188 lines
6 KiB
Python
188 lines
6 KiB
Python
from __future__ import annotations
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from repixelizer.inference import (
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SpacingEstimate,
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_axis_prior_from_estimates,
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_candidate_dims,
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_combine_axis_priors,
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_hint_target_sizes_from_spacing,
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_resolve_candidate_dims_from_spacing,
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_top_candidates_by_size,
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infer_fixed_lattice,
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infer_lattice,
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)
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from repixelizer.types import InferenceCandidate
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from repixelizer.synthetic import fake_pixelize, make_emblem
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def _make_spacing_estimate(
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*,
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best_cell: int,
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confidence: float,
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peaks: dict[int, float],
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start: int = 2,
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stop: int = 24,
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) -> SpacingEstimate:
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candidate_cells = tuple(float(cell) for cell in range(start, stop + 1))
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candidate_scores: list[float] = []
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for cell in range(start, stop + 1):
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score = 0.16
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for peak_cell, peak_score in peaks.items():
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distance = abs(cell - peak_cell)
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if distance == 0:
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score = max(score, peak_score)
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elif distance == 1:
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score = max(score, peak_score - 0.14)
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candidate_scores.append(float(score))
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return SpacingEstimate(
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spacing=float(best_cell),
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confidence=confidence,
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best_cell=float(best_cell),
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best_score=float(peaks[best_cell]),
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candidate_cells=candidate_cells,
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candidate_scores=tuple(candidate_scores),
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)
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def test_axis_prior_stays_close_to_spacing_when_autocorr_hits_large_multiple() -> None:
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prior, reliability = _axis_prior_from_estimates(8.0, 0.75, 32.0)
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assert prior < 10.0
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assert reliability > 0.6
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def test_combined_axis_prior_prefers_consistent_shared_cell_size() -> None:
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shared_prior, reliability = _combine_axis_priors([(9.0, 0.7), (11.2, 0.2)])
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assert 8.5 < shared_prior < 10.5
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assert 0.2 < reliability < 0.6
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def test_spacing_hints_can_add_dense_candidates_around_true_size() -> None:
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hinted_sizes = _hint_target_sizes_from_spacing(
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1024,
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1024,
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(8.05, 0.74),
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(4.0, 0.08),
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)
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dims = _candidate_dims(1024, 1024, None, hinted_sizes=hinted_sizes)
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sizes = {width for width, _ in dims}
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assert 128 in sizes
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def test_strong_spacing_signal_can_collapse_candidate_search_to_single_size() -> None:
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dims = _resolve_candidate_dims_from_spacing(
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1024,
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1024,
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None,
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hinted_sizes=[128],
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spacing_x=(8.0, 0.82),
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spacing_y=(8.02, 0.78),
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prior_reliability=0.74,
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)
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sizes = {width for width, _ in dims}
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assert sizes == {128}
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def test_weak_spacing_signal_without_spectrum_keeps_broad_candidate_search() -> None:
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dims = _resolve_candidate_dims_from_spacing(
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1024,
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1024,
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None,
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hinted_sizes=[128],
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spacing_x=(8.0, 0.18),
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spacing_y=(8.1, 0.12),
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prior_reliability=0.24,
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)
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sizes = {width for width, _ in dims}
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assert 128 in sizes
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assert len(sizes) > 10
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def test_weak_spacing_signal_uses_spectrum_modes_to_keep_candidate_search_compact() -> None:
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spectrum = _make_spacing_estimate(
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best_cell=8,
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confidence=0.18,
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peaks={4: 0.78, 8: 0.74, 16: 0.71},
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)
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dims = _resolve_candidate_dims_from_spacing(
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1024,
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1024,
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None,
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hinted_sizes=[128],
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spacing_x=(8.0, 0.18),
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spacing_y=(8.1, 0.12),
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prior_reliability=0.24,
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spacing_x_estimate=spectrum,
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spacing_y_estimate=spectrum,
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)
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sizes = {width for width, _ in dims}
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assert sizes
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assert len(sizes) <= 12
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assert any(abs(size - 128) <= 1 for size in sizes)
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assert all(any(abs(size - target) <= 2 for target in (64, 128, 256)) for size in sizes)
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def test_top_candidates_are_diversified_by_size() -> None:
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candidates = [
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InferenceCandidate(target_width=113, target_height=113, phase_x=0.0, phase_y=0.0, score=0.90, breakdown={}),
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InferenceCandidate(target_width=113, target_height=113, phase_x=0.2, phase_y=0.0, score=0.89, breakdown={}),
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InferenceCandidate(target_width=117, target_height=117, phase_x=0.0, phase_y=0.0, score=0.88, breakdown={}),
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InferenceCandidate(target_width=128, target_height=128, phase_x=0.0, phase_y=0.0, score=0.87, breakdown={}),
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]
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selected = _top_candidates_by_size(candidates, limit=8)
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assert [(candidate.target_width, candidate.phase_x) for candidate in selected] == [
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(113, 0.0),
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(117, 0.0),
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(128, 0.0),
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]
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def test_infer_lattice_recovers_emblem_scale() -> None:
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source = make_emblem(32, 32)
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fake = fake_pixelize(
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source,
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upscale=12,
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phase_x=0.2,
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phase_y=0.35,
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blur_radius=0.75,
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warp_strength=0.28,
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warp_detail=6,
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seed=5,
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)
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result = infer_lattice(fake)
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assert result.target_width in range(28, 37)
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assert result.target_height in range(28, 37)
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assert result.confidence >= 0.0
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def test_infer_fixed_lattice_honors_exact_size_and_phase() -> None:
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source = make_emblem(16, 16)
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fake = fake_pixelize(source, upscale=10, phase_x=0.2, phase_y=-0.2, blur_radius=0.4, seed=9)
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result = infer_fixed_lattice(
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fake,
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target_width=16,
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target_height=16,
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phase_x=0.2,
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phase_y=-0.2,
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device="cpu",
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)
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assert result.target_width == 16
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assert result.target_height == 16
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assert abs(result.phase_x - 0.2) <= 1e-6
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assert abs(result.phase_y + 0.2) <= 1e-6
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assert len(result.top_candidates) == 1
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def test_infer_fixed_lattice_searches_phase_within_pinned_size() -> None:
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source = make_emblem(16, 16)
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fake = fake_pixelize(source, upscale=8, phase_x=0.2, phase_y=0.25, blur_radius=0.45, seed=3)
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result = infer_fixed_lattice(
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fake,
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target_width=16,
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target_height=16,
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device="cpu",
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)
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assert result.target_width == 16
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assert result.target_height == 16
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assert len(result.top_candidates) > 1
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assert all(candidate.target_width == 16 for candidate in result.top_candidates)
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assert all(candidate.target_height == 16 for candidate in result.top_candidates)
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