"""BatDetect2 command line interface."""
import os
import warnings

warnings.filterwarnings("ignore", category=UserWarning)

import click  # noqa: E402

from bat_detect import api  # noqa: E402
from bat_detect.detector.parameters import DEFAULT_MODEL_PATH  # noqa: E402
from bat_detect.utils.detector_utils import save_results_to_file  # noqa: E402

CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))


INFO_STR = """
BatDetect2 - Detection and Classification
    Assumes audio files are mono, not stereo.
    Spaces in the input paths will throw an error. Wrap in quotes.
    Input files should be short in duration e.g. < 30 seconds.
"""


@click.group()
def cli():
    """BatDetect2 - Bat Call Detection and Classification."""
    click.echo(INFO_STR)


@cli.command()
@click.argument(
    "audio_dir",
    type=click.Path(exists=True),
)
@click.argument(
    "ann_dir",
    type=click.Path(exists=False),
)
@click.argument(
    "detection_threshold",
    type=float,
)
@click.option(
    "--cnn_features",
    is_flag=True,
    default=False,
    help="Extracts CNN call features",
)
@click.option(
    "--spec_features",
    is_flag=True,
    default=False,
    help="Extracts low level call features",
)
@click.option(
    "--time_expansion_factor",
    type=int,
    default=1,
    help="The time expansion factor used for all files (default is 1)",
)
@click.option(
    "--quiet",
    is_flag=True,
    default=False,
    help="Minimize output printing",
)
@click.option(
    "--save_preds_if_empty",
    is_flag=True,
    default=False,
    help="Save empty annotation file if no detections made.",
)
@click.option(
    "--model_path",
    type=str,
    default=DEFAULT_MODEL_PATH,
    help="Path to trained BatDetect2 model",
)
def detect(
    audio_dir: str,
    ann_dir: str,
    detection_threshold: float,
    **args,
):
    """Detect bat calls in files in AUDIO_DIR and save predictions to ANN_DIR.

    DETECTION_THRESHOLD is the detection threshold. All predictions with a
    score below this threshold will be discarded. Values between 0 and 1.

    Assumes audio files are mono, not stereo.

    Spaces in the input paths will throw an error. Wrap in quotes.

    Input files should be short in duration e.g. < 30 seconds.
    """
    click.echo(f"Loading model: {args['model_path']}")
    model, params = api.load_model(args["model_path"])

    click.echo(f"\nInput directory: {audio_dir}")
    files = api.list_audio_files(audio_dir)

    click.echo(f"Number of audio files: {len(files)}")
    click.echo(f"\nSaving results to: {ann_dir}")

    config = api.get_config(
        **{
            **params,
            **args,
            "spec_slices": False,
            "chunk_size": 2,
            "detection_threshold": detection_threshold,
        }
    )

    # process files
    error_files = []
    for audio_file in files:
        try:
            results = api.process_file(audio_file, model, config=config)

            if args["save_preds_if_empty"] or (
                len(results["pred_dict"]["annotation"]) > 0
            ):
                results_path = audio_file.replace(audio_dir, ann_dir)
                save_results_to_file(results, results_path)
        except (RuntimeError, ValueError, LookupError) as err:
            # TODO: Check what other errors can be thrown
            error_files.append(audio_file)
            click.echo(f"Error processing file!: {err}")
            raise err

    click.echo(f"\nResults saved to: {ann_dir}")

    if len(error_files) > 0:
        click.echo("\nUnable to process the follow files:")
        for err in error_files:
            click.echo(f"  {err}")


if __name__ == "__main__":
    cli()