from collections.abc import Callable

import xarray as xr
from soundevent import data

from batdetect2.train.augmentations import (
    add_echo,
    mix_examples,
    select_random_subclip,
)
from batdetect2.train.preprocess import (
    TrainPreprocessingConfig,
    generate_train_example,
)


def test_mix_examples(
    recording_factory: Callable[..., data.Recording],
):
    recording1 = recording_factory()
    recording2 = recording_factory()

    clip1 = data.Clip(recording=recording1, start_time=0.2, end_time=0.7)

    clip2 = data.Clip(recording=recording2, start_time=0.3, end_time=0.8)

    clip_annotation_1 = data.ClipAnnotation(clip=clip1)

    clip_annotation_2 = data.ClipAnnotation(clip=clip2)

    config = TrainPreprocessingConfig()

    example1 = generate_train_example(clip_annotation_1, config)
    example2 = generate_train_example(clip_annotation_2, config)

    mixed = mix_examples(example1, example2, config=config.preprocessing)

    assert mixed["spectrogram"].shape == example1["spectrogram"].shape
    assert mixed["detection"].shape == example1["detection"].shape
    assert mixed["size"].shape == example1["size"].shape
    assert mixed["class"].shape == example1["class"].shape


def test_add_echo(
    recording_factory: Callable[..., data.Recording],
):
    recording1 = recording_factory()
    clip1 = data.Clip(recording=recording1, start_time=0.2, end_time=0.7)
    clip_annotation_1 = data.ClipAnnotation(clip=clip1)
    config = TrainPreprocessingConfig()
    original = generate_train_example(clip_annotation_1, config)
    with_echo = add_echo(original, config=config.preprocessing)

    assert with_echo["spectrogram"].shape == original["spectrogram"].shape
    xr.testing.assert_identical(with_echo["size"], original["size"])
    xr.testing.assert_identical(with_echo["class"], original["class"])
    xr.testing.assert_identical(with_echo["detection"], original["detection"])


def test_selected_random_subclip_has_the_correct_width(
    recording_factory: Callable[..., data.Recording],
):
    recording1 = recording_factory()
    clip1 = data.Clip(recording=recording1, start_time=0.2, end_time=0.7)
    clip_annotation_1 = data.ClipAnnotation(clip=clip1)
    config = TrainPreprocessingConfig()
    original = generate_train_example(clip_annotation_1, config)
    subclip = select_random_subclip(original, width=100)

    assert subclip["spectrogram"].shape[1] == 100