397 lines
16 KiB
Python
397 lines
16 KiB
Python
"""
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Tests for backend/importers/ — the importer registry and each importer module.
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"""
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import os
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import tempfile
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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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from backend.data_types import DataField
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FIXTURES = Path(__file__).parent.parent / "fixtures"
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_SUBMODULE_HINT = (
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"run `git submodule update --init tests/fixtures` to fetch the tono-test-data submodule"
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)
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# ── Registry ─────────────────────────────────────────────────────────────────
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class TestRegistry:
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def test_get_importer_known_extensions(self):
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from backend.importers import get_importer
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for ext in (".gwy", ".sxm", ".ibw", ".npy", ".npz",
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".png", ".jpg", ".jpeg", ".tiff", ".tif", ".bmp",
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".h5", ".hdf5", ".he5"):
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assert get_importer(ext) is not None, f"No importer registered for {ext}"
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def test_get_importer_unknown_extension(self):
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from backend.importers import get_importer
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assert get_importer(".xyz") is None
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assert get_importer(".csv") is None
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def test_get_importer_case_insensitive(self):
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from backend.importers import get_importer
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assert get_importer(".NPY") is get_importer(".npy")
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assert get_importer(".GWY") is get_importer(".gwy")
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def test_all_extensions_returns_frozenset(self):
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from backend.importers import all_extensions
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exts = all_extensions()
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assert isinstance(exts, frozenset)
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assert ".npy" in exts
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assert ".gwy" in exts
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def test_calibrated_extensions(self):
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from backend.importers import calibrated_extensions
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cal = calibrated_extensions()
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# SPM and HDF5 are calibrated
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assert ".gwy" in cal
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assert ".sxm" in cal
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assert ".ibw" in cal
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assert ".h5" in cal
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# Images/arrays are not
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assert ".png" not in cal
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assert ".npy" not in cal
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def test_each_importer_has_required_interface(self):
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from backend.importers import _IMPORTERS
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for mod in _IMPORTERS:
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assert hasattr(mod, "extensions"), f"{mod.__name__} missing extensions"
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assert hasattr(mod, "calibrated"), f"{mod.__name__} missing calibrated"
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assert callable(getattr(mod, "load", None)), f"{mod.__name__} missing load()"
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assert callable(getattr(mod, "channel_names", None)), f"{mod.__name__} missing channel_names()"
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assert isinstance(mod.extensions, frozenset)
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assert isinstance(mod.calibrated, bool)
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# ── array_image importer ──────────────────────────────────────────────────────
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class TestArrayImageImporter:
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def setup_method(self):
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import backend.importers.array_image as mod
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self.mod = mod
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def test_npy_load(self):
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with tempfile.TemporaryDirectory() as tmp:
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data = np.random.default_rng(0).standard_normal((32, 48))
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path = Path(tmp) / "data.npy"
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np.save(path, data)
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fields = self.mod.load(path)
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assert len(fields) == 1
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assert isinstance(fields[0], DataField)
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assert np.allclose(fields[0].data, data)
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def test_npz_load(self):
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with tempfile.TemporaryDirectory() as tmp:
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data = np.random.default_rng(1).standard_normal((16, 16))
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path = Path(tmp) / "data.npz"
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np.savez(path, arr=data)
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fields = self.mod.load(path)
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assert len(fields) == 1
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assert np.allclose(fields[0].data, data)
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def test_png_grayscale(self):
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from PIL import Image as PILImage
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with tempfile.TemporaryDirectory() as tmp:
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arr = np.random.default_rng(2).integers(0, 256, (24, 32), dtype=np.uint8)
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path = Path(tmp) / "gray.png"
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PILImage.fromarray(arr).save(path)
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fields = self.mod.load(path)
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assert len(fields) == 1
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assert fields[0].data.shape == (24, 32)
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assert fields[0].data.dtype == np.float64
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def test_png_rgb_converted_to_grayscale(self):
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from PIL import Image as PILImage
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with tempfile.TemporaryDirectory() as tmp:
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arr = np.random.default_rng(3).integers(0, 256, (16, 16, 3), dtype=np.uint8)
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path = Path(tmp) / "rgb.png"
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PILImage.fromarray(arr).save(path)
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fields = self.mod.load(path)
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assert fields[0].data.shape == (16, 16)
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def test_not_calibrated(self):
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assert self.mod.calibrated is False
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def test_channel_names(self):
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "x.npy"
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np.save(path, np.zeros((4, 4)))
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assert self.mod.channel_names(path) == ["field"]
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def test_fixture_npy(self):
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path = FIXTURES / "nanoparticles.npy"
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if not path.exists():
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pytest.skip(f"nanoparticles.npy fixture not available — {_SUBMODULE_HINT}")
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fields = self.mod.load(path)
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assert len(fields) == 1
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assert fields[0].data.ndim == 2
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# ── ibw importer ─────────────────────────────────────────────────────────────
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class TestIBWImporter:
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def setup_method(self):
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import backend.importers.ibw as mod
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self.mod = mod
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self.fixture = FIXTURES / "Bacteria.ibw"
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def test_calibrated(self):
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assert self.mod.calibrated is True
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def test_extensions(self):
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assert ".ibw" in self.mod.extensions
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def test_load_fixture(self):
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if not self.fixture.exists():
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pytest.skip(f"Bacteria.ibw fixture not available — {_SUBMODULE_HINT}")
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fields = self.mod.load(self.fixture)
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assert len(fields) == 4
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for f in fields:
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assert isinstance(f, DataField)
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assert f.data.ndim == 2
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assert f.data.dtype == np.float64
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assert f.xreal > 0
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assert f.yreal > 0
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def test_channel_names_fixture(self):
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if not self.fixture.exists():
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pytest.skip(f"Bacteria.ibw fixture not available — {_SUBMODULE_HINT}")
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names = self.mod.channel_names(self.fixture)
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assert len(names) == 4
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assert all(isinstance(n, str) for n in names)
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# ── hdf5 importer (generic) ──────────────────────────────────────────────────
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class TestHDF5Importer:
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def setup_method(self):
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pytest.importorskip("h5py")
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import backend.importers.hdf5 as mod
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self.mod = mod
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def test_calibrated(self):
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assert self.mod.calibrated is True
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def test_extensions(self):
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assert {".h5", ".hdf5", ".he5"} <= self.mod.extensions
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def test_load_single_channel(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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data = np.random.default_rng(10).standard_normal((32, 32))
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path = Path(tmp) / "test.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("channel", data=data)
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fields = self.mod.load(path)
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assert len(fields) == 1
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assert np.allclose(fields[0].data, data)
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assert fields[0].data.dtype == np.float64
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def test_load_physical_attrs(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "cal.h5"
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with h5py.File(path, "w") as f:
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ds = f.create_dataset("topo", data=np.zeros((16, 16)))
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ds.attrs["xreal"] = 5e-6
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ds.attrs["yreal"] = 5e-6
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ds.attrs["si_unit_z"] = "V"
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fields = self.mod.load(path)
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assert fields[0].xreal == pytest.approx(5e-6)
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assert fields[0].si_unit_z == "V"
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def test_load_fallback_attrs(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "fallback.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("channel", data=np.zeros((8, 8)))
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fields = self.mod.load(path)
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assert fields[0].xreal == pytest.approx(1e-6)
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assert fields[0].si_unit_xy == "m"
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def test_empty_file_raises(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "empty.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("vec", data=np.zeros((10,)))
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with pytest.raises(ValueError, match="No 2-D"):
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self.mod.load(path)
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def test_channel_names_top_level(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "named.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("height", data=np.zeros((8, 8)))
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f.create_dataset("phase", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert set(names) == {"height", "phase"}
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def test_channel_names_nested(self):
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# Nested datasets return second-to-last path component.
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "nested.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("scan/height/data", data=np.zeros((8, 8)))
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f.create_dataset("scan/phase/data", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert set(names) == {"height", "phase"}
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# ── ergo_hdf5 importer (Asylum Research / Ergo format) ───────────────────────
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class TestErgoHDF5Importer:
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def setup_method(self):
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pytest.importorskip("h5py")
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import backend.importers.ergo_hdf5 as mod
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self.mod = mod
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def _make_h5(self, tmp: Path, data: np.ndarray, name: str = "channel",
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attrs: dict | None = None) -> Path:
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import h5py
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path = tmp / "test.h5"
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with h5py.File(path, "w") as f:
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ds = f.create_dataset(name, data=data)
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for k, v in (attrs or {}).items():
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ds.attrs[k] = v
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return path
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def test_calibrated(self):
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assert self.mod.calibrated is True
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def test_extensions(self):
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assert {".h5", ".hdf5", ".he5"} <= self.mod.extensions
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def test_load_single_channel(self):
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with tempfile.TemporaryDirectory() as tmp:
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data = np.random.default_rng(10).standard_normal((32, 32))
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path = self._make_h5(Path(tmp), data)
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fields = self.mod.load(path)
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assert len(fields) == 1
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assert np.allclose(fields[0].data, data)
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assert fields[0].data.dtype == np.float64
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def test_load_physical_attrs(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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data = np.zeros((16, 16))
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path = Path(tmp) / "cal.h5"
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with h5py.File(path, "w") as f:
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ds = f.create_dataset("topo", data=data)
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ds.attrs["xreal"] = 5e-6
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ds.attrs["yreal"] = 5e-6
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ds.attrs["si_unit_xy"] = "m"
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ds.attrs["si_unit_z"] = "V"
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fields = self.mod.load(path)
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assert fields[0].xreal == pytest.approx(5e-6)
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assert fields[0].yreal == pytest.approx(5e-6)
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assert fields[0].si_unit_z == "V"
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def test_load_fallback_attrs(self):
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with tempfile.TemporaryDirectory() as tmp:
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data = np.zeros((8, 8))
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path = self._make_h5(Path(tmp), data)
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fields = self.mod.load(path)
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# Default fallbacks when no AR sidecar is present
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assert fields[0].xreal == pytest.approx(1e-6)
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assert fields[0].si_unit_xy == "m"
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def test_load_multiple_channels(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "multi.h5"
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data_a = np.ones((16, 16))
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data_b = np.zeros((16, 16))
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with h5py.File(path, "w") as f:
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f.create_dataset("height", data=data_a)
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f.create_dataset("phase", data=data_b)
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fields = self.mod.load(path)
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assert len(fields) == 2
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shapes = {f.data.shape for f in fields}
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assert shapes == {(16, 16)}
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def test_ignores_non_2d_datasets(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "mixed.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("topo", data=np.zeros((16, 16)))
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f.create_dataset("vector", data=np.zeros((10,))) # 1-D, ignored
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f.create_dataset("volume", data=np.zeros((4, 4, 4))) # 3-D, ignored
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fields = self.mod.load(path)
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assert len(fields) == 1
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def test_empty_file_raises(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "empty.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("vec", data=np.zeros((10,)))
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with pytest.raises(ValueError, match="No 2-D"):
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self.mod.load(path)
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def test_channel_names_top_level(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "named.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("height", data=np.zeros((8, 8)))
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f.create_dataset("phase", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert set(names) == {"height", "phase"}
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def test_channel_names_strips_leaf(self):
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# "/image" leaf is stripped; display name is second-to-last component.
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "nested.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("scan/adhesion:retrace/image", data=np.zeros((8, 8)))
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f.create_dataset("scan/phase:retrace/image", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert set(names) == {"adhesion:retrace", "phase:retrace"}
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def test_channel_names_thumbnails_always_filtered(self):
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# All thumbnail datasets are hidden, including global ones.
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "thumbs.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("data/adhesion/image", data=np.zeros((8, 8)))
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f.create_dataset("info/channels/adhesion/thumbnail", data=np.zeros((8, 8)))
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f.create_dataset("info/global/thumbnail", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert names == ["adhesion"]
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def test_channel_names_sorted_alphabetically(self):
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "order.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("data/zzz/image", data=np.zeros((8, 8)))
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f.create_dataset("data/aaa/image", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert names == ["aaa", "zzz"]
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def test_channel_names_deduplication(self):
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# Two kept datasets with the same second-to-last name get disambiguated.
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import h5py
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with tempfile.TemporaryDirectory() as tmp:
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path = Path(tmp) / "dup.h5"
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with h5py.File(path, "w") as f:
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f.create_dataset("dataset/adhesion/imageA", data=np.zeros((8, 8)))
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f.create_dataset("datasetinfo/adhesion/imageB", data=np.zeros((8, 8)))
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names = self.mod.channel_names(path)
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assert set(names) == {"adhesion/imageA", "adhesion/imageB"}
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def test_he5_extension_registered(self):
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from backend.importers import get_importer
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assert get_importer(".he5") is self.mod
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