nldas_soil_moisture_ml.py 文件源码

def second_layer_input_matrix(X, models):
    '''Build a second layer model input matrix by taking the
    metadata from X given to the first layer models and forming
    a new matrix from the 1-D predictions of the first layer models
    '''
    preds = predict_many(dict(X=X), to_raster=False,
                         ensemble=models)
    example = preds[0].flat
    input_matrix = np.empty((example.shape[0], len(preds)))
    for j, pred in enumerate(preds):
        input_matrix[:, j] = pred.flat.values[:, 0]
    attrs = X.attrs.copy()
    attrs['old_dims'] = [X[SOIL_MOISTURE].dims] * len(preds)
    attrs['canvas'] = X[SOIL_MOISTURE].canvas
    tags = [tag for tag, _ in models]
    arr = xr.DataArray(input_matrix,
                       coords=[('space', example.space),
                               ('band', tags)],
                       dims=('space', 'band'),
                       attrs=attrs)
    return xr.Dataset(dict(flat=arr), attrs=attrs)