diff --git a/dask-stitch/scripts/fuse_volume.py b/dask-stitch/scripts/fuse_volume.py index 9b5fcde..32a8ad1 100644 --- a/dask-stitch/scripts/fuse_volume.py +++ b/dask-stitch/scripts/fuse_volume.py @@ -155,7 +155,7 @@ def wrapped_process_chunk(block, block_info=None): wrapped_process_chunk, chunks=chunk_shape, dtype=np.float32, - shape=fused_shape, + #shape=fused_shape, ) return fused_volume @@ -175,112 +175,13 @@ def wrapped_process_chunk(block, block_info=None): # Fuse the volume fused_volume = fuse_volume(ome_zarr_paths, optimized_translations, fused_shape, chunk_shape, bbox_min, voxel_size) -# Save the fused volume -fused_volume.to_zarr(snakemake.output.fused_volume) - - - - -def process_chunk(chunk_data, block_info, ome_zarr_paths, optimized_translations, bbox_min, voxel_size, chunk_shape): - """ - Process a single chunk of the fused volume. - - Parameters: - - chunk_data (np.ndarray): Placeholder data for the chunk. - - block_info (dict): Information about the block being processed. - - ome_zarr_paths (list of str): List of paths to OME-Zarr datasets. - - optimized_translations (np.ndarray): Optimized translations for each tile. - - bbox_min (np.ndarray): Minimum physical coordinates of the fused volume. - - voxel_size (np.ndarray): Voxel size in physical units. - - chunk_shape (tuple): Shape of the chunk being processed. - - Returns: - - np.ndarray: Fused chunk. - """ - # Extract chunk location and physical bounding box - chunk_start = np.array(block_info[0]["chunk-location"]) * voxel_size + bbox_min - chunk_end = chunk_start + np.array(chunk_shape) * voxel_size - - chunk = np.zeros(chunk_shape, dtype=np.float32) - weight = np.zeros(chunk_shape, dtype=np.float32) - - for path, translation in zip(ome_zarr_paths, optimized_translations): - znimg = ZarrNii.from_path(path) - tile = znimg.darr.squeeze().compute() - affine = znimg.vox2ras.affine - - # Resample tile to chunk - resampled_tile = resample_tile_to_chunk(tile, affine, translation, chunk_start, chunk_end, chunk_shape) - - # Fuse by summing intensities and weights - mask = resampled_tile > 0 - chunk[mask] += resampled_tile[mask] - weight[mask] += 1 - - # Avoid division by zero - fused_chunk = np.divide(chunk, weight, out=np.zeros_like(chunk), where=weight > 0) - return fused_chunk - - -def fuse_volume(ome_zarr_paths, optimized_translations, fused_shape, chunk_shape, bbox_min, voxel_size): - """ - Fuse all tiles into a single volume. - - Parameters: - - ome_zarr_paths (list of str): List of paths to OME-Zarr datasets. - - optimized_translations (np.ndarray): Optimized translations for each tile. - - fused_shape (tuple): Shape of the final fused volume. - - chunk_shape (tuple): Shape of each chunk. - - bbox_min (np.ndarray): Minimum coordinates of the fused volume. - - voxel_size (np.ndarray): Voxel size in physical units. - - Returns: - - dask.array: Fused volume. - """ - # Wrap process_chunk for Dask - def wrapped_process_chunk(chunk_data, block_info=None): - return process_chunk( - chunk_data, - block_info, - ome_zarr_paths, - optimized_translations, - bbox_min, - voxel_size, - chunk_shape, - ) - - # Define Dask array for the fused volume - fused_volume = da.map_blocks( - wrapped_process_chunk, - chunks=chunk_shape, - dtype=np.float32, - shape=fused_shape, - ) - - return fused_volume - - -# Example usage -ome_zarr_paths = snakemake.input.ome_zarr # List of input OME-Zarr paths -optimized_translations = np.loadtxt(snakemake.input.optimized_translations, dtype=float) # Optimized translations - -# Compute the fused volume shape -bbox_min, bbox_max, voxel_size = compute_fused_volume_shape(ome_zarr_paths, optimized_translations) - - -print(bbox_min) -print(bbox_max) -print(voxel_size) -assert all(voxel_size > 0), "Voxel size must be greater than zero." - -fused_shape = tuple(np.ceil((bbox_max - bbox_min) / voxel_size).astype(int)) -chunk_shape = (64, 64, 64) # Example chunk size - -# Fuse the volume -fused_volume = fuse_volume(ome_zarr_paths, optimized_translations, fused_shape, chunk_shape, bbox_min, voxel_size) +print(fused_volume.shape) # Save the fused volume -fused_volume.to_zarr(snakemake.output.fused_volume) +znimg = ZarrNii.from_darr(fused_volume) + +znimg.to_ome_zarr(snakemake.output.ome_zarr) +znimg.to_nifti(snakemake.output.nifti) diff --git a/poetry.lock b/poetry.lock index 567aa71..d6c7886 100644 --- a/poetry.lock +++ b/poetry.lock @@ -201,6 +201,17 @@ types-python-dateutil = ">=2.8.10" doc = ["doc8", "sphinx (>=7.0.0)", "sphinx-autobuild", "sphinx-autodoc-typehints", "sphinx_rtd_theme (>=1.3.0)"] test = ["dateparser (>=1.0.0,<2.0.0)", "pre-commit", "pytest", "pytest-cov", "pytest-mock", "pytz (==2021.1)", "simplejson (>=3.0.0,<4.0.0)"] +[[package]] +name = "asciitree" +version = "0.3.3" +description = "Draws ASCII trees." +category = "main" +optional = false +python-versions = "*" +files = [ + {file = "asciitree-0.3.3.tar.gz", hash = "sha256:4aa4b9b649f85e3fcb343363d97564aa1fb62e249677f2e18a96765145cc0f6e"}, 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