###########################################################################
# Copyright (C) 2025 ETH Zurich
# CosinorAge: Prediction of biological age based on accelerometer data
# using the CosinorAge method proposed by Shim, Fleisch and Barata
# (https://www.nature.com/articles/s41746-024-01111-x)
#
# Authors: Jacob Leo Oskar Hunecke
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#         http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
##########################################################################

"""
This module provides the functionality to compute a wide range
wearable-features based on minute-level ENMO data including
- Circadian rhythm features, e.g., IV, IS, RA, M10, L5
- Physical activity features, e.g., SB, LIPA, MVPA
- Sleep features, e.g., TST, WASO, SE, SR
"""

from .features import WearableFeatures
from .bulk_features import BulkWearableFeatures
from .utils.visualization import plot_sleep_predictions, plot_non_wear, plot_cosinor
from .utils.dashboard import dashboard

__all__ = [
    "WearableFeatures",
    "BulkWearableFeatures",
    "plot_sleep_predictions",
    "plot_non_wear",
    "plot_cosinor",
    "dashboard"
]

