. py:data:: BIOMODELS_BASE_URL
   :value: 'https://www.biomodels.org/'


.. py:data:: MAMO_ACCESSIONS
   :value: ['MAMO_0000030', 'MAMO_0000053']


   MAMO accessions for models that are compatible with BoolDog.

   The list contains the following accessions:
   * MAMO_0000030: logical model (http://identifiers.org/mamo/MAMO_0000030)
   * MAMO_0000053: Boolean model (http://identifiers.org/mamo/MAMO_0000053)

   :type: list

.. py:data:: EXAMPLE_MODEL_ID
   :value: 'BIOMD0000000562'


   BioModels model identifier for an example SBML-qual model (Chaouiya2013
   - EGF and TNFalpha mediated signalling pathway). See
   https://www.ebi.ac.uk/biomodels/BIOMD0000000562 for more details.

   :type: str

.. py:function:: fetch_model(model_id, sbml_file=None, local_file=None, check_modelling_approach=False)

   Fetch SBML from BioModels by model id

   :param model_id: BioModels model identifier (e.g. 'BIOMD0000000562')
   :type model_id: str
   :param sbml_file: Name of the file containing the model in the BioModels registry.
                     Optional, if not given, will be determined from the model info.
   :type sbml_file: str
   :param local_file: Name of path to save the downloaded model to. Optional, if not given
                      will save the model to the a file in the cwd with the name as on the
                      remote server.
   :type local_file: str or path-like
   :param check_modelling_approach: Whether to check modelling annotation "modellingApproach" falls into
                                    Boolean or logical modelling.
   :type check_modelling_approach: Bool

   :returns: **local_file** -- Name of the local file containing the download.
   :rtype: str

   .. rubric:: Notes

   This first collects the model info/metadata, and uses the 'files' --> 'main' attribute
   to find the first file with 'SBML'/'sbml' in the beginning of the description.

   Will always overwrite an existing file.


.. py:function:: fetch_model_info(model_id)

   Fetch model info/metadata from BioModels by model id.

   :param model_id: BioModels model identifier (e.g. 'BIOMD0000000562')
   :type model_id: str

   :returns: Model info/metadata as a dictionary.
   :rtype: dict


.. py:function:: _download(model_id, filename=None, local_file=None)

   Downloads a file from a model in BioModels

   :param model_id: BioModels model identifier (e.g. )
   :type model_id: str

   :returns: **local_file** -- Name of the local file containing the download.
   :rtype: str