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Examples Overview

This page provides an overview of the available examples and how to use them for diSPIM data processing with PySPIM.

Examples Directory Structure

The examples/ directory contains actual example code and data:

examples/
├── snakemake/                    # Snakemake workflow
│   ├── Snakefile                 # Main workflow definition
│   ├── config.yaml              # Configuration file
│   ├── slurm.yaml               # SLURM cluster configuration
│   └── scripts/                 # Workflow scripts
├── data/                        # Example data
│   ├── sample_data/             # GitHub-friendly sample data
│   │   ├── basic_usage.ipynb    # Complete workflow notebook
│   │   ├── sh/                  # SLURM job scripts
│   │   └── README.md            # Usage instructions
│   └── example_dispim_data/     # Full example datasets
└── nb/                          # Jupyter notebooks
    └── basic_usage.ipynb        # Basic usage example

Available Examples

1. Snakemake Workflow

Location: examples/snakemake/

A complete Snakemake workflow for automated diSPIM processing pipeline.

Features: - Complete processing pipeline (load → ROI → deskew → deconvolve → save) - SLURM cluster integration - Uses example data from examples/data/ - Modular and extensible design

Quick Start: 

cd examples/snakemake/
./run_workflow.sh --local --cores 4

SLURM Execution: 

cd examples/snakemake/
./run_workflow.sh --slurm --jobs 10

Documentation: See Snakemake Workflow for detailed instructions.

2. Sample Data and Scripts

Location: examples/data/sample_data/

Contains sample data and SLURM job scripts for testing PySPIM functionality.

Contents: - basic_usage.ipynb - Complete workflow demonstration - sh/ - SLURM job scripts for batch processing - README.md - Detailed usage instructions

Usage: 

cd examples/data/sample_data
jupyter notebook basic_usage.ipynb

3. Jupyter Notebooks

Location: examples/nb/

Contains standalone Jupyter notebooks demonstrating PySPIM usage.

Contents: - basic_usage.ipynb - Basic usage example

Data Sources

Example Data

The examples use data from examples/data/fruiting_body_subset/: - fruiting_body_subset.ome.tif - Multi-channel TIFF data - PSFA_demo.npy - PSF for channel A - PSFB_demo.npy - PSF for channel B - acquisition_params.txt - Acquisition parameters

Using Your Own Data

  1. For Snakemake: Update config.yaml with your data paths and parameters
  2. For Notebooks: Modify the data paths in the notebook cells
  3. For SLURM Scripts: Update the paths in the shell scripts

Integration Examples

Snakemake Integration

# Include in larger workflow
include: "path/to/pyspim/examples/snakemake/Snakefile"

Nextflow Integration

Convert the Snakemake workflow to Nextflow processes.

Galaxy Integration

Use individual scripts as Galaxy tools.

Workflow Comparison

Feature Snakemake Workflow Jupyter Notebooks SLURM Scripts
Use Case Automated processing Interactive exploration Batch processing
ROI Selection Automatic only Manual or automatic Manual or automatic
Processing Steps Complete pipeline Step-by-step Individual steps
Scalability Multiple acquisitions Single acquisition Multiple acquisitions
Cluster Support SLURM integration Manual submission Direct SLURM
Reproducibility Automated Manual Manual
Learning Curve Moderate Low Low

Recommendations

For Production Workflows

  • Use the Snakemake workflow for automated processing
  • Ideal for multiple acquisitions
  • Excellent for cluster environments
  • Ensures reproducibility

For Learning and Development

  • Use Jupyter notebooks for interactive exploration
  • Good for understanding individual steps
  • Easy to modify and experiment

For Integration

  • Snakemake workflow is particularly suitable for HPC environments
  • Can be integrated into larger bioinformatics pipelines
  • Individual scripts can be used as building blocks

Troubleshooting

Common Issues

  1. napari not found: Install with pip install napari
  2. Memory issues: Reduce data size or use chunked processing
  3. SLURM errors: Check slurm.yaml configuration
  4. GPU errors: Ensure CUDA is available and GPU memory is sufficient

Getting Help

  • Check the individual README files in each example directory
  • Review the PySPIM documentation
  • Examine the example data structure for reference
  • Open an issue on GitHub for specific problems

Contributing Examples

To add new examples:

  1. Create a new directory or file in examples/
  2. Include a README with usage instructions
  3. Use the example data when possible
  4. Document integration possibilities
  5. Test with the provided example data
  6. Update this overview page

Next Steps