reshape.py 文件源码

def concat_ml_features(*dsets, **kwargs):
    '''Concatenate MLDataset / Dataset (dsets) along concat_dim
    (by default the column dimension, typically called "layer")

    Parameters:
        :dsets: Any number of MLDataset / Dataset objects that are
                2D
        :features_layer: Typically "layer", the column dimension
        :concat_dim: If None, the column dimension is guessed
        :keep_attrs: If True, keep the attrs of the first dset in *dsets
    TODO - Gui: This could use the astype logic discussed elsewhere?

    '''
    features_layer = kwargs.get('features_layer', FEATURES_LAYER)
    concat_dim = kwargs.get('concat_dim', None)
    keep_attrs = kwargs.get('keep_attrs', False) # TODO True or False (convention?)

    from xarray_filters.mldataset import MLDataset
    if not dsets:
        raise ValueError('No MLDataset / Dataset arguments passed.  Expected >= 1')
    if keep_attrs:
        attrs = deepcopy(dsets[0].attrs)
    else:
        attrs = OrderedDict()
    concat_dim = concat_dim or FEATURES_LAYER_DIMS[1]
    data_arrs = []
    for dset in dsets:
        if not isinstance(dset, (MLDataset, xr.Dataset)):
            raise ValueError('TODO -error message here')
        data_arr = dset.data_vars.get(features_layer, None)
        if data_arr is None:
            raise ValueError('TODO -error message here')
        data_arrs.append(data_arr)
    data_arr = xr.concat(data_arrs, dim=concat_dim)
    return MLDataset(OrderedDict([(features_layer, data_arr)]), attrs=attrs)