diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 00000000..4c1144cc --- /dev/null +++ b/.dockerignore @@ -0,0 +1,53 @@ +# Git +.git +.gitignore +.github + +# Python +__pycache__ +*.py[cod] +*$py.class +*.so +.Python +*.egg-info +dist +build +.venv +venv +env +ENV + +# Testing +.pytest_cache +.coverage +htmlcov +.tox +.mypy_cache +.ruff_cache + +# Documentation +site +docs/requirements.txt + +# IDE +.vscode +.idea +*.swp +*.swo +*~ + +# OS +.DS_Store +Thumbs.db + +# Project specific +scripts/*.ipynb +scripts/*.nii +scripts/*.tiff +scripts/*.jpeg +scripts/*.yaml +tests/data + +# Poetry +poetry.lock.bak + diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index a1222a63..4049340b 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -37,4 +37,4 @@ jobs: run: poetry install --with dev --extras all - name: Run the automated tests run: poetry run pytest -v - working-directory: ./tests + working-directory: tests diff --git a/.github/workflows/docker-build.yml b/.github/workflows/docker-build.yml new file mode 100644 index 00000000..bf3e22c7 --- /dev/null +++ b/.github/workflows/docker-build.yml @@ -0,0 +1,66 @@ +name: Build and Push Docker Image + +on: + push: + branches: + - main + - master + tags: + - 'v*' + pull_request: + branches: + - main + - master + workflow_dispatch: + +env: + REGISTRY: ghcr.io + IMAGE_NAME: ${{ github.repository }} + +jobs: + build-and-push: + runs-on: ubuntu-latest + permissions: + contents: read + packages: write + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Set up Docker Buildx + uses: docker/setup-buildx-action@v3 + + - name: Log in to Container Registry + if: github.event_name != 'pull_request' + uses: docker/login-action@v3 + with: + registry: ${{ env.REGISTRY }} + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Extract metadata (tags, labels) for Docker + id: meta + uses: docker/metadata-action@v5 + with: + images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} + tags: | + type=ref,event=branch + type=ref,event=pr + type=semver,pattern={{version}} + type=semver,pattern={{major}}.{{minor}} + type=semver,pattern={{major}} + type=sha,prefix={{branch}}-,enable=${{ github.event_name != 'pull_request' }} + type=sha,enable=${{ github.event_name == 'pull_request' }} + type=raw,value=latest,enable={{is_default_branch}} + + - name: Build and push Docker image + uses: docker/build-push-action@v5 + with: + context: . + push: ${{ github.event_name != 'pull_request' }} + tags: ${{ steps.meta.outputs.tags }} + labels: ${{ steps.meta.outputs.labels }} + cache-from: type=gha + cache-to: type=gha,mode=max + diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 00000000..15387200 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,62 @@ +# ---------------------------------------------------------------------------- +# STAGE 1: Builder +# Used to install Poetry, compile dependencies, and create the virtual environment. +# ---------------------------------------------------------------------------- +FROM python:3.11-slim AS builder + +# Set working directory +WORKDIR /app + +# Install build dependencies (GCC, etc.) +# We need these to compile packages, but we don't want them in the final image. +RUN apt-get update && apt-get install -y \ + build-essential \ + && rm -rf /var/lib/apt/lists/* + +# Install Poetry +RUN pip install poetry==1.8.4 + +# Configure Poetry to create the venv inside the project folder +# This makes it easy to copy the whole folder to the next stage +ENV POETRY_NO_INTERACTION=1 \ + POETRY_VIRTUALENVS_IN_PROJECT=1 \ + POETRY_VIRTUALENVS_CREATE=1 \ + POETRY_CACHE_DIR=/tmp/poetry_cache + +# Copy dependency definition files first (for caching) +COPY pyproject.toml poetry.lock ./ +RUN poetry lock +# Install dependencies (only the libraries) +RUN poetry install --no-root --no-dev --extras all && rm -rf $POETRY_CACHE_DIR + +# Copy the rest of the application code +COPY . . +RUN poetry lock +# Install the application itself +#RUN poetry install --no-dev --extras all +RUN poetry build -f wheel +RUN ./.venv/bin/pip install dist/*.whl +# ---------------------------------------------------------------------------- +# STAGE 2: Runtime +# A fresh, empty image that only contains the Python runtime and our copied venv. +# ---------------------------------------------------------------------------- +FROM python:3.11-slim AS runtime + +WORKDIR /app + +# Create a non-root user for security (Best Practice) +RUN useradd -m -r appuser && chown appuser /app +USER appuser + +# Copy the virtual environment from the builder stage +# We assume the path structure is identical (/app/.venv) +COPY --from=builder --chown=appuser:appuser /app/.venv /app/.venv + +# Update PATH environment variable +# This allows us to type 'linc-convert' instead of '/app/.venv/bin/linc-convert' +ENV PATH="/app/.venv/bin:$PATH" +LABEL org.opencontainers.image.source=https://github.com/lincbrain/linc-convert +# Set the entrypoint +ENTRYPOINT ["linc-convert"] +# Default command +CMD ["--help"] diff --git a/linc_convert/modalities/lsm/__init__.py b/linc_convert/modalities/lsm/__init__.py index 402fb20f..690f9ba1 100644 --- a/linc_convert/modalities/lsm/__init__.py +++ b/linc_convert/modalities/lsm/__init__.py @@ -3,8 +3,24 @@ try: import tifffile as _ # noqa: F401 - __all__ = ["cli", "mosaic", "multi_slice", "spool"] + __all__ = [ + "cli", + "mosaic", + "multi_slice", + "spool", + "single_volume", + "strip", + "stitch_strips" + ] - from . import cli, mosaic, multi_slice, spool + from . import ( + cli, + mosaic, + multi_slice, + single_volume, + spool, + stitch_strips, + strip, + ) except ImportError: pass diff --git a/linc_convert/modalities/lsm/mosaic.py b/linc_convert/modalities/lsm/mosaic.py index 9af053e8..f6989448 100644 --- a/linc_convert/modalities/lsm/mosaic.py +++ b/linc_convert/modalities/lsm/mosaic.py @@ -4,6 +4,7 @@ Example input files can be found at https://lincbrain.org/dandiset/000004/0.240319.1924/files?location=derivatives%2F """ + import logging # stdlib diff --git a/linc_convert/modalities/lsm/multi_slice.py b/linc_convert/modalities/lsm/multi_slice.py index 9e4f958b..592584cd 100644 --- a/linc_convert/modalities/lsm/multi_slice.py +++ b/linc_convert/modalities/lsm/multi_slice.py @@ -4,6 +4,7 @@ Example input files can be found at https://lincbrain.org/dandiset/000010/draft/files?location=sourcedata%2Fderivatives """ + import logging # stdlib @@ -45,7 +46,7 @@ def convert( ) -> None: """ Convert a collection of tiff files generated by the LSM pipeline into a Zarr. - + Parameters ---------- inp diff --git a/linc_convert/modalities/lsm/single_volume.py b/linc_convert/modalities/lsm/single_volume.py new file mode 100644 index 00000000..9bab9e50 --- /dev/null +++ b/linc_convert/modalities/lsm/single_volume.py @@ -0,0 +1,94 @@ +"""Converts TIFF to OME-Zarr or NIfTI-Zarr.""" + +import logging +import os + +import cyclopts +import dask.array as da +import dask_image.imread +import numpy as np + +from linc_convert.modalities.lsm.cli import lsm +from linc_convert.utils.io.zarr import from_config +from linc_convert.utils.nifti_header import build_nifti_header +from linc_convert.utils.unit import to_ome_unit +from linc_convert.utils.zarr_config import ( + GeneralConfig, + NiftiConfig, + ZarrConfig, + autoconfig, +) + +logger = logging.getLogger(__name__) +single_volume = cyclopts.App(name="single_volume", help_format="markdown") +lsm.command(single_volume) + + +@single_volume.default +@autoconfig +def convert( + inp: str, + *, + voxel_size: list[float] = (1, 1, 1), + general_config: GeneralConfig = None, + zarr_config: ZarrConfig = None, + nii_config: NiftiConfig = None, +) -> None: + """ + Tiff to OME-Zarr. + + Convert tiff files + into a pyramidal OME-ZARR (or NIfTI-Zarr) hierarchy. + + Parameters + ---------- + inp + Path to the input tiff file + voxel_size + Voxel size along the X, Y and Z dimensions, in microns. + general_config + General configuration + zarr_config + Zarr related configuration + nii_config + NIfTI header related configuration + """ + general_config.set_default_name(os.path.splitext(inp)[0]) + + inp_data = dask_image.imread.imread(inp) + + # Prepare Zarr group + zgroup = from_config(general_config.out, zarr_config) + + if not hasattr(inp_data, "dtype"): + raise Exception("Input is not a numpy array. This is unexpected.") + + dataset = zgroup.create_array( + "0", + shape=inp_data.shape, + dtype=np.dtype(inp_data.dtype), + zarr_config=zarr_config, + ) + + if dataset.shards: + inp_data = da.rechunk(inp_data, dataset.shards) + else: + inp_data = da.rechunk(inp_data, dataset.chunks) + + da.store(inp_data, dataset) + voxel_size = list(map(float, reversed(voxel_size))) + # Generate Zarr pyramid and metadata + zgroup.generate_pyramid(mode="mean", no_pyramid_axis=zarr_config.no_pyramid_axis) + logger.info("Write OME-Zarr multiscale metadata") + zgroup.write_ome_metadata(axes=["z", "y", "x"], space_unit=to_ome_unit("um")) + + if nii_config.nii: + header = build_nifti_header( + zgroup=zgroup, + voxel_size_zyx=tuple(voxel_size), + unit="micrometer", + nii_config=nii_config, + ) + zgroup.write_nifti_header(header) + + logger.info("Conversion complete.") diff --git a/linc_convert/modalities/lsm/spool.py b/linc_convert/modalities/lsm/spool.py index 86d98016..97697aed 100644 --- a/linc_convert/modalities/lsm/spool.py +++ b/linc_convert/modalities/lsm/spool.py @@ -5,6 +5,7 @@ https://lincbrain.org/dandiset/000010/draft/files?location=sourcedata%2Frawdata %2Fmicr%2Fsample18_run10__y10_z01_HR&page=1 """ + import logging # stdlib @@ -233,4 +234,3 @@ def convert( omz.write_nifti_header(header) logger.info("Conversion complete.") - diff --git a/linc_convert/modalities/lsm/strip.py b/linc_convert/modalities/lsm/strip.py new file mode 100644 index 00000000..5fc411b5 --- /dev/null +++ b/linc_convert/modalities/lsm/strip.py @@ -0,0 +1,114 @@ +""" +Convert spool .dat files set in one strip generated by the LSM pipeline into a zarr. + +Example input files can be found at +https://lincbrain.org/dandiset/000010/draft/files?location=sourcedata%2Frawdata +%2Fmicr%2Fsample18_run10__y10_z01_HR&page=1 +""" + +# stdlib +import logging +import os.path as op +from typing import Optional + +# externals +import cyclopts +import dask.array as da +import numpy as np +from PIL import Image + +# internals +from linc_convert.modalities.lsm.cli import lsm +from linc_convert.utils.io.spool import SpoolSetInterpreter +from linc_convert.utils.io.zarr import from_config +from linc_convert.utils.nifti_header import build_nifti_header +from linc_convert.utils.zarr_config import ( + GeneralConfig, + NiftiConfig, + ZarrConfig, + autoconfig, +) + +logger = logging.getLogger(__name__) +strip = cyclopts.App(name="strip", help_format="markdown") +lsm.command(strip) + +def _save_mip_image(result: da.Array, mip_image_output: str) -> None: + """Save the maximum intensity projection of the result as an image.""" + mip = da.nanmax(result, axis=0) + mip = mip.compute() + mip = mip.astype(np.uint16) + Image.fromarray(mip).save(mip_image_output) + + +@strip.default +@autoconfig +def convert( + inp: str, + info_file: Optional[str] = None, + mip_image_output: Optional[str] = None, + *, + voxel_size: list[float] = (1, 1, 1), + general_config: GeneralConfig = None, + zarr_config: ZarrConfig = None, + nii_config: NiftiConfig = None, +) -> None: + """ + Convert a collection of spool files generated by the LSM pipeline into Zarr. + + Parameters + ---------- + inp + Path to the strip directory, which contains a + collection of files named `*spool.dat`. + info_file + Path to the info file (.mat), which contains the information + about the scan and the spool files. + voxel_size + Voxel size along the X, Y and Z dimensions, in microns. + general_config + General configuration + zarr_config + Zarr related configuration + nii_config + NIfTI header related configuration + """ + reader = SpoolSetInterpreter(inp, info_file) + + # Set default output path if not provided + general_config.set_default_name(op.basename(inp)) + + fullshape = reader.raw_assembled_spool_shape + + # Initialize Zarr group and array + omz = from_config(general_config.out, zarr_config) + array = omz.create_array( + "0", shape=fullshape, zarr_config=zarr_config, dtype=reader.dtype + ) + logger.info(general_config.out) + result = reader.assemble() + result = result.transpose(1, 2, 0) + if array.shards: + result = da.rechunk(result, array.shards) + else: + result = da.rechunk(result, array.chunks) + + print("Write level 0 with shape", fullshape) + da.store(result, array, compute=True) + if mip_image_output: + _save_mip_image(result, mip_image_output) + voxel_size = list(map(float, reversed(voxel_size))) + # Generate Zarr pyramid and metadata + omz.generate_pyramid(levels=zarr_config.levels) + omz.write_ome_metadata(axes=["z", "y", "x"], space_scale=voxel_size) + + if nii_config.nii: + header = build_nifti_header( + zgroup=omz, + voxel_size_zyx=tuple(voxel_size), + unit="micrometer", + nii_config=nii_config, + ) + omz.write_nifti_header(header) + + logger.info("Conversion complete.") diff --git a/linc_convert/modalities/psoct/multi_slice.py b/linc_convert/modalities/psoct/multi_slice.py index 46c7e03d..afc43e2c 100644 --- a/linc_convert/modalities/psoct/multi_slice.py +++ b/linc_convert/modalities/psoct/multi_slice.py @@ -16,7 +16,7 @@ from linc_convert.modalities.psoct._utils import make_json from linc_convert.modalities.psoct.cli import psoct -from linc_convert.utils.io.matlab import as_arraywrapper +from linc_convert.utils.io.matlab_array_wrapper import as_arraywrapper from linc_convert.utils.io.zarr import from_config from linc_convert.utils.math import ceildiv from linc_convert.utils.nifti_header import build_nifti_header diff --git a/linc_convert/modalities/psoct/single_volume.py b/linc_convert/modalities/psoct/single_volume.py index 227fdee9..51f0b4a1 100644 --- a/linc_convert/modalities/psoct/single_volume.py +++ b/linc_convert/modalities/psoct/single_volume.py @@ -16,7 +16,7 @@ from linc_convert.modalities.psoct._utils import make_json from linc_convert.modalities.psoct.cli import psoct from linc_convert.utils.chunk_processing import chunk_slice_generator -from linc_convert.utils.io.matlab import as_arraywrapper +from linc_convert.utils.io.matlab_array_wrapper import as_arraywrapper from linc_convert.utils.io.zarr import from_config from linc_convert.utils.nifti_header import build_nifti_header from linc_convert.utils.unit import to_ome_unit @@ -94,7 +94,8 @@ def convert( inp_chunk = [min(x, general_config.max_load) for x in inp.shape] dataset = zgroup.create_array( - "0", shape=inp.shape, dtype=np.dtype(inp.dtype), zarr_config=zarr_config) + "0", shape=inp.shape, dtype=np.dtype(inp.dtype), zarr_config=zarr_config + ) for idx, slc in chunk_slice_generator(inp.shape, inp_chunk): logger.info( diff --git a/linc_convert/utils/io/matlab.py b/linc_convert/utils/io/matlab.py deleted file mode 100644 index f8317f66..00000000 --- a/linc_convert/utils/io/matlab.py +++ /dev/null @@ -1,32 +0,0 @@ -"""Utilities for reading MATLAB .mat files and wrapping arrays.""" -import os -from typing import Optional, Union - -import h5py - -from linc_convert.utils.io.matlab_array_wrapper import ( - ArrayWrapper, - H5ArrayWrapper, - MatArraywrapper, -) - - -def make_wrapper(fname: str, key: Optional[str] = None) -> ArrayWrapper: - """Create an ArrayWrapper for a MATLAB .mat file.""" - try: - # "New" .mat file - f = h5py.File(fname, "r") - return H5ArrayWrapper(f, key) - except Exception: - # "Old" .mat file - return MatArraywrapper(fname, key) - - -def as_arraywrapper( - inp: Union[str, os.PathLike, ArrayWrapper], - key: Optional[str] = None, -) -> ArrayWrapper: - """Convert input to an ArrayWrapper if it is not already one.""" - if isinstance(inp, ArrayWrapper): - return inp - return make_wrapper(str(inp), key) diff --git a/linc_convert/utils/io/matlab_array_wrapper.py b/linc_convert/utils/io/matlab_array_wrapper.py index 91728414..30c7d8a6 100644 --- a/linc_convert/utils/io/matlab_array_wrapper.py +++ b/linc_convert/utils/io/matlab_array_wrapper.py @@ -1,7 +1,7 @@ """Utilities for reading HDF5 and MATLAB .mat files, and wrapping arrays.""" - +import os from _warnings import warn -from typing import Mapping, Optional +from typing import Mapping, Optional, Union import h5py import numpy as np @@ -71,6 +71,10 @@ def __getitem__(self, index: object) -> np.ndarray: """Get item by index.""" return self.array[index] + @property + def ndim(self) -> int: + """Get dimension of the array.""" + return self.array.ndim class MatArraywrapper(ArrayWrapper): """Wrapper for arrays stored in old-style MATLAB .mat files.""" @@ -117,3 +121,29 @@ def __getitem__(self, index: object) -> np.ndarray: if self.array is None: self.load() return self.array[index] + + @property + def ndim(self) -> int: + """Get dimension of the array.""" + return self.array.ndim + + +def make_wrapper(fname: str, key: Optional[str] = None) -> ArrayWrapper: + """Create an ArrayWrapper for a MATLAB .mat file.""" + try: + # "New" .mat file + f = h5py.File(fname, "r") + return H5ArrayWrapper(f, key) + except Exception: + # "Old" .mat file + return MatArraywrapper(fname, key) + + +def as_arraywrapper( + inp: Union[str, os.PathLike, ArrayWrapper], + key: Optional[str] = None, +) -> ArrayWrapper: + """Convert input to an ArrayWrapper if it is not already one.""" + if isinstance(inp, ArrayWrapper): + return inp + return make_wrapper(str(inp), key) diff --git a/linc_convert/utils/io/spool.py b/linc_convert/utils/io/spool.py index 2cd1cb74..5f3c3ef0 100644 --- a/linc_convert/utils/io/spool.py +++ b/linc_convert/utils/io/spool.py @@ -13,18 +13,21 @@ # stdlib import configparser import io +import logging import os import warnings from glob import glob from os import PathLike from typing import Iterator +import dask.array as da import numpy as np +from dask import delayed from scipy.io import loadmat from linc_convert.utils.math import ceildiv - +logger = logging.getLogger(__name__) class SpoolSetInterpreter: """ Interpreter for a set of spool files produced by a Zyla camera. @@ -66,7 +69,11 @@ def __init__( self.spool_shape[2], self.spool_shape[0] * len(self.spool_files), ) - + self.raw_assembled_spool_shape = ( + self.spool_shape[1], + self.spool_shape[2], + self.spool_shape[0] * len(self.spool_files), + ) def _load_info_file(self, info_file: str | PathLike[str]) -> None: loaded_info = loadmat(info_file) info = loaded_info.get("info", None) @@ -163,7 +170,7 @@ def _extract_config_values(self) -> None: def _load_spool_file(self, spool_file_name: str | PathLike[str]) -> np.ndarray: """Load a single spool file into a NumPy array.""" file = self._make_filename_from_spool_set(spool_file_name) - print(f"Reading file {spool_file_name}") + logger.debug(f"Reading file {spool_file_name}") with open(file, "rb") as f: array = np.frombuffer(f.read(), dtype=self.dtype) return np.reshape(array, self.spool_shape) @@ -241,33 +248,37 @@ def _get_spool_names_in_order(self) -> Iterator[str]: else: warnings.warn(f"{tmp} not located in spool directory") - def assemble(self) -> np.ndarray: + def assemble(self) -> da.Array: """ - Assemble all spool files into a single 3D volume. + Assemble all spool files into a single 3D volume (lazy Dask array). Returns ------- - A NumPy array of shape (frames_total, rows, columns), + A Dask array of shape (frames_total, rows, columns), where frames_total = images_per_file * number_of_files. """ - axis_0_shape = self.spool_shape[0] - canvas = np.zeros( - (axis_0_shape * len(self), *self.spool_shape[1:]), dtype=self.dtype - ) - for idx, spool_file in enumerate(self): - start = idx * axis_0_shape - stop = start + axis_0_shape - canvas[start:stop] = spool_file - return canvas + if not self.spool_files: + empty = np.zeros((0, *self.spool_shape[1:]), dtype=self.dtype) + return da.from_array(empty) + delayed_chunks = [ + da.from_delayed( + delayed(self._load_spool_file)(name), + shape=self.spool_shape, + dtype=self.dtype, + ) + for name in self.spool_files + ] + return da.concatenate(delayed_chunks, axis=0) # this is the modified version for lsm pipeline - def assemble_cropped(self) -> np.ndarray: + def assemble_cropped(self) -> da.Array: """ Assemble and transpose the volume, then crop to original depth. Returns ------- - A NumPy array transposed to (height, width, frames) + A Dask array transposed to (height, width, frames) and cropped to self.numDepths along the first axis. """ - return self.assemble().transpose(1, 2, 0)[: self.numDepths, :, :] + volume = self.assemble() + return volume.transpose(1, 2, 0)[: self.numDepths, :, :] diff --git a/linc_convert/utils/io/zarr/drivers/tensorstore.py b/linc_convert/utils/io/zarr/drivers/tensorstore.py index a9b58b55..33f31069 100644 --- a/linc_convert/utils/io/zarr/drivers/tensorstore.py +++ b/linc_convert/utils/io/zarr/drivers/tensorstore.py @@ -439,7 +439,7 @@ def make_kvstore(path: str | os.PathLike) -> dict: raise ValueError("Unsupported protocol:", path.protocol) -def default_read_config(path: os.PathLike | str) -> dict: +def default_read_config(path: str | PathLike[str]) -> dict: """ Generate a TensorStore configuration to read an existing Zarr. @@ -450,7 +450,7 @@ def default_read_config(path: os.PathLike | str) -> dict: """ path = UPath(path) if not path.protocol: - path = "file://" / path + path = UPath("file://" + str(path)) if (path / "zarr.json").exists(): zarr_version = 3 elif (path / ".zarray").exists(): @@ -498,7 +498,7 @@ def _detect_metadata(path: PathLike) -> Optional[Tuple[str, int]]: def default_write_config( - path: os.PathLike | str, + path: str | PathLike[str], shape: list[int], dtype: np.dtype | str, chunk: list[int] = [32], @@ -530,7 +530,7 @@ def default_write_config( """ path = UPath(path) if not path.protocol: - path = "file://" / path + path = UPath("file://" + str(path)) # Format compressor if version == 3 and compressor == "zlib": diff --git a/linc_convert/utils/io/zarr/drivers/zarr_python.py b/linc_convert/utils/io/zarr/drivers/zarr_python.py index f07ca575..0a49ee0a 100644 --- a/linc_convert/utils/io/zarr/drivers/zarr_python.py +++ b/linc_convert/utils/io/zarr/drivers/zarr_python.py @@ -93,6 +93,15 @@ def __getattr__(self, name: str) -> Any: # noqa: ANN401 raise AttributeError( f"'{self.__class__.__name__}' object has no attribute '{name}'" ) + + @classmethod + def open(cls, *args: Any, **kwargs: Any) -> "ZarrPythonArray": # noqa: ANN401 + """Open a Zarr array.""" + return cls(zarr.open_array(*args, **kwargs)) + @classmethod + def open_array(cls, *args: Any, **kwargs: Any) -> "ZarrPythonArray": # noqa: ANN401 + """Open a Zarr array.""" + return cls(zarr.open_array(*args, **kwargs)) class ZarrPythonGroup(ZarrGroup): @@ -116,10 +125,7 @@ def from_config( cls, out: str | PathLike[str], zarr_config: ZarrConfig ) -> "ZarrPythonGroup": """Create a Zarr group from a configuration object.""" - if out.startswith("/") or out.startswith("\\"): - store = zarr.storage.LocalStore(out) - else: - store = zarr.storage.FsspecStore(out) + store = zarr.storage.LocalStore(out) return cls( zarr.group( store=store, @@ -269,6 +275,17 @@ def create_array_from_base( arr[:] = data return ZarrPythonArray(arr) + @classmethod + def open(cls, *args: Any, **kwargs: Any) -> "ZarrPythonGroup": # noqa: ANN401 + """Open a Zarr group.""" + return cls(zarr.open_group(*args, **kwargs)) + + @classmethod + def open_group(cls, *args: Any, **kwargs: Any) -> 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+all = ["dask-image", "glymur", "h5py", "scipy", "tensorstore", "tifffile", "wkw"] +df = ["glymur"] +lsm = ["dask-image", "tifffile"] +psoct = ["h5py", "scipy"] +ts = ["tensorstore"] +wk = ["wkw"] + +[metadata] +lock-version = "2.1" +python-versions = "^3.11" +content-hash = "055e482a24d50e703d0cfd745f2e7e0e86363b7b42ad1e6cb181e8eb43f223f7" diff --git a/pyproject.toml b/pyproject.toml index f4e02fea..35f94479 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -44,14 +44,15 @@ h5py = { version = "*", optional = true } scipy = { version = "*", optional = true } wkw = { version = "*", optional = true } tensorstore = { version = "*", optional = true } +dask-image = { version = "*", optional = true } [tool.poetry.extras] df = ["glymur"] -lsm = ["tifffile"] +lsm = ["tifffile", "dask-image"] psoct = ["h5py", "scipy"] wk = ["wkw"] ts = ["tensorstore"] -all = ["glymur", "tifffile", "h5py", "scipy", "wkw", "tensorstore"] +all = ["glymur", "tifffile", "h5py", "scipy", "wkw", "tensorstore", "dask-image"] [tool.poetry.group.dev] optional = true @@ -61,6 +62,8 @@ mypy = "^1.9.0" pre-commit = "^3.7.0" pytest-cov = "^5.0.0" ruff = "^0.3.4" +scikit-image = "*" +pooch = "*" [tool.poetry.group.docs] optional = true @@ -74,6 +77,11 @@ pythonpath = [ testpaths = [ "tests" ] +markers = [ + "heavy: marks tests as slow or data-intensive", + "golden: regenerate golden Zarr archives" +] +addopts = "-m 'not heavy and not golden'" [tool.mypy] ignore_missing_imports = true diff --git a/tests/conftest.py b/tests/conftest.py index a116eaeb..0f2b63d5 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,7 +1,10 @@ +import os import subprocess from pathlib import Path +import numpy as np import pytest +import skimage DOWNLOAD_CMD = [ "dandi", @@ -36,3 +39,110 @@ def driver(request): @pytest.fixture(scope="module", params=[2, 3]) def zarr_version(request): return request.param + + +@pytest.fixture +def spool_dat(tmp_path): + brain = skimage.data.brain() + brain = brain.reshape(10, 4, 64, 256) + for z in range(1, 11): + for y in range(1, 4): + out_path = tmp_path / f"test_run{y:02d}_y{y:02d}_z{z:02d}_HR" + image = brain[z - y, y - 1][None, ...] + + write_zyla_spool_set(image, out_path, images_per_file=128) + + return tmp_path + + +def write_zyla_spool_set( + image: np.ndarray, + spool_set_path: str, + *, + pixel_encoding: str = "Mono16", + images_per_file: int = None, +): + """ + Given `image` of shape (numDepths, numColumns, numFrames), + create a Zyla‑compatible spool directory at `spool_set_path` + such that SpoolSetInterpreter(...).assemble_cropped() == image. + + Parameters + ---------- + image : np.ndarray + 3D array with shape (numDepths, numColumns, numFrames). Must be dtype uint16 if + pixel_encoding='Mono16' (or uint8 if 'Mono8'). + spool_set_path : str + Path to the directory to create. Will be mkdir'd if necessary. + pixel_encoding : {'Mono16','Mono8'} + Selects dtype and controls AOIStride = numColumns * itemsize. + images_per_file : int, optional + How many frames to pack into each spool file. Defaults to all frames in one + file. + """ + numDepths, numColumns, numFrames = image.shape + if images_per_file is None: + images_per_file = numFrames + if pixel_encoding == "Mono16": + dtype = np.uint16 + elif pixel_encoding == "Mono8": + dtype = np.uint8 + else: + raise ValueError("pixel_encoding must be 'Mono16' or 'Mono8'") + if image.dtype != dtype: + raise ValueError(f"Expected image.dtype={dtype}, got {image.dtype}") + + # compute padded rows: odd heights get +1, even get +2 + if numDepths % 2: + numRows = numDepths + 1 + else: + numRows = numDepths + 2 + + # stride in bytes + stride = numColumns * dtype().nbytes + # how many bytes per frame + frame_bytes = numRows * numColumns * dtype().nbytes + + # make directory + os.makedirs(spool_set_path, exist_ok=True) + + # marker for format detection + open(os.path.join(spool_set_path, "Spooled files.sifx"), "wb").close() + + # write acquisitionmetadata.ini + ini = f""" +[data] +AOIHeight = {numDepths} +AOIWidth = {numColumns} +AOIStride = {stride} +PixelEncoding = {pixel_encoding} +ImageSizeBytes = {frame_bytes} + +[multiimage] +ImagesPerFile = {images_per_file} +""" + with open( + os.path.join(spool_set_path, "acquisitionmetadata.ini"), "w", encoding="utf-8" + ) as f: + f.write(ini) + + # split into as many spool files as needed + n_files = (numFrames + images_per_file - 1) // images_per_file + for file_idx in range(n_files): + start_f = file_idx * images_per_file + end_f = min(start_f + images_per_file, numFrames) + this_count = end_f - start_f + + # prepare buffer: shape (this_count, numRows, numColumns) + buf = np.zeros((this_count, numRows, numColumns), dtype=dtype) + # fill the real depths into row 0..numDepths-1 + # image has shape (numDepths, numColumns, numFrames) + # buf[f, d, c] = image[d, c, f] + for f in range(this_count): + buf[f, :numDepths, :] = image[:, :, start_f + f] + + # name = reversed zero‑padded index + "spool.dat" + rev = str(file_idx).zfill(10)[::-1] + fn = f"{rev}spool.dat" + with open(os.path.join(spool_set_path, fn), "wb") as f: + f.write(buf.tobytes()) diff --git a/tests/data/lsm_single_volume_zarr2.nii.zarr.zip b/tests/data/lsm_single_volume_zarr2.nii.zarr.zip new file mode 100644 index 00000000..b6903eb6 Binary files /dev/null and b/tests/data/lsm_single_volume_zarr2.nii.zarr.zip differ diff --git a/tests/data/lsm_single_volume_zarr3.nii.zarr.zip b/tests/data/lsm_single_volume_zarr3.nii.zarr.zip new file mode 100644 index 00000000..801d5c16 Binary files /dev/null and b/tests/data/lsm_single_volume_zarr3.nii.zarr.zip differ diff --git a/tests/data/lsm_strip_zarr2.nii.zarr.zip b/tests/data/lsm_strip_zarr2.nii.zarr.zip new file mode 100644 index 00000000..100155ce Binary files /dev/null and b/tests/data/lsm_strip_zarr2.nii.zarr.zip differ diff --git a/tests/data/lsm_strip_zarr3.nii.zarr.zip b/tests/data/lsm_strip_zarr3.nii.zarr.zip new file mode 100644 index 00000000..6dfed036 Binary files /dev/null and b/tests/data/lsm_strip_zarr3.nii.zarr.zip differ diff --git a/tests/data/wkw_zarr2.nii.zarr.zip b/tests/data/wkw_zarr2.nii.zarr.zip index a367350f..a91c1a71 100644 Binary files a/tests/data/wkw_zarr2.nii.zarr.zip and b/tests/data/wkw_zarr2.nii.zarr.zip differ diff --git a/tests/data/wkw_zarr3.nii.zarr.zip b/tests/data/wkw_zarr3.nii.zarr.zip index d80a9bec..93a2303f 100644 Binary files a/tests/data/wkw_zarr3.nii.zarr.zip and b/tests/data/wkw_zarr3.nii.zarr.zip differ diff --git a/tests/test_lsm_mosaic.py b/tests/test_lsm_mosaic.py index a39b4c8a..83bcd83c 100644 --- a/tests/test_lsm_mosaic.py +++ b/tests/test_lsm_mosaic.py @@ -36,7 +36,7 @@ def test_lsm_mosaic(tmp_path, mosaic_tiff, zarr_version, driver): expected_zarr = f"data/lsm_mosaic_zarr{zarr_version}.nii.zarr.zip" output = tmp_path / "mosaic.nii.zarr" mosaic.convert( - str(mosaic_tiff), out=str(output), zarr_version=zarr_version, driver=driver + str(mosaic_tiff), out=str(output), zarr_version=zarr_version, driver=driver ) assert_zarr_equal(str(output), zarr.storage.ZipStore(expected_zarr, mode="r")) @@ -46,9 +46,9 @@ def test_lsm_mosaic_regen_golden(tmp_path, mosaic_tiff, zarr_version): expected_zarr = f"data/lsm_mosaic_zarr{zarr_version}.nii.zarr.zip" output = tmp_path / "mosaic.nii.zarr" mosaic.convert( - str(mosaic_tiff), - out=str(output), - zarr_version=zarr_version, + str(mosaic_tiff), + out=str(output), + zarr_version=zarr_version, ) base = Path(expected_zarr).with_suffix("") shutil.make_archive(str(base), "zip", str(output)) diff --git a/tests/test_lsm_single_volume.py b/tests/test_lsm_single_volume.py new file mode 100644 index 00000000..c39d0df6 --- /dev/null +++ b/tests/test_lsm_single_volume.py @@ -0,0 +1,77 @@ +import shutil +from pathlib import Path + +import numpy as np +import pytest +import skimage +import tifffile +import zarr.storage +from utils.compare_file import assert_zarr_equal + +from linc_convert.modalities.lsm import single_volume + + +@pytest.fixture +def single_volume_tiff(tmp_path): + """Create a temporary multi-page TIFF file containing a small volume.""" + path = tmp_path / "single_volume.tif" + slice2d = skimage.data.brain().astype(np.uint16) + volume = np.stack([slice2d] * 4, axis=0) + tifffile.imwrite(str(path), volume) + return path + + +@pytest.mark.parametrize( + "zarr_version, expected_zarr", + [ + (2, "data/lsm_single_volume_zarr2.nii.zarr.zip"), + (3, "data/lsm_single_volume_zarr3.nii.zarr.zip"), + ], +) +def test_lsm_single_volume( + tmp_path, single_volume_tiff, zarr_version, expected_zarr, driver +): + output = tmp_path / "single_volume.nii.zarr" + + single_volume.convert( + str(single_volume_tiff), + out=str(output), + zarr_version=zarr_version, + overwrite=True, + chunk=(64,), + driver=driver, + ) + + assert_zarr_equal( + str(output), + zarr.storage.ZipStore(expected_zarr, mode="r"), + ) + + +@pytest.mark.golden +@pytest.mark.parametrize( + "zarr_version, expected_zarr", + [ + (2, "data/lsm_single_volume_zarr2.nii.zarr.zip"), + (3, "data/lsm_single_volume_zarr3.nii.zarr.zip"), + ], +) +def test_lsm_single_volume_regen_golden( + tmp_path, single_volume_tiff, zarr_version, expected_zarr +): + """ + Rebuild lsm single-volume golden archives. Only run with --regenerate-golden. + """ + output = tmp_path / "single_volume.nii.zarr" + single_volume.convert( + str(single_volume_tiff), + out=str(output), + zarr_version=zarr_version, + overwrite=True, + chunk=(64,), + driver="zarr-python", + ) + base = Path(expected_zarr).with_suffix("") + shutil.make_archive(str(base), "zip", str(output)) + + diff --git a/tests/test_lsm_spool.py b/tests/test_lsm_spool.py index 875fcd88..47a773b7 100644 --- a/tests/test_lsm_spool.py +++ b/tests/test_lsm_spool.py @@ -1,123 +1,14 @@ -import os import shutil from pathlib import Path -import numpy as np import pytest -import skimage import zarr + from utils.compare_file import assert_zarr_equal from linc_convert.modalities.lsm import spool -@pytest.fixture -def spool_dat(tmp_path): - brain = skimage.data.brain() - brain = brain.reshape(10, 4, 64, 256) - for z in range(1, 11): - for y in range(1, 4): - out_path = tmp_path / f"test_run{y:02d}_y{y:02d}_z{z:02d}_HR" - image = brain[z - y, y - 1][None, ...] - - write_zyla_spool_set(image, out_path, images_per_file=128) - - return tmp_path - - -def write_zyla_spool_set( - image: np.ndarray, - spool_set_path: str, - *, - pixel_encoding: str = "Mono16", - images_per_file: int = None, -): - """ - Given `image` of shape (numDepths, numColumns, numFrames), - create a Zyla‑compatible spool directory at `spool_set_path` - such that SpoolSetInterpreter(...).assemble_cropped() == image. - - Parameters - ---------- - image : np.ndarray - 3D array with shape (numDepths, numColumns, numFrames). Must be dtype uint16 if - pixel_encoding='Mono16' (or uint8 if 'Mono8'). - spool_set_path : str - Path to the directory to create. Will be mkdir'd if necessary. - pixel_encoding : {'Mono16','Mono8'} - Selects dtype and controls AOIStride = numColumns * itemsize. - images_per_file : int, optional - How many frames to pack into each spool file. Defaults to all frames in one - file. - """ - numDepths, numColumns, numFrames = image.shape - if images_per_file is None: - images_per_file = numFrames - if pixel_encoding == "Mono16": - dtype = np.uint16 - elif pixel_encoding == "Mono8": - dtype = np.uint8 - else: - raise ValueError("pixel_encoding must be 'Mono16' or 'Mono8'") - if image.dtype != dtype: - raise ValueError(f"Expected image.dtype={dtype}, got {image.dtype}") - - # compute padded rows: odd heights get +1, even get +2 - if numDepths % 2: - numRows = numDepths + 1 - else: - numRows = numDepths + 2 - - # stride in bytes - stride = numColumns * dtype().nbytes - # how many bytes per frame - frame_bytes = numRows * numColumns * dtype().nbytes - - # make directory - os.makedirs(spool_set_path, exist_ok=True) - - # marker for format detection - open(os.path.join(spool_set_path, "Spooled files.sifx"), "wb").close() - - # write acquisitionmetadata.ini - ini = f""" -[data] -AOIHeight = {numDepths} -AOIWidth = {numColumns} -AOIStride = {stride} -PixelEncoding = {pixel_encoding} -ImageSizeBytes = {frame_bytes} - -[multiimage] -ImagesPerFile = {images_per_file} -""" - with open( - os.path.join(spool_set_path, "acquisitionmetadata.ini"), "w", encoding="utf-8" - ) as f: - f.write(ini) - - # split into as many spool files as needed - n_files = (numFrames + images_per_file - 1) // images_per_file - for file_idx in range(n_files): - start_f = file_idx * images_per_file - end_f = min(start_f + images_per_file, numFrames) - this_count = end_f - start_f - - # prepare buffer: shape (this_count, numRows, numColumns) - buf = np.zeros((this_count, numRows, numColumns), dtype=dtype) - # fill the real depths into row 0..numDepths-1 - # image has shape (numDepths, numColumns, numFrames) - # buf[f, d, c] = image[d, c, f] - for f in range(this_count): - buf[f, :numDepths, :] = image[:, :, start_f + f] - - # name = reversed zero‑padded index + "spool.dat" - rev = str(file_idx).zfill(10)[::-1] - fn = f"{rev}spool.dat" - with open(os.path.join(spool_set_path, fn), "wb") as f: - f.write(buf.tobytes()) - - def test_lsm_spool_convert(tmp_path, spool_dat, zarr_version): expected_zarr = f"data/lsm_spool_zarr{zarr_version}.nii.zarr.zip" output = tmp_path / "spool.nii.zarr" diff --git a/tests/test_lsm_strip.py b/tests/test_lsm_strip.py new file mode 100644 index 00000000..6c2ead56 --- /dev/null +++ b/tests/test_lsm_strip.py @@ -0,0 +1,49 @@ +import shutil +from pathlib import Path + +import pytest +import zarr.storage +from utils.compare_file import assert_zarr_equal + +from linc_convert.modalities.lsm import strip + + +def _get_first_strip_dir(root): + """Return the first spool strip directory inside the synthetic root.""" + for p in sorted(root.iterdir()): + if p.is_dir() and p.name.endswith("_HR"): + return p + raise RuntimeError(f"No strip directory found under {root}") + + +def test_lsm_strip_convert(tmp_path, spool_dat, zarr_version): + strip_dir = _get_first_strip_dir(spool_dat) + + output = tmp_path / "strip.nii.zarr" + strip.convert( + inp=str(strip_dir), + info_file=None, + out=str(output), + ) + + expected_zarr = f"data/lsm_strip_zarr{zarr_version}.nii.zarr.zip" + assert_zarr_equal( + str(output), + zarr.storage.ZipStore(expected_zarr, mode="r"), + ) + + +@pytest.mark.golden +def test_lsm_strip_regen_golden(tmp_path, spool_dat, zarr_version): + strip_dir = _get_first_strip_dir(spool_dat) + + output = tmp_path / "strip_output.nii.zarr" + strip.convert( + inp=str(strip_dir), + info_file=None, + out=str(output), + ) + + expected_zarr = f"data/lsm_strip_zarr{zarr_version}.nii.zarr.zip" + base = Path(expected_zarr).with_suffix("") + shutil.make_archive(str(base), "zip", str(output)) diff --git a/tests/test_wk.py b/tests/test_wk.py index 9cc15521..a315a5e4 100644 --- a/tests/test_wk.py +++ b/tests/test_wk.py @@ -1,6 +1,7 @@ import shutil from pathlib import Path +from nibabel.nifti1 import Nifti1Header import niizarr import numpy as np import pytest @@ -21,7 +22,7 @@ def wk_annotation(tmp_path): Nifti1Image(image, np.eye(4)), Nifti1Image(annotation, np.eye(4)), ) - + image.header.set_xyzt_units('mm') niizarr.nii2zarr(image, tmp_path / "image.nii.zarr", chunk=64) niizarr.nii2zarr(annotation, tmp_path / "annotation.nii.zarr", chunk=64) wkw_dir = tmp_path / "wkw" diff --git a/tests/utils/compare_file.py b/tests/utils/compare_file.py index 89e1e334..2f2abf70 100644 --- a/tests/utils/compare_file.py +++ b/tests/utils/compare_file.py @@ -149,7 +149,7 @@ def assert_zarr_equal( f" ‣ {dict(obj2.attrs)}" ) try: - np.testing.assert_array_equal(obj1[:], obj2[:]) + np.testing.assert_allclose(obj1[:], obj2[:], rtol=1e-6, atol=1e-8) except AssertionError as e: diffs.append(f"Array '{key}' differs:\n ‣ {e}") elif isinstance(obj1, zarr.Group):