roastcoffea.visualization.plots.memory

Memory utilization timeline plotting.

Functions

plot_memory_utilization_mean_timeline(...[, ...])

Plot mean memory utilization percentage over time with min-max band.

plot_memory_utilization_per_worker_timeline(...)

Plot memory utilization percentage per worker over time.

roastcoffea.visualization.plots.memory.plot_memory_utilization_mean_timeline(tracking_data, output_path=None, figsize=(10, 4), title='Memory Utilization Over Time')[source]

Plot mean memory utilization percentage over time with min-max band.

Shows aggregated memory usage across all workers, with mean line and shaded min-max range.

Parameters:
  • tracking_data (dict or None) – Tracking data with worker_memory and worker_memory_limit

  • output_path (Path, optional) – Save path

  • figsize (tuple) – Figure size

  • title (str) – Plot title

Returns:

fig, ax – Matplotlib figure and axes

Return type:

Figure and Axes

Raises:

ValueError – If tracking_data is None or missing memory data

roastcoffea.visualization.plots.memory.plot_memory_utilization_per_worker_timeline(tracking_data, output_path=None, figsize=(12, 6), title='Memory Utilization Per Worker Over Time', max_legend_entries=5)[source]

Plot memory utilization percentage per worker over time.

Shows actual memory usage as percentage of limit (0-100%) for each worker, providing insight into memory resource utilization.

Parameters:
  • tracking_data (dict or None) – Tracking data with worker_memory and worker_memory_limit

  • output_path (Path, optional) – Save path

  • figsize (tuple) – Figure size

  • title (str) – Plot title

  • max_legend_entries (int, optional) – Maximum number of workers to show in legend. Default is 5.

Returns:

fig, ax – Matplotlib figure and axes

Return type:

Figure and Axes

Raises:

ValueError – If tracking_data is None or missing memory data