imspy-vis

Lightweight visualization tools for timsTOF proteomics data.

Installation

pip install imspy-vis

For Jupyter notebook support:

pip install imspy-vis[notebook]

Features

• Frame Rendering: DDA and DIA frame visualization with annotation overlays
• Point Cloud Visualization: Interactive 3D visualization using Plotly
• Video Generation: Generate preview videos from timsTOF datasets
• Jupyter Integration: Interactive widgets for notebook-based exploration

Quick Start

Frame Rendering

from imspy_vis import DDAFrameRenderer, DIAFrameRenderer, generate_preview_video

# Generate a quick preview video
generate_preview_video(
    '/path/to/data.d',
    '/path/to/output.mp4',
    mode='dda',
    max_frames=100,
    fps=10
)

# Or use the renderer directly
renderer = DDAFrameRenderer('/path/to/data.d')
renderer.render_to_video('/path/to/output.mp4', max_frames=50)

Point Cloud Visualization (Jupyter)

from imspy_vis import DDAPrecursorPointCloudVis

# In a Jupyter notebook
visualizer = DDAPrecursorPointCloudVis(precursor_data)
visualizer.display_widgets()

Modules

• pointcloud: Interactive 3D point cloud visualization using Plotly
• frame_rendering: Frame-by-frame rendering and video generation

Dependencies

• imspy-core: Core data structures (required)
• plotly: Interactive plotting
• matplotlib: Static plotting and frame rendering
• imageio: Video generation
• ipywidgets: Jupyter notebook widgets

Related Packages

• imspy-core: Core data structures and timsTOF readers
• imspy-predictors: ML-based predictors
• imspy-simulation: TimSim simulation tools
• imspy-search: Database search functionality

License

MIT License - see LICENSE file for details.