def combine_meta_data(files_dict, meta_data_v2=True):
if len(files_dict) > <NUM_LIT:10>:<EOL><INDENT>logging.info("<STR_LIT>", len(files_dict))<EOL><DEDENT>total_length = <NUM_LIT:0>  <EOL>for file_name in files_dict.keys():<EOL><INDENT>with tb.open_file(file_name, mode="<STR_LIT:r>") as in_file_h5:  <EOL><INDENT>total_length += in_file_h5.root.meta_data.shape[<NUM_LIT:0>]<EOL><DEDENT><DEDENT>if meta_data_v2:<EOL><INDENT>meta_data_combined = np.empty((total_length, ), dtype=[<EOL>('<STR_LIT>', np.uint32),<EOL>('<STR_LIT>', np.uint32),<EOL>('<STR_LIT>', np.uint32),<EOL>('<STR_LIT>', np.float64),<EOL>('<STR_LIT>', np.float64),<EOL>('<STR_LIT:error>', np.uint32)])<EOL><DEDENT>else:<EOL><INDENT>meta_data_combined = np.empty((total_length, ), dtype=[<EOL>('<STR_LIT>', np.uint32),<EOL>('<STR_LIT>', np.uint32),<EOL>('<STR_LIT>', np.uint32),<EOL>('<STR_LIT>', np.float64),<EOL>('<STR_LIT:error>', np.uint32)])<EOL><DEDENT>if len(files_dict) > <NUM_LIT:10>:<EOL><INDENT>progress_bar = progressbar.ProgressBar(widgets=['<STR_LIT>', progressbar.Percentage(), '<STR_LIT:U+0020>', progressbar.Bar(marker='<STR_LIT:*>', left='<STR_LIT:|>', right='<STR_LIT:|>'), '<STR_LIT:U+0020>', progressbar.AdaptiveETA()], maxval=total_length, term_width=<NUM_LIT>)<EOL>progress_bar.start()<EOL><DEDENT>index = <NUM_LIT:0><EOL>for file_name in files_dict.keys():<EOL><INDENT>with tb.open_file(file_name, mode="<STR_LIT:r>") as in_file_h5:  <EOL><INDENT>array_length = in_file_h5.root.meta_data.shape[<NUM_LIT:0>]<EOL>meta_data_combined[index:index + array_length] = in_file_h5.root.meta_data[:]<EOL>index += array_length<EOL>if len(files_dict) > <NUM_LIT:10>:<EOL><INDENT>progress_bar.update(index)<EOL><DEDENT><DEDENT><DEDENT>if len(files_dict) > <NUM_LIT:10>:<EOL><INDENT>progress_bar.finish()<EOL><DEDENT>return meta_data_combined<EOL>
Takes the dict of hdf5 files and combines their meta data tables into one new numpy record array.

Parameters
----------
meta_data_v2 : bool
    True for new (v2) meta data format, False for the old (v1) format.