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aplose2raven deletion #396

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f0a24c5
so long suckers
mathieudpnt May 27, 2026
2e5713c
ruff4ever
mathieudpnt May 27, 2026
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179 changes: 0 additions & 179 deletions src/osekit/utils/formatting.py
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79 changes: 0 additions & 79 deletions tests/test_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,9 +6,7 @@
from typing import TYPE_CHECKING

import numpy as np
import pandas as pd
import pytest
from pandas import Timedelta

from osekit.core.ltas_dataset import LTASDataset
from osekit.core.spectro_dataset import SpectroDataset
Expand All @@ -20,88 +18,11 @@
nb_files_per_batch,
)
from osekit.utils.deserialization import deserialize_spectro_or_ltas_dataset
from osekit.utils.formatting import aplose2raven
from osekit.utils.path import is_absolute, move_tree

if TYPE_CHECKING:
from _pytest.monkeypatch import MonkeyPatch


@pytest.fixture
def aplose_dataframe() -> pd.DataFrame:
data = pd.DataFrame(
{
"dataset": ["dataset_test", "dataset_test", "dataset_test", "dataset_test"],
"filename": ["file1.wav", "file2.wav", "file3.wav", "file4.wav"],
"start_time": [0, 0, 5.9, 0],
"end_time": [30, 30, 8.1, 30],
"start_frequency": [0, 0, 18500.0, 0],
"end_frequency": [96000, 96000, 53000.0, 96000],
"annotation": ["boat", "boat", "boat", "boat"],
"annotator": ["bbjuni", "bbjuni", "bbjuni", "bbjuni"],
"start_datetime": [
pd.Timestamp("2020-05-29T11:30:00.000+00:00"),
pd.Timestamp("2020-05-29T11:31:00.000+00:00"),
pd.Timestamp("2020-05-29T11:31:05.900+00:00"),
pd.Timestamp("2020-05-29T11:32:50.000+00:00"),
],
"end_datetime": [
pd.Timestamp("2020-05-29T11:30:30.000+00:00"),
pd.Timestamp("2020-05-29T11:31:30.000+00:00"),
pd.Timestamp("2020-05-29T11:31:08.100+00:00"),
pd.Timestamp("2020-05-29T11:33:20.000+00:00"),
],
"is_box": [0, 0, 1, 0],
},
)

return data.reset_index(drop=True)


@pytest.fixture
def audio_timestamps() -> list:
return list(
pd.date_range(
start="2020-05-29T11:30:00.000+00:00",
end="2020-05-29T11:35:00.000+00:00",
freq="1min",
),
)


@pytest.fixture
def audio_durations(audio_timestamps: pytest.fixture) -> list:
return [Timedelta("30s")] * len(audio_timestamps)


@pytest.mark.unit
def test_aplose2raven(
aplose_dataframe: pytest.fixture,
audio_timestamps: pytest.fixture,
audio_durations: pytest.fixture,
) -> None:
raven_dataframe = aplose2raven(
aplose_result=aplose_dataframe,
list_audio_begin_time=audio_timestamps,
audio_durations=audio_durations,
)

expected_raven_dataframe = pd.DataFrame(
{
"Selection": [1, 2, 3, 4],
"View": [1, 1, 1, 1],
"Channel": [1, 1, 1, 1],
"Begin Time (s)": [0.0, 30.0, 35.9, 90.0],
"End Time (s)": [30.0, 60.0, 38.1, 110.0],
"Low Freq (Hz)": [0.0, 0.0, 18500.0, 0.0],
"High Freq (Hz)": [96000.0, 96000.0, 53000.0, 96000.0],
"Begin Date Time Real": aplose_dataframe["start_datetime"],
},
)

assert expected_raven_dataframe.equals(raven_dataframe)


@pytest.mark.parametrize(
("files", "destination", "excluded_files"),
[
Expand Down