Fix behavior, disorder and qualifier pipes

[Thomzoy]

Description

Fix #287

This PR has two main goals:

1) Impove and simplify the behaviors and disorders pipes 2) To do so, add a process method to the RuleBasedQualifier that only returns qualified entities and token without actually tagging them (defering this task to the __call__ method). This is useful when pipes need to use qualifier pipes internaly, but doesn't want to tag the original document.

1) Impove and simplify the behaviors and disorders pipes

1.1) Simplify the status attribute for disorder and behavior pipes

Currently, this status can take, for most disorder pipes, the values "PRESENT" or "ABSENT". I argue that:

• The "ABSENT" value is never used (it was in the behavior pipe, but see below)
• The "PRESENT" value isn't informative and can be misleading. For instance, "Tabac: 0" currently set status to "PRESENT" (and _.negation to True)

As such, we can simplify those and especialy remove this case with both "PRESENT" and "negation":

• By default, the status is set to None
• Instead of pipes setting status to "ABSENT", we now set ent._.negation to True and leave status to None

1.2) Fixing some issues with the alcohol and tobacco pipes, namely:

• Use the NegationQualifier to qualify the abstinence status, which we currently do directly with a basic regex
• As staed above, remove the use of status="ABSENT" in favor of using ent._.negation

⚠️ The negation pipe mentionned above will only be used to determine the abstinence status. As for any NER pipe, qualifiers should still be run after.

2) Add a process method to the RuleBasedQualifier

As stated above the tobacco and alcohol pipes now use the NegationQualifier internaly. They both need to qualify the patient's abstience, which can be negated (e.g. "Patient fumeur non sevré") but without tagging the document. To this end (and as this use case may be more broad than those two pipes), we implemented a process method to the RuleBasedQualifier that only returns qualified entities and token without actually tagging them (defering this task to the __call__ method).

Checklist

• [x] If this PR is a bug fix, the bug is documented in the test suite.
• [x] Changes were documented in the changelog (pending section).
• [x] If necessary, changes were made to the documentation (eg new pipeline).

[Thomzoy]

As using negation inside the TobaccoMatcher required to run nlp(span) (so that the original document isn't tagged with negation), I propose an update on the RuleBasedQualifier by adding a get_qualified method which returns a typed dictionary with mandatory keys tokens and ents, each containing a list of tuples. For instance,

# In qualifiers/base.py
class BaseQualifierResults(NamedTuple):
    tokens: List[NamedTuple]
    ents: List[NamedTuple]

# in negation.py
TokenNegationResults = namedtuple("TokenNegationResults", ["token", "negation"])
EntsNegationResults = namedtuple("TokenNegationResults", ["ent", "negation", "cues"])

class NegationResults(BaseQualifierResults):
    tokens: List[TokenNegationResults]
    ents: List[EntsNegationResults]

Most of the logic will be done in the get_qualified method, but no tagging.
Tagging is still done in the process method, which calls get_qualified

@percevalw

[percevalw]

Many of our pipelines actually use the process method to extract entities and __call__ to annotate on the document (ex with eds.dates or the generic eds.matcher), maybe we could continue in this direction ? so tag in __call__ and extract in process @Thomzoy

For the output of the extraction step (get_qualified in your comment), maybe we can find a way to type hint tokens and ents ? otherwise I'm ok with it !

[Thomzoy]

Many of our pipelines actually use the process method to extract entities and __call__ to annotate on the document (ex with eds.dates or the generic eds.matcher), maybe we could continue in this direction ? so tag in __call__ and extract in process @Thomzoy

For the output of the extraction step (get_qualified in your comment), maybe we can find a way to type hint tokens and ents ? otherwise I'm ok with it !

Fine with me ! For instance:

In qualifiers/base

@dataclass
class BaseTokenQualifierResults:
    token: Token

@dataclass
class BaseEntQualifierResults:
    ent: Span

@dataclass
class BaseQualifierResults:
    tokens: List[BaseTokenQualifierResults]
    ents: List[BaseEntQualifierResults]

In negation

@dataclass
class TokenNegationResults(BaseTokenQualifierResults):
    # Single token
    negation: bool

@dataclass
class EntNegationResults(BaseEntQualifierResults):
    # Single entity
    negation: bool
    cues: List[Span]

@dataclass
class NegationResults(BaseQualifierResults):
    # All qualified tokens and entities
    tokens: List[TokenNegationResults]
    ents: List[EntNegationResults]

[github-actions[bot]]

Coverage Report

Name	Stmts	Miss	∆ Miss	Cover
edsnlp/pipes/qualifiers/base.py New missing coverage at line 178 ! def __call__(self, doc: Doc) -> Doc: - results = self.process(doc) raise NotImplementedError(f"{type(results)} should be used to tag the document")	50	1	1	98.00%
TOTAL	9439	210	1	97.78%

Files without new missing coverage

Name	Stmts	Miss	∆ Miss	Cover
edsnlp/utils/span_getters.py Was already missing at lines 52-55 else: - for span in candidates: - if span.label_ in span_filter: - yield span Was already missing at lines 59-61 if span_getter is None: - yield doc[:], None - return if callable(span_getter): Was already missing at lines 62-64 if callable(span_getter): - yield from span_getter(doc) - return for key, span_filter in span_getter.items(): Was already missing at line 66 if key == "*": - candidates = ( (span, group) for group in doc.spans.values() for span in group Was already missing at lines 75-78 else: - for span, group in candidates: - if span.label_ in span_filter: - yield span, group Was already missing at line 82 if callable(span_setter): - span_setter(doc, matches) else: Was already missing at line 124 elif isinstance(v, str): - new_value[k] = [v] elif isinstance(v, list) and all(isinstance(i, str) for i in v): Was already missing at line 162 elif isinstance(v, str): - new_value[k] = [v] elif isinstance(v, list) and all(isinstance(i, str) for i in v):	153	14	0	90.85%
edsnlp/utils/resources.py Was already missing at line 33 if not verbs: - return conjugated_verbs	24	1	0	95.83%
edsnlp/utils/numbers.py Was already missing at line 34 else: - string = s string = string.lower().strip() Was already missing at lines 38-41 return int(string) - except ValueError: - parsed = DIGITS_MAPPINGS.get(string, None) - return parsed	16	4	0	75.00%
edsnlp/utils/lazy_module.py Was already missing at line 46 ): - continue for import_node in node.body:	31	1	0	96.77%
edsnlp/utils/filter.py Was already missing at line 206 if isinstance(label, int): - return [span for span in spans if span.label == label] else:	74	1	0	98.65%
edsnlp/utils/bindings.py Was already missing at line 22 return "." + path - return path	66	1	0	98.48%
edsnlp/train.py Was already missing at line 190 else: - sample_len = lambda idx, noise=True: 1 # noqa: E731 Was already missing at lines 257-263 if total + num_tokens > self.grad_accumulation_max_tokens: - print( ... - mini_batches.append([]) total += num_tokens Was already missing at line 349 if 0 <= self.limit <= count: - break if not (len(doc) and (filter_fn is None or filter_fn(doc))): Was already missing at line 351 if not (len(doc) and (filter_fn is None or filter_fn(doc))): - continue count += 1 Was already missing at lines 385-387 for ent in doc.ents: - for token in ent: - token.is_sent_start = False for sent in doc.sents if doc.has_annotation("SENT_START") else (doc[:],):	257	8	0	96.89%
edsnlp/processing/spark.py Was already missing at line 51 getActiveSession = SparkSession.getActiveSession - except AttributeError:	43	1	0	97.67%
edsnlp/processing/multiprocessing.py Was already missing at lines 227-231 if os.environ.get("TORCH_SHARING_STRATEGY"): - try: - torch.multiprocessing.set_sharing_strategy(os.environ["TORCH_SHARING_STRATEGY"]) - except NameError: - pass Was already missing at line 249 def save_align_devices_hook(pickler: Any, obj: Any): - pickler.save_reduce(load_align_devices_hook, (obj.__dict__,), obj=obj) Was already missing at lines 252-259 def load_align_devices_hook(state): - state["execution_device"] = MAP_LOCATION ... - AlignDevicesHook = None Was already missing at line 452 - new_batch_iterator = None Was already missing at lines 570-572 else: - batch = gpu_pipe.prepare_batch(docs, device=device) - inputs = None active_batches[batch_id] = (docs, task_id, inputs) Was already missing at line 949 if isinstance(outputs, BaseException): - raise outputs Was already missing at line 1017 if v is not None: - os.environ[k] = v	420	16	0	96.19%
edsnlp/processing/deprecated_pipe.py Was already missing at lines 207-209 def converter(doc): - res = results_extractor(doc) - return ( [{"note_id": doc._.note_id, **row} for row in res]	57	2	0	96.49%
edsnlp/pipes/trainable/span_linker/span_linker.py Was already missing at lines 401-403 if self.reference_mode == "synonym": - embeds = embeds.to(new_lin.weight) - new_lin.weight.data = embeds else:	172	2	0	98.84%
edsnlp/pipes/trainable/ner_crf/ner_crf.py Was already missing at line 250 if self.labels is not None and not self.infer_span_setter: - return Was already missing at lines 258-260 if callable(self.target_span_getter): - for span in get_spans(doc, self.target_span_getter): - inferred_labels.add(span.label_) else:	157	3	0	98.09%
edsnlp/pipes/trainable/layers/crf.py Was already missing at line 21 # out: 2 * N * O - return (log_A.unsqueeze(-1) + log_B.unsqueeze(-3)).logsumexp(-2) Was already missing at line 29 # out: 2 * N * O - return (log_A.unsqueeze(-1) + log_B.unsqueeze(-3)).max(-2) Was already missing at line 97 if learnable_transitions: - self.transitions = torch.nn.Parameter( torch.zeros_like(forbidden_transitions, dtype=torch.float) Was already missing at line 107 if learnable_transitions and with_start_end_transitions: - self.start_transitions = torch.nn.Parameter( torch.zeros(num_tags, dtype=torch.float) Was already missing at line 116 if learnable_transitions and with_start_end_transitions: - self.end_transitions = torch.nn.Parameter( torch.zeros(num_tags, dtype=torch.float)	137	5	0	96.35%
edsnlp/pipes/trainable/embeddings/transformer/transformer.py Was already missing at line 165 if quantization is not None: - kwargs["quantization_config"] = quantization	157	1	0	99.36%
edsnlp/pipes/qualifiers/reported_speech/reported_speech.py Was already missing at lines 24-28 return "REPORTED" - elif token._.rspeech is False: - return "DIRECT" - else: - return None	99	3	0	96.97%
edsnlp/pipes/qualifiers/negation/negation.py Was already missing at line 28 else: - return None	99	1	0	98.99%
edsnlp/pipes/qualifiers/hypothesis/hypothesis.py Was already missing at line 27 else: - return None	96	1	0	98.96%
edsnlp/pipes/qualifiers/history/history.py Was already missing at lines 26-32 def history_getter(token: Union[Token, Span]) -> Optional[str]: - if token._.history is True: - return "ATCD" - elif token._.history is False: - return "CURRENT" - else: - return None Was already missing at lines 337-343 ) - except ValueError: ... - note_datetime = None Was already missing at lines 352-358 ) - except ValueError: ... - birth_datetime = None Was already missing at lines 424-427 ) - except ValueError as e: - absolute_date = None - logger.warning( "In doc {}, the following date {} raises this error: {}. "	177	14	0	92.09%
edsnlp/pipes/qualifiers/family/family.py Was already missing at line 27 else: - return None	81	1	0	98.77%
edsnlp/pipes/ner/tnm/tnm.py Was already missing at lines 156-158 value = TNM.parse_obj(groupdict) - except ValidationError: - value = TNM.parse_obj({})	44	2	0	95.45%
edsnlp/pipes/ner/tnm/model.py Was already missing at line 139 def __str__(self): - return self.norm() Was already missing at line 163 ) - exclude_unset = skip_defaults	104	2	0	98.08%
edsnlp/pipes/ner/scores/sofa/sofa.py Was already missing at line 32 if not assigned: - continue if assigned.get("method_max") is not None: Was already missing at line 40 else: - method = "Non précisée"	25	2	0	92.00%
edsnlp/pipes/ner/scores/elston_ellis/patterns.py Was already missing at line 26 if x <= 5: - return 1 Was already missing at lines 32-36 else: - return 3 - - except ValueError: - return None	21	4	0	80.95%
edsnlp/pipes/ner/scores/charlson/patterns.py Was already missing at lines 21-23 return int(extracted_score) - except ValueError: - return None	13	2	0	84.62%
edsnlp/pipes/ner/scores/base_score.py Was already missing at line 154 if value is None: - continue normalized_value = self.score_normalization(value)	47	1	0	97.87%
edsnlp/pipes/ner/disorders/solid_tumor/solid_tumor.py Was already missing at lines 114-117 if use_tnm: - from edsnlp.pipes.ner.tnm import TNM - - self.tnm = TNM(nlp, pattern=None, attr="TEXT") Was already missing at lines 119-129 def process_tnm(self, doc): - spans = self.tnm.process(doc) ... - yield span Was already missing at line 149 if self.use_tnm: - yield from self.process_tnm(doc)	35	12	0	65.71%
edsnlp/pipes/ner/disorders/peripheral_vascular_disease/peripheral_vascular_disease.py Was already missing at line 107 if "peripheral" not in span._.assigned.keys(): - continue	15	1	0	93.33%
edsnlp/pipes/ner/disorders/diabetes/diabetes.py Was already missing at line 133 # Mostly FP - continue Was already missing at line 136 elif self.has_far_complications(span): - span._.status = 2 Was already missing at line 148 if next(iter(self.complication_matcher(context)), None) is not None: - return True return False	31	3	0	90.32%
edsnlp/pipes/ner/disorders/connective_tissue_disease/connective_tissue_disease.py Was already missing at line 103 # Huge change of FP / Title section - continue	14	1	0	92.86%
edsnlp/pipes/ner/disorders/ckd/ckd.py Was already missing at lines 120-123 dfg_value = float(dfg_span.text.replace(",", ".").strip()) - except ValueError: - logger.trace(f"DFG value couldn't be extracted from {dfg_span.text}") - return False	29	3	0	89.66%
edsnlp/pipes/ner/disorders/cerebrovascular_accident/cerebrovascular_accident.py Was already missing at lines 111-113 if span._.source == "ischemia": - if "brain" not in span._.assigned.keys(): - continue	17	2	0	88.24%
edsnlp/pipes/ner/adicap/models.py Was already missing at line 15 def norm(self) -> str: - return self.code Was already missing at line 18 def __str__(self): - return self.norm()	14	2	0	85.71%
edsnlp/pipes/misc/sections/sections.py Was already missing at line 126 if sections is None: - sections = patterns.sections sections = dict(sections)	45	1	0	97.78%
edsnlp/pipes/misc/quantities/quantities.py Was already missing at lines 147-149 def __getitem__(self, item: int): - assert isinstance(item, int) - return [self][item] Was already missing at lines 160-163 def __eq__(self, other: Any): - if isinstance(other, SimpleQuantity): - return self.convert_to(other.unit) == other.value - return False Was already missing at line 166 if other.unit == self.unit: - return self.__class__(self.value + other.value, self.unit, self.registry) return self.__class__( Was already missing at line 193 return self.convert_to(other_unit) - except KeyError: raise AttributeError(f"Unit {other_unit} not found") Was already missing at line 198 def verify(cls, ent): - return True Was already missing at line 237 def __lt__(self, other: Union[SimpleQuantity, "RangeQuantity"]): - return max(self.convert_to(other.unit)) < min((part.value for part in other)) Was already missing at line 248 return self.convert_to(other.unit) == other.value - return False Was already missing at line 262 def verify(cls, ent): - return True Was already missing at line 866 if snippet.end != last and doclike.doc[last: snippet.end].text.strip() == "": - pseudo.append("w") pseudo = "".join(pseudo) Was already missing at line 1040 if start_line is None: - continue Was already missing at lines 1071-1073 unit_norm = self.unit_followers[unit_before.label_] - except (KeyError, AttributeError, IndexError): - pass Was already missing at line 1116 ): - ent = doc[unit_text.start: number.end] else: Was already missing at lines 1123-1125 dims = self.unit_registry.parse_unit(unit_norm)[0] - except KeyError: - continue Was already missing at lines 1236-1238 last._.set(last.label_, new_value) - except (AttributeError, TypeError): - merged.append(ent) else:	432	20	0	95.37%
edsnlp/pipes/misc/dates/models.py Was already missing at line 152 else: - d["month"] = note_datetime.month if self.day is None: Was already missing at lines 156-162 else: - if self.year is None: ... - d["day"] = default_day Was already missing at lines 170-172 return dt - except ValueError: - return None Was already missing at line 188 else: - return None Was already missing at line 204 if self.second: - norm += f"{self.second:02}s"	196	11	0	94.39%
edsnlp/pipes/misc/dates/dates.py Was already missing at line 248 if isinstance(absolute, str): - absolute = [absolute] if isinstance(relative, str): Was already missing at line 250 if isinstance(relative, str): - relative = [relative] if isinstance(duration, str): Was already missing at line 252 if isinstance(duration, str): - relative = [duration] if isinstance(false_positive, str): Was already missing at lines 356-365 if self.merge_mode == "align": - alignments = align_spans(matches, spans, sort_by_overlap=True) ... - matches.append(span) Was already missing at line 450 elif d1 in seen or v1.bound is None or v2.bound is None: - continue Was already missing at lines 461-463 if v1.mode == Mode.DURATION: - m1 = Bound.FROM if v2.bound == Bound.UNTIL else Bound.UNTIL - m2 = v2.mode or Bound.FROM elif v2.mode == Mode.DURATION:	152	15	0	90.13%
edsnlp/pipes/misc/consultation_dates/consultation_dates.py Was already missing at line 131 else: - self.date_matcher = None Was already missing at line 134 if not consultation_mention: - consultation_mention = [] elif consultation_mention is True:	48	2	0	95.83%
edsnlp/pipes/core/normalizer/__init__.py Was already missing at line 7 def excluded_or_space_getter(t): - return t.is_space or t.tag_ == "EXCLUDED"	5	1	0	80.00%
edsnlp/pipes/core/endlines/endlines.py Was already missing at lines 151-155 if end_lines_model is None: - path = build_path(__file__, "base_model.pkl") - - with open(path, "rb") as inp: - self.model = pickle.load(inp) elif isinstance(end_lines_model, str): Was already missing at lines 158-160 self.model = pickle.load(inp) - elif isinstance(end_lines_model, EndLinesModel): - self.model = end_lines_model else: Was already missing at line 191 ): - return "ENUMERATION" Was already missing at line 278 if np.isnan(sigma): - sigma = 1	87	7	0	91.95%
edsnlp/pipes/core/contextual_matcher/models.py Was already missing at lines 19-23 if isinstance(v, list): - assert ( - len(v) == 2 - ), "`window` should be a tuple/list of two integer, or a single integer" - v = tuple(v) if isinstance(v, int):	115	2	0	98.26%
edsnlp/pipes/core/contextual_matcher/contextual_matcher.py Was already missing at line 94 ) - label = label_name if label is None: Was already missing at line 343 if assigned is None: - continue if replace_entity:	143	2	0	98.60%
edsnlp/patch_spacy.py Was already missing at lines 67-69 # if module is reloaded. - existing_func = registry.factories.get(internal_name) - if not util.is_same_func(factory_func, existing_func): raise ValueError(	31	2	0	93.55%
edsnlp/optimization.py Was already missing at line 32 def param_groups(self, value): - self.optim.param_groups = value Was already missing at line 36 def state(self): - return self.optim.state Was already missing at line 40 def state(self, value): - self.optim.state = value Was already missing at line 89 def __init__(self, groups): - self.param_groups = groups	77	4	0	94.81%
edsnlp/matchers/simstring.py Was already missing at line 280 if custom: - attr = attr[1:].lower() Was already missing at line 295 if custom: - token_text = getattr(token._, attr) else:	146	2	0	98.63%
edsnlp/language.py Was already missing at line 103 if last != begin: - logger.warning( "Missed some characters during"	51	1	0	98.04%
edsnlp/data/standoff.py Was already missing at line 43 def __init__(self, ann_file, line): - super().__init__(f"File {ann_file}, unrecognized Brat line {line}") Was already missing at line 83 if not len(ann_paths): - return { "text": text, Was already missing at line 197 ) - except Exception: raise Exception(	172	3	0	98.26%
edsnlp/data/polars.py Was already missing at line 26 if hasattr(data, "collect"): - data = data.collect() assert isinstance(data, pl.DataFrame)	44	1	0	97.73%
edsnlp/data/json.py Was already missing at line 94 if not is_jsonl: - obj[FILENAME] = filename results.append(obj) Was already missing at line 96 results.append(obj) - except Exception: raise Exception(f"Cannot parse {filename}")	107	2	0	98.13%
edsnlp/data/converters.py Was already missing at line 659 if isinstance(converter, type) or kwargs_to_init: - return converter(**kwargs), {} return converter, validate_kwargs(converter, kwargs)	192	1	0	99.48%
edsnlp/data/base.py Was already missing at lines 174-180 """ - data = LazyCollection.ensure_lazy(data) - if converter: - converter, kwargs = get_doc2dict_converter(converter, kwargs) - data = data.map(converter, kwargs=kwargs) - - return data	39	5	0	87.18%
edsnlp/core/torch_component.py Was already missing at line 390 if hasattr(self, "compiled"): - res = self.compiled(batch) else: Was already missing at line 436 """ - return self.preprocess(doc)	179	2	0	98.88%
edsnlp/core/registries.py Was already missing at line 78 if obj.error is not None: - raise obj.error	164	1	0	99.39%
edsnlp/core/pipeline.py Was already missing at line 552 if name in exclude: - continue if name not in components:	410	1	0	99.76%
edsnlp/core/lazy_collection.py Was already missing at line 51 def __call__(self, *args, **kwargs): - return self.forward(*args, **kwargs) Was already missing at line 448 for name, pipe, *_ in self.torch_components(): - pipe.to(device) return self	151	2	0	98.68%
edsnlp/connectors/omop.py Was already missing at line 69 if not isinstance(row.ents, list): - continue Was already missing at line 87 else: - doc.spans[span.label_].append(span) Was already missing at line 127 if df.note_id.isna().any(): - df["note_id"] = range(len(df)) Was already missing at line 171 if i > 0: - df.term_modifiers += ";" df.term_modifiers += ext + "=" + df[ext].astype(str)	84	4	0	95.24%

263 files skipped due to complete coverage.

Coverage success: total of 97.78% is above 97.76% 🎉

[sonarcloud[bot]]

Quality Gate passed

Issues
4 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
3.2% Duplication on New Code

See analysis details on SonarCloud