def _check_completeness_table(completeness, catalogue):
    """
    Generates the completeness table according to different instances
    """
    if isinstance(completeness, np.ndarray) and np.shape(completeness)[1] == 2:
        return completeness
    elif isinstance(completeness, float):
        return np.array([[float(np.min(catalogue.data['year'])),
                          completeness]])
    elif completeness is None:
        return np.array([[float(np.min(catalogue.data['year'])),
                          np.min(catalogue.data['magnitude'])]])
    else:
        raise ValueError('Completeness representation not recognised')
def _check_completeness_table ( completeness , catalogue ) : if isinstance ( completeness , np . ndarray ) and np . shape ( completeness ) [ 1 ] == 2 : return completeness elif isinstance ( completeness , float ) : return np . array ( [ [ float ( np . min ( catalogue . data [ 'year' ] ) ) , completeness ] ] ) elif completeness is None : return np . array ( [ [ float ( np . min ( catalogue . data [ 'year' ] ) ) , np . min ( catalogue . data [ 'magnitude' ] ) ] ] ) else : raise ValueError ( 'Completeness representation not recognised' )
Generates the completeness table according to different instances