trackpy

trackpy

Overview

trackpy is a Python library for single-particle tracking (SPT) in video microscopy. It implements the Crocker-Grier algorithm to locate bright spots in each frame with subpixel precision, then links those positions across frames into continuous trajectories. From trajectories, trackpy computes mean squared displacement (MSD), diffusion coefficients, and motion classifications (confined, normal, directed). It handles 2D fluorescence videos, 3D confocal z-stacks, and large image sequences via memory-efficient streaming through the pims image reader library.

When to Use

• You have a fluorescence microscopy video of labeled particles (quantum dots, fluorescent beads, vesicles, receptors) and need to extract individual trajectories and diffusion coefficients.
• You want to measure particle mobility: compute MSD curves and distinguish Brownian diffusion, directed motion, or confined motion from single-particle tracks.
• You are analyzing colloid dynamics, lipid membrane diffusion, intracellular cargo transport, or virus-cell interactions where you need per-particle trajectory data.
• You need 3D tracking from confocal z-stack time series to capture out-of-plane motion of particles or organelles.
• You want to apply drift correction to remove stage drift before computing intrinsic particle motion statistics.
• You need ensemble MSD averaged across hundreds of tracks to extract population-level diffusion behavior with statistical power.
• Use TrackMate (Fiji/ImageJ plugin) instead when you need a graphical interface, manual curation of tracks, or integration with biological object segmenters (Cellpose, StarDist).
• Use napari with napari-trackpy instead when you want interactive visualization and manual editing of trajectories alongside image data.

Prerequisites

• Python packages: trackpy, pims, pandas, numpy, matplotlib, scipy
• Data requirements: Grayscale or single-channel image sequence (TIF stack, AVI, or directory of PNG/TIF frames); particles should appear as bright Gaussian spots on a darker background (or use invert=True for dark spots on bright background)
• Environment: Works in Jupyter notebooks and scripts; pims handles most microscopy formats; for ND2 or CZI files install pims-nd2 or aicsimageio

pip install trackpy pims pandas numpy matplotlib scipy
# For reading multi-channel or proprietary formats:
pip install pims[bioformats]   # Bioformats via JPype
pip install aicsimageio        # ND2, CZI, LIF via AICSImageIO

Quick Start

import trackpy as tp
import pims

# Load a TIF image stack (T frames × Y × X)
frames = pims.open("particles.tif")   # shape: (T, Y, X)

# Locate particles in all frames