Installation Instructions¶

Install the package.

On macOS, use python3/pip3 if python/pip are not available.
```
python -m pip install pynnlf
```

This may take about 10 minutes. Although newer Python versions may work, the tool was tested on Python 3.12.3.

How to Use The Tool¶

Initialize a workspace in any directory you want. This guide uses example_project as the example workspace name. By default, only the sample dataset (ds0) is included.

Run this in Python. On macOS, start Python with python3 if python is not available.
```
import pynnlf

pynnlf.init("example_project")
```
Set up your experiment in example_project/specs/experiment.yaml.

Run the experiment.

import pynnlf

pynnlf.run_experiment("example_project/specs/experiment.yaml")

To skip plot generation and save storage for a run, pass plot_enabled=False.

import pynnlf

pynnlf.run_experiment(
    "example_project/specs/experiment.yaml",
    plot_enabled=False,
)

The tool outputs evaluation results in example_project/experiment_result/. When plotting is disabled, PyNNLF does not create the *_cv1_plots/ folder.

Example YAML inputs in example_project/specs/experiment.yaml:

dataset: ds0
forecast_horizon: fh1
model: m6
hyperparameter: hp1

For the list of available datasets and models, how to modify model hyperparameters, how to add a model, how to add a dataset, and the API reference, see the Detailed Guide page.