def get_scan_parameter(meta_data_array, unique=True):
try:<EOL><INDENT>last_not_parameter_column = meta_data_array.dtype.names.index('<STR_LIT>')  <EOL><DEDENT>except ValueError:<EOL><INDENT>last_not_parameter_column = meta_data_array.dtype.names.index('<STR_LIT:error>')  <EOL><DEDENT>if last_not_parameter_column == len(meta_data_array.dtype.names) - <NUM_LIT:1>:  <EOL><INDENT>return<EOL><DEDENT>scan_parameters = collections.OrderedDict()<EOL>for scan_par_name in meta_data_array.dtype.names[<NUM_LIT:4>:]:  <EOL><INDENT>scan_parameters[scan_par_name] = np.unique(meta_data_array[scan_par_name]) if unique else meta_data_array[scan_par_name]<EOL><DEDENT>return scan_parameters<EOL>
Takes the numpy meta data array and returns the different scan parameter settings and the name aligned in a dictionary

    Parameters
    ----------
    meta_data_array : numpy.ndarray
    unique: boolean
        If true only unique values for each scan parameter are returned

    Returns
    -------
    python.dict{string, numpy.Histogram}:
        A dictionary with the scan parameter name/values pairs