def loadDataframe(mean_file): mean_ps = PerformanceStatistics(mean_file) mean_df = mean_ps.getDataFrame() mean_df['walk_cycles'] = mean_ps.getWalkDuration() mean_df['cpu-cycles'] = mean_ps.getRuntime() mean_df['stlb_hits'] = mean_ps.getStlbHits() df = mean_df[['layout', 'walk_cycles', 'stlb_hits', 'cpu-cycles']] return df
def loadDataframe(mean_file, output): mean_ps = PerformanceStatistics(mean_file) mean_df = mean_ps.getDataFrame() mean_df['cpu-cycles'] = mean_ps.getRuntime() mean_df['walk_cycles'] = mean_ps.getWalkDuration() mean_df['stlb_hits'] = mean_ps.getStlbHits() mean_df['stlb_misses'] = mean_ps.getStlbMisses() df = mean_df[['layout', 'walk_cycles', 'stlb_hits', 'stlb_misses', 'cpu-cycles']] # drop duplicated rows important_columns = list(df.columns) important_columns.remove('layout') #df.drop_duplicates(inplace=True, subset=important_columns) df = df.drop_duplicates(subset=important_columns) df.to_csv(output) return df