PedestrianDynamics / PedestrianDynamics/PedPy

Add animation functions for trajectories and Voronoi cells in Jupyter notebooks

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documentation usability
Dominant language
Pascal
Stars
35
Forks
18
Avg merge
1d 14h
Merged PRs (30d)
2

Description

Summary

Add animate_trajectories and animate_voronoi_cells functions to PedPy that render frame-by-frame animations of pedestrian data directly in Jupyter notebooks.

Background / Context

PedPy currently supports static trajectory and Voronoi plots but has no animation capability. Animating pedestrian movement over time is a core analysis and presentation need for users working in notebook-based workflows. This is a frequently requested feature.

Technical Details

  • Animations should be based on matplotlib.animation.FuncAnimation and rendered in notebooks via IPython.display.HTML
  • Interface should align with existing plot_trajectories for parameter naming consistency (e.g. traj, walkable_area, color_data, color_column, cmap)
  • IPython should be an optional dependency with a descriptive error when called outside a notebook environment
  • New functions belong in pedpy/plotting/

Acceptance Criteria

  • Usage is demonstrated in the user guide notebook
  • IPython is listed as an optional dependency with a descriptive error when missing

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start in pedpy/plotting/ and read the existing plot_trajectories interface, then review the user guide notebook and the requested FuncAnimation/IPython.display.HTML approach. Done means both animation functions support the stated plotting parameters, notebook usage is documented, and missing IPython produces a descriptive error.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
data-visualization, documentation
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
65/100

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