How to use the pysat.utils.load_netcdf4 function in pysat

Note
    ----
    Any additional keyword arguments passed to pysat.Instrument
    upon instantiation are passed along to this routine and through
    to the load_netcdf4 call.

    Examples
    --------
    ::
        inst = pysat.Instrument('sport', 'ivm')
        inst.load(2019,1)

    """

    return pysat.utils.load_netcdf4(fnames, **kwargs)

DataFrame while metadata is a pysat.Meta instance.

    Note
    ----
    Any additional keyword arguments passed to pysat.Instrument
    upon instantiation are passed along to this routine.

    Examples
    --------
    ::
        inst = pysat.Instrument('icon', 'fuv')
        inst.load(2019,1)

    """

    return pysat.utils.load_netcdf4(fnames, epoch_name='EPOCH',
                                    units_label='Units',
                                    name_label='Long_Name',
                                    notes_label='Var_Notes',
                                    desc_label='CatDesc',
                                    plot_label='FieldNam',
                                    axis_label='LablAxis',
                                    scale_label='ScaleTyp',
                                    min_label='ValidMin',
                                    max_label='ValidMax',
                                    fill_label='FillVal')

DataFrame while metadata is a pysat.Meta instance.

    Note
    ----
    Any additional keyword arguments passed to pysat.Instrument
    upon instantiation are passed along to this routine.

    Examples
    --------
    ::
        inst = pysat.Instrument('icon', 'ivm', sat_id='a', tag='level_2')
        inst.load(2019,1)

    """

    return pysat.utils.load_netcdf4(fnames, epoch_name='Epoch',
                                    units_label='Units',
                                    name_label='Long_Name',
                                    notes_label='Var_Notes',
                                    desc_label='CatDesc',
                                    plot_label='FieldNam',
                                    axis_label='LablAxis',
                                    scale_label='ScaleTyp',
                                    min_label='ValidMin',
                                    max_label='ValidMax',
                                    fill_label='FillVal')

DataFrame while metadata is a pysat.Meta instance.

    Note
    ----
    Any additional keyword arguments passed to pysat.Instrument
    upon instantiation are passed along to this routine.

    Examples
    --------
    ::
        inst = pysat.Instrument('icon', 'fuv')
        inst.load(2019,1)

    """

    return pysat.utils.load_netcdf4(fnames, epoch_name='EPOCH',
                                    units_label='Units',
                                    name_label='Long_Name',
                                    notes_label='Var_Notes',
                                    desc_label='CatDesc',
                                    plot_label='FieldNam',
                                    axis_label='LablAxis',
                                    scale_label='ScaleTyp',
                                    min_label='ValidMin',
                                    max_label='ValidMax',
                                    fill_label='FillVal')

DataFrame while metadata is a pysat.Meta instance.

    Note
    ----
    Any additional keyword arguments passed to pysat.Instrument
    upon instantiation are passed along to this routine.

    Examples
    --------
    ::
        inst = pysat.Instrument('icon', 'ivm', sat_id='a', tag='level_2')
        inst.load(2019,1)

    """

    return pysat.utils.load_netcdf4(fnames, epoch_name='Epoch',
                                    units_label='Units',
                                    name_label='Long_Name',
                                    notes_label='Var_Notes',
                                    desc_label='CatDesc',
                                    plot_label='FieldNam',
                                    axis_label='LablAxis',
                                    scale_label='ScaleTyp',
                                    min_label='ValidMin',
                                    max_label='ValidMax',
                                    fill_label='FillVal')

--------
    ::
        inst = pysat.Instrument('ucar', 'tiegcm')
        inst.load(2019,1)

    """

    # netCDF4 files, particularly those produced
    # by pysat can be loaded using a pysat provided
    # function
    # Metadata in our notional example file is
    # labeled by strings determined by a standard
    # we can adapt pysat to the standard by specifying
    # the string labels used in the file
    # function below returns both data and metadata
    return pysat.utils.load_netcdf4(fnames, epoch_name='Epoch',
                                    units_label='Units',
                                    name_label='Long_Name',
                                    notes_label='Var_Notes',
                                    desc_label='CatDesc',
                                    plot_label='FieldNam',
                                    axis_label='LablAxis',
                                    scale_label='ScaleTyp',
                                    min_label='ValidMin',
                                    max_label='ValidMax',
                                    fill_label='FillVal')

    # This code below demonstrates the use of xarray
    # functions to load TIEGCM data
    # Metadata is transferred from xarray to the Instrument object
    # Data is transferred as well
    # data not indexed by time are transferred to the Instrument object as an

# create quick Instrument object for a new, random netCDF4 file
        # define filename template string to identify files
        # this is normally done by instrument code, but in this case
        # there is no built in pysat instrument support
        # presumes files are named default_2019-01-01.NC
        format_str = 'default_{year:04d}-{month:02d}-{day:02d}.NC'
        inst = pysat.Instrument('netcdf', 'pandas',
                                custom_kwarg='test'
                                data_path='./',
                                format_str=format_str)
        inst.load(2019,1)

    """

    return pysat.utils.load_netcdf4(fnames, **kwargs)