apply black

qurator/dinglehopper/character_error_rate.py

@@ -9,7 +9,9 @@ from .extracted_text import ExtractedText
 
 
 @multimethod
-def character_error_rate_n(reference: list[str], compared: list[str]) -> Tuple[float, int]:
+def character_error_rate_n(
+    reference: list[str], compared: list[str]
+) -> Tuple[float, int]:
     """
     Compute character error rate.
 
@@ -39,7 +41,9 @@ def character_error_rate_n(reference: str, compared: str) -> Tuple[float, int]:
 def character_error_rate_n(
     reference: ExtractedText, compared: ExtractedText
 ) -> Tuple[float, int]:
-    return character_error_rate_n(reference.grapheme_clusters, compared.grapheme_clusters)
+    return character_error_rate_n(
+        reference.grapheme_clusters, compared.grapheme_clusters
+    )
 
 
 def character_error_rate(reference, compared) -> float:

qurator/dinglehopper/cli_line_dirs.py

@@ -46,7 +46,9 @@ def process(gt_dir, ocr_dir, report_prefix, *, metrics=True):
         ocr = removesuffix(gt, gt_suffix) + ocr_suffix
 
         gt_text = plain_extract(os.path.join(gt_dir, gt), include_filename_in_id=True)
-        ocr_text = plain_extract(os.path.join(ocr_dir, ocr), include_filename_in_id=True)
+        ocr_text = plain_extract(
+            os.path.join(ocr_dir, ocr), include_filename_in_id=True
+        )
         gt_words = words_normalized(gt_text)
         ocr_words = words_normalized(ocr_text)
 
@@ -56,7 +58,9 @@ def process(gt_dir, ocr_dir, report_prefix, *, metrics=True):
             cer, n_characters = l_cer, l_n_characters
         else:
             # Rolling update
-            cer = (cer * n_characters + l_cer * l_n_characters) / (n_characters + l_n_characters)
+            cer = (cer * n_characters + l_cer * l_n_characters) / (
+                n_characters + l_n_characters
+            )
             n_characters = n_characters + l_n_characters
 
         # Compute WER

qurator/dinglehopper/edit_distance.py

@@ -17,6 +17,7 @@ def distance(seq1: list[str], seq2: list[str]):
     """
     return Levenshtein.distance(seq1, seq2)
 
+
 @multimethod
 def distance(s1: str, s2: str):
     """Compute the Levenshtein edit distance between two Unicode strings

qurator/dinglehopper/extracted_text.py

@@ -242,7 +242,9 @@ class ExtractedText:
     def from_str(cls, text, normalization=Normalization.NFC_SBB):
         normalized_text = normalize(text, normalization)
         clusters = list(grapheme_clusters(normalized_text))
-        return cls(None, None, None, normalized_text, clusters, normalization=normalization)
+        return cls(
+            None, None, None, normalized_text, clusters, normalization=normalization
+        )
 
 
 def invert_dict(d):

qurator/dinglehopper/ocr_files.py

@@ -103,9 +103,13 @@ def extract_texts_from_reading_order_group(group, tree, nsmap, textequiv_level):
     else:
         raise NotImplementedError
 
-
     for ro_child in ro_children:
-        if ET.QName(ro_child.tag).localname in ["OrderedGroup", "OrderedGroupIndexed", "UnorderedGroup", "UnorderedGroupIndexed"]:
+        if ET.QName(ro_child.tag).localname in [
+            "OrderedGroup",
+            "OrderedGroupIndexed",
+            "UnorderedGroup",
+            "UnorderedGroupIndexed",
+        ]:
             regions.extend(
                 extract_texts_from_reading_order_group(
                     ro_child, tree, nsmap, textequiv_level
@@ -139,7 +143,11 @@ def plain_extract(filename, include_filename_in_id=False):
         clusters = list(grapheme_clusters(normalized_text))
         return ExtractedText(
             id_template.format(filename=os.path.basename(filename), no=no),
-            None, None, normalized_text, clusters)
+            None,
+            None,
+            normalized_text,
+            clusters,
+        )
 
     with open(filename, "r") as f:
         return ExtractedText(
@@ -147,7 +155,7 @@ def plain_extract(filename, include_filename_in_id=False):
             [make_segment(no, line) for no, line in enumerate(f.readlines())],
             "\n",
             None,
-            None
+            None,
         )
     # XXX hardcoded SBB normalization
 

qurator/dinglehopper/ocrd_cli.py

@@ -33,7 +33,7 @@ class OcrdDinglehopperEvaluate(Processor):
         textequiv_level = self.parameter["textequiv_level"]
         gt_grp, ocr_grp = self.input_file_grp.split(",")
 
-        input_file_tuples = self.zip_input_files(on_error='abort')
+        input_file_tuples = self.zip_input_files(on_error="abort")
         for n, (gt_file, ocr_file) in enumerate(input_file_tuples):
             if not gt_file or not ocr_file:
                 # file/page was not found in this group

qurator/dinglehopper/word_error_rate.py

@@ -40,7 +40,6 @@ def words(s: str):
     if not word_break_patched:
         patch_word_break()
 
-
     # Check if c is an unwanted character, i.e. whitespace, punctuation, or similar
     def unwanted(c):