“Finishing” touches

allzweckmesser/__init__.py

-from . import config, corpus, db, meters, model, scan, scanner, wordlist
+from . import (config, corpus, db, features, meters, model, scan, scanner,
+               wordlist)

allzweckmesser/model.py

@@ -358,10 +358,12 @@ class Token:
 
 class Reading:
 
-    def __init__(self, tokens: List[Token] = None, phenomena: dict = None):
+    def __init__(self, tokens: List[Token] = None, phenomena: dict = None,
+                 meter=None):
         self.tokens = tokens or list()
         self.phenomena = phenomena or dict()
         self.features = defaultdict(lambda: 0)
+        self.meter = meter
 
     @classmethod
     def from_json(cls, json_file):

allzweckmesser/scan.py

@@ -3,9 +3,12 @@
 
 import argparse
 import sys
+from sklearn import joblib
 from typing import List
 
-from .meters import ALL_METERS
+from .config import RANKING_MODEL_PATH
+from .features import combine_features
+from .meters import ALL_METERS, get_reading_meter_combinations
 from .model import Verse
 from .scanner import Scanner
 
@@ -14,6 +17,24 @@ def scan(plain_verses: List[str], meters=ALL_METERS, **options) -> List[Verse]:
     """Scan Latin verses."""
     scanner = Scanner()
     scanned_verses = scanner.scan_verses(plain_verses)
+    model = joblib.load(RANKING_MODEL_PATH)
+    for verse in scanned_verses:
+        reading_meter_combinations = (
+            get_reading_meter_combinations(
+                verse.readings, meters
+            )
+        )
+        vectors = []
+        for reading, meter, rmfeatures in reading_meter_combinations:
+            reading.meter = meter
+            vectors.append(combine_features(reading.features, rmfeatures))
+        probs = model.predict_proba(vectors)
+        sorted_probs = sorted(
+            [(probs[i], reading) for i in range(len(probs))],
+            key=lambda x: x[0][0]
+        )
+        first_one = sorted_probs[:1]
+        verse.readings = [prob_reading[1] for prob_reading in first_one]
     return scanned_verses