From e5bf32a63f6394424e9bfdf19318a31d397d6b93 Mon Sep 17 00:00:00 2001
From: EvaBardou <bardou@teklia.com>
Date: Wed, 3 Jan 2024 17:01:32 +0100
Subject: [PATCH] Use csv.DictReader rather than csv.reader
---
demo/mapping_file.csv | 1 +
nerval/evaluate.py | 16 +++++++++++-----
2 files changed, 12 insertions(+), 5 deletions(-)
diff --git a/demo/mapping_file.csv b/demo/mapping_file.csv
index 5a2ce92..6b59366 100644
--- a/demo/mapping_file.csv
+++ b/demo/mapping_file.csv
@@ -1,2 +1,3 @@
+Annotation,Prediction
demo_annot.bio,demo_predict.bio
toy_test_annot.bio,toy_test_predict.bio
\ No newline at end of file
diff --git a/nerval/evaluate.py b/nerval/evaluate.py
index 5afe7cc..1a438da 100644
--- a/nerval/evaluate.py
+++ b/nerval/evaluate.py
@@ -1,5 +1,5 @@
+import csv
import logging
-from csv import reader
from pathlib import Path
from typing import List
@@ -19,6 +19,10 @@ from nerval.utils import print_result_compact, print_results
logger = logging.getLogger(__name__)
+ANNO_COLUMN = "Annotation"
+PRED_COLUMN = "Prediction"
+CSV_HEADER = [ANNO_COLUMN, PRED_COLUMN]
+
def compute_matches(
annotation: str,
@@ -346,7 +350,7 @@ def run_multiple(file_csv: Path, folder: Path, threshold: int, verbose: bool):
"""Run the program for multiple files (correlation indicated in the csv file)"""
# Read the csv in a list
with file_csv.open() as read_obj:
- csv_reader = reader(read_obj)
+ csv_reader = csv.DictReader(read_obj, fieldnames=CSV_HEADER)
list_cor = list(csv_reader)
if folder.is_dir():
@@ -361,10 +365,10 @@ def run_multiple(file_csv: Path, folder: Path, threshold: int, verbose: bool):
predict = None
for file in list_bio_file:
- if row[0] == file.name:
+ if row[ANNO_COLUMN] == file.name:
annot = file
for file in list_bio_file:
- if row[1] == file.name:
+ if row[PRED_COLUMN] == file.name:
predict = file
if annot and predict:
@@ -374,7 +378,9 @@ def run_multiple(file_csv: Path, folder: Path, threshold: int, verbose: bool):
recall += scores["All"]["R"]
f1 += scores["All"]["F1"]
else:
- raise Exception(f"No file found for files {row[0]}, {row[1]}")
+ raise Exception(
+ f"No file found for files {row[ANNO_COLUMN]}, {row[PRED_COLUMN]}"
+ )
if count:
logger.info("Average score on all corpus")
table = PrettyTable()
--
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