Add scripts/statistics.py

scripts/statistics.py

@@ -0,0 +1,182 @@
+"""
+Statistics for UD Vietnamese Dataset (UDD-v0.1)
+"""
+
+from collections import Counter
+from os.path import dirname, join
+
+
+def parse_conllu(filepath):
+    """Parse CoNLL-U file and return sentences."""
+    sentences = []
+    current_sentence = {
+        'tokens': [],
+        'upos': [],
+        'deprel': [],
+        'head': [],
+        'metadata': {}
+    }
+
+    with open(filepath, 'r', encoding='utf-8') as f:
+        for line in f:
+            line = line.strip()
+            if not line:
+                if current_sentence['tokens']:
+                    sentences.append(current_sentence)
+                    current_sentence = {
+                        'tokens': [],
+                        'upos': [],
+                        'deprel': [],
+                        'head': [],
+                        'metadata': {}
+                    }
+            elif line.startswith('#'):
+                # Metadata
+                if '=' in line:
+                    key, value = line[2:].split('=', 1)
+                    current_sentence['metadata'][key.strip()] = value.strip()
+            else:
+                parts = line.split('\t')
+                if len(parts) >= 10:
+                    # Skip multi-word tokens (e.g., 1-2)
+                    if '-' in parts[0] or '.' in parts[0]:
+                        continue
+                    current_sentence['tokens'].append(parts[1])
+                    current_sentence['upos'].append(parts[3])
+                    current_sentence['head'].append(parts[6])
+                    current_sentence['deprel'].append(parts[7])
+
+    # Add last sentence if exists
+    if current_sentence['tokens']:
+        sentences.append(current_sentence)
+
+    return sentences
+
+
+def compute_statistics(sentences):
+    """Compute statistics from parsed sentences."""
+    stats = {}
+
+    # Basic counts
+    stats['num_sentences'] = len(sentences)
+    stats['num_tokens'] = sum(len(s['tokens']) for s in sentences)
+
+    # Sentence length statistics
+    sent_lengths = [len(s['tokens']) for s in sentences]
+    stats['avg_sent_length'] = sum(sent_lengths) / len(sent_lengths) if sent_lengths else 0
+    stats['min_sent_length'] = min(sent_lengths) if sent_lengths else 0
+    stats['max_sent_length'] = max(sent_lengths) if sent_lengths else 0
+
+    # UPOS distribution
+    all_upos = []
+    for s in sentences:
+        all_upos.extend(s['upos'])
+    stats['upos_counts'] = Counter(all_upos)
+
+    # DEPREL distribution
+    all_deprel = []
+    for s in sentences:
+        all_deprel.extend(s['deprel'])
+    stats['deprel_counts'] = Counter(all_deprel)
+
+    # Tree depth statistics
+    depths = []
+    for s in sentences:
+        max_depth = compute_tree_depth(s['head'])
+        depths.append(max_depth)
+    stats['avg_tree_depth'] = sum(depths) / len(depths) if depths else 0
+    stats['max_tree_depth'] = max(depths) if depths else 0
+
+    # Root relation counts
+    root_upos = []
+    for s in sentences:
+        for i, (upos, deprel) in enumerate(zip(s['upos'], s['deprel'])):
+            if deprel == 'root':
+                root_upos.append(upos)
+    stats['root_upos_counts'] = Counter(root_upos)
+
+    return stats
+
+
+def compute_tree_depth(heads):
+    """Compute maximum depth of dependency tree."""
+    n = len(heads)
+    if n == 0:
+        return 0
+
+    depths = [0] * n
+
+    def get_depth(idx):
+        if depths[idx] > 0:
+            return depths[idx]
+        head = int(heads[idx])
+        if head == 0:
+            depths[idx] = 1
+        else:
+            depths[idx] = get_depth(head - 1) + 1
+        return depths[idx]
+
+    for i in range(n):
+        try:
+            get_depth(i)
+        except (RecursionError, IndexError):
+            depths[i] = 1
+
+    return max(depths) if depths else 0
+
+
+def print_statistics(stats):
+    """Print statistics in a nice format."""
+    print("=" * 60)
+    print("UD Vietnamese Dataset (UDD-v0.1) Statistics")
+    print("=" * 60)
+
+    print("\n## Basic Statistics")
+    print(f"  Sentences:         {stats['num_sentences']:,}")
+    print(f"  Tokens:            {stats['num_tokens']:,}")
+    print(f"  Avg sent length:   {stats['avg_sent_length']:.2f}")
+    print(f"  Min sent length:   {stats['min_sent_length']}")
+    print(f"  Max sent length:   {stats['max_sent_length']}")
+    print(f"  Avg tree depth:    {stats['avg_tree_depth']:.2f}")
+    print(f"  Max tree depth:    {stats['max_tree_depth']}")
+
+    print("\n## UPOS Distribution")
+    print(f"  {'Tag':<10} {'Count':>8} {'Percent':>8}")
+    print("  " + "-" * 28)
+    total_tokens = stats['num_tokens']
+    for tag, count in stats['upos_counts'].most_common():
+        pct = count / total_tokens * 100
+        print(f"  {tag:<10} {count:>8,} {pct:>7.2f}%")
+
+    print("\n## DEPREL Distribution")
+    print(f"  {'Relation':<20} {'Count':>8} {'Percent':>8}")
+    print("  " + "-" * 38)
+    for rel, count in stats['deprel_counts'].most_common():
+        pct = count / total_tokens * 100
+        print(f"  {rel:<20} {count:>8,} {pct:>7.2f}%")
+
+    print("\n## Root UPOS Distribution")
+    print(f"  {'UPOS':<10} {'Count':>8} {'Percent':>8}")
+    print("  " + "-" * 28)
+    total_roots = sum(stats['root_upos_counts'].values())
+    for tag, count in stats['root_upos_counts'].most_common():
+        pct = count / total_roots * 100
+        print(f"  {tag:<10} {count:>8,} {pct:>7.2f}%")
+
+    print("\n" + "=" * 60)
+
+
+def main():
+    # Find train.conllu file
+    base_dir = dirname(dirname(__file__))
+    conllu_file = join(base_dir, 'train.conllu')
+
+    print(f"Reading: {conllu_file}")
+    sentences = parse_conllu(conllu_file)
+
+    stats = compute_statistics(sentences)
+    print_statistics(stats)
+
+
+if __name__ == "__main__":
+    main()