diff --git a/nerval/evaluate.py b/nerval/evaluate.py
index a2af0bd904f25b2e7d328cb1fb84c8f171a682be..0efe5b4a53cd4c8fabfa9dad884e10e92c6df99f 100644
--- a/nerval/evaluate.py
+++ b/nerval/evaluate.py
@@ -4,6 +4,7 @@ import logging
import os
from csv import reader
from pathlib import Path
+from typing import List
import editdistance
import edlib
@@ -265,22 +266,11 @@ def compute_scores(
return scores
-def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> dict:
- """Compute recall and precision for each entity type found in annotation and/or prediction.
-
- Each measure is given at document level, global score is a micro-average across entity types.
- """
- # Get string and list of labels per character
- annot = parse_bio(annotation)
- predict = parse_bio(prediction)
-
- if not annot or not predict:
- raise Exception("No content found in annotation or prediction files.")
-
+def evaluate(annotation: dict, prediction: dict, threshold: int) -> dict:
# Align annotation and prediction
- align_result = edlib.align(annot["words"], predict["words"], task="path")
+ align_result = edlib.align(annotation["words"], prediction["words"], task="path")
nice_alignment = edlib.getNiceAlignment(
- align_result, annot["words"], predict["words"]
+ align_result, annotation["words"], prediction["words"]
)
annot_aligned = nice_alignment["query_aligned"]
@@ -288,10 +278,10 @@ def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> di
# Align labels from string alignment
labels_annot_aligned = get_labels_aligned(
- annot["words"], annot_aligned, annot["labels"]
+ annotation["words"], annot_aligned, annotation["labels"]
)
labels_predict_aligned = get_labels_aligned(
- predict["words"], predict_aligned, predict["labels"]
+ prediction["words"], predict_aligned, prediction["labels"]
)
# Get nb match
@@ -304,7 +294,33 @@ def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> di
)
# Compute scores
- scores = compute_scores(annot["entity_count"], predict["entity_count"], matches)
+ scores = compute_scores(
+ annotation["entity_count"], prediction["entity_count"], matches
+ )
+ return scores
+
+
+def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> dict:
+ """Compute recall and precision for each entity type found in annotation and/or prediction.
+
+ Each measure is given at document level, global score is a micro-average across entity types.
+ """
+
+ # Get string and list of labels per character
+ def read_file(path: Path) -> List[str]:
+ assert path.exists(), f"Error: Input file {path} does not exist"
+ return path.read_text().strip().splitlines()
+
+ logger.info(f"Parsing file @ {annotation}")
+ annot = parse_bio(read_file(annotation))
+
+ logger.info(f"Parsing file @ {prediction}")
+ predict = parse_bio(read_file(prediction))
+
+ if not (annot and predict):
+ raise Exception("No content found in annotation or prediction files.")
+
+ scores = evaluate(annot, predict, threshold)
# Print results
if verbose:
diff --git a/nerval/parse.py b/nerval/parse.py
index edf27155bda3036bb4c23e7c6adf84b6e6cf34b4..c4736fa5dfc687b1c59e27c908ac0dc82060fc8f 100644
--- a/nerval/parse.py
+++ b/nerval/parse.py
@@ -1,6 +1,6 @@
# -*- coding: utf-8 -*-
import re
-from pathlib import Path
+from typing import List
NOT_ENTITY_TAG = "O"
BEGINNING_POS = ["B", "S", "U"]
@@ -34,12 +34,12 @@ def get_position_label(label: str) -> str:
else re.match(r"([BIESLU])-(.*)$", label)[1]
)
except TypeError:
- raise (Exception(f"The label {label} is not valid in BIOES/BIOLU format."))
+ raise Exception(f"The label {label} is not valid in BIOES/BIOLU format.")
return pos
-def parse_line(index: int, line: str, path: Path):
+def parse_line(index: int, line: str):
try:
match_iob = REGEX_IOB_LINE.search(line)
@@ -47,33 +47,24 @@ def parse_line(index: int, line: str, path: Path):
return match_iob.group(1, 2)
except AssertionError:
- raise (
- Exception(
- f"The file @ {path} is not in BIO format: check line {index} ({line})"
- )
- )
+ raise Exception(f"The file is not in BIO format: check line {index} ({line})")
-def parse_bio(path: Path) -> dict:
+def parse_bio(lines: List[str]) -> dict:
"""Parse a BIO file to get text content, character-level NE labels and entity types count.
- Input : path to a valid BIO file
- Output format : { "words": str, "labels": list; "entity_count" : { tag : int } }
+ Input: lines of a valid BIO file
+ Output format: { "words": str, "labels": list, "entity_count": { tag: int } }
"""
- assert path.exists(), f"Error: Input file {path} does not exist"
-
words = []
labels = []
entity_count = {"All": 0}
last_tag = None
- with open(path, "r") as fd:
- lines = list(filter(lambda x: x != "\n", fd.readlines()))
-
if "§" in " ".join(lines):
raise (
Exception(
- f"§ found in input file {path}. Since this character is used in a specific way during evaluation, prease remove it from files."
+ "§ found in input file. Since this character is used in a specific way during evaluation, prease remove it from files."
)
)
@@ -82,7 +73,7 @@ def parse_bio(path: Path) -> dict:
containing_tag = None
for index, line in enumerate(lines):
- word, label = parse_line(index, line, path)
+ word, label = parse_line(index, line)
# Preserve hyphens to avoid confusion with the hyphens added later during alignment
word = word.replace("-", "§")
diff --git a/tests/test_parse_bio.py b/tests/test_parse_bio.py
index 09c3cb589f80ccec8386bd8794e441447299d619..10897953bde5caa825ea0070fd558d6498eb6f18 100644
--- a/tests/test_parse_bio.py
+++ b/tests/test_parse_bio.py
@@ -1,6 +1,4 @@
# -*- coding: utf-8 -*-
-from pathlib import Path
-
import pytest
from nerval import evaluate
@@ -181,7 +179,8 @@ expected_parsed_end_of_file = {
],
)
def test_parse_bio(test_input, expected):
- assert evaluate.parse_bio(test_input) == expected
+ lines = test_input.read_text().strip().splitlines()
+ assert evaluate.parse_bio(lines) == expected
def test_parse_bio_bad_input(bad_bio):
@@ -189,11 +188,6 @@ def test_parse_bio_bad_input(bad_bio):
evaluate.parse_bio(bad_bio)
-def test_parse_bio_no_input():
- with pytest.raises(AssertionError):
- evaluate.parse_bio(Path("not_a_bio"))
-
-
@pytest.mark.parametrize(
"line, word, label",
(
@@ -204,7 +198,7 @@ def test_parse_bio_no_input():
),
)
def test_parse_line(line, word, label):
- assert parse_line(index=0, line=line, path=Path("")) == (word, label)
+ assert parse_line(index=0, line=line) == (word, label)
@pytest.mark.parametrize(
@@ -213,7 +207,7 @@ def test_parse_line(line, word, label):
)
def test_parse_line_crash(line):
with pytest.raises(Exception):
- parse_line(index=0, line=line, path=Path(""))
+ parse_line(index=0, line=line)
@pytest.mark.parametrize(