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def segments_generator(self, segment_list: _Segment) -> None:
        """
        Generates original and augmented segments from a track.
        """
        if self.config.get('get_shifts'):
            segment_list = create_new_segments_from_splits(segment_list, nsplits=self.config['shift_segment'])
        else:
            segment_list = create_new_segments_from_splits(segment_list, nsplits=32)

        if self.config.get('get_vertical_flip'):

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def split_Nd_array(array: np.ndarray, nsplits: int) -> List[np.ndarray]:
    if array.ndim == 1:
        indices = range(0, len(array) - 31, nsplits)
        segments = [np.take(array, np.arange(i, i + 32), axis=0).copy() for i in indices]
    else:
        indices = range(0, array.shape[1] - 31, nsplits)
        segments = [np.take(array, np.arange(i, i + 32), axis=1).copy() for i in indices]
    return segments

def create_new_segments_from_splits(segment: _Segment, nsplits: int) -> List[_Segment]:

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def create_track_objects(self):
	df = self.data_df
	df = self.split_train_val_as_pd(data=df, ratio=self.config.get('valratio', 6))
	df.sort_values(by=['track_id', 'segment_id'], inplace=True)
	df.replace({'animal': 0, 'human': 1}, inplace=True)
	df['target_type'] = df['target_type'].astype(int)
	# validating that each track consists of segments with same values in following columns
	columns_to_check = ['geolocation_type', 'geolocation_id', 'sensor_id', 'snr_type', 'date_index', 'target_type']
	# creating boolean matrix for np.select
	conditions = [(df.groupby('track_id')[col].shift(0) == df.groupby('track_id')[col].shift(1).bfill())

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class _Segment(Dict, ABC):
    segment_id: Union[int, str]
    output_array: np.ndarray
    doppler_burst: np.ndarray
    target_type: np.ndarray
    segment_count: int

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pip install --upgrade pip
pip install upgrade jupyterlab
pip install autopep8
pip install --upgrade jupyterlab-git

venv_root_dir=${PWD##*/}
python -m ipykernel install --user --name=$venv_root_dir

pip install ipywidgets
jupyter nbextension enable --py widgetsnbextension --sys-prefix

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def hello_user(name):
    return f'Welcome {name} and thank you for using our calculator!'
def addition(a,b):
    return a+b
def subtraction(a,b):
    return a-b
def division(a,b):
    return a/b
def multiplication(a,b):
    return a*b