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get_filtered_data

Functions:

Name Description
get_filtered_data

Get filtered data from the dataset based on the specified variable name and filter type.

Functions#

get_filtered_data #

get_filtered_data(
    dataset: Dataset,
    var_name: str,
    filter_out: Literal["Bad", "Indeterminate"],
) -> tuple[np.ndarray, np.ndarray]

Get filtered data from the dataset based on the specified variable name and filter type. Args: dataset (xr.Dataset): The dataset containing the data. var_name (str): The name of the variable to filter. filter_out (Literal["Bad", "Indeterminate"]): The type of filter to apply. Returns: tuple[np.ndarray, np.ndarray]: A tuple containing the filtered data as a NumPy array and a mask indicating the filtered values.

Source code in tsdat/transform_v2/utils/get_filtered_data.py 
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def get_filtered_data(
    dataset: xr.Dataset, var_name: str, filter_out: Literal["Bad", "Indeterminate"]
) -> tuple[np.ndarray, np.ndarray]:
    """
    Get filtered data from the dataset based on the specified variable name and filter type.
    Args:
        dataset (xr.Dataset): The dataset containing the data.
        var_name (str): The name of the variable to filter.
        filter_out (Literal["Bad", "Indeterminate"]): The type of filter to apply.
    Returns:
        tuple[np.ndarray, np.ndarray]: A tuple containing the filtered data as a NumPy
        array and a mask indicating the filtered values.
    """
    data = QCFilter(dataset).get_masked_data(
        var_name, rm_assessments=[filter_out], return_nan_array=False
    )  # type: ignore
    return np.ma.filled(data, np.nan), data.mask