Add support for multidimensional metrics

[kzscisoft]

Add Support for Tensor Metrics

Issue: #833

Python Version(s) Tested: 3.13

Operating System(s): Ubuntu 25.04

Documentation PR: Issue on Docs repo.

📝 Summary

Allows the user to define a grid and then log tensors as metrics (or multidimensional metrics) to that grid.

🔄 Changes

Low Level API

• Creation of Grid class for defining a new grid:

grid = Grid.new(
    name="my_grid",
    grid=numpy.vstack([
        numpy.linspace(0, 10, 10),
        numpy.linspace(10, 20, 10)
    ]),
    labels=["x", "y"]
)
grid.assign_to_run(run_id)

• Creation of GridMetrics class for logging metrics across multiple grids for a given run:

metrics = GridMetrics.new(
    run=run_id,
    metrics=[
        {
            "timestamp": datetime.datetime.now(datetime.timezone.utc).strftime(
                "%Y-%m-%dT%H:%M:%S.%f"
            ),
            "time": _time,
            "step": _step,
            "array": numpy.ones((10, 10)),
            "grid_identifier": _grid.id
        }
    ],
)

User API

For the user, log_metrics has been updated to allow numpy arrays as metric values, the user must firstly assign or create a grid for that metric:

run.assign_metric_to_grid(
    metric_name="A",
    grid_name="base_grid",
    axes_ticks=numpy.vstack([
        numpy.linspace(0, 10, 10),
        numpy.linspace(10, 20, 10)
    ]),
    axes_labels=["x", "y"]
)
run.log_metrics({"x": 2, "A": numpy.ones((10, 10))}

Note if the user does not specify axes_ticks and axes_labels it is assumed the grid already exists.

✔️ Checklist

• Unit and integration tests passing.
• Pre-commit hooks passing.
• Quality checks passing.
• Updated the documentation.