DataAplose simplification

[mathieudpnt]

I simplified the process, now user only has to declare a dict of arguments and use DataAplose from_dict method. The rest of the process should remain the same.

Example:

from post_processing.dataclass.data_aplose import DataAplose

config = [
    {
        "detection_file": ...,
        "filename_format": ...,
    },
    {
        "detection_file": ...,
        "filename_format": ...,
    },
]

data = DataAplose.from_dict(config)

config can be either a dict or a list of dict.

A dict must contains the following arguments:

• detection_file: Path -> path to an APLOSE-formatted result csv file
• filename_format: str -> string to parse datetimes from filename column from the detection file

Others non-mandatory arguments can be given:

• timebin_new: Timedelta | None = None
• start_datetime: Timestamp | None = None
• end_datetime: Timestamp | None = None
• annotator: str | list[str] | None = None
• annotation: str | list[str] | None = None
• type: str | None = None
• recording_file: Path | None = None
• user_selection: str = "all"
• min_frequency: float | None = None
• max_frequency: float | None = None
• confidence: float | None = None

[mathieudpnt]

I also updated the utils script names, got rid of "_utils"

example:
glider_utils -> glider

from post_processing.utils import glider

[mathieudpnt]

I also (finally) renamed the package to disclose 🪩

[mathieudpnt]

and finally i update RecordingPeriod class, now to display the effort, user has to provide in the configuration dict recording_file which corresponds to the Path of a recording_period CSV file:

config ={
        "detection_file": Path(...),
        "filename_format": "...",
        "recording_file": Path(...),
}

data= DataAplose.from_dict(config)

fig, ax = plt.subplots(1, 1)
ax = data.set_ax(...)
data.plot(
    ...
    effort=True,
)
plt.tight_layout()
plt.show()