medkit.text.spacy.displacy_utils
================================

.. py:module:: medkit.text.spacy.displacy_utils


Functions
---------

.. autoapisummary::

   medkit.text.spacy.displacy_utils.medkit_doc_to_displacy
   medkit.text.spacy.displacy_utils.entities_to_displacy


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

.. py:function:: medkit_doc_to_displacy(medkit_doc: medkit.core.text.TextDocument, entity_labels: list[str] | None = None, entity_formatter: Callable[[medkit.core.text.Entity], str] | None = None, max_gap_length: int = 3) -> dict[str, Any]

   
   Build data dictionary for displaCy to visualize a document.


   :Parameters:

       **medkit_doc** : TextDocument
           Document to visualize.

       **entity_labels** : list of str, optional
           Labels of entities to display. If `None`, all entities are displayed.

       **entity_formatter** : Callable, optional
           Optional function returning the text to display as label for a given
           entity. If `None`, the entity label will be used. Can be used for
           instance to display normalization information available in entity
           attributes.

       **max_gap_length** : int, default=3
           When cleaning up gaps in spans, spans around gaps smaller than `max_gap_length`
           will be merged.
           Cf :func:`~medkit.core.text.span_utils.clean_up_gaps_in_normalized_spans()`.

   :Returns:

       dict of str to Any
           Data to be passed to `displacy.render()` as `docs` argument
           (with `manual=True` and `style="ent"`)













   ..
       !! processed by numpydoc !!

.. py:function:: entities_to_displacy(entities: list[medkit.core.text.Entity], raw_text: str, entity_formatter: Callable[[medkit.core.text.Entity], str] | None = None, max_gap_length: int = 3) -> dict[str, Any]

   
   Build data dictionary for displaCy to visualize entities.


   :Parameters:

       **entities** : list of Entity
           Entities to visualize in text context.

       **raw_text** : str
           Initial document text from which entities where extracted and to which they spans refer
           (typically the `text` attribute of a :class:`~medkit.core.text.document.TextDocument`).

       **entity_formatter** : Callable, optional
           Optional function returning the text to display as label for a given
           entity. If `None`, the entity label will be used. Can be used for
           instance to display normalization information available in entity
           attributes.

       **max_gap_length** : int, default=3
           When cleaning up gaps in spans, spans around gaps smaller than `max_gap_length`
           will be merged.
           Cf :func:`~medkit.core.text.span_utils.clean_up_gaps_in_normalized_spans()`.

   :Returns:

       dict of str to Any
           Data to be passed to `displacy.render()` as `docs` argument
           (with `manual=True` and `style="ent"`)













   ..
       !! processed by numpydoc !!