traffic_bay

Bases: time_series_dataloader

A data loader for San Francisco Bay Area traffic time series datasets.

This class handles loading, partitioning, and preparing San Francisco Bay Area traffic time series data for training and testing.

Attributes:

Name	Type	Description
name	str	Name of the dataset, default is 'traffic_bay'.
x_len	int	Length of the input time series.
y_len	int	Length of the output time series.
xy_gap	int	Gap between the input and output time series.
coverage_year_range	int	Range of years covered by the data.
time_granularity	str	Time granularity of the data, e.g., 'minutely', 'hourly', etc.
target_attributes	str	Target attribute to predict, default is 'All'.

Methods:

Name	Description
__init__	Initializes the traffic data loader for the Bay Area with dataset-specific configurations.

Source code in tinybig/data/time_series_dataloader.py

class traffic_bay(time_series_dataloader):
    """
    A data loader for San Francisco Bay Area traffic time series datasets.

    This class handles loading, partitioning, and preparing San Francisco Bay Area traffic time series data for training and testing.

    Attributes
    ----------
    name : str
        Name of the dataset, default is 'traffic_bay'.
    x_len : int
        Length of the input time series.
    y_len : int
        Length of the output time series.
    xy_gap : int
        Gap between the input and output time series.
    coverage_year_range : int
        Range of years covered by the data.
    time_granularity : str
        Time granularity of the data, e.g., 'minutely', 'hourly', etc.
    target_attributes : str
        Target attribute to predict, default is 'All'.

    Methods
    -------
    __init__(...)
        Initializes the traffic data loader for the Bay Area with dataset-specific configurations.
    """
    def __init__(
        self,
        name: str = TRAFFIC_BAY_DATA_PROFILE['name'],
        x_len: int = 10,
        y_len: int = 1,
        xy_gap: int = 1,
        coverage_year_range: int = 1,
        time_granularity: str = 'minutely',
        target_attributes: str = 'All',
        *args, **kwargs
    ):
        """
        Initializes the Bay Area traffic data loader with specific configurations.

        Parameters
        ----------
        name : str, optional
            Name of the dataset, default is 'traffic_bay'.
        x_len : int, optional
            Length of the input time series, default is 10.
        y_len : int, optional
            Length of the output time series, default is 1.
        xy_gap : int, optional
            Gap between the input and output time series, default is 1.
        coverage_year_range : int, optional
            Range of years covered by the data, default is 1.
        time_granularity : str, optional
            Time granularity of the data, default is 'minutely'.
        target_attributes : str, optional
            Target attribute to predict, default is 'All'.
        *args, **kwargs
            Additional arguments for the parent class initialization.

        Returns
        -------
        None
        """
        super().__init__(
            name=name,
            data_profile=TRAFFIC_BAY_DATA_PROFILE,
            x_len=x_len, y_len=y_len, xy_gap=xy_gap,
            coverage_year_range=coverage_year_range,
            time_granularity=time_granularity,
            target_attributes=target_attributes,
            *args, **kwargs
        )

__init__(name=TRAFFIC_BAY_DATA_PROFILE['name'], x_len=10, y_len=1, xy_gap=1, coverage_year_range=1, time_granularity='minutely', target_attributes='All', *args, **kwargs)

Initializes the Bay Area traffic data loader with specific configurations.

Parameters:

Name	Type	Description	Default
name	str	Name of the dataset, default is 'traffic_bay'.	TRAFFIC_BAY_DATA_PROFILE['name']
x_len	int	Length of the input time series, default is 10.	10
y_len	int	Length of the output time series, default is 1.	1
xy_gap	int	Gap between the input and output time series, default is 1.	1
coverage_year_range	int	Range of years covered by the data, default is 1.	1
time_granularity	str	Time granularity of the data, default is 'minutely'.	'minutely'
target_attributes	str	Target attribute to predict, default is 'All'.	'All'
*args		Additional arguments for the parent class initialization.	()
**kwargs		Additional arguments for the parent class initialization.	()

Returns:

Type	Description
None

Source code in tinybig/data/time_series_dataloader.py

def __init__(
    self,
    name: str = TRAFFIC_BAY_DATA_PROFILE['name'],
    x_len: int = 10,
    y_len: int = 1,
    xy_gap: int = 1,
    coverage_year_range: int = 1,
    time_granularity: str = 'minutely',
    target_attributes: str = 'All',
    *args, **kwargs
):
    """
    Initializes the Bay Area traffic data loader with specific configurations.

    Parameters
    ----------
    name : str, optional
        Name of the dataset, default is 'traffic_bay'.
    x_len : int, optional
        Length of the input time series, default is 10.
    y_len : int, optional
        Length of the output time series, default is 1.
    xy_gap : int, optional
        Gap between the input and output time series, default is 1.
    coverage_year_range : int, optional
        Range of years covered by the data, default is 1.
    time_granularity : str, optional
        Time granularity of the data, default is 'minutely'.
    target_attributes : str, optional
        Target attribute to predict, default is 'All'.
    *args, **kwargs
        Additional arguments for the parent class initialization.

    Returns
    -------
    None
    """
    super().__init__(
        name=name,
        data_profile=TRAFFIC_BAY_DATA_PROFILE,
        x_len=x_len, y_len=y_len, xy_gap=xy_gap,
        coverage_year_range=coverage_year_range,
        time_granularity=time_granularity,
        target_attributes=target_attributes,
        *args, **kwargs
    )