1. added blender deformation probe for marker size picking and optimization
2. added unwarp map export in current cli, don't need to generate by precompute in sensor running
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ykcheungab
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"""Tests for `probe_plot`: the optical-flow figures.
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matplotlib is an optional extra, so the whole module is skipped when it is absent —
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but nothing here needs Blender or cv2. Every figure is built from synthetic arrays and
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tiny JSON fixtures, which is deliberate: the figures are a view of measurements, so
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they must be testable without making a measurement.
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"""
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from __future__ import annotations
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import json
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from pathlib import Path
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import numpy as np
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import pytest
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pytest.importorskip("matplotlib")
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from orisys_sensor_design import probe_plot # noqa: E402
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PNG_MAGIC = b"\x89PNG\r\n\x1a\n"
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def _flow(height: int = 60, width: int = 60, value: float = 0.4) -> np.ndarray:
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flow = np.zeros((height, width, 2), dtype=np.float32)
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flow[..., 0] = value
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return flow
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def _panel(**overrides) -> dict:
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panel = {
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"label": "nx=31, dis_mode=1",
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"flow": _flow(),
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"roi": {"u": 30.0, "v": 30.0, "radius": 6.6},
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"cell_px": 16.13,
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"effective_patch_px": 16.0,
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"applied_px": 1.325,
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"response_px": 0.886,
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"direction_px": [1.0, 0.0],
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"scale_note": "render 500x500 | patch 8 px, finest 1",
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"note": "",
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}
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panel.update(overrides)
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return panel
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def _assert_png(path: Path) -> None:
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assert path.is_file()
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assert path.stat().st_size > 0
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assert path.read_bytes()[:8] == PNG_MAGIC
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def test_flow_comparison_writes_a_png(tmp_path: Path) -> None:
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out = probe_plot.render_flow_comparison(
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panels=[_panel(label="nx=31"), _panel(label="nx=80", cell_px=6.25, flow=_flow(value=0.9))],
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out_path=tmp_path / "flow.png",
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)
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_assert_png(out)
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def test_flow_comparison_annotates_a_missing_flow_array(tmp_path: Path) -> None:
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"""A failed setting must appear as a named placeholder, not vanish."""
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out = probe_plot.render_flow_comparison(
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panels=[
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_panel(label="ok"),
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_panel(label="broken", flow=None, note="missing flow array 010_x.npy"),
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],
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out_path=tmp_path / "flow_missing.png",
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)
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_assert_png(out)
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def test_flow_comparison_handles_empty_and_tiny_inputs(tmp_path: Path) -> None:
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out = probe_plot.render_flow_comparison(panels=[], out_path=tmp_path / "empty.png")
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_assert_png(out)
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tiny = _flow(height=3, width=3, value=0.1)
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out = probe_plot.render_flow_comparison(
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panels=[_panel(flow=tiny, roi={"u": 1.0, "v": 1.0, "radius": 0.5})],
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out_path=tmp_path / "tiny.png",
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)
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_assert_png(out)
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def test_tuning_writes_both_panels(tmp_path: Path) -> None:
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out = probe_plot.render_tuning(
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series=[
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{
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"label": "render | dis_mode=1",
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"points": [
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{"nx": 31, "cell_px": 16.13, "effective_patch_px": 16.0, "score": 69.2},
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{"nx": 80, "cell_px": 6.25, "effective_patch_px": 16.0, "score": 40.5},
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],
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},
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{
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"label": "render | dis_mode=0",
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"points": [
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{"nx": 31, "cell_px": 16.13, "effective_patch_px": 8.0, "score": 20.0},
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{"nx": 80, "cell_px": 6.25, "effective_patch_px": 8.0, "score": 55.0},
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],
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},
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],
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out_path=tmp_path / "tuning.png",
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patch_px=8.0,
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)
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_assert_png(out)
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def test_tuning_with_no_points_still_writes_a_placeholder(tmp_path: Path) -> None:
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out = probe_plot.render_tuning(series=[], out_path=tmp_path / "tuning_empty.png")
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_assert_png(out)
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def test_response_curves_writes_with_a_per_curve_floor(tmp_path: Path) -> None:
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out = probe_plot.render_response_curves(
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curves=[
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{
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"label": "nx=80 r=0.5 mm dm=1",
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"verdict": "resolvable",
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"score": 57.7,
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"floor_px": 0.0155,
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"points": [
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{"step_mm": 0.01, "response_px": 0.08, "applied_px": 0.13},
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{"step_mm": 0.10, "response_px": 0.89, "applied_px": 1.32},
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],
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},
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{
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"label": "nx=31 r=0.5 mm dm=1",
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"verdict": "resolvable",
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"score": 12.3,
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# A different floor, so the two must get their own lines.
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"floor_px": 0.0372,
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"points": [
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{"step_mm": 0.01, "response_px": 0.08, "applied_px": 0.13},
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{"step_mm": 0.10, "response_px": 0.48, "applied_px": 1.32},
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],
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},
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],
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out_path=tmp_path / "response.png",
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axis="x",
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)
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_assert_png(out)
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def test_response_curves_adds_a_retention_panel(tmp_path: Path) -> None:
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"""Retention is the panel that exposes a pattern collapsing under noise."""
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out = probe_plot.render_response_curves(
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curves=[
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{
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"label": "nx=80 r=0.5 mm dm=1",
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"points": [{"step_mm": 0.10, "response_px": 0.90, "applied_px": 1.32}],
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"floor_px": 0.0155,
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"retention": [
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{"sigma": 4.0, "response_retention": 0.99},
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{"sigma": 16.0, "response_retention": 0.84},
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],
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},
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{
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"label": "nx=31 r=0.5 mm dm=1",
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"points": [{"step_mm": 0.10, "response_px": 0.48, "applied_px": 1.32}],
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"floor_px": 0.0372,
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"retention": [
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{"sigma": 4.0, "response_retention": 0.72},
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{"sigma": 16.0, "response_retention": 0.59},
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],
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},
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],
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out_path=tmp_path / "retention.png",
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axis="x",
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)
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_assert_png(out)
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def test_response_curve_labels_must_be_unique_to_be_useful(tmp_path: Path) -> None:
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"""Regression: the old label was `nx=.. dm..` and omitted the radius, so two runs
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(nx80@r0.5@dm0 and nx80@r1.5@dm0) produced identical legend entries."""
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runs = [
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("nx=80 r=0.5 mm dm=0", 0.03),
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("nx=80 r=1.5 mm dm=0", 0.09),
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]
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out = probe_plot.render_response_curves(
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curves=[
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{
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"label": label,
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"points": [{"step_mm": 0.10, "response_px": 0.9, "applied_px": 1.32}],
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"floor_px": floor,
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}
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for label, floor in runs
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],
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out_path=tmp_path / "unique.png",
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axis="x",
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)
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_assert_png(out)
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assert len({label for label, _ in runs}) == 2
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def test_response_curves_without_curves(tmp_path: Path) -> None:
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out = probe_plot.render_response_curves(
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curves=[], out_path=tmp_path / "response_empty.png"
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)
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_assert_png(out)
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def _write_run(directory: Path, *, nx: int = 31, include_flow: bool = True) -> None:
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directory.mkdir(parents=True, exist_ok=True)
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frames_dir = directory / "frames"
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frames_dir.mkdir(exist_ok=True)
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frame_name = "000_reference"
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(frames_dir / f"{frame_name}.png").write_bytes(PNG_MAGIC)
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manifest = {
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"width": 500,
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"height": 500,
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"probe_roi_px": {"u": 30.0, "v": 30.0, "radius": 6.6},
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"frames": [
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{"index": 0, "name": frame_name, "axis": None, "step_mm": 0.0,
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"png": f"frames/{frame_name}.png", "centroid_px": [30.0, 30.0]},
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{"index": 1, "name": "001_x_+0.10mm", "axis": "x", "step_mm": 0.10,
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"png": "frames/001_x_+0.10mm.png", "centroid_px": [31.3, 30.0]},
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],
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}
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(directory / "render_manifest.json").write_text(json.dumps(manifest), encoding="utf-8")
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flow_report = {
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"tracker": {"patch_px": 8, "finest_scale": 1},
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"scales": [
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{"name": "render", "width": 500, "height": 500,
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"frames": [{"name": "001_x_+0.10mm",
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"roi": {"u": 30.0, "v": 30.0, "radius": 6.6, "pixels": 139}}]}
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],
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}
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(directory / "flow_report.json").write_text(json.dumps(flow_report), encoding="utf-8")
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sensitivity = {
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"scales": [
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{"name": "render", "cell_px": 500.0 / nx, "effective_patch_px": 16.0,
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"axes": [{"axis": "x", "direction_px": [1.0, 0.0],
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"points": [{"step_mm": 0.10, "response_px": 0.886,
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"applied_px": 1.325}]}]}
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]
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}
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(directory / "sensitivity_report.json").write_text(json.dumps(sensitivity), encoding="utf-8")
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if include_flow:
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flow_dir = directory / "flow" / "render"
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flow_dir.mkdir(parents=True, exist_ok=True)
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np.save(flow_dir / "001_x_+0.10mm.npy", _flow())
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def test_panel_from_run_reads_the_artifacts(tmp_path: Path) -> None:
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_write_run(tmp_path, nx=31)
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panel = probe_plot.panel_from_run(label="nx=31", output_dir=tmp_path, axis="x", step_mm=0.10)
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assert panel["label"] == "nx=31"
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assert panel["flow"] is not None
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assert panel["response_px"] == pytest.approx(0.886)
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assert panel["applied_px"] == pytest.approx(1.325)
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assert panel["cell_px"] == pytest.approx(500.0 / 31)
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assert panel["effective_patch_px"] == pytest.approx(16.0)
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assert "patch 8 px" in panel["scale_note"]
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def test_panel_from_run_names_a_missing_flow_array(tmp_path: Path) -> None:
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_write_run(tmp_path, include_flow=False)
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panel = probe_plot.panel_from_run(label="broken", output_dir=tmp_path, axis="x", step_mm=0.10)
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assert panel["flow"] is None
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assert "missing flow array" in panel["note"]
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def test_panel_from_run_survives_no_artifacts_at_all(tmp_path: Path) -> None:
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empty = tmp_path / "nothing"
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empty.mkdir()
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panel = probe_plot.panel_from_run(label="empty", output_dir=empty, axis="x", step_mm=0.10)
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assert panel["flow"] is None
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assert panel["cell_px"] is None
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# And the figure must still be drawable from it.
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out = probe_plot.render_flow_comparison(panels=[panel], out_path=tmp_path / "none.png")
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_assert_png(out)
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