seabird

Seabird Scientific data parsers.

This page provides functions for parsing data files in Seabird Scientific format. The Seabird Scientific format is commonly used for oceanographic data collection and is supported by Seabird Scientific.

`btl(file_path, encoding='UTF-8', xml_parsing_error_level='ERROR', save_orginal_header=False)` ¶

Parse Seabird BTL format.

Parameters:

Name	Type	Description	Default
`file_path`	`str`	file path	required
`encoding`	`str`	Encoding to use. Defaults to "UTF-8".	`'UTF-8'`
`xml_parsing_error_level`	`str`	Error level for XML parsing. Defaults to "ERROR".	`'ERROR'`
`save_orginal_header`	`bool`	Save original header. Defaults to False.	`False`

Returns:

Type	Description
`Dataset`	xarray.Dataset: Dataset

Source code in ocean_data_parser/parsers/seabird.py

def btl(
    file_path: str,
    encoding: str = "UTF-8",
    xml_parsing_error_level="ERROR",
    save_orginal_header: bool = False,
) -> xarray.Dataset:
    """Parse Seabird BTL format.

    Args:
        file_path (str): file path
        encoding (str, optional): Encoding to use. Defaults to "UTF-8".
        xml_parsing_error_level (str, optional): Error level for XML parsing. Defaults to "ERROR".
        save_orginal_header (bool, optional): Save original header. Defaults to False.

    Returns:
        xarray.Dataset: Dataset
    """
    with open(file_path, encoding=encoding) as f:
        header = _parse_seabird_file_header(
            f, xml_parsing_error_level=xml_parsing_error_level
        )

        # Retrieve variables from bottle header and lower the first letter of each variable
        variable_list = [
            var[0].lower() + var[1:] for var in header["bottle_columns"]
        ] + ["stats"]
        df = pd.read_fwf(
            f,
            widths=[10, 12] + [11] * (len(header["bottle_columns"]) - 1),
            names=variable_list,
            dtype={var: var_dtypes.get(var, float) for var in variable_list},
        )

    # Split statistical data info separate dateframes
    df["bottle"] = df["bottle"].ffill().astype(int)
    df["stats"] = df["stats"].str.extract(r"\((.*)\)")
    df = df.set_index("bottle")
    df_grouped = df.query("stats=='avg'")
    for stats in df.query("stats!='avg'")["stats"].drop_duplicates().to_list():
        df_grouped = df_grouped.join(df.query("stats==@stats").add_suffix(f"_{stats}"))
    df = df_grouped

    # Generate time variable
    df["time"] = pd.to_datetime(df.filter(like="date").apply(" ".join, axis="columns"))

    # Ignore extra variables
    drop_columns = [col for col in df if re.search("^date|^stats|^bottle_", col)]
    df = df.drop(columns=drop_columns)

    # Improve metadata

    n_scan_per_bottle = [
        int(step["scans_per_bottle"])
        for step in header["processing"]
        if step["module"] == "datcnv"
    ]
    if not n_scan_per_bottle:
        logger.warning("Failed to retrieve the number of scans per bottle")
        n_scan_per_bottle = "unknown"
    else:
        n_scan_per_bottle = n_scan_per_bottle[0]
    header = _generate_seabird_cf_history(header)

    # Retrieve vocabulary associated with each variables
    header["variables"] = {var: header["variables"].get(var, {}) for var in df.columns}
    header["variables"] = _add_seabird_vocabulary(header["variables"])

    # Convert to xarray
    ds = _convert_sbe_dataframe_to_dataset(df, header)

    # Add cell_method attribute
    for var in ds:
        if var.endswith("_sdev") and var[:-5] in ds:
            ds[var].attrs["cell_method"] = (
                f"scan: standard_deviation (previous {n_scan_per_bottle} scans)"
            )
            # TODO confirm that seabird uses the previous records from this timestamp
        elif var not in ["time", "bottle"]:
            ds[var].attrs["cell_method"] = (
                f"scan: mean (previous {n_scan_per_bottle} scans)"
            )

    if not save_orginal_header:
        ds.attrs.pop("seabird_header")
    return standardize_dataset(ds)

`cnv(file_path, encoding='UTF-8', encoding_errors='strict', xml_parsing_error_level='ERROR', generate_instrument_variables=False, save_orginal_header=False)` ¶

Parse Seabird CNV format.