cellmap-analyze

A suite of Dask-powered tools for processing and analyzing terabyte-scale 3D segmentation datasets. Supports both isotropic and anisotropic voxel sizes.

Features

Processing Tools

Analysis Tools

Anisotropic data

All operations handle anisotropic voxel sizes (e.g. (8, 8, 32) nm in ZYX). Physical-unit parameters like minimum_volume_nm_3, contact_distance_nm, and gaussian_smoothing_sigma_nm are automatically converted to the appropriate per-axis voxel units. When two datasets have different voxel sizes, they are resampled to a common resolution using nearest-neighbor interpolation.

Installation

pip install cellmap-analyze

Usage

All commands share the same basic interface:

<command> [options] <config_path>

• <command>: One of the processing or analysis tools listed above.

• <config_path>: Directory containing:

  • run-config.yaml (parameters for your chosen command)
  • dask-config.yaml (Dask cluster settings)

Options:

• -n, --num-workers N: Number of Dask workers to launch.

Output: A new directory named config_path-<YYYYMMDDHHMMSS> will be created, containing copies of your configs and an output.log for monitoring.

Configuration Examples

The following run-config.yaml could be used to run connected-components.

run-config.yaml

input_path: /path/to/predictions.zarr/mito/s0
output_path: /path/to/segmentations.zarr/mito
intensity_threshold_minimum: 0.71
minimum_volume_nm_3: 1E7
delete_tmp: true
connectivity: 1
mask_config:
  cell:
    path: /path/to/masks.zarr/cell/s0
    mask_type: inclusive
fill_holes: true

dask-config.yaml

The following dask-config.yaml files can be used for a variety of tasks.

Local

jobqueue:
  local:
    ncpus: 1
    processes: 1
    cores: 1
    log-directory: job-logs
    name: dask-worker

distributed:
  scheduler:
    work-stealing: true

LSF Cluster

jobqueue:
  lsf:
    ncpus: 8        # cores per job chunk
    processes: 12  # worker processes per chunk
    cores: 12      # threads per process (1 thread each)
    memory: 120GB  # 15 GB per slot
    walltime: 08:00
    mem: 120000000000
    use-stdin: true
    log-directory: job-logs
    name: cellmap-analyze
    project: charge_group

distributed:
  scheduler:
    work-stealing: true
  admin:
    log-format: '[%(asctime)s] %(levelname)s %(message)s'
    tick:
      interval: 20ms
      limit: 3h

Submission

To run on 12 dask workers:

Local run example:

connected-components -n 12 config_path

Cluster submit example (LSF):

bsub -n 4 -P chargegroup connected-components -n 12 config_path

Acknowledgements

The center-finding implementation is taken from funlib.evaluate.