experiment_runner.main

Entry point for the xai4tsc experiment runner.

Run from the repository root as a module:

python -m experiment_runner.main --conf path/to/config.yaml

Orchestrates the full evaluation pipeline as a nested loop over datasets, models, explainers, and metrics. Results are saved as metrics.csv files at three granularity levels (global, per-dataset, per-model) under results_rel_path.

Attributes

`logger`
`MASTER_CONFIG`
`parser`

Functions

`expand_datasets`(→ list[dict])	Expand archive wildcards and resolve per-member `overrides`.
`main`(→ None)	Run a complete XAI evaluation experiment from a YAML configuration file.
`initial_setup`(→ dict)	Set up experiment as described in the given configuration file.

Module Contents

experiment_runner.main.logger

experiment_runner.main.MASTER_CONFIG

experiment_runner.main.expand_datasets(datasets: list[dict]) → list[dict]

Expand archive wildcards and resolve per-member overrides.

Each entry is either a concrete dataset or an archive keyword (UCR / UEA) that expands to all its member datasets. An entry’s inline settings apply to every member it produces; an optional overrides map ({dataset_name: {setting: value}}) sets per-member exceptions that take precedence over the entry’s inline settings.

Parameters:: datasets (list[dict]) – Raw data_config["datasets"] entries.
Returns:: Concrete dataset entries with overrides resolved and stripped.
Return type:: list[dict]

experiment_runner.main.main(config_path: str, debug: bool = False) → None

Run a complete XAI evaluation experiment from a YAML configuration file.

Orchestrates the full pipeline as a nested loop over datasets → models → explainers → metrics. Results are saved as metrics.csv at three granularity levels (global, per-dataset, per-model) under results_rel_path.

experiment_runner.main.initial_setup(config_path: str, debug: bool = False) → dict

Set up experiment as described in the given configuration file.

Parameters:

config_path (str) – Path to the experiment configuration.
debug (bool) – Enable debug-level logging.

Returns:

The extracted configuration.

Return type:

dict

experiment_runner.main.parser