Implement version specific data structures

As ocr-d continues the support for Python 3.5 until the end of this year
version specific data structures have been implemented.

When the support for Python 3.5 is dropped the extra file can easily be
removed.

qurator/dinglehopper/flexible_character_accuracy.py

@@ -11,15 +11,31 @@ DOI: https://doi.org/10.1016/j.patrec.2020.02.003
 Note that we deviated from the original algorithm at some places.
 """
 
+import sys
 from collections import Counter
 from functools import lru_cache, reduce
 from itertools import product, takewhile
-from typing import List, NamedTuple, Tuple, Optional
+from typing import List, Tuple, Optional
 
 from . import editops
 
+if sys.version_info.minor == 5:
+    from .flexible_character_accuracy_ds_35 import (
+        PartVersionSpecific,
+        Match,
+        Distance,
+        Coefficients,
+    )
+else:
+    from .flexible_character_accuracy_ds import (
+        PartVersionSpecific,
+        Match,
+        Distance,
+        Coefficients,
+    )
 
-def flexible_character_accuracy(gt: str, ocr: str) -> Tuple[float, List["Match"]]:
+
+def flexible_character_accuracy(gt: str, ocr: str) -> Tuple[float, List[Match]]:
     """Calculate the flexible character accuracy.
 
     Reference: contains steps 1-7 of the flexible character accuracy algorithm.
@@ -53,7 +69,7 @@ def flexible_character_accuracy(gt: str, ocr: str) -> Tuple[float, List["Match"]
     return best_score, best_matches
 
 
-def match_with_coefficients(gt: str, ocr: str, coef: "Coefficients") -> List["Match"]:
+def match_with_coefficients(gt: str, ocr: str, coef: Coefficients) -> List[Match]:
     """Match ground truth with ocr and considers a given set of coefficients.
 
     Reference: contains steps 1 - 6 of the flexible character accuracy algorithm.
@@ -88,8 +104,8 @@ def match_with_coefficients(gt: str, ocr: str, coef: "Coefficients") -> List["Ma
 
 
 def match_longest_gt_lines(
-    gt_lines: List["Part"], ocr_lines: List["Part"], coef: "Coefficients"
-) -> Optional["Match"]:
+    gt_lines: List["Part"], ocr_lines: List["Part"], coef: Coefficients
+) -> Optional[Match]:
     """Find the best match for the longest line(s) in ground truth.
 
     The longest lines in ground truth are matched against lines in ocr to find the
@@ -127,8 +143,8 @@ def match_longest_gt_lines(
 
 
 def match_gt_line(
-    gt_line: "Part", ocr_lines: List["Part"], coef: "Coefficients"
-) -> Tuple[Optional["Match"], Optional["Part"]]:
+    gt_line: "Part", ocr_lines: List["Part"], coef: Coefficients
+) -> Tuple[Optional[Match], Optional["Part"]]:
     """Match the given ground truth line against all the lines in ocr.
 
     Reference: contains steps 3 of the flexible character accuracy algorithm.
@@ -166,7 +182,7 @@ def remove_or_split(original: "Part", match: "Part", lines: List["Part"]) -> boo
 
 
 @lru_cache(maxsize=1000000)
-def match_lines(gt_line: "Part", ocr_line: "Part") -> Optional["Match"]:
+def match_lines(gt_line: "Part", ocr_line: "Part") -> Optional[Match]:
     """Matches two lines searching for a local alignment.
 
     The shorter line is moved along the longer line
@@ -228,7 +244,7 @@ def match_lines(gt_line: "Part", ocr_line: "Part") -> Optional["Match"]:
 
 
 @lru_cache(maxsize=1000000)
-def distance(gt: "Part", ocr: "Part") -> "Match":
+def distance(gt: "Part", ocr: "Part") -> Match:
     """Calculate the editing distance between the two lines.
 
     Using the already available `editops()` function with the Levenshtein distance.
@@ -244,7 +260,7 @@ def distance(gt: "Part", ocr: "Part") -> "Match":
     return Match(gt=gt, ocr=ocr, dist=Distance(**edits), ops=ops)
 
 
-def score_edit_distance(match: "Match") -> int:
+def score_edit_distance(match: Match) -> int:
     """Calculate edit distance for a match.
 
     Formula: $deletes + inserts + 2 * replacements$
@@ -254,9 +270,7 @@ def score_edit_distance(match: "Match") -> int:
     return match.dist.delete + match.dist.insert + 2 * match.dist.replace
 
 
-def calculate_penalty(
-    gt: "Part", ocr: "Part", match: "Match", coef: "Coefficients"
-) -> float:
+def calculate_penalty(gt: "Part", ocr: "Part", match: Match, coef: Coefficients) -> float:
     """Calculate the penalty for a given match.
 
     For details and discussion see Section 3 in doi:10.1016/j.patrec.2020.02.003.
@@ -278,21 +292,21 @@ def calculate_penalty(
     )
 
 
-def character_accuracy_for_matches(matches: List["Match"]) -> float:
+def character_accuracy_for_matches(matches: List[Match]) -> float:
     """Character accuracy of a full text represented by a list of matches.
 
     See other `character_accuracy` for details.
 
     """
-    agg: Counter = reduce(
+    agg = reduce(
         lambda acc, match: acc + Counter(match.dist._asdict()), matches, Counter()
-    )
+    )  # type: Counter
 
     score = character_accuracy(Distance(**agg))
     return score
 
 
-def character_accuracy(edits: "Distance") -> float:
+def character_accuracy(edits: Distance) -> float:
     """Character accuracy calculated by necessary edit operations.
 
     Edit operations are needed edits to transform one text into another.
@@ -335,7 +349,7 @@ def initialize_lines(text: str) -> List["Part"]:
     return lines
 
 
-def combine_lines(matches: List["Match"]) -> Tuple[str, str]:
+def combine_lines(matches: List[Match]) -> Tuple[str, str]:
     """Combines the matches to aligned texts.
 
     TODO: just hacked, needs tests and refinement. Also missing insert/delete marking.
@@ -356,16 +370,7 @@ def combine_lines(matches: List["Match"]) -> Tuple[str, str]:
     return gt, ocr
 
 
-class Part(NamedTuple):
-    """Represent a line or part of a line.
-
-    This data object is maintained to be able to reproduce the original text.
-    """
-
-    text: str = ""
-    line: int = 0
-    start: int = 0
-
+class Part(PartVersionSpecific):
     @property
     def end(self) -> int:
         return self.start + self.length
@@ -402,33 +407,3 @@ class Part(NamedTuple):
         text = self.text[rel_start:rel_end]
         start = self.start + rel_start
         return Part(text=text, line=self.line, start=start)
-
-
-class Distance(NamedTuple):
-    """Represent distance between two sequences."""
-
-    match: int = 0
-    replace: int = 0
-    delete: int = 0
-    insert: int = 0
-
-
-class Match(NamedTuple):
-    """Represent a calculated match between ground truth and the ocr result."""
-
-    gt: "Part"
-    ocr: "Part"
-    dist: "Distance"
-    ops: List
-
-
-class Coefficients(NamedTuple):
-    """Coefficients to calculate penalty for substrings.
-
-    See Section 3 in doi:10.1016/j.patrec.2020.02.003
-    """
-
-    edit_dist: int = 25
-    length_diff: int = 20
-    offset: int = 1
-    length: int = 4

qurator/dinglehopper/flexible_character_accuracy_ds.py

@@ -0,0 +1,48 @@
+"""
+Datastructures to be used with the Flexible Character Accuracy Algorithm
+
+Separated because of version compatibility issues with Python 3.5.
+"""
+
+from typing import List, NamedTuple
+
+
+class PartVersionSpecific(NamedTuple):
+    """Represent a line or part of a line.
+
+    This data object is maintained to be able to reproduce the original text.
+    """
+
+    text: str = ""
+    line: int = 0
+    start: int = 0
+
+
+class Distance(NamedTuple):
+    """Represent distance between two sequences."""
+
+    match: int = 0
+    replace: int = 0
+    delete: int = 0
+    insert: int = 0
+
+
+class Match(NamedTuple):
+    """Represent a calculated match between ground truth and the ocr result."""
+
+    gt: "Part"
+    ocr: "Part"
+    dist: "Distance"
+    ops: List
+
+
+class Coefficients(NamedTuple):
+    """Coefficients to calculate penalty for substrings.
+
+    See Section 3 in doi:10.1016/j.patrec.2020.02.003
+    """
+
+    edit_dist: int = 25
+    length_diff: int = 20
+    offset: int = 1
+    length: int = 4

qurator/dinglehopper/flexible_character_accuracy_ds_35.py

@@ -0,0 +1,76 @@
+"""
+Datastructures to be used with the Flexible Character Accuracy Algorithm
+
+Separated because of version compatibility issues with Python 3.5.
+"""
+
+from collections import namedtuple
+from typing import Dict
+
+
+class PartVersionSpecific:
+    def __init__(self, text: str = "", line: int = 0, start: int = 0):
+        self.text = text
+        self.line = line
+        self.start = start
+
+    def __eq__(self, other):
+        return (
+            self.line == other.line
+            and self.start == other.start
+            and self.text == other.text
+        )
+
+    def __hash__(self):
+        return hash(self.text) ^ hash(self.line) ^ hash(self.start)
+
+
+class Distance:
+    def __init__(
+        self, match: int = 0, replace: int = 0, delete: int = 0, insert: int = 0
+    ):
+        self.match = match
+        self.replace = replace
+        self.delete = delete
+        self.insert = insert
+
+    def _asdict(self) -> Dict:
+        return {
+            "match": self.match,
+            "replace": self.replace,
+            "delete": self.delete,
+            "insert": self.insert,
+        }
+
+    def __eq__(self, other):
+        return (
+            self.match == other.match
+            and self.replace == other.replace
+            and self.delete == other.delete
+            and self.insert == other.insert
+        )
+
+    def __hash__(self):
+        return (
+            hash(self.match)
+            ^ hash(self.replace)
+            ^ hash(self.delete)
+            ^ hash(self.insert)
+        )
+
+
+Match = namedtuple("Match", ["gt", "ocr", "dist", "ops"])
+
+
+class Coefficients:
+    def __init__(
+        self,
+        edit_dist: int = 25,
+        length_diff: int = 20,
+        offset: int = 1,
+        length: int = 4,
+    ):
+        self.edit_dist = edit_dist
+        self.length_diff = length_diff
+        self.offset = offset
+        self.length = length