data.py 文件源码

python
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项目:psyplot 作者: Chilipp 项目源码 文件源码
def open_mfdataset(paths, decode_cf=True, decode_times=True,
                   decode_coords=True, engine=None, gridfile=None,
                   t_format=None, **kwargs):
    """
    Open multiple files as a single dataset.

    This function is essentially the same as the :func:`xarray.open_mfdataset`
    function but (as the :func:`open_dataset`) supports additional decoding
    and the ``'gdal'`` engine.
    You can further specify the `t_format` parameter to get the time
    information from the files and use the results to concatenate the files

    Parameters
    ----------
    %(xarray.open_mfdataset.parameters.no_engine)s
    %(open_dataset.parameters.engine)s
    %(get_tdata.parameters.t_format)s
    %(CFDecoder.decode_coords.parameters.gridfile)s

    Returns
    -------
    xarray.Dataset
        The dataset that contains the variables from `filename_or_obj`"""
    if t_format is not None or engine == 'gdal':
        if isinstance(paths, six.string_types):
            paths = sorted(glob(paths))
        if not paths:
            raise IOError('no files to open')
    if t_format is not None:
        time, paths = get_tdata(t_format, paths)
        kwargs['concat_dim'] = time
    if engine == 'gdal':
        from psyplot.gdal_store import GdalStore
        paths = list(map(GdalStore, paths))
        engine = None
        kwargs['lock'] = False

    ds = xr.open_mfdataset(
        paths, decode_cf=decode_cf, decode_times=decode_times, engine=engine,
        decode_coords=False, **kwargs)
    if decode_cf:
        return CFDecoder.decode_ds(ds, gridfile=gridfile, inplace=True,
                                   decode_coords=decode_coords,
                                   decode_times=decode_times)
    return ds
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