From d506b249a38ee927de434a02e31d86ae096dbccc Mon Sep 17 00:00:00 2001
From: manonBlanco <blanco@teklia.com>
Date: Wed, 3 Jan 2024 14:47:10 +0100
Subject: [PATCH] Use early returns
---
nerval/evaluate.py | 91 +++++++++++++++++++++++-----------------------
1 file changed, 46 insertions(+), 45 deletions(-)
diff --git a/nerval/evaluate.py b/nerval/evaluate.py
index 5afe7cc..26f0118 100644
--- a/nerval/evaluate.py
+++ b/nerval/evaluate.py
@@ -349,48 +349,49 @@ def run_multiple(file_csv: Path, folder: Path, threshold: int, verbose: bool):
csv_reader = reader(read_obj)
list_cor = list(csv_reader)
- if folder.is_dir():
- list_bio_file = list(folder.rglob("*.bio"))
-
- count = 0
- precision = 0
- recall = 0
- f1 = 0
- for row in list_cor:
- annot = None
- predict = None
-
- for file in list_bio_file:
- if row[0] == file.name:
- annot = file
- for file in list_bio_file:
- if row[1] == file.name:
- predict = file
-
- if annot and predict:
- count += 1
- scores = run(annot, predict, threshold, verbose)
- precision += scores["All"]["P"]
- recall += scores["All"]["R"]
- f1 += scores["All"]["F1"]
- else:
- raise Exception(f"No file found for files {row[0]}, {row[1]}")
- if count:
- logger.info("Average score on all corpus")
- table = PrettyTable()
- table.field_names = ["Precision", "Recall", "F1"]
- table.set_style(MARKDOWN)
- table.add_rows(
- [
- [
- round(precision / count, 3),
- round(recall / count, 3),
- round(f1 / count, 3),
- ],
- ],
- )
- print(table)
- else:
- raise Exception("No file were counted")
- else:
- raise Exception("the path indicated does not lead to a folder.")
+ if not folder.is_dir():
+ raise Exception("The path indicated does not lead to a folder.")
+
+ list_bio_file = list(folder.rglob("*.bio"))
+
+ count = 0
+ precision = 0
+ recall = 0
+ f1 = 0
+ for row in list_cor:
+ annot = None
+ predict = None
+
+ for file in list_bio_file:
+ if row[0] == file.name:
+ annot = file
+ for file in list_bio_file:
+ if row[1] == file.name:
+ predict = file
+
+ if not (annot and predict):
+ raise Exception(f"No file found for files {row[0]}, {row[1]}")
+
+ count += 1
+ scores = run(annot, predict, threshold, verbose)
+ precision += scores["All"]["P"]
+ recall += scores["All"]["R"]
+ f1 += scores["All"]["F1"]
+
+ if not count:
+ raise Exception("No file were counted")
+
+ logger.info("Average score on all corpus")
+ table = PrettyTable()
+ table.field_names = ["Precision", "Recall", "F1"]
+ table.set_style(MARKDOWN)
+ table.add_rows(
+ [
+ [
+ round(precision / count, 3),
+ round(recall / count, 3),
+ round(f1 / count, 3),
+ ],
+ ],
+ )
+ print(table)
--
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