Inference

Running inference with workflows-anemoi is straightforward and can be done in two main ways: from an input source or from an existing source node. Below are examples of both methods.

From Input

To create a workflow representation of an anemoi-inference task, use the following code:

from earthkit.workflows.plugins import anemoi as anemoi_workflows

CKPT = {"huggingface": "ecmwf/aifs-single-1.0"}

model_action = anemoi_workflows.fluent.from_input(
    CKPT, "mars", "2022-01-01T00:00", lead_time="7D"
)
model_action

This will use load the checkpoint, and use the mars input source, with a lead_time of 7 days. It is possible to configure the input source just like you would do with the anemoi-inference interfaces.

From Source

If more complex initial conditions are required, you can use the infer method on an existing source node.

from earthkit.workflows.plugins import anemoi as anemoi_workflows
from earthkit.workflows import fluent

SOURCE_NODES: fluent.Action
CKPT = {"huggingface": "ecmwf/aifs-single-1.0"}

SOURCE_NODES.anemoi.infer(CKPT, lead_time="7D")

This will use the existing source nodes as the initial conditions, and run the inference task with the specified checkpoint, lead time. If the source nodes have an ensemble dimension, it will also run the inference task for each ensemble member.