Plotly 3d surface scatter visualization

plotly-3d-surface-scatter-visualization

Summary

Create interactive 3D peak-map visualizations of mass spectrometry data using the Plotly backend in pyOpenMS-Viz. This skill enables rendering of m/z, retention time, and intensity dimensions as an interactive 3D surface or scatter plot, suitable for exploratory analysis of complex MS datasets.

When to use

Use this skill when you have mass spectrometry data (m/z, retention time, intensity) loaded into a Pandas DataFrame and need to explore the full 3D structure of a peak map interactively, particularly when static 2D heatmaps obscure important intensity relationships or when stakeholders require browser-based interactive inspection of MS data from mzML or Bruker .d format files.

When NOT to use

• Input data lacks three required dimensions (m/z, retention time, intensity) — fall back to 2D peakmap or spectrum visualization.
• Dataset is extremely large (>1 million points) and Plotly rendering becomes prohibitively slow — consider 2D heatmap or downsampled subset.
• Target deployment environment cannot serve HTML or JavaScript (e.g., headless server without display) — use static matplotlib or Bokeh backend instead.

Inputs

• Pandas DataFrame with columns for m/z, retention time, and intensity
• Mass spectrometry data file in mzML or Bruker .d format
• Plotly-compatible plotting backend configuration

Outputs

• Interactive Plotly 3D figure object (plotly.graph_objects.Figure)
• HTML file containing the interactive 3D peak-map visualization
• Browser-renderable visualization with rotation, zoom, and hover capabilities

How to apply

Load mass spectrometry data from mzML or Bruker .d files into a Pandas DataFrame with columns for m/z, retention time (rt), and intensity using PyOpenMS, pymzML, pyteomics, or alphatims. Set the Pandas plotting backend to 'plotly' and call the DataFrame.plot() method with parameters x='m/z', y='rt', z='intensity', kind='peakmap', and plot_3d=True. The Plotly rendering engine will generate an interactive HTML figure object; save it using fig.write_html() to produce a browser-viewable visualization. Verify that the 3D surface correctly maps all three dimensions and that interactivity (rotation, zoom, hover tooltips) functions without data loss.

Related tools

• pyOpenMS-Viz (Primary library providing the peakmap plotting interface and 3D rendering support via Plotly backend) — https://github.com/OpenMS/pyopenms_viz
• Pandas (Data manipulation and DataFrame structure required as input to pyOpenMS-Viz plotting API)
• Plotly (Interactive 3D graphing backend responsible for rendering and interactivity of the visualization)
• PyOpenMS (Mass spectrometry data loading and preprocessing from OpenMS formats)
• pymzML (Alternative tool for loading mass spectrometry data from mzML format files)
• pyteomics (Alternative tool for loading mass spectrometry data from mzML format files)
• alphatims (Tool for loading mass spectrometry data from Bruker .d format files)

Examples

import pandas as pd
from pyopenms import MSExperiment
ms_data = pd.read_csv('ms_peaks.csv')
pd.set_option('plotting.backend', 'plotly')
fig = ms_data.plot(x='m/z', y='rt', z='intensity', kind='peakmap', plot_3d=True)
fig.write_html('3d_peakmap.html')

Evaluation signals

• The rendered 3D plot displays all three dimensions (m/z on x-axis, retention time on y-axis, intensity on z-axis or color) without data loss or dimension conflation.
• Interactive controls (rotation, zoom, pan, hover tooltips showing m/z/rt/intensity values) respond smoothly without lag or visual artifacts.
• The HTML output file is valid and opens in a standard web browser without JavaScript errors or missing dependencies.
• Intensity values are correctly mapped to the z-axis or color scale; verify by hovering over peak regions and comparing reported values to source DataFrame.
• No warnings or exceptions are raised during plotting backend selection (pd.set_option('plotting.backend', 'plotly')) and figure generation.

Limitations

• Plotly 3D rendering supports peakmap plots but not mobilogram or chromatogram plots in 3D — those remain 2D only.
• Very large datasets (>1 million points) may experience slow interactivity or browser memory issues; downsampling may be required.
• The plot_3d=True flag is exclusive to Plotly backend; matplotlib and Bokeh backends do not support 3D peakmap rendering.
• Interactive HTML files require a modern web browser with JavaScript enabled; export to static image formats (PNG, SVG) is possible but loses interactivity.

Evidence

• [other] pyOpenMS-Viz integrates seamlessly with multiple plotting library backends including Plotly, which supports interactive visualizations of mass spectrometry data.: "pyOpenMS-Viz integrates seamlessly with multiple plotting library backends including Plotly, which supports interactive visualizations of mass spectrometry data."
• [other] Load mass spectrometry data from an mzML or Bruker .d file into a pandas DataFrame using PyOpenMS, pymzML, pyteomics (for mzML) or alphatims (for .d format): "Load mass spectrometry data from an mzML or Bruker .d file into a pandas DataFrame using PyOpenMS, pymzML, pyteomics (for mzML) or alphatims (for .d format)"
• [other] Call the DataFrame.plot() method with parameters x='m/z', y='rt', z='intensity' (or omit z for color mapping), kind='peakmap', and plot_3d=True to invoke the Plotly 3D rendering engine.: "Call the DataFrame.plot() method with parameters x='m/z', y='rt', z='intensity' (or omit z for color mapping), kind='peakmap', and plot_3d=True to invoke the Plotly 3D rendering engine."
• [other] Capture the returned Plotly figure object and save it as an interactive HTML file using fig.write_html() to verify successful 3D visualization and backend compatibility.: "Capture the returned Plotly figure object and save it as an interactive HTML file using fig.write_html() to verify successful 3D visualization and backend compatibility."
• [readme] PeakMap 3D requires x, y, z dimensions and is supported by matplotlib and Plotly but not Bokeh: "PeakMap 3D | x, y, z | peakmap (plot3d=True) | ✓ | | ✓"