diff --git a/README.md b/README.md index 7fdccec0..26efcaff 100644 --- a/README.md +++ b/README.md @@ -2,22 +2,27 @@ Pipeline scripts and tools for reconstructing Electron Microscopy volumes. ### Setup -1. If necessary, [install miniconda](https://docs.conda.io/en/latest/miniconda.html). +1. If necessary, [install pixi](https://pixi.sh/latest/#installation). -### Create Environment and Install +### Create Environment and Install ```bash git clone https://github.com/JaneliaSciComp/EM_recon_pipeline.git cd EM_recon_pipeline -conda env create -f janelia_emrp.environment.yml -conda activate janelia_emrp +pixi install +``` + +### Running Scripts +```bash +# Run a script using the pixi environment +pixi run python src/python/janelia_emrp/fibsem/dat_converter.py --help -poetry install +# Or activate a shell with the environment +pixi shell +python src/python/janelia_emrp/fibsem/dat_converter.py --help ``` ### Development Library Management -- Using conda with poetry as described -[here](https://ealizadeh.com/blog/guide-to-python-env-pkg-dependency-using-conda-poetry). -- To change/update dependencies, edit [pyproject.toml](pyproject.toml) -or use [poetry add](https://python-poetry.org/docs/cli/#add) and then run `poetry install`. \ No newline at end of file +- Environment is managed using [pixi](https://pixi.sh/) with dependencies defined in [pyproject.toml](pyproject.toml). +- To add/update dependencies, edit the `[project]` or `[tool.pixi.dependencies]` sections in `pyproject.toml` and run `pixi install`. \ No newline at end of file diff --git a/janelia_emrp.environment.yml b/janelia_emrp.environment.yml deleted file mode 100644 index 75f5fcc9..00000000 --- a/janelia_emrp.environment.yml +++ /dev/null @@ -1,10 +0,0 @@ -name: janelia_emrp - 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-[package.extras] -jupyter = ["ipytree", "notebook"] - -[[package]] -name = "zict" -version = "2.0.0" -description = "Mutable mapping tools" -category = "main" -optional = false -python-versions = "*" -files = [ - {file = "zict-2.0.0-py3-none-any.whl", hash = "sha256:26aa1adda8250a78dfc6a78d200bfb2ea43a34752cf58980bca75dde0ba0c6e9"}, - {file = "zict-2.0.0.tar.gz", hash = "sha256:8e2969797627c8a663575c2fc6fcb53a05e37cdb83ee65f341fc6e0c3d0ced16"}, -] - -[package.dependencies] -heapdict = "*" - -[metadata] -lock-version = "2.0" -python-versions = "^3.9" -content-hash = "440933c42c76eb6166801f7d2d8e76bd5b64037ef8f269aa022cbf303f141a9c" diff --git a/pyproject.toml b/pyproject.toml index b8fa61dd..3dabc1e1 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,28 +1,48 @@ -[tool.poetry] +[project] name = "janelia-emrp" -version = "0.1.0" +version = "0.2.0" description = "Pipeline scripts and tools for reconstructing Electron Microscopy volumes." -authors = ["Eric Trautman "] -license = 'BSD-3-Clause' +authors = [{name = "Eric Trautman", email = "trautmane@janelia.hhmi.org"}] +license = "BSD-3-Clause" +requires-python = ">= 3.12" +dependencies = [ + "fibsem-tools==7.0.5", + "dask-jobqueue", # For LSFCluster support (dask-janelia functionality vendored locally) + "xarray-multiscale>=0.3.3", + "render-python @ git+https://github.com/AllenInstitute/render-python.git", + "matplotlib", + "google-cloud-storage>=2.19.0", + "opencv-python>=4.10.0", + "basicpy" +] -[tool.poetry.dependencies] -python = "^3.9" -fibsem-tools = "0.3.1" -render-python = {git = "https://github.com/AllenInstitute/render-python.git"} -dask-janelia = "^0.1.4" -bokeh = "^2.3.3" -h5py = "^3.6.0" -pytest = "^7.1.1" -xarray-multiscale = "0.3.1" -pydantic = "^1.9.0" -numpy = "1.21.0" -scikit-image = "0.19.3" +[build-system] +build-backend = "hatchling.build" +requires = ["hatchling"] -[tool.poetry.dev-dependencies] +[tool.hatch.build.targets.wheel] +packages = ["src/python/janelia_emrp"] -[build-system] -requires = ["poetry-core>=1.0.0"] -build-backend = "poetry.core.masonry.api" +[tool.hatch.metadata] +allow-direct-references = true + +[tool.pixi.workspace] +channels = ["conda-forge"] +platforms = ["osx-arm64", "osx-64", "linux-64", "win-64"] + +[tool.pixi.pypi-dependencies] +janelia-emrp = { path = ".", editable = true } + +[tool.pixi.dependencies] +python = ">=3.12" +urllib3 = ">=1.26,<2.0" +bokeh = ">=2.3.3,<4.0.0" +h5py = ">=3.6.0" +pandas = ">=1.5.0,<3.0.0" +pytest = ">=7.1.1" +pydantic = ">=2.7.0" +numpy = ">=1.26.0,<2.0.0" +scikit-image = ">=0.22.0" # see https://docs.pytest.org/en/stable/how-to/capture-warnings.html [tool.pytest.ini_options] diff --git a/src/python/janelia_emrp/cluster.py b/src/python/janelia_emrp/cluster.py new file mode 100644 index 00000000..cb153993 --- /dev/null +++ b/src/python/janelia_emrp/cluster.py @@ -0,0 +1,189 @@ +""" +Dask cluster utilities for Janelia Research Campus compute cluster. + +This module provides convenience functions for creating dask clusters, +originally from the dask-janelia package (https://github.com/janelia-cosem/dask-janelia). +Vendored here to avoid dependency version conflicts. +""" + +from shutil import which +from distributed import LocalCluster +from dask_jobqueue import LSFCluster +import os +from pathlib import Path +import dask +from typing import Union, List, Dict, Any, Optional +import warnings + +dask.config.set({"jobqueue.lsf.use-stdin": True}) + +threading_env_vars = [ + "NUM_MKL_THREADS", + "OPENBLAS_NUM_THREADS", + "OPENMP_NUM_THREADS", + "OMP_NUM_THREADS", +] + + +def make_single_threaded_env_vars(threads: int) -> List[str]: + return [f"export {var}={threads}" for var in threading_env_vars] + + +def bsub_available() -> bool: + """Check if the `bsub` shell command is available + + Returns True if the `bsub` command is available on the path, False otherwise. This is used to check whether code is + running on the Janelia Compute Cluster. + """ + result = which("bsub") is not None + return result + + +def get_LSFCLuster( + threads_per_worker: int = 1, + walltime: str = "1:00", + death_timeout: str = "600s", + **kwargs, +) -> LSFCluster: + """Create a dask_jobqueue.LSFCluster for use on the Janelia Research Campus compute cluster. + + This function wraps the class dask_jobqueue.LSFCLuster and instantiates this class with some sensible defaults, + given how the Janelia cluster is configured. + + This function will add environment variables that prevent libraries (OPENMP, MKL, BLAS) from running multithreaded routines with parallelism + that exceeds the number of requested cores. + + Additional keyword arguments added to this function will be passed to the dask_jobqueue.LSFCluster constructor. + + Parameters + ---------- + threads_per_worker: int + Number of cores to request from LSF. Directly translated to the `cores` kwarg to LSFCluster. + walltime: str + The expected lifetime of a worker. Defaults to one hour, i.e. "1:00" + death_timeout: str + The duration for the scheduler to wait for workers before flagging them as dead, e.g. "600s". For jobs with a large number of workers, + LSF may take a long time (minutes) to request workers. This timeout value must exceed that duration, otherwise the scheduler will + flag these slow-to-arrive workers as unresponsive and kill them. + **kwargs: + Additional keyword arguments passed to the LSFCluster constructor + + Examples + -------- + + >>> cluster = get_LSFCLuster(threads_per_worker=2, project="scicompsoft", queue="normal") + + """ + + if "job_script_prologue" not in kwargs: + kwargs["job_script_prologue"] = [] + + kwargs["job_script_prologue"].extend(make_single_threaded_env_vars(threads_per_worker)) + + USER = os.environ["USER"] + HOME = os.environ["HOME"] + + if "local_directory" not in kwargs: + # The default local scratch directory on the Janelia Cluster + kwargs["local_directory"] = f"/scratch/{USER}/" + + if "log_directory" not in kwargs: + log_dir = f"{HOME}/.dask_distributed/" + Path(log_dir).mkdir(parents=False, exist_ok=True) + kwargs["log_directory"] = log_dir + + # Memory is required by dask_jobqueue but not meaningful for slot-based LSF clusters + # Set a default that satisfies the library without affecting job submission + if "memory" not in kwargs: + kwargs["memory"] = "16GB" + + cluster = LSFCluster( + cores=threads_per_worker, + walltime=walltime, + death_timeout=death_timeout, + **kwargs, + ) + return cluster + + +def get_LocalCluster(threads_per_worker: int = 1, n_workers: int = 0, **kwargs): + """ + Creata a distributed.LocalCluster with defaults that make it more similar to a deployment on the Janelia Compute cluster. + This function is a light wrapper around the distributed.LocalCluster constructor. + + Parameters + ---------- + n_workers: int + The number of workers to start the cluster with. This defaults to 0 here. + threads_per_worker: int + The number of threads to assign to each worker. + **kwargs: + Additional keyword arguments passed to the LocalCluster constructor + Examples + -------- + + >>> cluster = get_LocalCluster(threads_per_worker=8) + """ + return LocalCluster( + n_workers=n_workers, threads_per_worker=threads_per_worker, **kwargs + ) + + +def get_cluster( + threads_per_worker: int = 1, + deployment: Optional[str] = None, + local_kwargs: Dict[str, Any] = {}, + lsf_kwargs: Dict[str, Any] = {}, +) -> Union[LSFCluster, LocalCluster]: + + """Convenience function to generate a dask cluster on either a local machine or the compute cluster. + + Create a distributed.Client object backed by either a dask_jobqueue.LSFCluster (for use on the Janelia Compute Cluster) + or a distributed.LocalCluster (for use on a single machine). This function uses the output of the bsubAvailable function + to determine whether code is running on the compute cluster or not. + Additional keyword arguments given to this function will be forwarded to the constructor for the Client object. + + Parameters + ---------- + threads_per_worker: int + Number of threads per worker. Defaults to 1. + + deployment: str or None + Which deployment (LocalCluster or LSFCluster) to prefer. If deployment=None, then LSFCluster is preferred, but LocalCluster is used if + bsub is not available. If deployment='lsf' and bsub is not available, an error is raised. + local_kwargs: dict + Dictionary of keyword arguments for the distributed.LocalCluster constructor + lsf_kwargs: dict + Dictionary of keyword arguments for the dask_jobqueue.LSFCluster constructor + """ + + if "cores" in lsf_kwargs: + warnings.warn( + "The `cores` kwarg for LSFCLuster has no effect. Use the `threads_per_worker` argument instead." + ) + + if "threads_per_worker" in local_kwargs: + warnings.warn( + "the `threads_per_worker` kwarg was found in `local_kwargs`. It will be overwritten with the `threads_per_worker` argument to this function." + ) + + if deployment is None: + if bsub_available(): + cluster = get_LSFCLuster(threads_per_worker, **lsf_kwargs) + else: + cluster = get_LocalCluster(threads_per_worker, **local_kwargs) + elif deployment == "lsf": + if bsub_available(): + cluster = get_LSFCLuster(threads_per_worker, **lsf_kwargs) + else: + raise EnvironmentError( + "You requested an LSFCluster but the command `bsub` is not available." + ) + elif deployment == "local": + cluster = get_LocalCluster(threads_per_worker, **local_kwargs) + else: + raise ValueError( + f'deployment must be one of (None, "lsf", or "local"), not {deployment}' + ) + + return cluster diff --git a/src/python/janelia_emrp/dask_bag_test.py b/src/python/janelia_emrp/dask_bag_test.py index 4571fc3e..e0f49d1b 100644 --- a/src/python/janelia_emrp/dask_bag_test.py +++ b/src/python/janelia_emrp/dask_bag_test.py @@ -3,7 +3,7 @@ import dask.bag as dask_bag import sys import time -from dask_janelia import get_cluster +from janelia_emrp.cluster import get_cluster from distributed import Client logger = logging.getLogger() diff --git a/src/python/janelia_emrp/fibsem/dat_clipper.py b/src/python/janelia_emrp/fibsem/dat_clipper.py index 60fabe3f..0856a530 100644 --- a/src/python/janelia_emrp/fibsem/dat_clipper.py +++ b/src/python/janelia_emrp/fibsem/dat_clipper.py @@ -6,7 +6,7 @@ from pathlib import Path import numpy as np -from fibsem_tools.io.fibsem import OFFSET +from fibsem_tools.io.dat import OFFSET from janelia_emrp.fibsem.dat_to_scheffer_8_bit import compress_and_save from janelia_emrp.root_logger import init_logger diff --git a/src/python/janelia_emrp/fibsem/dat_converter.py b/src/python/janelia_emrp/fibsem/dat_converter.py index e7d939a0..92fb927a 100644 --- a/src/python/janelia_emrp/fibsem/dat_converter.py +++ b/src/python/janelia_emrp/fibsem/dat_converter.py @@ -13,7 +13,7 @@ import math import sys import time -from dask_janelia import get_cluster +from janelia_emrp.cluster import get_cluster from distributed import Client from janelia_emrp.fibsem.cyx_dat import CYXDat, new_cyx_dat @@ -409,7 +409,7 @@ def main(arg_list: list[str]): args = parser.parse_args(arg_list) - convert_volume(volume_transfer_info=VolumeTransferInfo.parse_file(args.volume_transfer_info), + convert_volume(volume_transfer_info=VolumeTransferInfo.model_validate_json(Path(args.volume_transfer_info).read_text()), num_workers=args.num_workers, parent_work_dir=args.parent_work_dir, first_dat=args.first_dat, diff --git a/src/python/janelia_emrp/fibsem/dat_to_h5_writer.py b/src/python/janelia_emrp/fibsem/dat_to_h5_writer.py index 525cd6b0..b983d833 100644 --- a/src/python/janelia_emrp/fibsem/dat_to_h5_writer.py +++ b/src/python/janelia_emrp/fibsem/dat_to_h5_writer.py @@ -9,7 +9,7 @@ import h5py import numpy as np import sys -from fibsem_tools.io.fibsem import OFFSET, MAGIC_NUMBER +from fibsem_tools.io.dat import OFFSET, MAGIC_NUMBER from h5py import Dataset, Group from xarray_multiscale import multiscale from xarray_multiscale.reducers import windowed_mean diff --git a/src/python/janelia_emrp/fibsem/h5_raw_to_align.py b/src/python/janelia_emrp/fibsem/h5_raw_to_align.py index b2b08451..a79c7328 100644 --- a/src/python/janelia_emrp/fibsem/h5_raw_to_align.py +++ b/src/python/janelia_emrp/fibsem/h5_raw_to_align.py @@ -12,7 +12,7 @@ import numpy as np import sys import time -from dask_janelia import get_cluster +from janelia_emrp.cluster import get_cluster from distributed import Client from janelia_emrp.fibsem.cyx_dat import CYXDat @@ -288,7 +288,7 @@ def main(arg_list: list[str]): args = parser.parse_args(arg_list) - convert_volume(volume_transfer_info=VolumeTransferInfo.parse_file(args.volume_transfer_info), + convert_volume(volume_transfer_info=VolumeTransferInfo.model_validate_json(Path(args.volume_transfer_info).read_text()), num_workers=args.num_workers, parent_work_dir=args.parent_work_dir, first_h5=args.first_h5, diff --git a/src/python/janelia_emrp/fibsem/h5_to_render.py b/src/python/janelia_emrp/fibsem/h5_to_render.py index 79c24a17..7a8a015e 100644 --- a/src/python/janelia_emrp/fibsem/h5_to_render.py +++ b/src/python/janelia_emrp/fibsem/h5_to_render.py @@ -9,7 +9,7 @@ import dask.bag as db import h5py import renderapi -from dask_janelia import get_cluster +from janelia_emrp.cluster import get_cluster from janelia_emrp.fibsem.dat_path import DatPath, new_dat_path from janelia_emrp.fibsem.dat_to_h5_writer import DAT_FILE_NAME_KEY @@ -571,7 +571,7 @@ def main(arg_list): args = parser.parse_args(args=arg_list) - volume_transfer_info: VolumeTransferInfo = VolumeTransferInfo.parse_file(args.volume_transfer_info) + volume_transfer_info: VolumeTransferInfo = VolumeTransferInfo.model_validate_json(Path(args.volume_transfer_info).read_text()) if volume_transfer_info.cluster_root_paths is None: raise ValueError(f"cluster_root_paths not defined in {args.volume_transfer_info}") diff --git a/src/python/janelia_emrp/fibsem/volume_transfer_info.py b/src/python/janelia_emrp/fibsem/volume_transfer_info.py index 69b3fc9c..f2adeb8d 100644 --- a/src/python/janelia_emrp/fibsem/volume_transfer_info.py +++ b/src/python/janelia_emrp/fibsem/volume_transfer_info.py @@ -65,8 +65,8 @@ class ScopeDataSet(BaseModel): data_set_id: str rows_per_z_layer: int = 1 columns_per_z_layer: int = 1 - first_dat_name: Optional[str] - last_dat_name: Optional[str] + first_dat_name: Optional[str] = None + last_dat_name: Optional[str] = None dat_x_and_y_nm_per_pixel: int dat_z_nm_per_pixel: int dat_tile_overlap_microns: int = 2 @@ -96,16 +96,16 @@ def last_dat_acquire_time(self): class ClusterRootDirectoryPaths(BaseModel): """Cluster accessible (e.g. /groups or /nrs) paths for data.""" - raw_dat: Optional[Path] - raw_h5: Optional[Path] - align_h5: Optional[Path] - export_n5: Optional[Path] + raw_dat: Optional[Path] = None + raw_h5: Optional[Path] = None + align_h5: Optional[Path] = None + export_n5: Optional[Path] = None class ArchiveRootDirectoryPaths(BaseModel): """Archive (e.g. /nearline) paths for data.""" - raw_dat: Optional[Path] - raw_h5: Optional[Path] + raw_dat: Optional[Path] = None + raw_h5: Optional[Path] = None class RenderConnect(BaseModel): @@ -143,9 +143,9 @@ class RenderDataSet(BaseModel): project: str stack: str restart_context_layer_count: int - mask_width: Optional[int] - mask_height: Optional[int] - connect: Optional[RenderConnect] + mask_width: Optional[int] = None + mask_height: Optional[int] = None + connect: Optional[RenderConnect] = None def __str__(self): return f"{self.owner}::{self.project}" @@ -241,17 +241,17 @@ class VolumeTransferInfo(BaseModel): # path of file from which the transfer information was loaded or None if not loaded from a file """ transfer_id: str - scope_data_set: Optional[ScopeDataSet] - cluster_root_paths: Optional[ClusterRootDirectoryPaths] - archive_root_paths: Optional[ArchiveRootDirectoryPaths] - max_mipmap_level: Optional[int] - render_data_set: Optional[RenderDataSet] - transfer_tasks: list[VolumeTransferTask] - fill_info: Optional[FillInfo] - cluster_job_project_for_billing: str - number_of_dats_converted_per_hour: Optional[int] - number_of_preview_workers: Optional[int] - parsed_from_path: Optional[Path] + scope_data_set: Optional[ScopeDataSet] = None + cluster_root_paths: Optional[ClusterRootDirectoryPaths] = None + archive_root_paths: Optional[ArchiveRootDirectoryPaths] = None + max_mipmap_level: Optional[int] = None + render_data_set: Optional[RenderDataSet] = None + transfer_tasks: list[VolumeTransferTask] = [] + fill_info: Optional[FillInfo] = None + cluster_job_project_for_billing: str = "" + number_of_dats_converted_per_hour: Optional[int] = None + number_of_preview_workers: Optional[int] = None + parsed_from_path: Optional[Path] = None def __str__(self): return self.transfer_id @@ -335,7 +335,7 @@ def build_volume_transfer_list(volume_transfer_dir_path: Path, if volume_transfer_dir_path.is_dir(): for path in volume_transfer_dir_path.glob("volume_transfer*.json"): - transfer_info: VolumeTransferInfo = VolumeTransferInfo.parse_file(path) + transfer_info: VolumeTransferInfo = VolumeTransferInfo.model_validate_json(path.read_text()) transfer_info.parsed_from_path = Path(path).absolute() if for_tasks is None or transfer_info.includes_at_least_one_of_these_tasks(for_tasks):