def add_name(self, cui, source_val, text=None, is_pref_name=False, tkn_inds=None, text_inds=None,
spacy_doc=None, lr=None, anneal=None, negative=False, only_new=False, desc=None, tui=None,
manually_created=False):
""" Adds a new concept or appends the name to an existing concept
if the cui already exists in the DB.
cui: Concept uniqe ID
source_val: Source value in the text
text: the text of a document where source_val was found
"""
# First add the name, get bac all cuis that link to this name
all_cuis = self._add_name(cui, source_val, is_pref_name, only_new=only_new, desc=desc, tui=tui)
# Now add context if text is present
if (text is not None and (source_val in text or text_inds)) or \
(spacy_doc is not None and (text_inds or tkn_inds)):
if spacy_doc is None:
spacy_doc = self(text)
if tkn_inds is None:
tkn_inds = tkn_inds_from_doc(spacy_doc=spacy_doc, text_inds=text_inds,
source_val=source_val)
if tkn_inds is not None and len(tkn_inds) > 0:
self.add_concept_cntx(cui, text, tkn_inds, spacy_doc=spacy_doc, lr=lr, anneal=anneal,
negative=negative)
if manually_created:
all_cuis.remove(cui)
for _cui in all_cuis:
self.add_concept_cntx(_cui, text, tkn_inds, spacy_doc=spacy_doc, lr=lr, anneal=anneal,
negative=True)
def add_name(self, cui, source_val, text=None, is_pref_name=False, tkn_inds=None, text_inds=None, spacy_doc=None, lr=None, anneal=None, negative=False, only_new=False):
""" Adds a new concept or appends the name to an existing concept
if the cui already exists in the DB.
cui: Concept uniqe ID
source_val: Source value in the text
text: the text of a document where source_val was found
"""
# First add the name
self._add_name(cui, source_val, is_pref_name, only_new=only_new)
# Now add context if text is present
if text is not None and (source_val in text or text_inds):
if spacy_doc is None:
spacy_doc = self(text)
if tkn_inds is None:
tkn_inds = tkn_inds_from_doc(spacy_doc=spacy_doc, text_inds=text_inds,
source_val=source_val)
if tkn_inds is not None and len(tkn_inds) > 0:
self.add_concept_cntx(cui, text, tkn_inds, spacy_doc=spacy_doc, lr=lr, anneal=anneal,
negative=negative)
def add_name(self,
cui,
source_val,
text=None,
is_pref_name=False,
tkn_inds=None,
text_inds=None,
spacy_doc=None,
lr=None,
anneal=None,
negative=False,
only_new=False,
desc=None,
tui=None,
manually_created=False):
r'''
This function will add a `name` (source_val) to a CUI (existing or new). It will teach medcat
that this source_val is linked to this CUI.
Args:
cui (str):
The CUI to which to add the name
source_val (str):
The `name` or span or source_value that will be linked to the cui
text (str, optional):
Text in which an example of this source_val can be found. Used for supervised/online
training. This is basically one sample in a dataset for supervised training.
is_pref_name (boolean):
Is this source_val the prefered `name` for this CUI (concept)
tkn_inds (list of ints, optional):
Should be in the form: [3, 4, 5, ...]. This should be used only if you are providing a spacy_doc also.
It gives the indicies of the tokens in a spacy document where the source_val can be found.
text_inds (list, optional):
A list that has only two values the start index for this `source_val` in the `text` and the end index.
Used if you are not providing a spacy_doc. But are providing a `text` - it is optional and if not provided
medcat will try to automatically find the start and end index.
spacy_doc ()
TODO:
lr (float):
The learning rate that will be used if you are providing the `text` that will be used for supervised/active
learning.
only_new (bool):
Only add the name if it does not exist in the current CDB and is not linked
to any concept (CUI) in the current CDB.
desc (str):
Description for this concept
tui (str):
Semenantic Type identifer for this concept, should be a TUI that exisit in the
current CDB. Have a look at cdb.tui2names - for a list of all existing TUIs
in the current CDB.
Examples:
Do not use.
'''
# First add the name, get bac all cuis that link to this name
all_cuis = self._add_name(cui,
source_val,
is_pref_name,
only_new=only_new,
desc=desc,
tui=tui)
# Now add context if text is present
if (text is not None and (source_val in text or text_inds)) or \
(spacy_doc is not None and (text_inds or tkn_inds)):
if spacy_doc is None:
spacy_doc = self(text)
if tkn_inds is None:
tkn_inds = tkn_inds_from_doc(spacy_doc=spacy_doc,
text_inds=text_inds,
source_val=source_val)
if tkn_inds is not None and len(tkn_inds) > 0:
self.add_concept_cntx(cui,
text,
tkn_inds,
spacy_doc=spacy_doc,
lr=lr,
anneal=anneal,
negative=negative)
if manually_created:
all_cuis.remove(cui)
for _cui in all_cuis:
self.add_concept_cntx(_cui,
text,
tkn_inds,
spacy_doc=spacy_doc,
lr=lr,
anneal=anneal,
negative=True)