The merger module¶
Utilities to process the data from a single .cubex file, or merge the
information that comes from multiple .cubex files.
Single/Multi .cubex files processing¶
-
merger.process_cubex(profile_file, exclusive=True)¶ Processes a single
.cubexfile, returning the numeric data from the profiling, plus information about the call tree and the metrics.Note: returns a dict.
- Parameters
profile_file (str) – The name of the
.cubexfile.exclusive (bool) – Whether to ask
cube_dumpfor exclusive (True) or inclusive (False) metrics.
- Returns
ctree (calltree.CubeTreeNode) – A call tree recursive object
ctree_df (pandas.DataFrame) – A DataFrame representation of the call tree object
df (pandas.DataFrame) – A dataframe containing the profiling data, from
conv_info (list) – convertibility information (to inclusive) for the metrics contained in the dump.
-
merger.process_multi(profile_files, exclusive=True)¶ Processes
.cubexfiles coming from different profiling runs, e.g. from ascalasca -analyzerun, aggregating the results.Assumes that there is a set of metrics which are common to all files, and that no pair of files share metrics that are not shared by all the others.
Note: returns a dict.
- Parameters
profile_file (list) – List of
.cubexfilenames;exclusive (bool) – Whether to ask
cube_dumpfor exclusive (True) or inclusive (False) metrics.
- Returns
ctree (calltree.CubeTreeNode) – A call tree recursive structure;
ctree_df (pandas.DataFrame) – DataFrame representation of the call tree;
common (pandas.DataFrame) – A data frame containing all the data relative to metrics that are shared among all the
.cubexfiles (“common” metrics);noncommon (pandas.DataFrame) – A data frame containing all the data relatige that are specific to single
.cubexfiles (“non-common” metrics);conv_info (list) – A list of metrics that can be converted to inclusive.
ncmetric (padas.DataFrame) – A dataframe expressing, for each metric coming from only a single
.cubexfile (the “non-common” metrics) the ID of the run it came from.