plotly / plotly/plotly.py

[FEATURE]: get_subplot_geometry()

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Python
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Description

[FEATURE]: get_subplot_geometry() — Expose Computed Subplot Cell Pixel Positions

Summary

When building dashboards or figures with custom overlays, users frequently need to know
the exact pixel position and dimensions of each subplot cell. Plotly computes these
internally but never surfaces them. This issue proposes a new method
get_subplot_geometry() that returns the computed pixel boundaries of every subplot
in a figure for production use.


Problem Statement

There is currently no reliable way to answer the question:

"Where exactly, in pixels, does subplot xy start and how wide and tall is it?"

Users who need this information are forced to either:

  • Hardcode pixel values based on trial and error (breaks on resize or data change)
  • Reverse-engineer Plotly's internal domain-to-pixel calculations (brittle, undocumented)
  • Call full_figure_for_development(), which is explicitly not for production use, slow,
    and returns normalized domain values (0–1) rather than actual pixels

This is a recurring pain point for users building:

  • Dashboards where external HTML elements must align with specific subplot axes
  • Stacked figures that need pixel-perfect y-axis alignment across separate charts
  • Custom annotation layers that anchor to subplot cell boundaries
  • Accessibility tools that need to describe where each chart lives on screen

Proposed Solution

A new method on Figure and FigureWidget:

geometry = fig.get_subplot_geometry()
Example Return Structure
{
    "subplots": {
        "xy": {
            "x": 80,
            "y": 60,
            "width": 400,
            "height": 300,
            "x2": 480,
            "y2": 360
        },
        "x2y2": {
            "x": 520,
            "y": 60,
            "width": 400,
            "height": 300,
            "x2": 920,
            "y2": 360
        }
    },
    "figure": {
        "total_width": 1000,
        "total_height": 800
    }
}

x and y are the top-left corner of the inner plotting area (inside the axes,
excluding tick labels and axis titles), measured in pixels from the top-left of
the figure.

Optional Parameters
# Include outer bounding box that covers tick labels and axis titles
fig.get_subplot_geometry(include_axis_labels=True)

# Limit results to specific subplots
fig.get_subplot_geometry(subplots=["xy", "x2y2"])
Two Backend Paths, One Interface
  • FigureWidget in Jupyter: queries the live graph div directly for true
    browser-rendered pixel values
  • Static Figure: falls back to a scoped Kaleido render using the figure's
    explicit width and height

The user does not manage which path is used — the method selects automatically.

JavaScript Access
// No new method needed for JS users
gd._computedLayout.subplots["xy"].x
gd._computedLayout.subplots["xy"].width
gd._computedLayout.figure.total_width

Why Not Use full_figure_for_development()?

full_figure_for_development() exposes normalized domain values (e.g. [0.0, 0.45])
but:

  • Does not return pixel positions
  • Is documented as not for production use
  • Is slow and returns a very large object
  • Does not reflect true browser dimensions when using FigureWidget

This feature is the production-safe, pixel-accurate alternative for layout geometry
specifically.


Prior Art
Tool Equivalent
matplotlib ax.get_position(), ax.get_window_extent()
bokeh plot.inner_width, plot.inner_height
Browser DOM element.getBoundingClientRect()

Backward Compatibility

This is a purely additive change. No existing figures, attributes, or workflows
are affected.


Related Issues

I'm happy to help refine the return structure, naming conventions, or scope.
The goal is to open a concrete discussion rather than a vague wish.

Guide de contribution

Ouvrir le guide de contribution

Par où commencer

  1. Lisez l'issue en entier, puis le guide de contribution du projet.
  2. Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
  3. Forkez le dépôt et travaillez sur une branche.
  4. Ouvrez une pull request qui référence le numéro de l'issue.

Piste de recherche

Commencez par localiser les points d’entrée de Figure et FigureWidget ainsi que la gestion existante de la mise en page ou de la géométrie qui se trouve derrière. Comparez le chemin proposé via live graph-div avec le chemin statique de Kaleido, puis définissez des tests pour les dimensions renvoyées des subplots et des figures, le filtrage et l’inclusion des libellés d’axes. Le travail est terminé lorsqu’une interface cohérente fonctionne pour les deux backends avec des coordonnées en pixels documentées.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Évaluation

Stack technique
javascript, jupyter-notebook, python
Domaine
api, data-visualization, frontend
Type d'issue
Fonctionnalité
Difficulté
5/5
Temps estimé
Plus d'une semaine
Activité
Calme
Clarté
Plutôt claire
Accessibilité débutants
35/100

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