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Quick Start Guide

Get up and running with PySPIM in minutes.

Prerequisites

  • Python 3.8.1 or higher
  • Napari (for the GUI plugin)
  • CUDA-compatible GPU (optional, for GPU acceleration)

Installation

# Clone and install
git clone https://github.com/matt-black/pyspim.git
cd pyspim
just install

Basic Usage

Napari Plugin Interface

  1. Launch Napari 

    napari

  2. Load the PySPIM Plugin

  3. Go to Plugins → PySPIM → DiSPIM Pipeline

  4. Follow the Workflow

  5. Tab 1: Load your data file
  6. Tab 2: Detect or select regions of interest
  7. Tab 3: Adjust deskewing parameters
  8. Tab 4: Configure registration settings
  9. Tab 5: Set deconvolution parameters

Command Line Interface

import pyspim
from pyspim.data import dispim as data
from pyspim import roi, deskew as dsk

# Load data
with data.uManagerAcquisition(data_path, False, numpy) as acq:
    a_raw = acq.get('a', 0, 0)
    b_raw = acq.get('b', 0, 0)

# ROI detection
roia = roi.detect_roi_3d(a_raw, 'otsu')
roib = roi.detect_roi_3d(b_raw, 'otsu')

# Deskewing
a_dsk = dsk.deskew_stage_scan(a_raw, pixel_size, step_size, 1)
b_dsk = dsk.deskew_stage_scan(b_raw, pixel_size, step_size, -1)

GPU Acceleration

For GPU acceleration:

# Install CuPy with CUDA support
pip install cupy-cuda12x

The plugin will automatically use GPU acceleration when available.

Next Steps