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https://github.com/lllin000/PaperForge.git
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426 lines
14 KiB
Python
426 lines
14 KiB
Python
from __future__ import annotations
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def test_normalize_strict_inventory_maps_bucket_variants_to_common_fields() -> None:
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from paperforge.worker.ocr_figure_reader import _normalize_strict_figure_inventory
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strict_inventory = {
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"matched_figures": [
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{
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"figure_number": 6,
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"block_id": 15,
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"text": "Fig. 6 The figure represents...",
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"matched_assets": [{"block_id": 40, "bbox": [1, 2, 3, 4]}],
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"match_score": 0.91,
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}
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],
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"ambiguous_figures": [
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{
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"figure_number": 3,
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"legend_block_id": 9,
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"text": "FIGURE 3 | Histological evaluation...",
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"candidates": [
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{"asset_block_id": 10, "match_score": 0.51},
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{"asset_block_id": 11, "match_score": 0.49},
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],
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}
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],
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"unmatched_legends": [
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{
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"block_id": 21,
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"text": "FIGURE 2 | Treadmill exercise protocols...",
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"figure_number": 2,
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}
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],
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"unresolved_clusters": [
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{
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"page": 7,
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"media_block_ids": [30, 31],
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}
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],
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}
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structured_blocks = [
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{
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"block_id": 21,
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"marker_signature": {"type": "figure_number"},
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"zone": "display_zone",
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"style_family": "legend_like",
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}
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]
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normalized = _normalize_strict_figure_inventory(strict_inventory, structured_blocks)
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assert normalized["matched_figures"][0]["legend_block_id"] == 15
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assert normalized["matched_figures"][0]["caption_text"] == "Fig. 6 The figure represents..."
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assert normalized["matched_figures"][0]["asset_block_ids"] == [40]
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assert normalized["ambiguous_figures"][0]["candidate_asset_ids"] == [10, 11]
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assert normalized["unmatched_legends"][0]["legend_block_id"] == 21
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assert normalized["unresolved_clusters"][0]["asset_block_ids"] == [30, 31]
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def test_reader_figure_preserves_separate_reader_and_strict_status() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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normalized_inventory = {
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"matched_figures": [],
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"held_figures": [],
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"ambiguous_figures": [
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{
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"figure_number": 3,
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"legend_block_id": 9,
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"caption_text": "FIGURE 3 | Histological evaluation...",
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"candidate_asset_ids": [10, 11],
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"strict_status": "ambiguous",
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"marker_type": "figure_number",
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}
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],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(normalized_inventory, structured_blocks=[])
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rf = result["reader_figures"][0]
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assert rf["reader_status"] == "GROUPED_APPROXIMATE"
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assert rf["strict_status"] == "ambiguous"
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assert rf["strict_source"] == "ambiguous_figures"
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def test_reader_figure_id_uses_first_asset_id_for_visual_group_when_figure_number_missing() -> None:
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from paperforge.worker.ocr_figure_reader import _stable_reader_figure_id
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assert _stable_reader_figure_id(None, page=7, first_asset_block_id=31, ordinal=2) == "visual_group_7_31_reader"
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def test_coverage_total_counts_deduplicated_eligible_inputs() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"ambiguous_figures": [
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{
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"figure_number": 2,
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"legend_block_id": 21,
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"caption_text": "FIGURE 2 | Treadmill exercise protocols...",
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"candidate_asset_ids": [30, 31],
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"marker_type": "figure_number",
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}
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],
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"unmatched_legends": [
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{
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"figure_number": 2,
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"legend_block_id": 21,
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"caption_text": "FIGURE 2 | Treadmill exercise protocols...",
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"marker_type": "figure_number",
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}
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],
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"matched_figures": [],
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"held_figures": [],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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assert result["reader_coverage"]["total"] == 1
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def test_ambiguous_without_formal_legend_does_not_enter_reader_layer() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"matched_figures": [],
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"held_figures": [],
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"ambiguous_figures": [
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{
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"legend_block_id": 50,
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"caption_text": "Figure 2 shows the progression...",
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"candidate_asset_ids": [70],
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"marker_type": "figure_number",
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"inline_mention": True,
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}
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],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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assert result["reader_figures"] == []
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assert result["reader_coverage"]["total"] == 0
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def test_grouped_approximate_requires_visual_candidates() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"matched_figures": [],
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"held_figures": [],
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"ambiguous_figures": [
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{
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"figure_number": 4,
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"legend_block_id": 44,
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"caption_text": "FIGURE 4 | Immunohistochemical staining...",
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"candidate_asset_ids": [],
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"marker_type": "figure_number",
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}
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],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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assert len(result["reader_figures"]) == 1
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rf = result["reader_figures"][0]
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assert rf["reader_status"] == "LEGEND_ONLY"
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assert rf["visual_groups"] == [
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{
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"page": None,
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"asset_block_ids": [],
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"group_status": "legend_only_group",
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"rendered_as_representative": False,
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}
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]
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def test_reader_hold_does_not_default_to_caption_consumption() -> None:
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from paperforge.worker.ocr_figure_reader import _materialize_hold_outcome
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hold = _materialize_hold_outcome(
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legend_block_id=80,
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caption_text="weak fragment",
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page=10,
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candidate_asset_ids=[],
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hold_visibility="audit_hold",
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)
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assert hold["consumed_caption_block_ids"] == []
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assert hold["debug_refs"]["hold_visibility"] == "audit_hold"
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def test_legend_only_consumes_caption_when_rendered() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"matched_figures": [],
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"held_figures": [],
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"ambiguous_figures": [],
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"unmatched_legends": [
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{
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"figure_number": 2,
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"legend_block_id": 21,
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"caption_text": "FIGURE 2 | Treadmill exercise protocols...",
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"marker_type": "figure_number",
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}
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],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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assert len(result["reader_figures"]) == 1
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rf = result["reader_figures"][0]
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assert rf["reader_status"] == "LEGEND_ONLY"
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assert rf["consumed_caption_block_ids"] == [{"page": None, "block_id": 21}]
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def test_reader_sequence_match_promoted_figure_gets_proper_status() -> None:
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"""A figure promoted via sequence_match must get SEQUENCE_MATCH reader_status."""
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"matched_figures": [
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{
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"figure_number": 2,
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"legend_block_id": 12,
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"text": "Figure 2. Histological analysis.",
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"matched_assets": [],
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"match_score": {"score": 0.0, "decision": "sequence_match", "evidence": ["sequence_promotion"]},
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"flags": ["sequence_match"],
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"strict_status": "sequence_match",
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"marker_type": "figure_number",
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}
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],
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"held_figures": [],
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"ambiguous_figures": [],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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assert len(result["reader_figures"]) == 1
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rf = result["reader_figures"][0]
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assert rf["reader_status"] == "SEQUENCE_MATCH", f"Expected SEQUENCE_MATCH, got {rf['reader_status']}"
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assert rf["strict_status"] == "sequence_match"
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assert rf["strict_source"] == "matched_figures"
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def test_reader_payload_coverage_accounted_matches_reader_figures() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"matched_figures": [
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{
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"figure_number": 1,
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"legend_block_id": 5,
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"text": "Fig. 1 Overview of the system...",
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"matched_assets": [{"block_id": 10, "bbox": [1, 2, 3, 4]}],
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"match_score": 0.91,
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"marker_type": "figure_number",
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}
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],
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"held_figures": [],
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"ambiguous_figures": [],
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"unmatched_legends": [
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{
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"figure_number": 2,
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"legend_block_id": 21,
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"text": "FIGURE 2 | Treadmill exercise protocols...",
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"marker_type": "figure_number",
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}
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],
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"unresolved_clusters": [],
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}
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result = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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assert result["reader_coverage"]["total"] == 2
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assert result["reader_coverage"]["accounted"] == 2
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assert result["reader_coverage"]["gap_count"] == 0
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assert result["reader_coverage"]["ratio"] == 1.0
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assert result["consumed_caption_block_ids"] == [
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{"page": None, "block_id": 5},
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{"page": None, "block_id": 21},
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]
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def test_reader_figures_emit_from_matched_or_unresolved_object_inputs() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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payload = synthesize_reader_figures(
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{
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"matched_figures": [
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{
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"figure_id": "figure_001",
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"page": 2,
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"legend_block_id": 21,
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"asset_block_ids": [90],
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"strict_status": "matched",
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}
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],
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"held_figures": [],
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"ambiguous_figures": [],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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},
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structured_blocks=[{"block_id": 21, "page": 2, "role": "figure_caption_candidate", "text": "Fig. 1 Caption"}],
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)
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assert len(payload["reader_figures"]) >= 1
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def test_reader_normalization_keeps_same_block_id_legends_separate_by_page() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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structured_blocks = [
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{
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"page": 5,
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"block_id": 5,
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"role": "figure_caption",
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"text": "Fig. 1 Critical shoulder angle.",
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"marker_signature": {"type": "figure_number", "number": 1},
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"style_family": "legend_like",
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"zone": "display_zone",
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},
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{
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"page": 6,
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"block_id": 5,
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"role": "figure_caption",
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"text": "Fig. 5 Acromial index.",
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"marker_signature": {"type": "figure_number", "number": 5},
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"style_family": "legend_like",
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"zone": "display_zone",
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},
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]
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strict_inventory = {
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"figure_legends": structured_blocks,
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"unmatched_legends": [structured_blocks[0], structured_blocks[1]],
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}
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payload = synthesize_reader_figures(strict_inventory, structured_blocks)
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numbers = [item["figure_number"] for item in payload["normalized_inputs"]["unmatched_legends"]]
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rendered_numbers = [item["figure_number"] for item in payload["reader_figures"]]
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assert numbers == [1, 5]
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assert rendered_numbers == [1, 5]
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def test_reader_materializes_grouped_strict_match_as_single_visual_group() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"figure_legends": [],
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"matched_figures": [
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{
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"figure_number": 2,
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"legend_block_id": 10,
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"page": 3,
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"text": "Fig. 2 A and B, paired figure.",
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"matched_assets": [
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{"block_id": 20, "bbox": [100, 100, 300, 300]},
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{"block_id": 21, "bbox": [320, 100, 520, 300]},
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],
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"match_score": {"score": 0.82, "decision": "matched", "evidence": ["same_row_pair"]},
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"caption_score": {"score": 0.9},
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}
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],
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"held_figures": [],
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"ambiguous_figures": [],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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}
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payload = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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rf = payload["reader_figures"][0]
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assert rf["figure_number"] == 2
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assert len(rf["visual_groups"]) == 1
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assert rf["visual_groups"][0]["asset_block_ids"] == [20, 21]
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assert rf["visual_groups"][0]["group_status"] == "matched_group"
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def test_reader_matched_cross_page_figure_consumes_caption_on_legend_page() -> None:
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from paperforge.worker.ocr_figure_reader import synthesize_reader_figures
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strict_inventory = {
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"figure_legends": [],
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"matched_figures": [
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{
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"figure_id": "figure_004",
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"figure_number": 4,
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"legend_block_id": 6,
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"page": 12,
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"legend_page": 13,
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"asset_pages": [12],
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"text": "Figure 4. Cross-page caption.",
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"matched_assets": [
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{"block_id": 101, "bbox": [100, 100, 300, 300]},
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],
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"asset_block_ids": [101],
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"strict_status": "matched",
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"match_score": {"score": 0.8, "decision": "matched"},
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}
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],
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"held_figures": [],
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"ambiguous_figures": [],
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"unmatched_legends": [],
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"unresolved_clusters": [],
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}
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payload = synthesize_reader_figures(strict_inventory, structured_blocks=[])
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rf = payload["reader_figures"][0]
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assert rf["visual_groups"][0]["page"] == 12
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assert rf["consumed_caption_block_ids"] == [{"page": 13, "block_id": 6}]
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assert payload["consumed_caption_block_ids"] == [{"page": 13, "block_id": 6}]
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