Parallel Coordinates Plot

neptunecontrib.viz.parallel_coordinates_plot.make_parallel_coordinates_plot(html_file_path=None, metrics=False, text_logs=False, params=True, properties=False, experiment_id=None, state=None, owner=None, tag=None, min_running_time=None)[source]

Visualize experiments on the parallel coordinates plot.

This function, when executed in Notebook, displays interactive parallel coordinates plot in the cell’s output. Another option is to save visualization to the standalone html file. You can also inspect the lineage of experiments.

See example for the full use case.

Axes are ordered as follows: first axis is neptune experiment id, second is experiment owner, then params and properties in alphabetical order. Finally, metrics on the right side (alphabetical order as well).

This visualization it built using HiPlot. It is a library published by the Facebook AI group. Learn more about the parallel coordinates plot.

Tip

Use metrics, params and properties arguments to select what data you want to see as axes.

Use experiment_id, state, owner, tag, min_running_time arguments to filter experiments included in a plot. Only experiments matching all the criteria will be returned.

Note

Make sure you have your project set: neptune.init('USERNAME/example-project')

Parameters:
  • html_file_path (str, optional, default is None) –
    Saves visualization as a standalone html file. No external dependencies needed.
  • metrics (bool or str or list of str, optional, default is False) –
    Metrics to display on the plot (as axes).
    If True, then display all metrics.
    If False, then exclude all metrics.
  • text_logs (bool or str or list of str, optional, default is False) –
    Text logs to display on the plot (as axes).
    If True, then display all text logs.
    If False, then exclude all text logs.
  • params (bool or str or list of str, optional, default is True) –
    Parameters to display on the plot (as axes).
    If True, then display all parameters.
    If False, then exclude all parameters.
  • properties (bool or str or list of str, optional, default is False) –
    Properties to display on the plot (as axes).
    If True, then display all properties.
    If False, then exclude all properties.
  • experiment_id (str or list of str, optional, default is None) –
    An experiment id like 'SAN-1' or list of ids like ['SAN-1', 'SAN-2'].
    Matching any element of the list is sufficient to pass criterion.
  • state (str or list of str, optional, default is None) –
    An experiment state like 'succeeded' or list of states like ['succeeded', 'running'].
    Possible values: 'running', 'succeeded', 'failed', 'aborted'.
    Matching any element of the list is sufficient to pass criterion.
  • owner (str or list of str, optional, default is None) –
    Username of the experiment owner (User who created experiment is an owner) like 'josh' or list of owners like ['frederic', 'josh'].
    Matching any element of the list is sufficient to pass criterion.
  • tag (str or list of str, optional, default is None) –
    An experiment tag like 'lightGBM' or list of tags like ['pytorch', 'cycleLR'].
    Only experiments that have all specified tags will match this criterion.
  • min_running_time (int, optional, default is None) – Minimum running time of an experiment in seconds, like 2000.
Returns:

ExperimentDisplayed, object that can be used to get a list of Datapoint objects, like this: ExperimentDisplayed.get_selected(). This is only implemented for Jupyter notebook. Check HiPlot docs.

Examples

# Make sure you have your project set:
neptune.init('USERNAME/example-project')

# (example 1) visualization for all experiments in project
make_parallel_coordinates_plot()

# (example 2) visualization for experiment with tag 'optuna' and saving to html file.
make_parallel_coordinates_plot(html_file_path='visualizations.html', tag='optuna')

# (example 3) visualization with all params, two metrics for experiment with tag 'optuna'
make_parallel_coordinates_plot(tag='optuna', metrics=['epoch_accuracy', 'eval_accuracy'])

# (example 4) visualization with all params and two metrics. All experiments created by john.
make_parallel_coordinates_plot(metrics=['epoch_accuracy', 'eval_accuracy'], owner='john')